Publications by Year: 2016

BACKGROUND: Emphysema is characterised by distinct pathological sub-types, but little is known about the divergent underlying aetiology. Matrix-metalloproteinases (MMPs) are proteolytic enzymes that can degrade the extracellular matrix and have been identified as potentially important in the development of emphysema. However, the relationship between MMPs and emphysema sub-type is unknown. We investigated the role of MMPs and their inhibitors in the development of emphysema sub-types by quantifying levels and determining relationships with these sub-types in mild-moderate COPD patients and ex/current smokers with preserved lung function. METHODS: Twenty-four mild-moderate COPD and 8 ex/current smokers with preserved lung function underwent high resolution CT and distinct emphysema sub-types were quantified using novel local histogram-based assessment of lung density. We analysed levels of MMPs and tissue inhibitors of MMPs (TIMPs) in bronchoalveolar lavage (BAL) and assessed their relationship with these emphysema sub-types. RESULTS: The most prevalent emphysema subtypes in COPD subjects were mild and moderate centrilobular (CLE) emphysema, while only small amounts of severe centrilobular emphysema, paraseptal emphysema (PSE) and panlobular emphysema (PLE) were present. MMP-3, and -10 associated with all emphysema sub-types other than mild CLE, while MMP-7 and -8 had associations with moderate and severe CLE and PSE. MMP-9 also had associations with moderate CLE and paraseptal emphysema. Mild CLE occurred in substantial quantities irrespective of whether airflow obstruction was present and did not show any associations with MMPs. CONCLUSION: Multiple MMPs are directly associated with emphysema sub-types identified by CT imaging, apart from mild CLE. This suggests that MMPs play a significant role in the tissue destruction seen in the more severe sub-types of emphysema, whereas early emphysematous change may be driven by a different mechanism. TRIAL REGISTRATION: Trial registration number NCT01701869 .

The National Alliance for Medical Image Computing (NA-MIC) was launched in 2004 with the goal of investigating and developing an open source software infrastructure for the extraction of information and knowledge from medical images using computational methods. Several leading research and engineering groups participated in this effort that was funded by the US National Institutes of Health through a variety of infrastructure grants. This effort transformed 3D Slicer from an internal, Boston-based, academic research software application into a professionally maintained, robust, open source platform with an international leadership and developer and user communities. Critical improvements to the widely used underlying open source libraries and tools-VTK, ITK, CMake, CDash, DCMTK-were an additional consequence of this effort. This project has contributed to close to a thousand peer-reviewed publications and a growing portfolio of US and international funded efforts expanding the use of these tools in new medical computing applications every year. In this editorial, we discuss what we believe are gaps in the way medical image computing is pursued today; how a well-executed research platform can enable discovery, innovation and reproducible science ("Open Science"); and how our quest to build such a software platform has evolved into a productive and rewarding social engineering exercise in building an open-access community with a shared vision.

BACKGROUND: Salience network (SN) dysconnectivity has been hypothesized to contribute to schizophrenia. Nevertheless, little is known about the functional and structural dysconnectivity of SN in subjects at risk for psychosis. We hypothesized that SN functional and structural connectivity would be disrupted in subjects with At-Risk Mental State (ARMS) and would be associated with symptom severity and disease progression. METHOD: We examined 87 ARMS and 37 healthy participants using both resting-state functional magnetic resonance imaging and diffusion tensor imaging. Group differences in SN functional and structural connectivity were examined using a seed-based approach and tract-based spatial statistics. Subject-level functional connectivity measures and diffusion indices of disrupted regions were correlated with CAARMS scores and compared between ARMS with and without transition to psychosis. RESULTS: ARMS subjects exhibited reduced functional connectivity between the left ventral anterior insula and other SN regions. Reduced fractional anisotropy (FA) and axial diffusivity were also found along white-matter tracts in close proximity to regions of disrupted functional connectivity, including frontal-striatal-thalamic circuits and the cingulum. FA measures extracted from these disrupted white-matter regions correlated with individual symptom severity in the ARMS group. Furthermore, functional connectivity between the bilateral insula and FA at the forceps minor were further reduced in subjects who transitioned to psychosis after 2 years. CONCLUSIONS: Our findings support the insular dysconnectivity of the proximal SN hypothesis in the early stages of psychosis. Further developed, the combined structural and functional SN assays may inform the prognosis of persons at-risk for psychosis.

Animal models play a critical role in the study of acute respiratory distress syndrome (ARDS) and ventilator-induced lung injury (VILI). One limitation has been the lack of a suitable method for serial assessment of acute lung injury (ALI) in vivo. In this study, we demonstrate the sensitivity of magnetic resonance imaging (MRI) to assess ALI in real time in rat models of VILI. Sprague-Dawley rats were untreated or treated with intratracheal lipopolysaccharide or PBS. After 48 h, animals were mechanically ventilated for up to 15 h to induce VILI. Free induction decay (FID)-projection images were made hourly. Image data were collected continuously for 30 min and divided into 13 phases of the ventilatory cycle to make cinematic images. Interleaved measurements of respiratory mechanics were performed using a flexiVent ventilator. The degree of lung infiltration was quantified in serial images throughout the progression or resolution of VILI. MRI detected VILI significantly earlier (3.8 ± 1.6 h) than it was detected by altered lung mechanics (9.5 ± 3.9 h, P = 0.0156). Animals with VILI had a significant increase in the Index of Infiltration (P = 0.0027), and early regional lung infiltrates detected by MRI correlated with edema and inflammatory lung injury on histopathology. We were also able to visualize and quantify regression of VILI in real time upon institution of protective mechanical ventilation. Magnetic resonance lung imaging can be utilized to investigate mechanisms underlying the development and propagation of ALI, and to test the therapeutic effects of new treatments and ventilator strategies on the resolution of ALI.

We study the influence of diffusion on NMR experiments when the molecules undergo random motion under the influence of a force field and place special emphasis on parabolic (Hookean) potentials. To this end, the problem is studied using path integral methods. Explicit relationships are derived for commonly employed gradient waveforms involving pulsed and oscillating gradients. The Bloch-Torrey equation, describing the temporal evolution of magnetization, is modified by incorporating potentials. A general solution to this equation is obtained for the case of parabolic potential by adopting the multiple correlation function (MCF) formalism, which has been used in the past to quantify the effects of restricted diffusion. Both analytical and MCF results were found to be in agreement with random walk simulations. A multidimensional formulation of the problem is introduced that leads to a new characterization of diffusion anisotropy. Unlike the case of traditional methods that employ a diffusion tensor, anisotropy originates from the tensorial force constant, and bulk diffusivity is retained in the formulation. Our findings suggest that some features of the NMR signal that have traditionally been attributed to restricted diffusion are accommodated by the Hookean model. Under certain conditions, the formalism can be envisioned to provide a viable approximation to the mathematically more challenging restricted diffusion problems.

Diffusion tensor imaging (DTI) tractography and functional magnetic resonance imaging (fMRI) are powerful techniques to elucidate the anatomical and functional aspects of brain connectivity. However, integrating these approaches to describe the precise link between structure and function within specific brain circuits remains challenging. In this study, a novel DTI-fMRI integration method is proposed, to provide the topographical characterization and the volumetric assessment of the functional and anatomical connections within the language circuit. In a group of 21 healthy elderly subjects (mean age 68.5 ± 5.8 years), the volume of connection between the cortical activity elicited by a verbal fluency task and the cortico-cortical fiber tracts associated with this function are mapped and quantified. An application of the method to a case study in neuro-rehabilitation context is also presented. Integrating structural and functional data within the same framework, this approach provides an overall view of white and gray matter when studying specific brain circuits.

In Parkinson’s disease (PD), pathological microstructural changes occur and such changes might be detected using diffusion magnetic resonance imaging (dMRI). However, it is unclear whether dMRI improves PD diagnosis or helps differentiating between phenotypes, such as postural instability gait difficulty (PIGD) and tremor dominant (TD) PD. We included 105 patients with PD and 44 healthy controls (HC), all of whom underwent dMRI as part of the prospective Swedish BioFINDER study. Diffusion kurtosis imaging (DKI) and neurite density imaging (NDI) analyses were performed using regions of interest in the basal ganglia, the thalamus, the pons and the midbrain as well as tractography of selected white matter tracts. In the putamen, the PD group showed increased mean diffusivity (MD) (p = .003), decreased fractional anisotropy (FA) (p = .001) and decreased mean kurtosis (MK), compared to HC (p = .024). High MD and a low MK in the putamen were associated with more severe motor and cognitive symptomatology (p .05). Also, patients with PIGD exhibited increased MD in the putamen compared to the TD patients (p = .009). In the thalamus, MD was increased (p = .001) and FA was decreased (p = .032) in PD compared to HC. Increased MD and decreased FA correlated negatively with motor speed and balance (p .05). In the superior longitudinal fasciculus (SLF), MD (p = .019) and fiso were increased in PD compared to HC (p = .03). These changes correlated negatively with motor speed (p .002) and balance (p .037). However, most of the observed changes in PD were also present in cases with either multiple system atrophy (n = 11) or progressive supranuclear palsy (n = 10). In conclusion, PD patients exhibit microstructural changes in the putamen, the thalamus, and the SLF, which are associated with worse disease severity. However, the dMRI changes are not sufficiently specific to improve the diagnostic work-up of PD. Longitudinal studies should evaluate whether dMRI measures can be used to track disease progression.

Negative affective stimuli elicit behavioral and neural responses which vary on a continuum from adaptive to maladaptive, yet are typically investigated in a dichotomous manner (healthy controls vs. psychiatric diagnoses). This practice may limit our ability to fully capture variance from acute responses to negative affective stimuli to psychopathology at the extreme end. To address this, we conducted a functional magnetic resonance imaging study to examine the neural responses to negative valence/high arousal and neutral valence/low arousal images as a function of dysphoric mood and sex across individuals (n = 99) who represented traditional categories of healthy controls, major depressive disorder, bipolar psychosis, and schizophrenia. Observation of negative (vs. neutral) stimuli elicited blood oxygen-level dependent responses in the following circuitry: periaqueductal gray, hypothalamus (HYPO), amygdala (AMYG), hippocampus (HIPP), orbitofrontal cortex (OFC), medial prefrontal cortex (mPFC), and greater connectivity between AMYG and mPFC. Across all subjects, severity of dysphoric mood was associated with hyperactivity of HYPO, and, among females, right (R) AMYG. Females also demonstrated inverse relationships between severity of dysphoric mood and connectivity between HYPO - R OFC, R AMYG - R OFC, and R AMYG - R HIPP. Overall, our findings demonstrated sex-dependent deficits in response to negative affective stimuli increasing as a function of dysphoric mood state. Females demonstrated greater inability to regulate arousal as mood became more dysphoric. These findings contribute to elucidating biosignatures associated with response to negative stimuli across disorders and suggest the importance of a sex-dependent lens in determining these biosignatures. Hum Brain Mapp 37:3733-3744, 2016. © 2016 Wiley Periodicals, Inc.

The most widely used task functional magnetic resonance imaging (fMRI) analyses use parametric statistical methods that depend on a variety of assumptions. In this work, we use real resting-state data and a total of 3 million random task group analyses to compute empirical familywise error rates for the fMRI software packages SPM, FSL, and AFNI, as well as a nonparametric permutation method. For a nominal familywise error rate of 5%, the parametric statistical methods are shown to be conservative for voxelwise inference and invalid for clusterwise inference. Our results suggest that the principal cause of the invalid cluster inferences is spatial autocorrelation functions that do not follow the assumed Gaussian shape. By comparison, the nonparametric permutation test is found to produce nominal results for voxelwise as well as clusterwise inference. These findings speak to the need of validating the statistical methods being used in the field of neuroimaging.