Advanced Modeled Iterative Reconstruction (ADMIRE) Facilitates Radiation Dose Reduction in Abdominal CT - Ellmann, Stephan; Kammerer, Ferdinand; Allmendinger, Thomas; Hammon, Matthias; Janka, Rolf Matthias; Lell, Michael; Uder, Michael; Kramer, Manuel (Academic Radiology, 2018)
RATIONALE AND OBJECTIVES: This study aimed to determine the potential degree of radiation dose reduction achievable using Advanced Modeled Iterative Reconstruction (ADMIRE) in abdominal computed tomography (CT) while maintaining image quality. Moreover, this study compared differences in image noise reduction of this iterative algorithm with radiation dose reduction. METHODS: Eleven consecutive patients scheduled for abdominal CT were scanned according to our institute's standard protocol (100 kV, 289 reference mAs). Using a proprietary reconstruction software, CT images of these patients were reconstructed as either full-dose weighted filtered back projections or with simulated radiation dose reductions down to 10% of the full-dose level and ADMIRE at either strength 3 or strength 5. Images were marked with arrows pointing on anatomic structures of the abdomen, differing in their contrast to the surrounding tissue. Structures were grouped into high-, medium-, and low-contrast subgroups. In addition, the intrinsic noise of these structures was measured. That followed, image pairs were presented to observers, with five readers assessing image quality using two-alternative-forced-choice comparisons. In total, 3000 comparisons were performed that way. RESULTS: Both ADMIRE 3 and 5 decreased noise of the anatomic structures significantly compared to the filtered back projection, with an additional significant difference between ADMIRE 3 and 5. Radiation dose reduction potential for ADMIRE ranged from 29.0% to 53.5%, with no significant differences between ADMIRE 3 and 5 within the contrast subgroups.The potential levels of radiation dose reduction for ADMIRE 3 differed significantly between high-, medium-, and low-contrast structures, whereas for ADMIRE 5, there was only a significant difference between the high- and the medium-contrast subgroups. CONCLUSION: Although ADMIRE 5 permits significantly higher noise reduction potential than ADMIRE 3, it does not facilitate higher levels of radiation dose reduction. ADMIRE nonetheless holds remarkable potential for radiation dose reduction, which features a certain dependency on the contrast of the structure of interest. Applying ADMIRE with a strength of 3 in abdominal CT may permit radiation dose reduction of about 30%.
EVALuna2:34687

An AI classifier derived from 4D radiomics of dynamic contrast-enhanced breast MRI data: potential to avoid unnecessary breast biopsies - Poetsch, Nina; Dietzel, Matthias; Kapetas, Panagiotis; Clauser, Paola; Pinker, Katja; Ellmann, Stephan; Uder, Michael; Helbich, Thomas; Baltzer, Pascal A. T. (European Radiology, 2021)
Objectives Due to its high sensitivity, DCE MRI of the breast (bMRI) is increasingly used for both screening and assessment purposes. The high number of detected lesions poses a significant logistic challenge in clinical practice. The aim was to evaluate a temporally and spatially resolved (4D) radiomics approach to distinguish benign from malignant enhancing breast lesions and thereby avoid unnecessary biopsies. Methods This retrospective study included consecutive patients with MRI-suspicious findings (BI-RADS 4/5). Two blinded readers analyzed DCE images using a commercially available software, automatically extracting BI-RADS curve types and pharmacokinetic enhancement features. After principal component analysis (PCA), a neural network-derived A.I. classifier to discriminate benign from malignant lesions was constructed and tested using a random split simple approach. The rate of avoidable biopsies was evaluated at exploratory cutoffs (C-1, 100%, and C-2, >= 95% sensitivity). Results Four hundred seventy (295 malignant) lesions in 329 female patients (mean age 55.1 years, range 18-85 years) were examined. Eighty-six DCE features were extracted based on automated volumetric lesion analysis. Five independent component features were extracted using PCA. The A.I. classifier achieved a significant (p < .001) accuracy to distinguish benign from malignant lesion within the test sample (AUC: 83.5%; 95% CI: 76.8-89.0%). Applying identified cutoffs on testing data not included in training dataset showed the potential to lower the number of unnecessary biopsies of benign lesions by 14.5% (C-1) and 36.2% (C-2). Conclusion The investigated automated 4D radiomics approach resulted in an accurate A.I. classifier able to distinguish between benign and malignant lesions. Its application could have avoided unnecessary biopsies.
CRIS-Team WoS Importer:2021-04-02

A Novel Pairwise Comparison-Based Method to Determine Radiation Dose Reduction Potentials of Iterative Reconstruction Algorithms, Exemplified Through Circle of Willis Computed Tomography Angiography - Ellmann, Stephan; Kammerer, Ferdinand; Brand, Michael; Allmendinger, Thomas; May, Matthias; Uder, Michael; Lell, Michael; Kramer, Manuel (Investigative Radiology, 2016)
The aim of this study was to determine the dose reduction potential of iterative reconstruction (IR) algorithms in computed tomography angiography (CTA) of the circle of Willis using a novel method of evaluating the quality of radiation dose-reduced images.This study relied on ReconCT, a proprietary reconstruction software that allows simulating CT scans acquired with reduced radiation dose based on the raw data of true scans. To evaluate the performance of ReconCT in this regard, a phantom study was performed to compare the image noise of true and simulated scans within simulated vessels of a head phantom. That followed, 10 patients scheduled for CTA of the circle of Willis were scanned according to our institute's standard protocol (100 kV, 145 reference mAs). Subsequently, CTA images of these patients were reconstructed as either a full-dose weighted filtered back projection or with radiation dose reductions down to 10% of the full-dose level and Sinogram-Affirmed Iterative Reconstruction (SAFIRE) with either strength 3 or 5. Images were marked with arrows pointing on vessels of different sizes, and image pairs were presented to observers. Five readers assessed image quality with 2-alternative forced choice comparisons.In the phantom study, no significant differences were observed between the noise levels of simulated and true scans in filtered back projection, SAFIRE 3, and SAFIRE 5 reconstructions.The dose reduction potential for patient scans showed a strong dependence on IR strength as well as on the size of the vessel of interest. Thus, the potential radiation dose reductions ranged from 84.4% for the evaluation of great vessels reconstructed with SAFIRE 5 to 40.9% for the evaluation of small vessels reconstructed with SAFIRE 3.This study provides a novel image quality evaluation method based on 2-alternative forced choice comparisons. In CTA of the circle of Willis, higher IR strengths and greater vessel sizes allowed higher degrees of radiation dose reduction.
EVALuna2:14492

Application of machine learning algorithms for multiparametric MRI-based evaluation of murine colitis - Ellmann, Stephan; Langer, Victoria; Britzen-Laurent, Nathalie; Hildner, Kai; Huber, Carina; Tripal, Philipp; Seyler, Lisa; Waldner, Maximilian; Uder, Michael; Stürzl, Michael; Bäuerle, Tobias (PLoS ONE, 2018)
Magnetic resonance imaging (MRI) allows non-invasive evaluation of inflammatory bowel disease (IBD) by assessing pathologically altered gut. Besides morphological changes, relaxation times and diffusion capacity of involved bowel segments can be obtained by MRI. The aim of this study was to assess the use of multiparametric MRI in the diagnosis of experimentally induced colitis in mice, and evaluate the diagnostic benefit of parameter combinations using machine learning. This study relied on colitis induction by Dextran Sodium Sulfate (DSS) and investigated the colon of mice in vivo as well as ex vivo. Receiver Operating Characteristics were used to calculate sensitivity, specificity, positive- and negative-predictive values (PPV and NPV) of these single values in detecting DSS-treatment as a reference condition. A Model Averaged Neural Network (avNNet) was trained on the multiparametric combination of the measured values, and its predictive capacity was compared to those of the single parameters using exact binomial tests. Within the in vivo subgroup (n = 19), the avNNet featured a sensitivity of 91.3% (95% CI: 86.6-96.0%), specificity of 92.3% (95% CI: 85.1-99.6%), PPV of 96.9% (94.0-99.9%) and NPV of 80.0% (95% CI: 69.9-90.1%), significantly outperforming all single parameters in at least 2 accuracy measures (p < 0.003) and performing significantly worse compared to none of the single values. Within the ex vivo subgroup (n = 30), the avNNet featured a sensitivity of 87.4% (95% CI: 82.6-92.2%), specificity of 82.9% (95% CI: 76.1-89.7%), PPV of 88.9% (84.3-93.5%) and NPV of 80.8% (95% CI: 73.8-87.9%), significantly outperforming all single parameters in at least 2 accuracy measures (p < 0.015), exceeded by none of the single parameters. In experimental mouse colitis, multiparametric MRI and the combination of several single measured values to an avNNet can significantly increase diagnostic accuracy compared to the single parameters alone. This pilot study will provide new avenues for the development of an MR-derived colitis score for optimized diagnosis and surveillance of inflammatory bowel disease.
EVALuna2:35135

Assessment of a fully-automated diagnostic AI software in prostate MRI: Clinical evaluation and histopathological correlation - Bayerl, Nadine; Adams, Lisa C.; Cavallaro, Alexander Josef; Bäuerle, Tobias; Schlicht, Michael; Wullich, Bernd; Hartmann, Arndt; Uder, Michael; Ellmann, Stephan (European Journal of Radiology, 2024)
Objective: This study aims to evaluate the diagnostic performance of a commercial, fully-automated, artificial intelligence (AI) driven software tool in identifying and grading prostate lesions in prostate MRI, using histopathological findings as the reference standard, while contextualizing its performance within the framework of PI-RADS v2.1 criteria. Material and methods: This retrospective study analyzed 123 patients who underwent multiparametric prostate MRI followed by systematic and targeted biopsies. MRI protocols adhered to international guidelines and included T2-weighted, diffusion-weighted, T1-weighted, and dynamic contrast-enhanced imaging. The AI software tool mdprostate was integrated into the Picture Archiving and Communication System to automatically segment the prostate, calculate prostate volume, and classify lesions according to PI-RADS scores using biparametric T2-weighted and diffusion-weighted imaging. Histopathological analysis of biopsy cores served as the reference standard. Diagnostic performance metrics including sensitivity, specificity, positive and negative predictive value (PPV, NPV), and area under the ROC curve (AUC) were calculated. Results: mdprostate demonstrated 100 % sensitivity at a PI-RADS ≥ 2 cutoff, effectively ruling out both clinically significant and non-significant prostate cancers for lesions remaining below this threshold. For detecting clinically significant prostate cancer (csPCa) using a PI-RADS ≥ 4 cutoff, mdprostate achieved a sensitivity of 85.5 % and a specificity of 63.2 %. The AUC for detecting cancers of any grade was 0.803. The performance metrics of mdprostate were comparable to those reported in two meta-analyses of PI-RADS v2.1, with no significant differences in sensitivity and specificity (p > 0.05). Conclusion: The evaluated AI tool demonstrated high diagnostic performance in identifying and grading prostate lesions, with results comparable to those reported in meta-analyses of expert readers using PI-RADS v2.1. Its ability to standardize evaluations and potentially reduce variability underscores its potential as a valuable adjunct in the prostate cancer diagnostic pathway. The high accuracy of mdprostate, particularly in ruling out prostate cancers, highlights its clinical utility by reducing workload and enhancing patient outcomes.
CRIS-Team Scopus Importer:2024-11-15
Keywords: Artificial intelligence; Clinical evaluation; Diagnostic performance; PI-RADS; Prostate cancer; Prostate MRI

Automated volumetric radiomic analysis of breast cancer vascularization improves survival prediction in primary breast cancer - Dietzel, Matthias; Schulz-Wendtland, Rüdiger; Ellmann, Stephan; Zoubi, Ramy; Wenkel, Evelyn; Hammon, Matthias; Clauser, Paola; Uder, Michael; Runnebaum, Ingo B.; Baltzer, Pascal A.T. (Scientific Reports, 2020)
To investigate whether automated volumetric radiomic analysis of breast cancer vascularization (VAV) can improve survival prediction in primary breast cancer. 314 consecutive patients with primary invasive breast cancer received standard clinical MRI before the initiation of treatment according to international recommendations. Diagnostic work-up, treatment, and follow-up was done at one tertiary care, academic breast-center (outcome: disease specific survival/DSS vs. disease specific death/DSD). The Nottingham Prognostic Index (NPI) was used as the reference method with which to predict survival of breast cancer. Based on the MRI scans, VAV was accomplished by commercially available, FDA-cleared software. DSD served as endpoint. Integration of VAV into the NPI gave NPIVAV. Prediction of DSD by NPIVAV compared to standard NPI alone was investigated (Cox regression, likelihood-test, predictive accuracy: Harrell’s C, Kaplan Meier statistics and corresponding hazard ratios/HR, confidence intervals/CI). DSD occurred in 35 and DSS in 279 patients. Prognostication of the survival outcome by NPI (Harrell’s C = 75.3%) was enhanced by VAV (NPIVAV: Harrell’s C = 81.0%). Most of all, the NPIVAV identified patients with unfavourable outcome more reliably than NPI alone (hazard ratio/HR = 4.5; confidence interval/CI = 2.14-9.58; P = 0.0001). Automated volumetric radiomic analysis of breast cancer vascularization improved survival prediction in primary breast cancer. Most of all, it optimized the identification of patients at higher risk of an unfavorable outcome. Future studies should integrate MRI as a “gate keeper” in the management of breast cancer patients. Such a “gate keeper” could assist in selecting patients benefitting from more advanced diagnostic procedures (genetic profiling etc.) in order to decide whether are a more aggressive therapy (chemotherapy) is warranted.
CRIS-Team Scopus Importer:2020-03-17

Breast MRI in the era of diffusion weighted imaging: do we still need signal-intensity time curves? - Dietzel, Matthias; Ellmann, Stephan; Schulz-Wendtland, Rüdiger; Clauser, Paola; Wenkel, Evelyn; Uder, Michael; Baltzer, Pascal A.T. (European Radiology, 2019)
Objective: Dynamic contrast-enhanced imaging of the initial (IP) and delayed phase (DP) is an integral part of any clinical breast MRI protocol. Furthermore, DWI is increasingly used as an add-on sequence by the breast-imaging community. We investigated whether DWI could be used as a substitute DP. Material and methods: One hundred thirty-two consecutive patients with equivocal or suspicious findings at ultrasound and/or mammography received a full diagnostic breast MRI according to international recommendations. Histopathological verification served as reference standard. We evaluated three sections of the MRI protocol: IP, DP, and apparent diffusion coefficient (ADC) maps derived from DWI. Circular ROIs (regions of interest, mean size 5–10 mm2) were drawn into the enhancing parts of the lesion (first postcontrast). ROIs were transferred to the corresponding location on ADC maps and IP and DP images. Mean ROI values were investigated signal intensity (SI): (1) Initial-phase enhancement = (SI(IP) − SI(precontrast))/SI(precontrast); (2) Delayed-phase enhancement = (SI(DP) − SI(IP))/SI(IP); (3) ADC. Multiparametric combinations were computed using logistic regression analysis: (1) IP+: Initial-phase enhancement and ADC; (2) Curve: Initial-phase enhancement and delayed-phase enhancement; (3) Curve+: Curve and ADC. The diagnostic performances of these feature combinations to diagnose malignancy were compared by the area under the receiver-operating characteristics curve (AUC). Results: One hundred thirty-two patients (age: mean = 57.1 years, range 23–83 years) with 145 lesions were included (malignant/benign 101/44). IP+ (AUC = 0.877) outperformed Curve (AUC = 0.788, p = 0.03). Curve+ was not superior to IP+ (p = 1). Conclusion: DWI could substitute DP. Because DWI is typically used as an add-on to IP and DP, our results might help to abbreviate and to simplify current practice of breast MRI. Key Points: • DWI provides similar but superior diagnostic information for diagnosis of malignancy in enhancing breast lesions compared to DP. • Adding DP to DWI does not provide incremental information to distinguish benign from malignant lesions. • DWI could substitute DP. As DWI is typically used as an add-on to IP and DP, our findings might help to abbreviate and to simplify current breast MRI practice.
CRIS-Team Scopus Importer:2019-08-06
Keywords: Breast neoplasms; Diagnostic techniques and procedures; Differential diagnosis; Diffusion magnetic resonance imaging; Magnetic resonance imaging

Breast MRI in the era of diffusion weighted imaging: do we still need signal-intensity time curves? - Dietzel, Matthias; Ellmann, Stephan; Schulz-Wendtland, Rüdiger; Clauser, Paola; Wenkel, Evelyn; Uder, Michael; Baltzer, Pascal A. T. (European Radiology, 2020)
OBJECTIVE: Dynamic contrast-enhanced imaging of the initial (IP) and delayed phase (DP) is an integral part of any clinical breast MRI protocol. Furthermore, DWI is increasingly used as an add-on sequence by the breast-imaging community. We investigated whether DWI could be used as a substitute DP. MATERIAL AND METHODS: One hundred thirty-two consecutive patients with equivocal or suspicious findings at ultrasound and/or mammography received a full diagnostic breast MRI according to international recommendations. Histopathological verification served as reference standard. We evaluated three sections of the MRI protocol: IP, DP, and apparent diffusion coefficient (ADC) maps derived from DWI. Circular ROIs (regions of interest, mean size 5-10 mm2) were drawn into the enhancing parts of the lesion (first postcontrast). ROIs were transferred to the corresponding location on ADC maps and IP and DP images. Mean ROI values were investigated signal intensity (SI): (1) Initial-phase enhancement = (SI(IP) - SI(precontrast))/SI(precontrast); (2) Delayed-phase enhancement = (SI(DP) - SI(IP))/SI(IP); (3) ADC. Multiparametric combinations were computed using logistic regression analysis: (1) IP+: Initial-phase enhancement and ADC; (2) Curve: Initial-phase enhancement and delayed-phase enhancement; (3) Curve+: Curve and ADC. The diagnostic performances of these feature combinations to diagnose malignancy were compared by the area under the receiver-operating characteristics curve (AUC). RESULTS: One hundred thirty-two patients (age: mean = 57.1 years, range 23-83 years) with 145 lesions were included (malignant/benign 101/44). IP+ (AUC = 0.877) outperformed Curve (AUC = 0.788, p = 0.03). Curve+ was not superior to IP+ (p = 1). CONCLUSION: DWI could substitute DP. Because DWI is typically used as an add-on to IP and DP, our results might help to abbreviate and to simplify current practice of breast MRI. KEY POINTS: • DWI provides similar but superior diagnostic information for diagnosis of malignancy in enhancing breast lesions compared to DP. • Adding DP to DWI does not provide incremental information to distinguish benign from malignant lesions. • DWI could substitute DP. As DWI is typically used as an add-on to IP and DP, our findings might help to abbreviate and to simplify current breast MRI practice.
EVALuna2:210908

Cinematic Rendering in Anatomy: A Crossover Study Comparing a Novel 3D Reconstruction Technique to Conventional Computed Tomography - Binder, Johannes; Scholz, Michael; Ellmann, Stephan; Uder, Michael; Grützmann, Robert; Krautz, Christian; Weber, Georg (Anatomical Sciences Education, 2020)
Integration of medical imaging into preclinical anatomy courses is already underway in many medical schools. However, interpretation of two-dimensional grayscale images is difficult and conventional volume rendering techniques provide only images of limited quality. In this regard, a more photorealistic visualization provided by Cinematic Rendering (CR) may be more suitable for anatomical education. A randomized, two-period crossover study was conducted from July to December 2018, at the University Hospital of Erlangen, Germany to compare CR and conventional computed tomography (CT) imaging for speed and comprehension of anatomy. Sixteen students were randomized into two assessment sequences. During each assessment period, participants had to answer 15 anatomy-related questions that were divided into three categories: parenchymal, musculoskeletal, and vascular anatomy. After a washout period of 14 days, assessments were crossed over to the respective second reconstruction technique. The mean interperiod differences for the time to answer differed significantly between the CR-CT sequence (-204.21 +/- 156.0 seconds) and the CT-CR sequence (243.33 +/- 113.83 seconds;P < 0.001). Overall time reduction by CR was 65.56%. Cinematic Rendering visualization of musculoskeletal and vascular anatomy was higher rated compared to CT visualization (P P = 0.003), whereas CT visualization of parenchymal anatomy received a higher scoring than CR visualization (P < 0.001). No carryover effects were observed. A questionnaire revealed that students consider CR to be beneficial for medical education. These results suggest that CR has a potential to enhance knowledge acquisition and transfer from medical imaging data in medical education.
CRIS-Team WoS Importer:2020-07-17

Classification of Breast Cancer Histology Images Using Transfer Learning - Vesal, Sulaiman; Ravikumar, Nishant; Davari, Amirabbas; Ellmann, Stephan; Maier, Andreas (ICIAR 2018: Image Analysis and Recognition, 2018)

Combination of an ultrafast TWIST-VIBE Dixon sequence protocol and diffusion-weighted imaging into an accurate easily applicable classification tool for masses in breast MRI - Peter, Sandra C.; Wenkel, Evelyn; Weiland, Elisabeth; Dietzel, Matthias; Janka, Rolf Matthias; Hartmann, Arndt; Emons, Julius; Uder, Michael; Ellmann, Stephan (European Radiology, 2020)
Objectives: This study aimed to develop a tool for the classification of masses in breast MRI, based on ultrafast TWIST-VIBE Dixon (TVD) dynamic sequences combined with DWI. TVD sequences allow to abbreviate breast MRI protocols, but provide kinetic information only on the contrast wash-in, and because of the lack of the wash-out kinetics, their diagnostic value might be hampered. A special focus of this study was thus to maintain high diagnostic accuracy in lesion classification. Materials and methods: Sixty-one patients who received breast MRI between 02/2014 and 04/2015 were included, with 83 reported lesions (60 malignant). Our institute’s standard breast MRI protocol was complemented by an ultrafast TVD sequence. ADC and peak enhancement of the TVD sequences were integrated into a generalised linear model (GLM) for malignancy prediction. For comparison, a second GLM was calculated using ADC and conventional DCE curve type. The resulting GLMs were evaluated for standard diagnostic parameters. For easy application of the GLMs, nomograms were created. Results: The GLM based on peak enhancement of the TVD and ADC was as equally accurate as the GLM based on conventional DCE and ADC, with no significant differences (sensitivity, 93.3%/93.3%; specificity, 91.3%/87.0%; PPV, 96.6%/94.9%; NPV, 84.0%/83.3%; all, p ≥ 0.315). Conclusions: This study presents a method to integrate ultrafast TVD sequences into a breast MRI protocol, allowing a reduction of the examination time while maintaining diagnostic accuracy. A GLM based on the combination of TVD-derived peak enhancement and ADC provides high diagnostic accuracy, and can be easily applied using a nomogram. Key Points: • Ultrafast TWIST-VIBE Dixon sequence protocols in combination with diffusion-weighted imaging allow to shorten breast MRI examinations, while diagnostic accuracy is maintained. • Integrating peak enhancement from the TWIST-VIBE Dixon sequence and the apparent diffusion coefficient into a generalised linear model provides a comprehensible image evaluation approach. • This approach is further facilitated by nomograms.
CRIS-Team Scopus Importer:2020-02-11
Keywords: Breast cancer; Diagnostic imaging; Diffusion magnetic resonance imaging; Magnetic resonance imaging; Statistical model

Comparative analysis of unsupervised algorithms for breast MRI lesion segmentation - Vesal, Sulaiman; Ravikumar, Nishant; Ellmann, Stephan; Maier, Andreas (Informatik aktuell, 2018)
Accurate segmentation of breast lesions is a crucial step in evaluating the characteristics of tumors. However, this is a challenging task, since breast lesions have sophisticated shape, topological structure, and variation in the intensity distribution. In this paper, we evaluated the performance of three unsupervised algorithms for the task of breast Magnetic Resonance (MRI) lesion segmentation, namely, Gaussian Mixture Model clustering, K-means clustering and a markercontrolled Watershed transformation based method. All methods were applied on breast MRI slices following selection of regions of interest (ROIs) by an expert radiologist and evaluated on 106 subject’s images, which include 59 malignant and 47 benign lesions. Segmentation accuracy was evaluated by comparing our results with ground truth masks, using the Dice similarity coefficient (DSC), Jaccard index (JI), Hausdorff distance and precision-recall metrics. The results indicate that the marker-controlled Watershed transformation outperformed all other algorithms investigated.
CRIS-Team Scopus Importer:2022-06-05

Comparison of Readout-Segmented Echo-Planar Imaging and Single-Shot TSE DWI for Cholesteatoma Diagnostics - Wiesmüller, Marco; Wüst, Wolfgang; May, Matthias; Ellmann, Stephan; Heiß, Rafael; Saake, Marc; Janka, Rolf Matthias; Uder, Michael; Laun, Frederik Bernd (American Journal of Neuroradiology, 2021)
BACKGROUND AND PURPOSE: The high diagnostic value of DWI for cholesteatoma diagnostics is undisputed. This study compares the diagnostic value of readout-segmented echo-planar DWI and single-shot TSE DWI for cholesteatoma diagnostics.
CRIS-Team WoS Importer:2021-06-04

Computed Tomography Angiography of Carotid Arteries and Vertebrobasilar System: A Simulation Study for Radiation Dose Reduction - Kramer, Manuel; Ellmann, Stephan; Allmendinger, Thomas; Eller, Achim; Kammerer, Ferdinand; May, Matthias; Baigger, Joao F.; Uder, Michael; Lell, Michael (Medicine, 2015)
Computed tomography angiography (CTA) of carotid arteries and vertebrobasilar system is a standardized procedure with excellent image quality, but radiation exposure remains a matter of concern. The aim of this study is to examine to what extent radiation dose can be lowered in relation to a standard protocol by simulating examinations with lower tube currents applying a dedicated software.Lower tube current was simulated by a dedicated noise insertion and reconstruction software (ReconCT). In a phantom study, true scans were performed with different dose protocols and compared to the results of simulated dose reductions of the same degree, respectively. In a patient study, 30 CTAs of supra-aortic vessels were reconstructed at a level of 100%, 75%, 50%, and 25% of the initial dose. Objective and subjective image analyses were performed.No significant noise differences between true scans and simulated scans of mimicked contrasted vessels were found. In the patient study, the quality scores of the 4 dose groups differed statistically significant; this difference vanished for the comparison of the 100% and 75% datasets after dichotomization into the categories of diagnostic and nondiagnostic image quality (P = .50).This study suggests an easy-to-implement method of simulating CTAs of carotid arteries and vertebrobasilar system with lower tube current for dose reduction by artificially adding noise to the original raw data. Lowering the radiation dose in a moderate extent to 75% of the original dose levels does not significantly alter the diagnostic image quality.
EVALuna2:14495

Computer-aided diagnosis in multiparametric mri of the prostate: An open-access online tool for lesion classification with high accuracy - Ellmann, Stephan; Schlicht, Michael; Dietzel, Matthias; Janka, Rolf Matthias; Hammon, Matthias; Saake, Marc; Ganslandt, Thomas; Hartmann, Arndt; Kunath, Frank; Wullich, Bernd; Uder, Michael; Bäuerle, Tobias (Cancers, 2020)
Computer-aided diagnosis (CADx) approaches could help to objectify reporting on prostate mpMRI, but their use in many cases is hampered due to common-built algorithms that are not publicly available. The aim of this study was to develop an open-access CADx algorithm with high accuracy for classification of suspicious lesions in mpMRI of the prostate. This retrospective study was approved by the local ethics commission, with waiver of informed consent. A total of 124 patients with 195 reported lesions were included. All patients received mpMRI of the prostate between 2014 and 2017, and transrectal ultrasound (TRUS)-guided and targeted biopsy within a time period of 30 days. Histopathology of the biopsy cores served as a standard of reference. Acquired imaging parameters included the size of the lesion, signal intensity (T2w images), diffusion restriction, prostate volume, and several dynamic parameters along with the clinical parameters patient age and serum PSA level. Inter-reader agreement of the imaging parameters was assessed by calculating intraclass correlation coefficients. The dataset was stratified into a train set and test set (156 and 39 lesions in 100 and 24 patients, respectively). Using the above parameters, a CADx based on an Extreme Gradient Boosting algorithm was developed on the train set, and tested on the test set. Performance optimization was focused on maximizing the area under the Receiver Operating Characteristic curve (ROCAUC). The algorithm was made publicly available on the internet. The CADx reached an ROCAUC of 0.908 during training, and 0.913 during testing (p = 0.93). Additionally, established rule-in and rule-out criteria allowed classifying 35.8% of the malignant and 49.4% of the benign lesions with error rates of <2%. All imaging parameters featured excellent inter-reader agreement. This study presents an open-access CADx for classification of suspicious lesions in mpMRI of the prostate with high accuracy. Applying the provided rule-in and rule-out criteria might facilitate to further stratify the management of patients at risk.
CRIS-Team Scopus Importer:2020-09-18
Keywords: Artificial intelligence; Computer-aided diagnosis; Machine learning; Prostate cancer; Prostate mpMRI

Diagnostic value of 3D dynamic contrast-enhanced magnetic resonance imaging in lymph node metastases of head and neck tumors: a correlation study with histology - Treutlein, Christoph; Stollberg, Adrian; Scherl, Claudia; Agaimy, Abbas; Ellmann, Stephan; Iro, Heinrich; Lell, Michael; Uder, Michael; Bäuerle, Tobias (Acta Radiologica Open, 2020)
Background: Accurate staging of cervical lymph nodes (LN) is pivotal for further clinical management of patients with head and neck cancer. Functional magnetic resonance imaging (MRI) such as three-dimensional (3D) dynamic contrast-enhanced (DCE) acquisition might improve the diagnosis of cervical LN metastases.
CRIS-Team WoS Importer:2020-09-25

Dose reduction potential of iterative reconstruction algorithms in neck CTA-a simulation study - Ellmann, Stephan; Kammerer, Ferdinand; Allmendinger, Thomas; Brand, Michael; Janka, Rolf Matthias; Hammon, Matthias; Lell, Michael M.; Uder, Michael; Kramer, Manuel (Dentomaxillofacial Radiology, 2016)
This study aimed to determine the degree of radiation dose reduction in neck CT angiography (CTA) achievable with Sinogram-affirmed iterative reconstruction (SAFIRE) algorithms.10 consecutive patients scheduled for neck CTA were included in this study. CTA images of the external carotid arteries either were reconstructed with filtered back projection (FBP) at full radiation dose level or underwent simulated dose reduction by proprietary reconstruction software. The dose-reduced images were reconstructed using either SAFIRE 3 or SAFIRE 5 and compared with full-dose FBP images in terms of vessel definition. 5 observers performed a total of 3000 pairwise comparisons.SAFIRE allowed substantial radiation dose reductions in neck CTA while maintaining vessel definition. The possible levels of radiation dose reduction ranged from approximately 34 to approximately 90% and depended on the SAFIRE algorithm strength and the size of the vessel of interest. In general, larger vessels permitted higher degrees of radiation dose reduction, especially with higher SAFIRE strength levels. With small vessels, the superiority of SAFIRE 5 over SAFIRE 3 was lost.Neck CTA can be performed with substantially less radiation dose when SAFIRE is applied. The exact degree of radiation dose reduction should be adapted to the clinical question, in particular to the smallest vessel needing excellent definition.
EVALuna2:14595

Dynamic CT angiography for therapy evaluation after transarterial chemoembolization of hepatocellular carcinoma - Saake, Marc; Seuß, Hannes; Hammon, Matthias; Ellmann, Stephan; May, Matthias; Uder, Michael; Schmid, Axel (Acta Radiologica, 2019)
Background: Liver dynamic computed tomography (CT) is an established method for pre- and post-interventional evaluation of hepatocellular carcinoma. To date only the liver parenchyma and perfusion information of dynamic CT has been evaluated widely. Purpose: To evaluate the vascular information contained in dynamic CT datasets. Material and Methods: Dynamic CT performed one day after transarterial chemoembolization (60 mL of contrast medium, 6 mL/s, 40 s scan duration) were retrospectively evaluated. Conventional slice and angiographic maximum-intensity-projection reconstructions were calculated on a multi-modality post-processing platform. Datasets were evaluated for viable tumor, anatomy of the vasculature, and potential tumor-feeding vessels. The results were compared to digital subtraction angiography images. Results: In total, 94 treated hepatocellular carcinoma nodules were evaluated (62 dynamic CT scans, 46 patients [34 men; mean age = 69 years]). Forty-six partially viable tumors were diagnosed after transarterial chemoembolization. In all of these, tumor-feeding vessels were found in dynamic CT. Seventeen suspected extra-hepatic tumor feeders were reported, of which 14 had not been found during previous transarterial chemoembolization. Conclusion: Dynamic CT is useful in post-interventional imaging of hepatocellular carcinoma after transarterial chemoembolization due to its ability to detect residual viable tumor parts and to show previously unknown intra- and extra-hepatic tumor-feeding vessels.
CRIS-Team Scopus Importer:2019-07-02
Keywords: Abdomen; chemoembolization; computed tomography angiography; interventional; liver

Editorial for "Deep Learning Assisted Diagnosis of Musculoskeletal Tumors Based Upon Contrast-Enhanced Magnetic Resonance Imaging" - Ellmann, Stephan; Bäuerle, Tobias (Journal of Magnetic Resonance Imaging, 2021)
CRIS-Team WoS Importer:2021-12-31

Ein klinisch anwendbares Neuronales Netzwerk zur Klassifikation suspekter Läsionen in der Mamma-MRT - Ellmann, Stephan; Bielowski, Christian; Wenkel, Evelyn; Vesal, Sulaiman; Maier, Andreas; Uder, Michael; Bäuerle, Tobias (Fortschritte auf dem Gebiete der Röntgenstrahlen, 2018)
UnivIS-Import:2018-09-05:Pub.2018.tech.IMMD.IMMD5.einkli

Evaluation of Rib Fractures on a Single-in-plane Image Reformation of the Rib Cage in CT Examinations - Dankerl, Peter; Seuß, Hannes; Ellmann, Stephan; Uder, Michael; Hammon, Matthias; Cavallaro, Alexander Josef (Academic Radiology, 2016)
This study aimed to evaluate the diagnostic performance of using a reformatted single-in-plane image reformation of the rib cage for the detection of rib fractures in computed tomography (CT) examinations, employing different levels of radiological experience.We retrospectively evaluated 10 consecutive patients with and 10 patients without rib fractures, whose CT scans were reformatted to a single-in-plane image reformation of the rib cage. Eight readers (two radiologists, two residents in radiology, and four interns) independently evaluated the images for the presence of rib fractures using a reformatted single-in-plane image and a multi-planar image reformation. The time limit was 30 seconds for each read. A consensus of two radiologist readings was considered as the reference standard. Diagnostic performance (sensitivity, specificity, positive predictive value [PPV], and negative predictive value [NPV]) was assessed and evaluated per rib and per location (anterior, lateral, posterior). To determine the time limit, we prospectively analyzed the average time it took radiologists to assess the rib cage, in a bone window setting, in 50 routine CT examinations. McNemar test was used to compare the diagnostic performances.Single image reformation was successful in all 20 patients. The sensitivity, specificity, PPV, and NPV for the detection of rib fractures using the conventional multi-planar read were 77.5%, 99.2%, 89.9%, and 98.0% for radiologists; 46.3%, 99.7%, 92.5%, and 95.3% for residents; and 29.4%, 99.4%, 82.5%, and 93.9% for interns, respectively. Sensitivity, PPV, and NPV increased across all three groups of experience, using the reformatted single-in-plane image of the rib cage (radiologists: 85.0%, 98.6%, and 98.7%; residents: 80.0%, 92.8%, and 98.2%; interns: 66.9%, 89.9%, and 97.1%), whereas specificity did not change significantly (99.9%, 99.4%, and 99.3%). The diagnostic performance of the interns and residents was significantly better when evaluating the single-in-plane image reformations (P < .01). The diagnostic performance of the radiologists was better when evaluating the single-in-plane image reformations; however, there was no significant difference (statistical power: 0.32).The diagnostic performance for the detection of rib fractures, using CT images that have been reformatted to a single-in-plane image, improves for readers from different educational levels when the evaluation time is restricted to 30 seconds or less.
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Extent of simultaneous radiation dose and iodine reduction at stable image quality in computed tomography of the chest: A systematic approach using automated tube voltage adaption and iterative reconstructions - Eller, Achim; Wüst, Wolfgang; Saake, Marc; Ellmann, Stephan; Kämmerer, Nadine; Hammon, Matthias; Janka, Rolf Matthias; Uder, Michael; May, Matthias (Medicine, 2018)
BACKGROUND: Aim of this study was to systematically combine tube voltage adaptation and iterative reconstructions for reduction of iodine and radiation dose. METHODS: Settings for the study protocol were evaluated in ex-ante trials to provide image quality that is comparable to a reference protocol at 120 kV with tube current modulation. Consecutive patients were randomized to undergo computed tomography (CT) of the chest using the study protocol (n = 62) or reference protocol (n = 50). Objective and subjective image quality was assessed and compared. RESULTS: Tube voltage was decreased to 100 kV in 47 patients and to 80 kV in 15 patients in the study group. The iodine dosage (16.1 vs 10.5 g) and the effective radiation dose (3.6 vs 2.5 mSv) were significantly decreased in the study group (both P < .001). Contrast-to-noise ratio was comparable in the pulmonary trunk and increased in the aorta (P < .01). Subjective image quality was comparable without statistically significance. CONCLUSIONS: Simultaneous reductions in iodine dosage and radiation dose by one-third are feasible for CT of the chest.
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How COVID-19 kick-started online learning in medical education-The DigiMed study - Stoehr, Fabian; Müller, Lukas; Brady, Adrian; Trilla, Antoni; Mähringer-Kunz, Aline; Hahn, Felix; Düber, Christoph; Becker, Nicole; Wörns, Marcus Alexander; Chapiro, Julius; Hinrichs, Jan Bernd; Akata, Deniz; et al. (PLoS ONE, 2021)
Background The coronavirus disease 2019 (COVID-19) pandemic led to far-reaching restrictions of social and professional life, affecting societies all over the world. To contain the virus, medical schools had to restructure their curriculum by switching to online learning. However, only few medical schools had implemented such novel learning concepts. We aimed to evaluate students' attitudes to online learning to provide a broad scientific basis to guide future development of medical education. Methods Overall, 3286 medical students from 12 different countries participated in this cross-sectional, web-based study investigating various aspects of online learning in medical education. On a 7-point Likert scale, participants rated the online learning situation during the pandemic at their medical schools, technical and social aspects, and the current and future role of online learning in medical education. Results The majority of medical schools managed the rapid switch to online learning (78%) and most students were satisfied with the quantity (67%) and quality (62%) of the courses. Online learning provided greater flexibility (84%) and led to unchanged or even higher attendance of courses (70%). Possible downsides included motivational problems (42%), insufficient possibilities for interaction with fellow students (67%) and thus the risk of social isolation (64%). The vast majority felt comfortable using the software solutions (80%). Most were convinced that medical education lags behind current capabilities regarding online learning (78%) and estimated the proportion of online learning before the pandemic at only 14%. In order to improve the current curriculum, they wish for a more balanced ratio with at least 40% of online teaching compared to on-site teaching. Conclusion This study demonstrates the positive attitude of medical students towards online learning. Furthermore, it reveals a considerable discrepancy between what students demand and what the curriculum offers. Thus, the COVID-19 pandemic might be the long-awaited catalyst for a new "online era"in medical education.
CRIS-Team Scopus Importer:2021-10-22

Hybrid Imaging (PET-Computed Tomography/PET-MR Imaging) of Bone Metastases - Schmidkonz, Christian; Ellmann, Stephan; Ritt, Philipp; Roemer, Frank; Guermazi, Ali; Uder, Michael; Kuwert, Torsten; Bäuerle, Tobias (PET Clinics, 2019)
Bone metastases are a common source of osseous malignancy in the skeleton and affect up to 70% of all cancer patients. Hybrid imaging modalities including positron emission tomography (PET)/computed tomography (CT) and PET/MRI play an increasing role for the detection and follow-up of metastatic disease, especially in monitoring treatment response upon local or systemic therapy. This review summarizes current applications of PET/CT and PET/MRI in the clinical setting for imaging of metastases.
CRIS-Team WoS Importer:2020-02-21

Implementation of machine learning into clinical breast MRI: Potential for objective and accurate decision-making in suspicious breast masses - Ellmann, Stephan; Wenkel, Evelyn; Dietzel, Matthias; Bielowski, Christian; Vesal, Sulaiman; Maier, Andreas; Hammon, Matthias; Janka, Rolf Matthias; Fasching, Peter; Beckmann, Matthias; Schulz-Wendtland, Rüdiger; Uder, Michael; et al. (PLoS ONE, 2020)
We investigated whether the integration of machine learning (ML) into MRI interpretation can provide accurate decision rules for the management of suspicious breast masses. A total of 173 consecutive patients with suspicious breast masses upon complementary assessment (BI-RADS IV/V: n = 100/76) received standardized breast MRI prior to histological verification. MRI findings were independently assessed by two observers (R1/R2: 5 years of experience/no experience in breast MRI) using six (semi-)quantitative imaging parameters. Interobserver variability was studied by ICC (intraclass correlation coefficient). A polynomial kernel function support vector machine was trained to differentiate between benign and malignant lesions based on the six imaging parameters and patient age. Ten-fold cross-validation was applied to prevent overfitting. Overall diagnostic accuracy and decision rules (rule-out criteria) to accurately exclude malignancy were evaluated. Results were integrated into a web application and published online. Malignant lesions were present in 107 patients (60.8%). Imaging features showed excellent interobserver variability (ICC: 0.81–0.98) with variable diagnostic accuracy (AUC: 0.65–0.82). Overall performance of the ML algorithm was high (AUC = 90.1%; BI-RADS IV: AUC = 91.6%). The ML algorithm provided decision rules to accurately rule-out malignancy with a false negative rate <1% in 31.3% of the BI-RADS IV cases. Thus, integration of ML into MRI interpretation can provide objective and accurate decision rules for the management of suspicious breast masses, and could help to reduce the number of potentially unnecessary biopsies.<br

Influence of Cardiac MR Imaging on DNA Double-Strand Breaks in Human Blood Lymphocytes - Brand, Michael; Ellmann, Stephan; Sommer, Matthias; May, Matthias; Eller, Achim; Wüst, Wolfgang; Engert, Christina; Achenbach, Stephan; Kuefner, Michael A.; Bäuerle, Tobias; Lell, Michael; Uder, Michael (Radiology, 2015)
To evaluate the ability of magnetic resonance (MR) imaging to induce deoxyribonucleic acid (DNA) damage in patients who underwent cardiac MR imaging in daily routine by using ?-H2AX immunofluorescence microscopy.This study complies with the Declaration of Helsinki and was performed according to local ethics committee approval. Informed patient consent was obtained. Blood samples from 45 patients (13 women, 32 men; mean age, 50.3 years [age range, 20-89 years]) were obtained before and after contrast agent-enhanced cardiac MR imaging. MR imaging-induced double-strand breaks (DSBs) were quantified in isolated blood lymphocytes by using immunofluorescence microscopy after staining the phosphorylated histone variant ?-H2AX. Twenty-nine patients were examined with a myocarditis protocol (group A), 10 patients with a stress-testing protocol (group B), and six patients with flow measurements and angiography (group C). Paired t test was performed to compare excess foci before and after MR imaging.The mean baseline DSB level before MR imaging and 5 minutes after MR imaging was, respectively, 0.116 DSB per cell ± 0.019 (standard deviation) and 0.117 DSB per cell ± 0.019 (P = .71). There was also no significant difference in DSBs in these subgroups (group A: DSB per cell before and after MR imaging, respectively, 0.114 and 0.114, P = .91; group B: DSB per cell before and after MR imaging, respectively, 0.123 and 0.124, P = .78; group C: DSB per cell before and after MR imaging, respectively, 0.114 and 0.115, P = .36).By using ?-H2AX immunofluorescence microscopy, no DNA DSBs were detected after cardiac MR imaging.
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Influence of Different Antioxidants on X-Ray Induced DNA Double-Strand Breaks (DSBs) Using ?-H2AX Immunofluorescence Microscopy in a Preliminary Study - Brand, Michael; Sommer, Matthias; Ellmann, Stephan; Wüst, Wolfgang; May, Matthias; Eller, Achim; Vogt, Sabine; Lell, Michael; Kuefner, Michael A.; Uder, Michael (PLoS ONE, 2015)
Radiation exposure occurs in X-ray guided interventional procedures or computed tomography (CT) and ?-H2AX-foci are recognized to represent DNA double-strand breaks (DSBs) as a biomarker for radiation induced damage. Antioxidants may reduce the induction of ?-H2AX-foci by binding free radicals. The aim of this study was to establish a dose-effect relationship and a time-effect relationship for the individual antioxidants on DSBs in human blood lymphocytes.Blood samples from volunteers were irradiated with 10 mGy before and after pre-incubation with different antioxidants (zinc, trolox, lipoic acid, ß-carotene, selenium, vitamin E, vitamin C, N-acetyl-L-cysteine (NAC) and Q 10). Thereby, different pre-incubation times, concentrations and combinations of drugs were evaluated. For assessment of DSBs, lymphocytes were stained against the phosphorylated histone variant ?-H2AX.For zinc, trolox and lipoic acid regardless of concentration or pre-incubation time, no significant decrease of ?-H2AX-foci was found. However, ß-carotene (15%), selenium (14%), vitamin E (12%), vitamin C (25%), NAC (43%) and Q 10 (18%) led to a significant reduction of ?-H2AX-foci at a pre-incubation time of 1 hour. The combination of different antioxidants did not have an additive effect.Antioxidants administered prior to irradiation demonstrated the potential to reduce ?-H2AX-foci in blood lymphocytes.
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Iterative Metal Artifact Reduction in Head and Neck CT Facilitates Tumor Visualization of Oral and Oropharyngeal Cancer Obscured by Artifacts From Dental Hardware - Bayerl, Nadine; May, Matthias; Wuest, Wolfgang; Roth, Jessica; Kramer, Manuel; Hofmann, Christian; Schmidt, Bernhard; Uder, Michael; Ellmann, Stephan (Academic Radiology, 2023)
Rationale and Objectives: The purpose of this study was to evaluate the diagnostic utility of iterative metal artifact reduction (iMAR) in computed tomography (CT)-imaging of oral and oropharyngeal cancers when obscured by dental hardware artifacts and to determine the most appropriate iMAR settings for this purpose. Materials and Methods: The study retrospectively enrolled 27 patients (8 female, 19 male; mean age 64 ± 12.7 years) with histologically confirmed oral or oropharyngeal cancer obscured by dental artifacts in contrast-enhanced CT. Raw CT data were reconstructed with ascending iMAR strengths (levels 1/2/3/4/5) and one reconstruction without iMAR (level 0). For subjective analysis, two blinded radiologists rated tumor visualization and artifact severity on a five-point Likert scale. For objective analysis, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and artifact index (AI) were determined. Results: iMAR reconstructions improved the subjective image quality of tumor edge and contrast, and the objective parameters of tumor SNR and CNR, reaching their optimum at iMAR levels 4 and 5 (P < .001). AI decreased with iMAR reconstructions reaching its minimum at iMAR level 5 (P < .001). Tumor detection rates increased 2.4-fold with iMAR 5, 2.1-fold with iMAR 4, and 1.9-fold with iMAR 3 compared to reconstructions without iMAR. Disadvantages such as algorithm-induced artifacts increased significantly with higher iMAR strengths (P < .05), reaching a maximum with iMAR 5. Conclusion: iMAR significantly improves CT imaging of oral and oropharyngeal cancers, as confirmed by both subjective and objective measures, with best results at highest iMAR strengths.
CRIS-Team Scopus Importer:2023-05-26
Keywords: Artifact; Cancer imaging; Computed tomography; Head and neck; Metal artifact reduction

Large Language Models for Simplified Interventional Radiology Reports: A Comparative Analysis - Can, Elif; Uller, Wibke; Vogt, Katharina; Doppler, Michael C.; Busch, Felix; Bayerl, Nadine; Ellmann, Stephan; Kader, Avan; Elkilany, Aboelyazid; Makowski, Marcus R.; Bressem, Keno K.; Adams, Lisa C. (Academic Radiology, 2024)
Purpose: To quantitatively and qualitatively evaluate and compare the performance of leading large language models (LLMs), including proprietary models (GPT-4, GPT-3.5 Turbo, Claude-3-Opus, and Gemini Ultra) and open-source models (Mistral-7b and Mistral-8×7b), in simplifying 109 interventional radiology reports. Methods: Qualitative performance was assessed using a five-point Likert scale for accuracy, completeness, clarity, clinical relevance, naturalness, and error rates, including trust-breaking and post-therapy misconduct errors. Quantitative readability was assessed using Flesch Reading Ease (FRE), Flesch-Kincaid Grade Level (FKGL), SMOG Index, and Dale-Chall Readability Score (DCRS). Paired t-tests and Bonferroni-corrected p-values were used for statistical analysis. Results: Qualitative evaluation showed no significant differences between GPT-4 and Claude-3-Opus for any metrics evaluated (all Bonferroni-corrected p-values: p = 1), while they outperformed other assessed models across five qualitative metrics (p < 0.001). GPT-4 had the fewest content and trust-breaking errors, with Claude-3-Opus second. However, all models exhibited some level of trust-breaking and post-therapy misconduct errors, with GPT-4-Turbo and GPT-3.5-Turbo with few-shot prompting showing the lowest error rates, and Mistral-7B and Mistral-8×7B showing the highest. Quantitatively, GPT-4 surpassed Claude-3-Opus in all readability metrics (all p < 0.001), with a median FRE score of 69.01 (IQR: 64.88–73.14) versus 59.74 (IQR: 55.47–64.01) for Claude-3-Opus. GPT-4 also outperformed GPT-3.5-Turbo and Gemini Ultra (both p < 0.001). Inter-rater reliability was strong (κ = 0.77–0.84). Conclusions: GPT-4 and Claude-3-Opus demonstrated superior performance in generating simplified IR reports, but the presence of errors across all models, including trust-breaking errors, highlights the need for further refinement and validation before clinical implementation. Clinical relevance/applications: With the increasing complexity of interventional radiology (IR) procedures and the growing availability of electronic health records, simplifying IR reports is critical to improving patient understanding and clinical decision-making. This study provides insights into the performance of various LLMs in rewriting IR reports, which can help in selecting the most suitable model for clinical patient-centered applications.
CRIS-Team Scopus Importer:2024-10-11
Keywords: Artificial Intelligence; Interventional Radiology; Large Language Model; Patient Friendliness; Structured Reporting

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model - Ellmann, Stephan; Seyler, Lisa; Gillmann, Clarissa; Popp, Vanessa; Treutlein, Christoph; Bozec, Aline; Uder, Michael; Bäuerle, Tobias (Journal of Visualized Experiments, 2020)
Machine learning (ML) algorithms permit the integration of different features into a model to perform classification or regression tasks with an accuracy exceeding its constituents. This protocol describes the development of an ML algorithm to predict the growth of breast cancer bone macrometastases in a rat model before any abnormalities are observable with standard imaging methods. Such an algorithm can facilitate the detection of early metastatic disease (i.e., micrometastasis) that is regularly missed during staging examinations. The applied metastasis model is site-specific, meaning that the rats develop metastases exclusively in their right hind leg. The model's tumor-take rate is 60%-80%, with macrometastases becoming visible in magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) in a subset of animals 30 days after induction, whereas a second subset of animals exhibit no tumor growth. Starting from image examinations acquired at an earlier time point, this protocol describes the extraction of features that indicate tissue vascularization detected by MRI, glucose metabolism by PET/CT, and the subsequent determination of the most relevant features for the prediction of macrometastatic disease. These features are then fed into a model-averaged neural network (avNNet) to classify the animals into one of two groups: one that will develop metastases and the other that will not develop any tumors. The protocol also describes the calculation of standard diagnostic parameters, such as overall accuracy, sensitivity, specificity, negative/positive predictive values, likelihood ratios, and the development of a receiver operating characteristic. An advantage of the proposed protocol is its flexibility, as it can be easily adapted to train a plethora of different ML algorithms with adjustable combinations of an unlimited number of features. Moreover, it can be used to analyze different problems in oncology, infection, and inflammation.
CRIS-Team Scopus Importer:2020-09-11

Morphological, functional, and molecular assessment of breast cancer bone metastases by experimental ultrasound techniques compared with magnetic resonance imaging and histological analysis - Heinen, Henrik; Seyler, Lisa; Popp, Vanessa; Hellwig, Konstantin; Bozec, Aline; Uder, Michael; Ellmann, Stephan; Bäuerle, Tobias (Bone, 2021)
Background: The imaging of bone metastases, which is regularly performed by cross-sectional modalities, is clinically vital when characterizing and staging osseous lesions. In this paper, we aimed to establish a novel methodology using experimental ultrasound (US) techniques to assess the morphological, functional, and molecular features of breast cancer bone metastases in an animal model, compared with magnetic resonance imaging (MRI) and histological analysis. Materials and methods: Nude rats were implanted intra-arterially with MDA-MB-231 breast cancer cells to induce osteolytic metastasis in their right hind legs. Once tumors had developed, an experimental US technique using automatic 3D scanning and MRI were performed. For assessment of perfusion, functional imaging techniques included contrast-enhanced US (CEUS) and dynamic contrast-enhanced MRI (DCE-MRI). For molecular ultrasound, anti-VEGFR2 conjugated microbubbles were applied and correlated with immunostaining for VEGFR2 expression. Results: 3D US enabled the automatic assessment of osteolytic lesions, including the largest tumor diameters along the x-, y- and z-axes as well as the segmented tumor volumes, without significant differences between US and MRI (p > 0.18). The CEUS and DCE-MRI of osseous lesions showed corresponding results for the parameters peak enhancement, wash-in area under the curve (both, r > 0.5) and wash-in perfusion index (r > 0.3) when differentiating between tumor, necrotic tissue and healthy muscle tissue (all, p < 0.01). Finally, molecular US allowed the non-invasive assessment of increased VEGFR2 expression in skeletal lesions compared with surrounding muscle tissue (p = 0.03), while a control antibody could not discriminate between these tissues (p = 0.44)—a factor which was confirmed by histological analysis. Conclusion: To the best of our knowledge, this is the first report on an imaging protocol for breast cancer bone metastasis using an experimental US scanner. Therefore, we present a novel methodology to characterize these osseous lesions on the morphological, functional, and molecular level in correlation with MRI and histological analysis.
CRIS-Team Scopus Importer:2021-01-01
Keywords: Animal model; Bone metastases; Imaging; Magnetic resonance imaging; Microbubbles; Ultrasound

Multimodal imaging of bone metastases: From preclinical to clinical applications - Ellmann, Stephan; Beck, Michael; Kuwert, Torsten; Uder, Michael; Bäuerle, Tobias (Journal of Orthopaedic Translation, 2015)
Metastases to the skeletal system are commonly observed in cancer patients, highly affecting the patients' quality of life. Imaging plays a major role in detection, follow-up, and molecular characterisation of metastatic disease. Thus, imaging techniques have been optimised and combined in a multimodal and multiparametric manner for assessment of complementary aspects in osseous metastases. This review summarises both application of the most relevant imaging techniques for bone metastasis in preclinical models and the clinical setting.
CRIS-Team Scopus Importer:2023-03-08
Keywords: Bone metastases; Computed tomography; Magnetic resonance imaging; Multimodal imaging; Positron-emission tomography; Translational research

Multiparametric magnetic resonance imaging of experimental chronic kidney disease: A quantitative correlation study with histology - Schley, Gunnar; Jordan, Jutta; Ellmann, Stephan; Rosen, Seymour; Eckardt, Kai-Uwe; Uder, Michael; Willam, Carsten; Bäuerle, Tobias (PLoS ONE, 2018)
OBJECTIVES: In human chronic kidney disease (CKD) the extent of renal tubulointerstitial fibrosis correlates with progressive loss of renal function. However, fibrosis can so far only be assessed by histology of kidney biopsies. Magnetic resonance imaging (MRI) can provide information about tissue architecture, but its potential to assess fibrosis and inflammation in diseased kidneys remains poorly defined. MATERIALS AND METHODS: We evaluated excised kidneys in a murine adenine-induced nephropathy model for CKD by MRI and correlated quantitative MRI parameters (T1, T2, and T2* relaxation times, apparent diffusion coefficient and fractional anisotropy) with histological hallmarks of progressive CKD, including renal fibrosis, inflammation, and microvascular rarefaction. Furthermore, we analyzed the effects of paraformaldehyde fixation on MRI parameters by comparing kidney samples before and after fixation with paraformaldehyde. RESULTS: In diseased kidneys T2 and T2* relaxation times, apparent diffusion coefficient and fractional anisotropy in the renal cortex and/or outer medulla were significantly different from those in control kidneys. In particular, T2 relaxation time was the best parameter to distinguish control and CKD groups and correlated very well with the extent of fibrosis, inflammatory infiltrates, tubular dilation, crystal deposition, and loss of peritubular capillaries and normal tubules in the renal cortex and outer medulla. Fixation with paraformaldehyde had no impact on T2 relaxation time and fractional anisotropy, whereas T1 times significantly decreased and T2* times and apparent diffusion coefficients increased in fixed kidney tissue. CONCLUSIONS: MRI parameters provide a promising approach to quantitatively assess renal fibrosis and inflammation in CKD. Especially T2 relaxation time correlates well with histological features of CKD and is not influenced by paraformaldehyde fixation of kidney samples. Thus, T2 relaxation time might be a candidate parameter for non-invasive assessment of renal fibrosis in human patients.
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Non-Invasive Characterization of Experimental Bone Metastasis in Obesity Using Multiparametric MRI and PET/CT - Gregoric, Gasper; Gaculenko, Anastasia; Nagel, Lisa; Popp, Vanessa; Maschauer, Simone; Prante, Olaf; Saake, Marc; Schett, Georg; Uder, Michael; Ellmann, Stephan; Bozec, Aline; Bäuerle, Tobias (Cancers, 2022)
The growth of primary tumors and metastases is associated with excess body fat. In bone metastasis formation, the bone marrow microenvironment, and particularly adipocytes, play a pivotal role as growth mediators of disseminated tumor cells in the bone marrow. The aim of the present study is to non-invasively characterize the pathophysiologic processes in experimental bone metastasis resulting from accelerated tumor progression within adipocyte-rich bone marrow using multimodal imaging from magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT). To achieve this, we have employed small animal models after the administration of MDA-MB 231 breast cancer and B16F10 melanoma cells into the bone of nude rats or C57BL/6 mice, respectively. After tumor cell inoculation, ultra-high field MRI and mu PET/CT were used to assess functional and metabolic parameters in the bone marrow of control animals (normal diet, ND), following a high-fat diet (HFD), and/or treated with the peroxisome proliferator-activated receptor-gamma (PPAR gamma) antagonist bisphenol-A-diglycidylether (BADGE), respectively. In the bone marrow of nude rats, dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI), as well as [F-18]fluorodeoxyglucose-PET/CT([F-18]FDG-PET/CT), was performed 10, 20, and 30 days after tumor cell inoculation, followed by immunohistochemistry. DCE-MRI parameters associated with blood volume, such as area under the curve (AUC), were significantly increased in bone metastases in the HFD group 30 days after tumor cell inoculation as compared to controls (p < 0.05), while the DWI parameter apparent diffusion coefficient (ADC) was not significantly different between the groups. [F-18]FDG-PET/CT showed an enhanced glucose metabolism due to increased standardized uptake value (SUV) at day 30 after tumor cell inoculation in animals that received HFD (p < 0.05). BADGE treatment resulted in the inversion of quantitative DCE-MRI and [F-18]FDG-PET/CT data, namely a significant decrease in AUC and SUV in HFD-fed animals as compared to ND-fed controls (p < 0.05). Finally, immunohistochemistry and qPCR confirmed the HFD-induced stimulation in vascularization and glucose activity in murine bone metastases. In conclusion, multimodal and multiparametric MRI and [F-18]FDG-PET/CT were able to derive quantitative parameters in bone metastases, revealing an increase in vascularization and glucose metabolism following HFD. Thus, non-invasive imaging may serve as a biomarker for assessing the pathophysiology of bone metastasis in obesity, opening novel options for therapy and treatment monitoring by MRI and [F-18]FDG-PET/CT.
CRIS-Team WoS Importer:2022-06-10

Prediction of early metastatic disease in experimental breast cancer bone metastasis by combining PET/CT and MRI parameters to a Model-Averaged Neural Network - Ellmann, Stephan; Seyler, Lisa; Evers, Jochen; Heinen, Henrik; Bozec, Aline; Prante, Olaf; Kuwert, Torsten; Uder, Michael; Bäuerle, Tobias (Bone, 2019)
Macrometastases in bone are preceded by bone marrow invasion of disseminated tumor cells. This study combined functional imaging parameters from FDG-PET/CT and MRI in a rat model of breast cancer bone metastases to a Model-averaged Neural Network (avNNet) for the detection of early metastatic disease and prediction of future macrometastases. Metastases were induced in 28 rats by injecting MDA-MB-231 breast cancer cells into the right superficial epigastric artery, resulting in the growth of osseous metastases in the right hind leg of the animals. All animals received FDG-PET/CT and MRI at days 0, 10, 20 and 30 after tumor cell injection. In total, 18/28 rats presented with metastases at days 20 or 30 (64.3%). None of the animals featured morphologic bone lesions during imaging at day 10, and the imaging parameters acquired at day 10 did not differ significantly between animals with metastases at or after day 20 and those without (all p > 0.3). The avNNet trained with the imaging parameters acquired at day 10, however, achieved an accuracy of 85.7% (95% CI 67.3-96.0%) in predicting future macrometastatic disease (ROCAUC 0.90; 95% CI 0.76-1.00), and significantly outperformed the predictive capacities of all single parameters (all p <= 0.02). The integration of functional FDG-PET/CT and MRI parameters into an avNNet can thus be used to predict macrometastatic disease with high accuracy, and their combination might serve as a surrogate marker for bone marrow invasion as an early metastatic process that is commonly missed during conventional staging examinations.
CRIS-Team WoS Importer:2019-02-27

Predictive Value of Multiparametric MRI for Response to Single-Cycle Induction Chemo-Immunotherapy in Locally Advanced Head and Neck Squamous Cell Carcinoma - Hellwig, Konstantin; Ellmann, Stephan; Eckstein, Markus; Wiesmüller, Marco; Rutzner, Sandra; Semrau, Sabine; Frey, Benjamin; Gaipl, Udo; Hartmann, Arndt; Iro, Heinrich; Fietkau, Rainer; Uder, Michael; et al. (Frontiers in Oncology, 2021)
Objectives
CRIS-Team WoS Importer:2021-11-19

Prognostic value of cta-derived left ventricular mass in neonates with congenital heart disease - Ellmann, Stephan; Nickel, Julie-Marie; Heiß, Rafael; El Amrani, Nouhayla; Wüst, Wolfgang; Rompel, Oliver; Rueffer, Andre; Cesnjevar, Robert; Dittrich, Sven; Uder, Michael; May, Matthias (Diagnostics, 2021)
For therapeutic decisions regarding uni-or biventricular surgical repair in congenital heart disease (CHD), left ventricular mass (LVM) is an important factor. The aim of this retrospective study was to determine the LVM of infants with CHD in thoracic computed tomography angiographies (CTAs) and to evaluate its usefulness as a prognostic parameter, with special attention paid to hypoplastic left heart (HLH) patients. Manual segmentation of the left ventricular endo-and epicardial volumes was performed in CTAs of 132 infants. LVMs were determined from these volumes and normalized to body surface area. LVMs of patients with different types of CHD were compared to each other using analyses of variances (ANOVA). An LVM cutoff for discrimination between uni-and biventricular repair was determined using receiver operating characteristics. Survival rates were calculated using Kaplan–Meier statistics. Patients with a clinical diagnosis of an HLH had significantly lower mean LVM (21.88 g/m2) compared to patients without applicable disease (50.22 g/m2; p < 0.0001) and compared to other CHDs, including persistent truncus arteriosus, left ventricular outflow tract obstruction, transposition of the great arteries, pulmonary artery stenosis or atresia, and double-outlet right ventricle (all, p < 0.05). The LVM cutoff for uni-vs. biventricular surgery was 33.9 g/m2 (sensitivity: 82.3%; specificity: 73.7%; PPV: 94.9%). In a subanalysis of HLH patients, a sensitivity of 50.0%, specificity of 100%, PPV of 100%, and NPV of 83.3% was determined. Patient survival was not significantly different between the surgical approaches or between patients with LVM above or below the cutoff. LVM can be measured in chest CTA of newborns with CHD and can be used as a prognostic factor.
CRIS-Team Scopus Importer:2021-07-30
Keywords: Cardiac computed tomography; Computed tomography angiography; Congenital heart disease; Heart imaging; Heart surgery; Hypoplastic left heart

Semi-Automatic Algorithm for Breast MRI Lesion Segmentation Using Marker-Controlled Watershed Transformation - Vesal, Sulaiman; Diaz-Pinto, Andres; Ravikumar, Nishant; Ellmann, Stephan; Davari, Amirabbas; Maier, Andreas (2017 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC), 2017)
UnivIS-Import:2018-09-11:Pub.2017.tech.IMMD.IMMD5.semiau_5

Soluble CD83 Triggers Resolution of Arthritis and Sustained Inflammation Control in IDO Dependent Manner - Royzman, Dmytro; Andrev, Darja; Stich, Lena; Rauh, Manfred; Bäuerle, Tobias; Ellmann, Stephan; Boon, Louis; Kindermann, Markus; Peckert, Katrin; Bozec, Aline; Schett, Georg; Steinkasserer, Alexander; et al. (Frontiers in Immunology, 2019)
Interference with autoimmune-mediated cytokine production is a key yet poorly developed approach to treat autoimmune and inflammatory diseases such as rheumatoid arthritis. Herein, we show that soluble CD83 (sCD83) enhances the resolution of autoimmune antigen-induced arthritis (AIA) by strongly reducing the expression levels of cytokines such as IL-17A, IFN gamma, IL-6, and TNF alpha within the joints. Noteworthy, also the expression of RANKL, osteoclast differentiation, and joint destruction was significantly inhibited by sCD83. In addition, osteoclasts which were cultured in the presence of synovial T cells, derived from sCD83 treated AIA mice, showed a strongly reduced number of multinuclear large osteoclasts compared to mock controls. Enhanced resolution of arthritis by sCD83 was mechanistically based on IDO, since inhibition of IDO by 1-methyltryptophan completely abrogated sCD83 effects on AIA. Blocking experiments, using anti-TGF-beta antibodies further revealed that also TGF-beta is mechanistically involved in the sCD83 induced reduction of bone destruction and cartilage damage as well as enhanced resolution of inflammation. Resolution of arthritis was associated with increased numbers of regulatory T cells, which are induced in a sCD83-IDO-TGF-beta dependent manner. Taken together, sCD83 represents an interesting approach for downregulating cytokine production, inducing regulatory T cells and inducing resolution of autoimmune arthritis.
CRIS-Team WoS Importer:2019-04-12

The German COVID-19 Digital Contact Tracing App: A Socioeconomic Evaluation - Ellmann, Stephan; Maryschok, Markus; Schöffski, Oliver; Emmert, Martin (International Journal of Environmental Research and Public Health, 2022)
The COVID-19 pandemic posed challenges to governments in terms of contact tracing. Like many other countries, Germany introduced a mobile-phone-based digital contact tracing solution (“Corona Warn App”; CWA) in June 2020. At the time of its release, however, it was hard to assess how effective such a solution would be, and a political and societal debate arose regarding its efficiency, also in light of its high costs. This study aimed to analyze the effectiveness of the CWA, considering prevented infections, hospitalizations, intensive care treatments, and deaths. In addition, its efficiency was to be assessed from a monetary point of view, and factors with a significant influence on the effectiveness and efficiency of the CWA were to be determined. Mathematical and statistical modeling was used to calculate infection cases prevented by the CWA, along with the numbers of prevented complications (hospitalizations, intensive care treatments, deaths) using publicly available CWA download numbers and incidences over time. The monetized benefits of these prevented cases were quantified and offset against the costs incurred. Sensitivity analysis was used to identify factors critically influencing these parameters. Between June 2020 and April 2022, the CWA prevented 1.41 million infections, 17,200 hospitalizations, 4600 intensive care treatments, and 7200 deaths. After offsetting costs and benefits, the CWA had a net present value of EUR 765 m in April 2022. Both the effectiveness and efficiency of the CWA are decisively and disproportionately positively influenced by the highest possible adoption rate among the population and a high rate of positive infection test results shared via the CWA.
CRIS-Team Scopus Importer:2022-11-25
Keywords: Corona Warn App; cost–benefit analysis; COVID-19; digital contact tracing; utility analysis

Tumor grade-titude: XGBoost radiomics paves the way for RCC classification - Ellmann, Stephan; von Rohr, Felicitas; Komina, Selim; Bayerl, Nadine; Amann, Kerstin Ute; Polifka, Iris; Hartmann, Arndt; Sikic, Danijel; Wullich, Bernd; Uder, Michael; Bäuerle, Tobias (European Journal of Radiology, 2025)
This study aimed to develop and evaluate a non-invasive XGBoost-based machine learning model using radiomic features extracted from pre-treatment CT images to differentiate grade 4 renal cell carcinoma (RCC) from lower-grade tumours. A total of 102 RCC patients who underwent contrast-enhanced CT scans were included in the analysis. Radiomic features were extracted, and a two-step feature selection methodology was applied to identify the most relevant features for classification. The XGBoost model demonstrated high performance in both training (AUC = 0.87) and testing (AUC = 0.92) sets, with no significant difference between the two (p = 0.521). The model also exhibited high sensitivity, specificity, positive predictive value, and negative predictive value. The selected radiomic features captured both the distribution of intensity values and spatial relationships, which may provide valuable insights for personalized treatment decision-making. Our findings suggest that the XGBoost model has the potential to be integrated into clinical workflows to facilitate personalized adjuvant immunotherapy decision-making, ultimately improving patient outcomes. Further research is needed to validate the model in larger, multicentre cohorts and explore the potential of combining radiomic features with other clinical and molecular data.
CRIS-Team Scopus Importer:2025-05-16
Keywords: Computed tomography (CT); Diagnostic performance; Feature extraction; Machine learning; Personalized immunotherapy; Radiomics; Renal cell carcinoma (RCC); Treatment decision-making; Tumor grading

Vision, Development, and Structure of the First German Specialist Training Curriculum for Radiology - Molwitz, Isabel; Frisch, Anne; Adam, Gerhard; Afat, Saif; Ammon, Josefin; Antoch, Gerald; Baeßler, Bettina; Balks, Friederike; Barkhausen, Jörg; Bayerl, Nadine; Brendlin, Andreas; Bucher, Andreas Michael; et al. (Röfo: Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, 2022)
CRIS-Team Scopus Importer:2022-08-12

Work and Training Conditions of German Residents in Radiology - Results from a Nationwide Survey Conducted by the Young Radiology Forum in the German Roentgen Society - Oechtering, Thekla H.; Panagiotopoulos, Nikolaos; Völker, Martin; Lohwasser, Stefan; Ellmann, Stephan; Molwitz, Isabel; Storz, Corinna; Winther, Hinrich; Eisenblaetter, Michel; Antoch, Gerald; Schönberg, Stefan O.; Barkhausen, Jörg; et al. (Röfo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, 2020)
Purpose Good training is the basis for high job satisfaction and high-quality patient care in radiology. The aim of this survey was to record the current state of working conditions for residents in radiology training in Germany and to focus on the aspects of training and psychosocial workload. The description of the actual state should help to identify possible problem areas and to develop improvement approaches. Materials and Methods At the beginning of 2018, we sent an electronic questionnaire to the German Roentgen Society (DRG), the German Association of Chairmen in Academic Radiology (KLR), the Chief Physician Forum of the DRG (CAFRAD) and the Forum of Registered Radiologists (FUNRAD) with the request to forward it to radiology residents. With 63 questions, the questionnaire covered seven essential areas of medical working and training conditions. In order to ensure interdisciplinary comparability, most questions were identical to previous surveys among residents of other disciplines. Results 643 residents started the survey. 501 (78 %) questionnaires were fully processed and included in the final analysis. 65 % of respondents were satisfied with their current job situation. At the same time, shortcomings, especially with regard to the reconciliation of family and work as well as scientific and clinical work, became clear. Only 36 % of participants with children were satisfied with the compatibility of family and work at their workplace. Only 31 % of the researchers were satisfied with their research conditions. In addition, residents experienced a high psychosocial workload. Conclusion Job satisfaction is high among radiology residents in direct comparison to other disciplines. However, based on this survey, adjustments to working conditions and training in radiology seem necessary to maintain the health of the physicians concerned, to encourage motivation for scientific work and to enhance development opportunities, especially for women, through a better compatibility of work and family life. The present survey identifies strategies and leadership tools that can help to achieve this. Key Points: Residents in radiology training.. have a relatively high job satisfaction. experience a high psychosocial workload. evaluate the compatibility of family and work as in need of improvement. are interested in research, but evaluate research conditions as insufficient Citation Format Oechtering TH, Panagiotopoulos N, Völker M et al. Work and Training Conditions of German Residents in Radiology - Results from a Nationwide Survey Conducted by the Young Radiology Forum in the German Roentgen Society. Fortschr Röntgenstr 2020; 192: 458 - 469
CRIS-Team Scopus Importer:2020-05-22
Keywords: continuing education; ER-ratio; psychosocial workload; radiology; resident; working conditions