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    Online Resource
    Online Resource
    Ovid Technologies (Wolters Kluwer Health) ; 2019
    In:  Journal of Computer Assisted Tomography Vol. 43, No. 3 ( 2019-5), p. 434-442
    In: Journal of Computer Assisted Tomography, Ovid Technologies (Wolters Kluwer Health), Vol. 43, No. 3 ( 2019-5), p. 434-442
    Abstract: Motivated by the similar appearance of malignant breast lesions in high b -value diffusion-weighted imaging (DWI) and positron emission tomography, the purpose of this work was to evaluate the applicability of a threshold isocontouring approach commonly used in positron emission tomography to analyze DWI data acquired from female human breasts with minimal interobserver variability. Methods Twenty-three female participants (59.4 ± 10.0 years) with 23 lesions initially classified as suggestive of cancers in x-ray mammography screening were subsequently imaged on a 1.5-T magnetic resonance imaging scanner. Diffusion-weighted imaging was performed prior to biopsy with b values of 0, 100, 750, and 1500 s/mm 2 . Isocontouring with different threshold levels was performed on the highest b -value image to determine the voxels used for subsequent evaluation of diffusion metrics. The coefficient of variation was computed by specifying 4 different regions of interest drawn around the lesion. Additionally, a receiver operating statistical analysis was performed. Results Using a relative threshold level greater than or equal to 0.85 almost completely suppresses the intra-individual and inter-individual variability. Among 4 studied diffusion metrics, the diffusion coefficients from the intravoxel incoherent motion model returned the highest area under curve value of 0.9. The optimal cut-off diffusivity was found to be 0.85 μm 2 /ms with a sensitivity of 87.5% and specificity of 90.9%. Conclusion Threshold isocontouring on high b -value maps is a viable approach to reliably evaluate DWI data of suspicious focal lesions in magnetic resonance mammography.
    Type of Medium: Online Resource
    ISSN: 1532-3145 , 0363-8715
    RVK:
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2019
    detail.hit.zdb_id: 2039772-0
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