Prostate cancer detection with multi‐parametric MRI: Logistic regression analysis of quantitative T2, diffusion‐weighted imaging, and dynamic contrast‐enhanced MRI

Abstract

Purpose:To develop a multi-parametric model suitable for prospectively identifying prostate cancer in peripheral zone (PZ) using magnetic resonance imaging (MRI). Materials and Methods:Twenty-five radical prostatectomy patients (median age, 63 years; range, 44 -72 years) had T2-weighted, diffusion-weighted imaging (DWI), T2-mapping, and dynamic contrast-enhanced (DCE) MRI at 1.5 Tesla (T) with endorectal coil to yield parameters apparent diffusion coefficient (ADC), T2, volume transfer constant (K trans ) and extravascular extracellular volume fraction (v e ). Whole-mount histology was generated from surgical specimens and PZ tumors delineated. Thirty-eight tumor outlines, one per tumor, and pathologically normal PZ regions were transferred to MR images. Receiver operating characteristic (ROC) curves were generated using all identified normal and tumor voxels.Step-wise logistic-regression modeling was performed, testing changes in deviance for significance. Areas under the ROC curves (A z ) were used to evaluate and compare performance. .719], which was significantly higher than A z,T2 , A z,Ktrans , and A z,ve (P Ͻ 0.002). A z,LR-3p tended to be greater than A z,ADC , however, this result was not statistically significant (P ϭ 0.090). Conclusion:Using logistic regression, an objective model capable of mapping PZ tumor with reasonable performance can be constructed.

Diffusion weighted imaging in prostate cancer

“…The ADC is potentially an objective means by which to detect tumours by DWI [27,39,61,62]. However, tissue diffusivity depends on both biological (patient's age and body temperature) and technical factors (b-value, location and size of the region of interest) [24,63].…”

“…Research has been directed towards combining various acquisition parameters (such as water diffusion, chemical environment and vascular properties) into a single value or image to improve tumour localisation [69]. Recently, Langer and colleagues were able to successfully combine quantitative T2WI, DWI and DCE-MRI data through logistic regression to develop an objective model for mapping the tumour within the PZ [62]. Some other authors have shown improvements in accuracy in combined T2WI, DCE-MRI and DWI [47], combined T2WI, DWI and MRS [48], as well as combined T2WI, DCE-MRI and MRS [70], whereas others have not seen as much benefit of two verse three parameter analysis [54].…”

Multiparametric MRI is helpful to predict tumor focality, stage, and size in patients diagnosed with unilateral low-risk prostate cancer

“…8 Multiparametric MRI combining DW images (DWI) and DCE has demonstrated its value in distinguishing malignant from benign prostate tissue. 9 However, most of the studies on multiparametric MRI have not specifically focused on low D'Amico risk patients, who are the potential candidates for less aggressive treatment strategies such as active surveillance, brachytherapy or focal ablation. The aims of this study were to evaluate which MR combination would be optimal for cancer detection, and to assess the incremental staging accuracy of multiparametric MRI in patients with suspected unilateral low-risk prostate cancer.…”

Risk-Based Prostate Cancer Screening: Who and How?

“…As compared with healthy gland tissue, prostate cancer has a higher cellular content and limits water molecule movement. DWI has been shown to be the most effective single parameter for prostate cancer detection [85]. MRS assesses physical and chemical properties of surrounding tissue, as well as concentrations of certain metabolites such as citrate, creatinine, and choline.…”