<p>Apparent diffusion coefficient in extraprostatic extension of prostate cancer: a systematic review and diagnostic meta-analysis</p>

Abstract

Objective: To evaluate the diagnostic performance of apparent diffusion coefficient (ADC) for local staging of prostate cancer. Methods: Databases of Web of Science, MEDLINE (Ovid and PubMed), Cochrane Library, EMBASE, and Google Scholar were searched up to May 31, 2018, with language restricted to English. All studies concerning multiparametric magnet resonance imaging (mpMRI) with ADC for detection of extracapsular extension (ECE, T3a) and/or extraprostatic extension (EPE, overall stage of T3) were identified by two reviewers independently, and quality of included studies was evaluated using Quality Assessment of Diagnostic Accuracy Studies-2 tool. True positive, false positive, false negative and true negative of each study were extracted to reconstruct the 2×2 tables for evaluating diagnostic accuracy. Summary estimates of sensitivity, specificity, and corresponding 95% CIs were calculated with bivariate model and hierarchical summary receiver operating characteristic model, then presented in forest plots. Multiple subgroup analyses and meta-regression were performed, and publication bias was evaluated with Deeks funnel. Results: A total of 18 studies were included, with 6 involved ECE and 12 for EPE. Pooled sensitivity was 80.5% (95% CI 76.5–83.9%) with specificity of 69.1% (95% CI 62.3–75.2%). Multiple subgroup analyses showed that if ADC and length of capsular contact are regarded as independent predictors, pooled sensitivity was 85% (95% CI 77–90%) and 81.1% (95% CI 76.0–85.3%), with specificity of 70.8% (95% CI 56.3–82.0%) and 66.6% (95% CI 57.6–74.5%), respectively. Meta-regression demonstrated that there was no substantially significant difference in types of coil, magnet field strength (1.5T versus 3.0T), and analysis method (per-lesion versus per-patient). Conclusion: By introducing ADC to MRI, we could obtain favorable sensitivity for diagnostic performance of EPE, but with a little decreased specificity.

The Quantitative Assessment of Using Multiparametric MRI for Prediction of Extraprostatic Extension in Patients Undergoing Radical Prostatectomy: A Systematic Review and Meta-Analysis

“…As for ADC, studies revealed that as tumor grade increases, a trend of increasing cellular density, with loss of the normal glandular structures and a decrease in the extracellular space, limiting water diffusivity and yielding lower ADC values (51,52). ADC value has been shown to inversely correlate with pathological stage (42,53), and a previous study demonstrated that when combining ADC value with other clinical information, the pooled sensitivity and specificity were 0.85 and 0.71 (54). The rationale of using tumor volume as predictor of EPE is based on findings that the diameter of the index lesion has a strong correlation with tumor volume at radical prostatectomy (42,55).…”

Calculation of Apparent Diffusion Coefficients in Prostate Cancer Using Deep Learning Algorithms: A Pilot Study

“…In our study, both the z-ADC and s-ADC sets showed less distortion and better reproducibility of the quantitative ADC values for all the evaluated tissues; they also showed better tumor detection and classification capacity than the f-ADC sets. The ADC values are generated for most of the current clinical implementations by calculating the signal intensity decay using two or more DWI sets with different b -values ( 1 – 5 , 9 – 11 , 13 , 14 ). The reproducibility and accuracy of the calculated ADC values are affected by the choice of b -values ( 3 , 4 , 34 ) and the DWI image quality ( 14 ).…”

“…Diffusion-weighted imaging (DWI) currently constitutes an integral part of multiparametric magnetic resonance imaging (MRI) examinations of the prostate. Apparent diffusion coefficients (ADCs) obtained with DWI are highly valuable for detecting and staging prostate cancer, evaluating cancer aggressiveness (1,2), guiding targeted biopsies, and assessing the response to treatment (3)(4)(5)(6)(7)(8)(9)(10). Clinically, the accuracy of the ADC measurement depends on the quality of the DWI image.…”

Personalized management of prostate cancer: from molecular and imaging markers to radiogenomics

“…Currently, one of the most investigated MRI-based imaging markers of localized PCa is the apparent diffusion coefficient (ADC) measured from diffusion-weighted images (DWI), which represent the degree of restriction of Brownian motion of hydrogen molecules in cancer tissues [ 13 ]. According to recent meta-analyses, ADC values showed moderate accuracy in separating high-risk from low-risk PCa in accordance to ISUP grades (76.9% sensitivity, 77.0% specificity, AUC = 0.67) [ 14 ] and also allowed detection of extraprostatic extension of PCa with polled sensitivity and specificity 80.5% and 69.1%, respectively [ 15 ]. Notwithstanding, there are 2 major unsolved diagnostic problems inherent for mpMRI: the inability to reliably distinguish PCa from benign processes in PI-RADS 3 lesions (equivocal risk) and the predominant invisibility of aggressive cribriform/glomeruloid Gleason 4 patterns on MR-images [ 16 ].…”