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This prospective study suggests that FDG PET/CT can more accurately stage mediastinal lymph nodes than CT. Considering lymph node calcification and distribution pattern could improve specificity at the cost of a decrease in sensitivity.

• 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.

A high FDG uptake of breast tumor is correlated with several poor prognosis factors, such as tumor invasiveness >2 cm, higher tumor grade, higher MIB-1, hormonal receptor negativity, and triple negativity. However, PET has a limited value in discriminating axillary lymph nodes. Pre-operative PET is a useful modality to predict biologic poor prognosis factors which could affect adjunctive therapy of breast cancer.

Predicting response to neo-adjuvant chemotherapy (NAC) and survival in locally advanced breast cancer (LABC) is important. This study investigated the prognostic value of tumor heterogeneity evaluated with textural analysis through F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) and diffusion-weighted imaging (DWI). We enrolled 83 patients with LABC who had completed NAC and curative surgery. Tumor texture indices from pretreatment FDG PET and DWI were extracted from histogram analysis and 7 different parent matrices: co-occurrence matrix, the voxel-alignment matrix, neighborhood intensity difference matrix, intensity size-zone matrix (ISZM), normalized gray-level co-occurrence matrix (NGLCM), neighboring gray-level dependence matrix (NGLDM), and texture spectrum matrix. The predictive values of textural features were tested regarding both pathologic NAC response and progression-free survival. Among 83 patients, 46 were pathologic responders, while 37 were nonresponders. The PET texture indices from 7 parent matrices, DWI texture indices from histogram, and 1 parent matrix (NGLCM) showed significant differences according to NAC response. On multivariable analysis, number nonuniformity of PET extracted from the NGLDM was an independent predictor of pathologic response (P = .009). During a median follow-up period of 17.3 months, 14 patients experienced recurrence. High-intensity zone emphasis (HIZE) and high-intensity short-zone emphasis (HISZE) from PET extracted from ISZM were significant textural predictors (P = .011 and P = .033). On Cox regression analysis, only HIZE was a significant predictor of recurrence (P = .027), while HISZE showed borderline significance (P = .107). Tumor texture indices are useful for NAC response prediction in LABC. Moreover, PET texture indices can help to predict disease recurrence.

BSGI showed an equivocal sensitivity and a high specificity compared to MRI in the diagnosis of breast lesions. In addition, BSGI had a good sensitivity in discriminating breast cancers ≤1 cm. The results of this study suggest that BSGI could play a crucial role as an adjunctive imaging modality which can be used to evaluate breast cancer patients with dense breasts.