Treatment recommendations made by WFO and the tumor board were highly concordant for breast cancer cases examined. Breast cancer stage and patient age had significant influence on concordance, while receptor status alone did not. This study demonstrates that the AI clinical decision-support system WFO may be a helpful tool for breast cancer treatment decision making, especially at centers where expert breast cancer resources are limited.

Background Pericardial fat volume (PFV) and thoracic fat volume (TFV) can be routinely measured from noncontrast CT (NCT) performed for calculating coronary calcium score (CCS) and may predict major adverse cardiovascular event (MACE) risk. Methods From a registry of 2751 asymptomatic patients without known CAD and 4-year follow-up for MACE (cardiac death, myocardial infarction, stroke, late revascularization) after NCT, we compared 58 patients with MACE (“EVENTS”) to 174 same-sex event-free controls matched by a propensity score to account for age, risk factors, and CCS. TFV was automatically calculated, and PFV was calculated with manual assistance in defining the pericardial contour, within which fat voxels were automatically identified. Independent relationships of PFV and TFV to MACE were evaluated using conditional multivariable logistic regression. Results EVENTS had higher mean PFV (101.8±49.2 cm3 vs. 84.9±37.7 cm3, p=0.007) and TFV (204.7±90.3 cm3 vs. 177±80.3 cm3, p=0.029) and higher frequencies of PFV>125 cm3 (33% vs. 14%, p=0.002) and TFV>250 cm3 (31% vs. 17%, p=0.025). After adjusting for Framingham Risk Score, CCS, and body-mass-index, PFV and TFV were significantly associated with MACE (odds ratio (OR) 1.74, 95%CI 1.03–2.95 for each doubling of PFV; OR 1.78, 95%CI 1.01–3.14 for TFV). Areas-under-the-curve from receiver operating characteristic analyses showed a trend of improved MACE prediction when PFV was added to FRS and CCS (0.73 vs 0.68, p=0.058). Addition of PFV, but not TFV, to FRS and CCS improved estimated specificity (0.72 vs 0.66, p=0.008) and overall accuracy (0.70 vs 0.65, p=0.009) in predicting MACE. Conclusion Asymptomatic patients who experience MACE exhibit greater PFV on pre-MACE NCT when compared to event-free controls with similar cardiovascular risk profiles. Our preliminary findings suggest that PFV may help improve prediction of MACE.

Introduction-Pericardial fat is emerging as an important parameter for cardiovascular risk stratification. We extended previously developed quantitation of thoracic fat volume (TFV) from non-contrast coronary calcium (CC) CT scans to also quantify pericardial fat volume (PFV) and investigated the associations of PFV and TFV with CC and the Metabolic Syndrome (METS).

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