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Updated: Feb 25, 2026

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Role of exponential apparent diffusion coefficient in characterizing breast lesions by 3.0 Tesla diffusion-weighted
Shweta Kothari1, Archana Singh1, Utpalendu Das1
1Department of Radio Diagnosis, IPGME and R and SSKM Hospital, Kolkata, West Bengal, India.
Objective:
To evaluate the role of exponential apparent diffusion coefficient (ADC) as a tool for differentiating benign and malignant breast lesions.
Patients And Methods:
This prospective observational study included 88 breast lesions in 77 patients (between 18 and 85 years of age) who underwent 3T breast magnetic resonance imaging (MRI) including diffusion-weighted imaging (DWI) using b-values of 0 and 800 s/mm2 before biopsy. Mean exponential ADC and ADC of benign and malignant lesions obtained from DWI were compared. Receiver operating characteristics (ROC) curve analysis was undertaken to identify any cut-off for exponential ADC and ADC to predict malignancy. P value of <0.05 was considered statistically significant. Histopathology was taken as the gold standard.
Results:
According to histopathology, 65 lesions were malignant and 23 were benign. The mean ADC and exponential ADC values of malignant lesions were 0.9526 ± 0.203 × 10-3 mm2/s and 0.4774 ± 0.071, respectively, and for benign lesions were 1.48 ± 0.4903 × 10-3 mm2/s and 0.317 ± 0.1152, respectively. For both the parameters, differences were highly significant (P < 0.001). Cut-off value of ≤0.0011 mm2/s (P < 0.0001) for ADC provided 92.3% sensitivity and 73.9% specificity, whereas with an exponential ADC cut-off value of >0.4 (P < 0.0001) for malignant lesions, 93.9% sensitivity and 82.6% specificity was obtained. The performance of ADC and exponential ADC in distinguishing benign and malignant breast lesions based on respective cut-offs was comparable (P = 0.109).
Conclusion:
Exponential ADC can be used as a quantitative adjunct tool for characterizing breast lesions with comparable sensitivity and specificity as that of ADC.

