With the increasing use of magnetic resonance imaging (MRI) in children, radiologists frequently encounter incidental findings that may mimic pathology. One such underrecognized finding is T2-weighted hyperintensity in the superior extraconal orbital fat, which is occasionally mistaken for an infiltrative or neoplastic process. Our objective was to characterize the imaging appearance, prevalence, and clinical associations of superior extraconal orbital fat T2 hyperintensity in pediatric MRI. We conducted a retrospective study of 143 pediatric patients (mean age 7.2±5.1 years) who underwent brain MRI with an orbit-specific protocol between 2015 and 2022. Patients were grouped based on the presence or absence of bilateral papilledema and whether imaging was performed under general anesthesia. Clinical data were extracted from the electronic medical records. Three neuroradiologists reviewed images for the presence of a hyperintense signal along the superior extraconal orbital fat. Interobserver agreement was calculated using Fleiss’ kappa. Univariate and multivariable logistic regression analyses were performed to assess associations with age, anesthesia, gender, and magnet strength. Symmetric T2-hyperintense bands along the superior extraconal orbital fat were observed in 45.5

This article reviews the key concepts in pediatric headaches and provides a guide for neuroimaging assessment of children (≥ 2 years) and adolescents presenting with this chief complaint in both emergent and non-emergent settings. Contemporary imaging approaches (such as upfront utilization of abbreviated brain MR imaging) have been incorporated in the provided flow charts whenever appropriate. Our aim is to improve patient care and clinical outcomes by identifying the cases that need additional examinations and rapidly depicting any underlying serious disease (especially those requiring acute interventions) while at the same time reducing overuse of neuroimaging (especially irradiating CT) and associated risks and costs, thereby contributing to health system efficiency.

The early identification of intracranial aneurysms (IAs) enables risk stratification and the timely initiation of optimal management. This study aimed to identify patients with missed aneurysms for follow-up and possible treatment, and to evaluate the effectiveness of a commercial deep learning algorithm in retrospectively detecting missed IAs on CTA. All consecutive head CTA studies of adult patients performed at a single referral center between February 18, 2020, and July 31, 2022, were retrospectively collected. A machine learning algorithm using natural language processing (NLP) classified radiology reports as positive or negative for aneurysms, and a convolutional neural network (CNN) algorithm analyzed the imaging data. Concordant results with the original reports were accepted as ground truth, while discordant cases were reviewed by three neuroradiologists, with majority voting determining the reference standard. A total of 2,615 head CTA studies were analyzed. the algorithm flagged 34 suspected missed aneurysms, with 67

Single large-scale mitochondrial DNA deletion syndromes (SLSMDSs) are rare mitochondrial disorders that present a continuum of phenotypes, including Pearson syndrome, Kearns-Sayre syndrome, and progressive external ophthalmoplegia. Neuroimaging findings in SLSMDSs are underreported, and their role in diagnosis and disease monitoring remains inadequately defined. This study aims to characterize clinical features and analyze neuroimaging findings, including spectroscopy and diffusion imaging, in patients with SLSMDSs. A retrospective review of 11 patients diagnosed with SLSMDSs at a tertiary referral center between 2013 and 2024 was conducted. Clinical, genetic, and neuroimaging data were analyzed. MRI scans were reviewed for abnormalities in various brain regions, including white matter, basal ganglia, thalami, corpus callosum, cerebellum, and brainstem. The cohort had a mean age of 8.3 years (63.6

We aim to describe the imaging findings in pre-symptomatic and early-symptomatic individuals carrying a recently described novel APP duplication rearrangement causing early-onset AD (EOAD). We studied individuals from one pedigree that carry APP duplication and CH 5 mutation gain that had structural and resting state functional (rs-f) brain MRI. Non-carrier family members were assessed as controls. Volumetric analysis was performed using Freesurfer and normalized to total intracranial volume. Fazekas scores for white matter hyperintensities (WMH) and microbleed count were performed visually by two neuroradiologists. rs-fMRI seed to whole brain analysis was used to create functional connectivity maps of the default mode network (DMN). F18-Flutemetamol amyloid-PET was available for two of the mutation carriers. Amyloid deposition was quantified using SUVR with the pons as reference region and compared to SUVR of young adults and amyloid-positive older adults (Ab+OA). Fourteen mutation carriers (mean age 29.8[19-39], 8 (57%) F, median education 12Y[11-14Y], mean MMSE 28[23-30]), and nine non-carrier family members were included (36.8Y[19-56Y], 5 (55%)F, 12Y[12-19], 29[27-30]). Volumetric analysis revealed an increase in amygdala volume (log) (estimate = 0.01, p = 0.03) and a (non-statistically significant) trend toward decrease in the putamen, globus pallidus, and pons volume with age in mutation carriers (Figure 1A). WMHs and microbleeds were found in some mutation carriers from the age of 28Y (Figure 1B). rs-fMRI showed a trend toward a disconnection between the anterior and the posterior component of the DMN in the APP-dup carriers >30Y (n = 6) compared with non-carrier (n = 8; U = 10, p = 0.08). Moreover, increased connectivity was found between the anterior component of the DMN and the striatum compared to carriers <30Y (n = 8, U = 9, p = 0.06) and to non-carriers (U = 9, p = 0.06) (Figure 2). Cortical amyloid deposition was high but within the range of Ab+OA, and extremely high, above the level of deposition in Ab+OA in the putamen, caudate, and thalamus (Figure 3). We found early basal ganglia abnormalities in presymptomatic and early symptomatic novel APP duplication mutation carriers, including high amyloid deposition, DMN disconnection, increased connectivity between anterior DMN and striatum, and volumetric alterations. These findings point to the basal ganglia as a region of early pathology that requires further research.

Amyloid beta (Aβ) deposition marks an early stage in the progression of Alzheimer's disease (AD), detectable in-vivo years before symptoms emerge and targeted by recently FDA-approved drugs. This has propelled advancements in understanding, measuring, and treating AD, paving the way for disease prevention in those at risk. However, the psychological impact of disclosing Aβ status to cognitively unimpaired individuals remains underexplored. Our study aimed to evaluate the behavioral responses to Aβ status disclosure in this population. Two observational studies and two clinical trials incorporating Aβ-PET were conducted, involving research participants who received information on Aβ-PET scans, results, and interpretation. Questionnaires were administered before the scan and four-to-six months post-disclosure to assess anxiety, depression, subjective memory complaints, and motivation for risk-reduction behaviors. Bivariate analysis and mixed models were employed to analyze responses, with logistic regression used to identify predictors of unfavorable responses to negative scan disclosure. Among 178 participants with amyloid-negative scans (mean age 64, 57% females) and 21 with amyloid-positive scans (mean age 77, 38% females), no significant pre-scan differences were observed. Negative amyloid disclosure correlated with reductions in all domains tested, including memory complaints, depression, anxiety, and motivation to change lifestyle (p≤0.001). Positive amyloid disclosure also resulted in decreases, particularly in anxiety and depression, albeit to a lesser extent and with greater variability (0.007<p<0.07 for pre to post PET change in amyloid positives vs. negatives). Higher education was linked to fewer memory complaints post-negative Aβ PET disclosure (Odds ratio=0.79, CI=0.65-0.97, p=0.02). In conclusion, as AD enters an era of disease-modifying and preventive treatments, understanding how cognitively normal adults respond to AD biomarker status disclosure becomes crucial. Negative amyloid results offer a comforting effect, reflected in reduced subjective memory concerns and lower anxiety, depression, and motivation for lifestyle changes. However, caution is needed to prevent false reassurance. Positive amyloid results also provide comfort, albeit to a lesser extent and with more variability. Lower education levels may predict unfavorable responses to negative amyloid disclosures.

Neurodegeneration with brain iron accumulation (NBIA) refers to a group of rare genetic disorders characterized by abnormal iron deposition in the basal ganglia and brainstem due to impaired iron homeostasis. Disease severity and manifestations vary according to the underlying genetic mutation and age of presentation; however, most subtypes share progressive neurological features such as dystonia, Parkinsonism, spasticity, cognitive decline, and intellectual disability. In this review, we first outline the physiological role of iron in the central nervous system, emphasizing its importance for neurotransmitter synthesis, myelination, and mitochondrial metabolism, and discuss how disruption of homeostatic mechanisms may lead to ferroptosis and neuronal injury. We then explore the role of neuroimaging in the diagnosis of NBIA, with a focus on MRI as the modality of choice. Finally, we provide an overview of the clinical and imaging features of the major NBIA subtypes, highlighting both shared characteristics and distinctive patterns. Covered NBIA include primary disorders of iron metabolism, such as neuroferritinopathy and aceruloplasminemia, and secondary disorders with disrupted iron regulation, including Pantothenate Kinase-Associated Neurodegeneration, Phospholipase A2 Group VI-Associated Neurodegeneration, Mitochondrial Membrane Protein-Associated Neurodegeneration, Beta-Propeller Protein-Associated Neurodegeneration, Fatty Acid Hydroxylase-Associated Neurodegeneration, Coenzyme A Synthetase Protein-Associated Neurodegeneration, Woodhouse-Sakati syndrome, and Kufor-Rakeb Disease. By integrating genetics, pathophysiology, and imaging, this review aims to improve recognition of NBIA and support comprehensive clinical management.

BACKGROUND:The central vein sign (CVS), detected through susceptibility-sensitive MRI sequences, is increasingly recognized as a reliable biomarker distinguishing Multiple Sclerosis from mimickers. However, variability in MRI protocols limits reproducibility and clinical integration. PURPOSE:To systematically review susceptibility-sensitive MRI protocols used in CVS research, aiming to identify standardized approaches and improve reproducibility. DATA SOURCES:A comprehensive search was performed in PubMed/MEDLINE, Scopus, and Web of Science, and the reference lists of pertinent meta-analyses. STUDY SELECTION:Original English-language studies on brain MRI CVS detection in MS, neuroinflammatory conditions and common mimickers, excluding non-original research and non-English articles. Studies were selected following PRISMA guidelines. Ultimately, 94 studies were included in the final review. DATA ANALYSIS:MRI sequence types and parameters were systematically extracted and analyzed. DATA SYNTHESIS:Susceptibility-weighted imaging (SWI), 3D T2* EPI, and SWAN were commonly used, with considerable variability in imaging parameters. Many studies did not report essential protocol specifics, limiting reproducibility and comparability across studies. Comparative data on SWI versus 3D T2* EPI at standard clinical field strengths (1.5T and 3T MRI) remain insufficient, creating uncertainty about which sequence provides superior sensitivity for CVS detection. LIMITATIONS:Variability in study designs, exclusion of non-English studies, and potential publication bias. CONCLUSIONS:There is substantial variability in MRI protocols for CVS detection, emphasizing the need for standardization. Further research comparing susceptibility-sensitive sequences is needed. Establishing standardized MRI protocols is essential for reliably integrating the CVS into routine clinical practice, particularly in anticipation of its inclusion in the forthcoming revision of the McDonald criteria.

Background: Measuring brain volume changes over time is an objective and dependable surrogate marker for the pathological processes that damage the brain in relapsing-remitting multiple sclerosis (RRMS). These measures are particularly valuable for monitoring the long-term impact of immunomodulatory treatments such as cladribine.Objectives: To evaluate the long-term impact of oral cladribine treatment on brain volume loss in patients with RRMS.Methods: This real-world study processed magnetic resonance imaging (MRI) scans using FreeSurfer's recon-all-clinical pipeline leveraging SynthSeg for brain segmentation. Piecewise linear regression was used to analyze brain atrophy changes over 4.5 years before and after cladribine treatment and estimate the time breakpoint of atrophy rate change.Results: A total of 448 MRI exams from 102 RRMS patients were analyzed. Before the initiation of cladribine treatment, brain atrophy rates were significantly steep with an alpha 1 slope between -1.27 and -0.62 for the Thalamus, DGM, Subcortical GM, Cerebral WM, and BP. Over 2 years after treatment, breakpoints marked a shift in atrophy rates, with post-breakpoint slopes (alpha 2) becoming non-significant, reflecting stabilization of brain atrophy.Conclusions: Cladribine treatment in highly active RRMS patients protects the brain from atrophy, with stabilization occurring over 2 years after initiation. The extended observation period highlights its sustained benefits compared with shorter clinical trials.

Detection and prediction of the rate of brain volume loss with age is a significant unmet need in patients with primary progressive multiple sclerosis (PPMS). In this study we construct detailed brain volume maps for PPMS patients. These maps compare age-related changes in both cortical and sub-cortical regions with those in healthy individuals. We conducted retrospective analyses of brain volume using T1-weighted Magnetic Resonance Imaging (MRI) scans of a large cohort of PPMS patients and healthy subjects. The volume of brain parenchyma (BP), cortex, white matter (WM), deep gray matter, thalamus, and cerebellum were measured using the robust SynthSeg segmentation tool. Age- and gender-related regression curves were constructed based on data from healthy subjects, with the 95

Quantitative MRI (qMRI) has been shown to be clinically useful for numerous applications in the brain and body. The development of rapid, accurate, and reproducible qMRI techniques offers access to new multiparametric data, which can provide a comprehensive view of tissue pathology. This work introduces a multiparametric qMRI protocol along with full postprocessing pipelines, optimized for brain imaging at 3 Tesla and using state-of-the-art qMRI tools. The total scan time is under 50 minutes and includes eight pulse-sequences, which produce range of quantitative maps including T1, T2, and T2* relaxation times, magnetic susceptibility, water and macromolecular tissue fractions, mean diffusivity and fractional anisotropy, magnetization transfer ratio (MTR), and inhomogeneous MTR. Practical tips and limitations of using the protocol are also provided and discussed. Application of the protocol is presented on a cohort of 28 healthy volunteers and 12 brain regions-of-interest (ROIs). Quantitative values agreed with previously reported values. Statistical analysis revealed low variability of qMRI parameters across subjects, which, compared to intra-ROI variability, was x4.1 ± 0.9 times higher on average. Significant and positive linear relationship was found between right and left hemispheres’ values for all parameters and ROIs with Pearson correlation coefficients of r>0.89 (P<0.001), and mean slope of 0.95 ± 0.04. Finally, scan-rescan stability demonstrated high reproducibility of the measured parameters across ROIs and volunteers, with close-to-zero mean difference and without correlation between the mean and difference values (across map types, mean P value was 0.48 ± 0.27). The entire quantitative data and postprocessing scripts described in the manuscript are publicly available under dedicated GitHub and Figshare repositories. The quantitative maps produced by the presented protocol can promote longitudinal and multi-center studies, and improve the biological interpretability of qMRI by integrating multiple metrics that can reveal information, which is not apparent when examined using only a single contrast mechanism.

The predominant technique for quantifying myelin content in the white matter is multicompartment analysis of MRI’s T2 relaxation times (mcT2 analysis). The process of resolving the T2 spectrum at each voxel, however, is highly ill-posed and remarkably susceptible to noise and to inhomogeneities of the transmit field (B1+). To address these challenges, we employ a preprocessing stage wherein a spatially global data-driven analysis of the tissue is performed to identify a set of mcT2 configurations (motifs) that best describe the tissue under investigation, followed by using this basis set to analyze the signal in each voxel. This procedure is complemented by a new algorithm for correcting B1+ inhomogeneities, lending the overall fitting process with improved robustness and reproducibility. Successful validations are presented using numerical and physical phantoms vs. ground truth, showcasing superior fitting accuracy and precision compared with conventional (non-data-driven) fitting. In vivo application of the technique is presented on 26 healthy subjects and 29 people living with multiple sclerosis (MS), revealing substantial reduction in myelin content within normal-appearing white matter regions of people with MS (i.e., outside obvious lesions), and confirming the potential of data-driven myelin values as a radiological biomarker for MS.

Diabetes is associated with cognitive decline, but the underlying mechanisms are complex and their relationship with Alzheimer’s Disease biomarkers is not fully understood. We assessed the association of small vessel disease (SVD) and amyloid burden with cognitive functioning in 47 non-demented older adults with type-2 diabetes from the Israel Diabetes and Cognitive Decline Study (mean age 78Y, 64% females). FLAIR-MRI, Vizamyl amyloid-PET, and T1W-MRI quantified white matter hyperintensities as a measure of SVD, amyloid burden, and gray matter (GM) volume, respectively. Mean hemoglobin A1c levels and duration of type-2 diabetes were used as measures of diabetic control. Cholesterol level and blood pressure were used as measures of cardiovascular risk. A broad neuropsychological battery assessed cognition. Linear regression models revealed that both higher SVD and amyloid burden were associated with lower cognitive functioning. Additional adjustments for type-2 diabetes-related characteristics, GM volume, and cardiovascular risk did not alter the results. The association of amyloid with cognition remained unchanged after further adjustment for SVD, and the association of SVD with cognition remained unchanged after further adjustment for amyloid burden. Our findings suggest that SVD and amyloid pathology may independently contribute to lower cognitive functioning in non-demented older adults with type-2 diabetes, supporting a multimodal approach for diagnosing, preventing, and treating cognitive decline in this population.

BACKGROUND:Pediatric brain cancer survivors often experience hypothalamic-pituitary dysfunction due to cranial irradiation and chemotherapy. While hormone deficiencies have been studied, the changes in pituitary size and shape on long-term MRI and their relationship to endocrine dysfunction remain under-explored. PURPOSE:To evaluate pituitary gland height, volume, and shape in relation to long-term endocrine abnormalities in pediatric brain tumor survivors. STUDY TYPE:Retrospective cohort study. POPULATION:A total of 56 pediatric brain tumor survivors (50% male) with an average follow-up of 10.8 ± 1.6 years; 44.6% underwent radiotherapy, and 48% were treated with chemotherapy. One-third of the cohort experienced at least one pituitary hormone deficiency. FIELD STRENGTH/SEQUENCE:3 T, including volumetric 1 mm sagittal post-contrast T1 images. ASSESSMENT:Pituitary height, volume, and shape (concave, horizontal, convex) were measured. Endocrine abnormalities were diagnosed through routine serum hormone testing. STATISTICAL TESTS:The t test, chi-square test, and Pearson test with significance at P < 0.05 were used. Receiver-operating characteristic (ROC) analysis assessed the association of imaging parameters and pituitary dysfunction. RESULTS:Radiation and chemotherapy treatment were significantly associated with pituitary hormone deficiencies. There were significant differences in pituitary height and volume in patients with pituitary hormone deficiencies compared with normal pituitary function (4.0 ± 1.3 vs. 5.5 ± 1.5 mm, and 354.2 ± 198.0 vs. 568.3 ± 184.4 mm3, respectively). There was a significant association between radiation therapy and pituitary gland shape, with 60.0% of patients who received radiation therapy exhibiting a pituitary shape categorized as concave, 32.0% as horizontal, and 8.0% as convex, compared to 9.7%, 74.2%, and 16.1%, respectively. ROC analysis for association with pituitary hormone deficiency was 0.81, 0.8, and 0.74 for pituitary height, volume, and shape, respectively. DATA CONCLUSION:Cranial irradiation and chemotherapy in pediatric brain tumors are associated with endocrine dysfunction, with decreased pituitary height, volume, and concave shape in long-term MRI surveillance are associated with such late endocrine dysfunction. LEVEL OF EVIDENCE:4 TECHNICAL EFFICACY: Stage 2.

Background and purpose: Multiple studies demonstrated hypothalamic-pituitary dysfunction in survivors of pediatric brain tumors. However, few studies investigated the trajectories of pituitary height in these patients and their associations with pituitary function. We aimed to evaluate longitudinal changes of pituitary height in children and adolescents with brain tumors, and their association with endocrine deficiencies. Materials and methods: We conducted a retrospective analysis of 193 pediatric patients (54.9% male) diagnosed with brain tumors from 2002 to 2018, with a minimum of two years of radiological follow-up. Pituitary height was measured using MRI scans at diagnosis and at 2, 5, and 10 years post-diagnosis, with clinical data sourced from patient charts. Results: Average age at diagnosis was 7.6 +/- 4.5 years, with a follow-up of 6.1 +/- 3.4 years. 52.8% underwent radiotherapy and 37.8% experienced pituitary hormone deficiency. Radiation treatment was a significant predictor of decreased pituitary height at all observed time points (p = 0.016, p < 0.001, p = 0.008, respectively). Additionally, chemotherapy (p = 0.004) or radiotherapy (p = 0.022) history and pituitary height at 10 years (p = 0.047) were predictors of endocrine deficiencies. ANOVA revealed an expected increase in pituitary height over time in pediatric patients, but this growth was significantly impacted by radiation treatment and gender (p for interaction = 0.005 and 0.025, respectively). Conclusion: Cranial irradiation in pediatric patients is associated with impairment of the physiologic increase in pituitary size; in turn, decreased pituitary height is associated with endocrine dysfunction. We suggest that pituitary gland should be evaluated on surveillance imaging of pediatric brain tumor survivors, and if small for age, clinical endocrine evaluation should be pursued.

Background:Differential diagnosis in radiology relies on the accurate identification of imaging patterns. The use of large language models (LLMs) in radiology holds promise, with many potential applications that may enhance the efficiency of radiologists' workflow. The study aimed to evaluate the efficacy of generative pre-trained transformer (GPT)-4, a LLM, in providing differential diagnoses in neuroradiology, comparing its performance with board-certified neuroradiologists. Methods:Sixty neuroradiology reports with variable diagnoses were inserted into GPT-4, which was tasked with generating a top-3 differential diagnosis for each case. The results were compared to the true diagnoses and to the differential diagnoses provided by three blinded neuroradiologists. Diagnostic accuracy and agreement between readers were assessed. Results:Of the 60 patients (mean age 47.8 years, 65% female), GPT-4 correctly included the diagnoses in its differentials in 61.7% (37/60) of cases, while the neuroradiologists' accuracy ranged from 63.3% (38/60) to 73.3% (44/60). Agreement between GPT-4 and the neuroradiologists, and among the neuroradiologists was fair to moderate [Cohen's kappa (kw) 0.34-0.44 and kw 0.39-0.54, respectively]. Conclusions:GPT-4 shows potential as a support tool for differential diagnosis in neuroradiology, though it was outperformed by human experts. Radiologists should remain mindful to the limitations of LLMs, while harboring their potential to enhance educational and clinical work.

As pregnancy progresses, the germinal matrix volume decreases. Residual periventricular germinal matrix may be mistaken for hypoxic-ischemic white matter injury. This study aims to determine the prevalence and imaging characteristics of these findings. This retrospective study analyzed brain MRIs of newborns from 2012–2023, performed within the first week of life. MRIs were done for suspected hypoxic-ischemic injuries, post-natal neurological symptoms, and evaluation of prenatally diagnosed structural anomalies. Image analysis targeted the remnants of the frontal periventricular germinal matrix, assessing its imaging characteristics, including diffusion, T1, and T2 signal characteristics, and laterality. Frontal migrating cell bands were also assessed. Seventy newborns were included (mean gestational age at delivery was 38.3 ± 2.1 weeks, mean scan age 5.1 ± 1.9 days). Frontal periventricular gray matter was detected in 39 newborns (90

An association between subtle changes in T2 white matter hyper-intense signals (WMHSs) detected in fetal brain magnetic resonance imaging (fbMRI) and congenital cytomegalovirus (CMV) infection has been established. The research aim of this study is to compare children with congenital CMV infection with neurodevelopment outcome and hearing deficit with and without WMHSs in a historic prospective case study cohort of 58 fbMRIs. Of these, in 37 cases, fbMRI was normal (normal group) and WMHSs were detected in 21 cases (WMHS group). The median infection week of the WMHS group was earlier than the normal fbMRI group (8 and 17 weeks of gestation, respectively). The proportion of infants treated with valganciclovir in the WMHS group was distinctly higher. Hearing impairment was not significantly different between the groups. VABS scores in all four domains were within normal range in both groups. The median score of the motor skills corrected for week of infection was better in the WMHS group. A multivariate analysis using the week of infection interaction variable of WMHS and valganciclovir treatment showed better motor score outcomes in the valganciclovir treatment group despite an earlier week of infection. WMHSs were not associated with neurodevelopmental outcome and hearing deficit. In our cohort, valganciclovir treatment may have a protective effect on fetuses with WMHSs by improving neurodevelopmental outcome.

Purpose Abnormal fetal brain measurements might affect clinical management and parental counseling. The effect of between-field-strength differences was not evaluated in quantitative fetal brain imaging until now. Our study aimed to compare fetal brain biometry measurements in 3.0 T with 1.5 T scanners. Methods A retrospective cohort of 1150 low-risk fetuses scanned between 2012 and 2021, with apparently normal brain anatomy, were retrospectively evaluated for biometric measurements. The cohort included 1.5 T (442 fetuses) and 3.0 T scans (708 fetuses) of populations with comparable characteristics in the same tertiary medical center. Manually measured biometry included bi-parietal, fronto-occipital and trans-cerebellar diameters, length of the corpus-callosum, vermis height, and width. Measurements were then converted to centiles based on previously reported biometric reference charts. The 1.5 T centiles were compared with the 3.0 T centiles. Results No significant differences between centiles of bi-parietal diameter, trans-cerebellar diameter, or length of the corpus callosum between 1.5 T and 3.0 T scanners were found. Small absolute differences were found in the vermis height, with higher centiles in the 3.0 T, compared to the 1.5 T scanner (54.6th-centile, vs. 39.0th-centile, p < 0.001); less significant differences were found in vermis width centiles (46.9th-centile vs. 37.5th-centile, p = 0.03). Fronto-occipital diameter was higher in 1.5 T than in the 3.0 T scanner (66.0th-centile vs. 61.8th-centile, p = 0.02). Conclusions The increasing use of 3.0 T MRI for fetal imaging poses a potential bias when using 1.5 T-based charts. We elucidate those biometric measurements are comparable, with relatively small between-field-strength differences, when using manual biometric measurements. Small inter-magnet differences can be related to higher spatial resolution with 3 T scanners and may be substantial when evaluating small brain structures, such as the vermis.