Sarah Montagne1,2,3, Dimitri Hamzaoui4, Alexandre Allera5, Malek Ezziane5, Anna Luzurier5, Raphaelle Quint5, Mehdi Kalai5, Nicholas Ayache4, Hervé Delingette4, Raphaële Renard-Penna5,6,7. 1. Academic Department of Radiology, Hôpital Pitié-Salpétrière, Assistance Publique des Hôpitaux de Paris, Paris, France. sarah.montagne@aphp.fr. 2. Academic Department of Radiology, Hôpital Tenon, Assistance Publique des Hôpitaux de Paris, Paris, France. sarah.montagne@aphp.fr. 3. Sorbonne Universités, GRC n° 5, Oncotype-Uro, Paris, France. sarah.montagne@aphp.fr. 4. Inria, Epione Team, Université Côte D'Azur, Sophia Antipolis, Nice, France. 5. Academic Department of Radiology, Hôpital Pitié-Salpétrière, Assistance Publique des Hôpitaux de Paris, Paris, France. 6. Academic Department of Radiology, Hôpital Tenon, Assistance Publique des Hôpitaux de Paris, Paris, France. 7. Sorbonne Universités, GRC n° 5, Oncotype-Uro, Paris, France.
Abstract
BACKGROUND: Accurate prostate zonal segmentation on magnetic resonance images (MRI) is a critical prerequisite for automated prostate cancer detection. We aimed to assess the variability of manual prostate zonal segmentation by radiologists on T2-weighted (T2W) images, and to study factors that may influence it. METHODS: Seven radiologists of varying levels of experience segmented the whole prostate gland (WG) and the transition zone (TZ) on 40 axial T2W prostate MRI images (3D T2W images for all patients, and both 3D and 2D images for a subgroup of 12 patients). Segmentation variabilities were evaluated based on: anatomical and morphological variation of the prostate (volume, retro-urethral lobe, intensity contrast between zones, presence of a PI-RADS ≥ 3 lesion), variation in image acquisition (3D vs 2D T2W images), and reader's experience. Several metrics including Dice Score (DSC) and Hausdorff Distance were used to evaluate differences, with both a pairwise and a consensus (STAPLE reference) comparison. RESULTS: DSC was 0.92 (± 0.02) and 0.94 (± 0.03) for WG, 0.88 (± 0.05) and 0.91 (± 0.05) for TZ respectively with pairwise comparison and consensus reference. Variability was significantly (p < 0.05) lower for the mid-gland (DSC 0.95 (± 0.02)), higher for the apex (0.90 (± 0.06)) and the base (0.87 (± 0.06)), and higher for smaller prostates (p < 0.001) and when contrast between zones was low (p < 0.05). Impact of the other studied factors was non-significant. CONCLUSIONS: Variability is higher in the extreme parts of the gland, is influenced by changes in prostate morphology (volume, zone intensity ratio), and is relatively unaffected by the radiologist's level of expertise.
BACKGROUND: Accurate prostate zonal segmentation on magnetic resonance images (MRI) is a critical prerequisite for automated prostate cancer detection. We aimed to assess the variability of manual prostate zonal segmentation by radiologists on T2-weighted (T2W) images, and to study factors that may influence it. METHODS: Seven radiologists of varying levels of experience segmented the whole prostate gland (WG) and the transition zone (TZ) on 40 axial T2W prostate MRI images (3D T2W images for all patients, and both 3D and 2D images for a subgroup of 12 patients). Segmentation variabilities were evaluated based on: anatomical and morphological variation of the prostate (volume, retro-urethral lobe, intensity contrast between zones, presence of a PI-RADS ≥ 3 lesion), variation in image acquisition (3D vs 2D T2W images), and reader's experience. Several metrics including Dice Score (DSC) and Hausdorff Distance were used to evaluate differences, with both a pairwise and a consensus (STAPLE reference) comparison. RESULTS: DSC was 0.92 (± 0.02) and 0.94 (± 0.03) for WG, 0.88 (± 0.05) and 0.91 (± 0.05) for TZ respectively with pairwise comparison and consensus reference. Variability was significantly (p < 0.05) lower for the mid-gland (DSC 0.95 (± 0.02)), higher for the apex (0.90 (± 0.06)) and the base (0.87 (± 0.06)), and higher for smaller prostates (p < 0.001) and when contrast between zones was low (p < 0.05). Impact of the other studied factors was non-significant. CONCLUSIONS: Variability is higher in the extreme parts of the gland, is influenced by changes in prostate morphology (volume, zone intensity ratio), and is relatively unaffected by the radiologist's level of expertise.
Entities:
Keywords:
Atlas; MRI; Prostate; Segmentation; Zones
Authors: Anne Sofie Korsager; Valerio Fortunati; Fedde van der Lijn; Jesper Carl; Wiro Niessen; Lasse Riis Østergaard; Theo van Walsum Journal: Med Phys Date: 2015-04 Impact factor: 4.071
Authors: F Rozet; C Hennequin; J-B Beauval; P Beuzeboc; L Cormier; G Fromont; P Mongiat-Artus; A Ouzzane; G Ploussard; D Azria; I Brenot-Rossi; G Cancel-Tassin; O Cussenot; T Lebret; X Rebillard; M Soulié; R Renard-Penna; A Méjean Journal: Prog Urol Date: 2016-11 Impact factor: 0.915
Authors: Geert Litjens; Robert Toth; Wendy van de Ven; Caroline Hoeks; Sjoerd Kerkstra; Bram van Ginneken; Graham Vincent; Gwenael Guillard; Neil Birbeck; Jindang Zhang; Robin Strand; Filip Malmberg; Yangming Ou; Christos Davatzikos; Matthias Kirschner; Florian Jung; Jing Yuan; Wu Qiu; Qinquan Gao; Philip Eddie Edwards; Bianca Maan; Ferdinand van der Heijden; Soumya Ghose; Jhimli Mitra; Jason Dowling; Dean Barratt; Henkjan Huisman; Anant Madabhushi Journal: Med Image Anal Date: 2013-12-25 Impact factor: 8.545
Authors: F Rozet; P Mongiat-Artus; C Hennequin; J B Beauval; P Beuzeboc; L Cormier; G Fromont-Hankard; R Mathieu; G Ploussard; R Renard-Penna; I Brenot-Rossi; F Bruyere; A Cochet; G Crehange; O Cussenot; T Lebret; X Rebillard; M Soulié; L Brureau; A Méjean Journal: Prog Urol Date: 2020-11 Impact factor: 0.915
Authors: Jeffrey C Weinreb; Jelle O Barentsz; Peter L Choyke; Francois Cornud; Masoom A Haider; Katarzyna J Macura; Daniel Margolis; Mitchell D Schnall; Faina Shtern; Clare M Tempany; Harriet C Thoeny; Sadna Verma Journal: Eur Urol Date: 2015-10-01 Impact factor: 20.096
Authors: Nicolas Mottet; Joaquim Bellmunt; Michel Bolla; Erik Briers; Marcus G Cumberbatch; Maria De Santis; Nicola Fossati; Tobias Gross; Ann M Henry; Steven Joniau; Thomas B Lam; Malcolm D Mason; Vsevolod B Matveev; Paul C Moldovan; Roderick C N van den Bergh; Thomas Van den Broeck; Henk G van der Poel; Theo H van der Kwast; Olivier Rouvière; Ivo G Schoots; Thomas Wiegel; Philip Cornford Journal: Eur Urol Date: 2016-08-25 Impact factor: 20.096
Authors: Baris Turkbey; Andrew B Rosenkrantz; Masoom A Haider; Anwar R Padhani; Geert Villeirs; Katarzyna J Macura; Clare M Tempany; Peter L Choyke; Francois Cornud; Daniel J Margolis; Harriet C Thoeny; Sadhna Verma; Jelle Barentsz; Jeffrey C Weinreb Journal: Eur Urol Date: 2019-03-18 Impact factor: 20.096
Authors: Nandita M deSouza; Aad van der Lugt; Christophe M Deroose; Angel Alberich-Bayarri; Luc Bidaut; Laure Fournier; Lena Costaridou; Daniela E Oprea-Lager; Elmar Kotter; Marion Smits; Marius E Mayerhoefer; Ronald Boellaard; Anna Caroli; Lioe-Fee de Geus-Oei; Wolfgang G Kunz; Edwin H Oei; Frederic Lecouvet; Manuela Franca; Christian Loewe; Egesta Lopci; Caroline Caramella; Anders Persson; Xavier Golay; Marc Dewey; James P B O'Connor; Pim deGraaf; Sergios Gatidis; Gudrun Zahlmann Journal: Insights Imaging Date: 2022-10-04