BACKGROUND: Acute anorexia nervosa (AN) is characterized by reduced brain mass and corresponding increased sulcal and ventricular cerebrospinal fluid. Recent studies of white matter using diffusion tensor imaging consistently identified alterations in the fornix, such as reduced fractional anisotropy (FA). However, because the fornix penetrates the ventricles, it is prone to cerebrospinal fluid-induced partial volume effects that interfere with a valid assessment of FA. We investigated the hypothesis that in the acute stage of AN, FA of the fornix is markedly affected by ventricular volumes.
METHODS: First, using diffusion tensor imaging data we established the inverse associations between forniceal FA and volumes of the third and lateral ventricles in a prestudy with 32 healthy subjects to demonstrate the strength of ventricular influence on forniceal FA independent of AN. Second, we investigated a sample of 25 acute AN patients and 25 healthy control subjects.
RESULTS: Using ventricular volumes as covariates markedly reduced the group effect of forniceal FA, even with tract-based spatial statistics focusing only on the center of the fornix. In addition, after correcting for free water on voxel level, the group differences in forniceal FA between AN patients and controls disappeared completely.
CONCLUSIONS: It is unlikely that microstructural changes affecting FA occurred in the fornix of AN patients. Previously identified alterations in acute AN may have been biased by partial volume effects and the proposed central role of this structure in the pathophysiology may need to be reconsidered. Future studies on white matter alterations in AN should carefully deal with partial volume effects.
Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations.
Low fat-free mass index (FFMI) is an independent risk factor for mortality in chronic obstructive pulmonary disease (COPD) not typically measured during routine care. In the present study, we aimed to derive fat-free mass from the pectoralis muscle area (FFM) and assess whether low FFMIis associated with all-cause mortality in COPD cases. We used data from two independent COPD cohorts, ECLIPSE and COPDGene.Two equal sized groups of COPD cases (n=759) from the ECLIPSE study were used to derive and validate an equation to calculate the FFMmeasured using bioelectrical impedance from PMA. We then applied the equation in COPD cases (n=3121) from the COPDGene cohort, and assessed survival. Low FFMIwas defined, using the Schols classification (FFMI <16 in men, FFMI <15 in women) and the fifth percentile normative values of FFMI from the UK Biobank.The final regression model included PMA, weight, sex and height, and had an adjusted Rof 0.92 with fat-free mass (FFM) as the outcome. In the test group, the correlation between FFMand FFM remained high (Pearson correlation=0.97). In COPDGene, COPD cases with a low FFMIhad an increased risk of death (HR 1.6, p<0.001).We demonstrated COPD cases with a low FFMIhave an increased risk of death.
Schizophrenia is characterized by deficits in gesturing that is important for nonverbal communication. Research in healthy participants and brain-damaged patients revealed a left-lateralized fronto-parieto-temporal network underlying gesture performance. First evidence from structural imaging studies in schizophrenia corroborates these results. However, as of yet, it is unclear if cortical thickness abnormalities contribute to impairments in gesture performance. We hypothesized that patients with deficits in gesture production show cortical thinning in 12 regions of interest (ROIs) of a gesture network relevant for gesture performance and recognition. Forty patients with schizophrenia and 41 healthy controls performed hand and finger gestures as either imitation or pantomime. Group differences in cortical thickness between patients with deficits, patients without deficits, and controls were explored using a multivariate analysis of covariance. In addition, the relationship between gesture recognition and cortical thickness was investigated. Patients with deficits in gesture production had reduced cortical thickness in eight ROIs, including the pars opercularis of the inferior frontal gyrus, the superior and inferior parietal lobes, and the superior and middle temporal gyri. Gesture recognition correlated with cortical thickness in fewer, but mainly the same, ROIs within the patient sample. In conclusion, our results show that impaired gesture production and recognition in schizophrenia is associated with cortical thinning in distinct areas of the gesture network.
Compound exocytosis is considered the most massive mode of exocytosis, during which the membranes of secretory granules (SGs) fuse with each other to form a channel through which the entire contents of their granules is released. The underlying mechanisms of compound exocytosis remain largely unresolved. Here we show that the small GTPase Rab5, a known regulator of endocytosis, is pivotal for compound exocytosis in mast cells. Silencing of Rab5 shifts receptor-triggered secretion from a compound to a full exocytosis mode, in which SGs individually fuse with the plasma membrane. Moreover, we show that Rab5 is essential for FcεRI-triggered association of the SNARE protein SNAP23 with the SGs. Direct evidence is provided for SNAP23 involvement in homotypic SG fusion that occurs in the activated cells. Finally, we show that this fusion event is prevented by inhibition of the IKKβ2 kinase, however, neither a phosphorylation-deficient nor a phosphomimetic mutant of SNAP23 can mediate homotypic SG fusion in triggered cells. Taken together our findings identify Rab5 as a heretofore-unrecognized regulator of compound exocytosis that is essential for SNAP23-mediated granule-granule fusion. Our results also implicate phosphorylation cycles in controlling SNAP23 SNARE function in homotypic SG fusion.
Objective: Repetitive subconcussive head impacts (RSHI) may lead to structural, functional, and metabolic alterations of the brain. While differences between males and females have already been suggested following a concussion, whether there are sex differences following exposure to RSHI remains unknown. The aim of this study was to identify and to characterize sex differences following exposure to RSHI. Methods: Twenty-five collegiate ice hockey players (14 males and 11 females, 20.6 ± 2.0 years), all part of the Hockey Concussion Education Project (HCEP), underwent diffusion-weighted magnetic resonance imaging (dMRI) before and after the Canadian Interuniversity Sports (CIS) ice hockey season 2011-2012 and did not experience a concussion during the season. Whole-brain tract-based spatial statistics (TBSS) were used to compare pre- and postseason imaging in both sexes for fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). Pre- and postseason neurocognitive performance were assessed by the Immediate Post-Concussion Assessment and Cognitive Test (ImPACT). Results: Significant differences between the sexes were primarily located within the superior longitudinal fasciculus (SLF), the internal capsule (IC), and the corona radiata (CR) of the right hemisphere (RH). In significant voxel clusters (p < 0.05), decreases in FA (absolute difference pre- vs. postseason: 0.0268) and increases in MD (0.0002), AD (0.00008), and RD (0.00005) were observed in females whereas males showed no significant changes. There was no significant correlation between the change in diffusion scalar measures over the course of the season and neurocognitive performance as evidenced from postseason ImPACT scores. Conclusions: The results of this study suggest sex differences in structural alterations following exposure to RSHI. Future studies need to investigate further the underlying mechanisms and association with exposure and clinical outcomes.
Hydration is a key aspect of the skin that influences its physical and mechanical properties. Here, we investigate the interplay between molecular and macroscopic properties of the outer skin layer - the stratum corneum (SC) and how this varies with hydration. It is shown that hydration leads to changes in the molecular arrangement of the peptides in the keratin filaments as well as dynamics of C-H bond reorientation of amino acids in the protruding terminals of keratin protein within the SC. The changes in molecular structure and dynamics occur at a threshold hydration corresponding to ca. 85% relative humidity (RH). The abrupt changes in SC molecular properties coincide with changes in SC macroscopic swelling properties as well as mechanical properties in the SC. The flexible terminals at the solid keratin filaments can be compared to flexible polymer brushes in colloidal systems, creating long-range repulsion and extensive swelling in water. We further show that the addition of urea to the SC at reduced RH leads to similar molecular and macroscopic responses as the increase in RH for SC without urea. The findings provide new molecular insights to deepen the understanding of how intermediate filament organization responds to changes in the surrounding environment.
Diffusion MRI (dMRI) is the only noninvasive method for mapping white matter connections in the brain. We describe SlicerDMRI, a software suite that enables visualization and analysis of dMRI for neuroscientific studies and patient-specific anatomic assessment. SlicerDMRI has been successfully applied in multiple studies of the human brain in health and disease, and here, we especially focus on its cancer research applications. As an extension module of the 3D Slicer medical image computing platform, the SlicerDMRI suite enables dMRI analysis in a clinically relevant multimodal imaging workflow. Core SlicerDMRI functionality includes diffusion tensor estimation, white matter tractography with single and multi-fiber models, and dMRI quantification. SlicerDMRI supports clinical DICOM and research file formats, is open-source and cross-platform, and can be installed as an extension to 3D Slicer (www.slicer.org). More information, videos, tutorials, and sample data are available at dmri.slicer.org.
Migraine is a common neurological disease with a high prevalence and unsatisfactory treatment options. The specific pathophysiological mechanisms of migraine remain unclear, which restricts the development of effective treatments for this prevalent disorder. The aims of this study were to 1) compare the spontaneous brain activity differences between Migraine without Aura (MwoA) patients and healthy controls (HCs), using amplitude of low-frequency fluctuations (ALFF) calculation method, and 2) explore how an effective treatment (verum acupuncture) could modulate the ALFF of MwoA patients. One hundred MwoA patients and forty-six matched HCs were recruited. Patients were randomized to four weeks' verum acupuncture, sham acupuncture, and waiting list groups. Patients had resting state BOLD-fMRI scan before and after treatment, while HCs only had resting state BOLD-fMRI scan at baseline. Headache intensity, headache frequency, self-rating anxiety and self-rating depression were used for clinical efficacy evaluation. Compared with HCs, MwoA patients showed increased ALFF in posterior insula and putamen/caudate, and reduced ALFF in rostral ventromedial medulla (RVM)/trigeminocervical complex (TCC). After longitudinal verum acupuncture treatment, the decreased ALFF of the RVM/TCC was normalized in migraine patients. Verum acupuncture and sham acupuncture have different modulation effects on ALFF of RVM/TCC in migraine patients. Our results suggest that impairment of the homeostasis of the trigeminovascular nociceptive pathway is involved in the neural pathophysiology of migraines. Effective treatments, such as verum acupuncture, could help to restore this imbalance.
PURPOSE: This study was a systematic evaluation across different and prominent diffusion MRI models to better understand the ways in which scalar metrics are influenced by experimental factors, including experimental design (diffusion-weighted imaging [DWI] sampling) and noise. METHODS: Four diffusion MRI models-diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator MRI (MAP-MRI), and neurite orientation dispersion and density imaging (NODDI)-were evaluated by comparing maps and histogram values of the scalar metrics generated using DWI datasets obtained in fixed mouse brain with different noise levels and DWI sampling complexity. Additionally, models were fit with different input parameters or constraints to examine the consequences of model fitting procedures. RESULTS: Experimental factors affected all models and metrics to varying degrees. Model complexity influenced sensitivity to DWI sampling and noise, especially for metrics reporting non-Gaussian information. DKI metrics were highly susceptible to noise and experimental design. The influence of fixed parameter selection for the NODDI model was found to be considerable, as was the impact of initial tensor fitting in the MAP-MRI model. CONCLUSION: Across DTI, DKI, MAP-MRI, and NODDI, a wide range of dependence on experimental factors was observed that elucidate principles and practical implications for advanced diffusion MRI.
PURPOSE: Accurate segmentation of lung nodules is crucial in the development of imaging biomarkers for predicting malignancy of the nodules. Manual segmentation is time consuming and affected by inter-observer variability. We evaluated the robustness and accuracy of a publically available semiautomatic segmentation algorithm that is implemented in the 3D Slicer Chest Imaging Platform (CIP) and compared it with the performance of manual segmentation.
METHODS: CT images of 354 manually segmented nodules were downloaded from the LIDC database. Four radiologists performed the manual segmentation and assessed various nodule characteristics. The semiautomatic CIP segmentation was initialized using the centroid of the manual segmentations, thereby generating four contours for each nodule. The robustness of both segmentation methods was assessed using the region of uncertainty (δ) and Dice similarity index (DSI). The robustness of the segmentation methods was compared using the Wilcoxon-signed rank test (pWilcoxon<0.05). The Dice similarity index (DSIAgree) between the manual and CIP segmentations was computed to estimate the accuracy of the semiautomatic contours.
RESULTS: The median computational time of the CIP segmentation was 10 s. The median CIP and manually segmented volumes were 477 ml and 309 ml, respectively. CIP segmentations were significantly more robust than manual segmentations (median δCIP = 14ml, median dsiCIP = 99% vs. median δmanual = 222ml, median dsimanual = 82%) with pWilcoxon~10-16. The agreement between CIP and manual segmentations had a median DSIAgree of 60%. While 13% (47/354) of the nodules did not require any manual adjustment, minor to substantial manual adjustments were needed for 87% (305/354) of the nodules. CIP segmentations were observed to perform poorly (median DSIAgree≈50%) for non-/sub-solid nodules with subtle appearances and poorly defined boundaries.
CONCLUSION: Semi-automatic CIP segmentation can potentially reduce the physician workload for 13% of nodules owing to its computational efficiency and superior stability compared to manual segmentation. Although manual adjustment is needed for many cases, CIP segmentation provides a preliminary contour for physicians as a starting point.
We propose a method for the automated identification of key white matter fiber tracts for neurosurgical planning, and we apply the method in a retrospective study of 18 consecutive neurosurgical patients with brain tumors. Our method is designed to be relatively robust to challenges in neurosurgical tractography, which include peritumoral edema, displacement, and mass effect caused by mass lesions. The proposed method has two parts. First, we learn a data-driven white matter parcellation or fiber cluster atlas using groupwise registration and spectral clustering of multi-fiber tractography from healthy controls. Key fiber tract clusters are identified in the atlas. Next, patient-specific fiber tracts are automatically identified using tractography-based registration to the atlas and spectral embedding of patient tractography. Results indicate good generalization of the data-driven atlas to patients: 80% of the 800 fiber clusters were identified in all 18 patients, and 94% of the 800 fiber clusters were found in 16 or more of the 18 patients. Automated subject-specific tract identification was evaluated by quantitative comparison to subject-specific motor and language functional MRI, focusing on the arcuate fasciculus (language) and corticospinal tracts (motor), which were identified in all patients. Results indicate good colocalization: 89 of 95, or 94%, of patient-specific language and motor activations were intersected by the corresponding identified tract. All patient-specific activations were within 3mm of the corresponding language or motor tract. Overall, our results indicate the potential of an automated method for identifying fiber tracts of interest for neurosurgical planning, even in patients with mass lesions.
We introduce a novel Bayesian nonparametric model that uses the concept of disease trajectories for disease subtype identification. Although our model is general, we demonstrate that by treating fractions of tissue patterns derived from medical images as compositional data, our model can be applied to study distinct progression trends between population subgroups. Specifically, we apply our algorithm to quantitative emphysema measurements obtained from chest CT scans in the COPDGene Study and show several distinct progression patterns. As emphysema is one of the major components of chronic obstructive pulmonary disease (COPD), the third leading cause of death in the United States , an improved definition of emphysema and COPD subtypes is of great interest. We investigate several models with our algorithm, and show that one with age , pack years (a measure of cigarette exposure), and smoking status as predictors gives the best compromise between estimated predictive performance and model complexity. This model identified nine subtypes which showed significant associations to seven single nucleotide polymorphisms (SNPs) known to associate with COPD. Additionally, this model gives better predictive accuracy than multiple, multivariate ordinary least squares regression as demonstrated in a five-fold cross validation analysis. We view our subtyping algorithm as a contribution that can be applied to bridge the gap between CT-level assessment of tissue composition to population-level analysis of compositional trends that vary between disease subtypes.
Experts have previously postulated a linkage between lupus associated vascular pathology and abnormal brain barriers in the immunopathogenesis of neuropsychiatric lupus. Nevertheless, there are some discrepancies between the experimental evidence, or its interpretation, and the working hypotheses prevalent in this field; specifically, that a primary contributor to neuropsychiatric disease in lupus is permeabilization of the blood brain barrier. In this commonly held view, any contribution of the other known brain barriers, including the blood-cerebrospinal fluid and meningeal barriers, is mostly excluded from the discussion. In this review we will shed light on some of the blood brain barrier hypotheses and try to trace their roots. In addition, we will suggest new research directions to allow for confirmation of alternative interpretations of the experimental evidence linking the pathology of intra-cerebral vasculature to the pathogenesis of neuropsychiatric lupus.
Diffusion tensor imaging (DTI) studies in chronic schizophrenia have found widespread but often inconsistent patterns of white matter abnormalities. These studies have typically used the conventional measure of fractional anisotropy, which can be contaminated by extracellular free-water. A recent free-water imaging study reported reduced free-water corrected fractional anisotropy (FA) in chronic schizophrenia across several brain regions, but limited changes in the extracellular volume. The present study set out to validate these findings in a substantially larger sample. Tract-based spatial statistics (TBSS) was performed in 188 healthy controls and 281 chronic schizophrenia patients. Forty-two regions of interest (ROIs), as well as average whole-brain FAand FW were extracted from free-water corrected diffusion tensor maps. Compared to healthy controls, reduced FAwas found in the chronic schizophrenia group in the anterior limb of the internal capsule bilaterally, the posterior thalamic radiation bilaterally, as well as the genu and body of the corpus callosum. While a significant main effect of group was observed for FW, none of the follow-up contrasts survived correction for multiple comparisons. The observed FAreductions in the absence of extracellular FW changes, in a large, multi-site sample of chronic schizophrenia patients, validate the pattern of findings reported by a previous, smaller free-water imaging study of a similar sample. The limited number of regions in which FAwas reduced in the schizophrenia group suggests that actual white matter tissue degeneration in chronic schizophrenia, independent of extracellular FW, might be more localized than suggested previously.
BACKGROUND: Smoking-related lung injury may manifest on CT scans as both emphysema and interstitial changes. We have developed an automated method to quantify interstitial changes and hypothesized that this measurement would be associated with lung function, quality of life, mortality, and a mucin 5B (MUC5B) polymorphism.
METHODS: Using CT scans from the Genetic Epidemiology of COPD Study, we objectively labeled lung parenchyma as a tissue subtype. We calculated the percentage of the lung occupied by interstitial subtypes.
RESULTS: A total of 8,345 participants had clinical and CT scanning data available. A 5% absolute increase in interstitial changes was associated with an absolute decrease in FVC % predicted of 2.47% (P < .001) and a 1.36-point higher St. George's Respiratory Questionnaire score (P < .001). Among the 6,827 participants with mortality data, a 5% increase in interstitial changes was associated with a 29% increased risk of death (P < .001). These associations were present in a subgroup without visually defined interstitial lung abnormalities, as well as in those with normal spirometric test results, and in those without chronic respiratory symptoms. In non-Hispanic whites, for each copy of the minor allele of the MUC5B promoter polymorphism, there was a 0.64% (P < .001) absolute increase in the percentage of lung with interstitial changes.
CONCLUSIONS: Objective interstitial changes on CT scans were associated with impaired lung function, worse quality of life, increased mortality, and more copies of a MUC5B promoter polymorphism, suggesting that these changes may be a marker of susceptibility to smoking-related lung injury, detectable even in those who are healthy by other measures.
PURPOSE: To evaluate and compare the volumetric tumor burden changes during crizotinib therapy in mice and human cohorts with ALK-rearranged non-small-cell lung cancer (NSCLC).
METHODS: Volumetric tumor burden was quantified on serial imaging studies in 8 bitransgenic mice with ALK-rearranged adenocarcinoma treated with crizotinib, and in 33 human subjects with ALK-rearranged NSCLC treated with crizotinib. The volumetric tumor burden changes and the time to maximal response were compared between mice and humans.
RESULTS: The median tumor volume decrease (%) at the maximal response was -40.4% (range: -79.5%-+11.7%) in mice, and -72.9% (range: -100%-+72%) in humans (Wilcoxon p=0.03). The median time from the initiation of therapy to maximal response was 6 weeks in mice, and 15.7 weeks in humans. Overall volumetric response rate was 50% in mice and 97% in humans. Spider plots of tumor volume changes during therapy demonstrated durable responses in the human cohort, with a median time on therapy of 13.1 months.
CONCLUSION: The present study described an initial attempt to evaluate quantitative tumor burden changes in co-clinical imaging studies of genomically-matched mice and human cohorts with ALK-rearranged NSCLC treated with crizotinib. Differences are noted in the degree of maximal volume response between the two cohorts in this well-established paradigm of targeted therapy, indicating a need for further studies to optimize co-clinical trial design and interpretation.
A recent Editorial in Cognitive Neuroscience reconsiders the findings of our work on the accuracy of false positive rate control with cluster inference in functional magnetic resonance imaging (fMRI), in particular criticizing our use of resting-state fMRI as a source for null data in the evaluation of task fMRI methods. We defend this use of resting fMRI data, as while there is much structure in this data, we argue it is representative of task data noise and task analysis software should be able to accommodate this noise. We also discuss a potential problem with Slotnick's own method.