PRINCIPAL COMPONENTS OF THE 180°-TURN WITH THE BALL KINEMATICS IN YOUTH SOCCER PLAYERS

The interpretation of parameters extracted from sophisticated sport-specific techniques is not always straightforward. This is the case of the 180° change of direction with the ball in soccer. The 180°-turn performance of ten Under-13, sub-elite soccer players was recorded by means of a motion capture system. Principal Component Analysis (PCA) was applied to a set of 21 anthropometrics and kinematic variables including center of mass related quantities and joints range of motion. The first three principal components, explaining 61% of the overall variance, were retained and discussed. PCA unveiled the relevant structure of the dataset, describing both movement speed and amplitude issues, and the relationship between body size and the change of direction ability

Registration of dental arch models in 3D facial volumes: an alternative to CBCT acquisitions

Digital 3D models of dental arches and facial soft tissues may constitute an important support for clinicians and maxillofacial surgeons. They can be obtained using a noninvasive and harmless method1 starting from acquisitions made with a dental scanner and a stereophotogrammetric device. The aim of the study was to compare measures taken on the 3D dental and facial models with the ones obtained through a Cone Beam Computed Tomography (CBCT) device in order to evaluate the reliability of the proposed method and its repeatability. Dental and facial data about a population of seven healthy subjects just undergone CBCT have been acquired and registered twice by three operators following a protocol devised for previous works published by this same laboratory2,3. Five craniofacial and six dental landmarks have been taken into account and their linear distances have been calculated. The errors between the corresponding distances in the alternative method and in the CBCT volume have been normalized on the corresponding distance measured on the CBCT model. Statistically significant differences between repetitions and operators were found in the distances between the orbitalis and dental landmarks. We assume that these differences might have been caused by the difficulty in the positioning of the craniofacial soft-tissue landmarks on the CBCT scans. Also the delicate steps for registering the models of the dental arches could have generated errors as it has been suggested by the significant difference between experienced and inexperienced operators. It is advisable to continue the study on more patients in order to obtain a larger data set. It might also be good to consider soft tissue landmarks that are closer to the respective bone tissue ones

Assessment of facial asymmetry using stereophotogrammetry

Asymmetry in the dimensions and spatial position of facial structures is a common finding in healthy individuals and in esthetically pleasing faces (1). Additionally, a variety of craniofacial anomalies are characterized by severe hard- and soft-tissue asymmetry (2). Facial asymmetry can impair the affected people from both aesthetical and functional points of view. Currently, facial asymmetry is mainly evaluated using the entire facial surface, thus providing measurements that give only general information about facial morphology. In contrast, several pathologies affecting facial appearance are localized in selected parts of the face, and a local assessment can provide helpful information for clinical decisions. For these reasons a detailed, focused and objective evaluation of facial asymmetry is advised, both for surgical planning and treatment evaluation. In this study we present a new quantitative method to assess symmetry in different facial thirds, objectively defined on the territories of distribution of trigeminal branches. Forty healthy young adults (21 women; 19 men; average age 39 ± 12 years) were acquired with a stereophotogrammetric system and the level of asymmetry of their hemi-facial thirds was evaluated, comparing the root mean square of the distances (RMSD) between their original and mirrored facial surfaces. The method resulted highly reproducible (Bland and Altman coefficient of reproducibility for area selection, 98.8%). In the upper facial third, median asymmetry was 0.726 mm (IQ range: 0.579-0.954 mm); in the middle facial third, median asymmetry was 0.739 mm (IQ range: 0.558-0.887 mm); in the lower facial third, median asymmetry was 0.679 mm (IQ range: 0.552-0.907 mm). No significant differences in RMSD values among the facial thirds were found (ANOVA, p>0.05). The presented method provides an accurate, reproducible and local facial symmetry analysis, that can be used for different conditions, especially when only part of the face is asymmetric.This work was supported by grants from University of Milan (Grant for Research 2015-2017)

Evaluation of different registration approaches in 3D cephalometric landmark estimation

Thanks to the development of dedicated CBCT scanners, 3D cephalometric analysis is become a widely used tool for the diagnosis and treatment of dentofacial disharmonies in maxillofacial surgery and dentistry [1]. Traditionally, an expert manually annotates a set of cephalometric landmarks on a CBCT scan. Accuracy and repeatability of this manual approach are limited because of intra- and inter-subject variability in landmarks identification [2]. To improve the manual annotation, we are developing a nearly-automatic method that estimates the positions of a set of landmarks registering a previously annotated reference subject to the patient skull. In this study, in order to reduce the estimation error, we compare different registration approaches by varying two registration parameters, such as elasticity (affine or elastic) and domain (local or global) of geometric transformation. The algorithms were tested on 21 CBCT scans of adult caucasian women. To evaluate the outcome of the registration process, Euclidean distances in the 3D space between automatically and manually annotated landmarks were computed. Finally, for each landmark, accuracy and precision of the annotation process were calculated as the mean and standard deviation of the distances of the analyzed sample. Results show that the combination of a global affine registration followed by a global elastic registration significantly reduces the annotation error (p<0.001), increasing both accuracy (p<0.001) and precision (p>0.05). Paired Student’s t tests were used for comparisons. The obtained results are promising, nevertheless the study should be continued in order to reduce further estimation error

The face in Marfan syndrome: a 3D morphometric study

Marfan syndrome (MFS) is a rare congenital disorder of the connective tissue mainly caused by mutations in the FBN1 gene, resulting in an altered assembly of extracellular matrix microfibrils and TGF-beta signalling dysregulation. Major clinical manifestations of MFS involve the skeletal, ocular, and cardiovascular systems, with a high risk of life-threatening aortic dissection and rupture. An early recognition of the disorder is essential, but it could be difficult, due to the variable phenotypic expression of the disease and the current incomplete sensitivity of molecular genetic testing of FBN1. It has been suggested that craniofacial dysmorphism associated with MFS could facilitate obstructive sleep apnea, which in turn may promote aortic dilation. The study aimed to investigate the face in MFS through a 3D not invasive approach [1], identifying new morphometric features which could facilitate the early diagnosis of the disease. The 3D coordinates of 50 anatomical facial landmarks were obtained using a stereophotogrammetric system in 68 Italian subjects diagnosed with MFS, aged 4-64 years (27 males, mean ± SD age 29.6 ± 18.2 years; 41 females, mean ± SD age 37.2 ± 15.5 years). Subjects were divided in 11 non-overlapping age groups. Facial linear distances and angles were measured; z score values were calculated comparing patients with healthy Italian reference subjects (347 males, 388 females), matched for gender and age. Subjects with MFS showed a shorter mandibular ramus than controls (mean z score = -1.9), a greater facial divergence (mean z score = +2.0), a reduced ratio between posterior and anterior facial height (mean z score = -1.9), and a reduced ratio between facial width and facial height (mean z score = -1.5), together with an expected but overall mild increase of facial height (mean z score = +1.3). Noteworthy gender differences or age trends were not observed. Facial abnormalities pointed out in the current study could represent phenotypic traits of MFS; since they were observed also in young patients, their detection could facilitate the early recognition, management, and follow up of the disease. These promising findings need to be confirmed extending the study on more patients

Detection and quantification of breast arterial calcifications on mammograms: a deep learning approach

ObjectiveBreast arterial calcifications (BAC) are a sex-specific cardiovascular disease biomarker that might improve cardiovascular risk stratification in women. We implemented a deep convolutional neural network for automatic BAC detection and quantification.MethodsIn this retrospective study, four readers labelled four-view mammograms as BAC positive (BAC+) or BAC negative (BAC-) at image level. Starting from a pretrained VGG16 model, we trained a convolutional neural network to discriminate BAC+ and BAC- mammograms. Accuracy, F1 score, and area under the receiver operating characteristic curve (AUC-ROC) were used to assess the diagnostic performance. Predictions of calcified areas were generated using the generalized gradient-weighted class activation mapping (Grad-CAM++) method, and their correlation with manual measurement of BAC length in a subset of cases was assessed using Spearman rho.ResultsA total 1493 women (198 BAC+) with a median age of 59 years (interquartile range 52-68) were included and partitioned in a training set of 410 cases (1640 views, 398 BAC+), validation set of 222 cases (888 views, 89 BAC+), and test set of 229 cases (916 views, 94 BAC+). The accuracy, F1 score, and AUC-ROC were 0.94, 0.86, and 0.98 in the training set; 0.96, 0.74, and 0.96 in the validation set; and 0.97, 0.80, and 0.95 in the test set, respectively. In 112 analyzed views, the Grad-CAM++ predictions displayed a strong correlation with BAC measured length (rho = 0.88, p < 0.001).ConclusionOur model showed promising performances in BAC detection and in quantification of BAC burden, showing a strong correlation with manual measurements

Morphometric parameters for nasal septum deviation identification in CBCT data

Advances in the upper airway imaging allow to better evaluate and understand their morphology, pathology and mechanics [1]. In particular, Cone beam CT technology (CBCT), with its isotropic spatial resolution, undistorted images, X-ray lower radiation exposure, versatility and relatively low cost, takes over other imaging modalities [2]. The purpose of this study is to evaluate whether CBCT scans can be valuable tools for the extraction of quantitative parameters to confirm the deviation of the nasal septum in a specific patient. First, we assessed the difference in angle of septal deviation, calculated as proposed by Orhan et al., among a control group and a patient group [3]. Subsequently, we evaluated the percentage difference between the volume of the upper airways in the right side and left side of the nose in the same sample. The measurements were performed on 23 CBCT scans of Caucasian adult women, divided into 7 control subjects and 16 patients. The results demonstrate that there is a significant difference both in the deviation angle (p<0.05) and in the volume difference between healthy and patient subjects (p<0.001). Duplicate measurements of the deviation angle and the volume found no significant difference (p>0.05); random errors explained 0.77% (angle) and 0.99% (volume) of the sample variance. Paired Student’s t tests were used for comparisons. In particular, the volume difference appears to be less sensitive to the presence of isolated cartilaginous ridges that increase the angle of deviation even if the septum is not pathological. This makes it more suited to the identification of this pathology. The obtained outcomes are encouraging and it is advisable to continue the study on a larger sample

Comparison of direct linear measurements on dental plaster cast and digital measurements obtained from laser scanner and Cone-Beam CT dental models

Different dental imaging technologies are now daily used in clinical practice to evaluate oral anatomy. These new techniques allow to replace dental plaster casts with digital models that are easier to manage and store. Such models can be acquired with optical methods like laser scanner, stereophotogrammetry and intraoral scanner or reconstructed by 3D CT or CBCT images [1]. Since these digital casts are used in clinical routine, it is important to evaluate accuracy and reliability of measurements taken from them, in relation to traditional methods [2]. We wanted to compare linear measurements taken on digital models obtained from CBCT images and laser scanner surfaces, with direct measurements obtained with digital calliper on dental plaster casts. Data from 6 adult Caucasian subjects with full dentition, no history of implant surgery and without dental filling were obtained. The absence of implants and metal fillings was selected as inclusion criterion to reduce the presence of metal artefacts that can affect the measurement process. All patients were retrospectively selected from a clinical database and underwent CBCT examination for clinical reasons uncorrelated with this study. Six dental distances in the upper and six in the lower jaw were examined: the mesio-distal distance of teeth 21, 23, 24 and 26, the palatal-vestibular distance of teeth 24 and 26, and the corresponding distances on teeth 41, 43, 44 and 46. All measurements were performed using: 1) a digital calliper on dental plaster casts; 2) a virtual calliper on digital models obtained from CBCT images; and 3) a virtual calliper on laser scanner surfaces. Kruskal-Wallis test compared measurements performed with the 3 different techniques. There was no statistical significant difference among different techniques for all measurements (p>0.05) except for one distance, the mesio-distal distance of tooth 24 (

Evaluation of accuracy and reproducibility in manual point picking during 3D cephalometry on CBCT data

Three-dimensional cephalometry is currently emerging as an innovative diagnos- tic tool, due to accessibility and radiation low dose of Cone Beam CT (CBCT) scan ners (1). Despite annotation made by specialists is now considered the gold standard in clinical practice and research, reliability of manual point picking can be biased by intra and inter-operator differences (2). In order to estimate the variability of the manual procedure, in this study an evaluation of accuracy, precision and reproducibility was performed. Three experienced operators analyzed ten CBCT images, retrospectively selected from the SST Dentofacial Clinic database. They annotated 9 chosen landmarks on all the images for three times, under the same conditions and at least one week of distance. Accuracy and precision were calculated as the median and the interquartile range of the distances from each landmark to the corresponding barycenter, calculated as the mean of all operator annotations. Kruskal-Wallis test was performed to evaluate reproducibility, and post-hoc tests were carried out to assess whether the significance depended from operators. A remarkable difference was found in accuracy between anatomic and geometrical landmarks, in both the intra and inter-operator repetitions. The intra-operator analysis showed higher accuracy and precision values than the inter-operator one. Statistical analyses revealed significant differences in reproducibility (p<0.05) for all landmarks except for Sella turcica, but the post-hoc tests did not show a clear pattern between operators. Results demonstrate that both accuracy and reproducibility may vary, depending on the operators, suggesting the need for automatic or semiautomatic tools that will help the operator during annotation

Inter-observer Variability of Expert-derived Morphologic Risk Predictors in Aortic Dissection

OBJECTIVES: Establishing the reproducibility of expert-derived measurements on CTA exams of aortic dissection is clinically important and paramount for ground-truth determination for machine learning. METHODS: Four independent observers retrospectively evaluated CTA exams of 72 patients with uncomplicated Stanford type B aortic dissection and assessed the reproducibility of a recently proposed combination of four morphologic risk predictors (maximum aortic diameter, false lumen circumferential angle, false lumen outflow, and intercostal arteries). For the first inter-observer variability assessment, 47 CTA scans from one aortic center were evaluated by expert-observer 1 in an unconstrained clinical assessment without a standardized workflow and compared to a composite of three expert-observers (observers 2-4) using a standardized workflow. A second inter-observer variability assessment on 30 out of the 47 CTA scans compared observers 3 and 4 with a constrained, standardized workflow. A third inter-observer variability assessment was done after specialized training and tested between observers 3 and 4 in an external population of 25 CTA scans. Inter-observer agreement was assessed with intraclass correlation coefficients (ICCs) and Bland-Altman plots. RESULTS: Pre-training ICCs of the four morphologic features ranged from 0.04 (-0.05 to 0.13) to 0.68 (0.49-0.81) between observer 1 and observers 2-4 and from 0.50 (0.32-0.69) to 0.89 (0.78-0.95) between observers 3 and 4. ICCs improved after training ranging from 0.69 (0.52-0.87) to 0.97 (0.94-0.99), and Bland-Altman analysis showed decreased bias and limits of agreement. CONCLUSIONS: Manual morphologic feature measurements on CTA images can be optimized resulting in improved inter-observer reliability. This is essential for robust ground-truth determination for machine learning models. KEY POINTS: • Clinical fashion manual measurements of aortic CTA imaging features showed poor inter-observer reproducibility. • A standardized workflow with standardized training resulted in substantial improvements with excellent inter-observer reproducibility. • Robust ground truth labels obtained manually with excellent inter-observer reproducibility are key to develop reliable machine learning models