Introduction of a breast apparent diffusion coefficient category system (ADC-B) derived from a large multicenter MRI...

Area of Science:

• Radiology
• Oncology
• Medical Imaging

Background:

• Standard BI-RADS criteria may benefit from complementary assessment tools for breast lesions.
• Apparent Diffusion Coefficient (ADC) measurements in MRI offer insights into tissue characteristics.

Purpose of the Study:

• To develop and validate a user-friendly Breast Apparent Diffusion Coefficient (ADC-B) categorization system.
• To enhance the reporting, assessment, and documentation of breast lesions using ADC values.
• To complement existing BI-RADS criteria for improved diagnostic accuracy.

Main Methods:

• Multicentric retrospective analysis of 11 studies (2007-2019) involving 1625 patients and 1736 breast lesions.
• Development of ADC-B categories (ADC-B0-5) based on ADC values and cumulative malignancy rates.
• Statistical analysis including ANOVA, post hoc testing, and ROC analysis.

Main Results:

• Significant differences in mean ADC values were observed between benign and malignant lesions, and between invasive and in situ carcinomas (p < .001).
• The ADC-B categories were defined, with ADC-B5 (ADC < 1.0) showing a >24.5% cumulative malignancy rate.
• A positive predictive value of 95.8% was achieved for invasive versus non-invasive breast carcinomas at the ADC-B5 threshold.

Conclusions:

• The ADC-B system provides a simple, applicable categorization scheme for reporting ADC values in contrast-enhancing breast lesions on MRI.
• The ADC-B system is clinically relevant for stratifying breast cancer risk and complements BI-RADS for improved decision-making.
• This system offers a valuable tool for assessment and documentation, potentially improving patient outcomes.