Background: The MRI Breast Imaging-Reporting and Data System (BI-RADS) lexicon recommends that a breast MRI protocol contain T2-weighted and dynamic contrast-enhanced (DCE) MRI sequences. The addition of diffusion-weighted imaging (DWI) significantly improves diagnostic accuracy. This study aims to clarify which descriptors from DCE-MRI, DWI, and T2-weighted imaging are most strongly associated with a breast cancer diagnosis. Purpose/Hypothesis: To develop a multiparametric MRI (mpMRI) model for breast cancer diagnosis incorporating American College of Radiology (ACR) BI-RADS recommended descriptors for breast MRI with DCE, T2-weighted imaging, and DWI with apparent diffusion coefficient (ADC) mapping. Study Type: Retrospective. Subjects: In all, 188 patients (mean 51.6 years) with 210 breast tumors (136 malignant and 74 benign) who underwent mpMRI from December 2010 to September 2014. Field Strength/Sequence: IR inversion recovert DCE-MRI dynamic contrast-enhanced magnetic resonance imaging VIBE Volume-Interpolated-Breathhold-Examination FLASH turbo fast-low-angle-shot TWIST Time-resolved angiography with stochastic Trajectories. Assessment: Two radiologists in consensus and another radiologist independently evaluated the mpMRI data. Characteristics for mass (n = 182) and nonmass (n = 28) lesions were recorded on DCE and T2-weighted imaging according to BI-RADS, as well as DWI descriptors. Two separate models were analyzed, using DCE-MRI BI-RADS descriptors, T2-weighted imagines, and ADCmean as either a continuous or binary form using a previously published ADC cutoff value of ≤1.25 × 10−3 mm2/sec for differentiation between benign and malignant lesions. Histopathology was the standard of reference. Statistical Tests: χ2 test, Fisher’s exact test, Kruskal–Wallis test, Pearson correlation coefficient, multivariate logistic regression analysis, Hosmer–Lemeshow test of goodness-of-fit, receiver operating characteristics analysis. Results: In Model 1, ADCmean (P = 0.0031), mass margins with DCE (P = 0.0016), and delayed enhancement with DCE (P = 0.0016) were significantly and independently associated with breast cancer diagnosis; Model 2 identified ADCmean (P = 0.0031), mass margins with DCE (P = 0.0012), initial enhancement (P = 0.0422), and delayed enhancement with DCE (P = 0.0065) to be significantly independently associated with breast cancer diagnosis. T2-weighted imaging variables were not included in the final models. Data Conclusion: mpMRI with DCE-MRI and DWI with ADC mapping enables accurate breast cancer diagnosis. A model using quantitative and qualitative descriptors from DCE-MRI and DWI identifies breast cancer with a high diagnostic accuracy. T2-weighted imaging does not significantly contribute to breast cancer diagnosis. Level of Evidence: 3 Technical Efficacy: Stage 2

Multiparametric MRI model with dynamic contrast-enhanced and diffusion-weighted imaging enables breast cancer diagnosis with high accuracy

Marino M. A.;
2019-01-01

Abstract

Background: The MRI Breast Imaging-Reporting and Data System (BI-RADS) lexicon recommends that a breast MRI protocol contain T2-weighted and dynamic contrast-enhanced (DCE) MRI sequences. The addition of diffusion-weighted imaging (DWI) significantly improves diagnostic accuracy. This study aims to clarify which descriptors from DCE-MRI, DWI, and T2-weighted imaging are most strongly associated with a breast cancer diagnosis. Purpose/Hypothesis: To develop a multiparametric MRI (mpMRI) model for breast cancer diagnosis incorporating American College of Radiology (ACR) BI-RADS recommended descriptors for breast MRI with DCE, T2-weighted imaging, and DWI with apparent diffusion coefficient (ADC) mapping. Study Type: Retrospective. Subjects: In all, 188 patients (mean 51.6 years) with 210 breast tumors (136 malignant and 74 benign) who underwent mpMRI from December 2010 to September 2014. Field Strength/Sequence: IR inversion recovert DCE-MRI dynamic contrast-enhanced magnetic resonance imaging VIBE Volume-Interpolated-Breathhold-Examination FLASH turbo fast-low-angle-shot TWIST Time-resolved angiography with stochastic Trajectories. Assessment: Two radiologists in consensus and another radiologist independently evaluated the mpMRI data. Characteristics for mass (n = 182) and nonmass (n = 28) lesions were recorded on DCE and T2-weighted imaging according to BI-RADS, as well as DWI descriptors. Two separate models were analyzed, using DCE-MRI BI-RADS descriptors, T2-weighted imagines, and ADCmean as either a continuous or binary form using a previously published ADC cutoff value of ≤1.25 × 10−3 mm2/sec for differentiation between benign and malignant lesions. Histopathology was the standard of reference. Statistical Tests: χ2 test, Fisher’s exact test, Kruskal–Wallis test, Pearson correlation coefficient, multivariate logistic regression analysis, Hosmer–Lemeshow test of goodness-of-fit, receiver operating characteristics analysis. Results: In Model 1, ADCmean (P = 0.0031), mass margins with DCE (P = 0.0016), and delayed enhancement with DCE (P = 0.0016) were significantly and independently associated with breast cancer diagnosis; Model 2 identified ADCmean (P = 0.0031), mass margins with DCE (P = 0.0012), initial enhancement (P = 0.0422), and delayed enhancement with DCE (P = 0.0065) to be significantly independently associated with breast cancer diagnosis. T2-weighted imaging variables were not included in the final models. Data Conclusion: mpMRI with DCE-MRI and DWI with ADC mapping enables accurate breast cancer diagnosis. A model using quantitative and qualitative descriptors from DCE-MRI and DWI identifies breast cancer with a high diagnostic accuracy. T2-weighted imaging does not significantly contribute to breast cancer diagnosis. Level of Evidence: 3 Technical Efficacy: Stage 2
2019
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3160071
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