Deep Learning for Cancer Prognosis Prediction Using Portrait Photos by StyleGAN Embedding - Hagag, Amr; Gomaa, Ahmed; Kornek, Dominik; Maier, Andreas; Fietkau, Rainer; Bert, Christoph; Huang, Yixing; Putz, Florian (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2024)
Survival prediction for cancer patients is critical for optimal treatment selection and patient management. Current patient survival prediction methods typically extract survival information from patients’ clinical record data or biological and imaging data. In practice, experienced clinicians can have a preliminary assessment of patients’ health status based on patients’ observable physical appearances, which are mainly facial features. However, such assessment is highly subjective. In this work, the efficacy of objectively capturing and using prognostic information contained in conventional portrait photographs using deep learning for survival prediction purposes is investigated for the first time. A pre-trained StyleGAN2 model is fine-tuned on a custom dataset of our cancer patients’ photos to empower its generator with generative ability suitable for patients’ photos. The StyleGAN2 is then used to embed the photographs to its highly expressive latent space. Utilizing state-of-the-art survival analysis models and StyleGAN’s latent space embeddings, this approach predicts the overall survival for single as well as pan-cancer, achieving a C-index of 0.680 in a pan-cancer analysis, showcasing the prognostic value embedded in simple 2D facial images. In addition, thanks to StyleGAN’s interpretable latent space, our survival prediction model can be validated for relying on essential facial features, eliminating any biases from extraneous information like clothing or background. Moreover, our approach provides a novel health attribute obtained from StyleGAN’s extracted features, allowing the modification of face photographs to either a healthier or more severe illness appearance, which has significant prognostic value for patient care and societal perception, underscoring its potential important clinical value.
CRIS-Team Scopus Importer:2024-10-25
Keywords: cancer; deep learning; explainable AI; face prognosis; latent space; StyleGAN; Survival prediction

Development and clinical implementation of a digital system for risk assessments for radiation therapy - Kornek, Dominik; Menichelli, David; Leske, Jörg; Hofmann, Michael; Antkiewicz, David; Brandt, Tobias; Ott, Oliver; Lotter, Michael; Lang-Welzenbach, Marga; Fietkau, Rainer; Bert, Christoph (Zeitschrift für Medizinische Physik, 2023)
Before introducing new treatment techniques, an investigation of hazards due to unintentional radiation exposures is a reasonable activity for proactively increasing patient safety. As dedicated software is scarce, we developed a tool for risk assessment to design a quality management program based on best practice methods, i.e., process mapping, failure modes and effects analysis and fault tree analysis. Implemented as a web database application, a single dataset was used to describe the treatment process and its failure modes. The design of the system and dataset allowed failure modes to be represented both visually as fault trees and in a tabular form. Following the commissioning of the software for our department, previously conducted risk assessments were migrated to the new system after being fully re-assessed which revealed a shift in risk priorities. Furthermore, a weighting factor was investigated to bring risk levels of the migrated assessments into perspective. The compensation did not affect high priorities but did re-prioritize in the midrange of the ranking. We conclude that the tool is suitable to conduct multiple risk assessments and concomitantly keep track of the overall quality management activities.
CRIS-Team Scopus Importer:2023-09-15
Keywords: Failure modes and effects analysis (FMEA); Fault tree analysis (FTA); Process throughput; Radiation therapy; Risk analysis; Risk-based quality management

Improving the safety of radiotherapy treatment processes via incident-driven FMEA feedback loops - Kornek, Dominik; Lotter, Michael; Szkitsak, Juliane; Dürrbeck, Christopher; Karius, Andre; Ott, Oliver; Brandl, Carolin; Bert, Christoph (Journal of Applied Clinical Medical Physics, 2024)
Background: Failure mode and effects analysis (FMEA) is a valuable tool for radiotherapy risk assessment, yet its outputs might be unreliable due to failures not being identified or due to a lack of accurate error rates. Purpose: A novel incident reporting system (IRS) linked to an FMEA database was tested and evaluated. The study investigated whether the system was suitable for validating a previously performed analysis and whether it could provide accurate error rates to support the expert occurrence ratings of previously identified failure modes. Methods: Twenty-three pre-identified failure modes of our external beam radiotherapy process, covering the process steps from patient admission to treatment delivery, were proffered on dedicated FMEA feedback and incident reporting terminals generated by the IRS. The clinical setting involved a computed tomography scanner, dosimetry, and five linacs. Incoming reports were used as basis to identify additional failure modes or confirm initial ones. The Kruskal–Wallis H test was applied to compare the risk priorities of the retrospective and prospective failure modes. Wald's sequential probability ratio test was used to investigate the correctness of the experts’ occurrence ratings by means of the number of incoming reports. Results: Over a 15-month period, 304 reports were submitted. There were 0.005 (confidence interval [CI], 0.0014–0.0082) reported incidents per imaging study and 0.0006 (CI, 0.0003–0.0009) reported incidents per treatment fraction. Sixteen additional failure modes could be identified, and their risk priorities did not differ from those of the initial failure modes (p = 0.954). One failure mode occurrence rating could be increased, whereas the other 22 occurrence ratings could not be disproved. Conclusions: Our approach is suitable for validating FMEAs and deducing additional failure modes on a continual basis. Accurate error rates can only be provided if a sufficient number of reports is available.
CRIS-Team Scopus Importer:2024-08-23
Keywords: error rates; failure mode and effects analysis (FMEA); incident reporting system (IRS); radiotherapy; risk assessment

Process failure mode and effects analysis for external beam radiotherapy: Introducing a literature-based template and a novel action priority - Kornek, Dominik; Bert, Christoph (Zeitschrift für Medizinische Physik, 2024)
Purpose: The first aim of the study was to create a general template for analyzing potential failures in external beam radiotherapy, EBRT, using the process failure mode and effects analysis (PFMEA). The second aim was to modify the action priority (AP), a novel prioritization method originally introduced by the Automotive Industry Action Group (AIAG), to work with different severity, occurrence, and detection rating systems used in radiation oncology. Methods and materials: The AIAG PFMEA approach was employed in combination with an extensive literature survey to develop the EBRT-PFMEA template. Subsets of high-risk failure modes found through the literature survey were added to the template where applicable. Our modified AP for radiation oncology (RO AP) was defined using a weighted sum of severity, occurrence, and detectability. Then, Monte Carlo simulations were conducted to compare the original AIAG AP, the RO AP, and the risk priority number (RPN). The results of the simulations were used to determine the number of additional corrective actions per failure mode and to parametrize the RO AP to our department's rating system. Results: An EBRT-PFMEA template comprising 75 high-risk failure modes could be compiled. The AIAG AP required 1.7 additional corrective actions per failure mode, while the RO AP ranged from 1.3 to 3.5, and the RPN required 3.6. The RO AP could be parametrized so that it suited our rating system and evaluated severity, occurrence, and detection ratings equally to the AIAG AP. Conclusions: An adjustable EBRT-PFMEA template is provided which can be used as a practical starting point for creating institution-specific templates. Moreover, the RO AP introduces transparent action levels that can be adapted to any rating system.
CRIS-Team Scopus Importer:2024-03-29
Keywords: Action priority (AP); External beam radiation therapy (EBRT); Process failure mode and effects analysis (PFMEA); Prospective risk assessment; Template

Reporting and Evaluation System for Incidents in the Radiation Therapy to increase Patient Safety, Treatment Quality and the Efficiency of Process Flows - Kornek, Dominik; Lang-Welzenbach, Marga; Beck, A.; Reinhardt, A.; Brandt, Tobias; Bert, Christoph (STRAHLENTHERAPIE UND ONKOLOGIE, 2022)
CRIS-Team WoS Importer:2022-06-03

Systematizing the risk management process in clinical radiotherapy practice: Recommendations of the working group on risk management of the DGMP - Kornek, Dominik; Hoinkis, Cordelia; Milickovic, Natasa; Lange, Ailine; Knak, Alena; März, Manuel; Möller, Mieke L.; Buchgeister, Markus (Zeitschrift für Medizinische Physik, 2024)
Purpose: The Deutsche Gesellschaft für Medizinische Physik [German Society of Medical Physics] has recently published two coherent reports, No. 25 and No. 28, detailing the design and implementation of a risk management (RM) process for German radiotherapy (RT) departments. This study offers an overview and background of the efforts behind these reports. Methods and Materials: For three years, up to nine medical physicists (MPs) with practical RM experience held weekly meetings to develop recommendations for a clinical RM process. Care was taken to ensure that the recommendations were equally applicable to RT departments of various sizes. A process-based method derived from the failure mode and effects analysis (FMEA) was created to identify and address risks from unintentional radiation exposure. This method was applied to exemplarily analyze the hazardous scenarios in breast RT using surface guidance and deep inspiration breath hold (DIBH) techniques. Three common criticality methods—risk matrix, risk priority number, and action priority—were applied, and each step was schematically explained for first-time users. Each report was peer-reviewed by two radiation oncologists and 11 MPs. Results: In report No. 25, basic requirements were outlined for running the RM process, conducting risk assessments, and monitoring clinical procedures. A three-year plan-do-check-act cycle was proposed for continuous improvement. In report No. 28, general process lists for external beam radiotherapy (EBRT), brachytherapy, and radionuclide therapy were designed. Based on the EBRT process list, 45 hazardous scenarios in the surface-guided breast RT in DIBH were identified. Two scenarios were used to illustrate handling instructions for the three criticality methods. Conclusions: The recommendations provide clinical MPs and other health professionals with a pragmatic approach to RM, balancing both the needs of smaller practices and larger clinics in Germany. The risk of unintended exposures of patients is viewed acceptable once it has been lowered to a state that is as low as reasonably achievable.
CRIS-Team Scopus Importer:2025-02-04
Keywords: Best practice; FMEA; Patient safety; Radiotherapy; Risk management