Gliomas are the most common type of tumor in the brain. Although the definite diagnosis is routinely made ex vivo by histopathologic and molecular examination, diagnostic work-up of patients with suspected glioma is mainly done using MRI. Nevertheless, l--methyl-C-methionine (C-MET) PET holds great potential in the characterization of gliomas. The aim of this study was to establish machine-learning-driven survival models for glioma built on in vivo C-MET PET characteristics, ex vivo characteristics, and patient characteristics. The study included 70 patients with a treatment-naïve glioma that was C-MET-positive and had histopathology-derived ex vivo feature extraction, such as World Health Organization 2007 tumor grade, histology, and isocitrate dehydrogenase 1 R132H mutational status. TheC-MET-positive primary tumors were delineated semiautomatically on PET images, followed by the extraction of tumor-to-background-based general and higher-order textural features by applying 5 different binning approaches. In vivo and ex vivo features, as well as patient characteristics (age, weight, height, body mass index, Karnofsky score), were merged to characterize the tumors. Machine-learning approaches were used to identify relevant in vivo, ex vivo, and patient features and their relative weights for predicting 36-mo survival. The resulting feature weights were used to establish 3 predictive models per binning configuration: one model based on a combination of in vivo, ex vivo, and clinical patient information (M36); another based on in vivo and patient information only (M36); and a third based on in vivo information only (M36). In addition, a binning-independent model based on ex vivo and patient information only (M36) was created. The established models were validated in a Monte Carlo cross-validation scheme. The most prominent machine-learning-selected and -weighted features were patient-based and ex vivo-based, followed by in vivo-based. The highest areas under the curve for our models as revealed by the Monte Carlo cross-validation were 0.9 for M36, 0.87 for M36, 0.77 for M36, and 0.72 for M36 Prediction of survival in amino acid PET-positive glioma patients was highly accurate using computer-supported predictive models based on in vivo, ex vivo, and patient features.

ObjectivesThe software “SyMRI” generates different MR contrasts and characterizes tissue properties based on a single acquisition of a multi-dynamic multi-echo (MDME)-FLAIR sequence. The aim of this study was to assess the applicability of “SyMRI” in the assessment of myelination in preterm and term-born neonates. Furthermore, “SyMRI” was compared with conventional MRI.MethodsA total of 30 preterm and term-born neonates were examined at term-equivalent age using a standardized MRI protocol. MDME sequence (acquisition time, 5 min, 24 s)–based post-processing was performed using “SyMRI”. Myelination was assessed by scoring seven brain regions on quantitative T1-/T2-maps, generated by “SyMRI” and on standard T1-/T2-weighted images, acquired separately. Analysis of covariance (ANCOVA) (covariate, gestational age (GA) at MRI (GAMRI)) was used for group comparison.ResultsIn 25/30 patients (83.3%) (18 preterm and seven term-born neonates), “SyMRI” acquisitions were successfully performed. “SyMRI”-based myelination scores were significantly lower in preterm compared with term-born neonates (ANCOVA: T1: F(1, 22) = 7.420, p = 0.012; T2: F(1, 22) = 5.658, p = 0.026). “SyMRI”-based myelination scores positively correlated with GAMRI (T1: r = 0.662, n = 25, p ≤ 0.001; T2: r = 0.676, n = 25, p ≤ 0.001). The myelination scores based on standard MRI did not correlate with the GAMRI. No significant differences between preterm and term-born neonates were detectable.Conclusions“SyMRI” is a highly promising MR technique for neonatal brain imaging. “SyMRI” is superior to conventional MR sequences in the visual detection of delayed myelination in preterm neonates.Key Points• By providing multiple MR contrasts, “SyMRI” is a time-saving method in neonatal brain imaging.• Differences concerning the myelination in term-born and preterm infants are visually detectable on T1-/T2-weighted maps generated by “SyMRI”.• “SyMRI” allows a faster and more sensitive assessment of myelination compared with standard MR sequences.Electronic supplementary materialThe online version of this article (10.1007/s00330-019-06325-2) contains supplementary material, which is available to authorized users.

Postnatal growth restriction and deficits in fat-free mass are associated with impaired neurodevelopment. The optimal body composition to support normal brain growth and development remains unclear. This study investigated the association between body composition and brain size in preterm infants. We included 118 infants born <28 weeks of gestation between 2017–2021, who underwent body composition (fat-free mass (FFM) and fat mass (FM)) and cerebral magnetic resonance imaging to quantify brain size (cerebral biparietal diameter (cBPD), bone biparietal diameter (bBPD), interhemispheric distance (IHD), transverse cerebellar diameter (tCD)) at term-equivalent age. FFM Z-Score significantly correlated with higher cBPD Z-Score (rs = 0.69; p < 0.001), bBPD Z-Score (rs = 0.48; p < 0.001) and tCD Z-Score (rs = 0.30; p = 0.002); FM Z-Score significantly correlated with lower brain size (cBPD Z-Score (rs = −0.32; p < 0.001) and bBPD Z-Score (rs = −0.42; p < 0.001). In contrast weight (rs = 0.08), length (rs = −0.01) and head circumference Z-Score (rs = 0.14) did not. Linear regression model adjusted for important neonatal variables revealed that FFM Z-Score was independently and significantly associated with higher cBPD Z-Score (median 0.50, 95% CI: 0.59, 0.43; p < 0.001) and bBPD Z-Score (median 0.31, 95% CI: 0.42, 0.19; p < 0.001); FM Z-Score was independently and significantly associated with lower cBPD Z-Score (median −0.27, 95% CI: −0.42, −0.11; p < 0.001) and bBPD Z-Score (median −0.32, 95% CI: −0.45, −0.18; p < 0.001). Higher FFM Z-Score and lower FM Z-scores were significantly associated with larger brain size at term-equivalent age. These results indicate that early body composition might be a useful tool to evaluate and eventually optimize brain growth and neurodevelopment.

Background & Aims Human immunodeficiency virus (HIV)/hepatitis C virus (HCV) coinfection is common in people who inject drugs (PWIDs). Recently, ‘high‐risk’ behaviour among men who have sex with men (MSM) has emerged as another main route of HCV transmission. We analysed temporal trends in HCV epidemiology in a cohort of Viennese HIV+ patients. Methods Hepatitis C virus parameters were recorded at HIV diagnosis (baseline [BL]) and last visit (follow‐up [FU]) for all HIV+ patients attending our HIV clinic between January 2014 and December 2016. Proportions of HIV+ patients with anti‐HCV(+) and HCV viraemia (HCV‐RNA(+)) at BL/FU were assessed and stratified by route of transmission. Results In all, 1806/1874 (96.4%) HIV+ patients were tested for HCV at BL. Anti‐HCV(+) was detected in 93.2% (276/296) of PWIDs and in 3.7% (31/839) of MSM. After a median FU of 6.9 years, 1644 (91.0%) patients underwent FU HCV‐testing: 167 (90.3%) of PWIDs and 49 (6.7%) of MSM showed anti‐HCV(+). Among 208 viraemic HCV‐RNA(+) patients at BL, 30 (14.4%) had spontaneously cleared HCV, 76 (36.5%) achieved treatment‐induced eradication and 89 (42.8%) remained HCV‐RNA(+) at last FU. Among 1433 initially HCV‐naive patients, 45 (3.5%) acquired de‐novo HCV infection (11.1% PWIDs/80.0% MSM; incidence rate (IR) 0.004%; 95% confidence interval [CI] 0.0%‐0.022%) and 14 had HCV reinfections (85.7% PWIDs/14.3% other; IR 0.001%; 95% CI 0.0%‐0.018%) during a median FU of 6.7 years (interquartile range 7.4). Conclusion Hepatitis C virus testing was successfully implemented in the Viennese HIV(+) patients. Anti‐HCV(+) prevalence remained stable in HIV+ PWIDs but almost doubled in HIV+ MSM. De‐novo HCV infection occurred mostly in MSM, while HCV reinfections were mainly observed in PWIDs. HCV treatment uptake was suboptimal with 42.8% remaining HCV‐RNA(+) at FU.

BACKGROUND AND PURPOSE: Former preterm born males are at higher risk for neurodevelopmental disabilities compared with female infants born at the same gestational age. This retrospective study investigated sex-related differences in the maturity of early myelinating brain regions in infants born ,28 weeks' gestational age using diffusion tensor-and relaxometry-based MR imaging. MATERIALS AND METHODS:Quantitative MR imaging sequence acquisitions were analyzed in a sample of 35 extremely preterm neonates imaged at term-equivalent ages. Quantitative MR imaging metrics (fractional anisotropy; ADC [10 À3 mm 2 /s]; and T1-/T2relaxation times [ms]) of the medulla oblongata, pontine tegmentum, midbrain, and the right/left posterior limbs of the internal capsule were determined on diffusion tensor-and multidynamic, multiecho sequence-based imaging data. ANCOVA and a paired t test were used to compare female and male infants and to detect hemispheric developmental asymmetries. RESULTS:Seventeen female (mean gestational age at birth: 26 1 0 [SD, 1 1 4] weeks1days) and 18 male (mean gestational age at birth: 26 1 1 [SD, 1 1 3] weeks1days) infants were enrolled in this study. Significant differences were observed in the T2-relaxation time (P ¼ .014) of the pontine tegmentum, T1-relaxation time (P ¼ .011)/T2-relaxation time (P ¼ .024) of the midbrain, and T1-relaxation time (P ¼ .032) of the left posterior limb of the internal capsule. In both sexes, fractional anisotropy (P [$] , .001/P [#] , .001) and ADC (P [$] ¼ .017/P [#] ¼ .028) differed significantly between the right and left posterior limbs of the internal capsule. CONCLUSIONS:The combined use of various quantitative MR imaging metrics detects sex-related and interhemispheric differences of WM maturity. The brainstem and the left posterior limb of the internal capsule of male preterm neonates are more immature compared with those of female infants at term-equivalent ages. Sex differences in WM maturation need further attention for the personalization of neonatal brain imaging.