Diffusion tensor imaging for characterizing tumor microstructure and improving diagnostic performance on breast MRI: a prospective observational study.
Background: Diffusion-weighted imaging (DWI) can increase breast MRI diagnostic specificity due to the tendency of malignancies to restrict diffusion. Diffusion tensor imaging (DTI) provides further information over conventional DWI regarding diffusion directionality and anisotropy. Our study evalua...
| Publicado en: | Breast Cancer Research Vol. 21; no. 1 |
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| Autores principales: | , , , , , |
| Formato: | Journal Article |
| Publicado: |
BioMed Central
9/4/2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=138430794&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 138430794 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14655411 8UYJ jtl: Breast Cancer Research issn: 14655411 maglogo: N pubinfo: dt: 9/4/2019 vid: 21 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 138430794 138430794 NLM31484577 10.1186/s13058-019-1183-3 NLM31484577 138430794 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Diffusion tensor imaging for characterizing tumor microstructure and improving diagnostic performance on breast MRI: a prospective observational study. aug: au: Luo, Jing Hippe, Daniel S. Rahbar, Habib Parsian, Sana Rendi, Mara H. Partridge, Savannah C. affil: Department of Radiology, University of Washington School of Medicine, 825 Eastlake Avenue East, 98109, Seattle, WA, USA sug: subj: Breast Breast Neoplasms Pathology Magnetic Resonance Imaging Breast Neoplasms Image Enhancement Methods Middle Age Young Adult Image Interpretation, Computer Assisted Cell Physiology Aged, 80 and Over Diagnosis, Differential ROC Curve Breast Pathology Contrast Media Prospective Studies Adult Aged Female Barthel Index Psychological Tests Scales Middle Aged: 45-64 years Aged, 80 & over Adult: 19-44 years Aged: 65+ years Female ab: Background: Diffusion-weighted imaging (DWI) can increase breast MRI diagnostic specificity due to the tendency of malignancies to restrict diffusion. Diffusion tensor imaging (DTI) provides further information over conventional DWI regarding diffusion directionality and anisotropy. Our study evaluates DTI features of suspicious breast lesions detected on MRI to determine the added diagnostic value of DTI for breast imaging.Methods: With IRB approval, we prospectively enrolled patients over a 3-year period who had suspicious (BI-RADS category 4 or 5) MRI-detected breast lesions with histopathological results. Patients underwent multiparametric 3 T MRI with dynamic contrast-enhanced (DCE) and DTI sequences. Clinical factors (age, menopausal status, breast density, clinical indication, background parenchymal enhancement) and DCE-MRI lesion parameters (size, type, presence of washout, BI-RADS category) were recorded prospectively by interpreting radiologists. DTI parameters (apparent diffusion coefficient [ADC], fractional anisotropy [FA], axial diffusivity [λ1], radial diffusivity [(λ2 + λ3)/2], and empirical difference [λ1 - λ3]) were measured retrospectively. Generalized estimating equations (GEE) and least absolute shrinkage and selection operator (LASSO) methods were used for univariate and multivariate logistic regression, respectively. Diagnostic performance was internally validated using the area under the curve (AUC) with bootstrap adjustment.Results: The study included 238 suspicious breast lesions (95 malignant, 143 benign) in 194 women. In univariate analysis, lower ADC, axial diffusivity, and radial diffusivity were associated with malignancy (OR = 0.37-0.42 per 1-SD increase, p < 0.001 for each), as was higher FA (OR = 1.45, p = 0.007). In multivariate analysis, LASSO selected only ADC (OR = 0.41) as a predictor for a DTI-only model, while both ADC (OR = 0.41) and FA (OR = 0.88) were selected for a model combining clinical and imaging parameters. Post-hoc analysis revealed varying association of FA with malignancy depending on the lesion type. The combined model (AUC = 0.81) had a significantly better performance than Clinical/DCE-MRI-only (AUC = 0.76, p < 0.001) and DTI-only (AUC = 0.75, p = 0.002) models.Conclusions: DTI significantly improves diagnostic performance in multivariate modeling. ADC is the most important diffusion parameter for distinguishing benign and malignant breast lesions, while anisotropy measures may help further characterize tumor microstructure and microenvironment. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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