The spine and carina as a surrogate for target registration in cone-beam CT imaging verification in locally advanced lung cancer radiotherapy

Radiol Oncol. 2023 Mar 22;57(1):86-94. doi: 10.2478/raon-2022-0048. eCollection 2023 Mar 1.


Background: The aim of the study was to evaluate the accuracy of volumetric lung image guidance using the spine or carina as a surrogate to target for image registration, as the best approach is not established.

Patients and methods: Cone beam computed tomography images from the 1st, 10th, 15th, and 20th fraction in 40 lung cancer patients treated with radical radiotherapy were retrospectively registered to planning CT, using three approaches. The spine and carina alignment set-up deviations from a reference (tumour/lymph nodes) registration in the lateral (LAT), longitudinal (LONG) and vertical (VRT) directions were analysed and compared. Tumour location and nodal stage influence on registration accuracy were explored.

Results: The spine and carina mean set-up deviation from reference were largest in the LONG, with the best match in the VRT and LAT, respectively. Both strategies were more accurate in central tumours, with the carina being more precise in 50% LAT and 66% LONG mean deviations. For all measurements in all patients a carina vs. spine registration comparison showed improved carina accuracy in LAT and LONG. In comparative subgroup analysis the carina was superior compared to spine in LAT and LONG in centrally located tumours, N2 and N3. Both strategies were comparable for peripheral tumours and N0.

Conclusions: Carina registration shows greater accuracy compared to spine in the LAT and LONG directions and is superior in central tumours, N2 and N3. The spine and carina surrogates are equally accurate for peripheral tumours and N0. We propose the carina as a surrogate to target for CBCT image registration in locally advanced lung cancer.

Keywords: adaptive radiotherapy; carina registration; locally advanced lung cancer; spine registration; tumour registration; volumetric image verification.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cone-Beam Computed Tomography / methods
  • Humans
  • Lung
  • Lung Neoplasms* / diagnostic imaging
  • Lung Neoplasms* / pathology
  • Lung Neoplasms* / radiotherapy
  • Radiotherapy Planning, Computer-Assisted / methods
  • Radiotherapy, Image-Guided* / methods