The interaction between neuromuscular forces, aerodynamic forces, and anatomical motion in the upper airway predicts the severity of pediatric OSA

Upper airway neuromuscular response to air pressure during inhalation is an important factor in assessing pediatric subjects with obstructive sleep apnea (OSA). The neuromuscular response's strength, timing, and duration all contribute to the potential for airway collapses and the severity of OSA. This study quantifies these factors at the soft palate, tongue, and epiglottis to assess the relationship between neuromuscular control and OSA severity in 20 pediatric subjects with and without trisomy 21, under dexmedetomidine-induced sedation. The interaction between neuromuscular force and airflow pressure force was assessed based on power transferred between the airway wall and airflow calculated from airway wall motion (from cine magnetic resonance images) and air pressure acting on the airway wall (from computational fluid dynamics simulations). Airway wall motion could be asynchronous with pressure forces due to neuromuscular activation, or synchronous with pressure forces, indicating a passive response to airflow. The obstructive apnea-hypopnea index (oAHI) quantified OSA severity. During inhalation, the normalized work done through asynchronous dilation of the airway at the soft palate, tongue, and epiglottis correlated significantly with oAHI (Spearman's ρ = 0.54, 0.50, 0.64; P = 0.03, 0.03, 0.003). Synchronous collapse at the epiglottis correlated significantly with oAHI (ρ = 0.52; P = 0.02). Temporal order of synchronous and asynchronous epiglottis motion during inhalation predicted the severity of OSA (moderate vs. severe) with 100% sensitivity and 70% specificity. Subjects with severe OSA and/or trisomy 21 have insufficient neuromuscular activation during inhalation, leading to collapse and increased neuromuscular activation. Airflow-driven airway wall motion during late inhalation likely is the main determinant of OSA severity.NEW & NOTEWORTHY This is the first study that combines cine MRI and computational fluid dynamics with in vivo synchronous respiratory flow measurement to quantify the interaction between airway neuromuscular forces, aerodynamic forces, and airway anatomy noninvasively in pediatric patients with obstructive sleep apnea (OSA). The results indicate power transfer predicts OSA severity.

CUBITAL TUNNEL SYNDROME DUE TO AN INTRANEURAL GANGLION CYST OF THE ULNAR NERVE

Cubital tunnel syndrome is the second most common neuropathy of the upper extremity. Cubital tunnel syndrome caused by intraneural ganglion cysts is rare in clinical practice. We present the case of a 71-year-old male patient with a 4-month history of cubital tunnel syndrome of the left elbow due to an intraneural ganglion cyst. After revision of the ulnar nerve and resection of the intraneural cyst nearly complete recovery was achieved within a 5 month follow-up but some sensory deficits of the fifth fingertip. We recommend preoperative ultrasound examination of the cubital tunnel even in cases with clear diagnosis. Ganglion cyst as a cause of cubital tunnel is rare but needs to be diagnosed and treated as soon as possible to prevent irreversible complications.

TRAUMATIC PULMONARY HERNIATION: A RARE CHEST TRAUMA MANIFESTATION

Traumatic pulmonary hernia is an uncommon occurrence resulting from chest trauma, typically covered by the skin. Chest trauma may arise from penetrating or blunt mechanisms, with blunt trauma being more frequently observed. When lung herniation transpires, various symptoms such as chest pain, dyspnea, subcutaneous emphysema, bone crepitation, and hemoptysis (in cases of lung parenchymal damage) may manifest. We present the case of a 66-year-old woman suffering from chest pain and dyspnea after blunt chest trauma due to a fall induced by delirium following alcohol abuse.

AN INTRATENDINOUS GANGLION CYST OF THE PATELLAR TENDON: A RARE CAUSE OF ANTERIOR KNEE PAIN

Ganglion cysts in the knee region can manifest as anterior knee pain. Unlike synovial cysts, these lesions lack synovial epithelial lining and occur secondary to mucoid degeneration of connective tissue because, often in response to chronic irritation and repetitive traumas. However, an intratendinous location is a rare finding. In the knee region, infrapatellar fat pad, the alar folds, and the anterior cruciate ligament are recognized to degenerate into ganglion. There are few case reports describing an involvement of the patellar tendon. We present the clinical case of a 72 years old male patient suffering from anterior knee pain attributed to an intratendinous ganglion cyst of the patellar tendon, obviously after a single traumatic event. After aspiration of the ganglion cyst the patient reported no complaints, and there has been no recurrence during the latest follow-up examination.

Structural and functional asymmetry of the neonatal cerebral cortex

Features of brain asymmetry have been implicated in a broad range of cognitive processes; however, their origins are still poorly understood. Here we investigated cortical asymmetries in 442 healthy term-born neonates using structural and functional magnetic resonance images from the Developing Human Connectome Project. Our results demonstrate that the neonatal cortex is markedly asymmetric in both structure and function. Cortical asymmetries observed in the term cohort were contextualized in two ways: by comparing them against cortical asymmetries observed in 103 preterm neonates scanned at term-equivalent age, and by comparing structural asymmetries against those observed in 1,110 healthy young adults from the Human Connectome Project. While associations with preterm birth and biological sex were minimal, significant differences exist between birth and adulthood.

RETURN TO SPORT AFTER SURGICAL TREATED TIBIAL PLATEAU FRACTURES

Tibial plateau fractures (TPF) comprise 1% of all fractures, despite their limited frequency, due to their intraarticular nature they commonly result in significant functional morbidity. Generally, younger, and middle-aged men (64%) tend to have fractures as a result of high-energy trauma, such as high-speed motor vehicle accidents or falls from a considerable height, while older women have low-energy fractures (35%). While there is growing evidence on the clinical and radiological outcomes of surgical techniques, there remains limited evidence on return to sport following TPF. Aim of this retrospective study is to determine the sporting abilities of patients after operative treatment of TPF. 47 Patients (20 women, 27 men) who underwent surgical treatment for a TPF were surveyed by a questionnaire to determine their sporting activity were followed- up a mean of 47.6 months (Min: 12, Max: 115). All the patients fractures were systematically assessed using AO- Classification. The Lysholm-Gillquist scores, IKDC Score, Injury - Psychological Readiness to Return to Sport (I-PRRS) scales and ACL-Return to Sport Injury Scale (ACL-RSI) were used to assess clinical outcomes. All fractures united, and no revision surgeries were required. There were no intraoperative complications. Mean postoperative IKDC score was 75 (Min:13, Max: 100), mean postoperative Lysholm score was 82 (Min: 5, Max: 100), mean ACL-Return to Sport Injury Scale (ACL-RSI) was 66 (Min: 0, Max: 100), Injury-Psychological Readiness to Return to Sport Scale (I-PRRS-Scale) was 39 (Min: 0, Max: 80). 31/47 patients were able to return to their former -sports- activity level, 8/47 did not achieve their former sports activity level before injury, 2/47 cases changed their kind of sport and 6/47 stopped sporting activities. Tibial plateau fractures -a severe injury- have a great effect on patients in terms of quality and quantity of sporting activity. Nevertheless, most of our surgical treated patients were satisfied with the outcome with good values in the Lysholm- score, I-PRRS- Scale, IKDC score and ACL-Return to Sport Injury Scale.

HOW TO AVOID FRACTURE OF THE LOCKING SCREW IN MODULAR REVISION ARTHROPLASTY OF THE HIP USING THE MRP TITAN REVISION SYSTEM

The use of modular femoral stems in primary and revision arthroplasty of the hip has become popular within the last decade. On the other hand, modularity creates new potential problems like fretting, crevice and galvanic corrosion, component loosening, dissociation, and fracture of modular prostheses. Recently a problem of fracture of a locking screw in revision arthroplasty of the hip using the MRP Titan Stem (Peter Brehm GmbH, Weisendorf, 91085 Germany) appeared. The aim of this study is to evaluate the meaning of surface contamination in respect to fracture mechanism. The titanium nitrid coated locking screw M6 of the MRP Titan system was in vitro tested in several series. After experimental contamination (series 1-4) morse taper junction was fixed by the locking screw with a torque wrench: Series 1: The influence of contamination with dried blood was examined while screw M6 was put into pig's blood. Series 2: The influence of contamination with dried blood and biologic tissue was examined while screw M6 was covered with a pulpous mixture of pig's blood, pig's muscle, and pig's fat tissue. Series 3: The influence of contamination with dried blood and biologic tissue was examined while female thread was covered with a pulpous mixture of pig's blood, pig's muscle, and pig's fat tissue. Series 4: The influence of cleaning of the contaminated female component was examined while female thread contamination (with a pulpous mixture of pig's blood, pig's muscle, and pig's fat tissue) was cleaned with 50 ml saline solution. Comparing series 1 with series 4, series 2 with series 4 and series 3 with series 4 statistical analysis showed a significant reduction of fractures of screw M6 (p-values <0.01). To avoid fracture of the screw M6 of the MRP Titan System we recommend cleaning the inner thread of the morse taper junction with saline solution before junction is fixed with the screw and the torque wrench.

Computational assessment of upper airway muscular activity in obstructive sleep apnea - In vitro validation

Neuromuscular control of the upper airway contributes to obstructive sleep apnea (OSA). An accurate, non-invasive method to assess neuromuscular function is needed to improve surgical treatment outcomes. Currently, surgical approaches for OSA are based on airway anatomy and are often not curative. When the airway surface moves, the power transferred between air in the airway lumen and the structures of the upper airway may be a measure of airway neuromuscular activity. The aim of this study was to validate power transfer as a measure of externally applied forces, representing neuromuscular activity, through cine computed tomography (CT) imaging and computational fluid dynamics (CFD) analysis in a 3D-printed airway model. A hollow elastic airway model was manufactured. An insufflation/exsufflation device generated airflow within the model lumen. The model was contained in an airtight chamber that could be positively or negatively pressurized to represent muscular forces. These forces were systematically applied to dilate and collapse the model. Cine CT imaging captured airway wall movement during respiratory cycles with and without externally applied forces. Power transfer was calculated from the product of wall movement and internal aerodynamic pressure forces using CFD simulations. Cross-correlation peaks between power transfer and changes in externally applied pressure during exhalation and inhalation were -0.79 and 0.95, respectively. Power transfer calculated via cine CT imaging and CFD was an accurate surrogate measure of externally applied forces representing airway muscular activity. In the future, power transfer may be used in clinical practice to phenotype patients with OSA and select personalized therapies.

Predicting tracheal work of breathing in neonates based on radiological and pulmonary measurements

Tracheomalacia is an airway condition in which the trachea excessively collapses during breathing. Neonates diagnosed with tracheomalacia require more energy to breathe, and the effect of tracheomalacia can be quantified by assessing flow-resistive work of breathing (WOB) in the trachea using computational fluid dynamics (CFD) modeling of the airway. However, CFD simulations are computationally expensive; the ability to instead predict WOB based on more straightforward measures would provide a clinically useful estimate of tracheal disease severity. The objective of this study is to quantify the WOB in the trachea using CFD and identify simple airway and/or clinical parameters that directly relate to WOB. This study included 30 neonatal intensive care unit subjects (15 with tracheomalacia and 15 without tracheomalacia). All subjects were imaged using ultrashort echo time (UTE) MRI. CFD simulations were performed using patient-specific data obtained from MRI (airway anatomy, dynamic motion, and airflow rates) to calculate the WOB in the trachea. Several airway and clinical measurements were obtained and compared with the tracheal resistive WOB. The maximum percent change in the tracheal cross-sectional area (ρ = 0.560, P = 0.001), average glottis cross-sectional area (ρ = -0.488, P = 0.006), minute ventilation (ρ = 0.613, P < 0.001), and lung tidal volume (ρ = 0.599, P < 0.001) had significant correlations with WOB. A multivariable regression model with three independent variables (minute ventilation, average glottis cross-sectional area, and minimum of the eccentricity index of the trachea) can be used to estimate WOB more accurately (R2 = 0.726). This statistical model may allow clinicians to estimate tracheal resistive WOB based on airway images and clinical data.NEW & NOTEWORTHY The work of breathing due to resistance in the trachea is an important metric for quantifying the effect of tracheal abnormalities such as tracheomalacia, but currently requires complex dynamic imaging and computational fluid dynamics simulation to calculate it. This study produces a method to predict the tracheal work of breathing based on readily available imaging and clinical metrics.

INCIDENTAL INTRAOSSEOUS CALCANEAL LIPOMA IN A PATIENT SUFFERING FROM PLANTARFASZIITIS

Intraosseous calcaneal lipoma is a rare benign bone tumor. The incidence of intraosseous lipoma involving the calcaneus has been noted to account for fewer than 8-15% of all intraosseous lipoma. The etiology of the lesion is unknown. A post-traumatic secondary bone reaction, healing bone infarct, and benign neoplasm have been discussed. The symptoms can be nonspecific, varying from dull, intermittent pain to activity-related plantar pain. This pain can predictably be misdiagnosed as plantar fasciitis. We present the case of a 49-year-old male patient suffering from plantar fasciitis for three months and incidental asymptomatic intraosseous calcaneal lipoma, which was diagnosed by x-ray and CT scan. As the patient was out of complaints, the typical CT findings we saw no indication for biopsy but recommended regular CT and MRI controls.;

INTRAMUSCULAR MYXOMA OF THE BUTTOCK- A CASE REPORT

Intramuscular myxoma (IM) is a benign, soft tissue neoplasm of mesenchymal origin. IM is rare, with an incidence of between 0.1 and 0.13 in every 100,000 individuals. Onset is usually between the fourth and seventh decades of life, predominantly in women (70%). The thigh is the common site of involvement seen in 51% patients, followed by upper arm (9%), calf (7%), and rarely in buttocks. We present the case of a 63-year-old female patient with a 6-month history of a growing IM of the right buttock. Due to rapid tumor growth resection of the tumor was indicated to obtain histopathological examination and to rule out malignancy. Marginal surgical removal was performed. Histopathological examination brought the diagnosis of a big intramuscular myxoma. There is no recurrence at latest follow-up.

The Developing Human Connectome Project Neonatal Data Release

The Developing Human Connectome Project has created a large open science resource which provides researchers with data for investigating typical and atypical brain development across the perinatal period. It has collected 1228 multimodal magnetic resonance imaging (MRI) brain datasets from 1173 fetal and/or neonatal participants, together with collateral demographic, clinical, family, neurocognitive and genomic data from 1173 participants, together with collateral demographic, clinical, family, neurocognitive and genomic data. All subjects were studied in utero and/or soon after birth on a single MRI scanner using specially developed scanning sequences which included novel motion-tolerant imaging methods. Imaging data are complemented by rich demographic, clinical, neurodevelopmental, and genomic information. The project is now releasing a large set of neonatal data; fetal data will be described and released separately. This release includes scans from 783 infants of whom: 583 were healthy infants born at term; as well as preterm infants; and infants at high risk of atypical neurocognitive development. Many infants were imaged more than once to provide longitudinal data, and the total number of datasets being released is 887. We now describe the dHCP image acquisition and processing protocols, summarize the available imaging and collateral data, and provide information on how the data can be accessed.

Predicting age and clinical risk from the neonatal connectome

The development of perinatal brain connectivity underpins motor, cognitive and behavioural abilities in later life. Diffusion MRI allows the characterisation of subtle inter-individual differences in structural brain connectivity. Individual brain connectivity maps (connectomes) are by nature high in dimensionality and complex to interpret. Machine learning methods are a powerful tool to uncover properties of the connectome which are not readily visible and can give us clues as to how and why individual developmental trajectories differ. In this manuscript we used Deep Neural Networks and Random Forests to predict demographic and neurodevelopmental characteristics from neonatal structural connectomes in a large sample of babies (n = 524) from the developing Human Connectome Project. We achieved an accurate prediction of post menstrual age (PMA) at scan in term-born infants (mean absolute error (MAE) = 0.72 weeks, r = 0.83 and p<0.001). We also achieved good accuracy when predicting gestational age at birth in a cohort of term and preterm babies scanned at term equivalent age (MAE = 2.21 weeks, r = 0.82, p<0.001). We subsequently used sensitivity analysis to obtain feature relevance from our prediction models, with the most important connections for prediction of PMA and GA found to predominantly involve frontal and temporal regions, thalami, and basal ganglia. From our models of PMA at scan for infants born at term, we computed a brain maturation index (predicted age minus actual age) of individual preterm neonates and found a significant correlation between this index and motor outcome at 18 months corrected age. Our results demonstrate the applicability of machine learning techniques in analyses of the neonatal connectome and suggest that a neural substrate of brain maturation with implications for future neurodevelopment is detectable at term equivalent age from the neonatal connectome.

Neonatal multi-modal cortical profiles predict 18-month developmental outcomes

Developmental delays in infanthood often persist, turning into life-long difficulties, and coming at great cost for the individual and community. By examining the developing brain and its relation to developmental outcomes we can start to elucidate how the emergence of brain circuits is manifested in variability of infant motor, cognitive and behavioural capacities. In this study, we examined if cortical structural covariance at birth, indexing coordinated development, is related to later infant behaviour. We included 193 healthy term-born infants from the Developing Human Connectome Project (dHCP). An individual cortical connectivity matrix derived from morphological and microstructural features was computed for each subject (morphometric similarity networks, MSNs) and was used as input for the prediction of behavioural scores at 18 months using Connectome-Based Predictive Modeling (CPM). Neonatal MSNs successfully predicted social-emotional performance. Predictive edges were distributed between and within known functional cortical divisions with a specific important role for primary and posterior cortical regions. These results reveal that multi-modal neonatal cortical profiles showing coordinated maturation are related to developmental outcomes and that network organization at birth provides an early infrastructure for future functional skills.

Neonates With Tracheomalacia Generate Auto-Positive End-Expiratory Pressure via Glottis Closure

BACKGROUND

In pediatrics, tracheomalacia is an airway condition that causes tracheal lumen collapse during breathing and may lead to the patient requiring respiratory support. Adult patients can narrow their glottis to self-generate positive end-expiratory pressure (PEEP) to raise the pressure in the trachea and prevent collapse. However, auto-PEEP has not been studied in newborns with tracheomalacia. The objective of this study was to measure the glottis cross-sectional area throughout the breathing cycle and to quantify total pressure difference through the glottis in patients with and without tracheomalacia.

RESEARCH QUESTION

Do neonates with tracheomalacia narrow their glottises? How does the glottis narrowing affect the total pressure along the airway?

STUDY DESIGN AND METHODS

Ultrashort echo time MRI was performed in 21 neonatal ICU patients (11 with tracheomalacia, 10 without tracheomalacia). MRI scans were reconstructed at four different phases of breathing. All patients were breathing room air or using noninvasive respiratory support at the time of MRI. Computational fluid dynamics simulations were performed on patient-specific virtual airway models with airway anatomic features and motion derived via MRI to quantify the total pressure difference through the glottis and trachea.

RESULTS

The mean glottis cross-sectional area at peak expiration in the patients with tracheomalacia was less than half that in patients without tracheomalacia (4.0 ± 1.1 mm2 vs 10.3 ± 4.4 mm2; P = .002). The mean total pressure difference through the glottis at peak expiration was more than 10 times higher in patients with tracheomalacia compared with patients without tracheomalacia (2.88 ± 2.29 cm H2O vs 0.26 ± 0.16 cm H2O; P = .005).

INTERPRETATION

Neonates with tracheomalacia narrow their glottises, which raises pressure in the trachea during expiration, thereby acting as auto-PEEP.

Preterm birth alters the development of cortical microstructure and morphology at term-equivalent age

INTRODUCTION

The dynamic nature and complexity of the cellular events that take place during the last trimester of pregnancy make the developing cortex particularly vulnerable to perturbations. Abrupt interruption to normal gestation can lead to significant deviations to many of these processes, resulting in atypical trajectory of cortical maturation in preterm birth survivors.

METHODS

We sought to first map typical cortical micro- and macrostructure development using invivo MRI in a large sample of healthy term-born infants scanned after birth (n = 259). Then we offer a comprehensive characterization of the cortical consequences of preterm birth in 76 preterm infants scanned at term-equivalent age (37-44 weeks postmenstrual age). We describe the group-average atypicality, the heterogeneity across individual preterm infants, and relate individual deviations from normative development to age at birth and neurodevelopment at 18 months.

RESULTS

In the term-born neonatal brain, we observed heterogeneous and regionally specific associations between age at scan and measures of cortical morphology and microstructure, including rapid surface expansion, greater cortical thickness, lower cortical anisotropy and higher neurite orientation dispersion. By term-equivalent age, preterm infants had on average increased cortical tissue water content and reduced neurite density index in the posterior parts of the cortex, and greater cortical thickness anteriorly compared to term-born infants. While individual preterm infants were more likely to show extreme deviations (over 3.1 standard deviations) from normative cortical maturation compared to term-born infants, these extreme deviations were highly variable and showed very little spatial overlap between individuals. Measures of regional cortical development were associated with age at birth, but not with neurodevelopment at 18 months.

CONCLUSION

We showed that preterm birth alters cortical micro- and macrostructural maturation near the time of full-term birth. Deviations from normative development were highly variable between individual preterm infants.

Human upper-airway respiratory airflow: In vivo comparison of computational fluid dynamics simulations and hyperpolarized 129Xe phase contrast MRI velocimetry

Computational fluid dynamics (CFD) simulations of respiratory airflow have the potential to change the clinical assessment of regional airway function in health and disease, in pulmonary medicine and otolaryngology. For example, in diseases where multiple sites of airway obstruction occur, such as obstructive sleep apnea (OSA), CFD simulations can identify which sites of obstruction contribute most to airway resistance and may therefore be candidate sites for airway surgery. The main barrier to clinical uptake of respiratory CFD to date has been the difficulty in validating CFD results against a clinical gold standard. Invasive instrumentation of the upper airway to measure respiratory airflow velocity or pressure can disrupt the airflow and alter the subject's natural breathing patterns. Therefore, in this study, we instead propose phase contrast (PC) velocimetry magnetic resonance imaging (MRI) of inhaled hyperpolarized 129Xe gas as a non-invasive reference to which airflow velocities calculated via CFD can be compared. To that end, we performed subject-specific CFD simulations in airway models derived from 1H MRI, and using respiratory flowrate measurements acquired synchronously with MRI. Airflow velocity vectors calculated by CFD simulations were then qualitatively and quantitatively compared to velocity maps derived from PC velocimetry MRI of inhaled hyperpolarized 129Xe gas. The results show both techniques produce similar spatial distributions of high velocity regions in the anterior-posterior and foot-head directions, indicating good qualitative agreement. Statistically significant correlations and low Bland-Altman bias between the local velocity values produced by the two techniques indicates quantitative agreement. This preliminary in vivo comparison of respiratory airway CFD and PC MRI of hyperpolarized 129Xe gas demonstrates the feasibility of PC MRI as a technique to validate respiratory CFD and forms the basis for further comprehensive validation studies. This study is therefore a first step in the pathway towards clinical adoption of respiratory CFD.

Phenotyping the Preterm Brain: Characterizing Individual Deviations From Normative Volumetric Development in Two Large Infant Cohorts

The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process regression to create normative curves characterizing brain volumetric development in 274 term-born infants, modeling for age at scan and sex. We then compared 89 preterm infants scanned at term-equivalent age with these normative charts, relating individual deviations from typical volumetric development to perinatal risk factors and later neurocognitive scores. To test generalizability, we used a second independent dataset comprising of 253 preterm infants scanned using different acquisition parameters and scanner. We describe rapid, nonuniform brain growth during the neonatal period. In both preterm cohorts, cerebral atypicalities were widespread, often multiple, and varied highly between individuals. Deviations from normative development were associated with respiratory support, nutrition, birth weight, and later neurocognition, demonstrating their clinical relevance. Group-level understanding of the preterm brain disguises a large degree of individual differences. We provide a method and normative dataset that offer a more precise characterization of the cerebral consequences of preterm birth by profiling the individual neonatal brain.

The Developing Human Connectome Project: typical and disrupted perinatal functional connectivity

The Developing Human Connectome Project is an Open Science project that provides the first large sample of neonatal functional MRI data with high temporal and spatial resolution. These data enable mapping of intrinsic functional connectivity between spatially distributed brain regions under normal and adverse perinatal circumstances, offering a framework to study the ontogeny of large-scale brain organization in humans. Here, we characterize in unprecedented detail the maturation and integrity of resting state networks (RSNs) at term-equivalent age in 337 infants (including 65 born preterm). First, we applied group independent component analysis to define 11 RSNs in term-born infants scanned at 43.5–44.5 weeks postmenstrual age (PMA). Adult-like topography was observed in RSNs encompassing primary sensorimotor, visual and auditory cortices. Among six higher-order, association RSNs, analogues of the adult networks for language and ocular control were identified, but a complete default mode network precursor was not. Next, we regressed the subject-level datasets from an independent cohort of infants scanned at 37–43.5 weeks PMA against the group-level RSNs to test for the effects of age, sex and preterm birth. Brain mapping in term-born infants revealed areas of positive association with age across four of six association RSNs, indicating active maturation in functional connectivity from 37 to 43.5 weeks PMA. Female infants showed increased connectivity in inferotemporal regions of the visual association network. Preterm birth was associated with striking impairments of functional connectivity across all RSNs in a dose-dependent manner; conversely, connectivity of the superior parietal lobules within the lateral motor network was abnormally increased in preterm infants, suggesting a possible mechanism for specific difficulties such as developmental coordination disorder, which occur frequently in preterm children. Overall, we found a robust, modular, symmetrical functional brain organization at normal term age. A complete set of adult-equivalent primary RSNs is already instated, alongside emerging connectivity in immature association RSNs, consistent with a primary-to-higher order ontogenetic sequence of brain development. The early developmental disruption imposed by preterm birth is associated with extensive alterations in functional connectivity.

The effect of airway motion and breathing phase during imaging on CFD simulations of respiratory airflow

RATIONALE

Computational fluid dynamics (CFD) simulations of respiratory airflow can quantify clinically useful information that cannot be obtained directly, such as the work of breathing (WOB), resistance to airflow, and pressure loss. However, patient-specific CFD simulations are often based on medical imaging that does not capture airway motion and thus may not represent true physiology, directly affecting those measurements.

OBJECTIVES

To quantify the variation of respiratory airflow metrics obtained from static models of airway anatomy at several respiratory phases, temporally averaged airway anatomies, and dynamic models that incorporate physiological motion.

METHODS

Neonatal airway images were acquired during free-breathing using 3D high-resolution MRI and reconstructed at several respiratory phases in two healthy subjects and two with airway disease (tracheomalacia). For each subject, five static (end expiration, peak inspiration, end inspiration, peak expiration, averaged) and one dynamic CFD simulations were performed. WOB, airway resistance, and pressure loss across the trachea were obtained for each static simulation and compared with the dynamic simulation results.

RESULTS

Large differences were found in the airflow variables between the static simulations at various respiratory phases and the dynamic simulation. Depending on the static airway model used, WOB, resistance, and pressure loss varied up to 237%, 200%, and 94% compared to the dynamic simulation respectively.

CONCLUSIONS

Changes in tracheal size and shape throughout the breathing cycle directly affect respiratory airflow dynamics and breathing effort. Simulations incorporating realistic airway wall dynamics most closely represent airway physiology; if limited to static simulations, the airway geometry must be obtained during the respiratory phase of interest for a given pathology.

Cortical morphology at birth reflects spatiotemporal patterns of gene expression in the fetal human brain

Interruption to gestation through preterm birth can significantly impact cortical development and have long-lasting adverse effects on neurodevelopmental outcome. We compared cortical morphology captured by high-resolution, multimodal magnetic resonance imaging (MRI) in n = 292 healthy newborn infants (mean age at birth = 39.9 weeks) with regional patterns of gene expression in the fetal cortex across gestation (n = 156 samples from 16 brains, aged 12 to 37 postconceptional weeks [pcw]). We tested the hypothesis that noninvasive measures of cortical structure at birth mirror areal differences in cortical gene expression across gestation, and in a cohort of n = 64 preterm infants (mean age at birth = 32.0 weeks), we tested whether cortical alterations observed after preterm birth were associated with altered gene expression in specific developmental cell populations. Neonatal cortical structure was aligned to differential patterns of cell-specific gene expression in the fetal cortex. Principal component analysis (PCA) of 6 measures of cortical morphology and microstructure showed that cortical regions were ordered along a principal axis, with primary cortex clearly separated from heteromodal cortex. This axis was correlated with estimated tissue maturity, indexed by differential expression of genes expressed by progenitor cells and neurons, and engaged in stem cell differentiation, neuron migration, and forebrain development. Preterm birth was associated with altered regional MRI metrics and patterns of differential gene expression in glial cell populations. The spatial patterning of gene expression in the developing cortex was thus mirrored by regional variation in cortical morphology and microstructure at term, and this was disrupted by preterm birth. This work provides a framework to link molecular mechanisms to noninvasive measures of cortical development in early life and highlights novel pathways to injury in neonatal populations at increased risk of neurodevelopmental disorder.

Interruption to gestation through preterm birth can significantly impact cortical development and have long-lasting adverse effects on neurodevelopmental outcome. A large neuroimaging study of newborn infants reveals how their cortical structure at birth is associated with patterns of gene expression in the fetal cortex and how this relationship is affected by preterm birth.

Reduced structural connectivity in cortico-striatal-thalamic network in neonates with congenital heart disease

Impaired brain development has been observed in newborns with congenital heart disease (CHD). We performed graph theoretical analyses and network-based statistics (NBS) to assess global brain network topology and identify subnetworks of altered connectivity in infants with CHD prior to cardiac surgery. Fifty-eight infants with critical/serious CHD prior to surgery and 116 matched healthy controls as part of the developing Human Connectome Project (dHCP) underwent MRI on a 3T system and high angular resolution diffusion MRI (HARDI) was obtained. Multi-tissue constrained spherical deconvolution, anatomically constrained probabilistic tractography (ACT) and spherical-deconvolution informed filtering of tractograms (SIFT2) was used to construct weighted structural networks. Network topology was assessed and NBS was used to identify structural connectivity differences between CHD and control groups. Structural networks were partitioned into core and peripheral nodes, and edges classed as core, peripheral, or feeder. NBS identified one subnetwork with reduced structural connectivity in CHD infants involving basal ganglia, amygdala, hippocampus, cerebellum, vermis, and temporal and parieto-occipital lobe, primarily affecting core nodes and edges. However, we did not find significantly different global network characteristics in CHD neonates. This locally affected sub-network with reduced connectivity could explain, at least in part, the neurodevelopmental impairments associated with CHD.

Investigating altered brain development in infants with congenital heart disease using tensor-based morphometry

Magnetic resonance (MR) imaging studies have demonstrated reduced global and regional brain volumes in infants with congenital heart disease (CHD). This study aimed to provide a more detailed evaluation of altered structural brain development in newborn infants with CHD compared to healthy controls using tensor-based morphometry (TBM). We compared brain development in 64 infants with CHD to 192 age- and sex-matched healthy controls. T2-weighted MR images obtained prior to surgery were analysed to compare voxel-wise differences in structure across the whole brain between groups. Cerebral oxygen delivery (CDO₂) was measured in infants with CHD (n = 49) using phase contrast MR imaging and the relationship between CDO₂ and voxel-wise brain structure was assessed using TBM. After correcting for global scaling differences, clusters of significant volume reduction in infants with CHD were demonstrated bilaterally within the basal ganglia, thalami, corpus callosum, occipital, temporal, parietal and frontal lobes, and right hippocampus (p < 0.025 after family-wise error correction). Clusters of significant volume expansion in infants with CHD were identified in cerebrospinal fluid spaces (p < 0.025). After correcting for global brain size, there was no significant association between voxel-wise brain structure and CDO₂. This study localizes abnormal brain development in infants with CHD, identifying areas of particular vulnerability.

The developing Human Connectome Project (dHCP) automated resting-state functional processing framework for newborn infants

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An automated and robust pipeline to minimally pre-process highly confounded neonatal fMRI data.

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Includes integrated dynamic distortion and slice-to-volume motion correction.

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A robust multimodal registration approach which includes custom neonatal templates.

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Incorporates an automated and self-reporting QC framework to quantify data quality and identify issues for further inspection.

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Data analysis of 538 infants imaged at 26–45 weeks post-menstrual age.

The developing Human Connectome Project (dHCP) aims to create a detailed 4-dimensional connectome of early life spanning 20–45 weeks post-menstrual age. This is being achieved through the acquisition of multi-modal MRI data from over 1000 in- and ex-utero subjects combined with the development of optimised pre-processing pipelines. In this paper we present an automated and robust pipeline to minimally pre-process highly confounded neonatal resting-state fMRI data, robustly, with low failure rates and high quality-assurance. The pipeline has been designed to specifically address the challenges that neonatal data presents including low and variable contrast and high levels of head motion. We provide a detailed description and evaluation of the pipeline which includes integrated slice-to-volume motion correction and dynamic susceptibility distortion correction, a robust multimodal registration approach, bespoke ICA-based denoising, and an automated QC framework. We assess these components on a large cohort of dHCP subjects and demonstrate that processing refinements integrated into the pipeline provide substantial reduction in movement related distortions, resulting in significant improvements in SNR, and detection of high quality RSNs from neonates.

Development of Microstructural and Morphological Cortical Profiles in the Neonatal Brain

Interruptions to neurodevelopment during the perinatal period may have long-lasting consequences. However, to be able to investigate deviations in the foundation of proper connectivity and functional circuits, we need a measure of how this architecture evolves in the typically developing brain. To this end, in a cohort of 241 term-born infants, we used magnetic resonance imaging to estimate cortical profiles based on morphometry and microstructure over the perinatal period (37–44 weeks postmenstrual age, PMA). Using the covariance of these profiles as a measure of inter-areal network similarity (morphometric similarity networks; MSN), we clustered these networks into distinct modules. The resulting modules were consistent and symmetric, and corresponded to known functional distinctions, including sensory–motor, limbic, and association regions, and were spatially mapped onto known cytoarchitectonic tissue classes. Posterior regions became more morphometrically similar with increasing age, while peri-cingulate and medial temporal regions became more dissimilar. Network strength was associated with age: Within-network similarity increased over age suggesting emerging network distinction. These changes in cortical network architecture over an 8-week period are consistent with, and likely underpin, the highly dynamic processes occurring during this critical period. The resulting cortical profiles might provide normative reference to investigate atypical early brain development.

Modelling brain development to detect white matter injury in term and preterm born neonates

Premature birth occurs during a period of rapid brain growth. In this context, interpreting clinical neuroimaging can be complicated by the typical changes in brain contrast, size and gyrification occurring in the background to any pathology. To model and describe this evolving background in brain shape and contrast, we used a Bayesian regression technique, Gaussian process regression, adapted to multiple correlated outputs. Using MRI, we simultaneously estimated brain tissue intensity on T1- and T2-weighted scans as well as local tissue shape in a large cohort of 408 neonates scanned cross-sectionally across the perinatal period. The resulting model provided a continuous estimate of brain shape and intensity, appropriate to age at scan, degree of prematurity and sex. Next, we investigated the clinical utility of this model to detect focal white matter injury. In individual neonates, we calculated deviations of a neonate's observed MRI from that predicted by the model to detect punctate white matter lesions with very good accuracy (area under the curve > 0.95). To investigate longitudinal consistency of the model, we calculated model deviations in 46 neonates who were scanned on a second occasion. These infants' voxelwise deviations from the model could be used to identify them from the other 408 images in 83% (T2-weighted) and 76% (T1-weighted) of cases, indicating an anatomical fingerprint. Our approach provides accurate estimates of non-linear changes in brain tissue intensity and shape with clear potential for radiological use.

[Intense pulsed light (IPL) as a therapeutic option for Meibomian gland dysfunction]

Meibomian gland dysfunction (MGD) is a common cause of dry eye disease. Intense pulsed light (IPL) treatment is a new and approved therapeutic option for MGD. The treatment consists of 2-4 sessions where light impulses are applied to the lower lid and temporal lid margin. The IPL technique is a safe form of treatment when the required safety precautions are followed. Current studies document an improvement of patients' subjective symptoms and objectively measured clinical parameters.

Assessing the relationship between movement and airflow in the upper airway using computational fluid dynamics with motion determined from magnetic resonance imaging

BACKGROUND

Computational fluid dynamics simulations of respiratory airflow in the upper airway reveal clinically relevant information, including sites of local resistance, inhaled particle deposition, and the effect of pathological constrictions. Unlike previous simulations, which have been performed on rigid anatomical models from static medical imaging, this work utilises ciné imaging during respiration to create dynamic models and more closely represent airway physiology.

METHODS

Airway movement maps were obtained from non-rigid image registration of fast-cine MRI and applied to high-spatial-resolution airway surface models. Breathing flowrates were recorded simultaneously with imaging. These data formed the boundary conditions for large eddy simulation computations of the airflow from exterior mask to bronchi. Simulations with rigid geometries were performed to demonstrate the resulting airflow differences between airflow simulations in rigid and dynamic airways.

FINDINGS

In the analysed rapid breathing manoeuvre, incorporating airway movement significantly changed the findings of the CFD simulations. Peak resistance increased by 19.8% and occurred earlier in the breath. Overall pressure loss decreased by 19.2%, and the proportion of flow in the mouth increased by 13.0%. Airway wall motion was out-of-phase with the air pressure force, demonstrating the presence of neuromuscular motion. In total, the anatomy did 25.2% more work on the air than vice versa.

INTERPRETATIONS

Realistic movement of the airway is incorporated into CFD simulations of airflow in the upper airway for the first time. This motion is vital to producing clinically relevant computational models of respiratory airflow and will allow novel analysis of dynamic conditions, such as sleep apnoea.

Learning-Based Quality Control for Cardiac MR Images

The effectiveness of a cardiovascular magnetic resonance (CMR) scan depends on the ability of the operator to correctly tune the acquisition parameters to the subject being scanned and on the potential occurrence of imaging artifacts, such as cardiac and respiratory motion. In the clinical practice, a quality control step is performed by visual assessment of the acquired images; however, this procedure is strongly operator-dependent, cumbersome, and sometimes incompatible with the time constraints in clinical settings and large-scale studies. We propose a fast, fully automated, and learning-based quality control pipeline for CMR images, specifically for short-axis image stacks. Our pipeline performs three important quality checks: 1) heart coverage estimation; 2) inter-slice motion detection; 3) image contrast estimation in the cardiac region. The pipeline uses a hybrid decision forest method-integrating both regression and structured classification models-to extract landmarks and probabilistic segmentation maps from both long- and short-axis images as a basis to perform the quality checks. The technique was tested on up to 3000 cases from the UK Biobank and on 100 cases from the UK Digital Heart Project and validated against manual annotations and visual inspections performed by expert interpreters. The results show the capability of the proposed pipeline to correctly detect incomplete or corrupted scans (e.g., on UK Biobank, sensitivity and specificity, respectively, 88% and 99% for heart coverage estimation and 85% and 95% for motion detection), allowing their exclusion from the analyzed dataset or the triggering of a new acquisition.

A novel method to generate dynamic boundary conditions for airway CFD by mapping upper airway movement with non-rigid registration of dynamic and static MRI

Computational fluid dynamics (CFD) simulations of airflow in the human airways have the potential to provide a great deal of information that can aid clinicians in case management and surgical decision making, such as airway resistance, energy expenditure, airflow distribution, heat and moisture transfer, and particle deposition, as well as the change in each of these due to surgical interventions. However, the clinical relevance of CFD simulations has been limited to date, as previous models either did not incorporate neuromuscular motion or any motion at all. Many common airway pathologies, such as obstructive sleep apnea (OSA) and tracheomalacia, involve large movements of the structures surrounding the airway, such as the tongue and soft palate. Airway wall motion may be due to many factors including neuromuscular motion, internal aerodynamic forces, and external forces such as gravity. Therefore, to realistically model these airway diseases, a method is required to derive the airway wall motion, whatever the cause, and apply it as a boundary condition to CFD simulations. This paper presents and validates a novel method of capturing in vivo motion of airway walls from magnetic resonance images with high spatiotemporal resolution, through a novel combination of non-rigid image, surface, and surface-normal-vector registration. Coupled with image-synchronous pneumotachography, this technique provides the necessary boundary conditions for dynamic CFD simulations of breathing, allowing the effect of the airway's complex motion to be calculated for the first time, in both normal subjects and those with conditions such as OSA.

Structural brain imaging in Alzheimer's disease and mild cognitive impairment: biomarker analysis and shared morphometry database

Magnetic resonance (MR) imaging is a powerful technique for non-invasive in-vivo imaging of the human brain. We employed a recently validated method for robust cross-sectional and longitudinal segmentation of MR brain images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Specifically, we segmented 5074 MR brain images into 138 anatomical regions and extracted time-point specific structural volumes and volume change during follow-up intervals of 12 or 24 months. We assessed the extracted biomarkers by determining their power to predict diagnostic classification and by comparing atrophy rates to published meta-studies. The approach enables comprehensive analysis of structural changes within the whole brain. The discriminative power of individual biomarkers (volumes/atrophy rates) is on par with results published by other groups. We publish all quality-checked brain masks, structural segmentations, and extracted biomarkers along with this article. We further share the methodology for brain extraction (pincram) and segmentation (MALPEM, MALPEM4D) as open source projects with the community. The identified biomarkers hold great potential for deeper analysis, and the validated methodology can readily be applied to other imaging cohorts.

Construction of a neonatal cortical surface atlas using Multimodal Surface Matching in the Developing Human Connectome Project

We propose a method for constructing a spatio-temporal cortical surface atlas of neonatal brains aged between 36 and 44 weeks of post-menstrual age (PMA) at the time of scan. The data were acquired as part of the Developing Human Connectome Project (dHCP), and the constructed surface atlases are publicly available. The method is based on a spherical registration approach: Multimodal Surface Matching (MSM), using cortical folding for driving the alignment. Templates have been generated for the anatomical cortical surface and for the cortical feature maps: sulcal depth, curvature, thickness, T1w/T2w myelin maps and cortical regions. To achieve this, cortical surfaces from 270 infants were first projected onto the sphere. Templates were then generated in two stages: first, a reference space was initialised via affine alignment to a group average adult template. Following this, templates were iteratively refined through repeated alignment of individuals to the template space until the variability of the average feature sets converged. Finally, bias towards the adult reference was removed by applying the inverse of the average affine transformations on the template and de-drifting the template. We used temporal adaptive kernel regression to produce age-dependant atlases for 9 weeks (36-44 weeks PMA). The generated templates capture expected patterns of cortical development including an increase in gyrification as well as an increase in thickness and T1w/T2w myelination with increasing age.

Data-Driven Differential Diagnosis of Dementia Using Multiclass Disease State Index Classifier

Clinical decision support systems (CDSSs) hold potential for the differential diagnosis of neurodegenerative diseases. We developed a novel CDSS, the PredictND tool, designed for differential diagnosis of different types of dementia. It combines information obtained from multiple diagnostic tests such as neuropsychological tests, MRI and cerebrospinal fluid samples. Here we evaluated how the classifier used in it performs in differentiating between controls with subjective cognitive decline, dementia due to Alzheimer's disease, vascular dementia, frontotemporal lobar degeneration and dementia with Lewy bodies. We used the multiclass Disease State Index classifier, which is the classifier used by the PredictND tool, to differentiate between controls and patients with the four different types of dementia. The multiclass Disease State Index classifier is an extension of a previously developed two-class Disease State Index classifier. As the two-class Disease State Index classifier, the multiclass Disease State Index classifier also offers a visualization of its decision making process, which makes it especially suitable for medical decision support where interpretability of the results is highly important. A subset of the Amsterdam Dementia cohort, consisting of 504 patients (age 65 ± 8 years, 44% females) with data from neuropsychological tests, cerebrospinal fluid samples and both automatic and visual MRI quantifications, was used for the evaluation. The Disease State Index classifier was highly accurate in separating the five classes from each other (balanced accuracy 82.3%). Accuracy was highest for vascular dementia and lowest for dementia with Lewy bodies. For the 50% of patients for which the classifier was most confident on the classification the balanced accuracy was 93.6%. Data-driven CDSSs can be of aid in differential diagnosis in clinical practice. The decision support system tested in this study was highly accurate in separating the different dementias and controls from each other. In addition to the predicted class, it also provides a confidence measure for the classification.

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity.

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity.

Effects of single moor baths on physiological stress response and psychological state: a pilot study

Moor mud applications in the form of packs and baths are widely used therapeutically as part of balneotherapy. They are commonly given as therapy for musculoskeletal disorders, with their thermo-physical effects being furthest studied. Moor baths are one of the key therapeutic elements in our recently developed and evaluated 3-week prevention program for subjects with high stress level and increased risk of developing a burnout syndrome. An embedded pilot study add-on to this core project was carried out to assess the relaxing effect of a single moor bath. During the prevention program, 78 participants received a total of seven moor applications, each consisting of a moor bath (42 °C, 20 min, given between 02:30 and 05:20 p.m.) followed by resting period (20 min). Before and after the first moor application in week 1, and the penultimate moor application in week 3, salivary cortisol was collected, blood pressure and heart rate were measured, and mood state (Multidimensional Mood State Questionnaire) was assessed. A Friedman test of differences among repeated measures was conducted. Post hoc analyses were performed using the Wilcoxon signed-rank test. A significant decrease in salivary cortisol concentration was seen between pre- and post-moor bath in week 1 (Z = -3.355, p = 0.0008). A non-significant decrease was seen between pre- and post-moor bath in week 3. Mood state improved significantly after both moor baths. This pilot study has provided initial evidence on the stress-relieving effects of single moor baths, which can be a sensible and recommendable therapeutic element of multimodal stress-reducing prevention programs. The full potential of moor baths still needs to be validated. A randomized controlled trial should be conducted comparing this balneo-therapeutic approach against other types of stress reduction interventions.

Multimodal surface matching with higher-order smoothness constraints

In brain imaging, accurate alignment of cortical surfaces is fundamental to the statistical sensitivity and spatial localisation of group studies, and cortical surface-based alignment has generally been accepted to be superior to volume-based approaches at aligning cortical areas. However, human subjects have considerable variation in cortical folding, and in the location of functional areas relative to these folds. This makes alignment of cortical areas a challenging problem. The Multimodal Surface Matching (MSM) tool is a flexible, spherical registration approach that enables accurate registration of surfaces based on a variety of different features. Using MSM, we have previously shown that driving cross-subject surface alignment, using areal features, such as resting state-networks and myelin maps, improves group task fMRI statistics and map sharpness. However, the initial implementation of MSM's regularisation function did not penalize all forms of surface distortion evenly. In some cases, this allowed peak distortions to exceed neurobiologically plausible limits, unless regularisation strength was increased to a level which prevented the algorithm from fully maximizing surface alignment. Here we propose and implement a new regularisation penalty, derived from physically relevant equations of strain (deformation) energy, and demonstrate that its use leads to improved and more robust alignment of multimodal imaging data. In addition, since spherical warps incorporate projection distortions that are unavoidable when mapping from a convoluted cortical surface to the sphere, we also propose constraints that enforce smooth deformation of cortical anatomies. We test the impact of this approach for longitudinal modelling of cortical development for neonates (born between 31 and 43 weeks of post-menstrual age) and demonstrate that the proposed method increases the biological interpretability of the distortion fields and improves the statistical significance of population-based analysis relative to other spherical methods.

Aspergillus galactomannan detection in exhaled breath condensate compared to bronchoalveolar lavage fluid for the diagnosis of invasive aspergillosis in immunocompromised patients

OBJECTIVES

Exhaled breath condensate (EBC) is a noninvasive means of sampling the airways that has shown significant promise in the diagnosis of many disorders. There have been no reports of its usefulness in the detection of galactomannan (GM), a component of the cell wall of Aspergillus. The suitability of EBC for the detection of GM for the diagnosis of invasive aspergillosis (IA) using the Platelia Aspergillus enzyme-linked immunosorbent assay was investigated.

METHODS

Prospective, cross-sectional study of lung transplant recipient and haemotologic malignancy patients at a university centre. EBC samples were compared to concomitant bronchoalveolar lavage (BAL) samples among lung transplant recipients and healthy controls. EBC was collected over 10 minutes using a refrigerated condenser according to the European Respiratory Society/American Thoracic Society recommendations, with the BAL performed immediately thereafter.

RESULTS

A total of 476 EBC specimens with 444 matched BAL specimens collected from lung transplant recipients (n = 197) or haemotologic malignancy patients (n = 133) were examined. Both diluted and untreated EBC optical density (OD) values (0.0830, interquartile range (IQR) 0.0680-0.1040; and 0.1130, IQR 0.0940-0.1383), respectively, from all patients regardless of clinical syndrome were significantly higher than OD values in healthy control EBCs (0.0508, IQR 0.0597-0.0652; p < 0.0001). However, the OD index values did not correlate with the diagnosis of IA (44 samples were associated with IA). Furthermore, no significant correlation was found between EBC GM and the matched BAL specimen.

CONCLUSIONS

GM is detectable in EBC; however, no correlation between OD index values and IA was noted in lung transplant recipients.

Five-class differential diagnostics of neurodegenerative diseases using random undersampling boosting

Differentiating between different types of neurodegenerative diseases is not only crucial in clinical practice when treatment decisions have to be made, but also has a significant potential for the enrichment of clinical trials. The purpose of this study is to develop a classification framework for distinguishing the four most common neurodegenerative diseases, including Alzheimer's disease, frontotemporal lobe degeneration, Dementia with Lewy bodies and vascular dementia, as well as patients with subjective memory complaints. Different biomarkers including features from images (volume features, region-wise grading features) and non-imaging features (CSF measures) were extracted for each subject. In clinical practice, the prevalence of different dementia types is imbalanced, posing challenges for learning an effective classification model. Therefore, we propose the use of the RUSBoost algorithm in order to train classifiers and to handle the class imbalance training problem. Furthermore, a multi-class feature selection method based on sparsity is integrated into the proposed framework to improve the classification performance. It also provides a way for investigating the importance of different features and regions. Using a dataset of 500 subjects, the proposed framework achieved a high accuracy of 75.2% with a balanced accuracy of 69.3% for the five-class classification using ten-fold cross validation, which is significantly better than the results using support vector machine or random forest, demonstrating the feasibility of the proposed framework to support clinical decision making.