99mTc-MIP-1404 SPECT/CT for Patients With Metastatic Prostate Cancer: Interobserver and Intraobserver Variability in Treatment-Related Longitudinal Tracer Uptake Assessments of Prostate-Specific Membrane Antigen-Positive Lesions - Schmidkonz, Christian; Atzinger, Armin; Götz, Theresa; Beck, Michael; Ritt, Philipp; Prante, Olaf; Kuwert, Torsten; Bäuerle, Tobias; Cordes, Michael (Clinical Nuclear Medicine, 2020)
BACKGROUND: Tc-MIP-1404 is a SPECT-suitable prostate-specific membrane antigen (PSMA) ligand for detection of prostate cancer. In patients with metastatic prostate cancer, there are no data as yet on interobserver and intraobserver variability when assessing PSMA-positive lesions for longitudinal changes of tracer uptake. METHODS: Tc-MIP-1404 SPECT/CT scans of 22 patients with metastatic prostate cancer were analyzed, and each subject was imaged at 2 separate points in time, before and after treatment. Mean interval between scans was 10 months. Three independent observers visually assessed a total of 96 PSMA-positive metastases (bone, 69; lymph node, 22; viscera, 3) or local recurrences (n = 2) for longitudinal changes in tracer uptake on planar scintigraphy and SPECT/CT. All lesions were categorized as regressive, stable, or progressive based on visual findings and on peak SUV (SUVpeak) of quantitative SPECT/CT (progressive, >30% SUVpeak increase; regressive, <30% SUVpeak decrease; or stable, all others). RESULTS: Quantitative analysis of PSMA-positive lesions yielded significantly higher interobserver agreement (90.6%; 95% confidence interval [CI], 0.83%-0.96%) than visual assessments by either SPECT/CT (76.0%; 95% CI, 0.66%-0.84%) or planar scintigraphy (56.3%; 95% CI, 0.46%-0.66%). Intermethod comparison of aggregated results yielded significantly higher agreement between quantitative and visual SPECT/CT (85.1%; 95% CI, 0.80%-0.89%), as opposed to quantitative SPECT/CT and planar scintigraphy (53.1%; 95% CI, 0.47%-0.59%) or visual SPECT/CT and planar scintigraphy (54.9%; 95% CI, 0.49%-0.61%). In visual and quantitative analysis of 96 PSMA-positive lesions, the number of discrepancies ranged from 9 (9.4%) for quantitative SPECT/CT to 42 (43.8%) for planar scintigraphy. Overall reader confidence was higher for SPECT/CT than for planar scintigraphy (P < 0.001). Intraobserver agreement was near-perfect for all methods, whether SPECT/CT (visual, all κ = 0.94-0.97; quantitative κ = 0.94-0.98) or planar scintigraphy (all κ = 0.90-0.94). CONCLUSIONS: Quantitative evaluation of longitudinal change in tracer uptake by PSMA-positive lesions measured via SPECT/CT is superior to visual interpretation of images by planar scintigraphy or SPECT/CT. Compared with visual evaluation, quantitative SPECT/CT is highly reproducible, showing near-perfect agreement among observers and higher reader confidence.
CRIS-Team Scopus Importer:2020-01-14

99m Tc-MIP-1404-SPECT/CT for the detection of PSMA-positive lesions in 225 patients with biochemical recurrence of prostate cancer - Schmidkonz, Christian; Hollweg, Claudia; Beck, Michael; Reinfelder, Julia; Götz, Theresa; Sanders, James Chester; Schmidt, Daniela; Prante, Olaf; Bäuerle, Tobias; Uder, Michael; Wullich, Bernd; Goebell, Peter; et al. (Prostate, 2018)
99m Tc-MIP-1404 (Progenics Pharmaceuticals, Inc., New York, NY) is a novel, SPECT-compatible 99m Tc-labeled PSMA inhibitor for the detection of prostate cancer. We present results of its clinical use in a cohort of 225 men with histologically confirmed prostate cancer referred for workup of biochemical relapse.From April 2013 to April 2017, 99m Tc-MIP1404-scintigraphy was performed in 225 patients for workup of PSA biochemical relapse of prostate cancer. Whole-body planar and SPECT/CT images of the lower abdomen and thorax were obtained 3-4 h p.i. of 710 ± 64 MBq 99m Tc-MIP-1404. Images were visually analyzed for presence and location of abnormal uptake. In addition, quantitative analysis of the SPECT/CT data was carried out on a subset of 125 patients. Follow-up reports of subsequent therapeutic interventions were available for 59% (139) of all patients.Tracer-positive lesions were detected in 77% (174/225) of all patients. Detections occurred at the area of local recurrence in the prostate in 25% of patients (or a total of 56), with metastases in lymph nodes in 47% (105), bone in 27% (60), lung in 5% (12), and other locations in 2% (4) of patients. Detection rates were 90% at PSA levels >=2 ng/mL and 54% below that threshold. Lesional SUVmax values were, on average, 32.2 ± 29.6 (0.8-142.2), and tumor-to-normal ratios 146.6 ± 160.5 (1.9-1482.4). The PSA level correlated significantly with total uptake of MIP-1404 in tumors (P < 0.001). Furthermore, total tumor uptake was significantly higher in patients with Gleason scores >=8 compared to those with Gleason scores <=7 (P < 0.05). In patients with androgen deprivation therapy, the detection rate was significantly higher compared to patients without androgen deprivation therapy (86% vs 71%, P < 0.001). Based on 99m Tc-MIP-1404-imaging and other information, an interdisciplinary tumor board review recommended changes to treatment plans in 74% (104/139) of those patients for whom the necessary documentation was available.SPECT/CT with 99m Tc-labeled MIP-1404 has a high probability in detecting PSMA-positive lesions in patients with elevated PSA. Statistical analysis disclosed significant relationship between quantitative 99m Tc-MIP-1404 uptake, PSA level, and Gleason score.
EVALuna2:13874

A comparison of methods for adapting 177Lu dose-voxel-kernels to tissue inhomogeneities - Götz, Theresa; Schmidkonz, Christian; Lang, E. W.; Maier, Andreas; Kuwert, Torsten; Ritt, Philipp (Physics in Medicine and Biology, 2019)
In 177Lu radionuclide therapies, dosimetry is used for determining patient-individual dose burden. Standard approaches provide whole organ doses only. For assessing dose heterogeneity inside organs, voxel-wise dosimetry based on 3D SPECT/CT imaging could be applied. Often, this is achieved by convolving voxel-wise time-activity-curves with appropriate dose-voxel-kernels (DVK). The DVKs are meant to model dose deposition, and can be more accurate if modelled for the specific tissue type under consideration. In literature, DVKs are often not adapted to these inhomogeneities, or simple approximation schemes are applied. For 26 patients, which had previously undergone a 177Lu-PSMA or -DOTATOC therapy, decay maps, mass-density maps as well as tissue-type maps were derived from SPECT/CT acquisitions. These were used for a voxel-based dosimetry based on convolution with DVKs (each of size (4.8mm)3) obtained by four different DVK methods proposed in literature. The simplest only considers a spatially constant soft-tissue DVK (herein named 'constant'), while others either take into account only the local density of the center voxel of the DVK (herein named 'center-voxel') or scale each voxel linearly according to the proper mass density deduced from the CT image (herein named 'density') or considered both the local mass density as well as the direct path between the center voxel and any voxel in its surrounding (herein named 'percentage'). Deviations between resulting dose values and those from full Monte-Carlo simulations (MC simulations) were compared for selected organs and tissue-types. For each DVK method, inter-patient variability was considerable showing both under- and over-estimation of energy dose compared to the MC result for all tissue densities higher than soft tissue. In kidneys and spleen, 'constant' and 'density'-scaled DVKs achieved estimated doses with smallest deviations to the full MC gold standard (∼5%-8% underestimation). For low and high density tissue types such as lung and adipose or bone tissue, alternative DVK methods like 'center-voxel'- and 'percentage'- scaled achieved superior results, respectively. Concerning computational load, dose estimation with the DVK method 'constant' needs about 1.1 s per patient, center-voxel scaling amounts to 1.2 s, density scaling needs 1.4 s while percentage scaling consumes 860.3 s per patient. In this study encompassing a large patient cohort and four different DVK estimation methods, no single DVK-adaption method was consistently better than any other in case of soft tissue kernels. Hence in such cases the simplest DVK method, labeled 'constant', suffices. In case of tumors, often located in tissues of low (lung) or high (bone) density, more sophisticated DVK methods excel. The high inter-patient variability indicates that for evaluating new algorithms, a sufficiently large patient cohort needs to be involved.
CRIS-Team Scopus Importer:2020-02-21
Keywords: dose-voxel-kernel; dosimetry; SPECT/CT

A deep learning approach to radiation dose estimation - Götz, Theresa; Schmidkonz, Christian; Chen, Shuqing; Al-Baddai, S.; Kuwert, Torsten; Lang, E. W. (Physics in Medicine and Biology, 2020)
Currently methods for predicting absorbed dose after administering a radiopharmaceutical are rather crude in daily clinical practice. Most importantly, individual tissue density distributions as well as local variations of the concentration of the radiopharmaceutical are commonly neglected. The current study proposes machine learning techniques like Green's function-based empirical mode decomposition and deep learning methods on U-net architectures in conjunction with soft tissue kernel Monte Carlo (MC) simulations to overcome current limitations in precision and reliability of dose estimations for clinical dosimetric applications. We present a hybrid method (DNN-EMD) based on deep neural networks (DNN) in combination with empirical mode decomposition (EMD) techniques. The algorithm receives x-ray computed tomography (CT) tissue density maps and dose maps, estimated according to the MIRD protocol, i.e. employing whole organ S-values and related time-integrated activities (TIAs), and from measured SPECT distributions of 177Lu radionuclei, and learns to predict individual absorbed dose distributions. In a second step, density maps are replaced by their intrinsic modes as deduced from an EMD analysis. The system is trained using individual full MC simulation results as reference. Data from a patient cohort of 26 subjects are reported in this study. The proposed methods were validated employing a leave-one-out cross-validation technique. Deviations of estimated dose from corresponding MC results corroborate a superior performance of the newly proposed hybrid DNN-EMD method compared to its related MIRD DVK dose calculation. Not only are the mean deviations much smaller with the new method, but also the related variances are much reduced. If intrinsic modes of the tissue density maps are input to the algorithm, variances become even further reduced though the mean deviations are less affected. The newly proposed hybrid DNN-EMD method for individualized radiation dose prediction outperforms the MIRD DVK dose calculation method. It is fast enough to be of use in daily clinical practice.
CRIS-Team Scopus Importer:2020-02-14

A novel Slide-seq based image processing software to identify gene expression at the single cell level - Götz, Theresa; Cong, X.; Rauber, Simon; Angeli, Mario Raphael; Lang, E. W.; Ramming, Alina; Schmidkonz, Christian (Journal of Pathology Informatics, 2024)
Analysis of gene expression at the single-cell level could help predict the effectiveness of therapies in the field of chronic inflammatory diseases such as arthritis. Here, we demonstrate an adopted approach for processing images from the Slide-seq method. Using a puck, which consists of about 50,000 DNA barcode beads, an RNA sequence of a cell is to be read. The pucks are repeatedly brought into contact with liquids and then recorded with a conventional epifluorescence microscope. The image analysis initially consists of stitching the partial images of a sequence recording, registering images from different sequences, and finally reading out the bases. The new method enables the use of an inexpensive epifluorescence microscope instead of a confocal microscope.
CRIS-Team Scopus Importer:2024-06-28
Keywords: Cell segmentation; Deep neural networks; DNN complexity; Pruning; Slide-seq

Correction to: Assessment of treatment responses in children and adolescents with Ewing sarcoma with metabolic tumor parameters derived from 18F-FDG-PET/CT and circulating tumor DNA (European Journal of Nuclear Medicine and Molecular Imaging, (2019), 10.1007/s00259-019-04649-1) - Schmidkonz, Christian; Krumbholz, Manuela; Atzinger, Armin; Cordes, Michael; Götz, Theresa; Prante, Olaf; Ritt, Philipp; Schaefer, Christiane; Agaimy, Abbas; Hartmann, Wolfgang; Roessig, Claudia; Froehlich, Birgit; et al. (European Journal of Nuclear Medicine and Molecular Imaging, 2020)
The original version on this paper contained an error. The author names, though correctly appeared in the PDF version, were incorrectly displayed in indexing sites. This error occurred because of the incorrect tagging of their names in themetadata of this article. The purpose of this Erratum is the correction of metadata. Therefore, indexing sites should now reflect their names as Schmidkonz C, Krumbholz M, Atzinger A, Cordes M, Goetz TI, Prante O, Ritt P, Schaefer C, Agaimy A, Hartmann W, Rössig C, Fröhlich B, Bäuerle T, Dirksen U, Kuwert T, Metzler M. The original article has been corrected.
CRIS-Team Scopus Importer:2020-02-25

Influence of Photon Count-Level on Semi-Automatic Image Assessment in Myocardial Perfusion Imaging - Sanders, James Chester; Wetzl, Matthias; Götz, Theresa; Kuwert, Torsten; Ritt, Philipp (2018)
EVALuna2:212304

Large-Scale Graph Networks and AI Applied to Medical Image Data Processing - Meyer-Baese, Anke; Foo, Simon; Tahmassebi, Amirhessam; Meyer-Baese, Uwe; Amani, Ali Moradi; Götz, Theresa; Leithner, Doris; Stadlbauer, Andreas; Pinker-Domenig, Katja (COMPUTATIONAL IMAGING V, 2020)
CRIS-Team WoS Importer:2021-07-30

Monte-Carlo Simulation and Experimental Validation of a Gamma-Camera Prototype Featuring a Novel Collimation Technique - Meinderink, T.; Osterloh, P.; Osterloh, K.; Götz, Theresa; Kuwert, Torsten; Ritt, Philipp (2018)
EVALuna2:212303

Particle filter de-noising of voxel-specific time-activity-curves in personalized 177Lu therapy - Götz, Theresa; Götz, Th I.; Lang, E. W.; Schmidkonz, Christian; Maier, Andreas; Kuwert, Torsten; Ritt, Philipp (Zeitschrift für Medizinische Physik, 2019)
Background: Currently, there is a high interest in 177Lu targeted radionuclide therapies, which could be attributed to favorable results obtained from 177Lu compounds targeting neuro-endocrine and prostate tumors. SPECT based dosimetry could be used for deriving dose values for individual voxels, as is the standard in external-beam radiation-therapy (EBRT). For this a time-activity-curve (TAC) at voxel resolution and also a voxel-wise modeling of radiation energy deposition are necessary. But a voxel-wise determination of TACs is problematic, since several confounding factors exist, such as e.g. poor count-statistics or registration inaccuracies, which add noise to the observed activity states. A particle filter (PF) is a class of methods which applies regularization based on a model of the temporal evolution of activity states. The aim of this study is to introduce the application of PFs for de-noising of per-voxel time-activity curves. Methods: We applied a PF for de-noising the TACs of 26 patients, who underwent 177Lu-DOTATOC or -PSMA therapy. The TACs were obtained from fully-quantitative, serial SPECT(/CT) data, acquired at 4 h, 24 h, 48 h, 72 h p.i. The model used in the PF was a mono-exponential decay and its free parameters were determined based on objective criteria. The time-integrated activities (TIA) resulting from the PF (PFF) were compared to the results of a mono-exponential fit (SF) of individual voxels in several volumes of interest (kidneys, spleen, tumors). Additionally, an organ-averaged TIA was derived from whole-organ VOIs and subsequent curve-fitting. This whole-organ TIA was also compared to the whole-organ TIAs obtained from summation of the voxel-wise TIAs from PFF and SF. Results: The number of particles was set to 1000. Optimal values for noise of observations and noise of the model were 0.25 and 0.5, respectively. The deviation of whole-organ TIAs from conventional organ-based dosimetry and the summation of the voxel-wise TIAs was substantial for SF (kidneys −22.3%, spleen −49.6%, tumor −60.0%), as well as for PFF (kidneys −37.1%, spleen −57.9%, tumor −70.9%). The distribution of voxel-wise half-lives resulting from the PFF method was considerably closer to the organ-averaged value, and the number of implausibly long half-lives (>physical HL) was reduced. Conclusion: The PFF leads to voxel-wise half-lives, which are more plausible than those resulting from SF. However, one has to admit that voxel-wise fitting generally leads to considerable deviations from the organ-averaged TIA as obtained by conventional whole-organ evaluation. Unfortunately, we did not have ground-truth TIA of our patient data and proper ground-truth could even be impossible to obtain. Nevertheless, there are strong indicators that particle filtering can be used for reducing voxel-wise TAC noise.
CRIS-Team Scopus Importer:2019-12-27
Keywords: Dosimetry; Nuclear medicine; Time-activity-curve; Voxelwise

PSMA SPECT/CT with 99mTc-MIP-1404 in biochemical recurrence of prostate cancer: predictive factors and efficacy for the detection of PSMA-positive lesions at low and very-low PSA levels - Schmidkonz, Christian; Götz, Theresa; Kuwert, Torsten; Ritt, Philipp; Prante, Olaf; Bäuerle, Tobias; Goebell, Peter; Cordes, Michael (Annals of Nuclear Medicine, 2019)
Background: The in vivo expression of the prostate-specific membrane antigen (PSMA) can be investigated using the SPECT-suitable tracer 99mTc-MIP-1404. We investigated the performance of 99mTc-MIP-1404 PSMA SPECT/CT in the detection of PSMA-positive tumor lesions in patients suffering from biochemical recurrence of prostate cancer presenting with serum levels of the prostate-specific antigen (PSA) below 1 ng/mL. Methods: We retrospectively analyzed 99mTc-MIP-1404-SPECT/CT scans of 50 patients (25 with low PSA levels between > 0.5 and 1 ng/mL and 25 with very low PSA levels between 0.2 and 0.5 ng/mL) that had undergone whole-body planar scintigraphy and SPECT/CT of the thorax, abdomen and pelvis 3–4 h p.i. of 691 ± 72 MBq 99mTc-MIP-1404. All datasets were evaluated for the presence and location of PSMA-positive tumor lesions, in which maximal standardized uptake values (SUVmax) were also measured. Based on the results of the quantitative evaluation as well as on biochemical and histological parameters, predictive factors for a positive 99mTc-MIP-1404 scan result were determined. The influence of 99mTc-MIP-1404 PSMA SPECT/CT on further therapy planning was assessed, based on the decision-making of the interdisciplinary tumor board. Results: Pathological 99mTc-MIP-1404 uptake was detected in a total of 25 patients (50%). In the very low PSA subgroup, detection rates of PSMA-positive lesions suggestive of tumor recurrence were 44%, in the low-PSA subgroup 56%. Gleason scores ≥ 8 and the presence of antiandrogen deprivation therapy were further significant predictors of pathological 99mTc-MIP-1404 uptake. This was paralleled by significantly higher lesional SUVmax patients with PSA levels > 0.5 ng/mL and Gleason scores ≥ 8 compared to those without these two features. Changes in therapeutic strategy following MIP-1404 imaging were recommended by the interdisciplinary tumor board in 25/50 of patients. Conclusion: 99mTc-MIP-1404 PSMA-SPECT/CT demonstrated a high performance in detecting PSMA-positive lesions suggestive of tumor recurrence in patients with biochemical recurrence of prostate cancer and low and very low serum PSA levels. Results from MIP-1404 PSMA SPECT/CT have therapeutic impact in one-half of the patients examined by this technology.
CRIS-Team Scopus Importer:2019-10-29
Keywords: Low PSA levels; MIP-1404; Prostate cancer; PSMA; Quantitative SPECT/CT; SPECT/CT