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Updated: Jun 20, 2026

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification (ADCI) and Dose Estimation
Published on: September 4, 2017
MIRD Pamphlet No. 34, Part 2: Benchmarking of MIRDct Software for CT Organ Dose Estimation
Gunjan Kayal1, Juan Camilo Ocampo Ramos2, Laura E Dinwiddie3
1Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York; kayalg1@mskcc.org.
Abstract:
Accurate estimation of organ and effective doses in CT imaging is essential for risk assessment, protocol optimization, and personalized care in diagnostic radiology and nuclear medicine. We systematically benchmarked MIRDct, a freely available mesh phantom-based CT dose calculation software, against established reference software (National Cancer Institute Dosimetry System for Computed Tomography [NCICT] and VirtualDose [Virtual Phantoms]) by evaluating agreement between organ-absorbed doses and effective doses across representative scanners, phantoms, and protocols. Methods: Organ absorbed and effective doses were calculated for adult and pediatric phantoms for whole-body (WB) and regional (head, chest, abdomen-pelvis [AP]) CT examinations. MIRDct uses mesh-based International Commission on Radiologic Protection (ICRP) reference phantoms with anatomically realistic organ surfaces, whereas NCICT and VirtualDose use voxel-based ICRP 110 and hybrid Rensselaer Polytechnic Institute/University of Florida phantom models, respectively. For each software, volumetric CT dose index (CTDIvol) values were obtained from the software interface using matched acquisition parameters; in MIRDct, these values were derived from scanner console-reported outputs for the corresponding protocol settings. Organ absorbed doses, dose coefficients, and effective doses were computed across 44 matched scanner-phantom-protocol configurations. Inter-software differences were summarized using medians and interquartile ranges. For regional protocols, organ-absorbed doses were stratified by irradiation category (in-field, partial-in-field, out-of-field), to assess field-dependent variability. Results: CTDIvol values reported by the 3 software tools showed close agreement across matched protocol configurations, with median inter-software differences not exceeding 7%. For in-field organs, dose coefficients from NCICT and VirtualDose generally agreed with MIRDct values within ±25% across adult and pediatric head, chest, AP, and WB protocols, indicating good agreement in the primary beam region. Larger relative deviations occurred for partial-in-field and out-of-field organs, where doses were scatter-dominated; however, absolute organ doses were less than 2 mGy, limiting clinical relevance. Effective dose estimates showed similar concordance: differences were below 25% for all VirtualDose comparisons except head scans and for WB protocols, whereas adult chest and AP protocols differed by up to 40% relative to NCICT. These differences were associated with variations in phantom anatomy and fixed, pre-tabulated CTDIvol reference values in NCICT and VirtualDose, compared with protocol-specific, console-reported CTDIvol inputs in MIRDct. Conclusion: MIRDct provides organ- and effective-dose estimates that are broadly consistent with established CT dosimetry tools, with agreement typically within ±25% for in-field organs and within a few milligray for absolute doses across adult and pediatric protocols. The use of mesh-based ICRP reference phantoms with anatomically realistic organ surfaces, protocol-specific CTDIvol inputs from the scanner console, and uncertainty propagation supports its application as a research tool for CT dose benchmarking, protocol optimization, and quality assurance in diagnostic CT and nuclear medicine.
