초록/요약

Objectives: 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 SUVmax 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 (ADCmin) and ADC difference (ADCdiff) 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 SUVmax (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 ADCmin (p = 0.016) and higher ADCdiff (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. Key Points: • Preoperative identification of invasion in DCIS is important for axillary nodal management • Higher SUVmaxand 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 ADCminand higher ADCdifffrom DWI may indicate invasive components of DCIS • AUC-CSH, an index of metabolic heterogeneity, is an independent predictor for invasive components © 2015, European Society of Radiology.