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Diffusivity in breast malignancies analyzed for b > 1000 s/mm2 at 1 mm in‐plane resolutions: Insight from Gaussian and non‐Gaussian behaviors

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Diffusion‐weighted imaging (DWI) can improve breast cancer characterizations, but often suffers from low image quality –particularly at informative b > 1000 s/mm2 values. The aim of this study was to evaluate multishot approaches… Click to show full abstract

Diffusion‐weighted imaging (DWI) can improve breast cancer characterizations, but often suffers from low image quality –particularly at informative b > 1000 s/mm2 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/mm2 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 mm2/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/mm2 (Sorensen–Dice coefficient = 0.67); DWI data recorded with b = 850 and 1200 s/mm2, 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/mm2 DWI.

Keywords: breast malignancies; breast; non gaussian; mm2; 1000 mm2; gaussian non

Journal Title: Journal of Magnetic Resonance Imaging
Year Published: 2020

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