Thoracic CT imaging in obesity: Technical challenges, imaging findings and future outlook

Abstract

Obesity is a highly prevalent and increasing global medical problem. It is expected that most radiologists will come across computed tomography studies of obese patients in their daily work. Obesity has multiple well known effects on the cardiovascular, endocrine, and musculoskeletal systems. Prevalent, but less well described, are the multiple effects that obesity causes in the lungs; this occurs through both direct mechanical and indirect metabolic mechanisms. These result in characteristic imaging features in CT in which this review article will illustrated. Radiologists who interpret chest CT should be aware of these findings and pitfalls in their assessment of obese patients to avoid misdiagnosis. In addition, there are multiple technical challenges to CT scanning of obese patients to achieve diagnostic images. In this review article the pathological mechanisms underlying the imaging findings in the obese lung are presented, as well as technical considerations for optimal scanning and the typical imaging findings. An overall review of the increasing use of AI body morphometry and its use in lung cancer risk and outcome prediction is also explored. We hope this review can provide clinical radiologists and those who have special interests in medical imaging comprehensive summary of the pathophysiology, diagnostic and technical challenges involved in thoracic CT imaging in obesity, as well as the insights into the future outlook with artificial intelligence.