Intravoxel Incoherent Motion Predicts Positive Surgical Margins and Gleason Score Upgrading After Radical Prostatectomy for Prostate Cancer

Overview

Journal Radiol Med

Specialty Radiology

Date 2023 Jun 5

PMID 37277573

Authors

Shuang Meng

Wanting Gan

Lihua Chen

Nan Wang

Ailian Liu

Affiliations

Soon will be listed here.

Abstract

Background: Whether Intravoxel incoherent motion (IVIM) can be used as a predictive tool of positive surgical margins (PSMs) and Gleason score (GS) upgrading in prostate cancer (PCa) patients after radical prostatectomy (RP) still remains unclear. The aim of this study is to explore the ability of IVIM and clinical characteristics to predict PSMs and GS upgrading.

Methods: A total of 106 PCa patients after RP who underwent pelvic mpMRI (multiparametric Magnetic Resonance Imaging) between January 2016 and December 2021 and met the requirements were retrospectively included in our study. IVIM parameters were obtained using GE Functool post-processing software. Logistic regression models were fitted to confirm the predictive risk factor of PSMs and GS upgrading. The area under the curve and fourfold contingency table were used to evaluate the diagnostic efficacy of IVIM and clinical parameters.

Results: Multivariate logistic regression analyses revealed that percent of positive cores, apparent diffusion coefficient and molecular diffusion coefficient (D) were independent predictors of PSMs (Odds Ratio (OR) were 6.07, 3.62 and 3.16, respectively), Biopsy GS and pseudodiffusion coefficient (D*) were independent predictors of GS upgrading (OR were 0.563 and 7.15, respectively). The fourfold contingency table suggested that combined diagnosis increased the ability of predicting PSMs but had no advantage in predicting GS upgrading except the sensitivity from 57.14 to 91.43%.

Conclusions: IVIM showed good performance in predicting PSMs and GS upgrading. Combining IVIM and clinical factors enhanced the performance of predicting PSMs, which may contribute to clinical diagnosis and treatment.

Citing Articles

Recent trends in AI applications for pelvic MRI: a comprehensive review.

Tsuboyama T, Yanagawa M, Fujioka T, Fujita S, Ueda D, Ito R Radiol Med. 2024; 129(9):1275-1287.

PMID: 39096356 DOI: 10.1007/s11547-024-01861-4.

Precise Prostate Cancer Assessment Using IVIM-Based Parametric Estimation of Blood Diffusion from DW-MRI.

Balaha H, Ayyad S, Alksas A, Shehata M, Elsorougy A, Badawy M Bioengineering (Basel). 2024; 11(6).

PMID: 38927865 PMC: 11200510. DOI: 10.3390/bioengineering11060629.

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