Preoperative predicting malignancy in breast mass-like lesions: value of adding histogram analysis of apparent diffusion coefficient maps to dynamic contrast-enhanced magnetic resonance imaging for improving confidence level
| Autor: | Min Zong, Qi-Gui Zou, Hai-Bin Shi, Hong-Li Liu, Han Wei, Siqi Wang, Jianjuan Lou, Yanni Jiang |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Adult
Pathology medicine.medical_specialty Contrast Media Breast Neoplasms Logistic regression Malignancy 030218 nuclear medicine & medical imaging Diagnosis Differential 03 medical and health sciences 0302 clinical medicine Histogram Medicine Effective diffusion coefficient Humans Radiology Nuclear Medicine and imaging Breast skin and connective tissue diseases Retrospective Studies medicine.diagnostic_test Receiver operating characteristic Full Paper business.industry Univariate Magnetic resonance imaging General Medicine Middle Aged medicine.disease Magnetic Resonance Imaging Confidence interval ROC Curve 030220 oncology & carcinogenesis Area Under Curve Regression Analysis Female business Nuclear medicine |
| Popis: | This study aims to find out the benefits of adding histogram analysis of apparent diffusion coefficient (ADC) maps onto dynamic contrast-enhanced MRI (DCE-MRI) in predicting breast malignancy.This study included 95 patients who were found with breast mass-like lesions from January 2014 to March 2016 (47 benign and 48 malignant). These patients were estimated by both DCE-MRI and diffusion-weighted imaging (DWI) and classified into two groups, namely, the benign and the malignant. Between these groups, the DCE-MRI parameters, including morphology, enhancement homogeneity, maximum slope of increase (MSI) and time-signal intensity curve (TIC) type, as well as histogram parameters generated from ADC maps were compared. Then, univariate and multivariate logistic regression analyses were conducted to determine the most valuable variables in predicting malignancy. Receiver operating characteristic curve analyses were taken to assess their clinical values.The lesion morphology, MSI and TIC Type (p0.05) were significantly different between the two groups. Multivariate logistic regression analyses revealed that irregular morphology, TIC Type II/III and ADCIrregular morphology, TIC Type II/III and ADC |
| Databáze: | OpenAIRE |
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