2 research outputs found
Stromal collagen content in breast tumors correlates with in vivo diffusion-weighted imaging: A comparison of multi b-value DWI with histologic specimen from benign and malignant breast lesions
Background:Increased deposition and reorientation of stromal collagenfibers are associated with breast cancer progres-sion and invasiveness. Diffusion-weighted imaging (DWI) may be sensitive to the collagenfiber organization in the stromaand could provide important biomarkers for breast cancer characterization.Purpose:To understand how collagenfibers influence water diffusion in vivo and evaluate the relationship between colla-gen content and the apparent diffusion coefficient (ADC) and the signal fractions of the biexponential model using a highb-value scheme.Study Type:Prospective.Subjects/Specimens:Forty-five patients with benign (n= 8), malignant (n= 36), and ductal carcinoma in situ (n= 1) breasttumors. Lesions and normalfibroglandular tissue (n= 9) were analyzed using sections of formalin-fixed, paraffin-embeddedtissue stained with hematoxylin, erythrosine, and saffron.Field Strength/Sequence:MRI (3T) protocols:Protocol I:Twice-refocused spin-echo echo-planar imaging with: echo time(TE) 85 msec; repetition time (TR) 9300/11600 msec; matrix 90Ă90Ă60; voxel size 2Ă2Ă2.5 mm3;b-values: 0 and700 s/mm2.Protocol II:StejskalâTanner spin-echo echo-planar imaging with: TE: 88 msec; TR: 10600/11800 msec, matrix90Ă90Ă60; voxel size 2Ă2Ă2.5 mm3;b-values [0, 200, 600, 1200, 1800, 2400, 3000] s/mm2.Assessment:Area fractions of cellular and collagen content in histologic sections were quantified using whole-slide imageanalysis and compared with the corresponding DWI parameters.Statistical Tests:Correlations were assessed using Pearsonâsr. Univariate analysis of group median values was done usingthe MannâWhitneyU-test.Results:Collagen content correlated with the fast signal fraction (r= 0.67,P< 0.001) and ADC (r= 0.58,P< 0.001) andwas lower (P< 0.05) in malignant lesions than benign and normal tissues. Cellular content correlated inversely with the fastsignal fraction (r=â0.67,P< 0.001) and ADC (r=â0.61,P< 0.001) and was different (P< 0.05) between malignant,benign, and normal tissues.Data Conclusion:Ourfindings suggest stromal collagen content increases diffusivity observed by MRI and is associatedwith higher ADC and fast signal fraction of the biexponential mode
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Modeling the diffusion-weighted imaging signal for breast lesions in the b = 200 to 3000 s/mm 2 range: quality of fit and classification accuracy for different representations
Purpose
To evaluate different nonâGaussian representations for the diffusionâweighted imaging (DWI) signal in the bâvalue range 200 to 3000 s/mm2 in benign and malignant breast lesions.
Methods
Fortyâthree patients diagnosed with benign (n = 18) or malignant (n = 25) tumors of the breast underwent DWI (bâvalues 200, 600, 1200, 1800, 2400, and 3000 s/mm2). Six different representations were fit to the average signal from regions of interest (ROIs) at different bâvalue ranges. Quality of fit was assessed by the corrected Akaike information criterion (AICc), and the Friedman test was used for assessing representation ranks. The area under the curve (AUC) of receiver operating characteristic curves were used to evaluate the power of derived parameters to differentiate between malignant and benign lesions. The lesion ROI was divided in central and peripheral parts to assess potential effect of heterogeneity. Sensitivity to noiseâfloor correction was also evaluated.
Results
The PadĂ© exponent was ranked as the best based on AICc, whereas 3 models (kurtosis, fractional, and biexponential) achieved the highest AUC = 0.99 for lesion differentiation. The monoexponential model at bmax = 600 s/mm2 already provides AUC = 0.96, with considerably shorter acquisition time and simpler analysis. Significant differences between central and peripheral parts of lesions were found in malignant lesions. The monoâ and biexponential models were most stable against varying degrees of noiseâfloor correction.
Conclusion
NonâGaussian representations are required for fitting of the DWI curve at high bâvalues in breast lesions. However, the added clinical value from the high bâvalue data for differentiation of benign and malignant lesions is not clear