Opportunistic Extraction of Quantitative CT Biomarkers: Turning the Incidental Into Prognostic Information

Abstract

The past two decades have seen a significant increase in the use of CT, with a corresponding rise in the mean population radiation dose. This rise in CT use has caused improved diagnostic certainty in conditions that were not previously routinely evaluated using CT, such as headaches, back pain, and chest pain. Unused data, unrelated to the primary diagnosis, embedded within these scans have the potential to provide organ-specific measurements that can be used to prognosticate or risk-profile patients for a wide variety of conditions. The recent increased availability of computing power, expertise and software for automated segmentation and measurements, assisted by artificial intelligence, provides a conducive environment for the deployment of these analyses into routine use. Data gathering from CT has the potential to add value to examinations and help offset the public perception of harm from radiation exposure. We review the potential for the collection of these data and propose the incorporation of this strategy into routine clinical practice.

Use of Opportunistic CT Biomarkers: Population Health Opportunities in Radiology

“…The aggregate benefits of opportunistic imaging will need to be evaluated from ethical, population-level, and patient-level perspectives. The recent article by Shah et al (2023) entitled: "Opportunistic Extraction of Quantitative CT Biomarkers: Turning the Incidental Into Prognostic Information" outlined several ways in which opportunistic extraction of computed tomography (CT) biomarkers could provide clinically meaningful data. 1 In Canada, lung cancer screening programs are becoming more common: this CT imaging creates the potential to offer insights into other aspects of health, beyond the lungs.…”

“…The recent article by Shah et al (2023) entitled: "Opportunistic Extraction of Quantitative CT Biomarkers: Turning the Incidental Into Prognostic Information" outlined several ways in which opportunistic extraction of computed tomography (CT) biomarkers could provide clinically meaningful data. 1 In Canada, lung cancer screening programs are becoming more common: this CT imaging creates the potential to offer insights into other aspects of health, beyond the lungs. For example, coronary artery calcification detected through CT scans can serve as a predictor for future cardiovascular adverse events, which are elevated in this patient population.…”

“…If identified early, it can potentially be managed and reversed before chronic sequela including NASH (non-alcoholic steatohepatitis) and cirrhosis have time to develop. 1 Osteoporosis, an underdiagnosed and undertreated condition, is associated with patient morbidity, and mortality and a resultant large economic burden. 3 There have been several articles published in recent years investigating the use of artificial intelligence and machine learning for diagnosing osteoporosis.…”

“…This article by Shah et al (2023) brings to light how opportunistic extraction of CT biomarkers can help in earlier disease detection, management planning, prognostication, and future disease risk stratification. 1 Perhaps, not too far in the future, a patient undergoing a screening CT for lung cancer could also simultaneously result in clinically meaningful measurements for breast density, bone density, and aortic/ coronary artery calcification. Compounded by the power of artificial intelligence, the potential breadth of information to be gained appears almost infinite.…”

“…The recent article by Shah et al (2023) entitled: “Opportunistic Extraction of Quantitative CT Biomarkers: Turning the Incidental Into Prognostic Information” outlined several ways in which opportunistic extraction of computed tomography (CT) biomarkers could provide clinically meaningful data. 1…”