How DOSE by Qaelum tackles the goals of patient exposure analysis of the new IAEA Safety Report Series no. 112

August 24, 2023

The recently published report from the International Atomic Energy Agency [1] provides a comprehensive description of dose management systems, including the rationale for monitoring patient radiation exposure, the required data and its collection, the relevant analysis, as well as its implementation. DOSE by Qaelum is a dose management solution that contains all the necessary tools to monitor patient radiation dose, image quality, and department performance across patients, modalities, facilities and vendors.

It is widely known that optimization in medical radiation exposure must account for both radiation dose and image quality following the ALARA principle [2]. The IAEA report provides recommendations on assessing the collected data to track the relationship between the size of the patient, exposure, and quality of the image. Ensuring a 20% confidence interval at a 95% confidence level requires study cohorts of 20-30 procedures within a sufficiently narrow category of e.g. clinical indication, patient size, scanner etc. Cohort trends in DLP and CTDI with respect to patient size (e.g. weight, water equivalent diameter) and image quality as visualized in DOSE can be seen in Figures 1 and 2.


Figure 1. DLP as a function of patient weight for the same scanner. Outliers can be easily spotted and investigated to determine deviations in exposure parameters and technique.

Automated image quality analysis is performed using the Global Noise Level metric [3,4]. Noise is presented as the standard deviation in Hounsfield units per tissue type on a three-dimensional chart (Figure 2) as a function of patient size (e.g. water equivalent diameter) and dose (e.g. CTDIvol), and linked to the convolution kernel reconstruction. DLP can also be visualized as a function of patient height, and chart data can be filtered by patient age and weight groups, as specified in Table 3 of the IAEA report.


Figure 2. Automated image noise for soft tissue evaluated on a three-dimensional chart as a function of patient water equivalent diameter and CTDI.  

Four specific goals of patient radiation exposure data analysis are outlined in the report and summarized below, including some examples of their implementation in DOSE.

Goal 1: Optimization and consistency of imaging practices across and within devices, facilities, and operators. More specifically, the monitoring of:

  • Dose data trends over time
    • Trends in dose data as a function of the time of day to identify and target any differences between shifts
    • Trends in dose data and number of exams to assess optimization efforts, changes in exam frequency, and collective dose to a population in terms of typical values (Figure 3)
    • Changes in imaging protocols and assessment of dose reduction in newly purchased equipment (Figure 4)


Figure 3. Daily trend of the number of studies, mean and cumulated administered radioactivity (MBq), and unique patient count for a nuclear medicine hotlab management system. The parameter can be changed to e.g. effective dose to evaluate collective population dose.


Figure 4. CTDI as a function of patient size and attenuation (in terms of the water equivalent diameter) for two scanners. The scanner plotted in blue clearly contains more outliers and a more dispersed distribution, indicating more potential for optimization.

  • Examinations performed most frequently and examinations with the highest contribution to patient radiation exposure for better optimization targeting
  • Variability in protocols including acquisition parameters, patient positioning and attributes, deviations from typical values
  • Adequate image quality for diagnosis

Charts can be created for individual and multiple devices at the same time, as well as across facilities, that can be further filtered by multiple parameters including date range, operator, protocol name, patient age and size, and many others. Moreover, DOSE offers the ability to customize exam groupings to facilitate the transition from protocols on the basis of anatomical region only to protocols that take into account clinical indications, as well as the monitoring of typical values and local, regional, and national diagnostic reference levels as described in table 5 of the report.

Goal 2: Safe and precise individual patient imaging, utilizing:

  • Dose alerts for threshold and trigger level exceedances for deterministic effects in individual patient cases, configurable in DOSE for customizable combinations of parameters, time intervals and reference values
  • Data outliers per protocol and patient size in the 5th and 95th percentiles to investigate potential reasons for under- and over-exposure
  • Close exposure monitoring and organ dose estimates for pregnant and pediatric patients
  • Flagging functionality for unintended exposures such as duplicated examinations, outliers, incorrect protocol use/patient/body part etc.)


Figure 5. Live dashboard feature for operators that displays the last studies performed, benchmarks its dose against similar studies, and allows technologists to flag any issues related to unintended exposures or justify abnormal dose ranges.

  • Record of patient exposure history across different modalities

Goal 3: Supporting the justification and appropriateness process by:

  • Providing typical effective dose values for specific referrals

Goal 4: Information on collective dose to a population from different medical exposures.

Table 8 of the report lists all the feature specifications of a dose management system including reporting, queries, and metrics.

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[1] INTERNATIONAL ATOMIC ENERGY AGENCY, Patient Radiation Exposure Monitoring in Medical Imaging, Safety Reports Series No. 112, IAEA, Vienna (2023).

[2] International Commission on Radiological Protection. Recommendations of the ICRP. Pergamon Press for the International Commission on Radiological Protection; 1977.

[3] Christianson O, Winslow J, Frush DP, Samei E. Automated Technique to Measure Noise in Clinical CT Examinations, American Journal of Roentgenology. 2015; 205: W93-W99.

[4] Ria F, Wilson JM, Zhang Y, Samei S. Image noise and dose performance across a clinical population: Patient size adaptation as a metric of CT performance, Medical Physics. 2017; 44: 2141-2147.

Anna Romanyukha received her Ph.D. degree in medical physics from the Centre of Medical Radiation Physics (UOW, Australia) and her M.Sc. degree in health physics from Georgetown University (Washington DC, USA). She worked as a post baccalaureate and pre doctoral fellow at the National Cancer Institute (NIH, Washington DC) on various projects including radiation dose estimation from diagnostic exposures. She now works in Qaelum NV, focusing on advanced software tools in patient radiation dose management and quality.

Niki Fitousi, PhD, is a certified medical physicist with professional experience in all fields of Medical Physics (Radiation Therapy, Diagnostic Radiology, Nuclear Medicine, Radiation Protection). She is currently the Head of Research and Applications in Qaelum, focusing mostly in the fields of radiation dose management, quality and efficiency in medical imaging. She is also a member of the Medical Physics World Board of the International Organization for Medical Physics.