Dose prediction model and cancer risk estimation as quality check in multi-detector computed tomography

Background

Due to the health risks associated with radiation exposure, the radiology community currently controls and tracks the radiation dosage from computed tomography imaging technology. In order to protect patients from radiation exposure, radiology must be planned to keep patient doses "As Low as Reasonably Achievable" (ALARA). As a result, numerous initiatives such as optimisation of scan protocols, application of automatic exposure control etc. have been made to reduce the radiation exposure from CT scans. This study sought to develop a tool to assess organ specific doses and estimate cancer incidence and mortality risk for pelvic CT examinations.

Method

Rando anthropomorphic female phantom was used in this study. Positions of five selected organs in the female pelvic region were identified by Radiologists in scanned CT images and organ doses to the bladder, uterus, rectum, ovary and cervix were measured with lithium fluoride (LiF) thermoluminescent dosimeters (TLDs) -100 by varying tube voltage (kVp) and tube current (mAs) of the Philips Ingenuity 128 slice CT scanner (Serial number: 50762; MRC 880). Specific organ dose mathematical models were generated using Minitab statistical tool and the Biological Effect of Ionising Radiation (BEIR) VII risk model was used to estimate the excess relative risk (ERR) for the organs). User friendly organ dose prediction and cancer risk estimation tool was developed using C +  + programming software.

Results

The measured organ dose increased with increasing kVp and mAs at an average rate of 0.15 and 0.03 respectively. The cancer incidence and mortality risk also increased with increasing kVp and mAs at an average rate of 0.09 and 0.03 respectively. The proposed mathematical organ dose models had a statistical significance less than 0.001. The organ doses were observed to have a good correlation (89.85% to 90.32%) with the kVp and mAs. The user-friendly dose prediction and cancer risk estimation tool (Bour’s Dose Measurement APP) developed, enables quick and easy prediction of the dose and cancer risk estimates, enabling a quality check on the imaging procedures to ensure patient radiation protection.

Conclusion

The Bour’s Dose Measurement APP will enhance patient protection for pelvic CT examinations for female patients.

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