Opportunistic AI-enabled automated bone mineral density measurements in lung cancer screening and coronary calcium scoring CT scans are equivalent

• Type of Material: Article
• Authors: Morteza Naghavi, HeartLung AI Technologies; Isabel De Oliveira, HeartLung AI Technologies; Song Shou Mao, Harbor-UCLA Medical Center; Amirhossein Jaberzadeh, HeartLung AI Technologies; Juan Montoya, HeartLung AI Technologies; Chenyu Zhang, HeartLung AI Technologies; Kyle Atlas, HeartLung AI Technologies; Venkat Manubolu, Harbor-UCLA Medical Center; Marlon Montes, HeartLung AI Technologies; Dong Li, Emory University; Thomas Atlas, HeartLung AI Technologies; Anthony Reeves, Cornell University; Claudia Henschke, Mount Sinai; David Yankelevitz, Mount Sinai; Matthew Budoff, Harbor-UCLA Medical Center
• Language: English
• Date: 2023-01-01
• Publisher: Elsevier Ltd.
• Publication Version: Final Published Version
• Copyright Statement: © 2023 Published by Elsevier Ltd.
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1016/j.ejro.2023.100492
• Title of Journal or Parent Work: European Journal of Radiology Open
• Volume: 10
• Start Page: 100492
• End Page: 100492
• Keywords: Deep learning; Coronary artery calcium score; Osteoporosis; Opportunistic; Bone mineral density; Lung cancer screening; Quantitative computed tomography; Artificial intelligence; Osteopenia; Cardiovascular Screening
• Research Categories: Health Sciences, Medicine and Surgery

Abstract

Rationale and objectives: We previously reported a novel manual method for measuring bone mineral density (BMD) in coronary artery calcium (CAC) scans and validated our method against Dual X-Ray Absorptiometry (DEXA). Furthermore, we have developed and validated an artificial intelligence (AI) based automated BMD (AutoBMD) measurement as an opportunistic add-on to CAC scans that recently received FDA approval. In this report, we present evidence of equivalency between AutoBMD measurements in cardiac vs lung CT scans. Materials and methods: AI models were trained using 132 cases with 7649 (3 mm) slices for CAC, and 37 cases with 21918 (0.5 mm) slices for lung scans. To validate AutoBMD against manual measurements, we used 6776 cases of BMD measured manually on CAC scans in the Multi-Ethnic Study of Atherosclerosis (MESA). We then used 165 additional cases from Harbor UCLA Lundquist Institute to compare AutoBMD in patients who underwent both cardiac and lung scans on the same day. Results: Mean±SD for age was 69 ± 9.4 years with 52.4% male. AutoBMD in lung and cardiac scans, and manual BMD in cardiac scans were 153.7 ± 43.9, 155.1 ± 44.4, and 163.6 ± 45.3 g/cm3, respectively (p = 0.09). Bland-Altman agreement analysis between AutoBMD lung and cardiac scans resulted in 1.37 g/cm3 mean differences. Pearson correlation coefficient between lung and cardiac AutoBMD was R2 = 0.95 (p < 0.0001). Conclusion: Opportunistic BMD measurement using AutoBMD in CAC and lung cancer screening scans is promising and yields similar results. No extra radiation plus the high prevalence of asymptomatic osteoporosis makes AutoBMD an ideal screening tool for osteopenia and osteoporosis in CT scans done for other reasons.