[Diffusion-weighted imaging for prostate cancer localization: comparison of apparent diffusion coefficient values in cancerous and non-cancerous tissues, and the Gleason score of the radical prostatectomy specimens]

[Effect of Imaging Parameters for High-resolution Diffusion-weighted Imaging on Signal-to-noise Ratio and ADC in Prostate Examination]

Readout-segmented echo-planar imaging (readout segmentation of long variable echo trains [RESOLVE]) can be set to higher resolution than single-shot echo planar imaging, but there is concern that the signal-to-noise ratio (SNR) is low. The purpose was to examine the effect of imaging parameters (repetition time: TR, number of excitations: NEX) for RESOLVE on SNR and apparent diffusion coefficient (ADC) value in 1.5 T MRI, assuming a prostate examination. We imaged eight healthy male volunteers at a b value of 800 s/mm2. SNR and ADC value were calculated by setting the ROI in the transition zone (TZ) and the peripheral zone (PZ) of the prostate. Then, 3 radiologists visually evaluated the graininess. In TZ, there was no significant difference in SNR with changing TR. In PZ, SNR increased with increasing TR. In PZ, median SNR was 8.1 [6.9-9.3] at TR=11000 ms and NEX=2. On the other hand, at TR=5000 ms and NEX=3,4, median SNRs were 8.5 [7.5-9.3] and 9.8 [8.8-11.2]. Moreover, NEX=5 with median SNR of 11.1 [10.7-11.7] was significant (p<0.008). Setting more NEX was more effective in increasing SNR. In addition, visual evaluation showed similar results. The ADC value in TZ was around 1404×10-6 mm2/s, and the ADC value in PZ was around 1469×10-6 mm2/s. There were no significant differences under each condition. In conclusion, NEX is more effective than TR for improving SNR both quantitatively and visually in PZ.

A comparative study of Gaussian and non-Gaussian diffusion models for differential diagnosis of prostate cancer with in-bore transrectal MR-guided biopsy as a pathological reference

Background Although several studies have been reported on evaluating the performance of Gaussian and different non-Gaussian diffusion models on prostate cancer, few studies have been reported on the comparison of different models on differential diagnosis for prostate cancer. Purpose To compare the utility of various metrics derived from monoexponential model (MEM), biexponential model (BEM), stretched-exponential model (SEM) based diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in the differential diagnosis of prostate cancer. Material and Methods Thirty-three patients underwent magnetic resonance imaging (MRI) examination. Multi-b value and multi-direction DWIs were performed. In-bore MR-guided biopsy was performed. Apparent diffusion coefficient (ADC), pure molecular diffusion (ADC_slow), pseudo-diffusion coefficient (ADC_fast), perfusion fraction (f), water molecular diffusion heterogeneity index (α), distributed diffusion coefficient (DDC), non-Gaussian diffusion coefficient (MD), and mean kurtosis (MK) values were calculated and compared between cancerous and non-cancerous groups. Receiver operating characteristic (ROC) analysis was performed for all parameters and models. Results ADC, ADC_slow, DDC, and MD values were significantly lower while MK value was significantly higher in prostate cancer than those of prostatitis and benign prostatic hyperplasia. ADC, ADC_slow, DDC, MD, and MK could discriminate between tumor and non-tumorous lesions (area under the curve, 0.856, 0.835, 0.866, 0.918, and 0.937, respectively). MK was superior to ADC in the discrimination of prostate cancer. DKI was superior to MEM in the discrimination of prostate cancer. Conclusions Parameters derived from both Gaussian and non-Gaussian models could characterize prostate cancer. DKI may be advantageous than DWI for detection of prostate cancer.