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Automated AI-Based Aortic Measurements From Attenuation Correction CT as an Adjunctive Cardiovascular Risk Biomarker:
Anna M Marcinkiewicz1,2, Aakash Shanbhag1,3, Panithaya Chareonthaitawee4
1Artificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).
Insights
Artificial intelligence can automatically measure aortic size from myocardial perfusion imaging CT scans. This opportunistic aortic measurement is linked to increased mortality risk, offering a new biomarker without extra imaging.
Area of Science:
- Cardiology
- Radiology
- Artificial Intelligence
Background:
- Aortic enlargement predicts dissection and rupture but is often overlooked in myocardial perfusion imaging.
- Computed tomography (CT) attenuation correction scans are widely available during these procedures.
Purpose of the Study:
- To determine if automated, AI-derived aortic measurements from CT scans correlate with adverse outcomes.
- To assess the prognostic value of opportunistic aortic measurements in a large patient cohort.
Main Methods:
- Utilized CT attenuation correction scans from 29,339 patients across 10 centers.
- Employed a deep learning model for automated thoracic aorta segmentation and diameter measurement.
- Calculated aortic size index (ASI) by normalizing diameters to body surface area.
Main Results:
- Elevated ASI (ascending >2.2 cm/m², descending >1.6 cm/m²) was significantly associated with increased all-cause mortality.
- Ascending ASI showed an adjusted hazard ratio of 1.16 (P<0.001), and descending ASI showed 1.23 (P<0.001).
- The prognostic value of abnormal ASI remained significant, independent of age, sex, and perfusion abnormalities.
Conclusions:
- Artificial intelligence can extract valuable aortic size information from routine CT scans.
- Opportunistic aortic measurements from CT attenuation correction scans can serve as an adjunctive risk biomarker.
- This method adds prognostic value to myocardial perfusion imaging without additional radiation or imaging.
Background:
Aortic enlargement is a powerful predictor of dissection and rupture, yet it is rarely evaluated during routine myocardial perfusion imaging, despite the widespread availability of computed tomography (CT) attenuation correction scans. The aim of this study was to determine whether fully automated, opportunistically derived, artificial intelligence-based aortic measurements from myocardial perfusion imaging CT attenuation correction scans are associated with adverse outcomes in a large multicenter cohort.
Methods:
CT attenuation correction scans from patients undergoing positron emission tomography/CT and single-photon emission CT/CT myocardial perfusion imaging across 10 centers were included. A deep learning model automatically segmented the thoracic aorta, and a postprocessing algorithm extracted maximum ascending and descending diameters. The aortic size index was calculated by indexing the diameter to body surface area.
Results:
A total of 29 339 patients (56% men; median age, 66 years [interquartile range, 58-75 years]) were included. Over a median follow-up of 3.5 years (interquartile range, 1.9-5.0 years), 5083 (17.3%) patients died. Median ascending and descending aortic size index values were 1.8 cm/m2 (interquartile range, 1.6-2.0) and 1.5 cm/m2 (interquartile range, 1.4-1.6), respectively, with an increase with age and higher values in females. Elevated aortic size index thresholds (ascending >2.2 cm/m2; descending >1.6 cm/m2) were significantly associated with increased all-cause mortality (ascending: adjusted hazard ratio, 1.16 [95% CI, 1.07-1.26], P<0.001; descending: adjusted hazard ratio, 1.23 [95% CI, 1.14-1.31]; P<0.001). Notably, the prognostic value of an abnormal aortic size index persisted independent of age, sex, and perfusion abnormalities.
Conclusions:
Artificial intelligence can unlock previously unused information within routine myocardial perfusion imaging CT attenuation correction scans by rapidly and automatically quantifying aortic size at scale. Opportunistic aortic measurements derived from CT attenuation correction may serve as an adjunctive risk biomarker and could add prognostic value to standard myocardial perfusion imaging without additional imaging or radiation.
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