Accelerated Segmented Diffusion-Weighted Prostate Imaging for Higher Resolution, Higher Geometric Fidelity, and Multi-b Perfusion Estimation

Abstract

Purpose: To improve the geometric fidelity and spatial-resolution of multi-b diffusion-weighted MRI of the prostate. Materials and Methods: An accelerated segmented diffusion imaging sequence was developed and evaluated in 25 patients undergoing multi-parametric MRI exams of the prostate. A reduced field-of-view was acquired using an endo-rectal coil. The number of sampled diffusion weightings, or b-factors, was increased to allow estimation of tissue perfusion based on the intra-voxel incoherent motion (IVIM) model. Apparent diffusion coefficients (ADCs) measured with the proposed segmented method were compared to those obtained with conventional single-shot echoplanar imaging (EPI). Results: Compared to single-shot EPI, the segmented method resulted in faster acquisition with twofold improvement in spatial resolution and a greater than threefold improvement in geometric fidelity. ADC values measured with the novel sequence demonstrated excellent agreement with those obtained from the conventional scan (R 2 =0.91 for b max =500 s/mm 2 and R 2 =0.89 for b max =1400 s/mm 2). IVIM perfusion fraction was 4.0+/−2.7% for normal peripheral zone, 6.6+/ −3.6% for normal transition zone and 4.4+/−2.9% for suspected tumor lesions. Conclusion: The proposed accelerated segmented prostate diffusion imaging sequence achieved improvements in both spatial resolution and geometric fidelity, along with concurrent quantification of IVIM perfusion.

Revisiting DCE-MRI

“…In a next step, the machine learning models need to be trained on larger data sets, including healthy subjects and a broader variety of lesions to create viable predictor models. Moreover, the use of clinical data and laboratory parameters (such as PSA level, age, or comorbidities) as input variables in combination with further promising image-derived parameters such as T2 mapping 49 or improved DWI sequences 50 might advance the prediction of clinically significant prostate cancer. In summary, additional studies are needed to evaluate and validate our method, as well as the general potential of high spatiotemporal DCE-MRI to improve the detection and characterization of prostate cancer.…”

Prostate lesions characterization using diffusion‐weighted spatiotemporal encoded MRI: Feasibility and initial assessment

“…Although this can reduce susceptibility‐associated prostate image distortions, the clinical value of such reduced FOVs in terms of improving diagnostic quality is ambiguous 16 . The combination of reduced FOV imaging and segmented EPI acquisitions has also been reported using endorectal coils for signal reception 17 . In addition to such modified data‐acquisition strategies, prostate image distortions have been reduced by relying on the acquisition of ancillary ΔB 0 field maps 18 and by acquiring two b = 0 scans with opposing PE polarities, 19,20 which are subsequently used to correct for distortions.…”

De Novo Radiomics Approach Using Image Augmentation and Features From T1 Mapping to Predict Gleason Scores in Prostate Cancer

“…Therefore, a reliable noninvasive and accurate method to determine Gleason score with high accuracy would be desirable, as it could spare patients painful biopsies with the risk of procedural complications/false-negative results and it could have a significant impact on clinical decision making, prediction of patient outcomes, and individual patient care 14 . Multiparametric magnetic resonance imaging (mpMRI) is a hallmark of state-of-the art PCa imaging and combines high-resolution T2-weighted imaging with diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MRI 15–18 . Although quantitative T1 and T2 imaging techniques (T1 and T2 mapping) are currently not an integral part of mpMRI in clinical practice, they allow for a more reliable evaluation of “absolute” T1 and T2 relaxation times, providing more reproducible data on intrinsic biological tissue characteristics 19,20 .…”