AIM: Reliable post-implant evaluation of prostate seed implants requires optimal seed identification and accurate delineation of anatomical structures. In this study the GEC-ESTRO groups BRAPHYQS and PROBATE investigated the interobserver variability in post-implant prostate contouring, seed reconstruction and image fusion and its impact on the dose-volume parameters. MATERIALS: Post-implant T2-TSE, T1-GE and CT images were acquired for three patients, in order to evaluate four post-plan techniques: (a) CT, (b) T1+T2, (c) CT+T2, (d) CT+T1(int)+T2. Three interobserver studies were set up. (1) Contouring: the CTV-prostate was delineated on CT and T2 by eight physicians. Additionally one reference contour was defined on both image modalities for each patient. (2) Seed reconstruction: seven physicists localised the seeds on T1 and CT, manually and with CT seed finder tools. A reference seed geometry was defined on CT and T1. (3) Fusion: six physicists registered the image sets for technique (b)-(d), using seeds (if visible) and anatomical landmarks. A reference fusion was determined for each combined technique. RESULTS: (1) The SD(ref) for contouring (1 SD with respect to the reference volume) was largest for CT (23%), but also surprisingly large for MRI (17%). This resulted in large SD(ref) values for D90 for all techniques (17-23%). The surprisingly large SD(ref) for MRI was partly due to variations in interpretation of what to include in the prostate contour. (2) The SD(ref) in D90 for seed reconstruction was small (2%) for all techniques, except for T1+T2 (7%). (3) The SD(ref) in D90 due to image fusion was quite large, especially for direct fusion of CT+T2 (16%) where clearly corresponding landmarks were missing (seeds hardly visible on T2). In general, we observed large differences in D90 depending on the technique used. CONCLUSIONS: The dosimetric parameters for prostate post-implant evaluation showed large technique-dependent interobserver variabilities. Contouring and image fusion are the 'weak links' in the procedure. Guidelines and training in contouring together with incorporation of automated fusion software need to be implemented.
AIM: Reliable post-implant evaluation of prostate seed implants requires optimal seed identification and accurate delineation of anatomical structures. In this study the GEC-ESTRO groups BRAPHYQS and PROBATE investigated the interobserver variability in post-implant prostate contouring, seed reconstruction and image fusion and its impact on the dose-volume parameters. MATERIALS: Post-implant T2-TSE, T1-GE and CT images were acquired for three patients, in order to evaluate four post-plan techniques: (a) CT, (b) T1+T2, (c) CT+T2, (d) CT+T1(int)+T2. Three interobserver studies were set up. (1) Contouring: the CTV-prostate was delineated on CT and T2 by eight physicians. Additionally one reference contour was defined on both image modalities for each patient. (2) Seed reconstruction: seven physicists localised the seeds on T1 and CT, manually and with CT seed finder tools. A reference seed geometry was defined on CT and T1. (3) Fusion: six physicists registered the image sets for technique (b)-(d), using seeds (if visible) and anatomical landmarks. A reference fusion was determined for each combined technique. RESULTS: (1) The SD(ref) for contouring (1 SD with respect to the reference volume) was largest for CT (23%), but also surprisingly large for MRI (17%). This resulted in large SD(ref) values for D90 for all techniques (17-23%). The surprisingly large SD(ref) for MRI was partly due to variations in interpretation of what to include in the prostate contour. (2) The SD(ref) in D90 for seed reconstruction was small (2%) for all techniques, except for T1+T2 (7%). (3) The SD(ref) in D90 due to image fusion was quite large, especially for direct fusion of CT+T2 (16%) where clearly corresponding landmarks were missing (seeds hardly visible on T2). In general, we observed large differences in D90 depending on the technique used. CONCLUSIONS: The dosimetric parameters for prostate post-implant evaluation showed large technique-dependent interobserver variabilities. Contouring and image fusion are the 'weak links' in the procedure. Guidelines and training in contouring together with incorporation of automated fusion software need to be implemented.
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Authors: Jingfei Ma; Marinus A Moerland; Aradhana M Venkatesan; Tharakeswara K Bathala; Rajat J Kudchadker; Kristy K Brock; Steven J Frank Journal: Brachytherapy Date: 2017-01-04 Impact factor: 2.362
Authors: Kris T Huang; Radka Stoyanova; Gail Walker; Kiri Sandler; Matthew T Studenski; Nesrin Dogan; Tahseen Al-Saleem; Mark K Buyyounouski; Eric M Horwitz; Alan Pollack Journal: Radiother Oncol Date: 2015-05-08 Impact factor: 6.280
Authors: Jeremiah W Sanders; Rajat J Kudchadker; Chad Tang; Henry Mok; Aradhana M Venkatesan; Howard D Thames; Steven J Frank Journal: Radiol Artif Intell Date: 2022-01-26
Authors: Christian Kirisits; Mark J Rivard; Dimos Baltas; Facundo Ballester; Marisol De Brabandere; Rob van der Laarse; Yury Niatsetski; Panagiotis Papagiannis; Taran Paulsen Hellebust; Jose Perez-Calatayud; Kari Tanderup; Jack L M Venselaar; Frank-André Siebert Journal: Radiother Oncol Date: 2013-11-30 Impact factor: 6.280