AI analysis of chest CT scans helps connect high-risk patients with specialist care
Competition in the health screening market is shifting from simply offering more tests to determining how effectively high-risk individuals are managed after their checkups. Artificial intelligence is increasingly being used not only to detect potential abnormalities in medical images, but also to support a broader process linking physician review, patient guidance and follow-up care.
Medical AI company Coreline Soft said on July 7 that it has signed a supply agreement with comprehensive health screening center Gangnam Heart Scan for AVIEW Aorta, its AI-powered cardiovascular imaging detection and diagnostic support software.
The deployment marks the first time AVIEW Aorta has been introduced at a health screening center.
Gangnam Heart Scan plans to use the system to strengthen integrated lung and cardiovascular analysis based on chest CT scans, as well as its follow-up management system for high-risk individuals. Rather than simply delivering test results, the center is building a process in which AI findings are reviewed by medical professionals before patients requiring further attention are guided by a follow-up care team and connected with cardiologists.
AVIEW Aorta automatically segments and visualizes the aorta on CT images and measures its diameter and volume by anatomical region. The software also supports two-dimensional and three-dimensional image comparison and integration with picture archiving and communication systems, or PACS.
Aortic aneurysms can remain largely asymptomatic for extended periods, but their size, location and progression may require follow-up monitoring or more detailed examinations. This makes the screening stage important for identifying aortic enlargement and selecting patients who may need additional evaluation.
Gangnam Heart Scan is also using Coreline Soft’s AVIEW Premium Report. Based on a single low-dose chest CT scan, the system can analyze pulmonary nodules, emphysema and bronchial abnormalities, while also assessing cardiovascular risk indicators such as coronary artery calcification.
The results are presented with 3D visualization to help patients better understand their health status.
While chest CT has traditionally been used primarily to detect lung diseases, the combination of AI analysis allows medical professionals to extract information related to the lungs, cardiovascular system and aorta from a single imaging examination.
The approach also changes what happens after a screening. Patients classified as high-risk following AI analysis and physician review are contacted directly by the center’s follow-up care team. When additional evaluation is required, they can be connected with cardiologists at the center.
According to Gangnam Heart Scan, physicians analyzed 1,100 people who underwent lung CT scans and identified 120 patients with stage-three or higher cardiovascular conditions requiring medication. The figure represents about 11 percent of the patients analyzed.
The results suggest that expanding the use of information contained in chest CT scans beyond lung disease could help identify additional high-risk patients whose cardiovascular risks might otherwise receive less attention during routine screening.
Health checkups have traditionally focused on performing tests and delivering written reports. Patients often leave the screening center after receiving their results, while providers have limited visibility into whether they subsequently seek medical care.
The problem is particularly relevant to imaging tests such as CT scans, which contain a wide range of clinical information. When findings are communicated mainly through technical language and text-based reports, patients may struggle to understand their level of risk, limiting the likelihood of appropriate follow-up care.
The role of AI in medical imaging is also evolving accordingly. Rather than replacing physicians’ judgment, the technology is increasingly being used to structure potential risk signals within images and help clinicians identify patients who require closer review.
Gangnam Heart Scan is also considering applying coronary artery calcium, or CAC, and aortic analysis reports to a corporate health screening program for employees of a major business group in July and August.
Under the proposed program, employees who choose chest CT scans would receive additional information on coronary artery calcification and aortic conditions, allowing the center to assess patient responses to the expanded reporting system.
MRI scans, colonoscopies and ultrasound examinations have traditionally dominated the premium options offered in corporate health screening programs. Advances in AI analysis, however, are increasing the amount of clinical information that can be extracted from a single chest CT scan, potentially changing how screening packages are designed.
The value of medical AI is therefore becoming increasingly difficult to measure solely by how many abnormalities an algorithm can detect. A more important question is whether identified risks lead to physician assessment, further testing and timely treatment.
The deployment at Gangnam Heart Scan highlights how AI imaging analysis is beginning to move beyond improving diagnostic accuracy and serve as a tool for designing the critical period after a health screening.
