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BackgroundOsimertinib, an irreversible inhibitor of the epidermal growth factor receptor (EGFR) is an important drug in the treatment of EGFR-mutation positive non-small cell lung cancer (NSCLC). Clinical trials with osimertinib could not demonstrate an exposure-efficacy relationship, while a relationship between exposure and toxicity has been found. In this study, we report the exposure–response relationships of osimertinib in a real-life setting.MethodsA retrospective observational cohort study was performed, including patients receiving 40 - 80 mg osimertinib as ≥ 2 line therapy and from whom pharmacokinetic samples were collected during routine care. Trough plasma concentrations (Cmin,pred) were estimated and used as a measure of osimertinib exposure. A previously defined exploratory pharmacokinetic threshold of 166 µg/L was taken to explore the exposure-efficacy relationship.ResultsA total of 145 patients and 513 osimertinib plasma concentration samples were included. Median progression free survival (PFS) was 13.3 (95% confidence interval (CI):10.3 – 19.1) months and 9.3 (95% CI: 7.2 – 11.1) months for patients with Cmin,pred < 166 µg/L and Cmin,pred ≥ 166 µg/L, respectively (p = 0.03). In the multivariate analysis, a Cmin,pred < 166 µg/L resulted in a non-statistically significant hazard ratio of 1.10 (95% CI: 0.60 – 2.01; p = 77). Presence of a EGFR driver-mutation other than the exon 19 del or L858R mutations, led to a shorter PFS with a hazard ratio of 2.89 (95% CI: 1.18 – 7.08; p = 0.02). No relationship between exposure and toxicity was observed (p = 0.91).ConclusionIn our real-life cohort, no exposure–response relationship was observed for osimertinib in the current dosing scheme. The feasibility of a standard lower fixed dosing of osimertinib in clinical practice should be studied prospectively.

The cerebral cortex develops rapidly in the last trimester of pregnancy. In preterm infants, brain development is very vulnerable because of their often complicated extra-uterine conditions. The aim of this study was to quantitatively describe cortical development in a cohort of 85 preterm infants with and without brain injury imaged at 30 and 40 weeks postmenstrual age (PMA). In the acquired T2-weighted MR images, unmyelinated white matter (UWM), cortical grey matter (CoGM), and cerebrospinal fluid in the extracerebral space (CSF) were automatically segmented. Based on these segmentations, cortical descriptors evaluating volume, surface area, thickness, gyrification index, and global mean curvature were computed at both time points, for the whole brain, as well as for the frontal, temporal, parietal, and occipital lobes separately. Additionally, visual scoring of brain abnormality was performed using a conventional scoring system at 40 weeks PMA. The evaluated descriptors showed larger change in the occipital lobes than in the other lobes. Moreover, the cortical descriptors showed an association with the abnormality scores: gyrification index and global mean curvature decreased, whereas, interestingly, median cortical thickness increased with increasing abnormality score. This was more pronounced at 40 weeks PMA than at 30 weeks PMA, suggesting that the period between 30 and 40 weeks PMA might provide a window of opportunity for intervention to prevent delay in cortical development.

Deep brain stimulation (DBS) for Parkinson's disease often alleviates the motor symptoms, but causes cognitive and emotional side effects in a substantial number of cases. Identification of the motor part of the subthalamic nucleus (STN) as part of the presurgical workup could minimize these adverse effects. In this study, we assessed the STN's connectivity to motor, associative, and limbic brain areas, based on structural and functional connectivity analysis of volunteer data. For the structural connectivity, we used streamline counts derived from HARDI fiber tracking. The resulting tracks supported the existence of the so-called \"hyperdirect\" pathway in humans. Furthermore, we determined the connectivity of each STN voxel with the motor cortical areas. Functional connectivity was calculated based on functional MRI, as the correlation of the signal within a given brain voxel with the signal in the STN. Also, the signal per STN voxel was explained in terms of the correlation with motor or limbic brain seed ROI areas. Both right and left STN ROIs appeared to be structurally and functionally connected to brain areas that are part of the motor, associative, and limbic circuit. Furthermore, this study enabled us to assess the level of segregation of the STN motor part, which is relevant for the planning of STN DBS procedures.

Background Normative adult body composition values from North American patients were recently provided, yet sex- and age-specific reference values for Europeans remain unexplored. Materials and methods This cross-sectional study was performed on adult trauma patients who underwent CT imaging that included the abdomen in the University Medical Center Utrecht, a level-1 trauma center, between January 2017 and December 2020. An artificial intelligence algorithm was used to automatically segment muscle and fat components on axial CT images at the level of the third lumbar vertebra. Measurements included areas and attenuation values for muscle and fat, including total muscle areas and “pure-muscle” sub-areas. Skeletal muscle indices were calculated by dividing skeletal muscle areas by the squared height of patients. Age- and sex-specific percentile curves for all parameters were generated. Results Of the 2383 adult trauma patients who underwent CT imaging that included the abdomen, 2286 were included. The median age was 53 years (IQR 32–69), and 67.2% were male. The mean BMI was 25.4 ± 4.4 kg/m 2 . The total muscle index decreased with age starting around 60 years in males. In females, the total muscle index decreased with age when intramuscular fat was excluded from the analysis. Mean muscle attenuation of all included muscles showed substantial declines with age in both sexes. Visceral fat areas increased rapidly with age in both sexes, yet with higher values among males. Conclusion This study provides CT-derived populational body composition parameters established in Dutch adults, intended to be used as reference values in clinical practice. Critical relevance statement Obesity and sarcopenia are risk factors for various diseases and mortality. CT-based body composition assessment provides precise muscle and fat data, enabling personalized treatment plans and early identification of individual risks, ultimately improving patient outcomes and care management strategies. Key Points European reference values of CT-derived muscle and fat parameters are not yet well established. This study provides Dutch reference curves and values of CT-derived body composition. CT-derived body composition assessment enables personalized risk assessment and treatment. Graphical Abstract

This study investigates the predictive ability of automatic quantitative brain MRI descriptors for the identification of infants with low cognitive and/or motor outcome at 2–3 years chronological age. MR brain images of 173 patients were acquired at 30 weeks postmenstrual age (PMA) (n = 86) and 40 weeks PMA (n = 153) between 2008 and 2013. Eight tissue volumes and measures of cortical morphology were automatically computed. A support vector machine classifier was employed to identify infants who exhibit low cognitive and/or motor outcome (<85) at 2–3 years chronological age as assessed by the Bayley scales. Based on the images acquired at 30 weeks PMA, the automatic identification resulted in an area under the receiver operation characteristic curve (AUC) of 0.78 for low cognitive outcome, and an AUC of 0.80 for low motor outcome. Identification based on the change of the descriptors between 30 and 40 weeks PMA (n = 66) resulted in an AUC of 0.80 for low cognitive outcome and an AUC of 0.85 for low motor outcome. This study provides evidence of the feasibility of identification of preterm infants at risk of cognitive and motor impairments based on descriptors automatically computed from images acquired at 30 and 40 weeks PMA.

Preterm birth is often associated with impaired brain development. The state and expected progression of preterm brain development can be evaluated using quantitative assessment of MR images. Such measurements require accurate segmentation of different tissue types in those images. This paper presents an algorithm for the automatic segmentation of unmyelinated white matter (WM), cortical grey matter (GM), and cerebrospinal fluid in the extracerebral space (CSF). The algorithm uses supervised voxel classification in three subsequent stages. In the first stage, voxels that can easily be assigned to one of the three tissue types are labelled. In the second stage, dedicated analysis of the remaining voxels is performed. The first and the second stages both use two-class classification for each tissue type separately. Possible inconsistencies that could result from these tissue-specific segmentation stages are resolved in the third stage, which performs multi-class classification. A set of T1- and T2-weighted images was analysed, but the optimised system performs automatic segmentation using a T2-weighted image only. We have investigated the performance of the algorithm when using training data randomly selected from completely annotated images as well as when using training data from only partially annotated images. The method was evaluated on images of preterm infants acquired at 30 and 40weeks postmenstrual age (PMA). When the method was trained using random selection from the completely annotated images, the average Dice coefficients were 0.95 for WM, 0.81 for GM, and 0.89 for CSF on an independent set of images acquired at 30weeks PMA. When the method was trained using only the partially annotated images, the average Dice coefficients were 0.95 for WM, 0.78 for GM and 0.87 for CSF for the images acquired at 30weeks PMA, and 0.92 for WM, 0.80 for GM and 0.85 for CSF for the images acquired at 40weeks PMA. Even though the segmentations obtained using training data from the partially annotated images resulted in slightly lower Dice coefficients, the performance in all experiments was close to that of a second human expert (0.93 for WM, 0.79 for GM and 0.86 for CSF for the images acquired at 30weeks, and 0.94 for WM, 0.76 for GM and 0.87 for CSF for the images acquired at 40weeks). These results show that the presented method is robust to age and acquisition protocol and that it performs accurate segmentation of WM, GM, and CSF when the training data is extracted from complete annotations as well as when the training data is extracted from partial annotations only. This extends the applicability of the method by reducing the time and effort necessary to create training data in a population with different characteristics. •An automatic segmentation method for WM, GM and CSF in neonatal MRI is presented.•The method is based on sequential supervised voxel classification.•The method can perform segmentation based on a T2-weighted image only.•The method is robust to age and acquisition protocol.•The method does not require fully annotated training images.

Background Body composition during childhood may predispose to negative health outcomes later in life. Automatic segmentation may assist in quantifying pediatric body composition in children. Objective To evaluate automatic segmentation for body composition on pediatric computed tomography (CT) scans and to provide normative data on muscle and fat areas throughout childhood using automatic segmentation. Materials and methods In this pilot study, 537 children (ages 1–17 years) who underwent abdominal CT after high-energy trauma at a Dutch tertiary center (2002–2019) were retrospectively identified. Of these, the CT images of 493 children (66% boys) were used to establish normative data. Muscle (psoas, paraspinal and abdominal wall) and fat (subcutaneous and visceral) areas were measured at the third lumbar vertebral (L3) level by automatic segmentation. A representative subset of 52 scans was also manually segmented to evaluate the performance of automatic segmentation. Results For manually-segmented versus automatically-segmented areas (52 scans), mean Dice coefficients were high for muscle (0.87–0.90) and subcutaneous fat (0.88), but lower for visceral fat (0.60). In the control group, muscle area was comparable for both sexes until the age of 13 years, whereafter, boys developed relatively more muscle. From a young age, boys were more prone to visceral fat storage than girls. Overall, boys had significantly higher visceral-to-subcutaneous fat ratios (median 1.1 vs. 0.6, P <0.01) and girls higher fat-to-muscle ratios (median 1.0 vs. 0.7, P <0.01). Conclusion Automatic segmentation of L3-level muscle and fat areas allows for accurate quantification of pediatric body composition. Using automatic segmentation, the development in muscle and fat distribution during childhood (in otherwise healthy) Dutch children was demonstrated.

Cortical folding mainly takes place in the third trimester of pregnancy and may therefore be influenced by preterm birth. The aim of this study was to evaluate the development of specific cortical structures between early age (around 30weeks postmenstrual age) and term-equivalent age (TEA, around 40weeks postmenstrual age) in 71 extremely preterm infants, and to associate this to clinical characteristics and neurodevelopmental outcome at two years of age. First, analysis showed that the central sulcus (CS), lateral fissure (LF) and insula (INS) were present at early MRI in all infants, whereas the other sulci (post-central sulcus [PCS], superior temporal sulcus [STS], superior [SFS] and inferior [IFS] frontal sulcus) were only seen in part of the infants. Relative growth from early to TEA examination was largest in the SFS. A rightward asymmetry of the surface area was seen in development between both examinations except for the LF, which showed a leftward asymmetry at both time points. Second, lower birth weight z-score, multiple pregnancy and prolonged mechanical ventilation showed negative effects on cortical folding of the CS, LF, INS, STS and PCS, mainly on the first examination, suggesting that sulci developing the earliest were the most affected by clinical factors. Finally, in this cohort, a clear association between cortical folding and neurodevelopmental outcome at two years corrected age was found, particularly for receptive language.

Background: This study aimed to assess cortical gray matter growth and maturation in neonates with congenital heart disease (CHD). Methods: Thirty-one (near) term neonates with severe CHD (8 univentricular heart malformation (UVH), 21 d-transposition of great arteries (d-TGA) and 2 aortic coarctation) underwent cerebral MRI before (postnatal-day 7) and after (postnatal-day 24) surgery. Eighteen controls with similar gestational age had one MRI (postnatal-day 23). Cortical gray matter volume (CGM), inner cortical surface ( i CS), and median cortical thickness were extracted as measures of volumetric growth, and gyrification index (GI) as measure of maturation. Results: Over a median of 18 d, CGM increased by 21%, i CS by 17%, thickness and GI both by 9%. Decreased postoperative CGM and i CS were seen for CHD compared to controls ( P values < 0.01), however with similar thickness and GI. UVH showed lower postoperative i CS, thickness ( P values < 0.05) and GI ( P value < 0.01) than d-TGA and controls. Infants requiring preoperative balloon-atrioseptostomy (BAS, 61%) had reduced postoperative CGM, i CS, and GI ( P values < 0.05). Conclusion: Infants with severe CHD show reduced cortical volumes compared to controls with gyrification being delayed in UVH, but not in d-TGA. Infants requiring BAS show higher risk of impaired cortical volume and gyrification.

Background and ObjectiveTo investigate the relation of early brain activity with structural (growth of the cortex and cerebellum) and white matter microstructural brain development.MethodsA total of 33 preterm neonates (gestational age 26±1 weeks) without major brain abnormalities were continuously monitored with electroencephalography during the first 48 h of life. Rate of spontaneous activity transients per minute (SAT rate) and inter-SAT interval (ISI) in seconds per minute were calculated. Infants underwent brain magnetic resonance imaging ∼30 (mean 30.5; min: 29.3-max: 32.0) and 40 (41.1; 40.0-41.8) weeks of postmenstrual age. Increase in cerebellar volume, cortical gray matter volume, gyrification index, fractional anisotropy (FA) of posterior limb of the internal capsule, and corpus callosum (CC) were measured.ResultsSAT rate was positively associated with cerebellar growth (P=0.01), volumetric growth of the cortex (P=0.027), increase in gyrification (P=0.043), and increase in FA of the CC (P=0.037). ISI was negatively associated with cerebellar growth (P=0.002).ConclusionsIncreased early brain activity is associated with cerebellar and cortical growth structures with rapid development during preterm life. Higher brain activity is related to FA microstructural changes in the CC, a region responsible for interhemispheric connections. This study underlines the importance of brain activity for microstructural brain development.