A phantom study on the evaluation of the YOLOv8 deep learning model in the detection of tooth ankylosis on cone-beam computed tomography images

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Three-dimensional C-arm Cone-beam CT: Applications in the Interventional Suite

To investigate the accuracy and reliability of cone beam computed tomography (CBCT) measurements of buccal alveolar bone height (BBH) and thickness (BBT) using custom acquisition settings. School of Dentistry, Oregon Health & Science University. Twelve embalmed cadavers. Cadaver heads were imaged by CBCT (i-CAT® 17-19, Imaging Sciences International, Hatfield, PA) using a 'long scan' (LS) setting with 619 projection images, 360° revolution, 26.9 s duration, and 0.2 mm voxel size, and using a 'short scan' (SS) setting with 169 projection images, 180° rotation, 4.8 s duration, and 0.3 mm voxel size. BBH and BBT were measured with 65 teeth, indirectly from CBCT images and directly through dissection. Comparisons were assessed using paired t-tests (p≤0.05). Level of agreement was assessed by concordance correlation coefficients, Pearson's correlation coefficients, and Bland-Altman plots. Mean differences in measurements compared to direct measurements were as follows, LS 0.17±0.12 (BBH) and 0.10±0.07 mm (BBT), and SS 0.41±0.32 (BBH) and 0.12±0.11 mm (BBT). No statistical differences were found with any of BBH or BBT measurements. Correlation coefficients and Bland-Altman plots showed agreement was high between direct and indirect measurement methods, although agreement was stronger for measurements of BBH than BBT. Compared to the LS, the similarity in results with the reduced scan times and hence reduced effective radiation dose, favors use of shorter scans, unless other purposes for higher resolution imaging can be defined.

Purpose: Cone Beam CT (CBCT) kilovoltage imaging devices are increasingly available for daily imaging in radiotherapy departments. Flat‐panel based CBCT scanners present a distinctive set of artifacts due mostly to increased scatter, longer data acquisition time and reduced detector quantum efficiency as compared to helical Fan Beam CT (FBCT) systems. Our purpose is to characterize image quality from FBCT and CBCT scanners based on noise, contrast and dose, using FBCT as a benchmark. Method and Materials: we acquired phantom and clinical patient images with a CBCT Varian On‐Board Imager as well as with a FBCT Picker PQ5000 single‐row helical scanner. The CBCT scanner was equipped with antiscatter grid and bowtie filter. By comparing CBCT and FBCT images of a high contrast resolution insert, the CBCT reconstruction voxel size and filter were adjusted until the spatial resolution of the FBCT and CBCT images was approximately matched. Dose was measured with standard CTDI and Farmer chambers. Noise, contrast and SNR were evaluated and compared. Results: CBCT images of both phantom and patient were relatively free of streaking and cupping artifacts, indicating that the grid had successfully attenuated most of the scatter. Low contrast detectability threshold is similar for the two modalities, when CBCT dose is about twice as large as FBCT. Noise and non‐uniformities are more prevalent in patient CBCT images, but pelvic soft tissue structures are well discernible. For patient and phantom images Dose×SNR2 is about 4 times lower for FBCT than in CBCT, which is about 1.5–2 times larger than expected, given the measured grid transmission and detector quantum efficiency. Conclusion: In this study, resolution‐matched CBCT and FBCT images could exhibit similar SNRs and contrast‐to‐noise ratios through a combination of increased imaging dose and reduced spatial resolution.

Evaluation of marginal fit of CAD/CAM restorations fabricated through cone beam computerized tomography and laboratory scanner data

To develop an automated deep-learning algorithm for detection and 3D segmentation of incidental bone lesions in maxillofacial CBCT scans. The dataset included 82 cone beam CT (CBCT) scans, 41 with histologically confirmed benign bone lesions (BL) and 41 control scans (without lesions), obtained using three CBCT devices with diverse imaging protocols. Lesions were marked in all axial slices by experienced maxillofacial radiologists. All cases were divided into sub-datasets: training (20,214 axial images), validation (4530 axial images), and testing (6795 axial images). A Mask-RCNN algorithm segmented the bone lesions in each axial slice. Analysis of sequential slices was used for improving the Mask-RCNN performance and classifying each CBCT scan as containing bone lesions or not. Finally, the algorithm generated 3D segmentations of the lesions and calculated their volumes. The algorithm correctly classified all CBCT cases as containing bone lesions or not, with an accuracy of 100%. The algorithm detected the bone lesion in axial images with high sensitivity (95.9%) and high precision (98.9%) with an average dice coefficient of 83.5%. The developed algorithm detected and segmented bone lesions in CBCT scans with high accuracy and may serve as a computerized tool for detecting incidental bone lesions in CBCT imaging. Our novel deep-learning algorithm detects incidental hypodense bone lesions in cone beam CT scans, using various imaging devices and protocols. This algorithm may reduce patients' morbidity and mortality, particularly since currently, cone beam CT interpretation is not always preformed. • A deep learning algorithm was developed for automatic detection and 3D segmentation of various maxillofacial bone lesions in CBCT scans, irrespective of the CBCT device or the scanning protocol. • The developed algorithm can detect incidental jaw lesions with high accuracy, generates a 3D segmentation of the lesion, and calculates the lesion volume.

BackgroundThe emergence of robotic Cone Beam Computed Tomography (CBCT) imaging systems in trauma departments has enabled 3D anatomical assessment of musculoskeletal injuries, supplementing conventional 2D fluoroscopic imaging for examination, diagnosis, and treatment planning. To date, the primary focus has been on trauma sites in the extremities.PurposeTo determine if CBCT images can be used during the treatment planning process in spinal instrumentation and laminectomy procedures, allowing accurate 3D‐printed pedicle screw and laminectomy drill guides to be generated for the cervical and thoracic spine.MethodsThe accuracy of drill guides generated from CBCT images was assessed using animal cadavers (ovine and porcine). Preoperative scans were acquired using a robotic CBCT C‐arm system, the Siemens ARTIS pheno (Siemens Healthcare, GmbH, Germany). The CBCT images were imported into 3D‐Slicer version 4.10.2 (www.slicer.org) where vertebral models and specific guides were developed and subsequently 3D‐printed. In the ovine cadaver, 11 pedicle screw guides from the T1–T5 and T7–T12 vertebra and six laminectomy guides from the C2–C7 vertebra were planned and printed. In the porcine cadaver, nine pedicle screw guides from the C3–T4 vertebra were planned and printed. For the pedicle screw guides, accuracy was assessed by three observers according to pedicle breach via the Gertzbein–Robbins grading system as well as measured mean axial and sagittal screw error via postoperative CBCT and CT scans. For the laminectomies, the guides were designed to leave 1 mm of lamina. The average thickness of the lamina at the mid‐point was used to assess the accuracy of the guides, measured via postoperative CBCT and CT scans from three observers. For all measurements, the intraclass correlation coefficient (ICC) was calculated to determine observer reliability.ResultsCompared with the planned screw angles for both the ovine and porcine procedures (n = 32), the mean axial and sagittal screw error measured on the postoperative CBCT scans from three observers were 3.9 ± 1.9° and 1.8 ± 0.8°, respectively. The ICC among the observes was 0.855 and 0.849 for the axial and sagittal measurements, respectively, indicating good reliability. In the ovine cadaver, directly comparing the measured axial and sagittal screw angle of the visible screws (n = 14) in the postoperative CBCT and conventional CT scans from three observers revealed an average difference 1.9 ± 1.0° in axial angle and 1.8 ± 1.0° in the sagittal angle. The average thickness of the lamina at the middle of each vertebra, as measured on‐screen in the postoperative CBCT scans by three observes was 1.6 ± 0.2 mm. The ICC among observers was 0.693, indicating moderate reliability. No lamina breaches were observed in the postoperative images.ConclusionHere, CBCT images have been used to generate accurate 3D‐printed pedicle screw and laminectomy drill guides for use in the cervical and thoracic spine. The results demonstrate sufficient precision compared with those previously reported, generated from standard preoperative CT and MRI scans, potentially expanding the treatment planning capabilities of robotic CBCT imaging systems in trauma departments and operating rooms.

Working with DICOM craniofacial images

Computed gray levels in multislice and cone-beam computed tomography

Quantification of external root resorption by low- vs high-resolution cone-beam computed tomography and periapical radiography: A volumetric and linear analysis

Purpose: To evaluate the intrafractional motion errors in patient with prostate cancer received pelvis irradiation during RapidArc radiotherapy.Materials and Methods: A total of eighteen high risk group prostate cancer patients were treated prostate and pelvis lymph nodes by RapidArc radiotherapy then boost dose by Cyberknife. All patients had kV cone beam computerized tomography (CBCT) scans in their first three fractions of treatment. During these treatments, the CBCT scans were registered to planning CT simulation images as reference to perform registration procedure based on soft tissue windows matched with clinical tumor volume (CTV). The errors of isocenter position were corrected by couch shifted. The second and third CBCT images were immediately acquired before and after RapidArc treatment. These errors of isocenter position on the left-right (LR), superior–inferior (SI) and anterior–posterior (AP) directions were analyzed retrospectively.Results: Under RapidArc technique with a shortened treatment delivery time (about 3 min), the residual systemic and random errors in pre and post-radiation treatment revealed limited. Based on the paired 2^(nd) and 3^(rd) CBCT images, the intrafractional errors (mean ± SD) in LR-SI-AP directions were -0.4 ± 0.8, -0.2 ± 1.0, 0.1 ± 0.8 mm. No intrafractional error differences in three axes, except borderline significant in LR direction (p= 0.046). Isotropic planning margins created with the linear addition of internal margin to clinical tumor volume was respectively 3.6, 4.4, 4.5 mm in LR-SI-AP axes and 2.5, 3.2, 3.3 mm if generated with quadrature addition.Conclusion: Use of the faster RapidArc technique with accurate kV CBCT images online verification for prostate cancer pelvis radiotherapy, the intrafractional motion errors were limited. These speculated intrafractional errors could be applied to improve the accuracy of radiation delivery and a smaller PTV margin might be adopted.

On-board CBCT images are used to generate patient geometric models to assist patient setup. The image data can also, potentially, be used for dose reconstruction in combination with the fluence maps from treatment plan. Here we evaluate the achievable accuracy in using a kV CBCT for dose calculation. Relative electron density as a function of HU was obtained for both planning CT (pCT) and CBCT using a Catphan-600 calibration phantom. The CBCT calibration stability was monitored weekly for 8 consecutive weeks. A clinical treatment planning system was employed for pCT- and CBCT-based dose calculations and subsequent comparisons. Phantom and patient studies were carried out. In the former study, both Catphan-600 and pelvic phantoms were employed to evaluate the dosimetric performance of the full-fan and half-fan scanning modes. To evaluate the dosimetric influence of motion artefacts commonly seen in CBCT images, the Catphan-600 phantom was scanned with and without cyclic motion using the pCT and CBCT scanners. The doses computed based on the four sets of CT images (pCT and CBCT with/without motion) were compared quantitatively. The patient studies included a lung case and three prostate cases. The lung case was employed to further assess the adverse effect of intra-scan organ motion. Unlike the phantom study, the pCT of a patient is generally acquired at the time of simulation and the anatomy may be different from that of CBCT acquired at the time of treatment delivery because of organ deformation. To tackle the problem, we introduced a set of modified CBCT images (mCBCT) for each patient, which possesses the geometric information of the CBCT but the electronic density distribution mapped from the pCT with the help of a BSpline deformable image registration software. In the patient study, the dose computed with the mCBCT was used as a surrogate of the ‘ground truth’. We found that the CBCT electron density calibration curve differs moderately from that of pCT. No significant fluctuation was observed in the calibration over the period of 8 weeks. For the static phantom, the doses computed based on pCT and CBCT agreed to within 1%. A notable difference in CBCT- and pCT-based dose distributions was found for the motion phantom due to the motion artefacts which appeared in the CBCT images (the maximum discrepancy was found to be ∼3.0% in the high dose region). The motion artefacts-induced dosimetric inaccuracy was also observed in the lung patient study. For the prostate cases, the mCBCT- and CBCT-based dose calculations yielded very close results (<2%). Coupled with the phantom data, it is concluded that the CBCT can be employed directly for dose calculation for a disease site such as the prostate, where there is little motion artefact. In the prostate case study, we also noted a large discrepancy between the original treatment plan and the CBCT (or mCBCT)-based calculation, suggesting the importance of inter-fractional organ movement and the need for adaptive therapy to compensate for the anatomical changes in the future.

The added value of a new high-performance ring-gantry CBCT imaging system for prostate cancer patients

The present study is based on evidence indicating a potential correlation between cone-beam CT (CBCT) measurements of tumor size, shape, and the stage of locally advanced rectal cancer. To further investigate this relationship, the study quantitatively assesses the correlation between positioning CT (pCT) and CBCT in the radiomics features of these cancers, and examines their potential for substitution. In this study, 103 patients diagnosed with locally advanced rectal cancer and undergoing neoadjuvant chemoradiotherapy were selected as participants. Their CBCT and pCT images were used to divide the participants into two groups: a training set and a validation set, with a 7:3 ratio. An improved conventional 3D-RUNet (CLA-UNet) deep learning model was trained on the training set data and then applied to the validation set. The DSC, HD95 and ASSD were calculated for quantitative evaluation purposes. Then, radiomics features were extracted from 30 patients of the test set. The experiments demonstrate that, the modified model achieves an average DSC score 0.792 for pCT and 0.672 for CBCT scans. 1037 features were extracted from each patient's CBCT and pCT images, 73 image features were found to have R values greater than 0.9, including three features related to the staging and prognosis of rectal cancer. In this study, we proposed an automatic, fast, and consistent method for rectal cancer GTV segmentation for pCT and CBCT scans. The findings of radiomic results indicate that CBCT images have significant research value in the field of radiomics.

Cone Beam Computed Tomography Assessment of Cervical Spine Bone Density