Open AccessThe utility of apparent diffusion coefficient values in the risk stratification of prostate cancer using a 1.5T magnetic resonance imaging without endorectal coil
Author(s) -
João Lopes Dias,
João Magalhães Pina,
Nuno Costa,
Sandra Carmo,
Cecília Leal,
Tiago Bilhim,
Rui Marques,
Luís Campos Pinheiro
Publication year - 2017
Publication title -
acta urológica portuguesa
Language(s) - English
Resource type - Journals
eISSN - 2387-0419
pISSN - 2341-4022
DOI - 10.24915/aup.33.3.33
Subject(s) - medicine , effective diffusion coefficient , confidence interval , magnetic resonance imaging , prostate cancer , receiver operating characteristic , prostate , prostatectomy , nuclear medicine , radiology , cancer
PurposeTo evaluate the relationship between mean apparent diffusion coefficient (ADC) and post-surgical Gleason scores. To determine the diagnostic accuracy of multiparametric magnetic resonance imaging (mp-MRI) on a 1.5T magnet in distinguishing low, intermediate and high-grade prostate tumors.Material and methodsThis is a retrospective institutional-review-board-approved, single-center study including 30 patients (median age, 60 years) who underwent mp-MRI before prostatectomy for prostate cancer. Using histological reports for guidance, the tumors were localized in ADC maps, and mean ADCs were measured and examined for correlation with Gleason scores. 2 patients had 2 measurable foci, so a total of 32 tumors were studied. The diagnostic accuracy of the mean ADC was assessed by using the area under the receiver operating characteristic curve (ROC).ResultsIn the differentiation of tumors with a Gleason score of 6 from those with a Gleason score of at least 7, mean ADC yielded an AUC of 0.76 (95% confidence interval: 0.59, 0.93). In the differentiation of tumors with Gleason scores of 6 or 7 from those with a Gleason score of at least 8, mean ADC yielded an AUC of 0.94 (95% confidence interval: 0.86, 1.00).ConclusionMean ADC values may allow a correct assessment of the patient risk using a 1.5T magnet without ERC.