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Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources

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Building a comprehensive quality infrastructure in a large radiography practice.

Z Long¹, S J Dean¹, A K Forney¹

¹Department of Radiology, Mayo Clinic, Rochester, MN, USA.

Radiography (London, England : 1995)

|June 2, 2026

Summary

This summary is machine-generated.

A new radiography quality infrastructure standardized imaging and improved quality over six years. This system integrates image scoring, radiologist feedback, and data analytics for better technologist education and equipment management.

Keywords:

DICOM Image quality Quality infrastructure Radiography

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Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources

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Published on: October 6, 2023

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Published on: April 11, 2018

Area of Science:

Radiological Sciences
Medical Imaging Technology
Quality Improvement in Healthcare

Background:

Modern radiography faces challenges with high volume, staffing, and equipment variability.
Standardizing image acquisition and processing is crucial for consistent diagnostic quality.
A robust infrastructure is needed to address these challenges in radiography practices.

Purpose of the Study:

To design, implement, and evaluate a radiography infrastructure for imaging standardization.
To improve overall image quality and technologist performance through a structured system.
To provide a framework for ongoing quality assessment and enhancement in diagnostic imaging.

Main Methods:

Developed a four-component quality infrastructure including image scoring, radiologist feedback, DICOM metadata analytics, and equipment scoring.
Utilized a standardized four-point scale for clinical image quality assessment across multiple projections.
Employed custom MATLAB programs for DICOM metadata analysis and a formula-based system for equipment ranking.

Main Results:

Over six years, 87,437 radiographs were scored, with average scores consistently above the monitoring threshold.
The SARS-CoV-2 pandemic was associated with a minor, statistically significant drop in average image scores.
DICOM analytics identified areas for improvement, leading to significant reductions in exposure index variability for specific exams.

Conclusions:

The integrated quality infrastructure is feasible and essential for technologist education and image quality standardization.
Quantitative analysis of clinical data and equipment performance provides critical insights for radiography practices.
This adaptable infrastructure supports continuous quality improvement and informed equipment management.