OBJECTIVE: To analyze the fertilization, developmental, and pregnancy potentials in oocytes with narrow perivitelline space.
METHODS: Perivitelline space (PVS) of oocytes was evaluated at the time of ICSI, and those without sufficient PVS were judged as oocytes with narrow PVS (NPVS oocytes), and those with sufficient PVS formation were judged as oocytes with non-narrow PVS (non-NPVS oocytes). The analysis included 634 NPVS oocytes from 278 cycles and 12,121 non-NPVS oocytes from 1698 cycles. The fertilization and developmental potentials of NPVS and non-NPVS oocytes were compared by calculating odds ratios using a mixed-effects logistic regression model. We also compared the embryo transfer outcomes of those used for single vitrified-warmed blastocyst transfer after developing into the blastocyst stage.
RESULTS: NPVS oocytes had higher odds ratios for degeneration (adjusted odds ratio [aOR], 1.555; 95% confidence interval [CI], 1.096-2.206; p = 0.0133) and 0PN (aOR, 1.387; 95% CI, 1.083-1.775; p = 0.0095), resulting in a lower 2PN rate (aOR, 0.761; 95% CI, 0.623-0.929; p = 0.0072). Even embryos with confirmed 2PN had lower odds ratios for cleavage (aOR, 0.501; 95% CI, 0.294-0.853; p = 0.0109) and blastocyst development (Gardner criteria; CC-AA) rates (aOR, 0.612; 95% CI, 0.476-0.788; p = 0.0001). Blastocysts developed from NPVS oocytes had significantly lower odds ratios for clinical pregnancy (aOR, 0.435; 95% CI, 0.222-0.854; p = 0.0156) than those developed from non-NPVS oocytes.
CONCLUSIONS: Oocytes with NPVS have low fertilization and developmental potential, as well as low likelihood of pregnancy.

UNASSIGNED: Mandibulo-Facial Dysostosis with Microcephaly (MFDM) is a rare disease with a broad spectrum of symptoms, characterized by zygomatic and mandibular hypoplasia, microcephaly, and ear abnormalities. Here, we aimed at describing the external ear phenotype of MFDM patients, and train an Artificial Intelligence (AI)-based model to differentiate MFDM ears from non-syndromic control ears (binary classification), and from ears of the main differential diagnoses of this condition (multi-class classification): Treacher Collins (TC), Nager (NAFD) and CHARGE syndromes.
UNASSIGNED: The training set contained 1,592 ear photographs, corresponding to 550 patients. We extracted 48 patients completely independent of the training set, with only one photograph per ear per patient. After a CNN-(Convolutional Neural Network) based ear detection, the images were automatically landmarked. Generalized Procrustes Analysis was then performed, along with a dimension reduction using PCA (Principal Component Analysis). The principal components were used as inputs in an eXtreme Gradient Boosting (XGBoost) model, optimized using a 5-fold cross-validation. Finally, the model was tested on an independent validation set.
UNASSIGNED: We trained the model on 1,592 ear photographs, corresponding to 1,296 control ears, 105 MFDM, 33 NAFD, 70 TC and 88 CHARGE syndrome ears. The model detected MFDM with an accuracy of 0.969 [0.838-0.999] (p < 0.001) and an AUC (Area Under the Curve) of 0.975 within controls (binary classification). Balanced accuracies were 0.811 [0.648-0.920] (p = 0.002) in a first multiclass design (MFDM vs. controls and differential diagnoses) and 0.813 [0.544-0.960] (p = 0.003) in a second multiclass design (MFDM vs. differential diagnoses).
UNASSIGNED: This is the first AI-based syndrome detection model in dysmorphology based on the external ear, opening promising clinical applications both for local care and referral, and for expert centers.

The primary aim of this study was to estimate the prevalence of NTDs at ultrasound examination in communities of Addis Ababa and secondarily to provide a description of the dysmorphology of the NTD cases.
We enrolled 958 pregnant women from 20 randomly selected health centers in Addis Ababa during the period from October 1, 2018, to April 30, 2019. Of these 958 women, 891 had an ultrasound examination after enrollment, with a special focus on NTDs. We estimated the prevalence of NTDs and compared it with previously reported hospital-based birth prevalence estimates from Addis Ababa.
Among 891 women, 13 had twin pregnancies. We identified 15 NTD cases among 904 fetuses, corresponding to an ultrasound-based prevalence of 166 per 10,000 (95% CI: 100-274). There were no NTD cases among the 26 twins. Eleven had spina bifida (122 per 10,000, 95% CI: 67-219). Among the 11 fetuses with spina bifida, three had a cervical and one had a thoracolumbar defect while the anatomical site for 7 was not registered. Seven of the 11 spina bifida defects had skin covering, while two of the cervical lesions were uncovered.
We report a high prevalence of NTDs among pregnancies in communities of Addis Ababa based on screening by ultrasound. The prevalence was higher than in previous hospital-based studies in Addis, and the prevalence of spina bifida was particularly high.

To present the longitudinal MR imaging of 4 children with an acquired corpus callosum hump, in order to demonstrate graphically that this represents a dysmorphology caused through a constellation of pre-existing pathology, timing, and complications of treatment.
Four cases with a corpus callosum hump were evaluated for common findings in the clinical history and on MRI scans. Those patients with available follow-up imaging were specifically evaluated for the presence of the hump on initial neonatal imaging and for evidence of development and progression of the deformity over time. Corpus callosum length was measured and compared against normal standards.
Congenital hydrocephalus, chronic ventricular over-shunting, white matter volume loss, and lateral ventricle communication were common to all cases. Corpus callosum length was above normal values. The corpus callosum hump term was previously described as dysplasia but was not present on initial scans in our cases. We conclude that the corpus callosum hump can be acquired as a complication of over-shunting in children with congenital hydrocephalus. Thus, we present our examples as \"acquired hump of the corpus callosum,\" which differs from the prior example. We postulate that the lengthening of the stretched corpus callosum due to chronic hydrocephalus in the pre-myelinated state renders it unable to return to its normal shape when the ventricles are drained. Over-shunting of both lateral ventricles simultaneously in the absence of a septum pellucidum results in collapse and folding in of the corpus callosum on itself, resulting in the hump.

The field of clinical genetics and genomics continues to evolve. In the past few decades, milestones like the initial sequencing of the human genome, dramatic changes in sequencing technologies, and the introduction of artificial intelligence, have upended the field and offered fascinating new insights. Though difficult to predict the precise paths the field will follow, rapid change may continue to be inevitable. Within genetics, the practice of dysmorphology, as defined by pioneering geneticist David W. Smith in the 1960s as \"the study of, or general subject of abnormal development of tissue form\" has also been affected by technological advances as well as more general trends in biomedicine. To address possibilities, potential, and perils regarding the future of dysmorphology, a group of clinical geneticists, representing different career stages, areas of focus, and geographic regions, have contributed to this piece by providing insights about how the practice of dysmorphology will develop over the next several decades.

Cardinal and non-cardinal dysmorphic features are associated with prenatal alcohol exposure (PAE); however, their association with neurodevelopment is less clear. The objective of this study was to determine whether alcohol-related dysmorphic features predict neurodevelopmental delay in infants and toddlers.
We analyzed a prospective pregnancy cohort in western Ukraine enrolled between 2008 and 2014. A dysmorphology examination comprising body size and three cardinal and 14 non-cardinal dysmorphic features was performed at approximately 6 to 12 months of age. PAE was self-reported and operationalized as absolute ounces of alcohol per day around the time of conception. Neurodevelopment was assessed at 6 to 12 months with the Bayley Scales of Infant Development-II (BSID-II), and at 3.5 to 4.5 years of age with the Differential Ability Scales-II, the Child Behavior Checklist, and multiple measures that were used to create an executive functioning factor score. We performed logistic regression to predict children\'s neurodevelopment from dysmorphic features, growth measures, sex, and PAE.
From an analytic sample of 582 unique children, 566 had BSID-II scores in infancy, and 289 completed the preschool battery. Models with all cardinal and non-cardinal dysmorphic features, growth measures, sex, and PAE performed better than models with subsets of those inputs. In general, models had poor performance classifying delays in infancy (area under the curve (AUC) <0.7) and acceptable performance on preschool-aged outcomes (AUC ~0.75). When the sample was limited to children with moderate-to-high PAE, predictive ability improved on preschool-aged outcomes (AUC 0.76 to 0.89). Sensitivity was relatively low for all models (12% to 63%), although other metrics of performance were higher.
Predictive analysis based on dysmorphic features and measures of growth performed modestly in this sample. As these features are more reliably measured than neurodevelopment at an earlier age, the inclusion of dysmorphic features and measures of growth in predictive models should be further explored and validated in different settings and populations.

Rare diseases can often be diagnosed by carefully assessing the phenotype of the patient, as characteristic deviations (dysmorphisms) occur in many genetic diseases. These affect, for example, the features of the face - the \"facial gestalt.\"This paper highlights an area of artificial intelligence (AI) in which there has been great progress in recent years: the recognition of characteristic patterns in medical image data using deep, convolutional neural networks (next-generation phenotyping - NGP). The technical basis of the method is briefly described and the high relevance of FAIR data for the scientific community to develop AI is discussed. Furthermore, it is explained why decisions made by AI should always remain comprehensible and how it can overcome the challenges with regard to data protection and transparency.In the future, software applications with AI will support medical professionals in the diagnosis of rare diseases. AI will be trustworthy if patients retain their data sovereignty and can understand how the diagnosis was made.
UNASSIGNED: Durch die Analyse des Erscheinungsbildes (Phänotyp) von Patient:innen kann die Diagnostik von Seltenen Erkrankungen unterstützt werden, da bei vielen genetischen Erkrankungen charakteristische Abweichungen (Dysmorphologien) auftreten. Diese betreffen z. B. die Merkmale des Gesichts – die „faziale Gestalt“.In diesem Beitrag wird ein Bereich der künstlichen Intelligenz (KI) beleuchtet, in dem es in den letzten Jahren große Fortschritte gegeben hat: die Erkennung charakteristischer Muster in medizinischen Bilddaten mittels vielschichtiger, gefalteter künstlicher neuronaler Netzwerke (Next-Generation Phenotyping – NGP). Die technischen Grundlagen der Methode werden kurz beschrieben und es wird auf die hohe Relevanz von frei zugänglichen Daten für die Wissenschaftsgemeinschaft zur Entwicklung von KI eingegangen. Des Weiteren wird erläutert, warum Entscheidungen von KI immer nachvollziehbar bleiben sollten und wie es gelingen kann, die Herausforderungen in Hinblick auf Datenschutz und Transparenz zu meistern.Zukünftig können Software-Anwendungen mit KI ärztliche Fachkräfte bei der Diagnostik von Seltenen Erkrankungen unterstützen. Das Vertrauen in den Einsatz von KI wird steigen, wenn Patient:innen ihre Datenhoheit behalten und nachvollziehen können, auf welchem Weg die Diagnose entstanden ist.

An international group of clinicians working in the field of dysmorphology has initiated the standardization of terms used to describe human morphology. The goals are to standardize these terms and reach consensus regarding their definitions. In this way, we will increase the utility of descriptions of the human phenotype and facilitate reliable comparisons of findings among patients. Additional discussions with other workers in dysmorphology and related fields, such as developmental biology and molecular genetics, will become more precise. Here we introduce the anatomy of the trunk and limbs and define and illustrate the terms that describe the major characteristics of these body regions.

UNASSIGNED: Mothers of children with fetal alcohol spectrum disorders tend to have lower weight compared to other mothers. Yet how alcohol and maternal weight may predispose infants to poorer physical growth and neurodevelopmental trajectories is relatively unexplained.
UNASSIGNED: South African mothers (n = 406) were recruited prenatally and their offspring were provided standardized dysmorphology and neurodevelopment examinations at 6 weeks and 9 months of age. Maternal weight was obtained postpartum, and linear mixed modeling determined whether postpartum maternal weight and prenatal alcohol exposure significantly influenced infant growth, dysmorphology, and neurodevelopment within the first year of life.
UNASSIGNED: Postpartum maternal weight was positively associated with birth length, weight, and head circumference centile, but the rate of growth from birth to nine months was similar among all infants. Maternal weight was inversely associated with dysmorphology. Many infants in this population were performing within the borderline or extremely low range. Higher maternal weight was associated with significantly better cognitive and motor performance at 6 weeks; however, the rate of developmental growth was similar among all infants, regardless of postpartum maternal weight.
UNASSIGNED: Higher postpartum maternal weight may be a protective factor but does not eliminate the adverse effects of alcohol on infant growth and dysmorphology. Regardless of maternal weight, alcohol remains a powerful teratogen and moderate to high use prenatally can result in adverse infant physical and neurocognitive development.

This study aims to determine the utility of 3D photography for evaluating the severity of metopic craniosynostosis (MCS) using a validated, supervised machine learning (ML) algorithm.
This single-center retrospective cohort study included patients who were evaluated at our tertiary care center for MCS from 2016 to 2020 and underwent both head CT and 3D photography within a 2-month period.
The analysis method builds on our previously established ML algorithm for evaluating MCS severity using skull shape from CT scans. In this study, we regress the model to analyze 3D photographs and correlate the severity scores from both imaging modalities.
14 patients met inclusion criteria, 64.3% male (n = 9). The mean age in years at 3D photography and CT imaging was 0.97 and 0.94, respectively. Ten patient images were obtained preoperatively, and 4 patients did not require surgery. The severity prediction of the ML algorithm correlates closely when comparing the 3D photographs to CT bone data (Spearman correlation coefficient [SCC] r = 0.75; Pearson correlation coefficient [PCC] r = 0.82).
The results of this study show that 3D photography is a valid alternative to CT for evaluation of head shape in MCS. Its use will provide an objective, quantifiable means of assessing outcomes in a rigorous manner while decreasing radiation exposure in this patient population.