Intratumoral metabolic heterogeneity predicts invasive components in breast ductal carcinoma in situ.
Objective: This study investigated whether texture-based imaging parameters could identify invasive components of ductal carcinoma in situ (DCIS).
Methods: We enrolled 65 biopsy-confirmed DCIS patients (62 unilateral, 3 bilateral) who underwent (18) F-FDG PET, diffusion-weighted imaging (DWI), or breast-specific gamma imaging (BSGI). We measured SUV max and intratumoral metabolic heterogeneity by the area under the curve (AUC) of cumulative SUV histograms (CSH) on PET, tumour-to-normal ratio (TNR) and coefficient of variation (COV) as an index of heterogeneity on BSGI, minimum ADC (ADC min ) and ADC difference (ADC diff ) as an index of heterogeneity on DWI. After surgery, final pathology was categorized as pure-DCIS (DCIS-P), DCIS with microinvasion (DCIS-MI), or invasive ductal carcinoma (IDC). Clinicopathologic features of DCIS were correlated with final classification.
Results: Final pathology confirmed 44 DCIS-P, 14 DCIS-MI, and 10 IDC. The invasive component of DCIS was significantly correlated with higher SUV max (p = 0.017) and lower AUC-CSH (p < 0.001) on PET, higher TNR (p = 0.008) and COV (p = 0.035) on BSGI, lower ADC min (p = 0.016) and higher ADC diff (p = 0.009) on DWI, and larger pathologic size (p = 0.018). On multiple regression analysis, AUC-CSH was the only significant predictor of invasive components (p = 0.044).
Conclusions: The intratumoral metabolic heterogeneity of (18) F-FDG PET was the most important predictor of invasive components of DCIS. Conclusions: • Preoperative identification of invasion in DCIS is important for axillary nodal management • Higher SUV max and lower AUC-CSH from FDG PET may indicate invasive components of DCIS • Higher TNR and COV from BSGI may indicate invasive components of DCIS • Lower ADC min and higher ADC diff from DWI may indicate invasive components of DCIS • AUC-CSH, an index of metabolic heterogeneity, is an independent predictor for invasive components.