Novel 3D magnetic resonance fingerprinting radiomics in adult brain tumors: a feasibility study.

OBJECTIVES: To test the feasibility of using 3D MRF maps with radiomics analysis and machine learning in the characterization of adult brain intra-axial neoplasms. METHODS: 3D MRF acquisition was performed on 78 patients with newly diagnosed brain tumors including 33 glioblastomas (grade IV), 6 grade III gliomas, 12 grade II gliomas, and 27 patients with brain metastases. Regions of enhancing tumor, non-enhancing tumor, and peritumoral edema were segmented and radiomics analysis with gray-level co-occurrence matrices and gray-level run-length matrices was performed. Statistical analysis was performed to identify features capable of differentiating tumors based on type, grade, and isocitrate dehydrogenase (IDH1) status. Receiver operating curve analysis was performed and the area under the curve (AUC) was calculated for tumor classification and grading. For gliomas, Kaplan-Meier analysis for overall survival was performed using MRF T1 features from enhancing tumor region. RESULTS: Multiple MRF T1 and T2 features from enhancing tumor region were capable of differentiating glioblastomas from brain metastases. Although no differences were identified between grade 2 and grade 3 gliomas, differentiation between grade 2 and grade 4 gliomas as well as between grade 3 and grade 4 gliomas was achieved. MRF radiomics features were also able to differentiate IDH1 mutant from the wild-type gliomas. Radiomics T1 features for enhancing tumor region in gliomas correlated to overall survival (p < 0.05). CONCLUSION: Radiomics analysis of 3D MRF maps allows differentiating glioblastomas from metastases and is capable of differentiating glioblastomas from metastases and characterizing gliomas based on grade, IDH1 status, and survival. KEY POINTS: • 3D MRF data analysis using radiomics offers novel tissue characterization of brain tumors. • 3D MRF with radiomics offers glioma characterization based on grade, IDH1 status, and overall patient survival.

Increased intrathoracic and hepatic visceral adipose tissue independently correlates with coronary artery calcification in asymptomatic patients.

BACKGROUND: Visceral adipose tissue (VAT) is associated with cardiac events, but it is not clear which, if any of the various measures of VAT independently correlate with coronary artery disease (CAD). METHODS: We studied 400 patients undergoing computed tomography to determine coronary artery calcium (CAC) score. VAT was measured in the form of epicardial adipose tissue (EAT) volume and thickness, intrathoracic adipose tissue volume (ITAV), and hepatic steatosis. RESULTS: Of the 400 subjects, the average CAC score was 112.2 ± 389.3. When each measure of VAT (EAT volume and thickness, ITAV, hepatic steatosis) was added to the traditional model (they were independently associated with greater risk of CAC score ≥100 AU as measured by IDI/NRI (P < .05). On univariable logistic regression analysis, each of the 4 measures of VAT showed association with greater risk of a CAC score of ≥100 AU (OR > 1). CONCLUSIONS: Each measure of VAT is a strong correlate of CAC score ≥100 AU in asymptomatic subjects-these VAT assessments correlate more significantly than do traditional CAD risk factors. This incremental power in the predictive models is likely the result of measurement of a fundamental expression of the metabolic syndrome and consequent proatherogenic derangements.