Peritumoral-to-tumoral apparent diffusion coefficient ratio as a marker of tumor microenvironment activity across breast cancer molecular subtypes.

[PURPOSE] This study aimed to evaluate the prognostic significance of tumoral apparent diffusion coefficient (tADC), peritumoral ADC (pADC), and the peritumoral-to-tumoral ADC (p/tADC) ratio in invasive breast cancers using high-resolution diffusion-weighted imaging.

[METHODS] A retrospective cohort of 149 patients with invasive breast cancer was analyzed. pADC, tADC, and p/tADC values were independently measured by two experienced radiologists. The associations between these parameters and histological grade, receptor status, Ki-67 index, and molecular subtypes were assessed. Interobserver agreement was evaluated using the intraclass correlation coefficient (ICC), and multivariate logistic regression was performed to identify independent predictors.

[RESULTS] Although tADC was significantly associated only with tumor size ( < 0.050), both pADC and p/tADC were significantly associated with high histological grade, estrogen receptor/progesterone receptor negativity, human epidermal growth factor receptor 2 positivity, and high Ki-67 index ( < 0.01). The p/tADC ratio emerged as an independent predictor of high-grade tumors and Ki-67 ≥ 20%. Excellent interobserver agreement was observed for all ADC measurements (ICC > 0.90).

[CONCLUSION] The p/tADC ratio reflects stromal and microenvironmental alterations associated with tumor aggressiveness and demonstrates stronger prognostic relevance than tADC alone. Incorporating the p/tADC ratio into routine magnetic resonance imaging (MRI) interpretation may improve preoperative risk stratification and support personalized treatment planning in invasive breast cancer.

[CLINICAL SIGNIFICANCE] The p/tADC ratio reflects stromal and microenvironmental changes associated with tumor aggressiveness and may serve as a noninvasive imaging biomarker. Its integration into preoperative MRI protocols may facilitate risk stratification and personalized treatment planning.