Segmentation process significantly influences the accuracy of 3D surface models derived from cone beam computed tomography

Horizontal ridge augmentation in the maxillary aesthetic region using the autogenous circular cortical-lamina anchoring technique: A case series study

AIM

This case series aimed to evaluate the effectiveness of the autologous circular cortical lamina-anchoring (CCA) technique for horizontal bone augmentation in the maxillary aesthetic region.

MATERIALS AND METHODS

A total of 25 patients with 28 implants underwent horizontal bone augmentation using CCA followed by implant placement and crown delivery. The primary outcome measures were alveolar ridge width (ARW) and buccal bone thickness (BBT), whereas the secondary outcome measures included marginal bone loss (MBL), mid-facial mucosal margin loss (MML), clinical assessment of peri-implant and aesthetic parameters, patient-reported outcome measures (PROMs), and implant survival rates.

RESULTS

All 25 patients with 28 implants completed the treatment, no dropouts occurred. After CCA, the mean ARW at 1, 2, and 4 mm below the alveolar crest significantly increased from 2.38 ± 0.48, 2.85 ± 0.51, and 3.21 ± 0.53 mm to 6.80 ± 0.48, 6.99 ± 0.50, and 8.08 ± 0.52 mm, respectively. At the 3-year follow-up, the mean BBT0 , BBT2 , and BBT4 slightly decreased from 2.51 ± 0.26, 2.63 ± 0.31, and 2.75 ± 0.29 mm to 2.43 ± 0.27, 2.51 ± 0.30, and 2.64 ± 0.28 mm, respectively. Although the overall MBL was <0.15 mm, the results were statistically significant. The mean MML at the 3-year follow-up was 0.02 mm. All implant sites showed acceptable peri-implant and aesthetic outcomes. Incisions healed without complications, and no significant differences in PROMs observed at any time point. The 3-year follow-up showed a 100% implant survival rate.

CONCLUSION

The autologous CCA technique is a useful method for increasing ARW and maintaining BBT in the maxillary aesthetic region.

Three-dimensional evaluation of a virtual setup considering the roots and alveolar bone in molar distalization cases

We aimed to evaluate root parallelism and the dehiscence or fenestrations of virtual teeth setup using roots isolated from cone beam computed tomography (CBCT) images. Sixteen patients undergoing non-extraction orthodontic treatment with molar distalization were selected. Composite teeth were created by merging CBCT-isolated roots with intraoral scan-derived crowns. Three setups were performed sequentially: crown setup considering only the crowns, root setup-1 considering root alignment, and root setup-2 considering the roots and surrounding alveolar bone. We evaluated the parallelism and exposure of the roots and compared the American Board of Orthodontics Objective Grading System (ABO-OGS) scores using three-dimensionally printed models among the setups. The mean angulation differences between adjacent teeth in root setups-1 and -2 were significantly smaller than in the crown setup, except for some posterior teeth (p < 0.05). The amount of root exposure was significantly smaller in root setup-2 compared to crown setup and root setup-1 except when the mean exposure was less than 0.6 mm (p < 0.05). There was no significant difference in ABO-OGS scores among the setups. Thus, virtual setup considering the roots and alveolar bone can improve root parallelism and reduce the risk of root exposure without compromising occlusion quality.

The impact of teeth and dental restorations on gray value distribution in cone-beam computer tomography: a pilot study

PURPOSE

To investigate the influence of teeth and dental restorations on the facial skeleton's gray value distributions in cone-beam computed tomography (CBCT).

METHODS

Gray value selection for the upper and lower jaw segmentation was performed in 40 patients. In total, CBCT data of 20 maxillae and 20 mandibles, ten partial edentulous and ten fully edentulous in each jaw, respectively, were evaluated using two different gray value selection procedures: manual lower threshold selection and automated lower threshold selection. Two sample t tests, linear regression models, linear mixed models, and Pearson's correlation coefficients were computed to evaluate the influence of teeth, dental restorations, and threshold selection procedures on gray value distributions.

RESULTS

Manual threshold selection resulted in significantly different gray values in the fully and partially edentulous mandible. (p = 0.015, difference 123). In automated threshold selection, only tendencies to different gray values in fully edentulous compared to partially edentulous jaws were observed (difference: 58-75). Significantly different gray values were evaluated for threshold selection approaches, independent of the dental situation of the analyzed jaw. No significant correlation between the number of teeth and gray values was assessed, but a trend towards higher gray values in patients with more teeth was noted.

CONCLUSIONS

Standard gray values derived from CT imaging do not apply for threshold-based bone segmentation in CBCT. Teeth influence gray values and segmentation results. Inaccurate bone segmentation may result in ill-fitting surgical guides produced on CBCT data and misinterpreting bone density, which is crucial for selecting surgical protocols. Created with BioRender.com.

Quantitative and qualitative comparisons of pulp cavity volumes produced by cone beam computed tomography and micro-computed tomography through semiautomatic segmentation: An ex vivo investigation

OBJECTIVE

The aim of this study was to measure the volume and visually assess 3-dimensional (3D) virtual models of pulp cavities obtained through semiautomatic segmentation on images from 6 cone beam computed tomography (CBCT) units compared with the reference standard of micro-CT.

STUDY DESIGN

Fifteen mandibular premolar teeth were scanned with 6 CBCT units: Prexion 3D Elite, i-CAT Next Generation, NewTom 5G, Cranex 3D, 3Shape X1, and Orthophos SL 3D, using the smallest available field of view and highest resolution settings. Pulp cavity volumes were quantitatively assessed by 2 calibrated examiners. The volumes from each CBCT unit were compared with micro-CT. Qualitative assessment of the 3D reconstructions was also performed. Repeated-measures analysis of variance and the Friedman test compared the CBCT reconstructions to micro-CT. Intra- and interexaminer agreements were calculated with the intraclass correlation coefficient and kappa statistic.

RESULTS

The CBCT-based volumes were all significantly larger than micro-CT (P ≤ .0061). Prexion, X1, and Orthophos provided the segmentations that most closely resembled the reference standard. Intra- and interexaminer agreements ranged from good to excellent for quantitative measurements. Interexaminer agreement for qualitative evaluation was substantial.

CONCLUSIONS

Semiautomatic segmentation of CBCT images is a feasible method to produce virtual 3D models of the pulp cavity. Prexion, X1, and Orthophos were the CBCT units that resulted in 3D reconstructions most similar to the reference standard.

Effect of the Segmentation Threshold on Computed Tomography-Based Reconstruction of Skull Bones with Reference Optical Three-Dimensional Scanning

BACKGROUND

A variety of applications related to neurosurgical procedures, education, and training require accurate reconstruction of the involved structures from the medical images such as computed tomography (CT). This study evaluates the quality of CT-based reconstruction of dry skull bones for advanced neurosurgical applications. The accuracy and precision of these models were examined with reference optical scanning.

METHODS

Three consecutive CT and optical scans of different skull bones were acquired and used to develop three-dimensional models. The accuracy of three-dimensional models was examined by manual inspection of the defined anatomical landmarks of the skull. Reproducibility was examined by deviation analysis of the models developed from repeated CT and optical scans.

RESULTS

Precision was excellent in both the techniques with less than 0.1 mm deviation error. On the interscan evaluation of the CT versus optical scan model, deviations of more than 0.1 mm were observed in 16 out of 21 instances. CT reconstruction using standard segmentation algorithms results in missing bone portions while using the default bone segmentation threshold. The segmentation threshold was varied to construct missing bone regions, and its effect on the iso-surface generation was evaluated. The threshold variation led to increased mean deviations of surfaces up to 0.6 mm.

CONCLUSIONS

The study reveals that bone structure, complexity, and segmentation threshold lead to CT reconstruction variability. The trade-off between the desirable model and accepted mean deviation should be considered as per traits of the desired application.

Comparability of skeletal fibulae surfaces generated by different source scanning (dual-energy CT scan vs. high resolution laser scanning) and 3D geometric morphometric validation

This work aims to test accuracy and comparability of 3D models of human skeletal fibulae generated by clinical CT and laser scanner virtual acquisitions. Mesh topology, segmentation and smoothing protocols were tested to assess variation among meshes generated with different scanning methods and procedures, and to evaluate meshes‐interchangeability in 3D geometric morphometric analysis. A sample of 13 left human fibulae were scanned separately with Revolution Discovery CT dual energy (0.625 mm resolution) and ARTEC Space Spider 3D structured light laser scanner (0.1 mm resolution). Different segmentation methods, including half‐maximum height (HMH) and MIA‐clustering protocols, were compared to their high‐resolution standard generated with laser‐scanner by calculating topological surface deviations. Different smoothing algorithms were also evaluated, such as Laplacian and Taubin smoothing. A total of 142 semilandmarks were used to capture the shape of both proximal and distal fibular epiphyses. After Generalized Procrustes superimposition, the Procrustes coordinates of the proximal and distal fibular epiphyses were used separately to assess variation due to scanning methods and the operator error. Smoothing algorithms at low iteration do not provide significant variation among reconstructions, but segmentation protocol may influence final mesh quality (0.09–0.24 mm). Mean deviation among CT‐generated meshes that were segmented with MIA‐clustering protocol, and laser scanner‐generated ones, is optimal (0.42 mm, ranging 0.35–0.56 mm). Principal component analysis reveals that homologous samples scanned with the two methods cluster together for both the proximal and distal fibular epiphyses. Similarly, Procrustes ANOVA reveals no shape differences between scanning methods and replicates, and only 1.38–1.43% of shape variation is due to scanning device. Topological similarities support the comparability of CT‐ and laser scanner‐generated meshes and validate its simultaneous use in shape analysis with potential clinical relevance. We precautionarily suggest that dedicated trials should be performed in each study when merging different data sources prior to analyses.

Algorithms used in medical image segmentation for 3D printing and how to understand and quantify their performance

BACKGROUND

3D printing (3DP) has enabled medical professionals to create patient-specific medical devices to assist in surgical planning. Anatomical models can be generated from patient scans using a wide array of software, but there are limited studies on the geometric variance that is introduced during the digital conversion of images to models. The final accuracy of the 3D printed model is a function of manufacturing hardware quality control and the variability introduced during the multiple digital steps that convert patient scans to a printable format. This study provides a brief summary of common algorithms used for segmentation and refinement. Parameters for each that can introduce geometric variability are also identified. Several metrics for measuring variability between models and validating processes are explored and assessed.

METHODS

Using a clinical maxillofacial CT scan of a patient with a tumor of the mandible, four segmentation and refinement workflows were processed using four software packages. Differences in segmentation were calculated using several techniques including volumetric, surface, linear, global, and local measurements.

RESULTS

Visual inspection of print-ready models showed distinct differences in the thickness of the medial wall of the mandible adjacent to the tumor. Volumetric intersections and heatmaps provided useful local metrics of mismatch or variance between models made by different workflows. They also allowed calculations of aggregate percentage agreement and disagreement which provided a global benchmark metric. For the relevant regions of interest (ROIs), statistically significant differences were found in the volume and surface area comparisons for the final mandible and tumor models, as well as between measurements of the nerve central path. As with all clinical use cases, statistically significant results must be weighed against the clinical significance of any deviations found.

CONCLUSIONS

Statistically significant geometric variations from differences in segmentation and refinement algorithms can be introduced into patient-specific models. No single metric was able to capture the true accuracy of the final models. However, a combination of global and local measurements provided an understanding of important geometric variations. The clinical implications of each geometric variation is different for each anatomical location and should be evaluated on a case-by-case basis by clinicians familiar with the process. Understanding the basic segmentation and refinement functions of software is essential for sites to create a baseline from which to evaluate their standard workflows, user training, and inter-user variability when using patient-specific models for clinical interventions or decisions.

Comparison of Bone Segmentation Software over Different Anatomical Parts

Three-dimensional bone shape reconstruction is a fundamental step for any subject-specific musculo-skeletal model. Typically, medical images are processed to reconstruct bone surfaces via slice-by-slice contour identification. Freeware software packages are available, but commercial ones must be used for the necessary certification in clinics. The commercial software packages also imply expensive hardware and demanding training, but offer valuable tools. The aim of the present work is to report the performance of five commercial software packages (Mimics®, AmiraTM, D2PTM, SimplewareTM, and Segment 3D PrintTM), particularly the time to import and to create the model, the number of triangles of the mesh, and the STL file size. DICOM files of three different computed tomography scans from five different human anatomical areas were utilized for bone shape reconstruction by using each of these packages. The same operator and the same hosting hardware were used for these analyses. The computational time was found to be different between the packages analyzed, probably because of the pre-processing implied in this operation. The longer “time-to-import” observed in one software is likely due to the volume rendering during uploading. A similar number of triangles per megabyte (approximately 20 thousand) was observed for the five commercial packages. The present work showed the good performance of these software packages, with the main features being better than those analyzed previously in freeware packages.

Marginal fit of 3-unit CAD-CAM zirconia frameworks fabricated using cone beam computed tomography scans: an experimental study

Whether cone beam computed tomography (CBCT) scans can be used for the fabrication of computer-aided design and computer-aided manufacturing (CAD-CAM) fixed dental prostheses (FDPs) is not known. The purpose of the present study was to compare the marginal fit of 3-unit zirconia FDPs fabricated by using CBCT or 3-dimensional (3D) laboratory scanning. Extracted second premolar and molar teeth in a maxillary typodont model were prepared. The first molar was removed and the typodont model was scanned with a laboratory or a CBCT scanner to generate two virtual 3D cast groups (3DL and CBCT). Forty four 3-unit zirconia FDPs were designed on virtual casts and milled. The vertical marginal discrepancy (VMD) was measured by ×100-magnification microscopy at seven locations on each abutment. A total of 616 measurements were made at 14 fixed locations in two groups of 22 specimens. The VMD data for 3DL and CBCT groups were statistically analyzed using the Mann-Whitney U test (α = 0.05). The mean VMDs on premolar ranged between 44 and 55 µm (median: 43-55 µm) in 3DL, and 74 and 100 µm (median: 72-93 µm) in CBCT; and on the molar, between 47 and 114 µm (median: 46-114 µm) in 3DL, and 91 and 162 µm (median: 93-156 µm) in CBCT. There was a significant difference between the gaps in 3DL and CBCT groups (p < 0.001). FDPs fabricated using 3D laboratory scanner had significantly smaller VMDs. Nevertheless, the 3-unit zirconia FDPs fabricated using CBCT scans presented promising marginal integrity.

Fully automatic segmentation of the mandible based on convolutional neural networks (CNNs)

OBJECTIVES

To evaluate the accuracy of automatic deep learning-based method for fully automatic segmentation of the mandible from CBCTs.

SETTING AND SAMPLE POPULATION

CBCT-derived mandible fully automatic segmentation.

METHODS

Forty CBCT scans from healthy patients (20 females and 20 males, mean age 23.37 ± 3.34) were collected, and a manual mandible segmentation was carried out by using Mimics software. Twenty CBCT scans were randomly selected and used for training the artificial intelligence model file. The remaining 20 CBCT segmentation masks were used to test the accuracy of the CNN automatic method by comparing the segmentation volumes of the 3D models obtained with automatic and manual segmentations. The accuracy of the CNN-based method was also assessed by using the DICE Score coefficient (DSC) and by the surface-to-surface matching technique. The intraclass correlation coefficient (ICC) and Dahlberg's formula were used respectively to test the intra-observer reliability and method error. Independent Student's t test was used for between-groups volumetric comparison.

RESULTS

Measurements were highly correlated with an ICC value of 0.937, while the method error was 0.24 mm³ . A difference of 0.71 (±0.49) cm³ was found between the methodologies, but it was not statistically significant (P > .05). The matching percentage detected was 90.35% (±1.88) (tolerance 0.5 mm) and 96.32% ± 1.97% (tolerance 1.0 mm). The differences, measured as DSC in percentage, between the assessments done with both methods were, respectively, 2.8% and 3.1%.

CONCLUSION

The tested deep learning CNN-based technology is accurate and performs as well as an experienced image reader but at much higher speed, which is of significant clinical relevance.

Angular and linear measurements of adult flexible flatfoot via weight-bearing CT scans and 3D bone reconstruction tools

Acquired adult flatfoot is a frequent deformity which implies multiple, complex and combined 3D modifications of the foot skeletal structure. The difficult thorough evaluation of the degree of severity pre-op and the corresponding assessment post-op can now be overcome by cone-beam (CBCT) technology, which can provide access to the 3D skeletal structure in weight-bearing. This study aims to report flatfoot deformities originally in 3D and in weight-bearing, with measurements taken using two different bone segmentation techniques. 21 such patients, with indication for surgical corrections, underwent CBCT (Carestream, US) while standing on one leg. From these scans, 3D models of each bone of the foot were reconstructed by using two different state-of-the-art segmentation tools: a semi-automatic (Mimics Innovation Suite, Materialise, Belgium), and an automatic (Bonelogic Ortho Foot and Ankle, Disior, Finland). From both reconstructed models, Principal Component Analysis was used to define anatomical reference frames, and original foot and ankle angles and other parameters were calculated mostly based on the longitudinal axis of the bones, in anatomical plane projections and in 3D. Both bone model reconstructions revealed a considerable valgus of the calcareous, plantarflexion and internal rotation of the talus, and typical Meary’s angles in the lateral and transverse plane projections. The mean difference from these angles between semi-automatic and automatic segmentations was larger than 3.5 degrees for only 3 of the 32 measurements, and a large number of these differences were not statistically significant. CBCT and the present techniques for bone shape reconstruction finally provide a novel and valuable 3D assessment of complex foot deformities in weight-bearing, eliminating previous limitations associated to unloaded feet and bidimensional measures. Corresponding measurements on the bone models from the two segmentation tools compared well. Other more representative measurements can be defined in the future using CBCT and these techniques.

The question about the numerical value and quantitative data transfer of implant prosthodontics-orom experience guidance to digital guidance

The correct implant site design and placement are the basic clinical techniques that must be known for implant restoration. For a long time, most implants have been placed by free hands, and the choice of site is mostly dependent on the accumulation of long-term experience of the surgeon. The selection of implant site guided by this experience analogy logic is often based on the surgeon's level of experience,which often makes it very easy to produce complications related to the implant restoration of the incorrect site. In contrast, a clinical program using digital guidance and real-time measurable verification has emerged based on the restoration-oriented implantation concept, which marks the formation of an accurate, measurable and verifiable whole-process digital implant prototype. Furthermore, from the perspective of surveying, the numerical requirements that digital implant restoration relies on are actually incomplete to the four elements of measurement, which leading to the doubts about its authenticity. This article will question the numbers in implant restoration, and conduct a preliminary demonstration, and propose a new reliable actual measurement and verification method of the correct location and the numerical requirements of the restoration space and a new clinical program that relies on numbers from the perspective of the evolution of digital restoration, guided implantology and actual measurement technology. And this article further discusses the current mainstream implant restoration technology based on experience analogy which cannot effectively support the whole process of digital implant restoration and provides a new logical cognitive basis for the final realization of the entire process of digital implant restoration.

Geometric accuracy of magnetic resonance imaging-derived virtual 3-dimensional bone surface models of the mandible in comparison to computed tomography and cone beam computed tomography: A porcine cadaver study

BACKGROUND

Providing accurate 3-dimensional virtual bone surface models is a prerequisite for virtual surgical planning and additive manufacturing in craniomaxillofacial surgery. For this purpose, magnetic resonance imaging (MRI) may be a radiation-free alternative to computed tomography (CT) and cone beam computed tomography (CBCT).

PURPOSE

The aim of this study was to assess the geometric accuracy of 3-dimensional T1-weighted MRI-derived virtual bone surface models of the mandible in comparison to CT and CBCT.

MATERIALS AND METHODS

Specimens of the mandible from porcine cadavers were scanned with (1) a 3-dimensional T1-weighted MRI sequence (0.6 mm isotropic voxel) optimized for bone imaging, (2) CT, and (3) CBCT. Cortical mandibular structures (n = 10) were segmented using semiautomated and manual techniques. Imaging-based virtual 3-dimensional models were aligned with a high-resolution optical 3-dimensional surface scan of the dissected bone (=ground truth) and global geometric deviations were calculated (mean surface distance [MSD]/root-mean-square distance [RMSD]). Agreement between the imaging modalities was assessed by equivalence testing and Bland-Altman analysis.

RESULTS

Intra- and inter-rater agreement was on a high level for all modalities. Global geometric deviations (MSD/RMSD) between optical scans and imaging modalities were 0.225 ± 0.020 mm/0.345 ± 0.074 mm for CT, 0.280 ± 0.067 mm/0.371 ± 0.074 mm for MRI, and 0.352 ± 0.076 mm/0.454 ± 0.071 mm for CBCT. All imaging modalities were statistically equivalent within an equivalence margin of ±0.3 mm, and Bland-Altman analysis indicated high agreement as well.

CONCLUSIONS

The results of this study indicate that the accuracy and reliability of MRI-derived virtual 3-dimensional bone surface models is equal to CT and CBCT. MRI may be considered as a reliable alternative to CT and CBCT in computer-assisted craniomaxillofacial surgery.

Automated cortical thickness measurement of the mandibular condyle head on CBCT images using a deep learning method

This study proposes a deep learning model for cortical bone segmentation in the mandibular condyle head using cone-beam computed tomography (CBCT) and an automated method for measuring cortical thickness with a color display based on the segmentation results. In total, 12,800 CBCT images from 25 normal subjects, manually labeled by an oral radiologist, served as the gold-standard. The segmentation model combined a modified U-Net and a convolutional neural network for target region classification. Model performance was evaluated using intersection over union (IoU) and the Hausdorff distance in comparison with the gold standard. The second automated model measured the cortical thickness based on a three-dimensional (3D) model rendered from the segmentation results and presented a color visualization of the measurements. The IoU and Hausdorff distance showed high accuracy (0.870 and 0.928 for marrow bone and 0.734 and 1.247 for cortical bone, respectively). A visual comparison of the 3D color maps showed a similar trend to the gold standard. This algorithm for automatic segmentation of the mandibular condyle head and visualization of the measured cortical thickness as a 3D-rendered model with a color map may contribute to the automated quantification of bone thickness changes of the temporomandibular joint complex on CBCT.

Dimensional measurement accuracy of 3-dimensional models from cone beam computed tomography using different voxel sizes

OBJECTIVES

To compare the geometric accuracy and measurement reliability of 3-dimensional (3D) reconstructed models of the mandible created from cone beam computed tomography (CBCT) images obtained with 0.2-mm and 0.4-mm voxel sizes with the reference standard model and compare the accuracy of the CBCT-based models to each other.

STUDY DESIGN

The reference standard 3D model of a dry human mandible was obtained using a white light scanner. The mandible was scanned with CBCT 10 times at each voxel size. The models created from the CBCT data were compared with the reference standard by using a point-based rigid registration algorithm where the distance differences between the superimposed CBCT models and the reference standard model were recorded. The measurements derived from the 2 CBCT-based scans were also compared.

RESULTS

Mean deviations from the reference standard for 0.2-mm and 0.4-mm voxel scans were 0.4342 mm and 0.4580 mm, respectively (P ≥ .16). The CBCT scans with both 0.2-mm and 0.4-mm voxels produced good measurement reliability and did not significantly differ from each other (P ≥ .20).

CONCLUSIONS

CBCT scans with 0.2-mm and 0.4-mm voxel sizes delivered similarly accurate models. Larger voxels can be used to minimize radiation exposure.

Automatic Segmentation of Mandible from Conventional Methods to Deep Learning-A Review

Medical imaging techniques, such as (cone beam) computed tomography and magnetic resonance imaging, have proven to be a valuable component for oral and maxillofacial surgery (OMFS). Accurate segmentation of the mandible from head and neck (H&N) scans is an important step in order to build a personalized 3D digital mandible model for 3D printing and treatment planning of OMFS. Segmented mandible structures are used to effectively visualize the mandible volumes and to evaluate particular mandible properties quantitatively. However, mandible segmentation is always challenging for both clinicians and researchers, due to complex structures and higher attenuation materials, such as teeth (filling) or metal implants that easily lead to high noise and strong artifacts during scanning. Moreover, the size and shape of the mandible vary to a large extent between individuals. Therefore, mandible segmentation is a tedious and time-consuming task and requires adequate training to be performed properly. With the advancement of computer vision approaches, researchers have developed several algorithms to automatically segment the mandible during the last two decades. The objective of this review was to present the available fully (semi)automatic segmentation methods of the mandible published in different scientific articles. This review provides a vivid description of the scientific advancements to clinicians and researchers in this field to help develop novel automatic methods for clinical applications.

Establishing Quality and Safety in Hospital-based 3D Printing Programs: Patient-first Approach

The adoption of three-dimensional (3D) printing is rapidly spreading across hospitals, and the complexity of 3D-printed models and devices is growing. While exciting, the rapid growth and increasing complexity also put patients at increased risk for potential errors and decreased quality of the final product. More than ever, a strong quality management system (QMS) must be in place to identify potential errors, mitigate those errors, and continually enhance the quality of the product that is delivered to patients. The continuous repetition of the traditional processes of care, without insight into the positive or negative impact, is ultimately detrimental to the delivery of patient care. Repetitive tasks within a process can be measured, refined, and improved and translate into high levels of quality, and the same is true within the 3D printing process. The authors share their own experiences and growing pains in building a QMS into their 3D printing processes. They highlight errors encountered along the way, how they were addressed, and how they have strived to improve consistency, facilitate communication, and replicate successes. They also describe the vital intersection of health care providers, regulatory groups, and traditional manufacturers, who contribute essential elements to a common goal of providing quality and safety to patients. ©RSNA, 2021.

Robust and Accurate Mandible Segmentation on Dental CBCT Scans Affected by Metal Artifacts Using a Prior Shape Model

Accurate mandible segmentation is significant in the field of maxillofacial surgery to guide clinical diagnosis and treatment and develop appropriate surgical plans. In particular, cone-beam computed tomography (CBCT) images with metal parts, such as those used in oral and maxillofacial surgery (OMFS), often have susceptibilities when metal artifacts are present such as weak and blurred boundaries caused by a high-attenuation material and a low radiation dose in image acquisition. To overcome this problem, this paper proposes a novel deep learning-based approach (SASeg) for automated mandible segmentation that perceives overall mandible anatomical knowledge. SASeg utilizes a prior shape feature extractor (PSFE) module based on a mean mandible shape, and recurrent connections maintain the continuity structure of the mandible. The effectiveness of the proposed network is substantiated on a dental CBCT dataset from orthodontic treatment containing 59 patients. The experiments show that the proposed SASeg can be easily used to improve the prediction accuracy in a dental CBCT dataset corrupted by metal artifacts. In addition, the experimental results on the PDDCA dataset demonstrate that, compared with the state-of-the-art mandible segmentation models, our proposed SASeg can achieve better segmentation performance.

Non-Hodgkin Lymphoma Mimicking Endodontic Lesion: A Case Report with 3-dimensional Analysis, Segmentation, and Printing

Non-Hodgkin lymphoma (NHL) of the oral cavity can present with pain, swelling and radiolucent lesion mimicking endodontic diseases. This article reports on a case of diffuse large B-cell lymphoma initially diagnosed and treated as periodontal disease and then endodontic disease in the maxillary anterior and premolar area of a 40-year old female. A cone beam computed tomography (CBCT) image of the lesion was taken. The lesion was segmented using Mimics software (Materialise NV, Lueven, Belgium). Three-dimensional models of the tumor were printed. During the surgical phase teeth #4, 6, and 7 were extracted and biopsy samples were obtained. Histopathologic examination showed invasive sheets of large, atypical, basophilic cells strongly and diffusely positive for CD20. Three-dimensional analysis, segmentation, and printing of radiolucent lesions of the jaws assists with differential diagnosis and efficient treatment. Oral health professionals can play a crucial role in the early detection and diagnosis of oral NHL, thereby preventing extensive loss of function and esthetics, and even saving lives.

Comparison of 3-dimensional postoperative dental movement in Class III surgical correction with and without presurgical orthodontic treatment

Background

Surgery-first approach (SFA) is an emerging concept that surgically reposition the jaw bones without presurgical orthodontic treatment phase. The study investigated 3D dental movement in the postoperative orthodontic phase with orthodontic-first (OF) and SFA in orthognathic surgery (OGS).

Methods

This study included consecutive 40 patients (20, SF group; 20, OF group) skeletal Class III who underwent 2-jaw OGS correction. The data of cone-beam computed tomography were acquired at 3 stages with the scan of dental models to replace the dentition of the craniofacial images; at before OGS (T0), 1 week after OGS (T1) and at the completion of treatment (T2). The skeletal changes were obtained by overall superimposition. The post-operative dental movement was measured by 3D regional superimposition between T1 and T2.

Results

There were no significant difference in the postsurgical orthodontic movement in both groups except significant upper and lower molars extrusion by 2 mm in the SF group. Both groups exhibited no significant difference in mandibular stability in sagittal and vertical directions. The amount of extrusion in the molars was correlated with a postoperative sagittal mandibular forward movement. The total treatment duration was significantly shorter 230 days in the SF group.

Conclusion

The completion of the orthodontic treatment after OGS in the SFA was mainly accomplished through molar extrusive movement in both arches. The surgical setup of dental occlusion with 4 mm posterior open bite could be corrected during the postsurgical orthodontics in SFA through molar extrusion. The dental occlusion outcome was no different between OF and SFA.

Comparative Reliability Assessment of Tooth Volume Measurement with Different Three-Dimensional Imaging Software

Objective. To evaluate the in vivo tooth volume through VRMesh and 3Matic programs and to compare the measurements to the physical volume. So, the aim of the study was to ensure the reliability and sensitivity of the three-dimensional software (VRMesh and 3Matic) in measuring tooth volume. Material and Methods. The volume of 26 extracted upper first premolars from orthodontic patients who had CBCT before orthodontic treatment were measured. Two different commercial programs, which were VRMesh and 3Matic, were used to calculate the volume of the segmented upper first premolar from CBCT. The in vivo tooth volume was compared to the physical tooth volume to examine the accuracy of the two software in measuring the tooth volume. Results. The difference between the mean of the in vivo and in vitro tooth volume measurements was too small, making it clinically nonsignificant. ANOVA test was used as a statistical tool, and no statistically significant difference was noticed among the measurements. The values were normally distributed when tested for normality by Kolmogorov-Smirnov and Shapiro-Wilk test. $\mathit{P}$ value less than or equal to 0.05 ( $\mathit{P}\le 0.05$ ) was considered statistically significant. Conclusion. The assessment of the in vivo tooth volume measurement with different three-dimensional imaging software (VRMesh and 3Matic) programs in comparison with the tooth physical volume is reliable. The use of a mouse pen during the refining stage of the segmentation may have increased the accuracy of the procedure. The determined in vivo tooth volumes are dependable and can be applied in orthodontic diagnosis and treatment planning.

Effect of connective tissue grafting on buccal bone changes based on cone beam computed tomography scans in the esthetic zone of single immediate implants: A 1-year randomized controlled trial

BACKGROUND

Connective tissue grafting has a beneficial effect on the peri-implant mucosa, but the effect of grafting the buccal mucosa on buccal bone thickness (BBT) has not been investigated, although BBT is proposed to be a key factor for the soft-tissue contour. The aim of this trial was to assess the outcome of a connective tissue graft (CTG) in the esthetic zone of single immediate implants on the change of BBT according to cone beam computed tomography (CBCT) scan analysis.

METHODS

In a 1-year randomized controlled trial, 60 patients received an immediately placed implant and provisionalization, either combined with CTG (test group) or without CTG (control group). CBCTs were taken preoperatively (T_pre ) and 1 year after definitive restoration (T₂ ). Any change in BBT was assessed at different implant levels. Additionally, the change in mid-buccal mucosal level (MBML) and approximal marginal bone level were assessed.

RESULTS

Fifty-five patients were available for statistical analysis (test group, n = 28; control group, n = 27). At T₂ , the average change in BBT was significantly larger in the test group (-0.84 ± 0.61 mm) than in the control group (-0.46 ± 0.54 mm, P = 0.02). A MBML gain of 0.07 ± 0.85 mm in the test and a MBML loss -0.52 ± 1.16 mm in the control group was observed at T₂ . Average loss of marginal bone was 0.05 ± 0.33 mm and 0.01 ± 0.38 mm, respectively.

CONCLUSIONS

The application of CTG in the esthetic zone of immediately placed and provisionalized implants is accompanied with more loss of BBT, but at the same time better maintains the mid-buccal mucosal level.

Reliability and accuracy of a method for measuring temporomandibular joint condylar volume

OBJECTIVE

The aim of this study was to develop and validate a technique for mandibular condyle segmentation and volume determination by using cone beam computed tomography (CBCT).

STUDY DESIGN

A dry skull was used to generate 3 dimensional (3-D)-printed mandible models that were then imaged by using CBCT. Semiautomatic segmentation of condyles was completed. The Frankfurt plane was established and translated to the most inferior point of the sigmoid notch, and the condylar volume superior to the plane was determined. This procedure was repeated on 3-D-printed mandibles by using physical landmarks and the water displacement method to obtain the physical volume. This was repeated 3 times to evaluate reliability. Sensitivity analysis was performed to demonstrate the effect of discrepancies in locating landmarks in the Frankfurt plane. Condylar volume measurements obtained from CBCT were compared with physical measurements through repeated-measures analysis of variance (ANOVA) to determine accuracy.

RESULTS

Condylar volume obtained from CBCT and physical measurements resulted in an intraclass correlation coefficient of 0.988 (0.918, 0.998) (P < .01) with both modalities, demonstrating excellent intrarater reliability. The mean difference of volume measurements between the modalities was not statistically significant (P = .365). Potential discrepancies in porion coordinates had minimal impact on condylar volume change.

CONCLUSIONS

The condylar segmentation technique proved to be a reliable and accurate method for evaluating condylar volume.

Evaluation of Imaging Software Accuracy for 3-Dimensional Analysis of the Mandibular Condyle. A Comparative Study Using a Surface-to-Surface Matching Technique

The aim of this study was to assess the accuracy of 3D rendering of the mandibular condylar region obtained from different semi-automatic segmentation methodology. A total of 10 Cone beam computed tomography (CBCT) were selected to perform semi-automatic segmentation of the condyles by using three free-source software (Invesalius, version 3.0.0, Centro de Tecnologia da Informação Renato Archer, Campinas, SP, Brazil; ITK-Snap, version2.2.0; Slicer 3D, version 4.10.2) and one commercially available software Dolphin 3D (Dolphin Imaging, version 11.0, Chatsworth, CA, USA). The same models were also manually segmented (Mimics, version 17.01, Materialise, Leuven, Belgium) and set as ground truth. The accuracy of semi-automatic segmentation was evaluated by (1) comparing the volume of each semi-automatic 3D rendered condylar model with that obtained with manual segmentation, (2) deviation analysis of each 3D rendered mandibular models with those obtained from manual segmentation. No significant differences were found in the volumetric dimensions of the condylar models among the tested software (p > 0.05). However, the color-coded map showed underestimation of the condylar models obtained with ITK-Snap and Slicer 3D, and overestimation with Dolphin 3D and Invesalius. Excellent reliability was found for both intra-observer and inter-observer readings. Despite the excellent reliability, the present findings suggest that data of condylar morphology obtained with semi-automatic segmentation should be taken with caution when an accurate definition of condylar boundaries is required.

One Step before 3D Printing-Evaluation of Imaging Software Accuracy for 3-Dimensional Analysis of the Mandible: A Comparative Study Using a Surface-to-Surface Matching Technique

The accuracy of 3D reconstructions of the craniomaxillofacial region using cone beam computed tomography (CBCT) is important for the morphological evaluation of specific anatomical structures. Moreover, an accurate segmentation process is fundamental for the physical reconstruction of the anatomy (3D printing) when a preliminary simulation of the therapy is required. In this regard, the objective of this study is to evaluate the accuracy of four different types of software for the semiautomatic segmentation of the mandibular jaw compared to manual segmentation, used as a gold standard. Twenty cone beam computed tomography (CBCT) with a manual approach (Mimics) and a semi-automatic approach (Invesalius, ITK-Snap, Dolphin 3D, Slicer 3D) were selected for the segmentation of the mandible in the present study. The accuracy of semi-automatic segmentation was evaluated: (1) by comparing the mandibular volumes obtained with semi-automatic 3D rendering and manual segmentation and (2) by deviation analysis between the two mandibular models. An analysis of variance (ANOVA) was used to evaluate differences in mandibular volumetric recordings and for a deviation analysis among the different software types used. Linear regression was also performed between manual and semi-automatic methods. No significant differences were found in the total volumes among the obtained 3D mandibular models (Mimics = 40.85 cm³, ITK-Snap = 40.81 cm³, Invesalius = 40.04 cm³, Dolphin 3D = 42.03 cm³, Slicer 3D = 40.58 cm³). High correlations were found between the semi-automatic segmentation and manual segmentation approach, with R coefficients ranging from 0,960 to 0,992. According to the deviation analysis, the mandibular models obtained with ITK-Snap showed the highest matching percentage (Tolerance A = 88.44%, Tolerance B = 97.30%), while those obtained with Dolphin 3D showed the lowest matching percentage (Tolerance A = 60.01%, Tolerance B = 87.76%) (p < 0.05). Colour-coded maps showed that the area of greatest mismatch between semi-automatic and manual segmentation was the condylar region and the region proximate to the dental roots. Despite the fact that the semi-automatic segmentation of the mandible showed, in general, high reliability and high correlation with the manual segmentation, caution should be taken when evaluating the morphological and dimensional characteristics of the condyles either on CBCT-derived digital models or physical models (3D printing).

The effect of threshold level on bone segmentation of cranial base structures from CT and CBCT images

The use of a single grey intensity threshold is one of the most straightforward and widely used methods to segment cranial base surface models from a 3D radiographic volume. In this study we used thirty Cone Beam Computer Tomography (CBCT) scans from three different machines and ten CT scans of growing individuals to test the effect of thresholding on the subsequently produced anterior cranial base surface models. From each scan, six surface models were generated using a range of voxel intensity thresholds. The models were then superimposed on a manually selected reference surface model, using an iterative closest point algorithm. Multivariate tests showed significant effects of the machine type, threshold value, and superimposition on the spatial position and the form of the created models. For both, CT and CBCT machines, the distance between the models, as well as the variation within each threshold category, was consistently increasing with the magnitude of difference between thresholds. The present findings highlight the importance of accurate anterior cranial base segmentation for reliable assessment of craniofacial morphology through surface superimposition or similar methods that utilize this anatomical structure as reference.

Automatic Method for Bone Segmentation in Cone Beam Computed Tomography Data Set

Due to technical aspects of Cone Beam Computed Tomography (CBCT), the automatic methods for bone segmentation are not widely used in the clinical practice of endodontics, orthodontics, oral and maxillofacial surgery. The aim of this study was to evaluate method’s accuracy for bone segmentation in CBCT data sets. The sliding three dimensional (3D) window, histogram filter and Otsu’s method were used to implement the automatic segmentation. The results of automatic segmentation were compared with the results of segmentation performed by an experienced oral and maxillofacial surgeon. Twenty patients and their forty CBCT data sets were used in this study (20 preoperative and 20 postoperative). Intraclass Correlation Coefficients (ICC) were calculated to prove the reliability of surgeon segmentations. ICC was 0.958 with 95% confidence interval [0.896 ... 0.983] in preoperative data sets and 0.931 with 95% confidence interval [0.836 ... 0.972] in postoperative data sets. Three basic metrics were used in order to evaluate the accuracy of the automatic method—Dice Similarity Coefficient (DSC), Root Mean Square (RMS), Average Distance Error (ADE) of surfaces mismatch and additional metric in order to evaluate computation time of segmentation was used. The mean value of preoperative DSC was 0.921, postoperative—0.911, the mean value of preoperative RMS was 0.559 mm, postoperative—0.647 mm, the ADE value of preoperative cases was 0.043 mm, postoperative—0.057 mm, the mean computational time to perform the segmentation was 46 s. The automatic method showed clinically acceptable accuracy results and thus can be used as a new tool for automatic bone segmentation in CBCT data. It can be applied in oral and maxillofacial surgery for performance of 3D Virtual Surgical Plan (VSP) or for postoperative follow-up.

Reliability and accuracy of segmentation of mandibular condyles from different three-dimensional imaging modalities: a systematic review

OBJECTIVE

To critically synthesize the literature surrounding segmentation of the mandibular condyle using three-dimensional imaging modalities. Specifically, analyzing the reliability and accuracy of methods used for three-dimensional condyle segmentation.

METHODS

Three electronic databases were searched for studies reporting the reliability and accuracy of various methods used to segment mandibular condyles from three-dimensional imaging modalities. Two authors independently reviewed articles for eligibility and data extraction.

RESULTS

Nine studies fulfilled the inclusion criteria. Eight studies assessed the condylar segmentation from CBCT images and limited studies were available on non-CBCT three-dimensional imaging modalities. Threshold-based volume segmentation, manual segmentation, and semi-automatic segmentation techniques were presented. Threshold-based volume segmentation reported higher accuracy when completed by an experienced technician compared to clinicians. Adequate reliability and accuracy were observed in manual segmentation. Although adequate reliability was reported in semi-automatic segmentation, data on its accuracy were lacking.

CONCLUSION

A definitive conclusion with regards to which current technique is most reliable and accurate to efficiently segment the mandibular condyle cannot be made with the currently available evidence. This is especially true in terms of non-CBCT imaging modalities with very limited literature available.

A review on multiplatform evaluations of semi-automatic open-source based image segmentation for cranio-maxillofacial surgery

BACKGROUND AND OBJECTIVES

Computer-assisted technologies, such as image-based segmentation, play an important role in the diagnosis and treatment support in cranio-maxillofacial surgery. However, although many segmentation software packages exist, their clinical in-house use is often challenging due to constrained technical, human or financial resources. Especially technological solutions or systematic evaluations of open-source based segmentation approaches are lacking. The aim of this contribution is to assess and review the segmentation quality and the potential clinical use of multiple commonly available and license-free segmentation methods on different medical platforms.

METHODS

In this contribution, the quality and accuracy of open-source segmentation methods was assessed on different platforms using patient-specific clinical CT-data and reviewed with the literature. The image-based segmentation algorithms GrowCut, Robust Statistics Segmenter, Region Growing 3D, Otsu & Picking, Canny Segmentation and Geodesic Segmenter were investigated in the mandible on the platforms 3D Slicer, MITK and MeVisLab. Comparisons were made between the segmentation algorithms and the ground truth segmentations of the same anatomy performed by two clinical experts (n = 20). Assessment parameters were the Dice Score Coefficient (DSC), the Hausdorff Distance (HD), and Pearsons correlation coefficient (r).

RESULTS

The segmentation accuracy was highest with the GrowCut (DSC 85.6%, HD 33.5 voxel) and the Canny (DSC 82.1%, HD 8.5 voxel) algorithm. Statistical differences between the assessment parameters were not significant (p < 0.05) and correlation coefficients were close to the value one (r > 0.94) for any of the comparison made between the segmentation methods and the ground truth schemes. Functionally stable and time-saving segmentations were observed.

CONCLUSION

High quality image-based semi-automatic segmentation was provided by the GrowCut and the Canny segmentation method. In the cranio-maxillofacial complex, these segmentation methods provide algorithmic alternatives for image-based segmentation in the clinical practice for e.g. surgical planning or visualization of treatment results and offer advantages through their open-source availability. This is the first systematic multi-platform comparison that evaluates multiple license-free, open-source segmentation methods based on clinical data for the improvement of algorithms and a potential clinical use in patient-individualized medicine. The results presented are reproducible by others and can be used for clinical and research purposes.

Buccal bone thickness at dental implants in the maxillary anterior region with large bony defects at time of immediate implant placement: A 1-year cohort study

Background

There is lack of studies regarding preservation and possible changes in BBT at dental implants.

Purpose

To assess, on cone beam computer tomograms, the presence of bone at the time of tooth extraction in the maxillary esthetic region and the mean buccal bone thickness 1 month and 1 year after final restoration placement in patients with large bony defects.

Material and Methods

In a cohort study, patients were selected presenting a failing tooth with a large bony defect (test group [n = 20]: large bony defect, immediate placed implant and delayed provisionalization). Results were compared with a group in which patients presented a failing tooth without or with a small bony defect: (control group [n = 20]: without or small bony defect, immediate placed implant and delayed provisionalization). Cone beam computer tomograms were made preoperatively, and 1 month and 1 year after placement of the restoration, and buccal bone thickness was analyzed.

Results

In both groups approximately 1 mm of buccal bone thickness was present after 1 month and 1 year, without a significant difference between the groups.

Conclusion

In patients with large bony defects at a failing tooth it was possible to create a bone layer buccally of the implant and this bone layer remained stable during a 1‐year follow‐up; there were no significant differences between thickness of buccal bone at 1 month and 1 year in patients with large buccal bony defects and patients without or with small bony defects.

Clinical evaluation of semi-automatic open-source algorithmic software segmentation of the mandibular bone: Practical feasibility and assessment of a new course of action

INTRODUCTION

Computer assisted technologies based on algorithmic software segmentation are an increasing topic of interest in complex surgical cases. However-due to functional instability, time consuming software processes, personnel resources or licensed-based financial costs many segmentation processes are often outsourced from clinical centers to third parties and the industry. Therefore, the aim of this trial was to assess the practical feasibility of an easy available, functional stable and licensed-free segmentation approach to be used in the clinical practice.

MATERIAL AND METHODS

In this retrospective, randomized, controlled trail the accuracy and accordance of the open-source based segmentation algorithm GrowCut was assessed through the comparison to the manually generated ground truth of the same anatomy using 10 CT lower jaw data-sets from the clinical routine. Assessment parameters were the segmentation time, the volume, the voxel number, the Dice Score and the Hausdorff distance.

RESULTS

Overall semi-automatic GrowCut segmentation times were about one minute. Mean Dice Score values of over 85% and Hausdorff Distances below 33.5 voxel could be achieved between the algorithmic GrowCut-based segmentations and the manual generated ground truth schemes. Statistical differences between the assessment parameters were not significant (p<0.05) and correlation coefficients were close to the value one (r > 0.94) for any of the comparison made between the two groups.

DISCUSSION

Complete functional stable and time saving segmentations with high accuracy and high positive correlation could be performed by the presented interactive open-source based approach. In the cranio-maxillofacial complex the used method could represent an algorithmic alternative for image-based segmentation in the clinical practice for e.g. surgical treatment planning or visualization of postoperative results and offers several advantages. Due to an open-source basis the used method could be further developed by other groups or specialists. Systematic comparisons to other segmentation approaches or with a greater data amount are areas of future works.

Digital Diagnosis and Treatment Program for Maxillofacial Fractures: A Retrospective Analysis of 626 Cases

PURPOSE

The purpose of this study was to evaluate the accuracy of the digital diagnosis and treatment program for maxillofacial fractures.

MATERIALS AND METHODS

The data of 626 patients with maxillofacial fractures were analyzed retrospectively from January 2010 to August 2016. These patients were divided into 2 groups. In the experimental group, preoperative planning was conducted and transferred to patients with guiding templates and navigation according to the digital diagnosis and treatment program for maxillofacial fractures. In the control group, postsurgical planning was performed instead of preoperative planning. To assess the accuracy of the digital diagnosis and treatment program for maxillofacial fractures, preoperative planning and postoperative computed tomographic models were superimposed and imported to dedicated software (Geomagic Studio 13.0, Geomagic, Inc, Research Triangle Park, NC) to calculate the difference between the 2 models in the 2 groups.

RESULTS

Results of the experimental set showed that the mean error between the preoperative planning model and the postoperative model ranged from 0.65 to 0.97 mm (average, 0.89 mm). For the control group, the mean error was 0.78 to 1.45 mm (average, 1.01 mm). Thus, the mean error of the experimental group was statistically lower than that of the control group (P < .0001). Postoperative analysis of the subjective evaluation of occlusion recovery showed that 92.13% of patients achieved good occlusion recovery in the experimental group compared with only 84.91% in the control group. The digital diagnosis and treatment program for maxillofacial fractures was more accurate.

CONCLUSION

Aided by the digital diagnosis and treatment program, the accuracy for maxillofacial fractures was notably improved. To facilitate the application and promotion of digital technology, further modification of the complete digital diagnosis and treatment pathway for maxillofacial fractures is highly desired.

Horizontal ridge reconstruction of the anterior maxilla using customized allogeneic bone blocks with a minimally invasive technique - a case series

BACKGROUND

Different surgical procedures have been proposed to achieve horizontal ridge reconstruction of the anterior maxilla; all these procedures, however, require bone replacement materials to be adapted to the bone defect at the time of implantation, resulting in complex and time-consuming procedures. The purpose of this study was to describe how to use a 3D printed hardcopy model of the maxilla to prepare customized milled bone blocks, to be adapted on the bone defect areas using a minimally invasive subperiosteal tunneling technique.

METHODS

Cone beam computed tomography (CBCT) images of the atrophic maxilla of six patients were acquired and modified into 3D reconstruction models. Data were transferred to a 3D printer and solid models were fabricated using autoclavable nylon polyamide. Before the surgery, freeze-dried cortico-cancellous blocks were manually milled and adapted on the 3D printed hardcopy models of the maxillary bone, in order to obtain customized allogeneic bone blocks.

RESULTS

In total, eleven onlay customized allogeneic bone grafts were prepared and implanted in 6 patients, using a minimally invasive subperiosteal tunneling technique. The scaffolds closely matched the shape of the defects: this reduced the operation time and contributed to good healing. The patients did not demonstrate adverse events such as inflammation, dehiscence or flap re-opening during the recovery period; however, one patient experienced scaffold resorption, which was likely caused by uncontrolled motion of the removable provisional prosthesis. Following a 6 month healing period, CBCT was used to assess graft integration, which was followed by insertion of implants into the augmented areas. Prosthetic restorations were placed 4 months later.

CONCLUSIONS

These observations suggest that customized bone allografts can be successfully used for horizontal ridge reconstruction of the anterior maxilla: patients demonstrated reduced morbidity and decreased total surgery time. Further studies on a larger sample of patients, with histologic evaluation and longer follow-up are needed to confirm the present observations.

Cone Beam Computed Tomographic imaging in orthodontics

Over the last 15 years, cone beam computed tomographic (CBCT) imaging has emerged as an important supplemental radiographic technique for orthodontic diagnosis and treatment planning, especially in situations which require an understanding of the complex anatomic relationships and surrounding structures of the maxillofacial skeleton. CBCT imaging provides unique features and advantages to enhance orthodontic practice over conventional extraoral radiographic imaging. While it is the responsibility of each practitioner to make a decision, in tandem with the patient/family, consensus-derived, evidence-based clinical guidelines are available to assist the clinician in the decision-making process. Specific recommendations provide selection guidance based on variables such as phase of treatment, clinically-assessed treatment difficulty, the presence of dental and/or skeletal modifying conditions, and pathology. CBCT imaging in orthodontics should always be considered wisely as children have conservatively, on average, a three to five times greater radiation risk compared with adults for the same exposure. The purpose of this paper is to provide an understanding of the operation of CBCT equipment as it relates to image quality and dose, highlight the benefits of the technique in orthodontic practice, and provide guidance on appropriate clinical use with respect to radiation dose and relative risk, particularly for the paediatric patient.

Measuring and Establishing the Accuracy and Reproducibility of 3D Printed Medical Models

Despite the rapid growth of three-dimensional (3D) printing applications in medicine, the accuracy and reproducibility of 3D printed medical models have not been thoroughly investigated. Although current technologies enable 3D models to be created with accuracy within the limits of clinical imaging spatial resolutions, this is not always achieved in practice. Inaccuracies are due to errors that occur during the imaging, segmentation, postprocessing, and 3D printing steps. Radiologists' understanding of the factors that influence 3D printed model accuracy and the metrics used to measure this accuracy is key in directing appropriate practices and establishing reference standards and validation procedures. The authors review the various factors in each step of the 3D model printing process that contribute to model inaccuracy, including the intrinsic limitations of each printing technology. In addition, common sources of model inaccuracy are illustrated. Metrics involving comparisons of model dimensions and morphology that have been developed to quantify differences between 3D models also are described and illustrated. These metrics can be used to define the accuracy of a model, as compared with the reference standard, and to measure the variability of models created by different observers or using different workflows. The accuracies reported for specific indications of 3D printing are summarized, and potential guidelines for quality assurance and workflow assessment are discussed. Online supplemental material is available for this article. ^©RSNA, 2017.

Anatomic modeling using 3D printing: quality assurance and optimization

Background

The purpose of this study is to provide a framework for the development of a quality assurance (QA) program for use in medical 3D printing applications. An interdisciplinary QA team was built with expertise from all aspects of 3D printing. A systematic QA approach was established to assess the accuracy and precision of each step during the 3D printing process, including: image data acquisition, segmentation and processing, and 3D printing and cleaning. Validation of printed models was performed by qualitative inspection and quantitative measurement. The latter was achieved by scanning the printed model with a high resolution CT scanner to obtain images of the printed model, which were registered to the original patient images and the distance between them was calculated on a point-by-point basis.

Results

A phantom-based QA process, with two QA phantoms, was also developed. The phantoms went through the same 3D printing process as that of the patient models to generate printed QA models. Physical measurement, fit tests, and image based measurements were performed to compare the printed 3D model to the original QA phantom, with its known size and shape, providing an end-to-end assessment of errors involved in the complete 3D printing process. Measured differences between the printed model and the original QA phantom ranged from -0.32 mm to 0.13 mm for the line pair pattern. For a radial-ulna patient model, the mean distance between the original data set and the scanned printed model was -0.12 mm (ranging from -0.57 to 0.34 mm), with a standard deviation of 0.17 mm.

Conclusions

A comprehensive QA process from image acquisition to completed model has been developed. Such a program is essential to ensure the required accuracy of 3D printed models for medical applications.

3D Printing of CT Dataset: Validation of an Open Source and Consumer-Available Workflow

The broad availability of cheap three-dimensional (3D) printing equipment has raised the need for a thorough analysis on its effects on clinical accuracy. Our aim is to determine whether the accuracy of 3D printing process is affected by the use of a low-budget workflow based on open source software and consumer's commercially available 3D printers. A group of test objects was scanned with a 64-slice computed tomography (CT) in order to build their 3D copies. CT datasets were elaborated using a software chain based on three free and open source software. Objects were printed out with a commercially available 3D printer. Both the 3D copies and the test objects were measured using a digital professional caliper. Overall, the objects' mean absolute difference between test objects and 3D copies is 0.23 mm and the mean relative difference amounts to 0.55 %. Our results demonstrate that the accuracy of 3D printing process remains high despite the use of a low-budget workflow.

Buccal bone thickness at dental implants in the aesthetic zone: A 1-year follow-up cone beam computed tomography study

Sufficient buccal bone thickness (BBT) is important for an optimal aesthetic outcome of implant treatment in the aesthetic zone. The aim of the study was to assess BBT at dental implants placed in the aesthetic zone (incisor, canine or first premolar in the maxilla) (immediate or delayed, with or without immediate provisionalization) with cone beam computed tomography (CBCT) as a function of time. Eighty patients were divided into 4 groups according to size of the buccal bony defect (<5 or ≥5 mm) after removal of the tooth, and timing of implant placement and provisionalization. CBCTs were made 1 month and 1 year after placement of the implant crown. BBT varied from 0.79 mm to 2.12 mm at 1 month and from 0.71 mm to 2.04 mm at 1 year. Change of BBT between 1 month and 1 year was negligible. This study concluded that BBT at dental implants in the aesthetic zone appears to be stable for immediate and delayed placed implants after placement of the definitive crown, independent of the size of buccal bone defect prior to implant insertion and timing of provisionalization.

Soft tissue coverage on the segmentation accuracy of the 3D surface-rendered model from cone-beam CT

OBJECTIVES

The aim of this study is to investigate the effect of soft tissue presence on the segmentation accuracy of the 3D hard tissue models from cone-beam computed tomography (CBCT).

MATERIALS AND METHODS

Seven pairs of CBCT Digital Imaging and Communication in Medicine (DICOM) datasets, containing data of human cadaver heads and their respective dry skulls, were used. The effect of the soft tissue presence on the accuracy of the segmented models was evaluated by performing linear and angular measurements and by superimposition and color mapping of the surface discrepancies after splitting the mandible and maxillo-facial complex in the midsagittal plane.

RESULTS

The linear and angular measurements showed significant differences for the more posterior transversal measurements on the mandible (p < 0.01). By splitting and superimposing the maxillo-facial complex, the mean root-mean-square error (RMSE) as a measurement of inaccuracy decreased insignificantly from 0.936 to 0.922 mm (p > 0.05). The RMSE value for the mandible, however, significantly decreased from 1.240 to 0.981 mm after splitting (p < 0.01).

CONCLUSIONS

The soft tissue presence seems to affect the accuracy of the 3D hard tissue model obtained from a cone-beam CT, below a generally accepted level of clinical significance of 1 mm. However, this level of accuracy may not meet the requirement for applications where high precision is paramount.

CLINICAL RELEVANCE

Accuracy of CBCT-based 3D surface-rendered models, especially of the hard tissues, are crucial in several dental and medical applications, such as implant planning and virtual surgical planning on patients undergoing orthognathic and navigational surgeries. When used in applications where high precision is paramount, the effect of soft tissue presence should be taken into consideration during the segmentation process.

Immediate Single-Tooth Implant Placement in Bony Defects in the Esthetic Zone: A 1-Year Randomized Controlled Trial

BACKGROUND

This study aims to assess, with regard to marginal bone level (MBL), whether the outcome of immediate implant placement in bony defects in the esthetic zone was non-inferior to delayed implant placement after 1 year.

METHODS

Forty patients with a failing tooth in the esthetic zone and a labial bony defect of ≥5 mm after removal of a tooth were randomly assigned for immediate (n = 20) or delayed (n = 20) implant placement. Second-stage surgery and provisionalization occurred after 3 months of healing. Follow-up was at 1 month and 1 year after definitive crown placement. The study was powered to detect a difference in MBL of >0.9 mm. Buccal bone thickness, soft tissue peri-implant parameters, esthetic indices, and patient satisfaction were also assessed.

RESULTS

One year after definitive crown placement, MBL loss was 0.56 ± 0.39 mm mesially and 0.74 ± 0.51 mm distally for the immediate placement group and 0.51 ± 0.43 mesially and 0.54 ± 0.45 distally mm for the delayed placement group, respectively (not significant). Regarding differences in means, non-inferiority was observed after 1 year (difference in mean for immediate versus delayed: mesially 0.04 mm [95% confidence interval (CI) = -0.22 to 0.30 mm, P = 0.40]; distally 0.21 mm [95% CI = -0.10 to 0.51 mm, P = 0.58]). No significant differences in the other outcome variables were observed.

CONCLUSIONS

Immediate implant placement with delayed provisionalization was non-inferior to delayed implant placement with delayed provisionalization in labial bony defects of ≥5 mm regarding change in MBL. Although not powered for other outcome variables, no clinically relevant differences were observed in these variables.

Cone beam computed tomography-based models versus multislice spiral computed tomography-based models for assessing condylar morphology

OBJECTIVE

To quantitatively compare condylar morphology using cone beam computed tomography (CBCT) and multislice spiral computed tomography (MSCT) virtual three-dimensional surface models.

STUDY DESIGN

The sample consisted of secondary data analyses of CBCT and MSCT scans obtained for clinical purposes from 74 patients treated with condylar resection and prosthetic joint replacement. Three-dimensional surface models of 146 condyles were constructed from each scan modality. Across-subject models were approximated and voxel-based registration was performed between homologous CBCT and MSCT images, making it possible to create average CBCT- and MSCT-based condylar models. SPHARM-PDM software provided matching points on each corresponding model. ShapeAnalysisMANCOVA software assessed statistically significant differences between observers and imaging modalities. One-sample t-tests evaluated the null hypothesis that the mean differences between each CBCT- and MSCT-based model were not clinically significant (<.5 mm). Tests were conducted at a significance level of P < .05.

RESULTS

ShapeAnalysisMANCOVA showed no statistically significant difference between the average CBCT- and MSCT-based models (P > .68). During pairwise comparison, the mean difference observed was .406 mm (SD, .173). One sample t-test showed that mean differences between each set of paired CBCT- and MSCT-based models were not clinically significant (P = .411).

CONCLUSION

Three-dimensional surface models constructed from CBCT images are comparable to those derived from MSCT scans and may be considered reliable tools for assessing condylar morphology.

Inter- and intraobserver reproducibility of buccal bone measurements at dental implants with cone beam computed tomography in the esthetic region

BACKGROUND

Sufficient buccal bone is important for optimal esthetic results of implant treatment in the anterior region. It can be measured with cone beam computed tomography (CBCT), but background scattering and problems with standardization of the measurements are encountered. The aim was to develop a method for reliable, reproducible measurements on CBCTs.

METHODS

Using a new method, buccal bone thickness was measured on ten CBCTs at six positions along the implant axis. Inter- and intraobserver reproducibility was assessed by repeated measurements by two examiners.

RESULTS

Mean buccal bone thickness measured by observers 1 and 2 was 2.42 mm (sd: 0.50) and 2.41 mm (sd: 0.47), respectively. Interobserver intraclass correlation coefficient was 0.96 (95% CI 0.93 to 0.98). The mean buccal bone thickness of the first measurement and the second measurement of observer 1 was 2.42 mm (sd: 0.50) and 2.53 mm (sd: 0.49), respectively, with an intraobserver intraclass correlation coefficient of 0.93 (95% CI 0.88 to 0.96). The mean buccal bone thickness of the first measurement and the second measurement of observer 2 was 2.41 mm (sd: 0.47) and 2.52 mm (sd: 0.47), respectively, with an intraobserver intraclass correlation coefficient of 0.96 (95% CI 0.93 to 0.97).

CONCLUSIONS

Applying the methods used in this study, CBCTs are suitable for reliable and reproducible measurements of buccal bone thickness at implants.