Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment
Cardiovascular CT is being widely used in the diagnosis of cardiovascular disease due to the rapid technological advancements in CT scanning techniques. These advancements include the development of multi-slice CT, from early generation to the latest models, which has the capability of acquiring ima...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
MDPI
2024
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| Online Access: | http://hdl.handle.net/20.500.11937/94241 |
| _version_ | 1848765850533756928 |
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| author | Sun, Zhonghua Silberstein, Jenna Vaccarezza, Mauro |
| author2 | Kheradvar, Arash |
| author_facet | Kheradvar, Arash Sun, Zhonghua Silberstein, Jenna Vaccarezza, Mauro |
| author_sort | Sun, Zhonghua |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Cardiovascular CT is being widely used in the diagnosis of cardiovascular disease due to the rapid technological advancements in CT scanning techniques. These advancements include the development of multi-slice CT, from early generation to the latest models, which has the capability of acquiring images with high spatial and temporal resolution. The recent emergence of photon-counting CT has further enhanced CT performance in clinical applications, providing improved spatial and contrast resolution. CT-derived fractional flow reserve is superior to standard CT-based anatomical assessment for the detection of lesion-specific myocardial ischemia. CT-derived 3D-printed patient-specific models are also superior to standard CT, offering advantages in terms of educational value, surgical planning, and the simulation of cardiovascular disease treatment, as well as enhancing doctor–patient communication. Three-dimensional visualization tools including virtual reality, augmented reality, and mixed reality are further advancing the clinical value of cardiovascular CT in cardiovascular disease. With the widespread use of artificial intelligence, machine learning, and deep learning in cardiovascular disease, the diagnostic performance of cardiovascular CT has significantly improved, with promising results being presented in terms of both disease diagnosis and prediction. This review article provides an overview of the applications of cardiovascular CT, covering its performance from the perspective of its diagnostic value based on traditional lumen assessment to the identification of vulnerable lesions for the prediction of disease outcomes with the use of these advanced technologies. The limitations and future prospects of these technologies are also discussed. |
| first_indexed | 2025-11-14T11:41:48Z |
| format | Journal Article |
| id | curtin-20.500.11937-94241 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:41:48Z |
| publishDate | 2024 |
| publisher | MDPI |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-942412024-01-24T05:11:48Z Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment Sun, Zhonghua Silberstein, Jenna Vaccarezza, Mauro Kheradvar, Arash cardiac computed tomography 3D visualization diagnosis coronary artery disease 3D printing virtual reality mixed reality artificial intelligence Cardiovascular CT is being widely used in the diagnosis of cardiovascular disease due to the rapid technological advancements in CT scanning techniques. These advancements include the development of multi-slice CT, from early generation to the latest models, which has the capability of acquiring images with high spatial and temporal resolution. The recent emergence of photon-counting CT has further enhanced CT performance in clinical applications, providing improved spatial and contrast resolution. CT-derived fractional flow reserve is superior to standard CT-based anatomical assessment for the detection of lesion-specific myocardial ischemia. CT-derived 3D-printed patient-specific models are also superior to standard CT, offering advantages in terms of educational value, surgical planning, and the simulation of cardiovascular disease treatment, as well as enhancing doctor–patient communication. Three-dimensional visualization tools including virtual reality, augmented reality, and mixed reality are further advancing the clinical value of cardiovascular CT in cardiovascular disease. With the widespread use of artificial intelligence, machine learning, and deep learning in cardiovascular disease, the diagnostic performance of cardiovascular CT has significantly improved, with promising results being presented in terms of both disease diagnosis and prediction. This review article provides an overview of the applications of cardiovascular CT, covering its performance from the perspective of its diagnostic value based on traditional lumen assessment to the identification of vulnerable lesions for the prediction of disease outcomes with the use of these advanced technologies. The limitations and future prospects of these technologies are also discussed. 2024 Journal Article http://hdl.handle.net/20.500.11937/94241 10.3390/jcdd11010022 English http://creativecommons.org/licenses/by/4.0/ MDPI fulltext |
| spellingShingle | cardiac computed tomography 3D visualization diagnosis coronary artery disease 3D printing virtual reality mixed reality artificial intelligence Sun, Zhonghua Silberstein, Jenna Vaccarezza, Mauro Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment |
| title | Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment |
| title_full | Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment |
| title_fullStr | Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment |
| title_full_unstemmed | Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment |
| title_short | Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment |
| title_sort | cardiovascular computed tomography in the diagnosis of cardiovascular disease: beyond lumen assessment |
| topic | cardiac computed tomography 3D visualization diagnosis coronary artery disease 3D printing virtual reality mixed reality artificial intelligence |
| url | http://hdl.handle.net/20.500.11937/94241 |