Cone-beam Computed Tomography Registration Research Articles

Application of intraoral scanning registration implant robot in dental implant surgery.

This paper aims to investigate the application of intraoral scanning and cone beam computed tomography (CBCT) registration implant robot in dental implant surgery. The data of 40 cases with dental defect of robot-assisted implantation from November 2023 to May 2024 were retrospectively analyzed. Before the operation, the intraoral scan data and CBCT data of the positioning markers were automatically fused with the initial CBCT images, and the registration error was calculated. The average registration error of positioning markers was determined during the operation, and the implantation accuracy was analyzed after the operation. The intraoral scan data and CBCT data of 40 patients with dental defect wearing positioning markers were successfully registered with the initial CBCT image, and the registration errors were (0.157±0.026) mm and (0.154±0.033) mm, respectively. Statistical analysis showed no statistical significance between them. The registration errors of the marker was (0.037 3±0.003 6) mm. A total of 55 implants were performed, and the total deviations of the implant point and the apical point were (0.78±0.41) and (0.89±0.28) mm, respectively. The transverse deviations of the implant point and the apical point were (0.44±0.36) and (0.58±0.25) mm, respectively. The depth deviations of the implant point and the apical point were (0.51±0.32) and (0.54±0.36) mm, respectively. The deviation of the implant angle was 1.24°±0.67°. The fusion technology based on intraoral scanning and CBCT registration can meet the accuracy requirements of preoperative registration of oral implant robots. The technology increases the choice of registration methods before robot-assisted dental implant surgery and reduces the multiple radiation exposuresof the patient.

Validation of a novel AI-based automated multimodal image registration of CBCT and intraoral scan aiding presurgical implant planning.

The objective of this study is to assess accuracy, time-efficiency and consistency of a novel artificial intelligence (AI)-driven automated tool for cone-beam computed tomography (CBCT) and intraoral scan (IOS) registration compared with manual and semi-automated approaches. A dataset of 31 intraoral scans (IOSs) and CBCT scans was used to validate automated IOS-CBCT registration (AR) when compared with manual (MR) and semi-automated registration (SR). CBCT scans were conducted by placing cotton rolls between the cheeks and teeth to facilitate gingival delineation. The time taken to perform multimodal registration was recorded in seconds. A qualitative analysis was carried out to assess the correspondence between hard and soft tissue anatomy on IOS and CBCT. In addition, a quantitative analysis was conducted by measuring median surface deviation (MSD) and root mean square (RMS) differences between registered IOSs. AR was the most time-efficient, taking 51.4 ± 17.2 s, compared with MR (840 ± 168.9 s) and SR approaches (274.7 ± 100.7 s). Both AR and SR resulted in significantly higher qualitative scores, favoring perfect IOS-CBCT registration, compared with MR (p = .001). Additionally, AR demonstrated significantly superior quantitative performance compared with SR, as indicated by low MSD (0.04 ± 0.07 mm) and RMS (0.19 ± 0.31 mm). In contrast, MR exhibited a significantly higher discrepancy compared with both AR (MSD = 0.13 ± 0.20 mm; RMS = 0.32 ± 0.14 mm) and SR (MSD = 0.11 ± 0.15 mm; RMS = 0.40 ± 0.30 mm). The novel AI-driven method provided an accurate, time-efficient, and consistent multimodal IOS-CBCT registration, encompassing both soft and hard tissues. This approach stands as a valuable alternative to manual and semi-automated registration approaches in the presurgical implant planning workflow.

Accuracy evaluation of dental CBCT and scanned model registration method based on pulp horn mapping surface: an in vitro proof-of-concept

Background and aim3D fusion model of cone-beam computed tomography (CBCT) and oral scanned data can be used for the accurate design of root canal access and guide plates in root canal therapy (RCT). However, the pose accuracy of the dental pulp and crown in data registration has not been investigated, which affects the precise implementation of clinical planning goals. We aimed to establish a novel registration method based on pulp horn mapping surface (PHMSR), to evaluate the accuracy of PHMSR versus traditional methods for crown-pulp registration of CBCT and oral scan data.Materials and methodsThis vitro study collected 8 groups of oral scanned and CBCT data in which the left mandibular teeth were not missing, No. 35 and No. 36 teeth were selected as the target teeth. The CBCT and scanned model were processed to generate equivalent point clouds. For the PHMSR method, the similarity between the feature directions of the pulp horn and the surface normal vectors of the crown were used to determine the mapping points in the CBCT point cloud that have a great influence on the pulp pose. The small surface with adjustable parameters is reconstructed near the mapping point of the crown, and the new matching point pairs between the point and the mapping surface are searched. The sparse iterative closest point (ICP) algorithm is used to solve the new matching point pairs. Then, in the C + + programming environment with a point cloud library (PCL), the PHMSR, the traditional sparse ICP, ICP, and coherent point drift (CPD) algorithms are used to register the point clouds under two different initial deviations. The root square mean error (RSME) of the crown, crown-pulp orientation deviation (CPOD), and position deviation (CPPD) were calculated to evaluate the registration accuracy. The significance between the groups was tested by a two-tailed paired t-test (p < 0.05).ResultsThe crown RSME values of the sparse ICP method (0.257), the ICP method (0.217), and the CPD method (0.209) were not significantly different from the PHMSR method (0.250). The CPOD and CPPD values of the sparse ICP method (4.089 and 0.133), the ICP method (1.787 and 0.700), and the CPD method (1.665 and 0.718) than for the PHMSR method, which suggests that the accuracy of crown-pulp registration is higher with the PHMSR method.ConclusionCompared with the traditional method, the PHMSR method has a smaller crown-pulp registration accuracy and a clinically acceptable deviation range, these results support the use of PHMSR method instead of the traditional method for clinical planning of root canal therapy.

Adaptable cascaded registration for personalized maxilla completion and cleft defect volume estimation.

Cone-beam computed tomography (CBCT) images provide high-resolution insights into the underlying craniofacial anomaly in patients with cleft lip and palate (CLP), requiring non-negligible annotation costs to measure the cleft defect for the guidance of the clinical secondary alveolar bone graft procedures. Considering the cumbersome volumetric image acquisition, there is a lack of paired CLP CBCTs and normal CBCTs for learning-based anatomical structure restoration models. Nowadays, the registration-based method relieves the annotation burden, though one-shot registration and the regular mask are limited to handling fine-grained shape variations and harmony between restored bony tissues and the defectedmaxilla. This study aimed to design and evaluate a novel method for deformable partial registration of the CLP CBCTs and normal CBCTs, enabling personalized maxilla completion and cleft defect volume prediction from CLPCBCTs. We proposed an adaptable deep registration framework for personalized maxilla completion and cleft defect volume prediction from CLP CBCTs. The key ingredient was a cascaded partial registration to exploit the maxillary morphology prior and attribute transfer. Cascaded registration with coarse-to-fine registration fields handled morphological variations of cleft defects and fine-grained maxillary restoration. We designed an adaptable cleft defect mask and volumetric Boolean operators for reliable voxel filling of the defected maxilla. A total of 36 clinically obtained CLP CBCTs were used to train and validate the proposed model, among which 22 CLP CBCTs were used to generate a training dataset with 440 synthetic CBCTs by B-spline deformation-based data augmentation and the remaining for testing. The proposed model was evaluated on maxilla completion and cleft defect volume prediction from clinically obtained unilateral and bilateral CLPCBCTs. Extensive experiments demonstrated the effectiveness of the adaptable cleft defect mask and the cascaded partial registration on maxilla completion and cleft defect volume prediction. The proposed method achieved state-of-the-art performances with the Dice similarity coefficient of 0.90 0.02 on the restored maxilla and 0.84 0.04 on the estimated cleft defect, respectively. The average Hausdorff distance between the estimated cleft defect and the manually annotated ground truth was 0.30 0.08 mm. The relative volume error of the cleft defect was 0.08. The proposed model allowed for the prediction of cleft defect maps that were in line with the ground truth in the challenging unilateral and bilateral CLP CBCTs. The results suggest that the proposed adaptable deep registration model enables patient-specific maxilla completion and automatic annotation of cleft defects, relieving tedious voxel-wise annotation and image acquisitionburdens.

Improving the registration stability of cone-beam computed tomography with the Sphere-Mask Optical Positioning System: a feasibility study.

Cone-beam computed tomography (CBCT) is an important tool for patient positioning in radiotherapy due to its outstanding advantages. However, the CBCT registration shows errors due to the limitations of the automatic registration algorithm and the nonuniqueness of manual verification results. The purpose of this study was to verify the feasibility of using the Sphere-Mask Optical Positioning System (S-M_OPS) to improve the registration stability of CBCT through clinical trials. From November 2021 to February 2022, 28 patients who received intensity-modulated radiotherapy and site verification with CBCT were included in this study. S-M_OPS was used as an independent third-party system to supervise the CBCT registration result in real time. The supervision error was calculated based on the CBCT registration result and using the S-M_OPS registration result as the standard. For the head and neck, patients with a supervision error ≥3 or ≤-3 mm in 1 direction were selected. For the thorax, abdomen, pelvis, or other body parts, patients with a supervision error ≥5 or ≤-5 mm in 1 direction were selected. Then, re-registration was performed for all patients (selected and unselected). The registration errors of CBCT and S-M_OPS were calculated based on the re-registration results as the standard. For selected patients with large supervision errors, CBCT registration errors (mean ± standard deviation) in the latitudinal (LAT; left/right), vertical (VRT; superior/inferior), and longitudinal (LNG; anterior/posterior) directions were 0.90±3.20, -1.70±0.98, and 7.30±2.14 mm, respectively. The S-M_OPS registration errors were 0.40±0.14, 0.32±0.66, and 0.24±1.12 mm in the LAT, VRT, and LNG directions, respectively. For all patients, CBCT registration errors in the LAT, VRT, and LNG directions were 0.39±2.69, -0.82±1.47, and 2.39±2.93 mm, respectively. The S-M_OPS registration errors were -0.25±1.33, 0.55±1.27, and 0.36±1.34 mm for all patients in the LAT, VRT, and LNG directions, respectively. This study shows that S-M_OPS registration offers comparable accuracy to CBCT for daily registration. S-M_OPS, as an independent third-party tool, can prevent large errors in CBCT registration, thereby improving the accuracy and stability of CBCT registration.

Adaptive Visual Saliency Feature Enhancement of CBCT for Image-Guided Radiotherapy

Unlike the high imaging radiation dose of computed tomography (CT), cone-beam CT (CBCT) has smaller radiation dose and presents less harm to patients. Therefore, CBCT is often used for target delineation, dose planning, and postoperative evaluation in the image-guided radiotherapy (IGRT) of various cancers. In the process of IGRT, CBCT images usually need to be collected multiple times in a radiotherapy stage for postoperative evaluation. The effectiveness of radiotherapy is measured by comparing and analyzing the registered CBCT and the source CT image obtained before radiotherapy. Hence, the registration of CBCT and CT is the most important step in IGRT. CBCT images usually have poor visual effects due to the small imaging dose used, which adversely affects the registration performance. In this paper, we propose a novel adaptive visual saliency feature enhancement method for CBCT in IGRT. Firstly, we denoised CBCT images using a structural similarity based low-rank approximation model (SSLRA) and then enhanced the denoised results with a visual saliency feature enhancement (VSFE)-based method. Experimental results show that the enhancement performance of the proposed method is superior to the comparison enhancement algorithms in visual objective comparison. In addition, the extended experiments prove that the proposed enhancement method can improve the registration accuracy of CBCT and CT images, demonstrating their application prospects in IGRT-based cancer treatment.

Comparative analysis of setup margin calculation in cone beam CT, by van Herk formula, using two different image registration methods

ABSTRACT Introduction: This study aimed to quantify the difference in setup margin in cone beam computed tomography (CBCT) setup imaging, utilising the van Herk formula for two different image registration methods. Two alternative techniques of registration, bony landmark (BL) matching and soft tissue matching (ST) for head and neck cancer patients, were investigated. Methods: This study included 30 head and neck cancer patients who received a simultaneous integrated boost of 54–60–66 Gy in 30 fractions, using volumetric modulated arc treatment. A total of 867 CBCT images were acquired during patient setup and further analysed for setup margin calculation. A region of interest was described using a clip box between the reference and CBCT image to calculate the patient’s positional inaccuracy in three translational directions, X, Y and Z, where X was mediolateral, Y was the cranial-caudal, and Z was the anterior-posterior direction in the patient-based coordinate system, respectively. The shifts were captured by altering the BL and ST matching, and the setup margin was calculated using the van Herk formula (=2·5Σ + 0·7σ where Σ was the systematic and σ was the random error). Results: The difference between bony and ST matching in most cases was observed to be 1·4 mm in all translational directions at a 95% confidence interval and &lt;1° in all rotational directions. The rotational error was found to be below the action level (±3°); hence, no corrections related to rotational error were made. The translational setup margin for bone and ST-based registration was X (BL) = 4·6 mm, X (ST) = 4·4 mm, Y (BL) = 6·3 mm, Y (ST) = 4·7 mm, Z (BL) = 3·0 mm, Z (ST) = 3·6mm. Conclusion: Two distinct registration approaches for head-neck patient setup did not yield any significant difference in the setup margin calculation. A suitable approach for CBCT and reference CT registration technique was required for the setup margin calculation. Confusion in selecting the correct image registration procedure can result in incorrect treatment execution. The compatibility of the two registration approaches was established in this study. Image fusion was neutralised before the second match (ST) to avoid hysteresis. For setup verification using CBCT for the head and neck region, both bone and ST registration were compatible for setup verification.

Validation of bowel and bladder preparation by rectum and bladder variation in prostate radiotherapy based on cone beam CTs

PurposeTo validate the effect of an individualized, patients-positive, Chinese-style diet bowel and bladder preparation protocol by analyzing bladder and rectum geometric and dosimetric variation in prostate radiotherapy. MethodsWe retrospectively evaluated 135 cone-beam computed tomography (CBCT) of 27 prostate patients. Organs at risk on CBCTs were re-contoured by the same radiotherapy doctor for consistency. The dose on CBCTs was recalculated with the forced mean electron density of organs in treatment isocenters to obtain the delivered dose. The volume and delivered dose on CBCTs were compared to planning dose. The relationship between delivered dose and translational shift to volume changes was analyzed. ResultsThe mean relative volume variations of the rectum and bladder were 112.12 ± 29.46% and 89.90 ± 24.77%, respectively. With the registration of CBCTs to planning CT by target matching, the translational shifts ≤3 mm, ≤4 mm and ≤5 mm were approximately 52%, 80% and 92% of 135 CBCTs, respectively. The normalized rectal volume was linearly related to the left-right shift (P = 0.0087, R = 0.0183), and the normalized bladder volume was linearly related to the superior-inferior shift (P = 0.0058, R = 0.0202).Remarkable bladder volume reduction was observed during the radiotherapy course. Dmean, Dmax, V30Gy, V40Gy, V50Gy, V55Gy, V60Gy and V65Gy of the rectum on cumulative or single CBCT were higher than planned (P < 0.05) and mostly met clinical constraints. V30Gy and V40Gy of the bladder on CBCTs were lower than planned (P < 0.05).There was a linear regression relationship between the normalized rectum volume and Dmin, Dmax and V50Gy. Negative regression relationship was found between the normalized bladder volume and Dmin, Dmean, V30Gy, V40Gy, V50Gy, V55Gy, V60Gy and V65Gy. ConclusionsThe delivered dose of the rectum met the planning constraints. Additionally, the delivered dose to the bladder was lower than planned dose. The results demonstrate the validity of the bowel and bladder preparation.

Machine log file-based dose verification using novel iterative CBCT reconstruction algorithm in commercial software during volumetric modulated arc therapy for prostate cancer patients.

To evaluate the utility of the use of iterative cone-beam computed tomography (CBCT) for machine log file-based dose verification during volumetric modulated arc therapy (VMAT) for prostate cancer patients. All CBCT acquisition data were used to reconstruct images with the Feldkamp-Davis-Kress algorithm (FDK-CBCT) and the novel iterative algorithm (iCBCT). The Hounsfield unit (HU)-electron density curves for CBCT images were created using the Advanced Electron Density Phantom. The I'mRT and anthropomorphic phantoms were irradiated with VMAT after CBCT registration. Subsequently, fourteen prostate cancer patients received VMAT after CBCT registration. Machine log files and both CBCT images were exported to the PerFRACTION software, and a 3D patient dose was reconstructed. Mean dose for planning target volume (PTV), the bladder, and rectum and the 3D gamma analysis were evaluated. For the phantom studies, the variation of HU values was observed at the central position surrounding the bones in FDK-CBCT. There were almost no changes in the difference of doses at the isocenter between measurement and reconstructed dose for planning CT (pCT), FDK-CBCT, and iCBCT. Mean dose differences of PTV, rectum, and bladder between iCBCT and pCT were approximately 2% lower than those between FDK-CBCT and pCT. For the clinical study, average gamma analysis for 2%/2 mm was 98.22% ± 1.07 and 98.81% ± 1.25% in FDK-CBCT and iCBCT, respectively. A similar machine log file-based dose verification accuracy is obtained for FDK-CBCT and iCBCT during VMAT for prostate cancer patients.

Magnetic Resonance Imaging and Cone Beam CT Image Registration for Osseous and Soft Tissue Abnormalities of Temporomandibular Joint: A Systematic Review

Abstract Introduction Proper diagnosis of temporomandibular disorders (TMDs) is paramount for proper management. Cone beam computed tomography (CBCT) provides additional information about osseous components of TMJ, but diagnosis of soft tissue abnormalities is still a challenging issue for the clinicians. To overcome this, magnetic resonance imaging (MRI) and CBCT registration has shown to be a new promising technique that combines key features of both images into one single fusion image. The purpose of this systematic review was to compile available literature regarding the usefulness of CBCT and MRI-CBCT fusion imaging in proper diagnosis of temporomandibular joint (TMJ) abnormalities. Materials and Methods Computerized literature search from January 2010 to 2020 using five databases: PubMed (MEDLINE) database (National Library of Medicine, NCBI), Cochrane Database, Scopus, Embase, and Science Direct was conducted by use of medical specific headings (MeSH) keywords. Results Only 10 articles met the inclusion criteria. Eight articles showed that CBCT accurately detected osseous components of TMJ but has low reliability in diagnosing soft tissue articular disc disorders. Relationship between hard and soft tissues were clearly visualized in fused images. Conclusion MRI-CBCT image registration is a reliable diagnostic tool for simultaneous evaluation of osseous and soft tissue abnormalities of TMJ and in future more studies should be encouraged to validate its accuracy for TMJ analysis.

Patch-based field-of-view matching in multi-modal images for electroporation-based ablations

Various multi-modal imaging sensors are currently involved at different steps of an interventional therapeutic work-flow. Cone beam computed tomography (CBCT), computed tomography (CT) or Magnetic Resonance (MR) images thereby provides complementary functional and/or structural information of the targeted region and organs at risk. Merging this information relies on a correct spatial alignment of the observed anatomy between the acquired images. This can be achieved by the means of multi-modal deformable image registration (DIR), demonstrated to be capable of estimating dense and elastic deformations between images acquired by multiple imaging devices. However, due to the typically different field-of-view (FOV) sampled across the various imaging modalities, such algorithms may severely fail in finding a satisfactory solution.In the current study we propose a new fast method to align the FOV in multi-modal 3D medical images. To this end, a patch-based approach is introduced and combined with a state-of-the-art multi-modal image similarity metric in order to cope with multi-modal medical images. The occurrence of estimated patch shifts is computed for each spatial direction and the shift value with maximum occurrence is selected and used to adjust the image field-of-view. The performance of the proposed method – in terms of both registration accuracy and computational needs – is analyzed in the practical case of on-line irreversible electroporation procedures. In total, 30 pairs of pre-/per-operative IRE images are considered to illustrate the efficiency of our algorithm.We show that a regional registration approach using voxel patches provides a good structural compromise between the voxel-wise and “global shifts” approaches. The method was thereby beneficial for CT to CBCT and MRI to CBCT registration tasks, especially when highly different image FOVs are involved. Besides, the benefit of the method for CT to CBCT and MRI to CBCT image registration is analyzed, including the impact of artifacts generated by percutaneous needle insertions. Additionally, the computational needs using commodity hardware are demonstrated to be compatible with clinical constraints in the practical case of on-line procedures. The proposed patch-based workflow thus represents an attractive asset for DIR at different stages of an interventional procedure.

Frameless Stereotactic Radiosurgery on the Gamma Knife Icon: Early Experience From 100 Patients.

The Gamma Knife (GK) Icon (Elekta AB) uses a cone-beam computed tomography (CBCT) scanner and an infrared camera system to support the delivery of frameless stereotactic radiosurgery (SRS). There are limited data on patients treated with frameless GK radiosurgery (GKRS). To describe the early experience, process, technical details, and short-term outcomes with frameless GKRS at our institution. We reviewed our patient selection and described the workflow in detail, including image acquisition, treatment planning, mask-based immobilization, stereotactic CBCT localization, registration, treatment, and intrafraction monitoring. Because of the short interval of follow-up, we provide crude rates of local control. Data from 100 patients are reported. Median age is 67 yr old. 56 patients were treated definitively, 21 postoperatively, and 23 had salvage GKRS for recurrence after surgery. Forty-two patients had brain metastases, 26 meningiomas, 16 vestibular schwannomas, 9 high-grade gliomas, and 7 other histologies. Median doses to metastases were 20 Gy in 1 fraction (range: 14-21), 24 Gy in 3 fractions (range: 19.5-27), and 25 Gy in 5 fractions (range: 25-30 Gy). Thirteen patients underwent repeat SRS to the same area. Median treatment time was 17.7 min (range: 5.8-61.7). We found an improvement in our workflow and a greater number of patients eligible for GKRS because of the ability to fractionate treatments. We report a large cohort of consecutive patients treated with frameless GKRS. We look forward to studies with longer follow-up to provide valuable data on clinical outcomes and to further our understanding of the radiobiology of hypofractionation in the brain.

Gamma Knife® icon CBCT offers improved localization workflow for frame-based treatment.

ObjectThe purpose of this study was to compare two methods of stereotactic localization in Gamma Knife treatment planning: cone beam computed tomography (CBCT) or fiducial. While the fiducial method is the traditional method of localization, CBCT is now available for use with the Gamma Knife Icon. This study seeks to determine whether a difference exists between the two methods and then whether one is better than the other regarding accuracy and workflow optimization.MethodsCone beam computed tomography was used to define stereotactic space around the Elekta Film Pinprick phantom and then treated with film in place. The same phantom was offset known amounts from center and then imaged with CBCT and registered with the reference CBCT image to determine if measured offsets matched those known. Ten frameless and 10 frame‐based magnetic resonance imaging (MRI) to CBCT patient fusions were retrospectively evaluated using the TG‐132 TRE method. The stereotactic coordinates defined by CBCT and traditional fiducials were compared on the Elekta 8 cm Ball phantom, an anthropomorphic phantom, and actual patient data. Offsets were introduced to the anthropomorphic phantom in the stereotactic frame and CBCT's ability to detect those offsets was determined.ResultsCone beam computed tomography defines stereotactic space well within the established limits of the mechanical alignment system. The CBCT to CBCT registration can detect offsets accurately to within 0.1 mm and 0.5°. In all cases, some disagreement existed between fiducial localization and that of CBCT which in some cases was small, but also was as high as 0.43 mm in the phantom domain and as much as 1.54 mm in actual patients.ConclusionCone beam computed tomography demonstrates consistent accuracy in defining stereotactic space. Since both localization methods do not agree with each other consistently, the more reliable method must be identified. Cone beam computed tomography can accurately determine offsets occurring within stereotactic space that would be nondiscernible utilizing the fiducial method and seems to be more reliable. Using CBCT localization offers the opportunity to streamline workflow both from a patient and clinic perspective and also shows patient position immediately prior to treatment.

Active contouring and 3D model deformable registration of radiotherapy planning and cone-beam computed tomography images

Background: To ensure high accuracy during radiation therapy (RT), the image-guided RT (IGRT) technique uses on-board cone-beam computed tomography (CBCT) scanning as an image guidance procedure for target localization before and during treatment. Adaptive RT aiming to modify RT target volumes according to kinetic changes in tumor shape during RT course is based on registration of CBCT and planning CT images. However, the re-contouring and re-planning procedures are extensively time and cost consuming. We developed a novel automatic contouring and image registration method to replace the manual re-contouring with accurate image registration. Methods: For the image sets with format of Digital Imaging and Communications in Medicine (DICOM) standard, we wrote a program in MATLAB language (Version R2016a) to read and convert CBCT images into cross-sectional (tomographic) images similar to those obtained via planning CT. For image enhancement, the active contouring by using Chan-Vese model with level set formulation was applied. To overcome the variations in spatial location of these two sets of CT images, the iterative closest point (ICP) algorithm was used for 3D model registration. The deformable image registration (DIR) with Double force Demons algorithm was performed for auto-transformation of contours from planning CT to CBCT images. Results: The customized program accurately converted the format of CBCT to planning CT. Image enhancement was achieved by our modified active contour model which solved the energy minimization problem. In 3D model registration, the variations in spatial location of the CBCT and planning CT images were corrected. After selection of most similar images, the planning CT images were registered to corresponding CBCT images. The registered images were clearer than CBCT images with removal of other confounding structures outside body contours. Conclusions: The planning CT and CBCT images could be precisely registered by using a novel established technique consisting of active contouring with 3D model and DIR. This technique would enable the on-line radiation treatment planning for adaptive radiotherapy.

Feasibility study of intraoperative cone‐beam CT navigation for benign bone tumour surgery

BackgroundIntraoperative cone‐beam computed tomography (CBCT) offers the advantage of navigation on the current anatomical situation and the possibility to take a control scan. We assessed the feasibility of using intraoperative CBCT for navigated intralesional curettage.MethodsNine benign bone tumour patients were studied. Feasibility was assessed by describing the workflow and indications for navigation, scoring CBCT image quality and registration accuracy, and measuring scan and navigation set‐up times. Short‐term follow‐up was described.ResultsCBCT navigation was successful in all patients. Median tumour visibility, tumour delineation, and vital structure visibility scores were good. Median registration accuracy score was very good. Median scan and verification times were 5 and 3 minutes, respectively. One patient had a tumour recurrence after 6 months.ConclusionsIntraoperative CBCT navigation is feasible and safe. Indications for use of navigation in clinical practice are closeness to vital structures, complexly shaped tumours or bone, minimally invasive surgery, and repeated surgery.

Accuracy and reliability of mandibular digital model registration with use of the mucogingival junction as the reference

The aim of the study was to validate a method of mandibular digital model (DM) registration, acquired from an intraoral scanner, compared with high-resolution voxel-based cone beam computed tomography (CBCT) registration with use of the mucogingival junction as the reference. Pre- and post-treatment CBCT and DM images from 12 adults were randomly selected from an initial sample of 40 patients who had undergone orthodontic treatment. The DM registration was performed in 6 steps: (1) construction of 3-dimensional (3-D) volumetric label maps of CBCT scans, (2) voxel-based registration of CBCT scans, (3) prelabeling of CBCT images, (4) approximation and registration of DM models to the corresponding CBCT models, (5) mucogingival-junction registration of pretreatment and post-treatment DM images, and (6) measurements. The Mann-Whitney U test was used to calculate the significance of differences between the CBCT and DM registrations. The intraclass correlation coefficient (ICC) was performed to assess reproducibility of the registration method. When registered CBCT models and registered DM models were compared, no statistically significant differences in the measurements were found (right-left P = .267; anterior-posterior P = .238; superior-inferior P = .384; and 3-D P = .076). ICC showed excellent intra- and inter-rater correlation (ICC > 0.90). The method of DM registration of the mandible with use of the mucogingival junction as the reference is accurate, reliable, and reproducible.

Analysis of which local set-up errors can be covered by a 5-mm margin for cone beam CT-guided radiotherapy for nasopharyngeal carcinoma

Objective:To analyse which local set-up errors can be covered by a 5-mm margin for cone beam computed tomography (CBCT)-guided radiotherapy in nasopharyngeal carcinoma (NPC).Methods:11 regions of interest (ROIs) were registered for 24 NPC patients, with a total of 323 CBCT scans. According to the registration results, clinical target volume–planning target volume (CTV–PTV)/organs at risk-planning risk volume (OAR-PRV) margin analysis; Pearson correlation analysis; Bland–Altman plots; and a receiver operating characteristic (ROC) analysis were used to investigate which local set-up errors of substructure can be represented by the PTVROI.Results:The clinical target volume-PTV/OAR-planning risk volume margins were less than 5 mm for C1ROI-C4ROI, mandible (MROI), and sphenoid sinus (SROI) with respect to PTVROI. C1ROI-C4ROI, MROI, and SROI exhibited significant correlations and consistencies in the mediolateral, superior–inferior, and anteroposterior (AP) directions and significant receiver operating characteristic analysis results in the anteroposterior direction.Conclusion:Only the upper local set-up error of C1ROI-C4ROI, MROI, and SROI can be covered by a 5-mm margin for CBCT-guided NPC radiotherapy with a large ROI. Using these ROIs as an integral reference ROI is better than individual bony landmark.Advances in knowledge:This report is helpful to CBCT registration for NPC radiotherapy in clinical practice.

Leveraging Advanced Practice: Building Capacity and Maximizing Impact

The Stereotactic Body Radiation Therapy (SBRT) program at our institution has rapidly grown in both anatomic sites and patient numbers since 2008; treating over 700 patients last year to sites including lung, liver, spine, prostate, kidney, pancreas, head and neck , bone and nodes. With such a rapidly expanding program, a clinical specialist radiation therapist (CSRT) position was created in 2012 to ensure optimal, consistent care across the program. Since inception, the role has demonstrated significant impact in terms of time savings for physicians and improved quality of care for patients. The next logical step was to translate the expertise of the CSRT into programmatic efficiencies. An initial area of focus for the position was to have the CSRT assume responsibility of approval of day 1 cone beam computed tomography (CBCT) registrations in place of the radiation oncologist (RO). The CSRT attained competence through a combination of didactic and practical instruction. Concordance between the CSRT and RO with respect to CBCT registration assessment was established. As the department's experience in certain sites of SBRT matured, specific clinical scenarios were identified where, with appropriate training, treatment therapists could independently review day 1 CBCT images for SBRT treatments. The CSRT implemented a therapist led day 1 CBCT registration review policy and facilitated staff education through creation and delivery of an instructional module. A follow up audit was performed to ensure maintenance of quality standards and to quantify departmental impact. Benefits: Greater autonomy for radiation therapists; Eliminated need for calling a third party for treatment and resultant delays; Freed up CSRT to focus on more complex tasks. Challenges: Maintaining continued clinical competence throughout department; Consistent adherence to new guidelines; Managing challenging cases within sites identified for therapist review. The progression of the CSRT in SBRT role highlights how advanced practice radiation therapy roles should evolve continuously. To maximize impact, it is necessary to be cognizant of the changing needs of the department and to align the role accordingly. This process demonstrated how advanced knowledge, skills and judgment of CSRTs can be leveraged for wider departmental benefit.

Non-rigid CT/CBCT to CBCT registration for online external beam radiotherapy guidance

Image-guided external beam radiotherapy (EBRT) allows radiation dose deposition with a high degree of accuracy and precision. Guidance is usually achieved by estimating the displacements, via image registration, between cone beam computed tomography (CBCT) and computed tomography (CT) images acquired at different stages of the therapy. The resulting displacements are then used to reposition the patient such that the location of the tumor at the time of treatment matches its position during planning. Moreover, ongoing research aims to use CBCT–CT image registration for online plan adaptation.However, CBCT images are usually acquired using a small number of x-ray projections and/or low beam intensities. This often leads to the images being subject to low contrast, low signal-to-noise ratio and artifacts, which ends-up hampering the image registration process. Previous studies addressed this by integrating additional image processing steps into the registration procedure. However, these steps are usually designed for particular image acquisition schemes, therefore limiting their use on a case-by-case basis.In the current study we address CT to CBCT and CBCT to CBCT registration by the means of the recently proposed EVolution registration algorithm. Contrary to previous approaches, EVolution does not require the integration of additional image processing steps in the registration scheme. Moreover, the algorithm requires a low number of input parameters, is easily parallelizable and provides an elastic deformation on a point-by-point basis. Results have shown that relative to a pure CT-based registration, the intrinsic artifacts present in typical CBCT images only have a sub-millimeter impact on the accuracy and precision of the estimated deformation. In addition, the algorithm has low computational requirements, which are compatible with online image-based guidance of EBRT treatments.

Dual Registration for Optimal Cone Beam Computed Tomography Registration for Locally Advanced Cervix Carcinoma

Dual Registration for Optimal Cone Beam Computed Tomography Registration for Locally Advanced Cervix Carcinoma