Publications

Diffusion MRI techniques are used widely to study the characteristics of the human brain connectome in vivo. However, to resolve and characterise white matter (WM) fibres in heterogeneous MRI voxels remains a challenging problem typically approached with signal models that rely on prior information and constraints. We have recently introduced a 5D relaxation-diffusion correlation framework wherein multidimensional diffusion encoding strategies are used to acquire data at multiple echo-times to increase the amount of information encoded into the signal and ease the constraints needed for signal inversion. Nonparametric Monte Carlo inversion of the resulting datasets yields 5D relaxation-diffusion distributions where contributions from different sub-voxel tissue environments are separated with minimal assumptions on their microscopic properties. Here, we build on the 5D correlation approach to derive fibre-specific metrics that can be mapped throughout the imaged brain volume. Distribution components ascribed to fibrous tissues are resolved, and subsequently mapped to a dense mesh of overlapping orientation bins to define a smooth orientation distribution function (ODF). Moreover, relaxation and diffusion measures are correlated to each independent ODF coordinate, thereby allowing the estimation of orientation-specific relaxation rates and diffusivities. The proposed method is tested on a healthy volunteer, where the estimated ODFs were observed to capture major WM tracts, resolve fibre crossings, and, more importantly, inform on the relaxation and diffusion features along with distinct fibre bundles. If combined with fibre-tracking algorithms, the methodology presented in this work has potential for increasing the depth of characterisation of microstructural properties along individual WM pathways.

BACKGROUND: Chronic tobacco smoke exposure results in a broad range of lung pathologies including emphysema, airway disease and parenchymal fibrosis as well as a multitude of extra-pulmonary comorbidities. Prior work using CT imaging has identified several clinically relevant subgroups of smoking related lung disease, but these investigations have generally lacked organ specific molecular correlates. RESEARCH QUESTION: Can CT imaging be used to identify clinical phenotypes of smoking related lung disease that have specific bronchial epithelial gene expression patterns to better understand disease pathogenesis? STUDY DESIGN AND METHODS: Using K-means clustering, we clustered participants from the COPDGene study (n = 5,273) based on CT imaging characteristics and then evaluated their clinical phenotypes. These clusters were replicated in the Detection of Early Lung Cancer Among Military Personnel (DECAMP) cohort (n = 360), and were further characterized using bronchial epithelial gene expression. RESULTS: Three clusters (preserved, interstitial predominant and emphysema predominant) were identified. Compared to the preserved cluster, the interstitial and emphysema clusters had worse lung function, exercise capacity and quality of life. In longitudinal follow-up, individuals from the emphysema group had greater declines in exercise capacity and lung function, more emphysema, more exacerbations, and higher mortality. Similarly, genes involved in inflammatory pathways (tumor necrosis factor-α, interferon-β) are more highly expressed in bronchial epithelial cells from individuals in the emphysema cluster, while genes associated with T-cell related biology are decreased in these samples. Samples from individuals in the interstitial cluster generally had intermediate levels of expression of these genes. INTERPRETATION: Using quantitative CT imaging, we identified three groups of individuals in older ever-smokers that replicate in two cohorts. Airway gene expression differences between the three groups suggests increased levels of inflammation in the most severe clinical phenotype, possibly mediated by the tumor necrosis factor-α and interferon-β pathways. CLINICAL TRIAL REGISTRATION: COPDGene (NCT00608764), DECAMP-1 (NCT01785342), DECAMP-2 (NCT02504697).

OBJECTIVE: To assess cortical thickness (CT) and surface area (SA) of frontal, temporal, and parietal brain regions in a large clinical high risk for psychosis (CHR) sample, and to identify cortical brain abnormalities in CHR who convert to psychosis and in the whole CHR sample, compared with the healthy controls (HC). METHODS: Magnetic resonance imaging, clinical, and cognitive data were acquired at baseline in 92 HC, 130 non-converters, and 22 converters (conversion assessed at 1-year follow-up). CT and SA at baseline were calculated for frontal, temporal, and parietal subregions. Correlations between regions showing group differences and clinical scores and age were also obtained. RESULTS: CT but not SA was significantly reduced in CHR compared with HC. Two patterns of findings emerged: (1) In converters, CT was significantly reduced relative to non-converters and controls in the banks of superior temporal sulcus, Heschl’s gyrus, and pars triangularis and (2) CT in the inferior parietal and supramarginal gyrus, and at trend level in the pars opercularis, fusiform, and middle temporal gyri was significantly reduced in all high-risk individuals compared with HC. Additionally, reduced CT correlated significantly with older age in HC and in non-converters but not in converters. CONCLUSIONS: These results show for the first time that fronto-temporo-parietal abnormalities characterized all CHR, that is, both converters and non-converters, relative to HC, while CT abnormalities in converters relative to CHR-NC and HC were found in core auditory and language processing regions.

AD is the highly severe part of the dementia spectrum and impairs cognitive abilities of individuals, bringing economic, societal and psychological burdens beyond the diseased. A promising approach in AD research is the analysis of structural and functional brain connectomes, i.e., sNETs and fNETs, respectively. We propose to use tensor representation (B-tensor) of uni-modal and multi-modal brain connectomes to define a low-dimensional space via tensor factorization. We show on a cohort of 47 subjects, spanning the spectrum of dementia, that diagnosis with an accuracy of 77% to 100% is achievable in a 5D connectome space using different structural and functional connectome constructions in a uni-modal and multi-modal fashion. We further show that multi-modal tensor factorization improves the results suggesting complementary information in structure and function. A neurological assessment of the connectivity patterns identified largely agrees with prior knowledge, yet also suggests new associations that may play a role in the disease progress.

RATIONALE AND OBJECTIVES: Bronchiectasis (BE) is associated with chronic obstructive pulmonary disease (COPD), but emphysema and small airways disease, main pathologic features of COPD, have been sparsely studied in BE. We aimed to objectively assess those features in smokers with and without radiographic BE and examine its relationships to airflow obstruction and exercise capacity. MATERIAL AND METHODS: We measured emphysema and small airways disease on paired inspiratory-expiratory computed tomography (CT) scans with the parametric response map (PRM and PRM) method in 1184 smokers with and without radiographic BE. PRM and PRM are expressed as the percentage of lung area. Clinical, spirometry, and exercise capacity data were measured with standardized methods. The differences in PRM and PRM between subjects with and without radiographic BE were assessed using multivariable linear regression analysis, and their associations with FEV and six-minute walk test (6MWT) were assessed with generalized linear models. RESULTS: Out of 1184 subjects, 383 (32%) had radiographic BE. PRM but not PRM was higher in subjects with radiographic BE than those without radiographic BE in adjusted models. Subjects with radiographic BE and PRM (defined as >=5% on paired CTs) had lower FEV (least square mean, 1479 mL vs. 2350 mL p < 0.0001) and 6MWT (372 m vs. 426 m p = 0.0007) than those with radiographic BE alone in adjusted models. CONCLUSION: Smokers with radiographic BE have an increased burden of emphysema on paired CTs, and those with radiographic BE and emphysema have lower airflow and exercise capacity.

Compared to healthy controls (HCs), individuals with attention-deficit/hyperactivity disorder (ADHD) exhibit more symptoms of sensory processing disorder (SPD), which is associated with difficulties in educational and social activities. Most studies examining comorbid SPD-ADHD have been conducted with children and have not explored relations to brain volumes. In this pilot study, we assessed a subtype of SPD, sensory modulation disorder (SMD), and its relation to select brain volumes in adults with ADHD. We administered part of the Sensory Processing 3-Dimensions Scale (SP3D) to assess subtypes of SMD and collected structural imaging scans from 25 adults with ADHD and 29 healthy controls (HCs). Relative to HCs, subjects with ADHD scored higher on sensory craving (SC) and sensory under-responsivity (SUR) subscales. Although sensory over-responsivity (SOR) was marginally higher, this was no longer true when accounting for co-occurring anxiety. In individuals with ADHD, both SC and SUR were positively associated with amygdalar volume, SUR was also positively associated with striatal volume, whereas SOR was negatively associated with posterior ventral diencephalon volume. These preliminary findings suggest that SC and SUR may be characteristic of ADHD while SOR may be driven by co-occurring anxiety. Because different modalities were associated with different brain volumes, our findings also suggest that the modalities may involve unique neural circuits, but with a partial overlap between SC and SUR. These pilot data provide support for conducting studies examining SMD in larger samples of adults with ADHD to determine reproducibility, applicability and implications of these findings.

OBJECTIVES: It is important to find biomarkers associated with transition to illness in individuals at clinical high-risk for psychosis (CHR). Here, we use free-water imaging, an advanced diffusion MRI technique, to identify white matter alterations in the brains of CHR subjects who subsequently develop psychosis (CHR-P) compared to those who do not (CHR-NP). METHODS: Twenty-four healthy controls (HC) and 30 CHR individuals, 8 of whom converted to schizophrenia after a mean follow-up of 15.16 months, received baseline MRI scans. Maps of fractional anisotropy (FA), FA of cellular tissue (FA), and extracellular free-water (FW) were extracted using tract-based spatial statistics after which voxel-wise non-parametric group statistics and correlations with symptom severity were performed. RESULTS: There were no significant differences between HCs and the combined CHR group. However, prior to conversion, CHR-P showed widespread lower FA compared to CHR-NP ( < 0.05). FA changes in CHR-P were associated with significantly lower FA and higher FW, compared to CHR-NP. Positive symptoms correlated significantly with diffusion parameters in similar regions as those discriminating CHR-P from CHR-NP. CONCLUSIONS: Our study suggests that cellular (FA) and extracellular (FW) white matter alterations are associated with positive symptom severity and indicate an elevated illness risk among CHR individuals.

Sport-related brain injury is very common, and the potential long-term effects include a wide range of neurological and psychiatric symptoms, and potentially neurodegeneration. Around the globe, researchers are conducting neuroimaging studies on primarily homogenous samples of athletes. However, neuroimaging studies are expensive and time consuming, and thus current findings from studies of sport-related brain injury are often limited by small sample sizes. Further, current studies apply a variety of neuroimaging techniques and analysis tools which limit comparability among studies. The ENIGMA Sports Injury working group aims to provide a platform for data sharing and collaborative data analysis thereby leveraging existing data and expertise. By harmonizing data from a large number of studies from around the globe, we will work towards reproducibility of previously published findings and towards addressing important research questions with regard to diagnosis, prognosis, and efficacy of treatment for sport-related brain injury. Moreover, the ENIGMA Sports Injury working group is committed to providing recommendations for future prospective data acquisition to enhance data quality and scientific rigor.

BACKGROUND: In the United States, 9 to 10 million Americans are estimated to be eligible for computed tomographic lung cancer screening (CTLS). Those meeting criteria for CTLS are at high-risk for numerous cardio-pulmonary co-morbidities. The objective of this study was to determine the association between qualitative emphysema identified on screening CTs and risk for hospital admission. STUDY DESIGN AND METHODS: We conducted a retrospective multicenter study from two CTLS cohorts: Lahey Hospital and Medical Center (LHMC) CTLS program, Burlington, MA and Mount Auburn Hospital (MAH) CTLS program, Cambridge, MA. CTLS exams were qualitatively scored by radiologists at time of screening for presence of emphysema. Multivariable Cox regression models were used to evaluate the association between CT qualitative emphysema and all-cause, COPD-related, and pneumonia-related hospital admission. RESULTS: We included 4673 participants from the LHMC cohort and 915 from the MAH cohort. 57% and 51.9% of the LHMC and MAH cohorts had presence of CT emphysema, respectively. In the LHMC cohort, the presence of emphysema was associated with all-cause hospital admission (HR 1.15, CI 1.07-1.23; p < 0.001) and COPD-related admission (HR 1.64; 95% CI 1.14-2.36; p = 0.007), but not with pneumonia-related admission (HR 1.52; 95% CI 1.27-1.83; p < 0.001). In the MAH cohort, the presence of emphysema was only associated with COPD-related admission (HR 2.05; 95% CI 1.07-3.95; p = 0.031). CONCLUSION: Qualitative CT assessment of emphysema is associated with COPD-related hospital admission in a CTLS population. Identification of emphysema on CLTS exams may provide an opportunity for prevention and early intervention to reduce admission risk.