This research was supported by the Intramural Research Program of the National Institute of Dental and Craniofacial Research (NIDCR) of the National Institutes of Health (NIH), and the Advanced Education in Orthodontics and Dentofacial Orthopedics program of Roseman University College of Dental Medicine.

3D Cephalometric Landmark Annotation Demonstration on Human CBCT Scans

<ol>
	<li>Proffit, W. R., Fields, H. W., Larson, B., Sarver, D. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Contemporary+Orthodontics+-+E-Book.">Contemporary Orthodontics - E-Book.</a> Elsevier Health Sciences. , (2018).</li><li>Broadbent, B. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+new+x-ray+technique+and+its+application+to+orthodontia.">A new x-ray technique and its application to orthodontia.</a> The Angle Orthodontist. 1 (2), 45-66 (1931).</li><li>Hans, M. G., Palomo, J. M., Valiathan, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=History+of+imaging+in+orthodontics+from+Broadbent+to+cone-beam+computed+tomography.">History of imaging in orthodontics from Broadbent to cone-beam computed tomography.</a> American Journal of Orthodontics and Dentofacial Orthopedics. 148 (6), 914-921 (2015).</li><li>Liberton, D. K., Verma, P., Contratto, A., Lee, J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+and+validation+of+novel+three-dimensional+craniofacial+landmarks+on+cone-beam+computed+tomography+scans.">Development and validation of novel three-dimensional craniofacial landmarks on cone-beam computed tomography scans.</a> The Journal of Craniofacial Surgery. 30 (7), e611-615 (2019).</li><li>Pittayapat, P., Limchaichana-Bolstad, N., Willems, G., Jacobs, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+cephalometric+analysis+in+orthodontics:+a+systematic+review.">Three-dimensional cephalometric analysis in orthodontics: a systematic review.</a> Orthodontics &amp; Craniofacial Research. 17 (2), 69-91 (2014).</li><li>Lo Giudice, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+evolution+of+the+cephalometric+superimposition+techniques+from+the+beginning+to+the+digital+era:+a+brief+descriptive+review.">The evolution of the cephalometric superimposition techniques from the beginning to the digital era: a brief descriptive review.</a> International Journal of Dentistry. 2021, 6677133 (2021).</li><li>Graf, C. C., Dritsas, K., Ghamri, M., Gkantidis, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reliability+of+cephalometric+superimposition+for+the+assessment+of+craniofacial+changes:+a+systematic+review.">Reliability of cephalometric superimposition for the assessment of craniofacial changes: a systematic review.</a> European Journal of Orthodontics. 44 (5), 477-490 (2022).</li><li>Dot, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automatic+3-dimensional+cephalometric+landmarking+via+deep+learning.">Automatic 3-dimensional cephalometric landmarking via deep learning.</a> Journal of Dental Research. 101 (11), 1380-1387 (2022).</li><li>Kang, S. H., Jeon, K., Kang, S. H., Lee, S. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=3D+cephalometric+landmark+detection+by+multiple+stage+deep+reinforcement+learning.">3D cephalometric landmark detection by multiple stage deep reinforcement learning.</a> Scientific Reports. 11 (1), 17509 (2021).</li><li>Schwendicke, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Deep+learning+for+cephalometric+landmark+detection:+systematic+review+and+meta-analysis.">Deep learning for cephalometric landmark detection: systematic review and meta-analysis.</a> Clinical Oral Investigations. 25 (7), 4299-4309 (2021).</li><li>Yun, H. S., Jang, T. J., Lee, S. M., Lee, S. H., Seo, J. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Learning-based+local-to-global+landmark+annotation+for+automatic+3D+cephalometry.">Learning-based local-to-global landmark annotation for automatic 3D cephalometry.</a> Physics in Medicine and Biology. 65 (8), 085018 (2020).</li><li>Bookstein, F. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Morphometric Tools for Landmark Data: Geometry and Biology. , (1992).</li><li>Almpani, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Loeys-Dietz+and+Shprintzen-Goldberg+syndromes:+analysis+of+TGF-&#946;-opathies+with+craniofacial+manifestations+using+an+innovative+multimodality+method.">Loeys-Dietz and Shprintzen-Goldberg syndromes: analysis of TGF-&#946;-opathies with craniofacial manifestations using an innovative multimodality method.</a> Journal of Medical Genetics. 59 (10), 938-946 (2022).</li><li>Liberton, D. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Craniofacial+analysis+may+indicate+co-occurrence+of+skeletal+malocclusions+and+associated+risks+in+development+of+cleft+lip+and+palate.">Craniofacial analysis may indicate co-occurrence of skeletal malocclusions and associated risks in development of cleft lip and palate.</a> Journal of Developmental Biology. 8 (1), 2 (2020).</li><li>Whitman, M. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=TUBB3+Arg262His+causes+a+recognizable+syndrome+including+CFEOM3,+facial+palsy,+joint+contractures,+and+early-onset+peripheral+neuropathy.">TUBB3 Arg262His causes a recognizable syndrome including CFEOM3, facial palsy, joint contractures, and early-onset peripheral neuropathy.</a> Human Genetics. 140 (12), 1709-1731 (2021).</li><li>Kidwai, F. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+craniofacial+analysis+and+generation+of+human+induced+pluripotent+stem+cells+for+Muenke+syndrome:+A+case+report.">Quantitative craniofacial analysis and generation of human induced pluripotent stem cells for Muenke syndrome: A case report.</a> Journal of Developmental Biology. 9 (4), 39 (2021).</li></ol>

The authors declare no conflicts of interest.

Medicine and dentistry have already entered the 3D imaging era. In the disciplines of craniofacial and dental imaging, CBCT scans are increasingly being used, due to the low radiation and decreased cost of the updated systems in comparison to traditional CT machines, easy personnel usage calibration, relatively quick and easy acquisition with minimal patient cooperation, as well as the ability to generate multiple other diagnostic images and analyses from one single scan. Therefore, it is essential for clinicians and researchers to know how to read, diagnose, and analyze these 3D images, as well as learn how to study craniofacial growth and development in 3D.
To assist clinicians and researchers in this field, we present a step-by-step protocol and video demonstration for the conduction of 3D cephalometric analysis with the use of human CBCT scans. These landmarks have been previously defined and validated in a previous publication, where their accuracy and repeatability were confirmed4. The detailed refinement instructions for each landmark also assist users in the correct annotation of each landmark. The landmark annotation process is further simplified with the use of preset views of the scan that correspond to the area that each landmark should be positioned. This function saves significant time and effort for the user. Nevertheless, there is a learning curve involved, and practice is required by users to achieve accurate landmark annotation.
The validated 3D landmark configuration used in this protocol provides sufficient coverage of the skeletal tissue of the face, maxilla, mandible, and cranial base. In this way, the true morphology of the craniofacial structures is more accurately represented for evaluation of the dimensions, configuration, and orientation of the craniofacial complex and its component structures. Soft tissue landmarks are not included in this protocol, but users can add landmarks of choice to the provided configuration, as described in the protocol. In addition, for practical reasons, this protocol could not include specific instructions for other 3D analysis software, but can be adapted accordingly by each user.
Apart from the diagnostic value of the generated standard cephalometric measurements, mainly for clinicians, the freedom offered with the use of this analysis to compute angles and linear distances between any 3D landmarks will allow the establishment of new cephalometric analyses that will provide more detailed and complete assessments. Nevertheless, our future direction includes establishing new respective normative values, in the same way that 2D normative values were created in the past.
Moreover, the applications of landmarked based GMA in the craniofacial clinical and research field are developing at a fast pace. Researchers in evolutionary and developmental biology and anthropology for have been using this analysis for more than a decade, but new clinical applications have also been recently presented in the fields of orthodontics, dentofacial orthopedics, and craniofacial surgery. GMA can be also used as part of a quantitative phenotyping in the case of congenital diseases with craniofacial manifestations, as well as for the detection of subtle morphological differences attributed to gene mutations13,14,15,16. In addition, the integration of different quantitative approaches by linking morphometric data with functional analysis as well as genetic data can provide new knowledge regarding craniofacial development in healthy, as well as disease, groups.
Because of recent advances in computation and visualization, the conduction of this type of analysis is now feasible on personal computers, with several software packages already available, including Checkpoint, Geomorph (a package of R statistical software), Amira-Avizo, and SlicerMorph. These programs can assist researchers in the medical fields that may be unfamiliar with multivariate statistical analyses to conduct GMA with the availability of built-in automated functions.

Cephalometric analysis, which examines the dental and skeletal relationships of the human skull, is the clinical application of cephalometry. In addition to anthropologists, developmental biologists, forensic experts, and craniofacial researchers who study human evolution and craniofacial development, it is utilized by oral health professionals, including dentists, orthodontists, and oral and maxillofacial surgeons, as a treatment planning tool. The earliest institutions that used cephalometric analysis in orthodontics were Hofrath in Germany and Broadbent in the USA in 19311,2,3. The primary objective of the analysis was to provide a theoretical and practical resource to evaluate the craniofacial proportions of an individual and to define the anatomical source of malocclusion1. This allowed for the growth pattern of the maxilla and mandible to be tracked, their relational positions in space to be monitored, and changes in soft tissue and teeth displacement to be observed. As a result, changes brought about by orthodontic treatment could be monitored, and skeletal and dental relationships could be characterized for a diagnosis to be made for treatment planning. Evaluation of the dentofacial complex was done by comparing a patient&#39;s cephalometric tracing with reference values that were representative of a normal population of similar age, race, and ethnicity1.
The traditional method of analysis consisted of a two-dimensional (2D) depiction of three-dimensional (3D) structures4,5. A major setback of this technique is the distortion and magnification of anatomical structures via conventional x-ray imaging on plain film or digital formats, which can lead to inaccurate cephalometric tracings and interpretations6,7. The initial introduction of 3D imaging in the form of axial computed tomography (CT) and spiral CT did not include dental or non-medical applications due to high cost and high radiation doses. However, the emergence of cone beam computed tomography (CBCT) scans mitigated these concerns, as expenses and radiation doses were significantly lower than CT1. The shift in this imaging narrative galvanized the widespread use of CBCT in orthodontics for improvement in diagnosis and treatment planning. The main advantage of 3D imaging over the conventional 2D image technique is that 3D allows the examiner to view anatomical structures without superimpositions and spatial distortions (i.e., head position of the individual). Therefore, a much more accurate positioning of the anatomical landmarks used for the conduction of cephalometric analysis is possible, especially in cases of facial asymmetry. Moreover, a much larger anatomical area can be analyzed.
One of the most recent advances in the field of cephalometry is the implementation of deep learning (DL) for automated landmark detection8,9,10,11. Although the results of these studies are promising, the levels of accuracy in the placement of the landmarks are not yet satisfactory. Moreover, most of these studies use relatively small landmark sets that are derived from previous 2D cephalometric analyses, providing insufficient coverage of the cranial base, which is an important structure for the study of craniofacial growth and development. This demonstration video showcases in detail a methodology for the conduction of manual, high-accuracy 3D cephalometric analysis with the use of a validated set of 3D skeletal tissue landmarks covering the areas of the face, cranial base, mandible, and teeth for use in clinical and research studies involving CBCT imaging4. An example of a completed 3D analysis can be seen in Figure 1.

<table><tbody><tr><td>Invivo6 Dental Software</td><td>Anatomage</td><td>N/A</td><td>3D Imaging Software (including 3D analysis module)</td></tr></tbody></table>

three-dimensional cephalometric landmark annotation demonstration on human cone beam computed tomography scans

Craniofacial cephalometric analysis is a diagnostic tool used for the assessment of the relationship of various bones and soft tissues in the head and face. Cephalometric analysis has been traditionally conducted with the use of 2D radiographs and landmark sets and restricted to size, linear and angular measurements, and 2D relationships. The increasing use of 3D cone beam computed tomography (CBCT) scans in the dental field dictates the need for the evolution to 3D cephalometric analysis, which incorporates shape and a more realistic analysis of longitudinal development in all three planes. This study is a demonstration of 3D cephalometric analysis with the use of a validated set of skeletal tissue landmarks on human CBCT scans. Detailed instructions for the annotation of each landmark on a 3D volume are provided as part of a step-by-step protocol. The generated measurements and 3D coordinates of the landmarks can be exported and used both for clinical and research purposes. The introduction of 3D cephalometric analysis in basic and clinical craniofacial studies will lead to future advancements in the field of craniofacial growth and development.

The annotation of a validated 3D landmark configuration is described in detail with the use of a step-by-step protocol and video demonstration. Specific instructions are provided for the annotation of each landmark on the 3D volume, as well as the refinement of their initial positions with the help of the 2D section views that correspond to each plane of space. By following the detailed methodology provided in the protocol in combination with the video instructions, the user can learn how to conduct cephalometric analysis with the use of human CBCT scans.
Figure 1 represents frontal and three-quarter views of a full head CBCT scan of a human skull with the annotated 3D landmarks included in the current configuration. All the described landmarks are Type 1 and Type 2. Type 1 landmarks represent clearly recognizable points usually observed at the intersection of distinct anatomical structures. Type 2 landmarks represent points of maximal curvature on the contour of recognizable anatomical structures12. No Type 3 or semi-landmarks were included in this analysis.
After the completion of the annotation of the landmarks, there are two types of data that can be exported and further analyzed by the user: cephalometric measurement and 3D coordinate values. The values of key cephalometric measurements required for the diagnosis and assessment of dentoskeletal malocclusion are provided. These measurements provide a detailed assessment of the skeletal and dental relationships in all three planes of space: sagittal, vertical, and transverse. The 3D coordinate values (x, y, z) of each landmark can be exported and used for the calculation of angles and linear distances. The values of the same coordinates can be used for the conduction of multivariate geometric morphometric analysis (GMA). GMA is a method for studying shape that can capture morphologically different shape variables utilizing Cartesian landmark and/or semi-landmark coordinates. Several statistical techniques can be used to examine shape, without taking into account the size, location, or orientation of the examined structures. Geometric morphometrics is currently the most established body of morphometric theory for handling landmark-based data.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65224/65224fig01.jpg" /> 
Figure 1: Frontal and three-quarter views of a full head CBCT scan of a human skull with the annotated 3D landmarks included in the current configuration. <a href="https://www.jove.com/files/ftp_upload/65224/65224fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplementary File 1: Configuration file including the landmarks used in this protocolwhich can be directly uploaded to the software for analysis. <a href="https://www.jove.com/files/ftp_upload/65224/AnalysisCFGUser.zip" target="_blank">Please click here to download this File.</a>

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Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans  

Presented here is a detailed protocol for the conduction of three-dimensional cephalometric analysis with the use of human cone beam computed tomography scans.

Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

Craniofacial cephalometric analysis is a diagnostic tool used for the assessment of the relationship of various bones and soft tissues in the head and ...

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2.5K Views.  National Institute of Dental and Craniofacial Research. Presented here is a detailed protocol for the conduction of three-dimensional cephalometric analysis with the use of human cone beam computed tomography scans.

Video: Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans  

Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers

Small animal fluorescence molecular imaging (FMI) can be a powerful tool for preclinical drug discovery and development studies1. However, light absorption by tissue chromophores (e.g., hemoglobin, water, lipids, melanin) typically limits optical signal propagation through thicknesses larger than a few millimeters2. Compared to other visible wavelengths, tissue absorption for red and near-infrared (near-IR) light absorption dramatically decreases and non-elastic scattering becomes the dominant light-tissue interaction mechanism. The relatively recent development of fluorescent agents that absorb and emit light in the near-IR range (600-1000 nm), has driven the development of imaging systems and light propagation models that can achieve whole body three-dimensional imaging in small animals3.
Despite great strides in this area, the ill-posed nature of diffuse fluorescence tomography remains a significant problem for the stability, contrast recovery and spatial resolution of image reconstruction techniques and the optimal approach to FMI in small animals has yet to be agreed on. The majority of research groups have invested in charge-coupled device (CCD)-based systems that provide abundant tissue-sampling but suboptimal sensitivity4-9, while our group and a few others10-13 have pursued systems based on very high sensitivity detectors, that at this time allow dense tissue sampling to be achieved only at the cost of low imaging throughput. Here we demonstrate the methodology for applying single-photon detection technology in a fluorescence tomography system to localize a cancerous brain lesion in a mouse model.
The fluorescence tomography (FT) system employed single photon counting using photomultiplier tubes (PMT) and information-rich time-domain light detection in a non-contact conformation11. This provides a simultaneous collection of transmitted excitation and emission light, and includes automatic fluorescence excitation exposure control14, laser referencing, and co-registration with a small animal computed tomography (microCT) system15. A nude mouse model was used for imaging. The animal was inoculated orthotopically with a human glioma cell line (U251) in the left cerebral hemisphere and imaged 2 weeks later. The tumor was made to fluoresce by injecting a fluorescent tracer, IRDye 800CW-EGF (LI-COR Biosciences, Lincoln, NE) targeted to epidermal growth factor receptor, a cell membrane protein known to be overexpressed in the U251 tumor line and many other cancers18. A second, untargeted fluorescent tracer, Alexa Fluor 647 (Life Technologies, Grand Island, NY) was also injected to account for non-receptor mediated effects on the uptake of the targeted tracers to provide a means of quantifying tracer binding and receptor availability/density27. A CT-guided, time-domain algorithm was used to reconstruct the location of both fluorescent tracers (i.e., the location of the tumor) in the mouse brain and their ability to localize the tumor was verified by contrast-enhanced magnetic resonance imaging.
Though demonstrated for fluorescence imaging in a glioma mouse model, the methodology presented in this video can be extended to different tumor models in various small animal models potentially up to the size of a rat17.

Diffuse fluorescence tomography offers a relatively low-cost and potentially high-throughout approach to preclinical in vivo tumor imaging. The methodology of optical data collection, calibration, and image reconstruction is presented for a computed tomography-guided non-contact time-domain system using fluorescent targeting of the tumor biomarker epidermal growth factor receptor in a mouse glioma model.

Small animal fluorescence molecular imaging (FMI) can be a powerful tool for preclinical drug discovery and development studies1. However, light ...

Human Neuroendocrine Tumor Cell Lines as a Three-Dimensional Model for the Study of Human Neuroendocrine Tumor Therapy

Neuroendocrine tumors (NETs) are rare tumors, with an incidence of two per 100,&#x200A;000 individuals per year, and they account for 0.5% of all human malignancies.1 Other than surgery for the minority of patients who present with localized disease, there is little or no survival benefit of systemic therapy. Therefore, there is a great need to better understand the biology of NETs, and in particular define new therapeutic targets for patients with nonresectable or metastatic neuroendocrine tumors. 3D cell culture is becoming a popular method for drug screening due to its relevance in modeling the in vivo tumor tissue organization and microenvironment.2,3 The 3D multicellular spheroids could provide valuable information in a more timely and less expensive manner than directly proceeding from 2D cell culture experiments to animal (murine) models.
To facilitate the discovery of new therapeutics for NET patients, we have developed an in vitro 3D multicellular spheroids model using the human NET cell lines. The NET cells are plated in a non-adhesive agarose-coated 24-well plate and incubated under physiological conditions (5% CO2, 37 &deg;C) with a very slow agitation for 16-24 hr after plating. The cells form multicellular spheroids starting on the 3rd or 4th day. The spheroids become more spherical by the 6th day, at which point the drug treatments are initiated. The efficacy of the drug treatments on the NET spheroids is monitored based on the morphology, shape and size of the spheroids with a phase-contrast light microscope. The size of the spheroids is estimated automatically using a custom-developed MATLAB program based on an active contour algorithm. Further, we demonstrate a simple method to process the HistoGel embedding on these 3D spheroids, allowing the use of standard histological and immunohistochemical techniques. 
This is the first report on generating 3D spheroids using NET cell lines to examine the effect of therapeutic drugs. We have also performed histology on these 3D spheroids, and displayed an example of a single drug's effect on growth and proliferation of the NET spheroids. Our results support that the NET spheroids are valuable for further studies of NET biology and drug development.

We present a simple agarose overlay platform to grow 3D multicellular spheroids using neuroendocrine cancer cell lines. This method provides a very convenient way to examine the effect of therapeutic drugs on the neuroendocrine tumor cells. It could also help us establish human neuroendocrine tumor spheroids for cancer therapy.

Neuroendocrine tumors (NETs) are rare tumors, with an incidence of two per 100,&#x200A;000 individuals per year, and they account for 0.5% of all human ...

Three-dimensional Imaging of Nociceptive Intraepidermal Nerve Fibers in Human Skin Biopsies

A punch biopsy of the skin is commonly used to quantify intraepidermal nerve fiber densities (IENFD) for the diagnosis of peripheral polyneuropathy 1,2. At present, it is common practice to collect 3 mm skin biopsies from the distal leg (DL) and the proximal thigh (PT) for the evaluation of length-dependent polyneuropathies 3. However, due to the multidirectional nature of IENFs, it is challenging to examine overlapping nerve structures through the analysis of two-dimensional (2D) imaging. Alternatively, three-dimensional (3D) imaging could provide a better solution for this dilemma.
In the current report, we present methods for applying 3D imaging to study painful neuropathy (PN). In order to identify IENFs, skin samples are processed for immunofluorescent analysis of protein gene product 9.5 (PGP), a pan neuronal marker. At present, it is standard practice to diagnose small fiber neuropathies using IENFD determined by PGP immunohistochemistry using brightfield microscopy 4. In the current study, we applied double immunofluorescent analysis to identify total IENFD, using PGP, and nociceptive IENF, through the use of antibodies that recognize tropomyosin-receptor-kinase A (Trk A), the high affinity receptor for nerve growth factor 5. The advantages of co-staining IENF with PGP and Trk A antibodies benefits the study of PN by clearly staining PGP-positive, nociceptive fibers. These fluorescent signals can be quantified to determine nociceptive IENFD and morphological changes of IENF associated with PN. The fluorescent images are acquired by confocal microscopy and processed for 3D analysis. 3D-imaging provides rotational abilities to further analyze morphological changes associated with PN. Taken together, fluorescent co-staining, confocal imaging, and 3D analysis clearly benefit the study of PN.

In order to study the changes of nociceptive intraepidermal nerve fibers (IENFs) in painful neuropathies (PN), we developed protocols that could directly examine three-dimensional morphological changes observed in nociceptive IENFs. Three-dimensional analysis of IENFs has the potential to evaluate the morphological changes of IENF in PN.

A punch biopsy of the skin is commonly used to quantify intraepidermal nerve fiber densities (IENFD) for the diagnosis of peripheral polyneuropathy 1,2. ...

Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization

The advent of cone-beam computed tomography (CBCT) in the angiography suite has been revolutionary in interventional radiology. CBCT offers 3 dimensional&#160;(3D) diagnostic imaging in the interventional suite and can enhance minimally-invasive therapy beyond the limitations of 2D angiography alone. The role of CBCT has been recognized in transarterial chemo-embolization (TACE) treatment of hepatocellular carcinoma (HCC). The recent introduction of a CBCT technique: dual-phase CBCT (DP-CBCT) improves intra-arterial HCC treatment with drug-eluting beads (DEB-TACE). DP-CBCT can be used to localize liver tumors with the diagnostic accuracy of multi-phasic multidetector computed tomography (M-MDCT) and contrast enhanced magnetic resonance imaging (CE-MRI) (See the tumor), to guide intra-arterially guidewire and microcatheter to the desired location for selective therapy (Reach the tumor), and to evaluate treatment success during the procedure (Treat the tumor). The purpose of this manuscript is to illustrate how DP-CBCT is used in DEB-TACE to see, reach, and treat HCC.

Dual-phase cone-beam computed tomography (DP-CBCT) is a useful intraprocedural imaging technique for transarterial chemo-embolization treatment with drug-eluting beads of hepatocellular carcinoma. DP-CBCT has been used to perform three major steps in oncologic interventional radiology: tumor localization (see), navigation and intraprocedural catheter guidance (reach), and intraprocedural evaluation of treatment success (treat).

The advent of cone-beam computed tomography (CBCT) in the angiography suite has been revolutionary in interventional radiology. CBCT offers 3 ...

Assessment of Viability of Human Fat Injection into Nude Mice with Micro-Computed Tomography

Lipotransfer is a vital tool in the surgeon&#8217;s armamentarium for the treatment of soft tissue deficits of throughout the body. Fat is the ideal soft tissue filler as it is readily available, easily obtained, inexpensive, and inherently biocompatible.1 However, despite its burgeoning popularity, fat grafting is hampered by unpredictable results and variable graft survival, with published retention rates ranging anywhere from 10-80%. 1-3
To facilitate investigations on fat grafting, we have therefore developed an animal model that allows for real-time analysis of injected fat volume retention. Briefly, a small cut is made in the scalp of a CD-1 nude mouse and 200-400 &#181;l&#160;of processed lipoaspirate is placed over the skull. The scalp is chosen as the recipient site because of its absence of native subcutaneous fat, and because of the excellent background contrast provided by the calvarium, which aids in the analysis process. Micro-computed tomography (micro-CT) is used to scan the graft at baseline and every two weeks thereafter. The CT images are reconstructed, and an imaging software is used to quantify graft volumes.
Traditionally, techniques to assess fat graft volume have necessitated euthanizing the study animal to provide just a single assessment of graft weight and volume by physical measurement ex vivo. Biochemical and histological comparisons have likewise required the study animal to be euthanized. This described imaging technique offers the advantage of visualizing and objectively quantifying volume at multiple time points after initial grafting without having to sacrifice the study animal. The technique is limited by the size of the graft able to be injected as larger grafts risk skin and fat necrosis. This method has utility for all studies evaluating fat graft viability and volume retention. It is particularly well-suited to providing a visual representation of fat grafts and following changes in volume over time.

Fat grafting is an essential technique for reconstructing soft tissue deficits. However, it remains an unpredictable procedure characterized by variable graft survival. Our goal was to devise a mouse model that utilizes a novel imaging method to compare volume retention between differing techniques of fat graft preparation and delivery.

Lipotransfer is a vital tool in the surgeon&#8217;s armamentarium for the treatment of soft tissue deficits of throughout the body. Fat is the ideal soft ...

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

Four-dimensional computed tomography (4DCT) provides a series of volume data and visualizes joint motions. However, numerical analysis of 4DCT data remains difficult because segmentation in all volumetric frames is time-consuming. We aimed to analyze joint kinematics using a sequential 3D-3D registration technique to provide the kinematics of the moving bone with respect to the fixed bone semiautomatically using 4DCT DICOM data and existing software. Surface data of the source bones are reconstructed from 3DCT. The trimmed surface data are respectively matched with surface data from the first frame in 4DCT. These trimmed surfaces are sequentially matched until the last frame. These processes provide positional information for target bones in all frames of the 4DCT. Once the coordinate systems of the target bones are decided, translation and rotation angles between any two bones can be calculated. This 4DCT analysis offers advantages in kinematic analyses of complex structures such as carpal or tarsal bones. However, fast or large-scale motions cannot be traced because of motion artifacts.

We analyzed joint kinematics from four-dimensional computed tomography data. The sequential 3D-3D registration method semiautomatically provides the kinematics of the moving bone with respect to the subject bone from four-dimensional computed tomography data.

Four-dimensional computed tomography (4DCT) provides a series of volume data and visualizes joint motions. However, numerical analysis of 4DCT data ...

Bioengineering

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Virtual, hybrid three-dimensional (3D) model acquisition is presented in this article, utilizing the sequence of radiographic image segmentation, spatial registration, and free-form surface modeling. Firstly cone-beam computed tomography datasets were reconstructed with a semi-automatic segmentation method. Alveolar bone and teeth are separated into different segments, allowing 3D morphology, and localization of periodontal intrabony defects to be assessed. The severity, extent, and morphology of acute and chronic alveolar ridge defects are validated concerning adjacent teeth. On virtual complex tissue models, positions of dental implants can be planned in 3D. Utilizing spatial registration of IOS and CBCT data and subsequent free-form surface modeling, realistic 3D hybrid models can be acquired, visualizing alveolar bone, teeth, and soft tissues. With the superimposition of IOS and CBCT soft tissue, thickness above the edentulous ridge can be assessed about the underlying bone dimensions; therefore, flap design and surgical flap management can be determined, and occasional complications may be avoided.

A workflow for creating three-dimensional (3D) virtual hybrid models has been designed based on cone-beam computed tomography dataset and intraoral optical scans utilizing radiographic image segmentation methods and free-form surface modeling. Digital models are used for the virtual planning of reconstructive dentoalveolar surgical procedures.

Virtual, hybrid three-dimensional (3D) model acquisition is presented in this article, utilizing the sequence of radiographic image segmentation, spatial ...

Guided Endodontics: Three-Dimensional Planning and Template-Aided Preparation of Endodontic Access Cavities

Pulp canal obliterations (PCO) are often a consequence of dental trauma, such as luxation injuries. Even though dentin apposition is a sign of vital pulp, pulpitis or apical periodontitis may develop in the long term. Root canal treatment of teeth with severe PCO and pulpal or periapical pathosis is challenging for general practitioners and even for well-equipped endodontic specialists. To ensure detection of the calcified root canal and avoid excessive loss of tooth structure or root perforation, static navigation using templates ("Guided Endodontics") was introduced a few years ago. The general workflow includes three-dimensional imaging using cone-beam computed tomography (CBCT), a digital surface scan, and superimposition of both in a planning software. This is followed by virtual planning of the access cavity and the design of a template that will guide the drill to the desired target point. To do this, a true-to-scale virtual image of the drill must be placed in a way that the tip of the drill reaches the orifice of the calcified root canal. Once the template has been fabricated using computer-aided design and computer-aided manufacturing (CAD/CAM) or a 3D printer, guided preparation of the access cavity can be performed clinically. For research purposes, a postoperative CBCT image can be used to quantify the accuracy of the access cavity performed. This work aims to present the technique of static guided endodontics from imaging to clinical implementation.

Guided endodontics describes a template-aided approach for access cavity preparation. The procedure requires cone-beam computed tomography and a surface scan to produce a template. An incorporated sleeve guides the drill to the target point. This allows the preparation of minimally invasive endodontic access cavities in calcified teeth.

Pulp canal obliterations (PCO) are often a consequence of dental trauma, such as luxation injuries. Even though dentin apposition is a sign of vital pulp, ...

A Finite Element Approach for Locating the Center of Resistance of Maxillary Teeth

The center of resistance (CRES) is regarded as the fundamental reference point for predictable tooth movement. The methods used to estimate the CRES of teeth range from traditional radiographic and physical measurements to in vitro analysis on models or cadaver specimens. Techniques involving finite element analysis of high-dose micro-CT scans of models and single teeth have shown a lot of promise, but little has been done with newer, low-dose, and low resolution cone beam computed tomography (CBCT) images. Also, the CRES for only a few select teeth (i.e., maxillary central incisor, canine, and first molar) have been described; the rest have been largely ignored. There is also a need to describe the methodology of determining the CRES in detail, so that it becomes easy to replicate and build upon.
This study used routine CBCT patient images for developing tools and a workflow to obtain finite element models for locating the CRES of maxillary teeth. The CBCT volume images were manipulated to extract three-dimensional (3D) biological structures relevant in determining the CRES of the maxillary teeth by segmentation. The segmented objects were cleaned and converted into a virtual mesh made up tetrahedral (tet4) triangles having a maximum edge length of 1 mm with 3matic software. The models were further converted into a solid volumetric mesh of tetrahedrons with a maximum edge length of 1 mm for use in finite element analysis. The engineering software, Abaqus, was used to preprocess the models to create an assembly and set material properties, interaction conditions, boundary conditions, and load applications. The loads, when analyzed, simulated the stresses and strains on the system, aiding in locating the CRES. This study is the first step in accurate prediction of tooth movement.

This study outlines the necessary tools for utilizing low-dose three-dimensional cone beam-based patient images of the maxilla and maxillary teeth to obtain finite element models. These patient models are then used to accurately locate the CRES of all the maxillary teeth.

The center of resistance (CRES) is regarded as the fundamental reference point for predictable tooth movement. The methods used to estimate the CRES of ...

Biology

Artificial Intelligence-Based Integration of Dental Images

Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images

This study aimed to introduce cone-beam computed tomography (CBCT) digitization and integration of digital dental images (DDI) based on artificial intelligence (AI)-based registration (ABR) and to evaluate the reliability and reproducibility using this method compared with those of surface-based registration (SBR). This retrospective study consisted of CBCT images and DDI of 17 patients who had undergone computer-aided bimaxillary orthognathic surgery. The digitization of CBCT images and their integration with DDI were repeated using an AI-based program. CBCT images and DDI were integrated using a point-to-point registration. In contrast, with the SBR method, the three landmarks were identified manually on the CBCT and DDI, which were integrated with the iterative closest points method.
After two repeated integrations of each method, the three-dimensional coordinate values of the first maxillary molars and central incisors and their differences were obtained. Intraclass coefficient (ICC) testing was performed to evaluate intra-observer reliability with each method&#39;s coordinates and compare their reliability between the ABR and SBR. The intra-observer reliability showed significant and almost perfect ICC in each method. There was no significance in the mean difference between the first and second registrations in each ABR and SBR and between both methods; however, their ranges were narrower with ABR than with the SBR method. This study shows that AI-based digitization and integration are reliable and reproducible.

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

A process of registering cone-beam computed tomography scans and digital dental images has been presented using artificial intelligence (AI) -assisted identification of landmarks and merging. A comparison with surface-based registration shows that AI-based digitization and integration are reliable and reproducible.