Diffusion-Weighted Imaging of Breast Masses: Comparison of Diagnostic Performance Using Various Apparent Diffusion Coefficient Parameters

The purpose of our study was to assess the utility of the minimum apparent diffusion coefficient (ADC), average ADC, maximum ADC, and ADC difference value and to find optimum ADC parameters for differentiation between benign and malignant lesions in breast diffusion-weighted imaging (DWI). Sixty-sev...

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Veröffentlicht in:American journal of roentgenology (1976) 2012-03, Vol.198 (3), p.717-722
Hauptverfasser: HIRANO, Maki, SATAKE, Hiroko, ISHIGAKI, Satoko, IKEDA, Mitsuru, KAWAI, Hisashi, NAGANAWA, Shinji
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container_issue 3
container_start_page 717
container_title American journal of roentgenology (1976)
container_volume 198
creator HIRANO, Maki
SATAKE, Hiroko
ISHIGAKI, Satoko
IKEDA, Mitsuru
KAWAI, Hisashi
NAGANAWA, Shinji
description The purpose of our study was to assess the utility of the minimum apparent diffusion coefficient (ADC), average ADC, maximum ADC, and ADC difference value and to find optimum ADC parameters for differentiation between benign and malignant lesions in breast diffusion-weighted imaging (DWI). Sixty-seven women with 75 masslike lesions (27 benign, 48 malignant) were examined with 3-T MRI. To assess heterogeneity within the lesion, the difference between minimum and maximum ADCs was recorded as the ADC difference value. Diagnostic performances of these parameters were compared by receiver operating characteristic (ROC) curve analysis. Each ADC parameter showed significant differences between malignant and benign lesions. The optimal cutoff levels for differentiating benign versus malignant lesions were determined by identifying the points where the sensitivity and specificity were equal on the ROC curves. According to ROC analyses, the following sensitivities and specificities were obtained: average ADC, 75.6% and 75.6%; minimum ADC, 85.5% and 85.5%; maximum ADC, 63.5% and 63.5%; ADC difference value, 70.1% and 70.1%. Minimum ADC had the largest area under the ROC curve (AUC) of 0.93. Minimum ADC combined with the ADC difference value improved the AUC to 0.95, with sensitivity and specificity of 89.1% and 89.1%. Minimum ADC may be an optimal DWI single parameter for differentiation between malignant and benign lesions of breast masses. Furthermore, the combination of the minimum ADC and ADC difference value significantly elevated diagnostic performance of breast DWI in comparison with average ADC.
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Sixty-seven women with 75 masslike lesions (27 benign, 48 malignant) were examined with 3-T MRI. To assess heterogeneity within the lesion, the difference between minimum and maximum ADCs was recorded as the ADC difference value. Diagnostic performances of these parameters were compared by receiver operating characteristic (ROC) curve analysis. Each ADC parameter showed significant differences between malignant and benign lesions. The optimal cutoff levels for differentiating benign versus malignant lesions were determined by identifying the points where the sensitivity and specificity were equal on the ROC curves. According to ROC analyses, the following sensitivities and specificities were obtained: average ADC, 75.6% and 75.6%; minimum ADC, 85.5% and 85.5%; maximum ADC, 63.5% and 63.5%; ADC difference value, 70.1% and 70.1%. Minimum ADC had the largest area under the ROC curve (AUC) of 0.93. 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source American Roentgen Ray Society; MEDLINE; Alma/SFX Local Collection
subjects Adolescent
Adult
Aged
Aged, 80 and over
Biological and medical sciences
Breast Neoplasms - diagnosis
Breast Neoplasms - pathology
Contrast Media
Diagnosis, Differential
Diffusion Magnetic Resonance Imaging - methods
Female
Gadolinium DTPA
Gynecology. Andrology. Obstetrics
Humans
Image Interpretation, Computer-Assisted
Investigative techniques, diagnostic techniques (general aspects)
Mammary gland diseases
Medical sciences
Middle Aged
Retrospective Studies
ROC Curve
Sensitivity and Specificity
Statistics, Nonparametric
Tumors
title Diffusion-Weighted Imaging of Breast Masses: Comparison of Diagnostic Performance Using Various Apparent Diffusion Coefficient Parameters
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