Neural differentiation, synaptic transmission, and action potential propagation depend on membrane sphingolipids, whose metabolism is tightly regulated. Mutations in the ceramide transporter CERT (CERT1), which is involved in sphingolipid biosynthesis, are associated with intellectual disability, but the pathogenic mechanism remains obscure. Here, we characterize 31 individuals with de novo missense variants in CERT1. Several variants fall into a previously uncharacterized dimeric helical domain that enables CERT homeostatic inactivation, without which sphingolipid production goes unchecked. The clinical severity reflects the degree to which CERT autoregulation is disrupted, and inhibiting CERT pharmacologically corrects morphological and motor abnormalities in a Drosophila model of the disease, which we call ceramide transporter (CerTra) syndrome. These findings uncover a central role for CERT autoregulation in the control of sphingolipid biosynthetic flux, provide unexpected insight into the structural organization of CERT, and suggest a possible therapeutic approach for patients with CerTra syndrome.

The recent development of highly undersampled radial gradient echo sequences in combination with nonlinear inverse image reconstruction now allows for MRI examinations in real time. Image acquisition times as short as 20 ms yield MRI videos with rates of up to 50 frames per second with spin density, T1- and T2-type contrast. The addition of an initial 180° inversion pulse achieves accurate T1 mapping within only 4 s. These technical advances promise specific advantages for studies of infants and young children by eliminating the need for sedation or anesthesia. Our preliminary data demonstrate new diagnostic opportunities ranging from dynamic studies of speech and swallowing processes and body movements to a rapid volumetric assessment of brain cerebrospinal fluid spaces in only few seconds. Real-time MRI of the heart and blood flow can be performed without electrocardiogram gating and under free breathing. The present findings support the idea that real-time MRI will complement existing methods by providing long-awaited diagnostic options for patients in early childhood. Major advantages are the avoidance of sedation or anesthesia and the yet unexplored potential to gain insights into arbitrary body functions.

Background: Quantitative mapping of MRI relaxation times is expected to uncover pathological processes in the brain more subtly than standard MRI techniques with weighted contrasts. So far, however, most mapping techniques suffer from a long measuring time, low spatial resolution or even sensitivity to magnetic field inhomogeneity. Objective: To obtain T1 relaxation times of the normal brain from early infancy to adulthood using a novel technique for fast and accurate T1 mapping at high spatial resolution. Materials and methods: We performed whole-brain T1 mapping within less than 3 min in 100 patients between 2 months and 18 years of age with normal brain at a field strength of 3 T. We analyzed T1 relaxation times in several gray-matter nuclei and white matter. Subsequently, we derived regression equations for mean value and confidence interval. Results: T1 relaxation times of the pediatric brain rapidly decrease in all regions within the first 3 years of age, followed by a significantly weaker decrease until adulthood. These characteristics are more pronounced in white matter than in deep gray matter. Conclusion: Regardless of age, quantitative T1 mapping of the pediatric brain is feasible in clinical practice. Normal age-dependent values should contribute to improved discrimination of subtle intracerebral alterations.

Objectives: This study aimed to evaluate the performance of an artificial intelligence (AI)-based software for fracture detection in pediatric patients within a real-life clinical setting. Specifically, it sought to assess (1) the stand-alone AI performance in real-life cohort and in selected set of medicolegal relevant fractures and (2) its influence on the diagnostic performance of inexperienced emergency room physicians. Materials and methods: The retrospective study involved 1672 radiographs of children under 18 years, obtained consecutively (real-life cohort) and selective (medicolegal cohort) in a tertiary pediatric emergency department. On these images, the stand-alone performance of a commercially available, deep learning-based software was determined. Additionally, three pediatric residents independently reviewed the radiographs before and after AI assistance, and the impact on their diagnostic accuracy was assessed. Results: In our cohort (median age 10.9 years, 59% male), the AI demonstrated a sensitivity of 92%, specificity of 83%, and accuracy of 87%. For medicolegally relevant fractures, the AI achieved a sensitivity of 100% for proximal tibia fractures, but only 68% for radial condyle fractures. AI assistance improved the residents’ patient-wise sensitivity from 84 to 87%, specificity from 91 to 92%, and diagnostic accuracy from 88 to 90%. In 2% of cases, the readers, with the assistance of AI, erroneously discarded their correct diagnosis. Conclusion: The AI exhibited strong stand-alone performance in a pediatric setting and can modestly enhance the diagnostic accuracy of inexperienced physicians. However, the economic implications must be weighed against the potential benefits in patient safety. Key Points: Question Does an artificial intelligence-based software for fracture detection influence inexperienced physicians in a real-life pediatric trauma population? Findings Addition of a well-performing artificial intelligence-based software led to a limited increase in diagnostic accuracy of inexperienced human readers. Clinical relevance Diagnosing fractures in children is especially challenging for less experienced physicians. High-performing artificial intelligence-based software as a “second set of eyes,” enhances diagnostic accuracy in a common pediatric emergency room setting. Graphical

Objectives: This study aimed to evaluate the performance of artificial intelligence (AI) software in bone age (BA) assessment, according to the Greulich and Pyle (G&P) method in a German pediatric cohort. Materials and methods: Hand radiographs of 306 pediatric patients aged 1–18 years (153 boys, 153 girls, 18 patients per year of life)—including a subgroup of patients in the age group for which the software is declared (243 patients)—were analyzed retrospectively. Two pediatric radiologists and one endocrinologist made independent blinded BA reads. Subsequently, AI software estimated BA from the same images. Both agreements, accuracy, and interchangeability between AI and expert readers were assessed. Results: The mean difference between the average of three expert readers and AI software was 0.39 months with a mean absolute difference (MAD) of 6.8 months (1.73 months for the mean difference and 6.0 months for MAD in the intended use subgroup). Performance in boys was slightly worse than in girls (MAD 6.3 months vs. 5.6 months). Regression analyses showed constant bias (slope of 1.01 with a 95% CI 0.99–1.02). The estimated equivalence index for interchangeability was − 14.3 (95% CI −27.6 to − 1.1). Conclusion: In terms of BA assessment, the new AI software was interchangeable with expert readers using the G&P method. Clinical relevance statement: The use of AI software enables every physician to provide expert reader quality in bone age assessment. Key Points: • A novel artificial intelligence–based software for bone age estimation has not yet been clinically validated. • Artificial intelligence showed a good agreement and high accuracy with expert radiologists performing bone age assessment. • Artificial intelligence showed to be interchangeable with expert readers.

To compare contrast-enhanced magnetic resonance angiography (ceMRA) and 3D steady-state free precession (SSFP) during systole and diastole for assessment of the right ventricle outflow tract (RVOT) in patients considered for percutaneous pulmonary valve implantation (PPVI) after tetralogy of Fallot (TOF) repair. We retrospectively evaluated 89 patients (male: 45, mean age 19 ± 8 years), who underwent cardiac-MRI after surgical TOF-repair. Datasets covering the whole heart in systole and diastole were acquired using ECG-gated 3D SSFP and non-gated ceMRA. Measurements were performed in SSFP-sequences and in ceMRA in the narrowest region of the RVOT to obtain the minimum, maximum and effective diameter. Invasive balloon sizing as the gold standard was available in 12 patients. The minimum diameter in diastolic SSFP, systolic SSFP and ceMRA were 21.4 mm (± 6.1 mm), 22.6 mm (± 6.2 mm) and 22.6 mm (± 6.0 mm), respectively. Maximum diameter was 29.9 mm (± 9.5 mm), 30.0 mm (± 7.0 mm) and 28.8 mm (± 8.1 mm) respectively. The effective diameter was 23.2 mm (± 5.7 mm), 27.4 mm (± 6.7 mm) and 24.4 mm (± 6.2 mm), differing significantly between diastole and systole (p < 0.0001). Measurements in ECG-gated SSFP showed a better inter- and intraobserver variability compared to measurements in non-ECG-gated ceMRA. Comparing invasive balloon sizing with our analysis, we found the highest correlation coefficients for the maximum and effective diameter measured in systolic SSFP (R = 0.99 respectively). ECG-gated 3D SSFP enables the identification and characterization of a potential landing zone for PPVI. The maximum and effective systolic diameter allow precise sizing for PPVI. Patients with TOF-repair could benefit from cardiac MRI before PPVI.