Diffusivity in breast malignancies analyzed for b > 1000 s/mm2 at 1 mm in‐plane resolutions: Insight from Gaussian and non‐Gaussian behaviors. Issue 6 (26th December 2020)

• Record Type: Journal Article
• Authors: Otikovs, Martins; Nissan, Noam; Furman‐Haran, Edna; Anaby, Debbie; Allweis, Tanir M.; Agassi, Ravit; Sklair‐Levy, Miri; Frydman, Lucio
• Is Part Of: Journal of magnetic resonance imaging. Volume 53:Issue 6(2021)
• Page Start: 1913
• Page End: 1925
• Publication Date: 2020-12-26
• Subjects: breast cancer diagnosis -- diffusion‐weighted imaging -- spatiotemporal encoding -- diffusion kurtosis imaging; Magnetic resonance imaging -- Periodicals; 616
• DOI: 10.1002/jmri.27489
• Languages: English
• ISSNs: 1053-1807

Abstract

Abstract: Diffusion‐weighted imaging (DWI) can improve breast cancer characterizations, but often suffers from low image quality –particularly at informative b > 1000 s/mm 2 values. The aim of this study was to evaluate multishot approaches characterizing Gaussian and non‐Gaussian diffusivities in breast cancer. This was a prospective study, in which 15 subjects, including 13 patients with biopsy‐confirmed breast cancers, were enrolled. DWI was acquired at 3 T using echo planar imaging (EPI) with and without zoomed excitations, readout‐segmented EPI (RESOLVE), and spatiotemporal encoding (SPEN); dynamic contrast‐enhanced (DCE) data were collected using three‐dimensional gradient‐echo T1 weighting; anatomies were evaluated with T2 ‐weighted two‐dimensional turbo spin‐echo. Congruence between malignancies delineated by DCE was assessed against high‐resolution DWI scans with b‐values in the 0–1800 s/mm 2 range, as well as against apparent diffusion coefficient (ADC) and kurtosis maps. Data were evaluated by independent magnetic resonance scientists with 3–20 years of experience, and radiologists with 6 and 20 years of experience in breast MRI. Malignancies were assessed from ADC and kurtosis maps, using paired t tests after confirming that these values had a Gaussian distribution. Agreements between DWI and DCE datasets were also evaluated using Sorensen–Dice similarity coefficients. Cancerous and normal tissues were clearly separable by ADCs: by SPEN their average values were (1.03 ± 0.17) × 10 −3 and (1.69 ± 0.19) × 10 −3 mm 2 /s ( p < 0.0001); by RESOLVE these values were (1.16 ± 0.16) × 10 −3 and (1.52 ± 0.14) × 10 −3 ( p = 0.00026). Kurtosis also distinguished lesions ( K = 0.64 ± 0.15) from normal tissues ( K = 0.45 ± 0.05), but only when measured by SPEN ( p = 0.0008). The best statistical agreement with DCE‐highlighted regions arose for SPEN‐based DWIs recorded with b = 1800 s/mm 2 (Sorensen–Dice coefficient = 0.67); DWI data recorded with b = 850 and 1200 s/mm 2, led to lower coefficients. Both ADC and kurtosis maps highlighted the breast malignancies, with ADCs providing a more significant separation. The most promising alternative for contrast‐free delineations of the cancerous lesions arose from b = 1800 s/mm 2 DWI. Level of Evidence: 2. Technical Efficacy Stage: 3.