Automated landmarking for palatal shape analysis using geometric deep learning.

OBJECTIVES: To develop and evaluate a geometric deep-learning network to automatically place seven palatal landmarks on digitized maxillary dental casts. SETTINGS AND SAMPLE POPULATION: The sample comprised individuals with permanent dentition of various ethnicities. The network was trained from manual landmark annotations on 732 dental casts and evaluated on 104 dental casts. MATERIALS AND METHODS: A geometric deep-learning network was developed to hierarchically learn features from point-clouds representing the 3D surface of each cast. These features predict the locations of seven palatal landmarks. RESULTS: Repeat-measurement reliability was <0.3 mm for all landmarks on all casts. Accuracy is promising. The proportion of test subjects with errors less than 2 mm was between 0.93 and 0.68, depending on the landmark. Unusually shaped and large palates generate the highest errors. There was no evidence for a difference in mean palatal shape estimated from manual compared to the automatic landmarking. The automatic landmarking reduces sample variation around the mean and reduces measurements of palatal size. CONCLUSIONS: The automatic landmarking method shows excellent repeatability and promising accuracy, which can streamline patient assessment and research studies. However, landmark indications should be subject to visual quality control.

Quantitative 3D Shape Analysis of CT Images of Thymoma: A Comparison With Histological Types.

OBJECTIVE. The purpose of this study is to differentiate between low- and high-risk types of thymoma using quantitative 3D shape analysis of CT images. MATERIALS AND METHODS. This retrospective study included 44 patients with a pathologic diagnosis of thymoma. Two radiologists semiautomatically contoured CT images of the tumors and evaluated 3D shape parameters-namely, quantitative indicators of surface smoothness, including sphericity, ellipsoidality, and discrete compactness. The visual CT findings that were analyzed included longest diameter, shape (round-oval, lobulated, or irregular), calcification, cystic or necrotic changes, and enhancement pattern (homogeneous or heterogeneous). The difference and discriminating performance between low-risk (types A, AB, and B1) and high-risk (types B2 and B3) thymomas were statistically assessed. Interobserver agreement was determined using the concordance correlation coefficient. RESULTS. Twenty-three low-risk and 21 high-risk thymomas were identified on the basis of pathologic findings. The median values of sphericity and ellipsoidality were significantly higher for low-risk thymomas than for high-risk thymomas (for sphericity, 0.566 vs 0.517; for ellipsoidality, 0.941 vs 0.875; p < 0.05 for both). The AUC values of sphericity and ellipsoidality were 0.704 and 0.712, respectively. The best cutoff values were 0.528 and 0.919 for sphericity and ellipsoidality, respectively. Risk assessment combining these cutoff values and the mode of tumor detection (incidental detection or detection based on the presence of symptoms) improved the AUC value to 0.856 (sensitivity, 81.0% [17 of 21 patients]; specificity, 82.6% [19 of 23 patients]). All 3D shape parameters showed almost perfect interobserver agreement (concordance correlation coefficient, > 0.90). The visual CT findings were not significantly different between low- and high-risk thymomas (p > 0.05 for all). CONCLUSION. Quantitative 3D shape analysis has excellent reproducibility, and combining this technique with information on the detection mode helps differentiate low- from high-risk thymomas.

Analyzing infant head flatness and asymmetry using kernel density estimation of directional surface data from a craniofacial 3D model.

Infant skull deformation is analyzed using the distribution of head normal vector directions computed from a 3D image. Severity of flatness and asymmetry are quantified by functionals of the kernel estimate of the normal vector direction density. Using image data from 99 infants and clinical deformation ratings made by experts, our approach is compared with some recently suggested methods. The results show that the proposed method performs competitively. Copyright © 2016 John Wiley & Sons, Ltd.

A statistical shape modelling framework to extract 3D shape biomarkers from medical imaging data: assessing arch morphology of repaired coarctation of the aorta.

BACKGROUND: Medical image analysis in clinical practice is commonly carried out on 2D image data, without fully exploiting the detailed 3D anatomical information that is provided by modern non-invasive medical imaging techniques. In this paper, a statistical shape analysis method is presented, which enables the extraction of 3D anatomical shape features from cardiovascular magnetic resonance (CMR) image data, with no need for manual landmarking. The method was applied to repaired aortic coarctation arches that present complex shapes, with the aim of capturing shape features as biomarkers of potential functional relevance. The method is presented from the user-perspective and is evaluated by comparing results with traditional morphometric measurements. METHODS: Steps required to set up the statistical shape modelling analyses, from pre-processing of the CMR images to parameter setting and strategies to account for size differences and outliers, are described in detail. The anatomical mean shape of 20 aortic arches post-aortic coarctation repair (CoA) was computed based on surface models reconstructed from CMR data. By analysing transformations that deform the mean shape towards each of the individual patient's anatomy, shape patterns related to differences in body surface area (BSA) and ejection fraction (EF) were extracted. The resulting shape vectors, describing shape features in 3D, were compared with traditionally measured 2D and 3D morphometric parameters. RESULTS: The computed 3D mean shape was close to population mean values of geometric shape descriptors and visually integrated characteristic shape features associated with our population of CoA shapes. After removing size effects due to differences in body surface area (BSA) between patients, distinct 3D shape features of the aortic arch correlated significantly with EF (r = 0.521, p = .022) and were well in agreement with trends as shown by traditional shape descriptors. CONCLUSIONS: The suggested method has the potential to discover previously unknown 3D shape biomarkers from medical imaging data. Thus, it could contribute to improving diagnosis and risk stratification in complex cardiac disease.

Lead-oriented synthesis: Investigation of organolithium-mediated routes to 3-D scaffolds and 3-D shape analysis of a virtual lead-like library.

Synthetic routes to six 3-D scaffolds containing piperazine, pyrrolidine and piperidine cores have been developed. The synthetic methodology focused on the use of N-Boc α-lithiation-trapping chemistry. Notably, suitably protected and/or functionalised medicinal chemistry building blocks were synthesised via concise, connective methodology. This represents a rare example of lead-oriented synthesis. A virtual library of 190 compounds was then enumerated from the six scaffolds. Of these, 92 compounds (48%) fit the lead-like criteria of: (i) -1⩽AlogP⩽3; (ii) 14⩽number of heavy atoms⩽26; (iii) total polar surface area⩾50Å(2). The 3-D shapes of the 190 compounds were analysed using a triangular plot of normalised principal moments of inertia (PMI). From this, 46 compounds were identified which had lead-like properties and possessed 3-D shapes in under-represented areas of pharmaceutical space. Thus, the PMI analysis of the 190 member virtual library showed that whilst scaffolds which may appear on paper to be 3-D in shape, only 24% of the compounds actually had 3-D structures in the more interesting areas of 3-D drug space.

ShapeAXI: Shape Analysis Explainability and Interpretability.

ShapeAXI represents a cutting-edge framework for shape analysis that leverages a multi-view approach, capturing 3D objects from diverse viewpoints and subsequently analyzing them via 2D Convolutional Neural Networks (CNNs). We implement an automatic N-fold cross-validation process and aggregate the results across all folds. This ensures insightful explainability heat-maps for each class across every shape, enhancing interpretability and contributing to a more nuanced understanding of the underlying phenomena. We demonstrate the versatility of ShapeAXI through two targeted classification experiments. The first experiment categorizes condyles into healthy and degenerative states. The second, more intricate experiment, engages with shapes extracted from CBCT scans of cleft patients, efficiently classifying them into four severity classes. This innovative application not only aligns with existing medical research but also opens new avenues for specialized cleft patient analysis, holding considerable promise for both scientific exploration and clinical practice. The rich insights derived from ShapeAXI's explainability images reinforce existing knowledge and provide a platform for fresh discovery in the fields of condyle assessment and cleft patient severity classification. As a versatile and interpretative tool, ShapeAXI sets a new benchmark in 3D object interpretation and classification, and its groundbreaking approach hopes to make significant contributions to research and practical applications across various domains. ShapeAXI is available in our GitHub repository https://github.com/DCBIA-OrthoLab/ShapeAXI.

Feasibility of Using Laser Imaging Detection and Ranging Technology for Contactless 3D Body Scanning and Anthropometric Assessment of Athletes.

The scope of this pilot study was to assess the feasibility of using the laser imaging detection and ranging (LiDAR) technology for contactless 3D body scanning of sports athletes and deriving anthropometric measurements of the lower limbs using available software. An Apple iPad Pro 3rd Generation with embedded LiDAR technology in combination with the iOS application Polycam were used. The effects of stance width, clothing, background, lighting, scan distance and measurement speed were initially assessed by scanning the lower limbs of one test person multiple times. Following these tests, the lower limbs of 12 male and 10 female participants were scanned. The resulting scans of the lower limbs were complete for half of the participants and categorized as good in quality, while the other scans were either distorted or presented missing data around the shank and/or the thigh. Bland-Altman plots between the LiDAR-based and manual anthropometric measures showed good agreement, with the coefficient of determination from correlation analysis being R2 = 0.901 for thigh length and R2 = 0.830 for shank length, respectively. The outcome of this pilot study is considered promising, and a further refinement of the proposed scanning protocol and advancement of available software for 3D reconstruction are recommended to exploit the full potential of the LiDAR technology for the contactless anthropometric assessment of athletes.

An Exploration of Pathologies of Multilevel Principal Components Analysis in Statistical Models of Shape.

3D facial surface imaging is a useful tool in dentistry and in terms of diagnostics and treatment planning. Between-group PCA (bgPCA) is a method that has been used to analyse shapes in biological morphometrics, although various "pathologies" of bgPCA have recently been proposed. Monte Carlo (MC) simulated datasets were created here in order to explore "pathologies" of multilevel PCA (mPCA), where mPCA with two levels is equivalent to bgPCA. The first set of MC experiments involved 300 uncorrelated normally distributed variables, whereas the second set of MC experiments used correlated multivariate MC data describing 3D facial shape. We confirmed results of numerical experiments from other researchers that indicated that bgPCA (and so also mPCA) can give a false impression of strong differences in component scores between groups when there is none in reality. These spurious differences in component scores via mPCA decreased significantly as the sample sizes per group were increased. Eigenvalues via mPCA were also found to be strongly affected by imbalances in sample sizes per group, although this problem was removed by using weighted forms of covariance matrices suggested by the maximum likelihood solution of the two-level model. However, this did not solve problems of spurious differences between groups in these simulations, which was driven by very small sample sizes in one group. As a "rule of thumb" only, all of our experiments indicate that reasonable results are obtained when sample sizes per group in all groups are at least equal to the number of variables. Interestingly, the sum of all eigenvalues over both levels via mPCA scaled approximately linearly with the inverse of the sample size per group in all experiments. Finally, between-group variation was added explicitly to the MC data generation model in two experiments considered here. Results for the sum of all eigenvalues via mPCA predicted the asymptotic amount for the total amount of variance correctly in this case, whereas standard "single-level" PCA underestimated this quantity.

Missing and murdered indigenous women and girls in Canada: a new population affinity assessment technique to aid in identification using 3D technology.

As of 2015, 204 cases of missing and murdered Indigenous women and girls (MMIWG) remained unsolved in Canada, making it a major concern for Canadian Indigenous communities, who are still pressing for the resolution of these cases. In forensic anthropology, the assessment of population affinity can be useful to help identify victims. Population affinity, previously referred to as ancestry, is evaluated based on morphological analyses, which examine the size and shape of skeletal features, and metric analyses, which utilise skeletal measurements. However, morphological analyses strongly depend on an anthropologist's experience with human variation, which makes the analyses particularly challenging to reproduce and standardise. The purpose of this study is to improve the rigour of morphological analyses by using 3D technology to quantify relevant cranial nonmetric population affinity traits. As there is currently little morphological data available for the Canadian Indigenous population, this research aims to develop a new technique that could aid in the identification of MMIWG. The study comprised a total of 87 adult female crania, including 24 of Canadian Inuit origin, 50 of European descent and 13 of African descent. The samples were imaged using photogrammetry, then analysed using a 3D shape analysis in 3DS Max. Results show that this method is satisfactory in correctly evaluating population affinity with an accuracy of 87.36% (jackknifed: 80.46%) and an average repeatability of 97%. Unfortunately, the small Canadian Indigenous sample size impacted the applicability of the results and further research will be required before the technique can be used to aid in the identification of MMIWG in Canada.

Understanding and Improving Risk Assessment After Myocardial Infarction Using Automated Left Ventricular Shape Analysis.

BACKGROUND: Left ventricular ejection fraction (LVEF) and end-systolic volume (ESV) remain the main imaging biomarkers for post-acute myocardial infarction (AMI) risk stratification. However, they are limited to global systolic function and fail to capture functional and anatomical regional abnormalities, hindering their performance in risk stratification. OBJECTIVES: This study aimed to identify novel 3-dimensional (3D) imaging end-systolic (ES) shape and contraction descriptors toward risk-related features and superior prognosis in AMI. METHODS: A multicenter cohort of AMI survivors (n = 1,021; median age 63 years; 74.5% male) who underwent cardiac magnetic resonance (CMR) at a median of 3 days after infarction were considered for this study. The clinical endpoint was the 12-month rate of major adverse cardiac events (MACE; n = 73), consisting of all-cause death, reinfarction, and new congestive heart failure. A fully automated pipeline was developed to segment CMR images, build 3D statistical models of shape and contraction in AMI, and find the 3D patterns related to MACE occurrence. RESULTS: The novel ES shape markers proved to be superior to ESV (median cross-validated area under the receiver-operating characteristic curve 0.681 [IQR: 0.679-0.684] vs 0.600 [IQR: 0.598-0.602]; P < 0.001); and 3D contraction to LVEF (0.716 [IQR: 0.714-0.718] vs 0.681 [IQR: 0.679-0.684]; P < 0.001) in MACE occurrence prediction. They also contributed to a significant improvement in a multivariable setting including CMR markers, cardiovascular risk factors, and basic patient characteristics (0.747 [IQR: 0.745-0.749]; P < 0.001). Based on these novel 3D descriptors, 3 impairments caused by AMI were identified: global, anterior, and basal, the latter being the most complementary signature to already known predictors. CONCLUSIONS: The quantification of 3D differences in ES shape and contraction, enabled by a fully automated pipeline, improves post-AMI risk prediction and identifies shape and contraction patterns related to MACE occurrence.

Subject-Specific Calculation of Left Atrial Appendage Blood-Borne Particle Residence Time Distribution in Atrial Fibrillation.

Atrial fibrillation (AF) is the most common arrhythmia that leads to thrombus formation, mostly in the left atrial appendage (LAA). The current standard of stratifying stroke risk, based on the CHA2DS2-VASc score, does not consider LAA morphology, and the clinically accepted LAA morphology-based classification is highly subjective. The aim of this study was to determine whether LAA blood-borne particle residence time distribution and the proposed quantitative index of LAA 3D geometry can add independent information to the CHA2DS2-VASc score. Data were collected from 16 AF subjects. Subject-specific measurements included left atrial (LA) and LAA 3D geometry obtained by cardiac computed tomography, cardiac output, and heart rate. We quantified 3D LAA appearance in terms of a novel LAA appearance complexity index (LAA-ACI). We employed computational fluid dynamics analysis and a systems-based approach to quantify residence time distribution and associated calculated variable (LAA mean residence time, t m) in each subject. The LAA-ACI captured the subject-specific LAA 3D geometry in terms of a single number. LAA t m varied significantly within a given LAA morphology as defined by the current subjective method and it was not simply a reflection of LAA geometry/appearance. In addition, LAA-ACI and LAA t m varied significantly for a given CHA2DS2-VASc score, indicating that these two indices of stasis are not simply a reflection of the subjects' clinical status. We conclude that LAA-ACI and LAA t m add independent information to the CHA2DS2-VASc score about stasis risk and thereby can potentially enhance its ability to stratify stroke risk in AF patients.

3D + Time Imaging and Image Reconstruction of Pectoral Fin During Zebrafish Embryogenesis.

Morphogenesis is the fundamental developmental process during which the embryo body is formed. Proper shaping of different body parts depends on cellular divisions and rearrangements in the growing embryo. Understanding three-dimensional shaping of organs is one of the basic questions in developmental biology. Here, we consider the early stages of pectoral fin development in zebrafish, which serves as a model for limb development in vertebrates, to study emerging shapes during embryogenesis. Most studies on pectoral fin are concerned with late stages of fin development when the structure is morphologically distinct. However, little is known about the early stages of pectoral fin formation because of the experimental difficulties in establishing proper imaging conditions during these stages to allow long-term live observation. In this protocol, we address the challenges of pectoral fin imaging during the early stages of zebrafish embryogenesis and provide a strategy for three-dimensional shape analysis of the fin. The procedure outlined here is aimed at studying pectoral fin during the first 24 h of its formation corresponding to the time period between 24 and 48 h of zebrafish development. The same principles could also be applied when studying three-dimensional shape establishment of other embryonic structures. We first discuss the imaging procedure and then propose strategies of extracting quantitative information regarding fin shape and dimensions.

Three-dimensional analysis of regional right ventricular shape and function in repaired tetralogy of Fallot using cardiovascular magnetic resonance.

BACKGROUND: Patients with surgically repaired tetralogy of Fallot (rTOF) often have residual pulmonic valve regurgitation, leading to abnormal remodeling and dysfunction of the right ventricle often requiring pulmonic valve replacement. We tested the hypothesis that 3D analysis of right ventricular (RV) shape and function may reveal differences in regional adaptive remodeling that occurs in patients with rTOF, depending on whether a transannular patch (TAP) was utilized. METHODS: Forty patients with rTOF who underwent cardiac magnetic resonance imaging (1.5 T), including 20 with and 20 without TAP, and 10 normal controls were studied. Images were analyzed to measure RV endocardial curvature and global and regional volume and function. RESULTS: RV ejection fraction (EF) was 42 ±â€¯11% in TAP and 38 ±â€¯9% in no-TAP (p = 0.19), both lower than 54 ±â€¯3% in controls (p < 0.01). Left ventricular (LV) EF was 54 ±â€¯9% in TAP, 54 ±â€¯8% in no-TAP (p = 0.87) and 61 ±â€¯16% in controls (both p < 0.01). Indexed LV end-diastolic volumes were higher in no-TAP than in TAP subgroup (p = 0.02). With TAP, mid RV septum showed lower curvature during diastole (less convex), than the mid and apical free walls and free wall adjacent to the RV outflow tract (RVOT; more convex). There were no differences in curvature during systole between rTOF subgroups but mid and RVOT free walls showed higher curvature versus controls. CONCLUSIONS: This is the first study to comprehensively describe the influence of TAP on changes in regional RV shape in patients with rTOF. Understanding these differences may help guide therapeutic options for residual pulmonary valve regurgitation in rTOF patients.

Development of user customized smart keyboard using Smart Product Design-Finite Element Analysis Process in the Internet of Things.

In a hyper-connected society, IoT environment, markets are rapidly changing as smartphones penetrate global market. As smartphones are applied to various digital media, development of a novel smart product is required. In this paper, a Smart Product Design-Finite Element Analysis Process (SPD-FEAP) is developed to adopt fast-changing tends and user requirements that can be visually verified. The user requirements are derived and quantitatively evaluated from Smart Quality Function Deployment (SQFD) using WebData. Then the usage scenarios are created according to the priority of the functions derived from SQFD. 3D shape analysis by Finite Element Analysis (FEA) was conducted and printed out through Rapid Prototyping (RP) technology to identify any possible errors. Thus, a User Customized Smart Keyboard has been developed using SPD-FEAP.

Associations between hippocampal morphology, diffusion characteristics, and salivary cortisol in older men.

High, unabated glucocorticoid (GC) levels are thought to selectively damage certain tissue types. The hippocampus is thought to be particularly susceptible to such effects, and though findings from animal models and human patients provide some support for this hypothesis, evidence for associations between elevated GCs and lower hippocampal volumes in older age (when GC levels are at greater risk of dysregulation) is inconclusive. To address the possibility that the effects of GCs in non-pathological ageing may be too subtle for gross volumetry to reliably detect, we analyse associations between salivary cortisol (diurnal and reactive measures), hippocampal morphology and diffusion characteristics in 88 males, aged ∼73 years. However, our results provide only weak support for this hypothesis. Though nominally significant peaks in morphology were found in both hippocampi across all salivary cortisol measures (standardised ß magnitudes<0.518, puncorrected>0.0000003), associations were both positive and negative, and none survived false discovery rate correction. We found one single significant association (out of 12 comparisons) between a general measure of hippocampal diffusion and reactive cortisol slope (ß=0.290, p=0.008) which appeared to be driven predominantly by mean diffusivity but did not survive correction for multiple testing. The current data therefore do not clearly support the hypothesis that elevated cortisol levels are associated with subtle variations in hippocampal shape or microstructure in non-pathological older age.