Few studies have reviewed the reduction of doses in Computed tomography (CT), while various diagnostic procedures use ionizing radiation to explore the optimal dose estimate using multiple exposure quantities, including milliampere-seconds, kilovoltage peak, and pitch factors while controlling the CT dose index volume (CTDIvol) and dose length product (DLP). Therefore, we considered optimizing CT protocols to reduce radiation and organ doses during head, chest, abdominal, and pelvic CT examinations. For establishing institutional diagnostic reference levels as a benchmark to correlate with national diagnostic reference levels (NDRLs) in KSA conforming to international guidelines for radiation exposure, 3000 adult-patients underwent imaging of organs. Dose parameters were obtained using Monte Carlo software and adjusted using the Siemens Teamplay™ software. CTDIvol, DLP, and effective dose were 40.67 ± 3.8, 757 ± 63.2, and 1.74 ± 0.19, for head; 14.9 ± 1.38, 547 ± 42.9, and 7.27 ± 0.95 for chest; and 16.84 ± 1.45, 658 ± 53.4, and 10.2 ± 0.66 for abdomen/pelvis, respectively. The NDRL post-optimization comparison showed adequate CT exposure. Head CT parameters required additional optimization to match the NDRL. Therefore, calculations were repeated to assess radiation doses. In conclusion, doses could be substantially minimized by selecting parameters per clinical indication of the study, patient size, and examined body region. Additional dose reduction to superficial organs requires a shielding material.

Purpose This study primarily aimed to evaluate the effectiveness of computational data management and analytical software for establishing departmental diagnostic reference levels (DRLs) for computed tomography (CT) scanning in clinical settings, and monitor achievable doses (ADs) for CT imaging, particularly during the coronavirus disease 2019 (COVID-19) era. Secondarily, it aimed to correlate these standards with national and international benchmarks. Patients and Methods This ambidirectional cohort study enrolled 4668 patients (6419 CT-based examinations) who visited King Fahd Hospital of the University from May 25, 2021, to November 4, 2021. Participants’ demographic data were acquired from their electronic medical charts, in addition to all corresponding CT-dose determinant parameters. The study was divided into two phases (pre- and post-data management) based on the implementation of digital data management software. Results In both phases of the study, the size-specific dose estimate (SSDE) was the most significant confounder of dose determination compared to the dose-length product (DLP) and computed tomography dose index (CTDI) (P = 0.003). The head was the most frequently imaged body region (pre-implementation, 1051 examinations [35.1%]; post-implementation, 1071 examinations [31.3%]; P = 0.001), followed by the abdominal region (pre-implementation, 616 examinations [20.6%]; post-implementation, 256 examinations [7.48%]; P = 0.001). Based on the SSDE, DLP, and volume CTDI, the average per-section radiation exposure among organ-based scanning type was highest for the lumbar spine during the pre- and post-implementation periods. Conclusion Data management software enabled the establishment of DRLs and reduction of ADs in CT examinations, which consequently improved key performance indicators, despite the ergonomic complexities of COVID-19. Institutions are encouraged to apply DRLs and ADs via automatic systems that monitor patient dose indices to evaluate aggregate results.

To evaluate the impact of using computational data management resources and analytical software on radiation doses in mammography and radiography during the COVID-19 pandemic, develop departmental diagnostic reference levels (DRLs), and describe achievable doses (ADs) for mammography and radiography based on measured dose parameters. Patients and Methods: This ambispective cohort study enrolled 795 and 12,115 patients who underwent mammography and radiography, respectively, at the King Fahd Hospital of the University, Al-Khobar City, Saudi Arabia between May 25 and November 4, 2021. Demographic data were acquired from patients' electronic medical charts. Data on mammographic and radiographic dose determinants were acquired from the data management software. Based on the time when the data management software was operational in the institute, the study was divided into the pre-implementation and post-implementation phases. Continuous and categorical variables were compared between the two phases using an unpaired t-test and the chi-square test. Results: The median accumulated average glandular dose (AGD; a mammographic dose determinant) in the post-implementation phase was three-fold higher than that in the pre-implementation phase. The average mammographic exposure time in the postimplementation phase was 16.3 ms shorter than that in the pre-implementation phase. Furthermore, the median values of the dose area product ([DAP], a radiographic dose determinant) were 9.72 and 19.4 cGycm 2 in the pre-implementation and post-implementation phases, respectively. Conclusion: Although the data management software used in this study helped reduce the radiation exposure time by 16.3 ms in mammography, its impact on the mean accumulated AGD was unfavorable. Similarly, radiographic exposure indices, including DAP, tube voltage, tube current, and exposure time, were not significantly different after the data management software was implemented. Close monitoring of patient radiation doses in mammography and radiography, and dose reduction will become possible if imaging facilities use DRLs and ADs via automated systems.