Computational imaging reveals shape differences between normal and malignant prostates on MRI
Year: 2017
Type: article
Study design: Observational Study
Abstract: We seek to characterize differences in the shape of the prostate and the central gland (combined central and transitional zones) between men with biopsy confirmed prostate cancer and men who were identified as not having prostate cancer either on account of a negative biopsy or had pelvic imaging done for a non-prostate malignancy. T2w MRI from 70 men were acquired at three institutions. The cancer positive group (PCa+) comprised 35 biopsy positive (Bx+) subjects from three institutions (Gleason scores: 6-9, Stage: T1-T3). The negative group (PCa-) combined 24 biopsy negative (Bx-) from two institutions and 11 subjects diagnosed with rectal cancer but with no clinical or MRI indications of prostate cancer (Cl-). The boundaries of the prostate and central gland were delineated on T2w MRI by two expert raters and were used to construct statistical shape atlases for the PCa+, Bx- and Cl- prostates. An atlas comparison was performed via per-voxel statistical tests to localize shape differences (significance assessed at p < 0.05). The atlas comparison revealed central gland hypertrophy in the Bx- subpopulation, resulting in significant volume and posterior side shape differences relative to PCa+ group. Significant differences in the corresponding prostate shapes were noted at the apex when comparing the Cl- and PCa+ prostates.
Source: Scientific Reports
DOI: 10.1038/srep41261
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,690
Funders: U.S. Department of Defense, Wallace H. Coulter Foundation, Cleveland Clinic, Case Western Reserve University, Case Comprehensive Cancer Center, Case Western Reserve University, Australian Prostate Cancer Research, National Institutes of Health, National Cancer Institute, National Institute of Diabetes and Digestive and Kidney Diseases
Awards: G1076473199, G12088891, Pathology Image Informatics Platform for visualization, analysis and management, G2779459091, G3564444776, IDENTIFYING MRI MARKERS FOR VIABLE POST-RADIATION PROSTATE TUMORS IN MEN UNDERGOING RADIATION THERAPY FOLLOWED BY PROSTATECTOMY, G4119534169, G5302883106, G554759712, G5850682332, Computerized morphologic-molecular predictor of progression in DCIS, G8632625050, G9000023716, G9000149699, G9000167609, G9000227358, G9000304339, G9000320085, G9000331623
OpenAlex ID: W2584774372
