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Diffusivity in breast malignancies analyzed for b > 1000 s/mm 2 at 1 mm in‐plane resolutions: Insight from Gaussian and non‐Gaussian behaviors
Author(s) -
Otikovs Martins,
Nissan Noam,
FurmanHaran Edna,
Anaby Debbie,
Allweis Tanir M.,
Agassi Ravit,
SklairLevy Miri,
Frydman Lucio
Publication year - 2021
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.27489
Subject(s) - kurtosis , breast cancer , nuclear medicine , gaussian , effective diffusion coefficient , diffusion mri , medicine , breast imaging , breast mri , magnetic resonance imaging , nuclear magnetic resonance , mathematics , physics , mammography , radiology , cancer , statistics , quantum mechanics
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 T 1 weighting; anatomies were evaluated with T 2 ‐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.
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