A novel evaluation model of image registration for cone-beam computed tomography guided lung cancer radiotherapy

The aim of the study was to establish a weighted comprehensive evaluation model (WCEM) of image registration for cone-beam computed tomography (CBCT) guided lung cancer radiotherapy that considers the geometric accuracy of gross target volume (GTV) and organs at risk (OARs), and assess the registration accuracy of different image registration methods to provide clinical references.

The planning CT and CBCT images of 20 lung cancer patients were registered using diverse algorithms (bony and grayscale) and regions of interest (target, ipsilateral, and body). We compared the coverage ratio (CR) of the planning target volume (PTV_CT) to GTV_CBCT, as well as the dice similarity coefficient (DSC) of the GTV and OARs, considering the treatment position across various registration methods. Furthermore, we developed a mathematical model to assess registration results comprehensively. This model was evaluated and validated using CRFs across four automatic registration methods.

The grayscale registration method, coupled with the registration of the ipsilateral structure, exhibited the highest level of automatic registration accuracy, the DSC were 0.87 ± 0.09 (GTV), 0.71 ± 0.09 (esophagus), 0.74 ± 0.09 (spinal cord), and 0.91 ± 0.05 (heart), respectively. Our proposed WCEM proved to be both practical and effective. The results clearly indicated that the grayscale registration method, when applied to the ipsilateral structure, achieved the highest CRF score. The average CRF scores, excellent rates, good rate and qualification rates were 58 ± 26, 40%, 75%, and 85%, respectively.

This study successfully developed a clinically relevant weighted evaluation model for CBCT-guided lung cancer radiotherapy. Validation confirmed the grayscale method's optimal performance in ipsilateral structure registration.