Diagnosis of thoracic aortic aneurysms and pathological pulmonary trunk dilation using chest computed tomography and artificial intelligence: modern approaches and prospects (a review)

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Abstract

Early diagnosis of thoracic aortic aneurysms and pathological pulmonary trunk dilation is crucial to prevent severe complications, including vascular wall rupture and acute right ventricular failure, and reduce cardiovascular mortality. This review examines contemporary imaging approaches for these conditions, focusing on computed tomography as the gold standard modality. Emphasis was placed on the implementation of artificial intelligence technologies, which enable automatic segmentation of vascular structures, measurement of their diameter, and opportunistic screening, allowing early detection of asymptomatic conditions without additional diagnostic procedures, thereby reducing radiologist workload and improving medical care quality. The study comprehensively analyzed the Moscow Experiment, wherein the application of artificial intelligence in medical image analysis showed high sensitivity, reproducibility, and reduced reporting time. Despite these significant advantages, the need for expert supervision of artificial intelligence-generated results to ensure diagnostic accuracy and reliability is emphasized. Moreover, the review highlights the importance of adapting algorithms to different scanning protocols and population-specific features. Additionally, the importance of interdisciplinary collaboration among cardiologists, radiologists, data scientists, and software developers for the effective integration into routine clinical practice is pointed out. Therefore, the review outlines the potential of artificial intelligence technologies to enhance diagnostic quality and underscores the need for further clinical research and standardization of methods for successful integration into daily practice.

About the authors

Alexander V. Solovev

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies; Morozov Children's Municipal Clinical Hospital

Author for correspondence.
Email: atlantis.92@mail.ru
ORCID iD: 0000-0003-4485-2638
SPIN-code: 9654-4005

MD

Russian Federation, Moscow; Moscow

Valentin E. Sinitsyn

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies; Lomonosov Moscow State University

Email: vsini@mail.ru
ORCID iD: 0000-0002-5649-2193
SPIN-code: 8449-6590

MD, Dr. Sci. (Medicine), Professor

Russian Federation, Moscow; Moscow

Anton V. Vladzymyrskyy

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies

Email: VladzimirskijAV@zdrav.mos.ru
ORCID iD: 0000-0002-2990-7736
SPIN-code: 3602-7120

MD, Dr. Sci. (Medicine)

Russian Federation, Moscow

Anastasia P. Pamova

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies

Email: PamovaAP@zdrav.mos.ru
ORCID iD: 0000-0002-0041-3281
SPIN-code: 5146-4355

MD, Cand. Sci. (Medicine)

Russian Federation, Moscow

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2. Fig. 1. Example of measuring the ratio of the pulmonary artery trunk and ascending aorta. On the axial section of the computed tomography images at the level of the pulmonary artery bifurcation, the diameters of the pulmonary artery and ascending aorta were measured. A computer caliper was used, which recorded the largest diameter of the vessels vertically from the long axis of the main pulmonary artery: a — with the use of contrast enhancement; b — without its use.

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3. Fig. 2. An example of the Russian service based on artificial intelligence: a — the green (normal) lines indicate the diameter of the ascending and descending thoracic aorta, as well as the pulmonary trunk. The pulmonary lymph node is highlighted in the red square (with the size and volume indicated); b — the yellow line (dilation) indicates the diameter of the ascending aorta, the orange line (pathological expansion) — the diameter of the pulmonary trunk, the absence of measurements of the descending aorta indicates incorrect operation of the artificial intelligence system. The orange contour highlights suspected compaction of lung tissue (pneumonia), the yellow contour — hydrothorax.

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