Identifying optimal dose head CT acquisition techniques through cluster analysis from 904,209 scans - Summary - MDSpire
Coming Soon: Introducing MDSpire News. Learn more
Conexiant’s news site is now MDSpire News. Learn more

Determining Ideal Head CT Acquisition Methods via Cluster Analysis of 904,209 Scans

  • By

  • Berk Yildirim

  • Denise Bos

  • Taewoon Kang

  • Carly Stewart

  • Timothy P. Szczykutowicz

  • Rebecca Smith-Bindman

  • September 2, 2026

Share

Objective:

To evaluate routine head CT examinations using a crowdsourcing approach and k-means clustering to identify acquisition techniques associated with higher versus lower radiation output.

Approach:
  • Data Collection: Diagnostic head CT examinations were recorded in the UCSF International CT Dose Registry from January 1, 2015, through March 11, 2021, across 131 medical facilities in seven countries.
  • Exclusion Criteria: CT examinations for biopsy, surgery, or radiation treatment, as well as those lacking data, were excluded from the analysis.
  • Statistical Analysis: K-means clustering was applied to group scans based on acquisition parameters, with analyses stratified by scan type and patient age group.
Key Findings:
  • Substantial variation in CT radiation exposure exists, primarily due to differences in parameter selection within CT protocols.
  • The analysis aimed to identify lower-dose protocols used in routine clinical practice.
Interpretation:

The study highlights the importance of addressing variability in CT acquisition methods to mitigate unnecessary radiation exposure.

Limitations:
  • The study excluded certain types of CT examinations, which may limit the generalizability of the findings regarding routine clinical practice.
  • Data were collected from a specific registry, which may not represent all clinical settings and could affect the applicability of the results.
Conclusion:

Standardizing CT acquisition methods could help reduce radiation exposure while maintaining image quality. ---

Original Source(s)

Related Content