Broad Goals
- Developing organ-level patient dosimetry
- Devising individual-level risk estimation
Radiation dose is an ever present aspect of medical imaging using ionizing radiation. That includes CT imaging, nuclear imaging, radiography, fluoroscopy, and mammography. While the dose in diagnosis is generally very small, there is a likelihood of harm that should still be minimized. This goal requires the quantification of dose and risk, in the most patient-informed manner, and then using that for meaningful characterization, optimization, and assurance of precision care in terms of radiation safety. The broad objective of this research activity of the lab is thus to devise patient-specific organ dosimetry and risk estimation methods. Current projects include fast Monte Carlo simulations for patient-specific dosimetry, the effect of patient attributes on the dose values, the various techniques to combine organ and intra-organ dose values into risk estimates, and the application of these techniques to safety monitoring and optimization.
Related Publications
- Medical imaging dose optimization from ground up: expert opinion of an international summit
- Size-based quality-informed framework for quantitative optimization of pediatric CT
- Radiation risk index for pediatric CT: A patient-derived metric
- Optimizing window settings for improved presentation of virtual mono-energetic images in dual‐energy computed tomography
- Organ dose variability and trends in tomosynthesis and radiography
- The effect of contrast material on radiation dose in CT: Part I. Incorporation of contrast medium dynamics in anthropomorphic phantoms
- Convolution-based estimation of organ dose in tube current modulated CT
- Li et al. Effects of protocol and obesity on dose conversion factors in adult body CT. Medical Physics 2012. PDF.
- Ria et al. Expanding the concept of diagnostic reference levels to noise and dose reference levels in CT. AJR 2019. https://pubmed.ncbi.nlm.nih.gov/31180737/
- Alsaihati et al. Making CT Dose Monitoring Meaningful: Augmenting Dose with Imaging Quality. Tomography 2023 https://doi.org/10.3390/tomography9020065
