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...

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Publicado en:Breast Cancer Research Vol. 21; no. 1
Autores principales: Luo, Jing, Hippe, Daniel S., Rahbar, Habib, Parsian, Sana, Rendi, Mara H., Partridge, Savannah C.
Formato: Journal Article
Publicado: BioMed Central 9/4/2019
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 9/4/2019
      vid: 21
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      pub: BioMed Central
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        10.1186/s13058-019-1183-3
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        atl: Diffusion tensor imaging for characterizing tumor microstructure and improving diagnostic performance on breast MRI: a prospective observational study.
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          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
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