Accuracy of 3D cephalometric measurements based on an automatic knowledge-based landmark detection algorithm

PURPOSE: To evaluate the accuracy of three-dimensional cephalometric measurements obtained through an automatic landmark detection algorithm compared to those obtained through manual identification. METHODS: The study demonstrates a comparison of 51 cephalometric measurements (28 linear, 16 angles and 7 ratios) on 30 CBCT (cone beam computed tomography) images. The analysis was performed to compare measurements based on 21 cephalometric landmarks detected automatically and those identified manually by three observers. RESULTS: Inter-observer ICC for each landmark was found to be excellent ([Formula: see text]) among three observers. The unpaired t-test revealed that there was no statistically significant difference in the measurements based on automatically detected and manually identified landmarks. The difference between the manual and automatic observation for each measurement was reported as an error. The highest mean error in the linear and angular measurements was found to be 2.63 mm ([Formula: see text] distance) and [Formula: see text] ([Formula: see text]-Me angle), respectively. The highest mean error in the group of distance ratios was 0.03 (for N-Me/N-ANS and [Formula: see text]). CONCLUSION: Cephalometric measurements computed from automatic detection of landmarks on 3D CBCT image were as accurate as those computed from manual identification

Automatic Landmark Identification in Lateral Cephalometric Images Using Optimized Template Matching

Cephalometric analysis has long helped researchers and orthodontic practitioners for evaluation of facial growth, understanding facial morphology and its ethnic variations, orthodontic diagnosis and treatment planning for patients presenting with malocclusion and dentofacial deformities. Mostly, inaccuracy in cephalometric measurements is a reflection of errors in identification and accurate localization of anatomical landmarks. The accuracy of landmark identification is greatly influenced by knowledge of the operator and experience. Moreover, the process of manual detection is tedious and time consuming. Therefore, a need for development of robust and accurate algorithms for automatic detection of landmarks on cephalometric images has been comprehended. In this work, we hereby propose an optimized template matching (OTM) algorithm which could automatically localize hard and soft tissue anatomical landmarks on lateral cephalometric images. This algorithm was tested for sixteen hard and eight soft tissue landmarks chosen in 12 regions on 37 lateral cephalograms obtained from subjects of either sex covering wide spectrum of malocclusion cases. The results of proposed automatic algorithm were compared to that of manual marking conducted by three experienced orthodontic specialists. All the 24 landmarks (100%) were detected within 3.0 mm error range of manual marking, 23 (96%) were detected within 2.5 mm error range and 16 (66.6%) landmarks were detected within 2.0 mm error range. The optimized template matching (OTM) algorithm may prove to be a promising approach in automatic detection of anatomical landmarks on cephalometric images

Craniofacial and upper airway morphology in adult obstructive sleep apnea patients: A systematic review and meta-analysis of cephalometric studies

Obstructive sleep apnea (OSA) is one of the common sleep breathing disorders in adults, characterised by frequent episodes of upper airway collapse during sleep. Craniofacial disharmony is an important risk factor for OSA. Overnight polysomnography (PSG) study is considered to be the most reliable confirmatory investigation for OSA diagnosis, whereas the precise localization of site of obstruction to the airflow cannot be detected. Identifying the cause of OSA in a particular ethnic population/individual subject helps to understand the etiological factors and effective management of OSA. The objective of the meta-analysis is to elucidate altered craniofacial anatomy on lateral cephalograms in adult subjects with established OSA. Significant weighted mean difference with insignificant heterogeneity was found for the following parameters: anterior lower facial height (ALFH: 2.48 mm), position of hyoid bone (Go-H: 5.45 mm, S–H: 6.89 mm, GoGn-H: 11.84°, GoGn-H: 7.22 mm, N–S–H: 2.14°), and pharyngeal airway space (PNS-Phw: −1.55 mm, pharyngeal space: −495.74 mm2 and oro-pharyngeal area: −151.15 mm2). Significant weighted mean difference with significant heterogeneity was found for the following parameters: cranial base (SN: −2.25 mm, S–N–Ba: −1.45°), position and length of mandible (SNB: −1.49° and Go-Me: −5.66 mm) respectively, maxillary length (ANS-PNS: −1.76 mm), tongue area (T: 366.51 mm2), soft palate area (UV: 125.02 mm2), and upper airway length (UAL: 5.39 mm). This meta-analysis supports the relationship between craniofacial disharmony and obstructive sleep apnea. There is a strong evidence for reduced pharyngeal airway space, inferiorly placed hyoid bone and increased anterior facial heights in adult OSA patients compared to control subjects. The cephalometric analysis provides insight into anatomical basis of the etiology of OSA that can influence making a choice of appropriate therapy

A pilot study for segmentation of pharyngeal and sino-nasal airway subregions by automatic contour initialization

Purpose The objective of the present study is to put forward a novel automatic segmentation algorithm to segment pharyngeal and sino-nasal airway subregions on 3D CBCT imaging datasets. Methods A fully automatic segmentation of sino-nasal and pharyngeal airway subregions was implemented in MATLAB programing environment. The novelty of the algorithm is automatic initialization of contours in upper airway subregions. The algorithm is based on boundary definitions of the human anatomy along with shape constraints with an automatic initialization of contours to develop a complete algorithm which has a potential to enhance utility at clinical level. Post-initialization; five segmentation techniques: Chan-Vese level set (CVL), localized Chan-Vese level set (LCVL), Bhattacharya distance level set (BDL), Grow Cut (GC), and Sparse Field method (SFM) were used to test the robustness of automatic initialization. Results Precision and F-score were found to be greater than 80% for all the regions with all five segmentation methods. High precision and low recall were observed with BDL and GC techniques indicating an under segmentation. Low precision and high recall values were observed with CVL and SFM methods indicating an over segmentation. A Larger F-score value was observed with SFM method for all the subregions. Minimum F-score value was observed for naso-ethmoidal and sphenoidal air sinus region, whereas a maximum F-score was observed in maxillary air sinuses region. The contour initialization was more accurate for maxillary air sinuses region in comparison with sphenoidal and naso-ethmoid regions. Conclusion The overall F-score was found to be greater than 80% for all the airway subregions using five segmentation techniques, indicating accurate contour initialization. Robustness of the algorithm needs to be further tested on severely deformed cases and on cases with different races and ethnicity for it to have global acceptance in Katradental radKatraiology workflow

The reliability of different methods of manual volumetric segmentation of pharyngeal and sinonasal subregions

Objectives The purpose of the study was to test the intra and interobserver reliability of manual volumetric segmentation of pharyngeal and sinonasal airway subregions. Study Design Cone beam computed tomography data of 15 patients were collected from an orthodontic clinical database. Two experienced orthodontists independently performed manual segmentation of the airway subregions. Four performance measures were considered to test intra and interobserver reliability of manual segmentation: (1) volume correlation, (2) mean slice correlation, (3) percentage of volume difference, and (4) percentage of nonoverlapping voxels. Results Intra and interobserver reliability was observed to be greater than 0.96 for the entire pharyngeal and sinonasal airway sinus subregions by both observers using the volume correlation method. Mean slice correlation was found to be greater than 0.84, showing the existence of nonoverlapping voxels. Therefore, the percentage of nonoverlapping voxels was used as a reliability measure and was found to be less than 20% for both intra and interobserver markings. Conclusions The mean slice correlation and percentage of nonoverlapping voxels were the most reliable performance measures of segmentation correctness. Volume correlation and the percentage of volume difference were observed to be the most reliable performance measures for volume correctness

Insights from a pan India sero-epidemiological survey (Phenome-india cohort) for SARS-CoV2.

To understand the spread of SARS-CoV2, in August and September 2020, the Council of Scientific and Industrial Research (India) conducted a serosurvey across its constituent laboratories and centers across India. Of 10,427 volunteers, 1058 (10.14%) tested positive for SARS-CoV2 anti-nucleocapsid (anti-NC) antibodies, 95% of which had surrogate neutralization activity. Three-fourth of these recalled no symptoms. Repeat serology tests at 3 (n = 607) and 6 (n = 175) months showed stable anti-NC antibodies but declining neutralization activity. Local seropositivity was higher in densely populated cities and was inversely correlated with a 30-day change in regional test positivity rates (TPRs). Regional seropositivity above 10% was associated with declining TPR. Personal factors associated with higher odds of seropositivity were high-exposure work (odds ratio, 95% confidence interval, p value: 2.23, 1.92–2.59, <0.0001), use of public transport (1.79, 1.43–2.24, <0.0001), not smoking (1.52, 1.16–1.99, 0.0257), non-vegetarian diet (1.67, 1.41–1.99, <0.0001), and B blood group (1.36, 1.15–1.61, 0.001)

Integrating Health Care Delivery and Data Collection in Rural India Using a Rapidly Deployable eHealth Center

<p>Integrating Health Care Delivery and Data Collection in Rural India Using a Rapidly Deployable eHealth Center</p

Human genetic factors associated with pneumonia risk, a cue for COVID-19 susceptibility

: Pneumonia, an acute respiratory tract infection, is one of the major causes of mortality worldwide. Depending on the site of acquisition, pneumonia can be community acquired pneumonia (CAP) or nosocomial pneumonia (NP). The risk of pneumonia, is partially driven by host genetics. CYP1A1 is a widely studied pulmonary CYP family gene primarily expressed in peripheral airway epithelium. The CYP1A1 genetic variants, included in this study, alter the gene activity and are known to contribute in lung inflammation, which may cause pneumonia pathogenesis. In this study, we performed a meta-analysis to establish the possible contribution of CYP1A1 gene, and its three variants (rs2606345, rs1048943 and rs4646903) towards the genetic etiology of pneumonia risk. Using PRISMA guidelines, we systematically reviewed and meta-analysed case-control studies, evaluating risk of pneumonia in patients carrying the risk alleles of CYP1A1 variants. Heterogeneity across the studies was evaluated using I2 statistics. Based on heterogeneity, a random-effect (using maximum likelihood) or fixed-effect (using inverse variance) model was applied to estimate the effect size. Pooled odds ratio (OR) was calculated to estimate the overall effect of the risk allele association with pneumonia susceptibility. Egger's regression test and funnel plot were used to assess publication bias. Subgroup analysis was performed based on pneumonia type (CAP and NP), population, as well as age group. A total of ten articles were identified as eligible studies, which included 3049 cases and 2249 healthy controls. The meta-analysis findings revealed CYP1A1 variants, rs2606345 [T vs G; OR = 1.12 (0.75-1.50); p = 0.02; I2 = 84.89%], and rs1048943 [G vs T; OR = 1.19 (0.76-1.61); p = 0.02; I2 = 0.00%] as risk markers whereas rs4646903 showed no statistical significance for susceptibility to pneumonia. On subgroup analysis, both the genetic variants showed significant association with CAP but not with NP. We additionally performed a spatial analysis to identify the key factors possibly explaining the variability across countries in the prevalence of the coronavirus disease 2019 (COVID-19), a viral pneumonia. We observed a significant association between the risk allele of rs2606345 and rs1048943, with a higher COVID-19 prevalence worldwide, providing us important links in understanding the variability in COVID-19 prevalence

Layout of the eHC.

<p>Two 20×8 feet containers were used in the proof-of-concept eHC. The telemedicine container (left) has provision for a small laboratory. The second container (top) is used for registration and pharmacy and also has space for a future minor operation theatre. The telemedicine container can be used by itself for basic eHC operations. Pictures of the deployment, exterior, and interior of the telemedicine container are shown.</p

Details of Utilization of the eHealth Center.

<p>Number of registrations and visits are stratified by gender, age, and frequency of repeat visits.</p>a<p>Percentage of total subjects of indicated gender for each age group.</p>b<p>Percentage of total subjects of indicated gender and age-group with repeat visits.</p