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

Martins Otikovs, Orith Portnoy*, Debbie Anaby, Barak Rosenzweig, Noam Nissan, Lucio Frydman*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Purpose: To assess the feasibility and reliability of a DWI protocol based on spatiotemporally encoding (SPEN), to target prostate lesions along guidelines normally used in EPI-based DWI clinical practice. Methods: Prostate Imaging—Reporting and Data System recommendations underlying clinical prostate scans were used to develop a SPEN-based DWI protocol, which included a novel, local, low-rank regularization algorithm. These DWI acquisitions were run at 3 T under similar nominal spatial resolutions and diffusion-weighting b-values as used in EPI-based clinical studies. Prostates of 11 patients suspected of clinically significant prostate cancer lesions were therefore scanned using the two methods, with the same number of slices, same slice thickness, and same interslice gaps. Results: Of the 11 patients scanned, SPEN and EPI provided comparable information in 7 of the cases, whereas EPI was deemed superior in a case for which SPEN images had to be acquired with a shorter effective TR owing to scan-time constraints. SPEN provided reduced susceptibility to field-derived distortions in 3 of the cases. Conclusions: SPEN's ability to provide prostate lesion contrast was most clearly evidenced for DW images acquired with b ≥ 900 s/mm2. SPEN also succeeded in decreasing occasional image distortions in regions close to the rectum, affected by field inhomogeneities. EPI advantages arose when using short effective TRs, a regime in which SPEN-based DWI was handicapped by its use of nonselective spin inversions, leading to the onset of an additional T1 weighting.

Original languageEnglish
Pages (from-to)643-654
Number of pages12
JournalMagnetic Resonance in Medicine
Volume90
Issue number2
DOIs
StatePublished - Aug 2023

Funding

FundersFunder number
Perlman Family Foundation
Minerva Foundation
Israel Science Foundation3594/21, 965/18

    Keywords

    • ADC mapping
    • LLR reconstruction
    • PI-RADS criteria
    • SPEN
    • diffusion-weighted imaging
    • prostate cancer

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