Quantitative evaluation of 4D Cone beam CT scans with reduced scan time in lung cancer patients

Research output: Contribution to journalArticle

  • External authors:
  • Abigail Bryce-atkinson
  • John Rodgers
  • Geoff Budgell
  • Gillian Whitfield

Abstract

Purpose
Image guided radiotherapy (IGRT) based on respiration correlated cone-beam CT (4D-CBCT) provides accurate tumour localisation in lung cancer patients by taking into account respiratory motion when deriving setup correction. However, 4D-CBCT scan times are typically longer than for acquisition of 3D-CBCT scans, e.g. 4 min. This work aims to quantitatively evaluate the effect of reduced scan times on 4D-CBCT image quality and registration accuracy in lung cancer patients.

Methods and materials
Scan times down to 1 min were simulated by retaining only projection images corresponding to every second, third or fourth respiratory cycle in forty-four 4D-CBCTs from 15 lung cancer patients. In addition twenty 2-minute scans were acquired for 12 lung cancer patients. Image quality was quantified by assessing registration accuracy in the shorter scan times, comparing to the 4-minute scan registration result where available as reference.

Results
Use of 2-minute scans had little impact on registration accuracy or ability to detect tumour motion: automatic registration accuracy was within 2 mm in 6/8 scans analysed with 2-minute acquisitions, and 96.6% of registration discrepancies were within 2 mm for the simulated scans. When the scan time simulated was below 2 min, automatic registration results still agreed within 2 mm for 84.7% of scans, however visual image quality was considerably degraded.

Conclusion
A 4D-CBCT acquisition time of 2 min produces scans of sufficient image quality for IGRT in most lung cancer patients, as demonstrated quantitatively by assessing the impact on automatic registration accuracy in simulated and real acquisitions.

Bibliographical metadata

Original languageEnglish
Pages (from-to)64-70
Number of pages6
JournalRadiotherapy and Oncology
Volume136
Early online date11 Apr 2019
DOIs
Publication statusPublished - Jul 2019