Petra J van Houdt1, Ghazaleh Ghobadi1, Ivo G Schoots2,3, Stijn W T P J Heijmink2, Jeroen de Jong4, Henk G van der Poel5, Floris J Pos1, Susanne Rylander6, Lise Bentzen7, Karin Haustermans8, Uulke A van der Heide1. 1. Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, The Netherlands. 2. Department of Radiology, the Netherlands Cancer Institute, Amsterdam, The Netherlands. 3. Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands. 4. Department of Pathology, the Netherlands Cancer Institute, Amsterdam, The Netherlands. 5. Department of Urology, the Netherlands Cancer Institute, Amsterdam, The Netherlands. 6. Department of Medical Physics, Aarhus University Hospital, Aarhus, Denmark. 7. Department of Oncology, Aarhus University Hospital, Aarhus, Denmark. 8. Department of Radiation Oncology, University Hospitals Leuven, Leuven, Belgium.
Abstract
BACKGROUND: Previous studies have reported tumor volume underestimation with multiparametric (mp)MRI in prostate cancer diagnosis. PURPOSE: To investigate why some parts of lesions are not visible on mpMRI by comparing their histopathology features to those of visible regions. STUDY TYPE: Retrospective. POPULATION: Thirty-four patients with biopsy-proven prostate cancer scheduled for prostatectomy (median 68.7 years). FIELD STRENGTH/SEQUENCE: T2 -weighted, diffusion-weighted imaging, T2 mapping, and dynamic contrast-enhanced MRI on two 3T systems and one 1.5T system. ASSESSMENT: Two readers delineated suspicious lesions on mpMRI. A pathologist delineated the lesions on histopathology. A patient-customized mold enabled the registration of histopathology and MRI. On histopathology we identified mpMRI visible and invisible lesions. Subsequently, within the visible lesions we identified regions that were visible and regions that were invisible on mpMRI. For each lesion and region the following characteristics were determined: size, location, International Society of Urological Pathology (ISUP) grade, and Gleason subpatterns (density [dense/intermediate], tumor morphology [homogeneous/heterogeneous], cribriform growth [yes/no]). STATISTICAL TESTS: With generalized linear mixed-effect modeling we investigated which features explain why a lesion or a region was invisible on MRI. We compared imaging values (T2 , ADC, and Ktrans ) for these features with one-way analysis of variance (ANOVA). RESULTS: Small, anterior, and ISUP grade 1-2 lesions (n = 34) were missed more frequent than large, posterior, ISUP grade ≥ 3 lesions (n = 35). Invisible regions on mpMRI had lower tumor density, heterogeneous tumor morphology, and were located in the transition zone. Both T2 and ADC values were higher in "intermediate" compared with "dense" regions (P = 0.002 and < 0.001) and in regions with heterogeneous compared with homogeneous morphology (P < 0.001 and 0.03). Ktrans was not significantly different (P = 0.24 and 0.99). DATA CONCLUSION: Regions of prostate cancer lesions that are invisible on mpMRI have different histopathology features than visible regions. This may have implications for monitoring during active surveillance and focal treatment strategies. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:1235-1246.
BACKGROUND: Previous studies have reported tumor volume underestimation with multiparametric (mp)MRI in prostate cancer diagnosis. PURPOSE: To investigate why some parts of lesions are not visible on mpMRI by comparing their histopathology features to those of visible regions. STUDY TYPE: Retrospective. POPULATION: Thirty-four patients with biopsy-proven prostate cancer scheduled for prostatectomy (median 68.7 years). FIELD STRENGTH/SEQUENCE: T2 -weighted, diffusion-weighted imaging, T2 mapping, and dynamic contrast-enhanced MRI on two 3T systems and one 1.5T system. ASSESSMENT: Two readers delineated suspicious lesions on mpMRI. A pathologist delineated the lesions on histopathology. A patient-customized mold enabled the registration of histopathology and MRI. On histopathology we identified mpMRI visible and invisible lesions. Subsequently, within the visible lesions we identified regions that were visible and regions that were invisible on mpMRI. For each lesion and region the following characteristics were determined: size, location, International Society of Urological Pathology (ISUP) grade, and Gleason subpatterns (density [dense/intermediate], tumor morphology [homogeneous/heterogeneous], cribriform growth [yes/no]). STATISTICAL TESTS: With generalized linear mixed-effect modeling we investigated which features explain why a lesion or a region was invisible on MRI. We compared imaging values (T2 , ADC, and Ktrans ) for these features with one-way analysis of variance (ANOVA). RESULTS: Small, anterior, and ISUP grade 1-2 lesions (n = 34) were missed more frequent than large, posterior, ISUP grade ≥ 3 lesions (n = 35). Invisible regions on mpMRI had lower tumor density, heterogeneous tumor morphology, and were located in the transition zone. Both T2 and ADC values were higher in "intermediate" compared with "dense" regions (P = 0.002 and < 0.001) and in regions with heterogeneous compared with homogeneous morphology (P < 0.001 and 0.03). Ktrans was not significantly different (P = 0.24 and 0.99). DATA CONCLUSION: Regions of prostate cancer lesions that are invisible on mpMRI have different histopathology features than visible regions. This may have implications for monitoring during active surveillance and focal treatment strategies. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:1235-1246.
Authors: Cheyenne Williams; Michael Ahdoot; Michael A Daneshvar; Christian Hague; Andrew R Wilbur; Patrick T Gomella; Joanna Shih; Nabila Khondakar; Nitin Yerram; Sherif Mehralivand; Sandeep Gurram; Minhaj Siddiqui; Paul Pinsky; Howard Parnes; Maria Merino; Bradford Wood; Baris Turkbey; Peter A Pinto Journal: J Urol Date: 2021-08-26 Impact factor: 7.450
Authors: Dominik Deniffel; Nathan Perlis; Sangeet Ghai; Stephanie Girgis; Gerard M Healy; Neil Fleshner; Robert Hamilton; Girish Kulkarni; Ants Toi; Theodorus van der Kwast; Alexandre Zlotta; Antonio Finelli; Masoom A Haider Journal: Eur Radiol Date: 2022-05-04 Impact factor: 7.034
Authors: Borna K Barth; Katharina Martini; Stephan M Skawran; Florian A Schmid; Niels J Rupp; Laura Zuber; Olivio F Donati Journal: Eur J Radiol Open Date: 2021-02-27