Artefacts in CBCT: a review

Feasibility of proton dosimetry overriding planning CT with daily CBCT elaborated through generative artificial intelligence tools

Radiotherapy commonly utilizes cone beam computed tomography (CBCT) for patient positioning and treatment monitoring. CBCT is deemed to be secure for patients, making it suitable for the delivery of fractional doses. However, limitations such as a narrow field of view, beam hardening, scattered radiation artifacts, and variability in pixel intensity hinder the direct use of raw CBCT for dose recalculation during treatment. To address this issue, reliable correction techniques are necessary to remove artifacts and remap pixel intensity into Hounsfield Units (HU) values. This study proposes a deep-learning framework for calibrating CBCT images acquired with narrow field of view (FOV) systems and demonstrates its potential use in proton treatment planning updates. Cycle-consistent generative adversarial networks (cGAN) processes raw CBCT to reduce scatter and remap HU. Monte Carlo simulation is used to generate CBCT scans, enabling the possibility to focus solely on the algorithm's ability to reduce artifacts and cupping effects without considering intra-patient longitudinal variability and producing a fair comparison between planning CT (pCT) and calibrated CBCT dosimetry. To showcase the viability of the approach using real-world data, experiments were also conducted using real CBCT. Tests were performed on a publicly available dataset of 40 patients who received ablative radiation therapy for pancreatic cancer. The simulated CBCT calibration led to a difference in proton dosimetry of less than 2%, compared to the planning CT. The potential toxicity effect on the organs at risk decreased from about 50% (uncalibrated) up the 2% (calibrated). The gamma pass rate at 3%/2 mm produced an improvement of about 37% in replicating the prescribed dose before and after calibration (53.78% vs 90.26%). Real data also confirmed this with slightly inferior performances for the same criteria (65.36% vs 87.20%). These results may confirm that generative artificial intelligence brings the use of narrow FOV CBCT scans incrementally closer to clinical translation in proton therapy planning updates.

Comparison of 96-kV and 120-kV cone-beam CT for the assessment of cochlear implants

BACKGROUND

To compare the diagnostic value of 120-kV with conventional 96-kV Cone-Beam CT (CBCT) of the temporal bone after cochlear implant (CI) surgery.

METHODS

This retrospective study included CBCT scans after CI surgery between 06/17 and 01/18. CBCT allowed examinations with 96-kV or 120-kV; other parameters were the same. Two radiologists independently evaluated following criteria on 5-point Likert scales: osseous spiral lamina, inner and outer cochlear wall, semi-circular canals, mastoid trabecular structure, overall image quality, metal and motion artefacts, depiction of intracochlear electrode position and visualisation of single electrode contacts. Effective radiation dose was assessed.

RESULTS

Seventy-five patients (females, n = 39 [52.0%], mean age, 55.8 ± 16.5 years) were scanned with 96-kV (n = 32, 42.7%) and 120-kV (n = 43, 57.3%) protocols including CI models from three vendors (vendor A n = 7; vendor B n = 43; vendor C n = 25). Overall image quality, depiction of anatomical structures, and electrode position were rated significantly better in 120-kV images compared to 96-kV (all p < = 0.018). Anatomical structures and electrode position were rated significantly better in 120-kV CBCT for CI models from vendor A and C, while 120-kV did not provide improved image quality in CI models from vendor B. Radiation doses were significantly higher for 120-kV scans compared to 96-kV (0.15 vs. 0.08 mSv, p < 0.001).

CONCLUSIONS

120-kV and 96-kV CBCT provide good diagnostic images for the postoperative CI evaluation. While 120-kV showed improved depiction of temporal bone and CI electrode position compared to 96-kV in most CI models, the 120-kV protocol should be chosen wisely due to a substantially higher radiation exposure.

Influence of tube current and metal artifact reduction on the diagnosis of external cervical resorption in teeth adjacent to a dental implant in CBCT: an ex-vivo study

OBJECTIVES

This ex-vivo study aimed to assess the influence of tube current (mA) and metal artifact reduction (MAR) on the diagnosis of early external cervical resorption (EECR) in cone-beam computed tomography (CBCT) in the presence of an adjacent dental implant.

MATERIALS AND METHODS

Twenty-three single-rooted teeth were sectioned longitudinally and EECR was induced using a spherical drill and 5% nitric acid in 10 teeth. Each tooth was positioned in the socket of the lower right canine of a dry human mandible and CBCT scans were acquired using 90 kVp, voxel of 0.085 mm, field of view of 5 x 5 cm, and varying tube current (4, 8 or 12 mA), MAR (enabled or disabled) and implant conditions (with a zirconia implant in the socket of the lower right first premolar or without). Five oral radiologists evaluated the presence of EECR in a 5-point scale and the diagnostic values (area under the receiver operating characteristic curve - AUC, sensitivity, and specificity) were compared using multi-way Analysis of Variance (α = 0.05). Kappa test assessed intra-/inter-evaluator agreement.

RESULTS

The tube current only influenced the AUC values in the presence of the implant and when MAR disabled; in this case, 8 mA showed lower values (p<0.007). MAR did not influence the diagnostic values (p>0.05). In general, the presence of an implant reduced the AUC values (p<0.0001); sensitivity values with 8 mA and MAR disabled, and specificity values with 4 mA and MAR enabled and 8 mA regardless MAR were also decreased (p<0.0001).

CONCLUSIONS

Variations in tube current and MAR were unable to improve EECR detection, which was impaired by the presence of an adjacent implant.

CLINICAL RELEVANCE

Increasing tube current or activating MAR tool does not improve EECR diagnosis, which is hampered by the artifacts generated by dental implants.

Radiographic diagnosis of periodontal diseases - Current evidence versus innovations

Accurate diagnosis of periodontal and peri-implant diseases relies significantly on radiographic examination, especially for assessing alveolar bone levels, bone defect morphology, and bone quality. This narrative review aimed to comprehensively outline the current state-of-the-art in radiographic diagnosis of alveolar bone diseases, covering both two-dimensional (2D) and three-dimensional (3D) modalities. Additionally, this review explores recent technological advances in periodontal imaging diagnosis, focusing on their potential integration into clinical practice. Clinical probing and intraoral radiography, while crucial, encounter limitations in effectively assessing complex periodontal bone defects. Recognizing these challenges, 3D imaging modalities, such as cone beam computed tomography (CBCT), have been explored for a more comprehensive understanding of periodontal structures. The significance of the radiographic assessment approach is evidenced by its ability to offer an objective and standardized means of evaluating hard tissues, reducing variability associated with manual clinical measurements and contributing to a more precise diagnosis of periodontal health. However, clinicians should be aware of challenges related to CBCT imaging assessment, including beam-hardening artifacts generated by the high-density materials present in the field of view, which might affect image quality. Integration of digital technologies, such as artificial intelligence-based tools in intraoral radiography software, the enhances the diagnostic process. The overarching recommendation is a judicious combination of CBCT and digital intraoral radiography for enhanced periodontal bone assessment. Therefore, it is crucial for clinicians to weigh the benefits against the risks associated with higher radiation exposure on a case-by-case basis, prioritizing patient safety and treatment outcomes.

Does the Outcome of Graft Materials at Dental Implant Sites Differ Between Patients With Normal and Compromised Bone Health?

The objective of this paper was to assess the outcome of bone graft material at alveolar bone augmentation sites combined with dental implants in postmenopausal women with compromised bone health by evaluating cone beam computerized tomography (CBCT) scans at multiple time points.CBCT scans were analyzed on 55 postmenopausal women with compromised bone health status to determine the fate of alveolar bone augmentation. CBCT scans were taken immediately after surgery and 9 and 24 months postoperatively. The patient's medication regimens and durations were recorded, and the pixel intensity value (PIV) was measured and standardized using scoring criteria and visual assessment. Statistical analyses included 2-sample t tests for continuous variables and Fisher's exact tests for categorical variables.Among the normal patients, 73% received a grade 2 visual score, and 27% received a grade 1 visual score. After 24 months, 45% of patients received a grade 2 score, and 27% received a grade 3 score. In the osteoporotic group receiving medication, 77% of participants received a grade 1 visual score at the 9-month postoperative evaluation, while 23% received a grade 2 score. At the 24-month assessment, 55% of patients received a grade 1 score, 41% received a grade 2 score, and only 5% received a grade 3 score. Notably, although the graft material did not remodel into native bone, it was a scaffold for implants in controlled osteoporotic patients. The study's results show that the pixel intensity values of particulate graft materials are similar across the three different time points, suggesting that the graft material's pixel intensity value remains constant in postmenopausal women with osteoporosis. The study's limitations include a small sample size and a restricted 24-month follow-up period. This limited time frame may need to capture long-term changes or variations in graft materials adequately. Future research should include a larger sample size and have a longer follow-up duration to provide a more comprehensive understanding of the change in graft materials between patients with normal and compromised bone health.

Assessing the Impact of the Metal Artifact Reduction Tool on Detecting Furcation Lesions in Maxillary Molars with Different Intracanal Posts: An Ex Vivo Cone-beam Computed Tomography Study

INTRODUCTION

Considering the potential image compromise and diagnostic challenges posed by metals, this study aimed to assess the efficacy of the metal artifact reduction (MAR) tool in cone-beam computed tomography examinations for detecting furcation lesions in upper molars treated endodontically and restored with different intracanal posts.

METHODS

This ex vivo study used 45 endodontically treated maxillary first molars, categorized into the following3 groups (n = 15): control (without intracanal post), metal post, and fiberglass post. Simulations were conducted in the laboratory to replicate alveolar bone, periodontal ligament, and grade I, II, and III furcation lesions. Cone-beam computed tomography scans were obtained with and without the MAR tool, and the furcation lesions were evaluated considering a 5-point Likert scale. Data were analyzed at 5%.

RESULTS

In the control group, there was no influence of MAR (P > .05); grade II lesions were not diagnosed, and grade III lesions were the most detected (P < .05). In the metal post group with MAR, grade III lesions were diagnosed more frequently than I and II (P < .05) and grade III without MAR (P < .05). In the fiberglass post group, the diagnosis of grade I lesions decreased with MAR (P < .05), and without MAR, grade III was most diagnosed (P < .05); grade III lesions were the most diagnosed (P < .05).

CONCLUSIONS

The MAR tool was only effective for diagnosing grade III furcation lesions, regardless of the intracanal material. Its application for grade I and II lesions did not contribute to improved diagnosis. Furthermore, in the fiberglass post group with grade I lesions, the MAR tool negatively affected the detection of the lesions.

A conservative approach to localize loose implant screw through cemented crown: an in vitro experimental study

BACKGROUND

Retrieval of cement-retained implant-supported restorations is intriguing in cases of screw loosening. Detecting the estimated size of the screw access hole (SAH) could decrease destruction to the prosthesis and preserve the crown.

OBJECTIVES

To precisely localize loose implant screws through cemented crowns to reduce crown damage after screw loosening.

MATERIALS AND METHODS

In this in vitro study, 60 cement-retained implants supported 30 zirconia-based, and 30 ceramics fused to metal (CFM) lower molar crowns were invented, and each was subdivided into three subgroups (10 each). In group I (AI/BI) (control), SAH was created with the aid of orthopantomography (OPG). In contrast, in group II (zirconia-crown), SAH was created with the aid of CBCT + 3D printed surgical guide with a 2 mm metal sleeve in subgroups IIA/IIIA and CBCT + MAR was used to develop SAH in subgroups IIB/IIIB. SEM and Micro-CT scanned the SAH openings to determine the diameter of the hole, cracking, chipping, and chipping volume.

RESULTS

Regarding the effect of plane CBCT and CBCT + MAR on prepared crowns, a highly significant association between group I with group II (p = 0.001) and group III (p = 0.002) was detected. Regarding the cracking of SAH, significant differences between the zirconium crown and CFM restoration (p = 0.009) were found, while for the chipping, no significant association was seen between groups (p = 0.19).

CONCLUSIONS

CBCT, either as a plane CBCT or with MAR, significantly improved the accuracy of drilling the screw channel and decreased injury to the existing restoration and abutment, aiding in better localization of SAH in loosened implant abutment screws.

The comparison of visibility of the maxillary sinus septa between cone-beam computed tomography scans and panoramic radiograph images as dependent on the cortical bone thickness: a retrospective comparative study

PURPOSE

To analyze the visibility of the maxillary sinus septa (MSS) in panoramic radiography (PR) versus cone beam computed tomography (CBCT) and to investigate whether the buccal cortical bone thickness (BT) or the septa dimensions influence their visibility.

METHODS

Corresponding PR and CBCT images of 355 patients were selected and examined for MSS visibility. The septa dimensions (width, height, depth) and the BT were measured. Results were analysed statistically.

RESULTS

Comparing the corresponding regions on CBCT and PR, 170 MSS were identified; however, only 106 of these were also visible using PR. The MSS visibility was significantly higher on CBCT versus PR images (P1: p = 0.039, P2: p = 0.015, M1: p = 0.041, M2: p = 0.017, M3: p = 0.000), except region C (p = 0.625). Regarding the measurements of MSS dimensions, only the height in region M1 (p = 0.013) and the width in region P2 (p = 0.034) were significantly more visible on CBCT. The BT in the area of the MSS was found to have a marginal influence on its visibility on the PR images only in regions M3 and M1 (M3: p = 0.043, M1: p = 0.047). In terms of MSS visibility based on the dimensions, significance was found for all three influencing variables only in region P2 (width; p = 0.041, height; p = 0.001, depth; p = 0.007). There were only isolated cases of further significance: M3 for width (p = 0.043), M2 for height (p = 0.024), and P1 for depth (p = 0.034), no further significance was noted.

CONCLUSION

MSS visibility appears significantly higher on CBCT versus PR images. It is concluded that the septa dimensions and BT can influence MSS visibility on PR images just in certain regions.

Facial soft-tissue thickness in children: A study of a CTBC Brazilian sample

As an auxiliary method in the process of human identification, forensic facial approximation (FFA) is an important tool for identifying unknown human bodies whose remains do not present the necessary traceability to any antemortem data collection. Specific characteristics are necessary when addressing children aged between 6 and 10 years, who have little sexual differentiation and a mixed dentition. Due to the chronology of eruption of the permanent second molars in this population, it is not possible to measure facial soft-tissue thickness (FSTT) from specific landmarks such as supra and infra M2. The objective of this research was to report the method for measuring the average FSTT of 32 landmarks adapting the method for adults replacing the landmarks at the upper and lower second molars (Supra M2 and Infra M2) in children up to 10 years of age for a measurement using the deciduous second molars as reference. We found statistical differences for some points, considering the variables of age and sex, but with a maximum difference of 2 mm, which allows the use of a single FSTT table. The deciduous teeth can replace the reference of the thicknesses at the supra and infra M2 landmarks. In addition to the new FSTT data for children in Brazil, we concluded that the proposed adaptation to the deciduous M2 points can be applied to obtain soft-tissue data for 32 facial points.

Fractures in Thoroughbred racing and the potential for pre-race identification of horses at risk

Risk rates for and predisposing factors to fractures occurring in Thoroughbred racing that have been published in peer reviewed journals are documented. The potential for currently available techniques to identify horses at increased risk for fracture is discussed on the bases of principles, practicalities, advantages, disadvantages and current data. All are reviewed in light of justifiable decision making and importance of fractures to horseracing's social license.

Surveying the landscape of diagnostic imaging in dentistry's future: Four emerging technologies with promise

BACKGROUND

Advances in digital radiography for both intraoral and panoramic imaging and cone-beam computed tomography have led the way to an increase in diagnostic capabilities for the dental care profession. In this article, the authors provide information on 4 emerging technologies with promise.

TYPES OF STUDIES REVIEWED

The authors feature the following: artificial intelligence in the form of deep learning using convolutional neural networks, dental magnetic resonance imaging, stationary intraoral tomosynthesis, and second-generation cone-beam computed tomography sources based on carbon nanotube technology and multispectral imaging. The authors review and summarize articles featuring these technologies.

RESULTS

The history and background of these emerging technologies are previewed along with their development and potential impact on the practice of dental diagnostic imaging. The authors conclude that these emerging technologies have the potential to have a substantial influence on the practice of dentistry as these systems mature. The degree of influence most likely will vary, with artificial intelligence being the most influential of the 4.

CONCLUSIONS AND PRACTICAL IMPLICATIONS

The readers are informed about these emerging technologies and the potential effects on their practice going forward, giving them information on which to base decisions on adopting 1 or more of these technologies. The 4 technologies reviewed in this article have the potential to improve imaging diagnostics in dentistry thereby leading to better patient care and heightened professional satisfaction.

AAPM Task Group Report 261: Comprehensive quality control methodology and management of dental and maxillofacial cone beam computed tomography (CBCT) systems

Cone-beam computed tomography (CBCT) systems specifically designed and manufactured for dental, maxillofacial imaging (MFI) and otolaryngology (OLR) applications have been commercially available in the United States since 2001 and have been in widespread clinical use since. Until recently, there has been a lack of professional guidance available for medical physicists about how to assess and evaluate the performance of these systems and about the establishment and management of quality control (QC) programs. The owners and users of dental CBCT systems may have only a rudimentary understanding of this technology, including how it differs from conventional multidetector CT (MDCT) in terms of acceptable radiation safety practices. Dental CBCT systems differ from MDCT in several ways and these differences are described. This report provides guidance to medical physicists and serves as a basis for stakeholders to make informed decisions regarding how to manage and develop a QC program for dental CBCT systems. It is important that a medical physicist with experience in dental CBCT serves as a resource on this technology and the associated radiation protection best practices. The medical physicist should be involved at the pre-installation stage to ensure that a CBCT room configuration allows for a safe and efficient workflow and that structural shielding, if needed, is designed into the architectural plans. Acceptance testing of new installations should include assessment of mechanical alignment of patient positioning lasers and x-ray beam collimation and benchmarking of essential image quality performance parameters such as image uniformity, noise, contrast-to-noise ratio (CNR), spatial resolution, and artifacts. Several approaches for quantifying radiation output from these systems are described, including simply measuring the incident air-kerma (Kair) at the entrance surface of the image receptor. These measurements are to be repeated at least annually as part of routine QC by the medical physicist. QC programs for dental CBCT, at least in the United States, are often driven by state regulations, accreditation program requirements, or manufacturer recommendations.

Low-cost dual-energy CBCT by spectral filtration of a dual focal spot X-ray source

Dual-energy cone beam computed tomography (DE-CBCT) has been shown to provide more information and improve performance compared to a conventional single energy spectrum CBCT. Here we report a low-cost DE-CBCT by spectral filtration of a carbon nanotube x-ray source array. The x-ray photons from two focal spots were filtered respectively by a low and a high energy filter. Projection images were collected by alternatively activating the two beams while the source array and detector rotated around the object, and were processed by a one-step materials decomposition and reconstruction method. The performance of the DE-CBCT scanner was evaluated by imaging a water-equivalent plastic phantom with inserts containing known densities of calcium or iodine and an anthropomorphic head phantom with dental implants. A mean energy separation of 15.5 keV was achieved at acceptable dose rates and imaging time. Accurate materials quantification was obtained by materials decomposition. Metal artifacts were reduced in the virtual monoenergetic images synthesized at high energies. The results demonstrated the feasibility of high quality DE-CBCT imaging by spectral filtration without using either an energy sensitive detector or rapid high voltage switching.

Fully automatic integration of dental CBCT images and full-arch intraoral impressions with stitching error correction via individual tooth segmentation and identification

We present a fully automated method of integrating intraoral scan (IOS) and dental cone-beam computerized tomography (CBCT) images into one image by complementing each image's weaknesses. Dental CBCT alone may not be able to delineate precise details of the tooth surface due to limited image resolution and various CBCT artifacts, including metal-induced artifacts. IOS is very accurate for the scanning of narrow areas, but it produces cumulative stitching errors during full-arch scanning. The proposed method is intended not only to compensate the low-quality of CBCT-derived tooth surfaces with IOS, but also to correct the cumulative stitching errors of IOS across the entire dental arch. Moreover, the integration provides both gingival structure of IOS and tooth roots of CBCT in one image. The proposed fully automated method consists of four parts; (i) individual tooth segmentation and identification module for IOS data (TSIM-IOS); (ii) individual tooth segmentation and identification module for CBCT data (TSIM-CBCT); (iii) global-to-local tooth registration between IOS and CBCT; and (iv) stitching error correction for full-arch IOS. The experimental results show that the proposed method achieved landmark and surface distance errors of 112.4μm and 301.7μm, respectively.

Volumetric analysis of artifacts from fiducial markers under cone beam computed tomography

Abstract Background/purpose

Computer aided implant surgery has been widely adopted in modern implant dentistry. However, absence of reliable anatomic landmarks for superimposing digital data sets for patients with terminal dentition or complete edentulism remained challenging. Utilization of additional fiducial markers intraorally as the reference points for the improvement of accuracy became crucial in implant digital workflow. Nevertheless, the choice of the material for fiducial markers should present the least radiographic artifacts under cone beam computed tomography (CBCT) for better accuracy. The aim of this in vitro study was to investigate the volume of radiographic artifacts generated through different materials under the image of CBCT.

Materials and methods

Fifteen dental materials were selected and configured into cubic shape. All the materials were scanned initially with the laboratory scanner as the control groups. The samples were scanned by CBCT machine as test groups and the volume of artifact generated under CBCT images were compared and analyzed using 3D modeling software.

Results

Eleven out of fifteen materials could be recognized under CBCT images. Volumetric analysis reported that statistically significant differences among the materials could be noted, and the flowable composite resin presented the least volumetric difference. Lithium disilicate glass-ceramic, flowable composite resin, and gutta-percha presented the least deformation and maintained their cubic shapes.

Conclusion

The results of the present study may imply that flowable composite resin compared to all ceramic materials, amalgam and gutta-percha may be a preferable choice when utilized as fiducial markers under CBCT images.

A carbon nanotube x-ray source array designed for a new multisource cone beam computed tomography scanner

Cone beam computed tomography (CBCT) is known to suffer from strong scatter and cone beam artifacts. The purpose of this study is to develop and characterize a rapidly scanning carbon nanotube (CNT) field emission x-ray source array to enable a multisource CBCT (ms-CBCT) image acquisition scheme which has been demonstrated to overcome these limitations. A CNT x-ray source array with eight evenly spaced focal spots was designed and fabricated for a medium field of view ms-CBCT for maxillofacial imaging. An external multisource collimator was used to confine the radiation from each focal spot to a narrow cone angle. For ms-CBCT imaging, the array was placed in the axial direction and rapidly scanned while rotating continuously around the object with a flat panel detector. The x-ray beam profile, temporal and spatial resolutions, energy and dose rate were characterized and evaluated for maxillofacial imaging. The CNT x-ray source array achieved a consistent focal spot size of 1.10 ± 0.04 mm × 0.84 ± 0.03 mm and individual beam cone angle of 2.4°±0.08 after collimation. The x-ray beams were rapidly switched with a rising and damping times of 0.21 ms and 0.19 ms, respectively. Under the designed operating condition of 110 kVp and 15 mA, a dose rate of 8245μGy s-1was obtained at the detector surface with the inherent Al filtration and 2312μGy s-1with an additional 0.3 mm Cu filter. There was negligible change of the x-ray dose rate over many operating cycles. A ms-CBCT scan of an adult head phantom was completed in 14.4 s total exposure time for the imaging dose in the range of that of a clinical CBCT scanner. A spatially distributed CNT x-ray source array was designed and fabricated. It has enabled a new multisource CBCT to overcome some of the main inherent limitations of the conventional CBCT.

Feasibility of frozen soft tissues to simulate fresh soft tissue conditions in cone beam CT scans

OBJECTIVES

To evaluate the feasibility of frozen soft tissues in simulating fresh soft tissues of pig mandibles using cone beam CT (CBCT).

METHODS

Two fresh pig mandibles with soft tissues containing 2 tubes filled with a radiopaque homogeneous solution were scanned using 4 CBCT units and 2 field-of-view (FOV) sizes each. The pig mandibles were deep-frozen and scanned again. Three cross-sections were exported from each CBCT volume and grouped into pairs, with one cross-section representing a fresh and one a frozen mandible. Three radiologists compared the pairs and attributed a score to assess the relative image quality using a 5-point scale. Mean grey values and standard deviation were obtained from homogeneous areas in the tubes, compared using the Wilcoxon matched-pair signed-rank test and subjected to Pearson correlation analysis between fresh and frozen physical states (α = .05).

RESULTS

Subjective evaluation revealed similarity of the CBCT image quality between fresh and frozen states. The distribution of mean grey values was similar between fresh and frozen states. Mean grey values of the frozen state in the small FOV were significantly greater than those of the fresh state (P = .037), and noise values of the frozen state in the large FOV were significantly greater than those of the fresh state (P = 0.007). Both mean grey values and noise exhibited significant and positive correlations between fresh and frozen states (P < 0.01).

CONCLUSIONS

The freezing of pig mandibles with soft tissues may serve as a method to prolong their usability and working time when CBCT imaging is planned.

Magnetic resonance imaging in dental implant surgery: a systematic review

PURPOSE

To comprehensively assess the existing literature regarding the rapidly evolving in vivo application of magnetic resonance imaging (MRI) for potential applications, benefits, and challenges in dental implant surgery.

METHODS

Electronic and manual searches were conducted in PubMed MEDLINE, EMBASE, Biosis, and Cochrane databases by two reviewers following the PICOS search strategy. This involved using medical subject headings (MeSH) terms, keywords, and their combinations.

RESULTS

Sixteen studies were included in this systematic review. Of the 16, nine studies focused on preoperative planning and follow-up phases, four evaluated image-guided implant surgery, while three examined artifact reduction techniques. The current literature highlights several MRI protocols that have recently investigated and evaluated the in vivo feasibility and accuracy, focusing on its potential to provide surgically relevant quantitative and qualitative parameters in the assessment of osseointegration, peri-implant soft tissues, surrounding anatomical structures, reduction of artifacts caused by dental implants, and geometric accuracy relevant to implant placement. Black Bone and MSVAT-SPACE MRI, acquired within a short time, demonstrate improved hard and soft tissue resolution and offer high sensitivity in detecting pathological changes, making them a valuable alternative in targeted cases where CBCT is insufficient. Given the data heterogeneity, a meta-analysis was not possible.

CONCLUSIONS

The results of this systematic review highlight the potential of dental MRI, within its indications and limitations, to provide perioperative surgically relevant parameters for accurate placement of dental implants.

Digital registration versus cone-beam computed tomography for evaluating implant position: a prospective cohort study

BACKGROUND

Postoperative cone-beam computed tomography (CBCT) examination is considered a reliable method for clinicians to assess the positions of implants. Nevertheless, CBCT has drawbacks involving radiation exposure and high costs. Moreover, the image quality can be affected by artifacts. Recently, some literature has mentioned a digital registration method (DRM) as an alternative to CBCT for evaluating implant positions. The aim of this clinical study was to verify the accuracy of the DRM compared to CBCT scans in postoperative implant positioning.

MATERIALS AND METHODS

A total of 36 patients who received anterior maxillary implants were included in this clinical study, involving a total of 48 implants. The study included 24 patients in the single implant group and 12 patients in the dual implant group. The postoperative three-dimensional (3D) positions of implants were obtained using both CBCT and DRM. The DRM included three main steps. Firstly, the postoperative 3D data of the dentition and intraoral scan body (ISB) was obtained through the intraoral scan (IOS). Secondly, a virtual model named registration unit which comprised an implant replica and a matching ISB was created with the help of a lab scanner and reverse engineering software. Thirdly, by superimposing the registration unit and IOS data, the postoperative position of the implant was determined. The accuracy of DRM was evaluated by calculating the Root Mean Square (RMS) values after superimposing the implant positions obtained from DRM with those from postoperative CBCT. The accuracy of DRM was compared between the single implant group and the dual implant group using independent sample t-tests. The superimposition deviations of CBCT and IOS were also evaluated.

RESULTS

The overall mean RMS was 0.29 ± 0.05 mm. The mean RMS was 0.30 ± 0.03 mm in the single implant group and 0.29 ± 0.06 mm in the dual implant group, with no significant difference (p = 0.27). The overall registration accuracy of the IOS and CBCT data ranged from 0.14 ± 0.05 mm to 0.21 ± 0.08 mm.

CONCLUSION

In comparison with the 3D implant positions obtained by CBCT, the implant positions located by the DRM showed clinically acceptable deviation ranges. This method can be used in single and dual implant treatments to assess the implant positions.

Effect of a metal artifact reduction algorithm on dehiscence and fenestration detection around zirconia implants with cone beam computed tomography

OBJECTIVE

To assess the efficacy of the metal artifact reduction algorithm (MARA) of the Cranex 3D cone beam computed tomography (CBCT) device in the detection of peri-implant dehiscence and fenestration around zirconia implants.

STUDY DESIGN

In total, 60 implants were placed in bovine ribs. Dehiscence and fenestration defects were created around the implants, after which 60 CBCT images were obtained with and 60 without activation of MARA. Three radiologists examined the images for the presence of defects. The area under the curve (AUC) from receiver operating characteristic analysis, sensitivity, and specificity were calculated to assess the ability to discriminate the presence vs absence of bone defects. One-way analysis of variance was employed to analyze outcome measures. The significance level was established at 5% (α = 0.05).

RESULTS

AUC values indicated excellent discrimination of dehiscence on images with MARA activation and an excellent to outstanding range of discrimination with MARA deactivation. For fenestration, MARA activation and deactivation both led to outstanding discrimination. Sensitivity and specificity values revealed that activation of MARA was helpful in distinguishing the presence vs. absence of dehiscence, while both MARA conditions were helpful for fenestration. However, there were no statistically significant differences between MARA activation and deactivation for any outcome measure (P >.05).

CONCLUSION

CBCT is suitable for detecting peri-implant defects, but MARA application does not significantly affect peri-implant dehiscence and fenestration detection.

A comprehensive review and update on the current state of computer-assisted rehabilitation in implant dentistry

AIM

This paper provides a comprehensive review of the established concepts and newer developments related to computer-assisted implant rehabilitation.

METHODS

Two independent researchers searched the English literature published to 31st December 2023 in the PubMed/Medline database for primary and secondary research and related publications on computer-assisted implant planning, computer-assisted implant placement and computer-assisted implant restoration.

RESULTS

A total of 58,923 papers were identified, 198 relevant papers were read in full text and 110 studies were finally included. Computer-assisted implant rehabilitation was found to result in more precise implant positioning than freehand placement. Advantages include reduced trauma and surgery time; disadvantages include reduced primary implant stability and higher cost.

CONCLUSION

Computer-assisted surgery is particularly indicated in cases of critical anatomy, but may encounter limitations in terms of cost, restricted mouth opening, visibility and adjustment of the surgical guides and the need for prior familiarisation with the procedure. Nonetheless, this surgical technique reduces the post-implant placement complication rate.

CBCT-Based synthetic CT image generation using conditional denoising diffusion probabilistic model

BACKGROUND

Daily or weekly cone-beam computed tomography (CBCT) scans are commonly used for accurate patient positioning during the image-guided radiotherapy (IGRT) process, making it an ideal option for adaptive radiotherapy (ART) replanning. However, the presence of severe artifacts and inaccurate Hounsfield unit (HU) values prevent its use for quantitative applications such as organ segmentation and dose calculation. To enable the clinical practice of online ART, it is crucial to obtain CBCT scans with a quality comparable to that of a CT scan.

PURPOSE

This work aims to develop a conditional diffusion model to perform image translation from the CBCT to the CT distribution for the image quality improvement of CBCT.

METHODS

The proposed method is a conditional denoising diffusion probabilistic model (DDPM) that utilizes a time-embedded U-net architecture with residual and attention blocks to gradually transform the white Gaussian noise sample to the target CT distribution conditioned on the CBCT. The model was trained on deformed planning CT (dpCT) and CBCT image pairs, and its feasibility was verified in brain patient study and head-and-neck (H&N) patient study. The performance of the proposed algorithm was evaluated using mean absolute error (MAE), peak signal-to-noise ratio (PSNR) and normalized cross-correlation (NCC) metrics on generated synthetic CT (sCT) samples. The proposed method was also compared to four other diffusion model-based sCT generation methods.

RESULTS

In the brain patient study, the MAE, PSNR, and NCC of the generated sCT were 25.99 HU, 30.49 dB, and 0.99, respectively, compared to 40.63 HU, 27.87 dB, and 0.98 of the CBCT images. In the H&N patient study, the metrics were 32.56 HU, 27.65 dB, 0.98 and 38.99 HU, 27.00, 0.98 for sCT and CBCT, respectively. Compared to the other four diffusion models and one Cycle generative adversarial network (Cycle GAN), the proposed method showed superior results in both visual quality and quantitative analysis.

CONCLUSIONS

The proposed conditional DDPM method can generate sCT from CBCT with accurate HU numbers and reduced artifacts, enabling accurate CBCT-based organ segmentation and dose calculation for online ART.

The effect of voxel and field of view size on the volumetric alteration artifact of high-density materials with 2 cone beam computed tomography devices

OBJECTIVE

We investigated the influence of voxel and field of view (FOV) sizes on expression of the volumetric alteration artifact (VAA) of 5 high-density materials in 2 cone beam computed tomography (CBCT) devices.

STUDY DESIGN

Cylinders of amalgam, cobalt-chromium, gutta-percha, titanium, and zirconium were individually positioned in a polymethyl methacrylate phantom. OP300 Maxio and ProMax 3D Classic CBCT devices were used to acquire images with varying voxel and FOV sizes, totaling 585 scans. Two evaluators segmented the high-density cylinder images to obtain the tomographic volumes. The difference between the tomographic and physical volume of each cylinder (i.e., volumetric alteration) was calculated. Statistical analysis was conducted with multiway ANOVA and the Tukey post hoc test (α = 5%). Evaluator reliability was measured with the intraclass correlation coefficient (ICC).

RESULTS

All studied parameters and nearly all interactions influenced the VAA (P < .05). The post hoc test demonstrated less volumetric alteration for the smallest voxel sizes, 61 × 78 mm FOV, and gutta-percha for OP300, and for the smallest voxel sizes, 80 × 80 mm FOV, and gutta-percha and titanium for ProMax 3D (P < .05). The ICC demonstrated perfect reliability (1.00).

CONCLUSIONS

Voxel and FOV sizes influenced VAA expression. Using smaller voxel sizes, the 61 × 78 mm FOV for OP300 and the 80 × 80 mm FOV for ProMax 3D, and materials with lower density and lower atomic number reduced VAA expression.

Contouring practices and artefact management within a synthetic CT-based radiotherapy workflow for the central nervous system

BACKGROUND

The incorporation of magnetic resonance (MR) imaging in radiotherapy (RT) workflows improves contouring precision, yet it introduces geometrical uncertainties when registered with computed tomography (CT) scans. Synthetic CT (sCT) images could minimize these uncertainties and streamline the RT workflow. This study aims to compare the contouring capabilities of sCT images with conventional CT-based/MR-assisted RT workflows, with an emphasis on managing artefacts caused by surgical fixation devices (SFDs).

METHODS

The study comprised a commissioning cohort of 100 patients with cranial tumors treated using a conventional CT-based/MR-assisted RT workflow and a validation cohort of 30 patients with grade IV glioblastomas treated using an MR-only workflow. A CE-marked artificial-intelligence-based sCT product was utilized. The delineation accuracy comparison was performed using dice similarity coefficient (DSC) and average Hausdorff distance (AHD). Artefacts within the commissioning cohort were visually inspected, classified and an estimation of thickness was derived using Hausdorff distance (HD). For the validation cohort, boolean operators were used to extract artefact volumes adjacent to the target and contrasted to the planning treatment volume.

RESULTS

The combination of high DSC (0.94) and low AHD (0.04 mm) indicates equal target delineation capacity between sCT images and conventional CT scans. However, the results for organs at risk delineation were less consistent, likely because of voxel size differences between sCT images and CT scans and absence of standardized delineation routines. Artefacts observed in sCT images appeared as enhancements of cranial bone. When close to the target, they could affect its definition. Therefore, in the validation cohort the clinical target volume (CTV) was expanded towards the bone by 3.5 mm, as estimated by HD analysis. Subsequent analysis on cone-beam CT scans showed that the CTV adjustment was enough to provide acceptable target coverage.

CONCLUSION

The tested sCT product performed on par with conventional CT in terms of contouring capability. Additionally, this study provides both the first comprehensive classification of metal artefacts on a sCT product and a novel method to assess the clinical impact of artefacts caused by SFDs on target delineation. This methodology encourages similar analysis for other sCT products.

Do metal artifact reduction algorithms influence the detection of implant-related injuries to the inferior alveolar canal in CBCT images?

BACKGROUND

The routine application of dental implants for replacing missing teeth has revolutionized restorative and prosthetic dentistry. However, cone beam computed tomography (CBCT) evaluations of structures adjacent to the implants are limited by metal artifacts. There are several methods for reducing metal artifacts, but this remains a challenging task. This study aimed to examine the effectiveness of metal artifact reduction (MAR) algorithms in identifying injuries of implants to the inferior alveolar canal in CBCT images.

METHOD

In this in vitro study, mono-cortical bone windows were created and the inferior alveolar canal was revealed. Using 36 implants, pilot drill and penetration damage of the implant tip into the canal was simulated and compared to the control implants with distance from the canal. CBCT images were evaluated by four experienced observers with and without the MAR algorithm and compared to direct vision as the gold standard. The values of accuracy, sensitivity, and specificity were obtained and compared by receiver operating characteristic (ROC) curve (α = 0.05).

RESULT

The area under the ROC curve values for detection of pilot drill injuries varied between 0.840-0.917 and 0.639-0.854 in the active and inactive MAR conditions, respectively. The increase in ROC area was only significant for one of the observers (P = 0.010). For diagnosing penetrative injuries, the area under the ROC curve values was between 0.990-1.000 and 0.722-1.000 in the active and inactive MAR conditions, respectively. The improvement of ROC curve values in active MAR mode was only significant for one of the observers (P = 0.006).

CONCLUSION

Activation of MAR improved the diagnostic values of CBCT images in detecting both types of implant-related injuries to the inferior alveolar canal. However, for most observers, this increase was not statistically significant.

Are Artificial Intelligence-Assisted Three-Dimensional Histological Reconstructions Reliable for the Assessment of Trabecular Microarchitecture?

Objectives: This study aimed to create a three-dimensional histological reconstruction through the AI-assisted classification of tissues and the alignment of serial sections. The secondary aim was to evaluate if the novel technique for histological reconstruction accurately replicated the trabecular microarchitecture of bone. This was performed by conducting micromorphometric measurements on the reconstruction and comparing the results obtained with those of microCT reconstructions. Methods: A bone biopsy sample was harvested upon re-entry following sinus floor augmentation. Following microCT scanning and histological processing, a modified version of the U-Net architecture was trained to categorize tissues on the sections. Detector-free local feature matching with transformers was used to create the histological reconstruction. The micromorphometric parameters were calculated using Bruker's CTAn software (version 1.18.8.0, Bruker, Kontich, Belgium) for both histological and microCT datasets. Results: Correlation coefficients calculated between the micromorphometric parameters measured on the microCT and histological reconstruction suggest a strong linear relationship between the two with p-values of 0.777, 0.717, 0.705, 0.666, and 0.687 for BV/TV, BS/TV, Tb.Pf Tb.Th, and Tb.Sp, respectively. Bland-Altman and mountain plots suggest good agreement between BV/TV measurements on the two reconstruction methods. Conclusions: This novel method for three-dimensional histological reconstruction provides researchers with a tool that enables the assessment of accurate trabecular microarchitecture and histological information simultaneously.

A 4D-CBCT correction network based on contrastive learning for dose calculation in lung cancer

OBJECTIVE

This study aimed to present a deep-learning network called contrastive learning-based cycle generative adversarial networks (CLCGAN) to mitigate streak artifacts and correct the CT value in four-dimensional cone beam computed tomography (4D-CBCT) for dose calculation in lung cancer patients.

METHODS

4D-CBCT and 4D computed tomography (CT) of 20 patients with locally advanced non-small cell lung cancer were used to paired train the deep-learning model. The lung tumors were located in the right upper lobe, right lower lobe, left upper lobe, and left lower lobe, or in the mediastinum. Additionally, five patients to create 4D synthetic computed tomography (sCT) for test. Using the 4D-CT as the ground truth, the quality of the 4D-sCT images was evaluated by quantitative and qualitative assessment methods. The correction of CT values was evaluated holistically and locally. To further validate the accuracy of the dose calculations, we compared the dose distributions and calculations of 4D-CBCT and 4D-sCT with those of 4D-CT.

RESULTS

The structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) of the 4D-sCT increased from 87% and 22.31 dB to 98% and 29.15 dB, respectively. Compared with cycle consistent generative adversarial networks, CLCGAN enhanced SSIM and PSNR by 1.1% (p < 0.01) and 0.42% (p < 0.01). Furthermore, CLCGAN significantly decreased the absolute mean differences of CT value in lungs, bones, and soft tissues. The dose calculation results revealed a significant improvement in 4D-sCT compared to 4D-CBCT. CLCGAN was the most accurate in dose calculations for left lung (V5Gy), right lung (V5Gy), right lung (V20Gy), PTV (D98%), and spinal cord (D2%), with the relative dose difference were reduced by 6.84%, 3.84%, 1.46%, 0.86%, 3.32% compared to 4D-CBCT.

CONCLUSIONS

Based on the satisfactory results obtained in terms of image quality, CT value measurement, it can be concluded that CLCGAN-based corrected 4D-CBCT can be utilized for dose calculation in lung cancer.

High-density objects in exomass affect the volume of high-density objects inside the field of view

OBJECTIVES

To evaluate the effect of the presence and the number of high-density objects in the exomass on the volume of a high-density object in cone-beam CT (CBCT).

METHODS

Cylinders of cobalt-chromium (Co-Cr), titanium (Ti), and zirconium (Zi) were inserted into a polymethylmethacrylate phantom in five different combinations of number and position: 1-no cylinder; 2-one cylinder in a posterior region; 3-one cylinder in an anterior region; 4-two cylinders in posterior regions; and 5-three cylinders in anterior and posterior regions. The phantom underwent CBCT scanning using OP300 and X800 systems, with the afore mentioned cylinders of the same composition placed in the exomass and an additional high-density cylinder placed in the centre of the field of view (FOV), corresponding to the left-anterior region. The tomographic volume of the cylinder inside the FOV was measured using semi-automatic segmentation. The volumetric alteration (VA) between the segmented and physical volumes, in percentage, was compared among the experimental groups using repeated measures ANOVA and Tukey post-hoc (α = 5%).

RESULTS

The factors material, combination, and their interaction affected the volume or both CBCT systems. In OP300, more cylinders in the exomass reduced the VA, mainly for Co-Cr. In X800, more cylinders in the exomass tended to increase the VA inside the FOV, except for Zi.

CONCLUSIONS

In general, the presence of high-density objects in the exomass influences the VA of the object inside the FOV, although this oscillates according to object composition, number and position in the exomass, and CBCT system.

Ultra-low-dose photon-counting CT of paranasal sinus: an in vivo comparison of radiation dose and image quality to cone-beam CT

PURPOSE

This study investigated the differences in subjective and objective image parameters as well as dose exposure of photon-counting CT (PCCT) compared to cone-beam CT (CBCT) in paranasal sinus imaging for the assessment of rhinosinusitis and sinonasal anatomy.

METHODS

This single-centre retrospective study included 100 patients, who underwent either clinically indicated PCCT or CBCT of the paranasal sinus. Two blinded experienced ENT radiologists graded image quality and delineation of specific anatomical structures on a 5-point Likert scale. In addition, contrast-to-noise ratio (CNR) and applied radiation doses were compared among both techniques.

RESULTS

Image quality and delineation of bone structures in paranasal sinus PCCT was subjectively rated superior by both readers compared to CBCT (P < .001). CNR was significantly higher for photon-counting CT (P < .001). Mean effective dose for PCCT examinations was significantly lower than for CBCT (0.038 mSv ± 0.009 vs. 0.14 mSv ± 0.011; P < .001).

CONCLUSION

In a performance comparison of PCCT and a modern CBCT scanner in paranasal sinus imaging, we demonstrated that first-use PCCT in clinical routine provides higher subjective image quality accompanied by higher CNR at close to a quarter of the dose exposure compared to CBCT.

Influence of exposure protocol, voxel size, and artifact removal algorithm on the trueness of segmentation utilizing an artificial-intelligence-based system

PURPOSE

To evaluate the effects of exposure protocol, voxel sizes, and artifact removal algorithms on the trueness of segmentation in various mandible regions using an artificial intelligence (AI)-based system.

MATERIALS AND METHODS

Eleven dry human mandibles were scanned using a cone beam computed tomography (CBCT) scanner under differing exposure protocols (standard and ultra-low), voxel sizes (0.15 mm, 0.3 mm, and 0.45 mm), and with or without artifact removal algorithm. The resulting datasets were segmented using an AI-based system, exported as 3D models, and compared to reference files derived from a white-light laboratory scanner. Deviation measurement was performed using a computer-aided design (CAD) program and recorded as root mean square (RMS). The RMS values were used as a representation of the trueness of the AI-segmented 3D models. A 4-way ANOVA was used to assess the impact of voxel size, exposure protocol, artifact removal algorithm, and location on RMS values (α = 0.05).

RESULTS

Significant effects were found with voxel size (p < 0.001) and location (p < 0.001), but not with exposure protocol (p = 0.259) or artifact removal algorithm (p = 0.752). Standard exposure groups had significantly lower RMS values than the ultra-low exposure groups in the mandible body with 0.3 mm (p = 0.014) or 0.45 mm (p < 0.001) voxel sizes, the symphysis with a 0.45 mm voxel size (p = 0.011), and the whole mandible with a 0.45 mm voxel size (p = 0.001). Exposure protocol did not affect RMS values at teeth and alveolar bone (p = 0.544), mandible angles (p = 0.380), condyles (p = 0.114), and coronoids (p = 0.806) locations.

CONCLUSION

This study informs optimal exposure protocol and voxel size choices in CBCT imaging for true AI-based automatic segmentation with minimal radiation. The artifact removal algorithm did not influence the trueness of AI segmentation. When using an ultra-low exposure protocol to minimize patient radiation exposure in AI segmentations, a voxel size of 0.15 mm is recommended, while a voxel size of 0.45 mm should be avoided.

Comparison between observer-based and AI-based reading of CBCT datasets: An interrater-reliability study

Objective

To assess the performance of human observers and convolutional neural networks (CNNs) in detecting periodontal lesions in cone beam computed tomography (CBCT), a total of 38 datasets were examined. Three human readers and a CNN-based solution were employed to evaluate the presence of periodontal pathologies in these datasets.

Materials and Methods

Datasets were acquired with a Veraview X800 L P (JMorita Mfg. Corp., Kyoto, Japan). Three general dentists, previously calibrated by a general principal investigator, read the datasets in 3D MPR mode using Horos(LGPL license at Horosproject.org and sponsored by Nimble Co LLC d/b/a Purview in Annapolis, MD, USA) as a DICOM reader. All pathological changes including vertical bone loss, furcation involvement, and periradicular osteolysis were detected. Furthermore, the same datasets were analyzed automatically by Diagnocat (Diagnocat LLC, Prague, Czech Republic), a deep CNN. Finally, the performance of the dentists and the CNN were compared and evaluated.

Results

The CNN's performance was significantly lower compared to the human readers in the search for different types of lesions. The human observers achieved good to very good interobserver agreement, except for the evaluation of the vertical lesions, which resulted in a moderate agreement.

Conclusion

The CNN used in this study was found to be ineffective in identifying periodontal lesions and was not adequately trained to offer significant assistance in the automated evaluation of periodontal lesions in CBCT datasets.

Cone-beam computed tomography in endodontics: from the specific technical considerations of acquisition parameters and interpretation to advanced clinical applications

The implementation of imaging methods that enable sensitive and specific observation of anatomical structures has been a constant in the evolution of endodontic therapy. Cone-beam computed tomography (CBCT) enables 3-dimensional (3D) spatial anatomical navigation in the 3 volumetric planes (sagittal, coronal and axial) which translates into great accuracy for the identification of endodontic pathologies/conditions. CBCT interpretation consists of 2 main components: (i) the generation of specific tasks of the image and (ii) the subsequent interpretation report. A systematic and reproducible method to review CBCT scans can improve the accuracy of the interpretation process, translating into greater precision in terms of diagnosis and planning of endodontic clinical procedures. MEDLINE (PubMed), Web of Science, Google Scholar, Embase and Scopus were searched from inception to March 2023. This narrative review addresses the theoretical concepts, elements of interpretation and applications of the CBCT scan in endodontics. In addition, the contents and rationale for reporting 3D endodontic imaging are discussed.

Influence of an adjacent zirconium implant, tube current, and metal artifact reduction algorithm on horizontal root fracture diagnosis in cone beam computed tomography

OBJECTIVE

We evaluated the influence of an adjacent zirconium implant, tube current (mA), and a metal artifact reduction algorithm (MARA) on horizontal root fracture (HRF) diagnosis in cone beam computed tomography (CBCT).

STUDY DESIGN

Nineteen teeth (9 with HRF, 10 without) were individually placed in a human maxilla. Scan volumes were acquired without and with a zirconium implant adjacent to the tooth at settings of 4, 8, and 10 mA, with MARA disabled and enabled, using a 5×5 cm field of view, 0.085-mm voxel size, and 90 kV. Four maxillofacial radiologists individually assessed the scans. Diagnostic metrics were compared by multiway analysis of variance (α=5%). Inter- and intraexaminer agreements for HRF diagnosis were evaluated with the weighted kappa test.

RESULTS

Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were significantly lower in the presence of the implant (P≤.005). AUC values were higher in scans obtained with 8 and 10 mA compared with 4 mA (P=0.010), but 10 mA without MARA was better with the implant present. MARA did not significantly influence outcomes (P≥0.240). Inter- and intraexaminer agreements ranged from moderate to almost perfect.

CONCLUSIONS

The presence of the zirconium implant impairs HRF detection. Settings of 8 or 10 mA improve HRF detection regardless MARA condition without the implant. With an adjacent implant, 10 mA without MARA is recommended to improve diagnostic performance.

Global cone-beam computed tomography adoption, usage and scan interpretation preferences of dentists and endodontists

AIM

This study investigated the adoption of cone-beam computed tomography (CBCT) by dentists and endodontists around the world, including their preferences in endodontic CBCT usage.

METHODOLOGY

An online questionnaire surveyed dental association members in Australia and New Zealand, and endodontic association members in Australia, Britain, Canada, Italy, New Zealand and the USA, about their CBCT training history, considerations in acquisition/interpretation, access to and usage of CBCT, preferred scan interpreter, and preferred endodontic scan settings. Data were analysed with Chi-squared, independent sample t-tests, Cochran's Q and McNemar's tests.

RESULTS

Responses from 578 endodontic specialists or postgraduates (Group E) and 185 non-endodontic dentists (Group NE) were included. Continuing professional education (CPE) was the most common source of CBCT training (69.2%). Factors considered in CBCT acquisition/interpretation included beam hardening (75.4%), radiation exposure (61.1%) and patient movement (58.3%). Group E reported higher CBCT usage (90.8%) than Group NE (45.4%, p < .001) and greater workplace access to CBCT (81.1% vs. 25.9%, p < .001). Scans were interpreted by the respondent in most workplace scans (83.3%) and externally taken scans (60.5%); Group E were significantly more likely to interpret themselves than Group NE. Small field of view (83.6%) and high resolution (86.6%) were most preferred as settings for endodontic CBCTs; Group NE were less likely to choose these settings. There were some geographic variations within Group E.

CONCLUSIONS

CBCT training was most commonly acquired via CPE. Endodontic respondents reported very high CBCT usage and access in the workplace. There are educational implications regarding CBCT limitations, appropriate applications and interpretation.

Transformer CycleGAN with uncertainty estimation for CBCT based synthetic CT in adaptive radiotherapy

Objective. Clinical implementation of synthetic CT (sCT) from cone-beam CT (CBCT) for adaptive radiotherapy necessitates a high degree of anatomical integrity, Hounsfield unit (HU) accuracy, and image quality. To achieve these goals, a vision-transformer and anatomically sensitive loss functions are described. Better quantification of image quality is achieved using the alignment-invariant Fréchet inception distance (FID), and uncertainty estimation for sCT risk prediction is implemented in a scalable plug-and-play manner.Approach. Baseline U-Net, generative adversarial network (GAN), and CycleGAN models were trained to identify shortcomings in each approach. The proposed CycleGAN-Best model was empirically optimized based on a large ablation study and evaluated using classical image quality metrics, FID, gamma index, and a segmentation analysis. Two uncertainty estimation methods, Monte-Carlo Dropout (MCD) and test-time augmentation (TTA), were introduced to model epistemic and aleatoric uncertainty.Main results. FID was correlated to blind observer image quality scores with a Correlation Coefficient of -0.83, validating the metric as an accurate quantifier of perceived image quality. The FID and mean absolute error (MAE) of CycleGAN-Best was 42.11 ± 5.99 and 25.00 ± 1.97 HU, compared to 63.42 ± 15.45 and 31.80 HU for CycleGAN-Baseline, and 144.32 ± 20.91 and 68.00 ± 5.06 HU for the CBCT, respectively. Gamma 1%/1 mm pass rates were 98.66 ± 0.54% for CycleGAN-Best, compared to 86.72 ± 2.55% for the CBCT. TTA and MCD-based uncertainty maps were well spatially correlated with poor synthesis outputs.Significance. Anatomical accuracy was achieved by suppressing CycleGAN-related artefacts. FID better discriminated image quality, where alignment-based metrics such as MAE erroneously suggest poorer outputs perform better. Uncertainty estimation for sCT was shown to correlate with poor outputs and has clinical relevancy toward model risk assessment and quality assurance. The proposed model and accompanying evaluation and risk assessment tools are necessary additions to achieve clinically robust sCT generation models.

Influence of the metal post material, tooth location in the dental arch, and metal artifact reduction tool on vertical root fracture diagnosis in cone beam CT

This study aimed to evaluate the influence of the metal post composition, tooth location in the dental arch, and metal artifact reduction (MAR) on vertical root fracture (VRF) diagnosis in cone beam computed tomography (CBCT). Twenty-two unirradicular premolars (12 sound and 10 fractured) and two alveolar sockets of a mandible (anterior and posterior regions) composed the sample. CBCT scans of each tooth with a metal post placed into the root canal-silver-palladium (Ag-Pd), cobalt-chromium (Co-Cr), or nickel-chromium (Ni-Cr)-were individually acquired for each mandibular region, and two conditions of MAR, using a OP300 device (Instrumentarium, Finland). Images were assessed by five evaluators independently for VRF detection. Diagnostic values were calculated and compared among all groups using multi-way ANOVA with Tukey post hoc test to investigate the effect of post material, anatomical region, and MAR on VRF diagnosis (α = 0.05). Values of area under the receiver operating curve and specificity were not influenced by the studied factors (p > 0.05). Sensitivity was influenced by the MAR in both mandibular regions (p < 0.05). In the anterior region, sensitivity values increased when the MAR was enabled, regardless of the metal post material (p < 0.05). Similar behavior was noticed in the posterior region for Ni-Cr (p < 0.05) but not for Ag-Pd and Co-Cr posts (p > 0.05). The MAR improved the sensitivity in VRF diagnosis for all tested metal posts in the mandibular anterior region and for the Ni-Cr post in the mandibular posterior region. Therefore, for images obtained in the OP300 CBCT device, activation of the MAR is suggested in these cases.

The role of implants and implant prostheses on the accuracy and artifacts of cone-beam computed tomography: an in-vitro study

To assess the accuracy of CBCT in implant-supported prostheses and to evaluate metal artifacts with and without implants or implant prostheses. Accuracy and artifacts were assessed in the dried mandible at three points on the buccal and lingual cortical plates on the mandible's body near the crest and the base. On the buccal cortical plate, these points were labelled as A, B and C near the crest and D, E and F near the base of the body of the mandible. Similarly, points a to f were marked on the lingual cortical plate corresponding to points A to F. The study had two control groups, C0 for physical linear measurement (PLM) and C1 for radiographic linear measurement (RLM) and artifact assessment. There were seven test groups, TG 1 to 7, progressing from a single implant to implant full-arch prosthesis. For accuracy assessment, PLM was compared to RLM. CBCT artifacts were investigated in images integrated at 0.25 mm, 10 mm, and 20 mm at regions of interest on concentric circles at different intersecting angles by comparing grayscale values at C1 and TG1 to 7. The data were collected and statistically analyzed. A significant difference was observed between C0 and C1, and RLM in test groups at the superior axial plane. Similarly, PLM and test RLM in the sagittal plane at A-B, B-C, and D-E were statistically significant. A significant difference between PLM and RLM was also observed in the vertical plane at A-D, B-E, and C-F. Quantification of CBCT artifacts in the presence of implants or prostheses revealed that full-arch prostheses had the highest mean grayscale value, whereas single implants with a prosthesis had the lowest. The mean grayscale change was greatest around the implant and implant prosthesis. The mean grayscale value was maximum at 20 mm voxel integration scales (VIS) and lowest at 0.25 mm. CBCT is a clinically reliable device. Metal in implants or implant-supported prostheses prevents true assessment of the peri-implant area; therefore, lower VIS is suggested in the presence of implants or implant prostheses.

Visualization of anatomical structures in the fetlock region of the horse using cone beam computed tomography in comparison with conventional multidetector computed tomography

Introduction

Cone-beam computed tomography (CBCT) is regarded as a convenient and suitable alternative to conventional computed tomography. However, in the horse, the quality of obtained data sets needs to be evaluated. Therefore, the aim of this study was to compare the visibility and accessibility of clinically relevant anatomical structures displayed in CBCT and conventional multidetector computed tomography (MDCT).

Materials and methods

Twenty-nine limbs from horses euthanized for reasons unrelated to this study were used. Native and intraarticular contrast scans of the fetlock (CBCT vs. MDCT) were performed. The visibility and accessibility of selected anatomical structures were blindly scored by three independent experienced observers using a scoring system previously reported and adapted to the fetlock joint.

Results

Only minor differences between CBCT and MDCT were identified concerning the diagnostic quality of images for osseous structures. Soft tissue structures were better evaluated on MDCT images. In CBCT as well as in MDCT articular cartilage could only be visualized after intraarticular injection of contrast medium.

Discussion/conclusion

Cone beam computed tomography of the fetlock is a useful and reliable diagnostic tool when evaluating osseous structures and delineating articular cartilage with contrast medium. However, this modality is limited for assessing soft tissues structures.

Mapping artifacts generated in a tooth adjacent to titanium and zirconia implants located in the endomass and exomass in cone beam computed tomography: an ex vivo study

OBJECTIVE

We evaluated artifact expression in a root adjacent to a dental implant located in the endomass or exomass in cone beam computed tomography (CBCT).

STUDY DESIGN

We placed a single titanium or zirconia implant adjacent to a premolar root in a dried human mandible and acquired CBCT scans using an OP300 Maxio and a Picasso Trio 3D unit exposing a 5x5cm field of view with the implant in the endomass or exomass (implant groups) or without an implant (control group). We measured the mean gray values (MGVs) for 8 lines of interest (LOIs) around the root canal of the premolar and compared the MGVs by analysis of variance, with significance established at P < 0.05.

RESULTS

For the OP300 Maxio scans, the MGVs of both implant groups in the endomass were lower than the MGVs of the control group. In the exomass, the titanium group had MGVs similar to the control group, but the zirconia group produced significantly lower MGVs than control and titanium groups (P <.0001), indicating the presence of hypodense artifacts. For the Picasso Trio 3D scans, the MGVs of both implant groups in the endomass were similar to the MGVs of the control group. In the exomass, the zirconia group generated lower MGVs than control and titanium groups (P <.0001), indicating hypodense artifacts.

CONCLUSIONS

When performing CBCT examination, titanium implants produce less artifact expression in the exomass, and zirconia implants have less artifact expression in the endomass.

Osseointegration and osteoimmunology in implantology: assessment of the immune sustainability of dental implants using advanced sonographic diagnostics: research and case reports

OBJECTIVE

Bone marrow defects of the jaw (BMDJ) surrounding dental implants, in combination with impaired bone-to-implant contact (BIC), are difficult to detect in X-rays. This study evaluated BMDJ surrounding titanium (Ti-Impl) and ceramic (Cer-Impl) dental implants and incomplete BIC using a new trans-alveolar ultrasonography device (TAU) with numerical scaling for BIC.

METHODS

The titanium stimulation test (Ti-Stim) was used to detect immune overactivation in response to titanium. Bone density surrounding implants was measured using TAU. We also validated osteoimmune dysregulation.

RESULTS

TAU values showed reduced BIC and decreased osseointegration for Ti-Impl. Moreover, TAU values in the Cer-Impl group were more than twice those in the Ti-Impl cohort. The multiplex analysis of C-C motif chemokine 5 (CCL5, also known as RANTES) expression revealed a 20-fold increase in BMDJ surrounding Ti-Impl. Higher levels of CCL5 inflammation were present in the positive Ti-Stim group.

CONCLUSIONS

Our data indicate that Cer-Impl have an osteoimmune advantage over Ti-Impl. The key determinant for osteoimmune sustainability appears to be the absence of inflammation at the implant site. We therefore recommend the use of TAU to assess the implant site prior to implantation.

Repetition Rate of Scanning Due to Motion Artefacts in Cone-Beam Computed Tomography: a Retrospective Study

Objectives

The objective of this retrospective study was to investigate the incidence of repeated cone-beam computed tomography scans due to motion artefacts in a Turkish subpopulation.

Material and Methods

A total of 6364 patients' cone-beam computed tomography data were analysed retrospectively to identify repeated scans due to motion artefacts. Patients were divided into eight age groups: 1) < 10-year-olds, 2) 10 to 19-year-olds, 3) 20 to 29-year-olds, 4) 30 to 39-year-olds, 5) 40 to 49-year-olds, 6) 50 to 59-year-olds, 7) 60 to 69-year-olds, and 8) > 70 year-olds. Chi-square test was applied to evaluate the repetition rate of scans by age and gender groups. Statistical significance was set at P < 0.05.

Results

Repeated scans due to motion artefacts were observed in 1.96% of the patients. The repetition rate of scans was significantly higher in males than in females (P = 0.006). Furthermore, the repetition rate of scans was significantly higher in patients < 10 years old compared to the other age groups. However, there was no significant difference in the repetition rate of scans due to motion artefacts among the other age groups (P > 0.05).

Conclusions

The present findings suggest that patient age and gender are associated with repeated cone-beam computed tomography scans due to motion artefacts. Males and children under the age of 10 had more common repeated scans due to motion artefacts.

Connecting the dots towards precision orthodontics

Precision orthodontics entails the use of personalized clinical, biological, social and environmental knowledge of each patient for deep individualized clinical phenotyping and diagnosis combined with the delivery of care using advanced customized devices, technologies and biologics. From its historical origins as a mechanotherapy and materials driven profession, the most recent advances in orthodontics in the past three decades have been propelled by technological innovations including volumetric and surface 3D imaging and printing, advances in software that facilitate the derivation of diagnostic details, enhanced personalization of treatment plans and fabrication of custom appliances. Still, the use of these diagnostic and therapeutic technologies is largely phenotype driven, focusing mainly on facial/skeletal morphology and tooth positions. Future advances in orthodontics will involve comprehensive understanding of an individual's biology through omics, a field of biology that involves large-scale rapid analyses of DNA, mRNA, proteins and other biological regulators from a cell, tissue or organism. Such understanding will define individual biological attributes that will impact diagnosis, treatment decisions, risk assessment and prognostics of therapy. Equally important are the advances in artificial intelligence (AI) and machine learning, and its applications in orthodontics. AI is already being used to perform validation of approaches for diagnostic purposes such as landmark identification, cephalometric tracings, diagnosis of pathologies and facial phenotyping from radiographs and/or photographs. Other areas for future discoveries and utilization of AI will include clinical decision support, precision orthodontics, payer decisions and risk prediction. The synergies between deep 3D phenotyping and advances in materials, omics and AI will propel the technological and omics era towards achieving the goal of delivering optimized and predictable precision orthodontics.

Technical note: Evaluation of deep learning based synthetic CTs clinical readiness for dose and NTCP driven head and neck adaptive proton therapy

BACKGROUND

Adaptive proton therapy workflows rely on accurate imaging throughout the treatment course. Our centre currently utilizes weekly repeat CTs (rCTs) for treatment monitoring and plan adaptations. However, deep learning-based methods have recently shown to successfully correct CBCT images, which suffer from severe imaging artifacts, and generate high quality synthetic CT (sCT) images which enable CBCT-based proton dose calculations.

PURPOSE

To compare daily CBCT-based sCT images to planning CTs (pCT) and rCTs of head and neck (HN) cancer patients to investigate the dosimetric accuracy of CBCT-based sCTs in a scenario mimicking actual clinical practice.

METHODS

Data of 56 HN cancer patients, previously treated with proton therapy was used to generate 1.962 sCT images, using a previously developed and trained deep convolutional neural network. Clinical IMPT treatment plans were recalculated on the pCT, weekly rCTs and daily sCTs. The dosimetric accuracy of sCTs was compared to same day rCTs and the initial planning CT. As a reference, rCTs were also compared to pCTs. The dose difference between sCTs and rCTs/pCT was quantified by calculating the D98 difference for target volumes and Dmean difference for organs-at-risk. To investigate the clinical relevancy of possible dose differences, NTCP values were calculated for dysphagia and xerostomia.

RESULTS

For target volumes, only minor dose differences were found for sCT versus rCT and sCT versus pCT, with dose differences mostly within ±1.5%. Larger dose differences were observed in OARs, where a general shift towards positive differences was found, with the largest difference in the left parotid gland. Delta NTCP values for grade 2 dysphagia and xerostomia were within ±2.5% for 90% of the sCTs.

CONCLUSIONS

Target doses showed high similarity between rCTs and sCTs. Further investigations are required to identify the origin of the dose differences at OAR levels and its relevance in clinical decision making.

Accuracy of facial skeletal surfaces segmented from CT and CBCT radiographs

The accuracy of three-dimensional (3D) facial skeletal surface models derived from radiographic volumes has not been extensively investigated yet. For this, ten human dry skulls were scanned with two Cone Beam Computed Tomography (CBCT) units, a CT unit, and a highly accurate optical surface scanner that provided the true reference models. Water-filled head shells were used for soft tissue simulation during radiographic imaging. The 3D surface models that were repeatedly segmented from the radiographic volumes through a single-threshold approach were used for reproducibility testing. Additionally, they were compared to the true reference model for trueness measurement. Comparisons were performed through 3D surface approximation techniques, using an iterative closest point algorithm. Differences between surface models were assessed through the calculation of mean absolute distances (MAD) between corresponding surfaces and through visual inspection of facial surface colour-coded distance maps. There was very high reproducibility (approximately 0.07 mm) and trueness (0.12 mm on average, with deviations extending locally to 0.5 mm), and no difference between radiographic scanners or settings. The present findings establish the validity of lower radiation CBCT imaging protocols at a similar level to the conventional CT images, when 3D surface models are required for the assessment of facial morphology.

CBCT-to-CT Synthesis for Cervical Cancer Adaptive Radiotherapy via U-Net-Based Model Hierarchically Trained with Hybrid Dataset

PURPOSE

To develop a deep learning framework based on a hybrid dataset to enhance the quality of CBCT images and obtain accurate HU values.

MATERIALS AND METHODS

A total of 228 cervical cancer patients treated in different LINACs were enrolled. We developed an encoder-decoder architecture with residual learning and skip connections. The model was hierarchically trained and validated on 5279 paired CBCT/planning CT images and tested on 1302 paired images. The mean absolute error (MAE), peak signal to noise ratio (PSNR), and structural similarity index (SSIM) were utilized to access the quality of the synthetic CT images generated by our model.

RESULTS

The MAE between synthetic CT images generated by our model and planning CT was 10.93 HU, compared to 50.02 HU for the CBCT images. The PSNR increased from 27.79 dB to 33.91 dB, and the SSIM increased from 0.76 to 0.90. Compared with synthetic CT images generated by the convolution neural networks with residual blocks, our model had superior performance both in qualitative and quantitative aspects.

CONCLUSIONS

Our model could synthesize CT images with enhanced image quality and accurate HU values. The synthetic CT images preserved the edges of tissues well, which is important for downstream tasks in adaptive radiotherapy.

Evaluation of a Decision Support System Developed with Deep Learning Approach for Detecting Dental Caries with Cone-Beam Computed Tomography Imaging

This study aims to investigate the effect of using an artificial intelligence (AI) system (Diagnocat, Inc., San Francisco, CA, USA) for caries detection by comparing cone-beam computed tomography (CBCT) evaluation results with and without the software. 500 CBCT volumes are scored by three dentomaxillofacial radiologists for the presence of caries separately on a five-point confidence scale without and with the aid of the AI system. After visual evaluation, the deep convolutional neural network (CNN) model generated a radiological report and observers scored again using AI interface. The ground truth was determined by a hybrid approach. Intra- and inter-observer agreements are evaluated with sensitivity, specificity, accuracy, and kappa statistics. A total of 6008 surfaces are determined as 'presence of caries' and 13,928 surfaces are determined as 'absence of caries' for ground truth. The area under the ROC curve of observer 1, 2, and 3 are found to be 0.855/0.920, 0.863/0.917, and 0.747/0.903, respectively (unaided/aided). Fleiss Kappa coefficients are changed from 0.325 to 0.468, and the best accuracy (0.939) is achieved with the aided results. The radiographic evaluations performed with aid of the AI system are found to be more compatible and accurate than unaided evaluations in the detection of dental caries with CBCT images.

Assessment of the root filling volume in C-shaped root canal on cone-beam CT and micro-CT in relation to nano-CT

AIM

To assess the observed volume of filled C-shaped root canals from different CBCT and micro-CT having nano-CT as a reference.

MATERIALS AND METHODS

Twelve extracted mandibular molars with C-shaped root canals were endodontically treated using Reciproc Blue R25 (VDW GMBH, Munich, Germany) in a reciprocating system and filled with gutta-percha (Dentsply Maillefer) and AH Plus sealer (Dentsply DeTrey, Konstanz, Germany). CBCT scans were performed using 3 units-3D Accuitomo 170 (J. Morita, Kyoto, Japan), ProMax 3D Max (Planmeca, Helsinki, Finland), and NewTom VGi EVO (Cefla QR, Verona, Italy)-at two resolution modes: standard and high. Micro-CT and nano-CT scans were also obtained. The volume of all filled C-shaped root canals was obtained using CTAn software (Bruker, Kontich, Belgium), and the blooming artifact, in relation to nano-CT volume, was calculated. The data were evaluated by the Bland-Altman plots and ANOVA two-way for repeated measures (α = 0.05).

RESULTS

All CBCT units and micro-CT showed significantly larger observed volume of root canal filling when compared to nano-CT. The blooming artifact of root canal filling in standard resolution was significantly larger than that in high resolution (p < 0.05) in all CBCT units.

CONCLUSIONS

Endodontic filling material with AH Plus sealer causes blooming artifacts in CBCT units and micro-CT.

CLINICAL RELEVANCE

Considering the anatomical complexity of C-shaped root canals and the challenges associated with endodontic treatment, CBCT is frequently recommended for follow-up evaluations. However, the presence of endodontic filling material can result in blooming artifacts that may potentially impact the accurate diagnosis of endodontic complications.

Does cone-beam CT convex triangular field of view influence the image shape distortion of high-density materials?

OBJECTIVES

To assess the distortion of high-density materials using two CBCT devices presenting convex triangular and cylindrical fields of view (FOVs).

METHODS AND MATERIALS

Four high-density cylinders were individually placed in a polymethylmethacrylate phantom. 192 CBCT scans were acquired using the convex triangular and cylindrical FOVs of Veraviewepocs® R100 (R100) and Veraview® X800 (X800) devices. Using HorosTM's software, two oral radiologists determined the cylinders' horizontal and vertical dimensional alterations. Nine oral radiologists subjectively identified each cylinder's axial shape distortion. Statistical analysis comprised Multiway ANOVA (α = 5%), and the Kruskal-Wallis test.

RESULTS

The distortion in the axial plane was greater in the convex triangular FOVs for both devices in almost all the materials (p < 0.05). The evaluators subjectively identified a shape distortion in both FOVs for R100 device (p < 0.001), while no distortion was identified for X800 device (p = 0.620). A vertical magnification of all materials was observed in both FOVs for both devices (p < 0.05). No differences among vertical regions (p = 0.988) nor FOVs (p = 0.544) were found for the R100 device, while all materials showed higher magnification in all regions in the cylindrical FOV (p < 0.001) of the X800 device.

CONCLUSIONS

The convex triangular FOV influenced the axial distortion of the high-density materials in both devices. A vertical magnification was observed in both FOVs of both devices, but it was greater in the cylindrical FOV of the X800 device.

Comparison and evaluation of different deep learning models of synthetic CT generation from CBCT for nasopharynx cancer adaptive proton therapy

BACKGROUND

Cone-beam computed tomography (CBCT) scanning is used for patient setup in image-guided radiotherapy. However, its inaccurate CT numbers limit its applicability in dose calculation and treatment planning.

PURPOSE

This study compares four deep learning methods for generating synthetic CT (sCT) to determine which method is more appropriate and offers potential for further clinical exploration in adaptive proton therapy for nasopharynx cancer.

METHODS

CBCTs and deformed planning CT (dCT) from 75 patients (60/5/10 for training, validation and testing) were used to compare cycle-consistent Generative Adversarial Network (cycleGAN), Unet, Unet+cycleGAN and conditionalGenerative Adversarial Network (cGAN) for sCT generation. The sCT images generated by each method were evaluated against dCT images using mean absolute error (MAE), structural similarity (SSIM), peak signal-to-noise ratio (PSNR), spatial non-uniformity (SNU) and radial averaging in the frequency domain. In addition, dosimetric accuracy was assessed through gamma analysis, differences in water equivalent thickness (WET), and dose-volume histogram metrics.

RESULTS

The cGAN model has demonstrated optimal performance in the four models across various indicators. In terms of image quality under global condition, the average MAE has been reduced to 16.39HU, SSIM has increased to 95.24%, and PSNR has increased to 28.98. Regarding dosimetric accuracy, the gamma passing rate (2%/2 mm) has reached 99.02%, and the WET difference is only 1.28 mm. The D95 value of CTVs coverage and Dmax value of spinal cord, brainstem show no significant differences between dCT and sCT generated by cGAN model.

CONCLUSIONS

The cGAN model has been shown to be a more suitable approach for generating sCT using CBCT, considering its characteristics and concepts. The resulting sCT has the potential for application in adaptive proton therapy.

Sparse-view synchrotron X-ray tomographic reconstruction with learning-based sinogram synthesis

Synchrotron radiation can be used as a light source in X-ray microscopy to acquire a high-resolution image of a microscale object for tomography. However, numerous projections must be captured for a high-quality tomographic image to be reconstructed; thus, image acquisition is time consuming. Such dense imaging is not only expensive and time consuming but also results in the target receiving a large dose of radiation. To resolve these problems, sparse acquisition techniques have been proposed; however, the generated images often have many artefacts and are noisy. In this study, a deep-learning-based approach is proposed for the tomographic reconstruction of sparse-view projections that are acquired with a synchrotron light source; this approach proceeds as follows. A convolutional neural network (CNN) is used to first interpolate sparse X-ray projections and then synthesize a sufficiently large set of images to produce a sinogram. After the sinogram is constructed, a second CNN is used for error correction. In experiments, this method successfully produced high-quality tomography images from sparse-view projections for two data sets comprising Drosophila and mouse tomography images. However, the initial results for the smaller mouse data set were poor; therefore, transfer learning was used to apply the Drosophila model to the mouse data set, greatly improving the quality of the reconstructed sinogram. The method could be used to achieve high-quality tomography while reducing the radiation dose to imaging subjects and the imaging time and cost.