['This study investigated whether texture-based imaging parameters could identify invasive components of ductal carcinoma in situ (DCIS).', 'We enrolled 65 biopsy-confirmed DCIS patients (62 unilateral, 3 bilateral) who underwent (18)\u2009F-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.', '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\u2009=\u20090.017) and lower AUC-CSH (p\u2009<\u20090.001) on PET, higher TNR (p\u2009=\u20090.008) and COV (p\u2009=\u20090.035) on BSGI, lower ADC min (p\u2009=\u20090.016) and higher ADC diff (p\u2009=\u20090.009) on DWI, and larger pathologic size (p\u2009=\u20090.018). On multiple regression analysis, AUC-CSH was the only significant predictor of invasive components (p\u2009=\u20090.044).'] Does intratumoral metabolic heterogeneity predict invasive components in breast ductal carcinoma in situ?