Publications

The question whether our brain pathways adhere to a geometric grid structure has been a popular topic of debate in the diffusion imaging and neuroscience societies. Wedeen et al. (2012a, b) proposed that the brain’s white matter is organized like parallel sheets of interwoven pathways. Catani et al. (2012) concluded that this grid pattern is most likely an artifact, resulting from methodological biases that cause the tractography pathways to cross in orthogonal angles. To date, ambiguities in the mathematical conditions for a sheet structure to exist (e.g. its relation to orthogonal angles) combined with the lack of extensive quantitative evidence have prevented wide acceptance of the hypothesis. In this work, we formalize the relevant terminology and recapitulate the condition for a sheet structure to exist. Note that this condition is not related to the presence or absence of orthogonal crossing fibers, and that sheet structure is defined formally as a surface formed by two sets of interwoven pathways intersecting at arbitrary angles within the surface. To quantify the existence of sheet structure, we present a novel framework to compute the sheet probability index (SPI), which reflects the presence of sheet structure in discrete orientation data (e.g. fiber peaks derived from diffusion MRI). With simulation experiments we investigate the effect of spatial resolution, curvature of the fiber pathways, and measurement noise on the ability to detect sheet structure. In real diffusion MRI data experiments we can identify various regions where the data supports sheet structure (high SPI values), but also areas where the data does not support sheet structure (low SPI values) or where no reliable conclusion can be drawn. Several areas with high SPI values were found to be consistent across subjects, across multiple data sets obtained with different scanners, resolutions, and degrees of diffusion weighting, and across various modeling techniques. Under the strong assumption that the diffusion MRI peaks reflect true axons, our results would therefore indicate that pathways do not form sheet structures at every crossing fiber region but instead at well-defined locations in the brain. With this framework, sheet structure location, extent, and orientation could potentially serve as new structural features of brain tissue. The proposed method can be extended to quantify sheet structure in directional data obtained with techniques other than diffusion MRI, which is essential for further validation.

BACKGROUND: There is growing evidence to suggest that delusions associated with schizophrenia arise from altered structural brain connectivity. The present study investigated whether structural changes in three major fasciculi that interconnect the limbic system - the cingulum bundle, uncinate fasciculus and fornix - are associated with delusions in chronic schizophrenia patients. METHODS: Free-water corrected Diffusion Tensor Imaging was used to investigate the association between delusions and both microstructural changes within these three fasciculi and extracellular changes in the surrounding free-water. Clinical data and diffusion MRI scans were obtained from 28 healthy controls and 86 schizophrenia patients, of whom 34 had present state delusions, 35 had a lifetime history but currently remitted delusions, and 17 had never experienced delusions. RESULTS: While present state and remitted delusions were found to be associated with reduced free-water corrected fractional anisotropy (FAT) and increased free-water corrected radial diffusivity (RDT) in the cingulum bundle bilaterally, extracellular free-water (FW) in the left cingulum bundle was found to be specifically associated with present state delusions in chronic schizophrenia. No changes were observed in the remaining tracts. CONCLUSIONS: These findings suggest that state and trait delusions in chronic schizophrenia are associated with microstructural processes, such as myelin abnormalities (as indicated by decreased FAT and increased RDT) in the cingulum bundle and that state delusions are additionally associated with extracellular processes such as neuroinflammation or atrophy (as indicated by increased FW) in the left cingulum bundle.

The structural heterogeneity of tumor tissue can be probed by diffusion MRI (dMRI) in terms of the variance of apparent diffusivities within a voxel. However, the link between the diffusional variance and the tissue heterogeneity is not well-established. To investigate this link we test the hypothesis that diffusional variance, caused by microscopic anisotropy and isotropic heterogeneity, is associated with variable cell eccentricity and cell density in brain tumors. We performed dMRI using a novel encoding scheme for diffusional variance decomposition (DIVIDE) in 7 meningiomas and 8 gliomas prior to surgery. The diffusional variance was quantified from dMRI in terms of the total mean kurtosis (MKT), and DIVIDE was used to decompose MKT into components caused by microscopic anisotropy (MKA) and isotropic heterogeneity (MKI). Diffusion anisotropy was evaluated in terms of the fractional anisotropy (FA) and microscopic fractional anisotropy (μFA). Quantitative microscopy was performed on the excised tumor tissue, where structural anisotropy and cell density were quantified by structure tensor analysis and cell nuclei segmentation, respectively. In order to validate the DIVIDE parameters they were correlated to the corresponding parameters derived from microscopy. We found an excellent agreement between the DIVIDE parameters and corresponding microscopy parameters; MKA correlated with cell eccentricity (r=0.95, p<10(-7)) and MKI with the cell density variance (r=0.83, p<10(-3)). The diffusion anisotropy correlated with structure tensor anisotropy on the voxel-scale (FA, r=0.80, p<10(-3)) and microscopic scale (μFA, r=0.93, p<10(-6)). A multiple regression analysis showed that the conventional MKT parameter reflects both variable cell eccentricity and cell density, and therefore lacks specificity in terms of microstructure characteristics. However, specificity was obtained by decomposing the two contributions; MKA was associated only to cell eccentricity, and MKI only to cell density variance. The variance in meningiomas was caused primarily by microscopic anisotropy (mean±s.d.) MKA=1.11±0.33 vs MKI=0.44±0.20 (p<10(-3)), whereas in the gliomas, it was mostly caused by isotropic heterogeneity MKI=0.57±0.30 vs MKA=0.26±0.11 (p<0.05). In conclusion, DIVIDE allows non-invasive mapping of parameters that reflect variable cell eccentricity and density. These results constitute convincing evidence that a link exists between specific aspects of tissue heterogeneity and parameters from dMRI. Decomposing effects of microscopic anisotropy and isotropic heterogeneity facilitates an improved interpretation of tumor heterogeneity as well as diffusion anisotropy on both the microscopic and macroscopic scale.

BACKGROUND: In chronic obstructive pulmonary disease, both smaller and larger airways are affected. FEV1 mainly reflects large airways obstruction, while the later fraction of forced exhalation reflects reduction in terminal expiratory flow. In this study, the objective was to evaluate the relationship between spirometric ratios, including the ratio of forced expiratory volume in 3 and 6 seconds (FEV3/FEV6), and small airways measures and gas trapping at quantitative chest CT scanning, and clinical outcomes in the Genetic Epidemiology of COPD (COPDGene) cohort. METHODS: Seven thousand eight hundred fifty-three current and ex-smokers were evaluated for airflow obstruction by using recently defined linear iteratively derived equations of Hansen et al to determine lower limit of normal (LLN) equations for prebronchodilator FEV1/FVC, FEV1/FEV6, FEV3/FEV6, and FEV3/FVC. General linear and ordinal regression models were applied to the relationship between prebronchodilator spirometric and radiologic and clinical data. RESULTS: Of the 10,311 participants included in the COPDGene phase I study, participants with incomplete quantitative CT scanning or relevant spirometric data were excluded, resulting in 7,853 participants in the present study. Of 4,386 participants with FEV1/FVC greater than or equal to the LLN, 15.4% had abnormal FEV3/FEV6. Compared with normal FEV3/FEV6 and FEV1/FVC, abnormal FEV3/FEV6 was associated with significantly greater gas trapping; St. George’s Respiratory Questionnaire score; modified Medical Research Council dyspnea score; and BMI, airflow obstruction, dyspnea, and exercise index and with shorter 6-min walking distance (all P  .0001) but not with CT scanning evidence of emphysema. CONCLUSIONS: Current and ex-smokers with prebronchodilator FEV3/FEV6 less than the LLN as the sole abnormality identifies a distinct population with evidence of small airways disease in quantitative CT scanning, impaired indexes of physical function and quality of life otherwise deemed normal by using the current spirometric definition.

Cellulose is insoluble in water but can be dissolved in strong acidic or alkaline conditions. How well dissolved cellulose is in solution and how it organizes are key questions often neglected in literature. The typical low pH required for dissolving cellulose in acidic solvents limits the use of typical characterization techniques. In this respect, Polarization Transfer Solid State NMR (PT ssNMR) emerges as a reliable alternative. In this work, combining PT ssNMR, microscopic techniques and X-ray diffraction, a set of different acidic systems (phosphoric acid/water, sulfuric acid/glycerol and zinc chloride/water) is investigated. The studied solvent systems are capable to efficiently dissolve cellulose, although degradation occurs to some extent. PT ssNMR is capable to identify the liquid and solid fractions of cellulose, the degradation products and it is also sensitive to gelation. The materials regenerated from the acidic dopes were found to be highly sensitive to the solvent system and to the presence of amphiphilic additives in solution.

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.