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Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation

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Automating population dose survey processing-An Australian feasibility study.

Kam L Lee¹, Masoumeh Sanagou¹, Hok C Lau²

¹Medical Imaging Section, Australian Radiation Protection and Nuclear Safety, Agency, Yallambie, Victoria, Australia.

Medical Physics

|July 9, 2024

Summary

This summary is machine-generated.

An automated tool was developed to categorize adult computed tomography (CT) procedures, enabling efficient population dose assessment in Australia. This method significantly reduces data collection efforts for national diagnostic imaging dose monitoring.

Keywords:

population dose procedure categorization rule‐based classifier text classification

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Area of Science:

Medical Imaging
Radiology
Public Health

Background:

Comprehensive dose data for adult computed tomography (CT) procedures in Australia is outdated.
Collecting this data is labor-intensive, hindering national population dose assessments.
Automating data collection could streamline the process and increase coverage.

Purpose of the Study:

Develop an automated tool for categorizing electronic imaging procedure records.
Standardize broad procedure types for consistent data analysis.
Validate the tool and assess its feasibility for computing population dose.

Main Methods:

Implemented a rule-based classifier using semantic and clinical rules.
Built and refined keyword lists from thousands of unique study descriptions.
Validated the classifier with radiologist input for ground truth.

Main Results:

The classifier achieved high accuracy, correctly classifying 2789 out of 2794 study types in a sample of 238,139 studies.
Demonstrated the feasibility of automated classification and highlighted the need for data pre-processing.
Compiled dose statistics for 21 categories using the large study dataset.

Conclusions:

The automated classifier demonstrated excellent performance on data from public facilities.
Potential bias exists as the classifier has not been tested on a mix of private and public facilities.
Further testing is required on a more representative dataset to confirm generalizability.