Gleason Probability Maps: A Radiomics Tool for Mapping Prostate Cancer Likelihood in MRI Space. Tomography 2019 Mar;5(1):127-134
Date
03/12/2019Pubmed ID
30854450Pubmed Central ID
PMC6403022DOI
10.18383/j.tom.2018.00033Scopus ID
2-s2.0-85071529534 (requires institutional sign-in at Scopus site) 36 CitationsAbstract
Prostate cancer is the most common noncutaneous cancer in men in the United States. The current paradigm for screening and diagnosis is imperfect, with relatively low specificity, high cost, and high morbidity. This study aims to generate new image contrasts by learning a distribution of unique image signatures associated with prostate cancer. In total, 48 patients were prospectively recruited for this institutional review board-approved study. Patients underwent multiparametric magnetic resonance imaging 2 weeks before surgery. Postsurgical tissues were annotated by a pathologist and aligned to the in vivo imaging. Radiomic profiles were generated by linearly combining 4 image contrasts (T2, apparent diffusion coefficient [ADC] 0-1000, ADC 50-2000, and dynamic contrast-enhanced) segmented using global thresholds. The distribution of radiomic profiles in high-grade cancer, low-grade cancer, and normal tissues was recorded, and the generated probability values were applied to a naive test set. The resulting Gleason probability maps were stable regardless of training cohort, functioned independent of prostate zone, and outperformed conventional clinical imaging (area under the curve [AUC] = 0.79). Extensive overlap was seen in the most common image signatures associated with high- and low-grade cancer, indicating that low- and high-grade tumors present similarly on conventional imaging.
Author List
McGarry SD, Bukowy JD, Iczkowski KA, Unteriner JG, Duvnjak P, Lowman AK, Jacobsohn K, Hohenwalter M, Griffin MO, Barrington AW, Foss HE, Keuter T, Hurrell SL, See WA, Nevalainen MT, Banerjee A, LaViolette PSAuthors
Anjishnu Banerjee PhD Associate Professor in the Institute for Health and Equity department at Medical College of WisconsinMichael O. Griffin MD, PhD Associate Professor in the Radiology department at Medical College of Wisconsin
Mark D. Hohenwalter MD Associate Dean, Executive Director, Professor in the Radiology department at Medical College of Wisconsin
Peter LaViolette PhD Professor in the Radiology department at Medical College of Wisconsin
MESH terms used to index this publication - Major topics in bold
AdultAged
Early Detection of Cancer
Humans
Image Interpretation, Computer-Assisted
Magnetic Resonance Imaging
Male
Middle Aged
Neoplasm Grading
Prospective Studies
Prostatectomy
Prostatic Neoplasms
ROC Curve
Risk Assessment
