Coronary Computed Tomography Angiography with Deep Learning Image Reconstruction: A Preliminary Study to Evaluate Radiation Exposure Reduction
Coronary computed tomography angiography (CCTA) is a medical imaging technique that produces detailed images of the coronary arteries. Our work focuses on the optimization of the prospectively ECG-triggered scan technique, which delivers the radiation efficiently only during a fraction of the R–R in...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Tomography |
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| Online Access: | https://www.mdpi.com/2379-139X/9/3/83 |
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| author | Rossana Bona Piergiorgio Marini Davide Turilli Salvatore Masala Mariano Scaglione |
| author_facet | Rossana Bona Piergiorgio Marini Davide Turilli Salvatore Masala Mariano Scaglione |
| author_sort | Rossana Bona |
| collection | DOAJ |
| description | Coronary computed tomography angiography (CCTA) is a medical imaging technique that produces detailed images of the coronary arteries. Our work focuses on the optimization of the prospectively ECG-triggered scan technique, which delivers the radiation efficiently only during a fraction of the R–R interval, matching the aim of reducing radiation dose in this increasingly used radiological examination. In this work, we analyzed how the median DLP (Dose-Length Product) values for CCTA of our Center decreased significantly in recent times mainly due to a notable change in the technology used. We passed from a median DLP value of 1158 mGy·cm to 221 mGy·cm for the whole exam and from a value of 1140 mGy·cm to 204 mGy·cm if considering CCTA scanning only. The result was obtained through the association of important factors during the dose imaging optimization: technological improvement, acquisition technique, and image reconstruction algorithm intervention. The combination of these three factors allows us to perform a faster and more accurate prospective CCTA with a lower radiation dose. Our future aim is to tune the image quality through a detectability-based study, combining algorithm strength with automatic dose settings. |
| first_indexed | 2024-03-11T01:51:49Z |
| format | Article |
| id | doaj.art-2c9cbf8318dc4b2b82add1f496dacbcc |
| institution | Directory Open Access Journal |
| issn | 2379-1381 2379-139X |
| language | English |
| last_indexed | 2024-03-11T01:51:49Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Tomography |
| spelling | doaj.art-2c9cbf8318dc4b2b82add1f496dacbcc2023-11-18T12:53:46ZengMDPI AGTomography2379-13812379-139X2023-05-01931019102810.3390/tomography9030083Coronary Computed Tomography Angiography with Deep Learning Image Reconstruction: A Preliminary Study to Evaluate Radiation Exposure ReductionRossana Bona0Piergiorgio Marini1Davide Turilli2Salvatore Masala3Mariano Scaglione4Medical Physics Unit, Azienda Ospedaliero-Universitaria (AOU), 07100 Sassari, ItalyMedical Physics Unit, Azienda Ospedaliero-Universitaria (AOU), 07100 Sassari, ItalyDepartment of Medicine, Surgery and Pharmacy, University of Sassari, 07100 Sassari, ItalyDepartment of Medicine, Surgery and Pharmacy, University of Sassari, 07100 Sassari, ItalyDepartment of Medicine, Surgery and Pharmacy, University of Sassari, 07100 Sassari, ItalyCoronary computed tomography angiography (CCTA) is a medical imaging technique that produces detailed images of the coronary arteries. Our work focuses on the optimization of the prospectively ECG-triggered scan technique, which delivers the radiation efficiently only during a fraction of the R–R interval, matching the aim of reducing radiation dose in this increasingly used radiological examination. In this work, we analyzed how the median DLP (Dose-Length Product) values for CCTA of our Center decreased significantly in recent times mainly due to a notable change in the technology used. We passed from a median DLP value of 1158 mGy·cm to 221 mGy·cm for the whole exam and from a value of 1140 mGy·cm to 204 mGy·cm if considering CCTA scanning only. The result was obtained through the association of important factors during the dose imaging optimization: technological improvement, acquisition technique, and image reconstruction algorithm intervention. The combination of these three factors allows us to perform a faster and more accurate prospective CCTA with a lower radiation dose. Our future aim is to tune the image quality through a detectability-based study, combining algorithm strength with automatic dose settings.https://www.mdpi.com/2379-139X/9/3/83ionizing radiation exposurecoronary vesselslow-dose computed tomographydeep learning algorithmexam optimization |
| spellingShingle | Rossana Bona Piergiorgio Marini Davide Turilli Salvatore Masala Mariano Scaglione Coronary Computed Tomography Angiography with Deep Learning Image Reconstruction: A Preliminary Study to Evaluate Radiation Exposure Reduction Tomography ionizing radiation exposure coronary vessels low-dose computed tomography deep learning algorithm exam optimization |
| title | Coronary Computed Tomography Angiography with Deep Learning Image Reconstruction: A Preliminary Study to Evaluate Radiation Exposure Reduction |
| title_full | Coronary Computed Tomography Angiography with Deep Learning Image Reconstruction: A Preliminary Study to Evaluate Radiation Exposure Reduction |
| title_fullStr | Coronary Computed Tomography Angiography with Deep Learning Image Reconstruction: A Preliminary Study to Evaluate Radiation Exposure Reduction |
| title_full_unstemmed | Coronary Computed Tomography Angiography with Deep Learning Image Reconstruction: A Preliminary Study to Evaluate Radiation Exposure Reduction |
| title_short | Coronary Computed Tomography Angiography with Deep Learning Image Reconstruction: A Preliminary Study to Evaluate Radiation Exposure Reduction |
| title_sort | coronary computed tomography angiography with deep learning image reconstruction a preliminary study to evaluate radiation exposure reduction |
| topic | ionizing radiation exposure coronary vessels low-dose computed tomography deep learning algorithm exam optimization |
| url | https://www.mdpi.com/2379-139X/9/3/83 |
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