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Emerging research shows that a multiple time-series deep learning model assessment of CT images provides 20 percent higher sensitivity than a delta radiomic model and 56 percent higher sensitivity than a clinical model for prognostic evaluation of ground-glass nodules.

In a second part of a new podcast episode on recently published research on projected radiation-induced cancers from computed tomography (CT) scans, Mahadevappa Mahesh, MS, Ph.D., and Joseph Cavallo, M.D., offer current perspectives on cardiac CT dosing, AI advances and the importance of teamwork in ensuring appropriate dosing for CT.

Researchers also noted a greater than 30 percent increase in treatment management changes resulting from the use of CT-based adjunctive AI to detect lung metastases in colorectal cancer patients.

In a new podcast, Mahadevappa Mahesh, MS, Ph.D., and Joseph Cavallo, M.D., share their perspectives on recently published research looking at projections for future radiation-induced cancers from computed tomography (CT) scans.

Emerging research suggests the use of computed tomography colonography (CTC) in colorectal cancer screening may provide significantly higher preventive benefit at lower costs in comparison to multitarget stool DNA testing.

Through AI assessment of chest CT scans, the SeleCT Screening may help identify candidates for bronchoscopic lung volume reduction to improve lung function.