Eli Gibson1, Glenn S Bauman2, Cesare Romagnoli3, Derek W Cool3, Matthew Bastian-Jordan4, Zahra Kassam3, Mena Gaed5, Madeleine Moussa6, José A Gómez6, Stephen E Pautler7, Joseph L Chin7, Cathie Crukley8, Masoom A Haider9, Aaron Fenster10, Aaron D Ward11. 1. Robarts Research Institute, University of Western Ontario, London, Ontario, Canada; Biomedical Engineering, University of Western Ontario, London, Ontario, Canada; Centre for Medical Image Computing, University College London, London, UK; Department of Radiology, Radboud University Medical Centre, Nijmegen, Netherlands. 2. Lawson Health Research Institute, London, Ontario, Canada; Department of Oncology, University of Western Ontario, London, Ontario, Canada. Electronic address: glenn.bauman@lhsc.on.ca. 3. Department of Medical Imaging, University of Western Ontario, London, Ontario, Canada. 4. Department of Medical Imaging, University of Western Ontario, London, Ontario, Canada; Queensland Health, Brisbane, Queensland, Australia. 5. Robarts Research Institute, University of Western Ontario, London, Ontario, Canada; Department of Pathology, University of Western Ontario, London, Ontario, Canada. 6. Department of Pathology, University of Western Ontario, London, Ontario, Canada. 7. Lawson Health Research Institute, London, Ontario, Canada; Department of Urology, University of Western Ontario, London, Ontario, Canada. 8. Robarts Research Institute, University of Western Ontario, London, Ontario, Canada; Lawson Health Research Institute, London, Ontario, Canada. 9. Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada. 10. Robarts Research Institute, University of Western Ontario, London, Ontario, Canada; Biomedical Engineering, University of Western Ontario, London, Ontario, Canada; Lawson Health Research Institute, London, Ontario, Canada; Department of Oncology, University of Western Ontario, London, Ontario, Canada; Department of Medical Biophysics, University of Western Ontario, London, Ontario, Canada. 11. Biomedical Engineering, University of Western Ontario, London, Ontario, Canada; Lawson Health Research Institute, London, Ontario, Canada; Department of Oncology, University of Western Ontario, London, Ontario, Canada; Department of Medical Biophysics, University of Western Ontario, London, Ontario, Canada; Baines Imaging Research Laboratory, London Regional Cancer Centre, London, Ontario, Canada.
Abstract
PURPOSE: Defining prostate cancer (PCa) lesion clinical target volumes (CTVs) for multiparametric magnetic resonance imaging (mpMRI) could support focal boosting or treatment to improve outcomes or lower morbidity, necessitating appropriate CTV margins for mpMRI-defined gross tumor volumes (GTVs). This study aimed to identify CTV margins yielding 95% coverage of PCa tumors for prospective cases with high likelihood. METHODS AND MATERIALS: Twenty-five men with biopsy-confirmed clinical stage T1 or T2 PCa underwent pre-prostatectomy mpMRI, yielding T2-weighted, dynamic contrast-enhanced, and apparent diffusion coefficient images. Digitized whole-mount histology was contoured and registered to mpMRI scans (error ≤2 mm). Four observers contoured lesion GTVs on each mpMRI scan. CTVs were defined by isotropic and anisotropic expansion from these GTVs and from multiparametric (unioned) GTVs from 2 to 3 scans. Histologic coverage (proportions of tumor area on co-registered histology inside the CTV, measured for Gleason scores [GSs] ≥6 and ≥7) and prostate sparing (proportions of prostate volume outside the CTV) were measured. Nonparametric histologic-coverage prediction intervals defined minimal margins yielding 95% coverage for prospective cases with 78% to 92% likelihood. RESULTS: On analysis of 72 true-positive tumor detections, 95% coverage margins were 9 to 11 mm (GS ≥ 6) and 8 to 10 mm (GS ≥ 7) for single-sequence GTVs and were 8 mm (GS ≥ 6) and 6 mm (GS ≥ 7) for 3-sequence GTVs, yielding CTVs that spared 47% to 81% of prostate tissue for the majority of tumors. Inclusion of T2-weighted contours increased sparing for multiparametric CTVs with 95% coverage margins for GS ≥6, and inclusion of dynamic contrast-enhanced contours increased sparing for GS ≥7. Anisotropic 95% coverage margins increased the sparing proportions to 71% to 86%. CONCLUSIONS: Multiparametric magnetic resonance imaging-defined GTVs expanded by appropriate margins may support focal boosting or treatment of PCa; however, these margins, accounting for interobserver and intertumoral variability, may preclude highly conformal CTVs. Multiparametric GTVs and anisotropic margins may reduce the required margins and improve prostate sparing.
PURPOSE: Defining prostate cancer (PCa) lesion clinical target volumes (CTVs) for multiparametric magnetic resonance imaging (mpMRI) could support focal boosting or treatment to improve outcomes or lower morbidity, necessitating appropriate CTV margins for mpMRI-defined gross tumor volumes (GTVs). This study aimed to identify CTV margins yielding 95% coverage of PCa tumors for prospective cases with high likelihood. METHODS AND MATERIALS: Twenty-five men with biopsy-confirmed clinical stage T1 or T2 PCa underwent pre-prostatectomy mpMRI, yielding T2-weighted, dynamic contrast-enhanced, and apparent diffusion coefficient images. Digitized whole-mount histology was contoured and registered to mpMRI scans (error ≤2 mm). Four observers contoured lesion GTVs on each mpMRI scan. CTVs were defined by isotropic and anisotropic expansion from these GTVs and from multiparametric (unioned) GTVs from 2 to 3 scans. Histologic coverage (proportions of tumor area on co-registered histology inside the CTV, measured for Gleason scores [GSs] ≥6 and ≥7) and prostate sparing (proportions of prostate volume outside the CTV) were measured. Nonparametric histologic-coverage prediction intervals defined minimal margins yielding 95% coverage for prospective cases with 78% to 92% likelihood. RESULTS: On analysis of 72 true-positive tumor detections, 95% coverage margins were 9 to 11 mm (GS ≥ 6) and 8 to 10 mm (GS ≥ 7) for single-sequence GTVs and were 8 mm (GS ≥ 6) and 6 mm (GS ≥ 7) for 3-sequence GTVs, yielding CTVs that spared 47% to 81% of prostate tissue for the majority of tumors. Inclusion of T2-weighted contours increased sparing for multiparametric CTVs with 95% coverage margins for GS ≥6, and inclusion of dynamic contrast-enhanced contours increased sparing for GS ≥7. Anisotropic 95% coverage margins increased the sparing proportions to 71% to 86%. CONCLUSIONS: Multiparametric magnetic resonance imaging-defined GTVs expanded by appropriate margins may support focal boosting or treatment of PCa; however, these margins, accounting for interobserver and intertumoral variability, may preclude highly conformal CTVs. Multiparametric GTVs and anisotropic margins may reduce the required margins and improve prostate sparing.
Authors: Maria Kramer; Simon K B Spohn; Selina Kiefer; Lara Ceci; August Sigle; Benedict Oerther; Wolfgang Schultze-Seemann; Christian Gratzke; Michael Bock; Fabian Bamberg; Anca L Grosu; Matthias Benndorf; Constantinos Zamboglou Journal: Front Oncol Date: 2020-11-23 Impact factor: 6.244
Authors: Christopher W Smith; Ryan Alfano; Douglas Hoover; Kathleen Surry; David D'Souza; Jonathan Thiessen; Irina Rachinsky; John Butler; Jose A Gomez; Mena Gaed; Madeleine Moussa; Joseph Chin; Stephen Pautler; Glenn S Bauman; Aaron D Ward Journal: Phys Imaging Radiat Oncol Date: 2021-07-30
Authors: Wei Liu; Andrew Loblaw; David Laidley; Hatim Fakir; Lucas Mendez; Melanie Davidson; Zahra Kassam; Ting-Yim Lee; Aaron Ward; Jonathan Thiessen; Jane Bayani; John Conyngham; Laura Bailey; Joseph D Andrews; Glenn Bauman Journal: Front Oncol Date: 2022-04-13 Impact factor: 5.738