Optimization of abdominal CT based on a model of total risk minimization by putting radiation risk in perspective with imaging benefit
Abstract Background Risk-versus-benefit optimization required a quantitative comparison of the two. The latter, directly related to effective diagnosis, can be associated to clinical risk. While many strategies have been developed to ascertain radiation risk, there has been a paucity of studies asse...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-12-01
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| Series: | Communications Medicine |
| Online Access: | https://doi.org/10.1038/s43856-024-00674-w |
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| author | Francesco Ria Anru R. Zhang Reginald Lerebours Alaattin Erkanli Ehsan Abadi Daniele Marin Ehsan Samei |
| author_facet | Francesco Ria Anru R. Zhang Reginald Lerebours Alaattin Erkanli Ehsan Abadi Daniele Marin Ehsan Samei |
| author_sort | Francesco Ria |
| collection | DOAJ |
| description | Abstract Background Risk-versus-benefit optimization required a quantitative comparison of the two. The latter, directly related to effective diagnosis, can be associated to clinical risk. While many strategies have been developed to ascertain radiation risk, there has been a paucity of studies assessing clinical risk, thus limiting the optimization reach to achieve a minimum total risk to patients undergoing imaging examinations. In this study, we developed a mathematical framework for an imaging procedure total risk index considering both radiation and clinical risks based on specific tasks and investigated diseases. Methods The proposed model characterized total risk as the sum of radiation and clinical risks defined as functions of radiation burden, disease prevalence, false-positive rate, expected life-expectancy loss for misdiagnosis, and radiologist interpretative performance (i.e., AUC). The proposed total risk model was applied to a population of one million cases simulating a liver cancer scenario. Results For all demographics, the clinical risk outweighs radiation risk by at least 400%. The optimization application indicates that optimizing typical abdominal CT exams should involve a radiation dose increase in over 90% of the cases, with the highest risk optimization potential in Asian population (24% total risk reduction; 306% $${{CTDI}}_{{vol}}$$ C T D I v o l increase) and lowest in Hispanic population (5% total risk reduction; 89% $${{CTDI}}_{{vol}}$$ C T D I v o l increase). Conclusions Framing risk-to-benefit assessment as a risk-versus-risk question, calculating both clinical and radiation risk using comparable units, allows a quantitative optimization of total risks in CT. The results highlight the dominance of clinical risk at typical CT examination dose levels, and that exaggerated dose reductions can even harm patients. |
| format | Article |
| id | doaj-art-934000b145014506a6d0ad368615f74c |
| institution | OA Journals |
| issn | 2730-664X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Medicine |
| spelling | doaj-art-934000b145014506a6d0ad368615f74c2025-08-20T01:57:12ZengNature PortfolioCommunications Medicine2730-664X2024-12-01411910.1038/s43856-024-00674-wOptimization of abdominal CT based on a model of total risk minimization by putting radiation risk in perspective with imaging benefitFrancesco Ria0Anru R. Zhang1Reginald Lerebours2Alaattin Erkanli3Ehsan Abadi4Daniele Marin5Ehsan Samei6Carl E. Ravin Advanced Imaging Labs, Center for Virtual Imaging Trials, Department of Radiology, Duke University Health SystemDepartment of Biostatistics & Bioinformatics and Department of Computer Science, Duke UniversityDepartment of Biostatistics & Bioinformatics and Department of Computer Science, Duke UniversityDepartment of Biostatistics & Bioinformatics and Department of Computer Science, Duke UniversityCarl E. Ravin Advanced Imaging Labs, Center for Virtual Imaging Trials, Department of Radiology, Duke University Health SystemDepartment of Radiology, Duke University Health SystemCarl E. Ravin Advanced Imaging Labs, Center for Virtual Imaging Trials, Department of Radiology, Duke University Health SystemAbstract Background Risk-versus-benefit optimization required a quantitative comparison of the two. The latter, directly related to effective diagnosis, can be associated to clinical risk. While many strategies have been developed to ascertain radiation risk, there has been a paucity of studies assessing clinical risk, thus limiting the optimization reach to achieve a minimum total risk to patients undergoing imaging examinations. In this study, we developed a mathematical framework for an imaging procedure total risk index considering both radiation and clinical risks based on specific tasks and investigated diseases. Methods The proposed model characterized total risk as the sum of radiation and clinical risks defined as functions of radiation burden, disease prevalence, false-positive rate, expected life-expectancy loss for misdiagnosis, and radiologist interpretative performance (i.e., AUC). The proposed total risk model was applied to a population of one million cases simulating a liver cancer scenario. Results For all demographics, the clinical risk outweighs radiation risk by at least 400%. The optimization application indicates that optimizing typical abdominal CT exams should involve a radiation dose increase in over 90% of the cases, with the highest risk optimization potential in Asian population (24% total risk reduction; 306% $${{CTDI}}_{{vol}}$$ C T D I v o l increase) and lowest in Hispanic population (5% total risk reduction; 89% $${{CTDI}}_{{vol}}$$ C T D I v o l increase). Conclusions Framing risk-to-benefit assessment as a risk-versus-risk question, calculating both clinical and radiation risk using comparable units, allows a quantitative optimization of total risks in CT. The results highlight the dominance of clinical risk at typical CT examination dose levels, and that exaggerated dose reductions can even harm patients.https://doi.org/10.1038/s43856-024-00674-w |
| spellingShingle | Francesco Ria Anru R. Zhang Reginald Lerebours Alaattin Erkanli Ehsan Abadi Daniele Marin Ehsan Samei Optimization of abdominal CT based on a model of total risk minimization by putting radiation risk in perspective with imaging benefit Communications Medicine |
| title | Optimization of abdominal CT based on a model of total risk minimization by putting radiation risk in perspective with imaging benefit |
| title_full | Optimization of abdominal CT based on a model of total risk minimization by putting radiation risk in perspective with imaging benefit |
| title_fullStr | Optimization of abdominal CT based on a model of total risk minimization by putting radiation risk in perspective with imaging benefit |
| title_full_unstemmed | Optimization of abdominal CT based on a model of total risk minimization by putting radiation risk in perspective with imaging benefit |
| title_short | Optimization of abdominal CT based on a model of total risk minimization by putting radiation risk in perspective with imaging benefit |
| title_sort | optimization of abdominal ct based on a model of total risk minimization by putting radiation risk in perspective with imaging benefit |
| url | https://doi.org/10.1038/s43856-024-00674-w |
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