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Development and Evaluation of an Automated Protocol Recommendation System for Chest CT Using Natural Language

Patrik Rogalla1, Jennifer Fratesi1, Sonja Kandel1

  • 1Joint Department of Medical Imaging, University of Toronto, Toronto, ON, Canada.

Canadian Association of Radiologists Journal = Journal L'Association Canadienne Des Radiologistes
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A new Protocol Recommendation System (PRS) for chest CT imaging requests shows accuracy comparable to human radiologists. This AI tool could help manage increasing radiologist workloads effectively.

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Area of Science:

  • Radiology
  • Artificial Intelligence
  • Medical Informatics

Background:

  • Chest CT imaging requests are increasing, posing a workload challenge for radiologists.
  • Accurate protocolling of imaging requests is crucial for effective diagnosis and patient care.
  • Existing methods for protocolling can be time-consuming and prone to variability.

Purpose of the Study:

  • To assess the clinical performance of an automated Protocol Recommendation System (PRS) for chest CT imaging requests.
  • To compare the accuracy and clinical acceptability of the PRS against human expert protocolling.
  • To determine the potential of the PRS in assisting radiologists with their workload.

Main Methods:

  • A multinomial logistic regression classifier was trained using a bag-of-words model on historical chest CT imaging requests.
  • The PRS was evaluated against 300 clinically executed protocols (CEP) protocolled by four human readers.
  • Reader agreement was assessed using Fleiss' Kappa, and accuracy/acceptability scores were calculated for both PRS and CEP.

Main Results:

  • The PRS demonstrated accuracy of 84.3% and clinical acceptability of 98.6%.
  • Human readers achieved 83.0% accuracy and 99.3% clinical acceptability.
  • Reader agreement (Fleiss' Kappa) was high at 0.805, indicating good inter-reader reliability.

Conclusions:

  • The Protocol Recommendation System (PRS) performs with accuracy similar to human radiologists in protocolling chest CT requests.
  • The PRS shows potential as a valuable tool to help radiologists manage increasing imaging request volumes.
  • Automated systems like the PRS can support clinical decision-making and improve efficiency in radiology departments.