MRI Features Associated with Histology of Benign Prostatic Hyperplasia Nodules: Generation of a Predictive Model
Jessica Dai, Tara Morgan, Ramy Goueli, Daniel Parrott, Alexander P. Kenigsberg, Ryan Mauck, Claus G. Roehrborn, Douglas W. Strand, Daniel N. Costa, Jeffrey Gahan
- Year
- 2021
- Citations
- 5
Abstract
Background: Histologic phenotypic variation of benign prostatic hyperplasia (BPH) has been hypothesized to underlie response to medical therapy. We evaluate preoperative MRI of robot-assisted simple prostatectomy (RASP) specimens and determine imaging features associated with histologic phenotype. Materials and Methods: All patients undergoing RASP from November 2015 to November 2019 with a multiparametric MRI ≤1 year before RASP were included. Patients without identifiable BPH nodules on histologic specimens were excluded. Histology slides were obtained from whole mount adenoma specimens and corresponding MRI were reviewed and graded independently by a blinded expert in BPH histopathology (D.W.S.) and an experienced radiologist specializing in prostate imaging (D.N.C.), respectively. Each nodule was assigned a phenotypic score on a 5-point Likert scale (1 = predominantly glandular; 5 = predominantly stromal) by each reviewer. Scores were compared using the sign test and univariate analysis. Signal intensity relative to background transition zone and nodule texture were noted on T2, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging sequences. Univariate and multivariate stepwise linear regression analysis were conducted to identify MRI features associated with histology score. All analyses were performed using Statistical Analysis System (version 9.4). Results: A total of 99 prostate nodules in 29 patients were included. Median phenotypic scores by histology and MRI were comparable (2, interquartile range [IQR] 2–3 vs 2, IQR 2–4, respectively; p = 0.63). Histology scores were positively correlated with MRI scores (Pearson's correlation 0.84, p < 0.0001). Multivariate stepwise linear regression analysis showed that low apparent diffusion coefficient (ADC) signal intensity ( p < 0.001) and DCE wash-in ( p = 0.03) were positively associated with more stromal histology, whereas ADC standard deviation ( p = 0.03), DCE wash-out ( p = 0.001), and heterogeneous T2 texture ( p = 0.003) were associated with more glandular histology. Conclusion: There is a strong correlation between MRI features and the histologic phenotype of BPH nodules. MRI may provide a noninvasive method to determine underlying BPH nodule histology.
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