Natural oscillatory modes of 3D deformation of the human brain in vivo.

Natural modes and frequencies of three-dimensional (3D) deformation of the human brain were identified from in vivo tagged magnetic resonance images (MRI) acquired dynamically during transient mild acceleration of the head. Twenty 3D strain fields, estimated from tagged MRI image volumes in 19 adult subjects, were analyzed using dynamic mode decomposition (DMD). These strain fields represented dynamic, 3D brain deformations during constrained head accelerations, either involving rotation about the vertical axis of the neck or neck extension. DMD results reveal fundamental oscillatory modes of deformation at damped frequencies near 7 Hz (in neck rotation) and 11 Hz (in neck extension). Modes at these frequencies were found consistently among all subjects. These characteristic features of 3D human brain deformation are important for understanding the response of the brain in head impacts and provide valuable quantitative criteria for the evaluation and use of computer models of brain mechanics.

A 3D Computational Head Model Under Dynamic Head Rotation and Head Extension Validated Using Live Human Brain Data, Including the Falx and the Tentorium.

We employ an advanced 3D computational model of the head with high anatomical fidelity, together with measured tissue properties, to assess the consequences of dynamic loading to the head in two distinct modes: head rotation and head extension. We use a subject-specific computational head model, using the material point method, built from T1 magnetic resonance images, and considering the anisotropic properties of the white matter which can predict strains in the brain under large rotational accelerations. The material model now includes the shear anisotropy of the white matter. We validate the model under head rotation and head extension motions using live human data, and advance a prior version of the model to include biofidelic falx and tentorium. We then examine the consequences of incorporating the falx and tentorium in terms of the predictions from the computational head model.

Automated Integration of Multimodal MRI for the Probabilistic Detection of the Central Vein Sign in White Matter Lesions.

BACKGROUND AND PURPOSE: The central vein sign is a promising MR imaging diagnostic biomarker for multiple sclerosis. Recent studies have demonstrated that patients with MS have higher proportions of white matter lesions with the central vein sign compared with those with diseases that mimic MS on MR imaging. However, the clinical application of the central vein sign as a biomarker is limited by interrater differences in the adjudication of the central vein sign as well as the time burden required for the determination of the central vein sign for each lesion in a patient's full MR imaging scan. In this study, we present an automated technique for the detection of the central vein sign in white matter lesions. MATERIALS AND METHODS: Using multimodal MR imaging, the proposed method derives a central vein sign probability, πij, for each lesion, as well as a patient-level central vein sign biomarker, ψi. The method is probabilistic in nature, allows site-specific lesion segmentation methods, and is potentially robust to intersite variability. The proposed algorithm was tested on imaging acquired at the University of Vermont in 16 participants who have MS and 15 participants who do not. RESULTS: By means of the proposed automated technique, participants with MS were found to have significantly higher values of ψ than those without MS (ψMS = 0.55 ± 0.18; ψnon-MS = 0.31 ± 0.12; P < .001). The algorithm was also found to show strong discriminative ability between patients with and without MS, with an area under the curve of 0.88. CONCLUSIONS: The current study presents the first fully automated method for detecting the central vein sign in white matter lesions and demonstrates promising performance in a sample of patients with and without MS.

Genetic relationships among Vietnamese local pigs investigated using genome-wide SNP markers.

Vietnam is one of the most important countries for pig domestication, and a total of 26 local breeds have been reported. In the present study, genetic relationships among the various pig breeds were investigated using 90 samples collected from local pigs (15 breeds) in 15 distantly separated, distinct areas of the country and six samples from Landrace pigs in Hanoi as an out-group of a common Western breed. All samples were genotyped using the Illumina Porcine SNP60 v2 Genotyping BeadChip. We used 15 160-15 217 SNPs that showed a high degree of polymorphism in the Vietnamese breeds for identifying genetic relationships among the Vietnamese breeds. Principal components analysis showed that most pigs indigenous to Vietnam formed clusters correlated with their original geographic locations. Some Vietnamese breeds formed a cluster that was genetically related to the Western breed Landrace, suggesting the possibility of crossbreeding. These findings will be useful for the conservation and management of Vietnamese local pig breeds.

Volumetric Analysis from a Harmonized Multisite Brain MRI Study of a Single Subject with Multiple Sclerosis.

BACKGROUND AND PURPOSE: MR imaging can be used to measure structural changes in the brains of individuals with multiple sclerosis and is essential for diagnosis, longitudinal monitoring, and therapy evaluation. The North American Imaging in Multiple Sclerosis Cooperative steering committee developed a uniform high-resolution 3T MR imaging protocol relevant to the quantification of cerebral lesions and atrophy and implemented it at 7 sites across the United States. To assess intersite variability in scan data, we imaged a volunteer with relapsing-remitting MS with a scan-rescan at each site. MATERIALS AND METHODS: All imaging was acquired on Siemens scanners (4 Skyra, 2 Tim Trio, and 1 Verio). Expert segmentations were manually obtained for T1-hypointense and T2 (FLAIR) hyperintense lesions. Several automated lesion-detection and whole-brain, cortical, and deep gray matter volumetric pipelines were applied. Statistical analyses were conducted to assess variability across sites, as well as systematic biases in the volumetric measurements that were site-related. RESULTS: Systematic biases due to site differences in expert-traced lesion measurements were significant (P < .01 for both T1 and T2 lesion volumes), with site explaining >90% of the variation (range, 13.0-16.4 mL in T1 and 15.9-20.1 mL in T2) in lesion volumes. Site also explained >80% of the variation in most automated volumetric measurements. Output measures clustered according to scanner models, with similar results from the Skyra versus the other 2 units. CONCLUSIONS: Even in multicenter studies with consistent scanner field strength and manufacturer after protocol harmonization, systematic differences can lead to severe biases in volumetric analyses.

Neutrophil autophagy and extracellular DNA traps contribute to airway inflammation in severe asthma.

BACKGROUND: Autophagy and neutrophil extracellular DNA traps (NETs) are implicated in asthma; however, their roles in asthma pathogenesis have not been elucidated. OBJECTIVES: We compared autophagy and NET production levels from peripheral blood neutrophils (PBNs) of patients with severe asthma (SA) and non-severe asthma (NSA). Additionally, we investigated the inflammatory effects of NETs on human airway epithelial cells (AECs) and peripheral blood eosinophils (PBEs). METHODS: Peripheral blood neutrophils from patients with SA (n = 30) and NSA (n = 38) were treated with interleukin (IL)-8 (100 ng/mL). Autophagy (light chain 3-II expression) and NET production levels were evaluated by Western blot, immunofluorescence microscopy, and PicoGreen assay. The effects of NETs on AECs were assessed by investigating cell death, cell detachment, expression of occludin and claudin-1, and IL-8 production; the effects of NETs on PBEs were examined by investigating the activation and release of eosinophil cationic protein (ECP) and eosinophil-derived neurotoxin (EDN). RESULTS: Untreated and IL-8-treated PBNs from the SA group produced higher autophagy and NET levels compared with those from the NSA group (P < 0.01). IL-8 increased autophagy and NET levels in PBNs from the SA group, but not from the NSA group. NET levels were correlated with autophagy levels in PBNs (P < 0.001). IL-8-induced NET production levels negatively were correlated with FEV1/FVC (r = -0.700, P = 0.016). NETs induced cell death, detachment, degradation of occludin and claudin-1, and IL-8 production from AECs. Higher levels of NET-induced ECP and EDN were released from PBEs in SA compared with NSA groups. CONCLUSIONS AND CLINICAL RELEVANCE: Neutrophil autophagy and NETs could enhance asthma severity by damaging airway epithelium and triggering inflammatory responses of AECs and PBEs. Modulating neutrophil autophagy and NET production may be a new target therapy for SA.

Autophagy mechanisms in sputum and peripheral blood cells of patients with severe asthma: a new therapeutic target.

BACKGROUND: Autophagy and genetic predisposition have been suggested to potentially play roles in the development of asthma. However, little is known about the role of autophagy in the pathogenesis of severe asthma. OBJECTIVE: We compared autophagy in the sputum granulocytes, peripheral blood cells (PBCs) and peripheral blood eosinophils (PBEs) between patients with severe asthma and those with non-severe asthma and investigated the functional effects of autophagy. METHODS: We enrolled 36 patients with severe asthma, 14 with non-severe asthma and 23 normal healthy controls in this study. Sputum granulocytes, PBCs and PBEs were isolated from each subject. Autophagy was evaluated based on the expression of microtubule-associated protein light chain 3 (LC3) by Western blot, confocal microscopy, transmission electron microscopy and flow cytometry. IL-8 levels were measured by ELISA. To induce autophagy, HL-60 cells, human primary small airway epithelial cells (SAECs) and A549 cells were treated with IL-5, IL-1ß and TNF-α. To inhibit autophagy, PI3K inhibitors (LY29400 and 3-methyladenine [3-MA]) and hydroxychloroquine (HCQ) were used. Knockdown of ATG5 and Beclin-1 was performed in A549 cells, and the therapeutic effects of dexamethasone were evaluated. RESULTS: Higher autophagy levels were noted in sputum granulocytes, PBCs and PBEs from patients with severe asthma than from patients with non-severe asthma and healthy controls (P < 0.05 for all). IL-5 increased autophagy levels in both PBCs and PBEs (P < 0.05). 3-MA attenuated the increased expression of LC3-II and eosinophil cationic protein in HL-60 cells induced by IL-5 (P = 0.034 for both). Dexamethasone did not affect autophagy levels in PBEs. IL-1ß increased LC3-II expression and IL-8 production (P < 0.01) in SAECs, and this was attenuated by LY294002, 3-MA, HCQ and knockdown of ATG5 and Beclin-1 (in A549 cells) (P < 0.01). CONCLUSIONS AND CLINICAL RELEVANCE: Autophagy could play a role in the pathogenesis of severe asthma. Autophagy modulation may be a novel therapeutic target for conventional therapy-resistant severe asthma.

Rapid, high-resolution, whole-brain, susceptibility-based MRI of multiple sclerosis.

BACKGROUND: Susceptibility-based MRI offers a unique opportunity to study neurological diseases such as multiple sclerosis (MS). In this work, we assessed a three-dimensional segmented echo-planar-imaging (3D-EPI) sequence to rapidly acquire high-resolution T2 -weighted and phase contrast images of the whole brain. We also assessed if these images could depict important features of MS at clinical field strength, and we tested the effect of a gadolinium-based contrast agent (GBCA) on these images. MATERIALS AND METHODS: The 3D-EPI acquisition was performed on four healthy volunteers and 15 MS cases on a 3T scanner. The 3D sagittal images of the whole brain were acquired with a voxel size of 0.55 × 0.55 × 0.55 mm(3) in less than 4 minutes. For the MS cases, the 3D-EPI acquisition was performed before, during, and after intravenous GBCA injection. RESULTS: Both T2-weighted and phase-contrast images from the 3D-EPI acquisition were sensitive to the presence of lesions, parenchymal veins, and tissue iron. Conspicuity of the veins was enhanced when images were obtained during injection of GBCA. CONCLUSIONS: We propose this rapid imaging sequence for investigating, in a clinical setting, the spatiotemporal relationship between small parenchymal veins, iron deposition, and lesions in MS patient brains.

MRI of the corpus callosum in multiple sclerosis: association with disability.

Inflammatory demyelination and axon damage in the corpus callosum are prominent features of multiple sclerosis (MS) and may partially account for impaired performance on complex tasks. The objective of this article was to characterize quantitative callosal MRI abnormalities and their association with disability. In 69 participants with MS and 29 healthy volunteers, lesional and extralesional callosal MRI indices were estimated via diffusion tensor tractography. expanded disability status scale (EDSS) and MS functional composite (MSFC) scores were recorded in 53 of the participants with MS. All tested callosal MRI indices were diffusely abnormal in MS. EDSS score was correlated only with age (r = 0.51). Scores on the overall MSFC and its paced serial auditory addition test (PASAT) and 9-hole peg test components were correlated with callosal fractional anisotropy (r = 0.27, 0.35, and 0.31, respectively) and perpendicular diffusivity (r = -0.29, -0.30, and -0.31) but not with overall callosal volume or callosal lesion volume; the PASAT score was more weakly correlated with callosal magnetization-transfer ratio (r = 0.21). Anterior callosal abnormalities were associated with impaired PASAT performance and posterior abnormalities with slow performance on the 9-hole peg test. In conclusion, abnormalities in the corpus callosum can be assessed with quantitative MRI and are associated with cognitive and complex upper-extremity dysfunction in MS.

Treatment outcome of asthma after one year follow-up in health centres of several developing countries.

SETTING: Seven selected out-patient clinics caring for asthma patients in Algeria, Guinea, Morocco, Syria, Turkey and Vietnam. DESIGN: Evaluation of treatment outcomes after one year of follow-up of a cohort of asthma patients consecutively enrolled in a prospective study evaluating routine practice. RESULTS: Among 310 asthma patients registered, the following outcomes were recorded after one year of follow-up: 95 (31%) successful, 61 (20%) under control, 35 (11%) failed, 116 (37%) defaulted and 3 (1%) transferred. Among the 167 (53.9%) patients still on treatment after one year there was a substantial increase in the proportion of patients classified as intermittent at the end of treatment (from 11% to 53%), with a decrease in all categories of persistent asthma (from 34% to 12% for mild, 45% to 28% for moderate and 10% to 8% for severe asthma). CONCLUSIONS: While patients' quality of life can be improved if they follow regular treatment, the key challenge in providing care is to ensure that patients adhere to their treatment.

Implementation of asthma guidelines in health centres of several developing countries.

SETTING: Nine selected out-patient clinics caring for asthma patients in Algeria, Guinea, Ivory Coast, Kenya, Mali, Morocco, Syria, Turkey and Vietnam. DESIGN: Prospective enrolment of consecutive patients considered by the practitioner to have asthma with evaluation of adherence of the practitioner with recommended standard case management, including proportion of patients confirmed to have asthma, proportion in whom severity was correctly graded and proportion in whom treatment with inhaled corticosteroids corresponded to severity grade. RESULTS: Of 499 consecutive patients, 456 (91%) were enrolled and evaluated. The diagnosis was confirmed in 263 (58%). Agreement between the practitioner and the guidelines in assigning grade of severity was moderate overall (kappa = 0.42). It was higher for assignment of grade using symptoms (K = 0.51), but poor for assignment of grade using peak expiratory flow (PEF) rate (kappa = 0.29), with practitioners tending to underestimate the severity. Agreement between the practitioners' assessment of severity and treatment with inhaled corticosteroids was poor (kappa = 0.18), with underutilisation of inhaled corticosteroids. CONCLUSIONS: Practitioners caring for asthma patients in this study tended to underutilise the PEF rate in assessing their patients and underutilised treatment of patients with inhaled corticosteroids.

Affordability of inhaled corticosteroids as a potential barrier to treatment of asthma in some developing countries.

SETTING: The cost and availability of the medications required for the treatment of asthma may represent potential barriers to effective management. METHOD: A survey of prices and policies for components of asthma treatment in 1998, in Algeria, Burkina Faso, Ivory Coast, Guinea, Mali, Syria, Turkey and Vietnam. RESULTS: Medications were consistently available in only four of the eight countries studied. The cost of essential medications for standard case management varied by over five times for beclomethasone and by over three times for inhaled salbutamol. In all but two countries, the cost of one year of drugs for treatment of a moderate, persistent case exceeded the monthly salary of a nurse in that country. The essential drugs list included inhaled salbutamol in five of eight countries and beclomethasone in three of eight. The costs of medications were lower where generic preparations were available and, to a lesser extent, where the medications are on the essential drugs list. CONCLUSIONS: The cost and availability of medications vary widely, and may represent an important barrier to effective management in some low and middle income countries.

Current methods in medical image segmentation.

Image segmentation plays a crucial role in many medical-imaging applications, by automating or facilitating the delineation of anatomical structures and other regions of interest. We present a critical appraisal of the current status of semi-automated and automated methods for the segmentation of anatomical medical images. Terminology and important issues in image segmentation are first presented. Current segmentation approaches are then reviewed with an emphasis on the advantages and disadvantages of these methods for medical imaging applications. We conclude with a discussion on the future of image segmentation methods in biomedical research.

Adaptive fuzzy segmentation of magnetic resonance images.

An algorithm is presented for the fuzzy segmentation of two-dimensional (2-D) and three-dimensional (3-D) multispectral magnetic resonance (MR) images that have been corrupted by intensity inhomogeneities, also known as shading artifacts. The algorithm is an extension of the 2-D adaptive fuzzy C-means algorithm (2-D AFCM) presented in previous work by the authors. This algorithm models the intensity inhomogeneities as a gain field that causes image intensities to smoothly and slowly vary through the image space. It iteratively adapts to the intensity inhomogeneities and is completely automated. In this paper, we fully generalize 2-D AFCM to three-dimensional (3-D) multispectral images. Because of the potential size of 3-D image data, we also describe a new faster multigrid-based algorithm for its implementation. We show, using simulated MR data, that 3-D AFCM yields lower error rates than both the standard fuzzy C-means (FCM) algorithm and two other competing methods, when segmenting corrupted images. Its efficacy is further demonstrated using real 3-D scalar and multispectral MR brain images.

Reconstruction of the human cerebral cortex from magnetic resonance images.

Reconstructing the geometry of the human cerebral cortex from MR images is an important step in both brain mapping and surgical path planning applications. Difficulties with imaging noise, partial volume averaging, image intensity inhomogeneities, convoluted cortical structures, and the requirement to preserve anatomical topology make the development of accurate automated algorithms particularly challenging. In this paper we address each of these problems and describe a systematic method for obtaining a surface representation of the geometric central layer of the human cerebral cortex. Using fuzzy segmentation, an isosurface algorithm, and a deformable surface model, the method reconstructs the entire cortex with the correct topology, including deep convoluted sulci and gyri. The method is largely automated and its results are robust to imaging noise, partial volume averaging, and image intensity inhomogeneities. The performance of this method is demonstrated, both qualitatively and quantitatively, and the results of its application to six subjects and one simulated MR brain volume are presented.

The importance of quality control of sputum smear microscopy: the effect of reading errors on treatment decisions and outcomes.

SETTING: Ho Chi Minh City, Vietnam. OBJECTIVE: To evaluate the impact of slide reading errors at peripheral level on case-finding and treatment decisions. DESIGN: Over a 6-month period in 1997, information on date, type of slide, results of other slides from the patient, and treatment status was collected for all slides from district TB centers detected as having reading errors during smear microscopy quality control re-readings. RESULTS: Reading errors were detected in 117 slides: 115 (98.3%) were incorrectly read as negative, and 75 (65.2%) of these errors occurred in case-finding slides. In the 75 falsely negative case-finding slides, re-reading resulted in initiation of treatment in 38 patients (50.7%). The remaining 37 (49.3%) had only one positive slide and were told to return for follow-up after 6 months; the two (5.4%) who did return were both diagnosed with active TB. Detection of errors in the 40 false-negative follow-up slides resulted in treatment changes in four patients (10%). CONCLUSIONS: Quality control plays a critical role in helping to ensure the timely diagnosis and treatment of new TB cases and appropriate management of patients currently on treatment. The usefulness of quality control could be enhanced by focusing greater efforts on case-finding slides initially read as negative.

Quality control of smear microscopy for acid-fast bacilli: the case for blinded re-reading.

SETTING: Quality control of sputum smear microscopy, which is essential for ensuring correct tuberculosis (TB) diagnosis, is often performed through the unblinded rereading of all positive slides and a sample of negative slides. OBJECTIVE: To assess misclassification error introduced by knowledge of prior results. METHODS: The Southern Vietnam Regional TB Laboratory prepared three gold-standard sets of 750 slides: an unblinded set, an unblinded set in which 13% of negative slides were replaced by weakly positive slides purposefully mislabelled as negative, and a blinded set. Six provincial technicians who normally perform district quality control each reread 125 slides from each set. RESULTS: In the three sets only one negative slide was misread as positive. In the unblinded set (referent), 2.9% (9/311) positive slides were misread as negative, compared with 18.7% (57/305) in the blinded set (prevalence ratio [PR] = 6.5; 95% confidence interval [CI] 3.3-12.8; P < 0.001), and 11.3% (33/293) in the unblinded set with mislabelled slides (PR = 3.9; 95%CI 1.9-8.0; P < 0.001). CONCLUSIONS: False-negative error was more common than false-positive error. Knowledge of prior reading influences re-reading. Blinded re-reading of systematically selected slides would appear preferable, although this method requires high levels of proficiency among quality control technicians.

An image-processing system for qualitative and quantitative volumetric analysis of brain images.

In this work, we developed, implemented, and validated an image-processing system for qualitative and quantitative volumetric analysis of brain images. This system allows the visualization and quantitation of global and regional brain volumes. Global volumes were obtained via an automated adaptive Bayesian segmentation technique that labels the brain into white matter, gray matter, and cerebrospinal fluid. Absolute volumetric errors for these compartments ranged between 1 and 3% as indicated by phantom studies. Quantitation of regional brain volumes was performed through normalization and tessellation of segmented brain images into the Talairach space with a 3D elastic warping model. Retest reliability of regional volumes measured in Talairach space indicated errors of < 1.5% for the frontal, parietal, temporal, and occipital brain regions. Additional regional analysis was performed with an automated hybrid method combining a region-of-interest approach and voxel-based analysis, named Regional Analysis of Volumes Examined in Normalized Space (RAVENS). RAVENS analysis for several subcortical structures showed good agreement with operator-defined volumes. This system has sufficient accuracy for longitudinal imaging data and is currently being used in the analysis of neuroimaging data of the Baltimore Longitudinal Study of Aging.