Diffusion-weighted breast MRI of malignancies with submillimeter resolution and immunity to artifacts by spatiotemporal encoding at 3T

Eddy Solomon, Gilad Liberman, Noam Nissan, Edna Furman-Haran, Miri Sklair-Levy, Lucio Frydman*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Purpose: Diffusion weighted imaging (DWI) is increasingly used in evaluating breast cancer, as complement to DCE measurements of superior spatial resolution. Extracting fine morphological features in DWI is complicated by limitations that sequences such as EPI face, when applied to heterogeneous organs. This study investigates the ability of spatiotemporal encoding (SPEN) MRI to screen breast cancers and define diffusivity features at mm and sub-mm resolutions on a 3T scanner. Methods: Twenty-one patients with biopsy-confirmed breast cancer lesions were examined by T2-weighted and DCE protocols, by EPI-based DWI, and by SPEN-based protocols optimized for SNR, robustness and spatial resolution, respectively. Results: Excellent agreement was found between the diffusivity parameters measured by all SPEN protocols and by EPI, with the lower ADCs characteristic of tumors being readily detected. SPEN provided systematically better SNR and improved qualitative results, particularly when dealing with small lesions surrounded by fatty tissue, or lesions close to tissue/air interfaces. SPEN-derived ADC maps collected at sub-mm in-plane resolutions recapitulated the high-resolution morphology shown by lesions using more sensitive DCE protocols. Conclusion: Measurements on a patient cohort validated SPEN’s ability to quantify the diffusivity changes associated with the presence of breast cancers, while imaging the lesions with reduced distortions at sub-mm resolutions.

Original languageEnglish
Pages (from-to)1391-1403
Number of pages13
JournalMagnetic Resonance in Medicine
Volume84
Issue number3
DOIs
StatePublished - 1 Sep 2020

Funding

FundersFunder number
ERC-2016-PoC
Kimmel Institute of Magnetic Resonance
MRI technical team
Sheba MC -Weizmann Institute Joint Research Program
Horizon 2020 Framework Programme751106
Perlman Family Foundation
Israel Science Foundation965/18, 2508/17

    Keywords

    • breast MRI
    • breast cancer
    • diffusion-weighted imaging
    • multiband spatiotemporal encoding
    • sub-mm resolution

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