Evaluation of a commercial deformable image registration algorithm for dual-energy CT processing

Geometric evaluation and quantifying dosimetric impact of diverse deformable image registration algorithms on abdomen images with biomechanically modeled deformations

PURPOSE

Deformable image registration (DIR) has been increasingly used in radiation therapy (RT). The accuracy of DIR algorithms and how it impacts on the RT plan dosimetrically were examined in our study for abdominal sites using biomechanically modeled deformations.

METHODS

Five pancreatic cancer patients were enrolled in this study. Following the guidelines of AAPM TG-132, a patient-specific quality assurance (QA) workflow was developed to evaluate DIR for the abdomen using the TG-132 recommended virtual simulation software ImSimQA (Shrewsbury, UK). First, the planning CT was deformed to simulate respiratory motion using the embedded biomechanical model in ImSimQA. Additionally, 5 mm translational motion was added to the stomach, duodenum, and small bowel. The original planning CT and the deformed CT were then imported into Eclipse and MIM to perform DIR. The output displacement vector fields (DVFs) were compared with the ground truth from ImSimQA. Furthermore, the original treatment plan was recalculated on the ground-truth deformed CT and the deformed CT (with Eclipse and MIM DVF). The dose errors were calculated on a voxel-to-voxel basis.

RESULTS

Data analysis comparing DVF from Eclipse versus MIM show the average mean DVF magnitude errors of 2.8 ± 1.0  versus 1.1 ± 0.7 mm for stomach and duodenum, 5.2 ± 4.0  versus 2.5 ± 1.0 mm for small bowel, and 4.8 ± 4.1  versus 2.7 ± 1.1 mm for the gross tumor volume (GTV), respectively, across all patients. The mean dose error on stomach+duodenum and small bowel were 2.3 ± 0.6% for Eclipse, and 1.0 ± 0.3% for MIM. As the DIR magnitude error increases, the dose error range increase, for both Eclipse and MIM.

CONCLUSION

In our study, an initial assessment was conducted to evaluate the accuracy of DIR and its dosimetric impact on radiotherapy. A patient-specific DIR QA workflow was developed for pancreatic cancer patients. This workflow exhibits promising potential for future implementation as a clinical workflow.

Motion-compensated scheme for sequential scanned statistical iterative dual-energy CT reconstruction

Objective.Dual-energy computed tomography (DECT) has been widely used to reconstruct numerous types of images due its ability to better discriminate tissue properties. Sequential scanning is a popular dual-energy data acquisition method as it requires no specialized hardware. However, patient motion between two sequential scans may lead to severe motion artifacts in DECT statistical iterative reconstructions (SIR) images. The objective is to reduce the motion artifacts in such reconstructions.Approach.We propose a motion-compensation scheme that incorporates a deformation vector field into any DECT SIR. The deformation vector field is estimated via the multi-modality symmetric deformable registration method. The precalculated registration mapping and its inverse or adjoint are then embedded into each iteration of the iterative DECT algorithm.Main results.Results from a simulated and clinical case show that the proposed framework is capable of reducing motion artifacts in DECT SIRs. Percentage mean square errors in regions of interest in the simulated and clinical cases were reduced from 4.6% to 0.5% and 6.8% to 0.8%, respectively. A perturbation analysis was then performed to determine errors in approximating the continuous deformation by using the deformation field and interpolation. Our findings show that errors in our method are mostly propagated through the target image and amplified by the inverse matrix of the combination of the Fisher information and Hessian of the penalty term.Significance.We have proposed a novel motion-compensation scheme to incorporate a 3D registration method into the joint statistical iterative DECT algorithm in order to reduce motion artifacts caused by inter-scan motion, and successfully demonstrate that interscan motion corrections can be integrated into the DECT SIR process, enabling accurate imaging of radiological quantities on conventional SECT scanners, without significant loss of either computational efficiency or accuracy.

Multiorientation Simultaneous Computation of Back-Projection CT Image Reconstruction Algorithm in Staging Diagnosis of Bladder Cancer

The objective of this research was to investigate the multidirectional synchronous calculation of the back-projection computed tomography (CT) image reconstruction algorithm (MSBP) in the staging diagnosis of bladder cancer. Sixty patients with bladder cancer admitted to the hospital were selected for enhanced CT scanning, all of which were randomly divided into control group (n = 30) and study group (n = 30). The filtered back-projection (FBP) algorithm was employed to reconstruct the scanned image, and the MSBP was additionally applied to the images of the study group. Fringe artifact (SA), overall mass (OQ), effective radiation dose (ED), CT dose-exponential volume (CTDI), and dose-length product (DLP) of the two groups of images were compared and analyzed. The results showed that the total time of the traditional algorithm was 5.473 s, and the total time of MSBP combined with FBP algorithm was 2.832 s, which was significantly higher than that of the traditional algorithm (P < 0.05). CT scan bladder cancer staging results of all patients were compared with surgical pathological staging results, and the results were evaluated according to the coincidence rate. SA in the study group was lower than that in the control group (P < 0.05), and OQ was not statistically significant. The ED of the study group was significantly lower than that of the control group by 33%. The coincidence rate of postoperative pathological staging results and CT staging results was 96%, and T1, T2a, and T4 coincidence rate was 100%, The coincidence rates of T2b, T3a, and T3b were 90%, 83.3%, and 66.67%, respectively. In summary, using MSBP method combined with FBP algorithm can improve OQ while reducing ED of patients. The introduction of MSBP into CT reconstruction image simplified the pixel location operation of projection calculation, showing an important application value in preoperative staging diagnosis of bladder cancer.