Publications

Psychotic disorders are severe, debilitating, and even fatal. The development of targeted and effective interventions for psychosis depends upon on clear understanding of the timing and nature of disease progression to target processes amenable to intervention. Strong evidence suggests early and ongoing neuroprogressive changes, but timing and inflection points remain unclear and likely differ across cognitive, clinical, and brain measures. Additionally, granular evidence across modalities is particularly sparse in the "bridging years" between first episode and established illness-years that may be especially critical for improving outcomes and during which interventions may be maximally effective. Our objective is the systematic, multimodal characterization of neuroprogression through the early course of illness in a cross-diagnostic sample of patients with psychosis. We aim to (1) interrogate neurocognition, structural brain measures, and network connectivity at multiple assessments over the first eight years of illness to map neuroprogressive trajectories, and (2) examine trajectories as predictors of clinical and functional outcomes. We will recruit 192 patients with psychosis and 36 healthy controls. Assessments will occur at baseline and 8- and 16-month follow ups using clinical, cognitive, and imaging measures. We will employ an accelerated longitudinal design (ALD), which permits ascertainment of data across a longer timeframe and at more frequent intervals than would be possible in a single cohort longitudinal study. Results from this study are expected to hasten identification of actionable treatment targets that are closely associated with clinical outcomes, and identify subgroups who share common neuroprogressive trajectories toward the development of individualized treatments.

OBJECTIVE: To date, the use of a fibrinogen concentrate (FC) administered in children with inherited fibrinogen deficiency is poorly documented. Treatment modalities may differ from those of adults. The aim of this study was to investigate the pharmacokinetics (PK), efficacy (bleeding/surgery) and safety of a triple-secured FC (FibCLOT, LFB, France) in young patients aged of 12 years or less. METHODS: This was a prospective, non-comparative, multicentre, phase 2-3 study. Estimated PK parameters were based on population PK modelling. Target fibrinogen levels were 1.2 and 1.0 g/L for major and minor events, respectively. In vivo recovery (IVR) was calculated at study entry to tailor the dose.

The outermost layer of the skin is the stratum corneum (SC), which is mainly comprised of solid proteins and lipids. Minor amounts of mobile proteins and lipids are crucial for the macroscopic properties of the SC, including softness, elasticity and barrier function. Still this minor number of mobile components are not well characterized in terms of structure or amount. Conventional quantitative direct polarization (Q-DP) 13C solid-state NMR gives signal amplitudes proportional to concentrations, but fails to quantify the SC mobile components because of spectral overlap with the overwhelming signals from the solids. Spectral editing with the INEPT scheme suppresses the signals from solids, but also modulates the amplitudes of the mobile components depending on their values of the transverse relaxation times T2, scalar couplings JCH, and number of covalently bound hydrogens nH. This study describes a quantitative INEPT (Q-INEPT) method relying on systematic variation of the INEPT timing variables to estimate T2, JCH, nH, and amplitude for each of the resolved resonances from the mobile components. Q-INEPT is validated with a series of model systems containing molecules with different hydrophobicity and dynamics. For selected systems where Q-DP is applicable, the results of Q-INEPT and Q-DP are similar with respect to the linearity and uncertainty of the obtained molar ratios. Utilizing a reference compound with known concentration, we quantify the concentrations of mobile lipids and proteins within the mainly solid SC. By melting all lipids at high temperature, we obtain the total lipid concentration. These Q-INEPT results are the first steps towards a quantitative understanding of the relations between mobile component concentrations and SC macroscopic properties.

This prospective, multicenter, single-arm, open-label phase 3 study aimed to evaluate the efficacy and safety of IqYmune in patients with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP). Patients received one induction dose of 2 g/kg and then seven maintenance doses of 1 g/kg at 3-week intervals. The primary endpoint was the responder rate at the end of study (EOS), defined as an improvement of >=1 point on the adjusted inflammatory neuropathy cause and treatment (INCAT) disability scale. The responder rate was compared with the responder rate of a historical placebo group (33.3%). Secondary endpoints included changes from baseline to EOS of adjusted INCAT disability score, grip strength, Medical Research Council (MRC) sum score, Rasch-modified MRC sum score, Rasch-built overall disability scale score and the clinical global impression. Forty-two patients, including 23 Ig-na ıve and 19 Ig-pre-treated, were included in the efficacy set. The overall response rate at EOS was 76.2% (95% confidence interval [60.5%-87.9%]). The superiority of IqYmune compared to the historical placebo control was demonstrated (P

Schizophrenia is a severe mental disorder with often a chronic course. Neuroimaging studies report brain abnormalities in both white and gray matter structures. However, the relationship between microstructural white matter differences and volumetric subcortical structures is not known. We investigated 30 long-term treated patients with schizophrenia and schizoaffective disorder (mean age 51.1 ± 7.9 years, mean illness duration 27.6 ± 8.0 years) and 42 healthy controls (mean age 54.1 ± 9.1 years) using 3 T diffusion and structural magnetic resonance imaging. The free-water imaging method was used to model the diffusion signal, and subcortical volumes were obtained from FreeSurfer. We applied multiple linear regression to investigate associations between (i) patient status and regional white matter microstructure, (ii) medication dose or clinical symptoms on white matter microstructure in patients, and (iii) for interactions between subcortical volumes and diagnosis on microstructural white matter regions showing significant patient-control differences. The patients had significantly decreased free-water corrected fractional anisotropy (FA), explained by decreased axial diffusivity and increased radial diffusivity (RD) bilaterally in the anterior corona radiata (ACR) and the left anterior limb of the internal capsule (ALIC) compared to controls. In the fornix, the patients had significantly increased RD. In patients, positive symptoms were associated with localized increased free-water and negative symptoms with localized decreased FA and increased RD. There were significant interactions between patient status and several subcortical structures on white matter microstructure and the free-water compartment for left ACR and fornix, and limited to the free-water compartment for right ACR and left ALIC. The Cohen’s d effect sizes were medium to large (0.61 to 1.20, absolute values). The results suggest a specific pattern of frontal white matter axonal degeneration and demyelination and fornix demyelination that is attenuated in the presence of larger structures of the limbic system in patients with chronic schizophrenia and schizoaffective disorder. Findings warrant replication in larger samples.

Accurately and precisely characterizing the morphology of small pulmonary structures from Computed Tomography (CT) images, such as airways and vessels, is becoming of great importance for diagnosis of pulmonary diseases. The smaller conducting airways are the major site of increased airflow resistance in chronic obstructive pulmonary disease (COPD), while accurately sizing vessels can help identify arterial and venous changes in lung regions that may determine future disorders. However, traditional methods are often limited due to image resolution and artifacts. We propose a Convolutional Neural Regressor (CNR) that provides cross-sectional measurement of airway lumen, airway wall thickness, and vessel radius. CNR is trained with data created by a generative model of synthetic structures which is used in combination with Simulated and Unsupervised Generative Adversarial Network (SimGAN) to create simulated and refined airways and vessels with known ground-truth. For validation, we first use synthetically generated airways and vessels produced by the proposed generative model to compute the relative error and directly evaluate the accuracy of CNR in comparison with traditional methods. Then, in-vivo validation is performed by analyzing the association between the percentage of the predicted forced expiratory volume in one second (FEV1%) and the value of the Pi10 parameter, two well-known measures of lung function and airway disease, for airways. For vessels, we assess the correlation between our estimate of the small-vessel blood volume and the lungs’ diffusing capacity for carbon monoxide (DLCO). The results demonstrate that Convolutional Neural Networks (CNNs) provide a promising direction for accurately measuring vessels and airways on chest CT images with physiological correlates.

The structure of the human brain has been studied extensively. Despite all the knowledge accrued, direct information about connections, from origin to termination, in the human brain is extremely limited. Yet there is a widespread misperception that human connectional neuroanatomy is well-established and validated. In this article, we consider what is known directly about human structural and connectional neuroanatomy. Information on neuroanatomical connections in the human brain is derived largely from studies in non-human experimental models in which the entire connectional pathway, including origins, course, and terminations, is directly visualized. Techniques to examine structural connectivity in the human brain are progressing rapidly; nevertheless, our present understanding of such connectivity is limited largely to data derived from homological comparisons, particularly with non-human primates. We take the position that an in-depth and more precise understanding of human connectional neuroanatomy will be obtained by a systematic application of this homological approach.

OBJECTIVE: The cochlear nucleus (CN) is the target of the auditory brainstem implant (ABI). Most ABI candidates have Neurofibromatosis Type 2 (NF2) and distorted brainstem anatomy from bilateral vestibular schwannomas. The CN is difficult to characterize as routine structural MRI does not resolve detailed anatomy. We hypothesize that diffusion tensor imaging (DTI) enables both in vivo localization and quantitative measurements of CN morphology. STUDY DESIGN: We analyzed 7 Tesla (T) DTI images of 100 subjects (200 CN) and relevant anatomic structures using an MRI brainstem atlas with submillimetric (50 μm) resolution. SETTING: Tertiary referral center. PATIENTS: Young healthy normal hearing adults. INTERVENTION: Diagnostic. MAIN OUTCOME MEASURES: Diffusion scalar measures such as fractional anisotropy (FA), mean diffusivity (MD), mode of anisotropy (Mode), principal eigenvectors of the CN, and the adjacent inferior cerebellar peduncle (ICP). RESULTS: The CN had a lamellar structure and ventral-dorsal fiber orientation and could be localized lateral to the inferior cerebellar peduncle (ICP). This fiber orientation was orthogonal to tracts of the adjacent ICP where the fibers run mainly caudal-rostrally. The CN had lower FA compared to the medial aspect of the ICP (0.44 ± 0.09 vs. 0.64 ± 0.08, p 

Measuring fibre dispersion in white matter with diffusion magnetic resonance imaging (MRI) is limited by an inherent degeneracy between fibre dispersion and microscopic diffusion anisotropy (i.e., the diffusion anisotropy expected for a single fibre orientation). This means that estimates of fibre dispersion rely on strong assumptions, such as constant microscopic anisotropy throughout the white matter or specific biophysical models. Here we present a simple approach for resolving this degeneracy using measurements that combine linear (conventional) and spherical tensor diffusion encoding. To test the accuracy of the fibre dispersion when our microstructural model is only an approximation of the true tissue structure, we simulate multi-compartment data and fit this with a single-compartment model. For such overly simplistic tissue assumptions, we show that the bias in fibre dispersion is greatly reduced ( 5x) for single-shell linear and spherical tensor encoding data compared with single-shell or multi-shell conventional data. In in-vivo data we find a consistent estimate of fibre dispersion as we reduce the b-value from 3 to 1.5 ms/μm, increase the repetition time, increase the echo time, or increase the diffusion time. We conclude that the addition of spherical tensor encoded data to conventional linear tensor encoding data greatly reduces the sensitivity of the estimated fibre dispersion to the model assumptions of the tissue microstructure.

Diffusion tensor distribution (DTD) imaging builds on principles from diffusion, solid-state and low-field NMR spectroscopies, to quantify the contents of heterogeneous voxels as nonparametric distributions, with tensor "size", "shape" and orientation having direct relations to corresponding microstructural properties of biological tissues. The approach requires the acquisition of multiple images as a function of the magnitude, shape and direction of the diffusion-encoding gradients, leading to long acquisition times unless fast image read-out techniques like EPI are employed. While in previous in vivo human brain studies performed at 3 T this proved a viable option, porting these measurements to very high magnetic fields and/or to heterogeneous organs induces B - and B -inhomogeneity artifacts that challenge the limits of EPI. To overcome such challenges, we demonstrate here that high spatial resolution DTD of mouse brain can be carried out at 15.2 T with a surface-cryoprobe, by relying on SPatiotemporal ENcoding (SPEN) imaging sequences. These new acquisition and data-processing protocols are demonstrated with measurements on in vivo mouse brain, and validated with synthetic phantoms designed to mimic the diffusion properties of white matter, gray matter and cerebrospinal fluid. While still in need of full extensions to 3D mappings and of scanning additional animals to extract more general physiological conclusions, this work represents another step towards the model-free, noninvasive in vivo characterization of tissue microstructure and heterogeneity in animal models, at ≈0.1 mm resolutions.