Quantitative evaluation of the performance of different deformable image registration algorithms in helical, axial, and cone-beam CT images using a mobile phantom

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

BACKGROUND

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.

METHODS

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 (PTVCT) to GTVCBCT, 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.

RESULTS

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.

CONCLUSIONS

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.

Dynamic CT myocardial perfusion without image registration

The aim of this study was to validate a motion-immune (MI) solution to dynamic CT myocardial perfusion measurement, in the presence of motion without image registration. The MI perfusion technique was retrospectively validated in six swine (37.3 ± 7.5 kg) with a motion-susceptible (MS) perfusion technique performed for comparison. In each swine, varying severities of stenoses were generated in the left anterior descending (LAD) coronary artery using a balloon under intracoronary adenosine stress, followed by contrast-enhanced imaging with 20 consecutive volume scans per stenosis. Two volume scans were then systematically selected from each acquisition for both MI and MS perfusion measurement, where the resulting LAD and left circumflex (LCx) measurements were compared to reference microsphere perfusion measurements using regression and diagnostic performance analysis. The MI (P_MI) and microsphere (P_MICRO) perfusion measurements were related through regression by P_MI = 0.98 P_MICRO + 0.03 (r = 0.97), while the MS (P_MS) and microsphere (P_MICRO) perfusion measurements were related by P_MS = 0.62 P_MICRO + 0.15 (r = 0.89). The accuracy of the MI and MS techniques in detecting functionally significant stenosis was 93% and 84%, respectively. The motion-immune (MI) perfusion technique provides accurate myocardial perfusion measurement in the presence of motion without image registration.

Comparison of an in-house hybrid DIR method to NiftyReg on CBCT and CT images for head and neck cancer

An in-house hybrid deformable image registration (DIR) method, which combines free-form deformation (FFD) and the viscous fluid registration method, is proposed. Its results on the planning computed tomography (CT) and the day 1 treatment cone-beam CT (CBCT) image from 68 head and neck cancer patients are compared with the results of NiftyReg, which uses B-spline FFD alone. Several similarity metrics, the target registration error (TRE) of annotated points, as well as the Dice similarity coefficient (DSC) and Hausdorff distance (HD) of the propagated organs at risk are employed to analyze their registration accuracy. According to quantitative analysis on mutual information, normalized cross-correlation, and the absolute pixel value differences, the results of the proposed DIR are more similar to the CBCT images than the NiftyReg results. Smaller TRE of the annotated points is observed in the proposed method, and the overall mean TRE for the proposed method and NiftyReg was 2.34 and 2.98 mm, respectively (p < 0.001). The mean DSC in the larynx, spinal cord, oral cavity, mandible, and parotid given by the proposed method ranged from 0.78 to 0.91, significantly higher than the NiftyReg results (ranging from 0.77 to 0.90), and the HD was significantly lower compared to NiftyReg. Furthermore, the proposed method did not suffer from unrealistic deformations as the NiftyReg did in the visual evaluation. Meanwhile, the execution time of the proposed method was much higher than NiftyReg (96.98 ± 11.88 s vs. 4.60 ± 0.49 s). In conclusion, the in-house hybrid method gave better accuracy and more stable performance than NiftyReg.