Time-dependent diffusion in prostate cancer

G Lemberskiy, AB Rosenkrantz, J Veraart… - Investigative …, 2017 - journals.lww.com
Investigative radiology, 2017journals.lww.com
Objective Prior studies in prostate diffusion-weighted magnetic resonance imaging (MRI)
have largely explored the impact of b-value and diffusion directions on estimated diffusion
coefficient D. Here we suggest varying diffusion time, t, to study time-dependent D (t) in
prostate cancer, thereby adding an extra dimension in the development of prostate cancer
biomarkers. Methods Thirty-eight patients with peripheral zone prostate cancer underwent 3-
T MRI using an external-array coil and a diffusion-weighted image sequence acquired for b …
Abstract
Objective
Prior studies in prostate diffusion-weighted magnetic resonance imaging (MRI) have largely explored the impact of b-value and diffusion directions on estimated diffusion coefficient D. Here we suggest varying diffusion time, t, to study time-dependent D (t) in prostate cancer, thereby adding an extra dimension in the development of prostate cancer biomarkers.
Methods
Thirty-eight patients with peripheral zone prostate cancer underwent 3-T MRI using an external-array coil and a diffusion-weighted image sequence acquired for b= 0, as well as along 12 noncollinear gradient directions for b= 500 s/mm 2 using stimulated echo acquisition mode (STEAM) diffusion tensor imaging (DTI). For this sequence, 6 diffusion times ranging from 20.8 to 350 milliseconds were acquired. Tumors were classified as low-grade (Gleason score [GS] 3+ 3; n= 11), intermediate-grade (GS 3+ 4; n= 16), and high-grade (GS≥ 4+ 3; n= 11). Benign peripheral zone and transition zone were also studied.
Results
Apparent diffusion coefficient (ADC) D (t) decreased with increasing t in all zones of the prostate, though the rate of decay in D (t) was different between sampled zones. Analysis of variance and area under the curve analyses suggested better differentiation of tumor grades at shorter t. Fractional anisotropy (FA) increased with t for all regions of interest. On average, highest FA was observed within GS 3+ 3 tumors.
Conclusions
There is a measurable time dependence of ADC in prostate cancer, which is dependent on the underlying tissue and Gleason score. Therefore, there may be an optimal selection of t for prediction of tumor grade using ADC. Controlling t should allow ADC to achieve greater reproducibility between different sites and vendors. Intentionally varying t enables targeted exploration of D (t), a previously overlooked biophysical phenomenon in the prostate. Its further microstructural understanding and modeling may lead to novel diffusion-derived biomarkers.
Lippincott Williams & Wilkins
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