| Title |
Gonzalez, Edgar MSRS 2025 |
| Alternative Title |
The Role of Artificial Intelligence in the Reduction of Radiation Exposure; in the Cath Lab |
| Creator |
Gonzalez, Edgar |
| Collection Name |
Master of Radiologic Sciences |
| Description |
This study focused on the application of artificial intelligence (AI) within the cardiac catheterization laboratory (cath lab) to improve radiation safety |
| Abstract |
This study focused on the application of artificial intelligence (AI) within the cardiac catheterization laboratory (cath lab) to improve radiation safety. Due to the high radiation dose seen within the cath lab, medical personnel are required to wear heavy lead aprons for safety. However, this results in a high percentage of orthopedic injuries or even early retirement. The purpose of this study was to examine whether artificial intelligence could efficiently reduce radiation exposure seen by patients and medical professionals without negatively affecting the quality of the procedure.; Therefore, a systematic literature review was conducted with the use of PRISMA guidelines. 47 peer-reviewed articles were selected for this study based on their relevance, quality, and alignment with the purpose of the study. A qualitative approach was utilized with a focus on synthesizing existing knowledge to AI dose management and image optimization. Due to the qualitative nature of the literature review there were no human participants but rather an extensive library of publications.; Some of the key findings in this study revealed that specific AI was able to significantly reduce the amount of radiation patients and staff are exposed to. For example, an AI-driven tool has the potential to reduce up to 50% of radiation during a specific imaging technique. Other findings suggested that AI improved procedural efficiency and reduced the physical burden on operators.; Through the evidence found in this study it was concluded that AI has the potential to significantly change cath lab environments into safer, more efficient, and ergonomically sustainable environments. However, there are still challenges to be faced such as the variability in AI implementation, a lack of standardization, and limited long-; term studies. This study recommends that guidelines be expanded to support the use of ultra-low radiation Coronary CT Angiography (CCTA) prior to cath lab procedures.; Further research could focus on the long-term effects of AI on patient outcomes, occupational safety, and economic burden. Additionally the scalability in resource-limited setting should be studied. Finally the potential for robotic assistance should be researched as this could further reduce radiation exposure and operator fatigue. |
| Subject |
Artificial intelligence; Cardiac catheterization; Medical technology |
| Digital Publisher |
Digitized by Special Collections & University Archives, Stewart Library, Weber State University. |
| Date |
2025 |
| Medium |
Thesis |
| Type |
Text |
| Access Extent |
45 page pdf |
| Conversion Specifications |
Adobe Acrobat |
| Language |
eng |
| Rights |
The author has granted Weber State University Archives a limited, non-exclusive, royalty-free license to reproduce his or her thesis, in whole or in part, in electronic or paper form and to make it available to the general public at no charge. The author retains all other rights. For further information:  |
| Source |
University Archives Electronic Records: Master of Radiologic Sciences. Stewart Library, Weber State University |
| Format |
application/pdf |
| ARK |
ark:/87278/s6x8p8b9 |
| Setname |
wsu_smt |
| ID |
153458 |
| Reference URL |
https://digital.weber.edu/ark:/87278/s6x8p8b9 |
