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Title: Toward Prostate Cancer Contouring Guidelines on Magnetic Resonance Imaging: Dominant Lesion Gross and Clinical Target Volume Coverage Via Accurate Histology Fusion

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)more » 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.« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [2]; ;  [6];  [6];  [7];  [6];  [1];  [2]; ;  [8]; ;  [5];  [2];  [1];  [2] more »;  [9]; « less
  1. Robarts Research Institute, University of Western Ontario, London, Ontario (Canada)
  2. (Canada)
  3. (United Kingdom)
  4. (Netherlands)
  5. Lawson Health Research Institute, London, Ontario (Canada)
  6. Department of Medical Imaging, University of Western Ontario, London, Ontario (Canada)
  7. (Australia)
  8. Department of Pathology, University of Western Ontario, London, Ontario (Canada)
  9. Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, Ontario (Canada)
Publication Date:
OSTI Identifier:
22648796
Resource Type:
Journal Article
Resource Relation:
Journal Name: International Journal of Radiation Oncology, Biology and Physics; Journal Volume: 96; Journal Issue: 1; Other Information: Copyright (c) 2016 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; ANIMAL TISSUES; ANISOTROPY; DISEASE INCIDENCE; HISTOLOGY; IMAGES; NEOPLASMS; NMR IMAGING; PROSTATE

Citation Formats

Gibson, Eli, Biomedical Engineering, University of Western Ontario, London, Ontario, Centre for Medical Image Computing, University College London, London, Department of Radiology, Radboud University Medical Centre, Nijmegen, Bauman, Glenn S., E-mail: glenn.bauman@lhsc.on.ca, Department of Oncology, University of Western Ontario, London, Ontario, Romagnoli, Cesare, Cool, Derek W., Bastian-Jordan, Matthew, Queensland Health, Brisbane, Queensland, Kassam, Zahra, Gaed, Mena, Department of Pathology, University of Western Ontario, London, Ontario, Moussa, Madeleine, Gómez, José A., Pautler, Stephen E., Chin, Joseph L., Department of Urology, University of Western Ontario, London, Ontario, Crukley, Cathie, Lawson Health Research Institute, London, Ontario, Haider, Masoom A., and and others. Toward Prostate Cancer Contouring Guidelines on Magnetic Resonance Imaging: Dominant Lesion Gross and Clinical Target Volume Coverage Via Accurate Histology Fusion. United States: N. p., 2016. Web. doi:10.1016/J.IJROBP.2016.04.018.
Gibson, Eli, Biomedical Engineering, University of Western Ontario, London, Ontario, Centre for Medical Image Computing, University College London, London, Department of Radiology, Radboud University Medical Centre, Nijmegen, Bauman, Glenn S., E-mail: glenn.bauman@lhsc.on.ca, Department of Oncology, University of Western Ontario, London, Ontario, Romagnoli, Cesare, Cool, Derek W., Bastian-Jordan, Matthew, Queensland Health, Brisbane, Queensland, Kassam, Zahra, Gaed, Mena, Department of Pathology, University of Western Ontario, London, Ontario, Moussa, Madeleine, Gómez, José A., Pautler, Stephen E., Chin, Joseph L., Department of Urology, University of Western Ontario, London, Ontario, Crukley, Cathie, Lawson Health Research Institute, London, Ontario, Haider, Masoom A., & and others. Toward Prostate Cancer Contouring Guidelines on Magnetic Resonance Imaging: Dominant Lesion Gross and Clinical Target Volume Coverage Via Accurate Histology Fusion. United States. doi:10.1016/J.IJROBP.2016.04.018.
Gibson, Eli, Biomedical Engineering, University of Western Ontario, London, Ontario, Centre for Medical Image Computing, University College London, London, Department of Radiology, Radboud University Medical Centre, Nijmegen, Bauman, Glenn S., E-mail: glenn.bauman@lhsc.on.ca, Department of Oncology, University of Western Ontario, London, Ontario, Romagnoli, Cesare, Cool, Derek W., Bastian-Jordan, Matthew, Queensland Health, Brisbane, Queensland, Kassam, Zahra, Gaed, Mena, Department of Pathology, University of Western Ontario, London, Ontario, Moussa, Madeleine, Gómez, José A., Pautler, Stephen E., Chin, Joseph L., Department of Urology, University of Western Ontario, London, Ontario, Crukley, Cathie, Lawson Health Research Institute, London, Ontario, Haider, Masoom A., and and others. Thu . "Toward Prostate Cancer Contouring Guidelines on Magnetic Resonance Imaging: Dominant Lesion Gross and Clinical Target Volume Coverage Via Accurate Histology Fusion". United States. doi:10.1016/J.IJROBP.2016.04.018.
@article{osti_22648796,
title = {Toward Prostate Cancer Contouring Guidelines on Magnetic Resonance Imaging: Dominant Lesion Gross and Clinical Target Volume Coverage Via Accurate Histology Fusion},
author = {Gibson, Eli and Biomedical Engineering, University of Western Ontario, London, Ontario and Centre for Medical Image Computing, University College London, London and Department of Radiology, Radboud University Medical Centre, Nijmegen and Bauman, Glenn S., E-mail: glenn.bauman@lhsc.on.ca and Department of Oncology, University of Western Ontario, London, Ontario and Romagnoli, Cesare and Cool, Derek W. and Bastian-Jordan, Matthew and Queensland Health, Brisbane, Queensland and Kassam, Zahra and Gaed, Mena and Department of Pathology, University of Western Ontario, London, Ontario and Moussa, Madeleine and Gómez, José A. and Pautler, Stephen E. and Chin, Joseph L. and Department of Urology, University of Western Ontario, London, Ontario and Crukley, Cathie and Lawson Health Research Institute, London, Ontario and Haider, Masoom A. and and others},
abstractNote = {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.},
doi = {10.1016/J.IJROBP.2016.04.018},
journal = {International Journal of Radiation Oncology, Biology and Physics},
number = 1,
volume = 96,
place = {United States},
year = {Thu Sep 01 00:00:00 EDT 2016},
month = {Thu Sep 01 00:00:00 EDT 2016}
}