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Summary
This summary is machine-generated.

An open-access AI algorithm accurately assesses patient centering in CT scans across multiple body regions and scanners. This artificial intelligence model shows strong correlations with manual measurements, aiding in the evaluation of image quality and patient positioning.

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence in Healthcare
  • Radiology

Background:

  • Patient centering is crucial for optimal image quality and diagnostic accuracy in CT scans.
  • Manual assessment of patient centering can be time-consuming and subjective.
  • The need for automated, objective methods to evaluate image segmentation and centering in multi-center studies is increasing.

Purpose of the Study:

  • To develop and validate an open-access artificial intelligence (AI) algorithm for assessing image segmentation and patient centering in CT examinations.
  • To evaluate the AI algorithm's performance across multiple body regions (head, chest, abdomen-pelvis), patient demographics, and scanner types.
  • To compare the AI algorithm's centering measurements against manual estimations.

Main Methods:

  • An open-access AI algorithm (AIc) was developed for image segmentation and patient centering analysis.
  • 825 CT scans (head, chest, abdomen-pelvis) from 275 patients were analyzed.
  • AIc-derived vertical and horizontal centering measurements were compared with manual measurements.

Main Results:

  • The AIc demonstrated strong correlations with manual estimates for both vertical (r=0.93-0.95) and horizontal (r=0.80-0.85) off-centering.
  • High performance was observed across different age groups, genders, and multiple scanners from five institutions.
  • The AIc achieved an area under the receiver operating characteristic curve ranging from 0.72 to 0.99 for distinguishing centered from off-centered scans.

Conclusions:

  • The developed AI algorithm effectively assesses vertical and horizontal patient off-centering in CT examinations.
  • PET/CT scans frequently show significant off-centering, particularly vertical deviations exceeding 30 mm.
  • The AIc provides a reliable, automated tool for evaluating patient centering, with slightly better performance in vertical centering assessment.