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While research has unveiled and quantified brain markers of abnormal neurodevelopment, clinicians still work with qualitative metrics for MRI brain investigation. The purpose of the current article is to bridge the knowledge gap between case-control cohort studies and individual patient care. Here, we provide a unique dataset of seventy-three 3-to-17 years-old healthy subjects acquired with a 6-minute MRI protocol encompassing T1 and T2 relaxation quantitative sequence that can be readily implemented in the clinical setting; MP2RAGE for T1 mapping and the prototype sequence GRAPPATINI for T2 mapping. White matter and grey matter volumes were automatically quantified. We further provide normative developmental curves based on these two imaging sequences; T1, T2 and volume normative ranges with respect to age were computed, for each ROI of a pediatric brain atlas. This open-source dataset provides normative values allowing to position individual patients acquired with the same protocol on the brain maturation curve and as such provides potentially useful quantitative biomarkers facilitating precise and personalized care. [ABSTRACT FROM AUTHOR]

Objectives: Microstructural characterization of patients with multiple sclerosis (MS) has been shown to correlate better with disability compared to conventional radiological biomarkers. Quantitative MRI provides effective means to characterize microstructural brain tissue changes both in lesions and normal-appearing brain tissue. However, the impact of the location of microstructural alterations in terms of neuronal pathways has not been thoroughly explored so far. Here, we study the extent and the location of tissue changes probed using quantitative MRI along white matter (WM) tracts extracted from a connectivity atlas. Methods: We quantified voxel-wise T1 tissue alterations compared to normative values in a cohort of 99 MS patients. For each WM tract, we extracted metrics reflecting tissue alterations both in lesions and normal-appearing WM and correlated these with cross-sectional disability and disability evolution after 2 years. Results: In early MS patients, T1 alterations in normal-appearing WM correlated better with disability evolution compared to cross-sectional disability. Further, the presence of lesions in supratentorial tracts was more strongly associated with cross-sectional disability, while microstructural alterations in infratentorial pathways yielded higher correlations with disability evolution. In progressive patients, all major WM pathways contributed similarly to explaining disability, and correlations with disability evolution were generally poor. Conclusions: We showed that microstructural changes evaluated in specific WM pathways contribute to explaining future disability in early MS, hence highlighting the potential of tract-wise analyses in monitoring disease progression. Further, the proposed technique allows to estimate WM tract-specific microstructural characteristics in clinically compatible acquisition times, without the need for advanced diffusion imaging. [ABSTRACT FROM AUTHOR]

Purpose: Studies at 3T have shown that T1 relaxometry enables characterization of brain tissues at the single‐subject level by comparing individual physical properties to a normative atlas. In this work, an atlas of normative T1 values at 7T is introduced with 0.6 mm isotropic resolution and its clinical potential is explored in comparison to 3T. Methods: T1 maps were acquired in two separate healthy cohorts scanned at 3T and 7T. Using transfer learning, a template‐based brain segmentation algorithm was adapted to ultra‐high field imaging data. After segmenting brain tissues, volumes were normalized into a common space, and an atlas of normative T1 values was established by modeling the T1 inter‐subject variability. A method for single‐subject comparisons restricted to white matter and subcortical structures was developed by computing Z‐scores. The comparison was applied to eight patients scanned at both field strengths for proof of concept. Results: The proposed method for morphometry delivered segmentation masks without statistically significant differences from those derived with the original pipeline at 3T and achieved accurate segmentation at 7T. The established normative atlas allowed characterizing tissue alterations in single‐subject comparisons at 7T, and showed greater anatomical details compared with 3T results. Conclusion: A high‐resolution quantitative atlas with an adapted pipeline was introduced and validated. Several case studies on different clinical conditions showed the feasibility, potential and limitations of high‐resolution single‐subject comparisons based on quantitative MRI atlases. This method in conjunction with 7T higher resolution broadens the range of potential applications of quantitative MRI in clinical practice. [ABSTRACT FROM AUTHOR]

Objectives: This study introduced a tailored MP2RAGE-based brain acquisition for a comprehensive assessment of the normal maturing brain. Methods: Seventy normal patients (35 girls and 35 boys) from 1 to 16 years of age were recruited within a prospective monocentric study conducted from a single University Hospital. Brain MRI examinations were performed at 1.5 T using a 20-channel head coil and an optimized 3D MP2RAGE sequence with a total acquisition time of 6:36 min. Automated 38 region segmentation was performed using the MorphoBox (template registration, bias field correction, brain extraction, and tissue classification) which underwent a major adaptation of three age-group T1-weighted templates. Volumetry and T1 relaxometry reference ranges were established using a logarithmic model and a modified Gompertz growth respectively. Results: Detailed automated brain segmentation and T1 mapping were successful in all patients. Using these data, an age-dependent model of normal brain maturation with respect to changes in volume and T1 relaxometry was established. After an initial rapid increase until 24 months of life, the total intracranial volume was found to converge towards 1400 mL during adolescence. The expected volumes of white matter (WM) and cortical gray matter (GM) showed a similar trend with age. After an initial major decrease, T1 relaxation times were observed to decrease progressively in all brain structures. The T1 drop in the first year of life was more pronounced in WM (from 1000–1100 to 650–700 ms) than in GM structures. Conclusion: The 3D MP2RAGE sequence allowed to establish brain volume and T1 relaxation time normative ranges in pediatrics. Key Points: • The 3D MP2RAGE sequence provided a reliable quantitative assessment of brain volumes and T1 relaxation times during childhood. • An age-dependent model of normal brain maturation was established. • The normative ranges enable an objective comparison to a normal cohort, which can be useful to further understand, describe, and identify neurodevelopmental disorders in children. [ABSTRACT FROM AUTHOR]

Background: Acute methanol poisoning leads to optic neuropathy and necrotic lesions of basal ganglia (BG) and subcortical white matter. Survivors of methanol poisoning exhibit long‐term executive and memory deficits. Associations between brain volumetry parameters and cognitive sequelae of methanol poisoning are not known. The aim of our study was to identify long‐term associations between the cognitive performance of survivors of methanol poisoning and the volume of the brain structures that are selectively vulnerable to methanol. Methods: We conducted a cross‐sectional follow‐up study on a sample of patients (n = 33, age 50 ± 14 years, 82% males) who survived acute methanol poisoning during methanol mass poisoning outbreak from September 2012 till January 2013 in the Czech Republic. A battery of neuropsychological tests and brain magnetic resonance imaging were included in the clinical examination protocol. Specific brain structures (putamen, globus pallidus, nucleus caudatus, and frontal white matter) were selected as regions of interest, and their volumes were estimated using the MorphoBox prototype software. Results: In robust multiple regression models, sustained visual attention performance (as assessed by Trail Making Test and Prague Stroop Test) was positively associated with BG structures and frontal white matter volumes (Wald = 9.03 to 85.50, p < 0.01), sensitivity to interference (as assessed by Frontal Battery Assessment) was negatively associated with frontal white matter volume (Wald = 35.44 to 42.25, p < 0.001), and motor performance (as assessed by Finger Tapping Test) was positively associated with globus pallidus and frontal white matter volumes (Wald = 9.66 to 13.29, p < 0.01). Conclusions: Our results demonstrate that smaller volumes of elements of BG–thalamocortical circuitry, namely the BG and frontal white matter, relate to attention and motor performance in methanol poisoning from a long‐term perspective. Disruption of those functional circuits may underlie specific cognitive deficits observed in methanol poisoning. [ABSTRACT FROM AUTHOR]

Age-related white matter lesions (WML) are common, impact neuronal connectivity, and affect motor function and cognition. In addition to pathological nigrostriatal losses, WML are also common co-morbidities in Parkinson's disease (PD) that affect postural stability and gait. Automated brain volume measures are increasingly incorporated into the clinical reporting workflow to facilitate precision in medicine. Recently, multi-modal segmentation algorithms have been developed to overcome challenges with WML quantification based on single-modality input. We evaluated WML volumes and their distribution in a case-control cohort of PD patients to predict the domain-specific clinical severity using a fully automated multi-modal segmentation algorithm. Fifty-five subjects comprising of twenty PD patients and thirty-five age- and gender-matched control subjects underwent standardized motor/gait and cognitive assessments and brain MRI. Spatially differentiated WML obtained using automated segmentation algorithms on multi-modal MPRAGE and FLAIR images were used to predict domain-specific clinical severity. Preliminary statistical analysis focused on describing the relationship between WML and clinical scores, and the distribution of WML by brain regions. Subsequent stepwise regressions were performed to predict each clinical score using WML volumes in different brain regions, while controlling for age. WML volume strongly correlates with both motor and cognitive dysfunctions in PD patients (p < 0.05), with differential impact in the frontal lobe and periventricular regions on cognitive domains (p < 0.01) and severity of motor deficits (p < 0.01), respectively. Automated multi-modal segmentation algorithms may facilitate precision medicine through regional WML load quantification, which show potential as imaging biomarkers for predicting domain-specific disease severity in PD. • White matter lesions (WML) are common co-morbidities in Parkinson's disease (PD) • Periventricular WML significantly predicted UPDRS-III motor scores in PD • Frontal WML predicted cognitive impairment and frontal lobe dysfunction in PD • Automated segmentation algorithms quantify WML, facilitating precision medicine • Regional WML quantification may aid domain-specific clinical assessment in PD [ABSTRACT FROM AUTHOR]