Gleason Probability Maps: A Radiomics Tool for Mapping Prostate Cancer Likelihood in MRI Space

Abstract

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.

Multiparametric radiomics methods for breast cancer tissue characterization using radiological imaging

“…In the breast lesions, consistent with other reports in breast and other cancers, malignant breast lesions had increased entropy or heterogeneity compared to benign lesions [8,22,40,41]. Importantly, no differences in the normal glandular tissue were noted between patients with either benign and malignant lesions [8,22,40,41].…”

Integrative radiogenomics for virtual biopsy and treatment monitoring in ovarian cancer

“…The mould-guided biopsy approach has recently gained popularity and has been used to investigate the association of radiomic features and histopathology phenotypes in different tumour types, such as prostate cancer [76][77][78][79], liver cancer [80] and renal cancer [81]. More recently, updates in the design of these moulds have been proposed to choose the preferred tissue sectioning angle, transforming the images and the corresponding maps [82].…”

Associations between Statin/Omega3 Usage and MRI-Based Radiomics Signatures in Prostate Cancer

“…Based on MRI used in the routine management of prostate cancer, radiomics is well posited to study these heterogeneities as well as to assess the heterogeneity among different patients. While still in an early stage of development as a discipline, radiomics has found success in prostate cancer diagnosis, risk characterization, genomic association, and prognosis prediction, offering a noninvasive and repeatable approach in these applications [ 18 , 19 , 20 , 21 , 22 , 24 , 25 , 27 , 40 ]. With recent research, epidemiological, and clinical development in prostate cancer, risk stratification has become an increasingly central theme in prostate cancer management.…”

“…In prostate cancer, like in many other cancer sites, radiomics has found success in detecting and diagnosing tumors, characterizing index lesions, predicting tumor aggressiveness, evaluating treatment response and prognosis, and associating with tumor genomics [ 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 ]. However, to the best of our knowledge, radiomics has never been explored as a potential tool to investigate the relationship between medication exposure and prostate cancer.…”