Luminal Water Imaging: A New MR Imaging T2 Mapping Technique for Prostate Cancer Diagnosis

Abstract

Purpose-To assess the feasibility of luminal water imaging (LWI), a quantitative T 2 -based MRI technique, for the detection and grading of prostatic cancer (PCa).Material and Methods-18 patients with biopsy proven PCa provided informed consent to be included in this institutional human ethics board approved prospective study between January 2015, and January 2016. Patients underwent 3T MRI shortly before radical prostatectomy. T 2 distributions were generated with regularized Non-Negative Least Squares (NNLS)algorithm from multi-echo spin echo MRI data. From T 2 distributions, maps of seven MR parameters: N comp , T 2-short , T 2-long , geometric mean T 2 (gmT 2 ), Luminal Water Fraction (LWF), A short , and A long were generated and compared with digitized images of Hematoxylin and Eosin (H&E) stained whole-mount histology sections. Paired-t-test determined significant differences between MR parameters in malignant and non-malignant tissue. Correlation with Gleason score (GS) was evaluated with Spearman's rank correlation test. Diagnostic accuracy was evaluated using logistic generalized linear mixed effect models (GLMMs) and receiver operating characteristic (ROC) analysis. Results-The average values of four MR parameters: gmT 2 , A short , A long , and LWF were significantly different between malignant and non-malignant tissue. All MR parameters except for T 2-long showed significant correlation (P<0.05) with GS in peripheral zone (PZ). The highest correlation with GS was obtained for LWF (−0.78 ± 0.11, p < 0.001

Probing structure of normal and malignant prostate tissue before and after radiation therapy with luminal water fraction and diffusion‐weighted MRI

“…Our estimates of short and long T 2 components and LWF were consistent with previous reports using NNLS fitting, indicating that our approach can be considered as a fully model‐based equivalent to the NNLS technique. BIC revealed a moderate preference for monoexponential fitting in tumor and the identification of regions of monoexponential decay may be useful for tissue characterization . Another advantage of estimation via mono‐ and biexponential models over NNLS methods is that they can be combined with a Rician noise model to explicitly account for the noise floor signal in voxels with low signal‐to‐noise ratio (SNR) at long echo times.…”

“…Thus, the proportions of the short and long T 2 components are likely to vary with histological tumor grade. This is supported by findings showing that the fractional amount of the long T 2 component, termed the luminal water fraction (LWF), is also correlated with the amount of luminal space and is negatively correlated with increasing Gleason grade . There is also emerging evidence that ADC is associated with the amount of luminal space …”

“…Only the even pairs of echoes were included in the analysis to account for stimulated echoes . The cutoff threshold for short T 2 values was set to 200 msec and the maximum long T 2 value was set as 2000 msec as derived by Sabouri et al…”

Simplified Luminal Water Imaging for the Detection of Prostate Cancer From Multiecho T2 MR Images

“…This would allow for a reduced number of protocols for grading prostate cancer, reducing overall scan times. The AUC for the detection of PCa is also lower in this study than previous results, possibly due to previous studies using patients scheduled for retropubic prostatectomy, weighting the lesions towards more advanced tumors.…”

“…Sabouri et al implemented a method to investigate quantitative T 2 imaging in the prostate, proposing the LWI technique, which produces an estimate of the fractional volume of luminal water in each voxel of the prostate, the luminal water fraction (LWF). Sabouri et al have shown that there is a good correlation between LWF and histologically measured luminal fractional volume and determined that LWI shows promise in being able to detect PCa and predict Gleason score . However, the fitting method used has a high number of degrees of freedom, potentially making it vulnerable to noise and local minima.…”