Predicting Pathological Tumor Size in Prostate Cancer Based on Multiparametric Prostate Magnetic Resonance Imaging and Preoperative Findings.

PURPOSE: Oncologic efficacy of focal therapies in prostate cancer depends heavily on accurate tumor size estimation. We aim to evaluate the agreement between radiologic tumor size and pathological tumor size, and identify predictors of pathological tumor size. MATERIALS AND METHODS: This single arm study cohort included all consecutive patients with biopsy proven prostate cancer and a corresponding PI-RADS®v2 3 or greater index tumor on multiparametric magnetic resonance imaging who subsequently underwent radical prostatectomy. Radiologic tumor size was defined as maximum tumor diameter on multiparametric magnetic resonance imaging and compared to whole mount histopathology tumor correlates. The difference between radiologic tumor size and pathological tumor size was assessed, and clinical, pathological and radiographic predictors of pathological tumor size were examined. RESULTS: A total of 461 consecutive lesions in 441 men were included for statistical analysis. Mean radiologic tumor size and pathological tumor size was 1.57 and 2.37 cm, respectively (p <0.001). Radiologic tumor size consistently underestimated pathological tumor size regardless of the preoperative covariates, and the degree of underestimation increased with smaller radiologic tumor size and lower PI-RADSv2 scores. Pathological tumor size was significantly larger for biopsy Gleason Grade Group (GG) 5 compared to GG1 (mean change 0.37 cm, p=0.014), PI-RADSv2 5 lesions compared to PI-RADSv2 4 (mean change 0.26, p=0.006) and higher prostate specific antigen density. The correlations between radiologic tumor size vs pathological tumor size according to biopsy GG and radiologic covariates were generally low with correlation coefficients ranging between 0.1 and 0.65. CONCLUSIONS: Multiparametric magnetic resonance imaging frequently underestimates pathological tumor size and the degree of underestimation increases with smaller radiologic tumor size and lower PI-RADSv2 scores. Therefore, a larger ablation margin may be required for smaller tumors and lesions with lower PI-RADSv2 scores. These variables must be considered when estimating treatment margins in focal therapy.

Immunosignaturing can detect products from molecular markers in brain cancer.

Immunosignaturing shows promise as a general approach to diagnosis. It has been shown to detect immunological signs of infection early during the course of disease and to distinguish Alzheimer's disease from healthy controls. Here we test whether immunosignatures correspond to clinical classifications of disease using samples from people with brain tumors. Blood samples from patients undergoing craniotomies for therapeutically naïve brain tumors with diagnoses of astrocytoma (23 samples), Glioblastoma multiforme (22 samples), mixed oligodendroglioma/astrocytoma (16 samples), oligodendroglioma (18 samples), and 34 otherwise healthy controls were tested by immunosignature. Because samples were taken prior to adjuvant therapy, they are unlikely to be perturbed by non-cancer related affects. The immunosignaturing platform distinguished not only brain cancer from controls, but also pathologically important features about the tumor including type, grade, and the presence or absence of O(6)-methyl-guanine-DNA methyltransferase methylation promoter (MGMT), an important biomarker that predicts response to temozolomide in Glioblastoma multiformae patients.