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. 2025 Feb:183:111897.
doi: 10.1016/j.ejrad.2024.111897. Epub 2024 Dec 20.

Automated 24-sector grid-map algorithm for prostate mpMRI improves precision and efficacy of prostate lesion location reporting

Thula C Walter-Rittel  1 , Anne Frisch  2 , Charlie Alexander Hamm  3 , Georg Lukas Baumgärtner  4 , Alexander Hartenstein  5 , Franziska Dräger  6 , Matthias Haas  7 , Hannes Cash  8 , Sebastian Hofbauer  9 , Bernd Hamm  10 , Nick Lasse Beetz  11 , Tobias Penzkofer  12
Affiliations
Free article

Automated 24-sector grid-map algorithm for prostate mpMRI improves precision and efficacy of prostate lesion location reporting

Thula C Walter-Rittel et al. Eur J Radiol. 2025 Feb.
Free article

Abstract

Background: The Prostate Imaging-Reporting and Data System (PI-RADS) calls for reporting the prostate index lesion and the location within the transition (TZ) or peripheral zone (PZ) and location on a corresponding sector map. The aim of this study was to train a deep learning DL-based algorithm for automatic prostate sector mapping and to validate its' performance.

Methods: An automatic 24-sector grid-map (ASG) of the prostate was developed, based on an automatic zone-specific deep learning segmentation of the prostate. To evaluate the efficacy of the method, fiducials for random locations within the prostate were placed, and the corresponding sectors were determined for 50 mpMRI datasets. The reference standard was defined in a consensus read by two expert uroradiologists. Annotated fiducial locations were evaluated automatically by the ASG and by four radiologists in two reads with and without the help of a superimposed sector grid-map and the success rate was compared.

Results: The ASG algorithm identified the correct prostate sector of the annotated lesions in 80 % (40/50 reads) of the cases and outperformed readings of the four radiologists with 55 % (109/200), p < 0.0001. The added use of the 24 ASG map significantly improved the rate of correct sector annotation for the four radiologists to 71 % (141/200), p < 0.004.

Conclusion: The 24 ASG map was effective for prostate sector segmentation and significantly improved location reporting of prostate lesions.

Keywords: Deep Learning; Magnetic Resonance Imaging; Peripheral Zone (Prostate); Prostate Segmentation; Transition Zone (Prostate).

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Conflict of interest statement

Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Prof. Bernd Hamm reports grant money from companies or nonprofit organizations to the Department of Radiology (outside of submitted work) from Abbott, Actelion Pharmaceuticals, Bayer Schering Pharma, Bayer Vital, BRACCO Group, Bristol-Myers Squibb, Charité Research Organization GmbH, Krebshilfe, Stiftung für Herzforschung, Essex Pharma, EU Programmes, Fibrex Medical Inc., Focused Ultrasound Surgery Foundation, Fraunhofer Gesellschaft, Guerbet, INC Research, InSightec Ltd., IPSEN Pharma, Kendle/MorphoSys AG, Lilly GmbH, Lundbeck GmbH, MeVis Medical Solutions AG, Nexus Oncology, Novartis, Parexel CRO Service, Perceptive, Pfizer GmbH, Philipps, Sanofi-Aventis S.A, Siemens, Spectranetics GmbH, Terumo Medical Corporation, TNS Healthcare GmbH, Toshiba, UCB Pharma, Wyeth Pharma and Zukunftsfond Berlin (TSB). Prof. Tobias Penzkofer was supported by the Berlin Institute of Health (Clinician Scientist Grant, Platform Grant), Ministry of Education and Research (BMBF) and reports research agreements (no personal payments, outside of submitted work) with AGO, Aprea AB, ARCAGY-GINECO, Astellas Pharma Global Inc. (APGD), Astra Zeneca, Clovis Oncology, Inc., Dohme Corp, Holaira, Incyte Corporation, Karyopharm, Lion Biotechnologies, Inc., MedImmune, Merck Sharp, Millennium Pharmaceuticals, Inc., Morphotec Inc., NovoCure Ltd., PharmaMar S.A. and PharmaMar USA, Inc., Roche, Siemens Healthineers, and TESARO Inc. and fees for a book translation (Elsevier). Dr. Nick Lasse Beetz and Dr. Charlie Hamm are participants of the BIH Charité Junior Clinician Scientist Program funded by Charité – Universitätsmedizin Berlin and the Berlin Institute of Health at Charité (BIH). Dr. Thula Walter-Rittel reports payments from Bayer Vital and Novartis Pharmaceuticals and Astellas Pharmaceuticals outside the current scope of this paper. Anne Frisch, Franziska Dräger, Matthias Haas, Lukas Baumgärtner, Alexander Hartenstein, Hannes Cash, and Sebastian Hofbauer declare that they have no conflicts of interest.

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