Publications

2021
Lampinen B, Lätt J, Wasselius J, van Westen D, Nilsson M. Time dependence in diffusion MRI predicts tissue outcome in ischemic stroke patients. Magn Reson Med. 2021.Abstract
PURPOSE: Reperfusion therapy enables effective treatment of ischemic stroke presenting within 4-6 hours. However, tissue progression from ischemia to infarction is variable, and some patients benefit from treatment up until 24 hours. Improved imaging techniques are needed to identify these patients. Here, it was hypothesized that time dependence in diffusion MRI may predict tissue outcome in ischemic stroke. METHODS: Diffusion MRI data were acquired with multiple diffusion times in five non-reperfused patients at 2, 9, and 100 days after stroke onset. Maps of "rate of kurtosis change" (k), mean kurtosis, ADC, and fractional anisotropy were derived. The ADC maps defined lesions, normal-appearing tissue, and the lesion tissue that would either be infarcted or remain viable by day 100. Diffusion parameters were compared (1) between lesions and normal-appearing tissue, and (2) between lesion tissue that would be infarcted or remain viable. RESULTS: Positive values of k were observed within stroke lesions on day 2 (P = .001) and on day 9 (P = .023), indicating diffusional exchange. On day 100, high ADC values indicated infarction of 50 ± 20% of the lesion volumes. Tissue infarction was predicted by high k values both on day 2 (P = .026) and on day 9 (P = .046), by low mean kurtosis values on day 2 (P = .043), and by low fractional anisotropy values on day 9 (P = .029), but not by low ADC values. CONCLUSIONS: Diffusion time dependence predicted tissue outcome in ischemic stroke more accurately than the ADC, and may be useful for predicting reperfusion benefit.
Weiller C, Reisert M, Peto I, Hennig J, Makris N, Petrides M, Rijntjes M, Egger K. The ventral pathway of the human brain: a continuous, single association tract system. Neuroimage. 2021 :117977.Abstract
The brain hemispheres can be divided into an upper dorsal and a lower ventral system. Each system consists of distinct cortical regions connected via long association tracts. The tracts cross the central sulcus or the limen insulae to connect the frontal lobe with the posterior brain. The dorsal stream is associated with sensorimotor mapping. The ventral stream serves structural analysis and semantics in different domains, as visual, acoustic or space processing. How does the prefrontal cortex, regarded as the platform for the highest level of integration, incorporate information from these different domains? In the current view, the ventral pathway consists of several separate tracts, related to different modalities. Originally the assumption was that the ventral path is a continuum, covering all modalities. The latter would imply a very different anatomical basis for cognitive and clinical models of processing. To further define the ventral connections, we used cutting-edge in vivo global tractography on high-resolution diffusion tensor imaging (DTI) data from 100 normal subjects from the human connectome project and ex vivo preparation of fiber bundles in the extreme capsule of 8 humans using the Klingler technique. Our data showed that ventral stream tracts, traversing through the extreme capsule, form a continuous band of fibers that fan out anteriorly to the prefrontal cortex, and posteriorly to temporal, occipital and parietal cortical regions. Introduction of additional volumes of interest in temporal and occipital lobes differentiated between the inferior fronto-occipital fascicle (IFOF) and uncinate fascicle (UF). Unequivocally, in both experiments, in all subjects a connection between the inferior frontal and middle-to-posterior temporal cortical region, otherwise known as the temporo-frontal extreme capsule fascicle (ECF) from nonhuman primate brain-tracing experiments was identified. In the human brain, this tract connects the language domains of Broca's area and Wernicke's area. The differentiation in the three tracts, IFOF, UF and ECF seems arbitrary, all three pass through the extreme capsule. Our data show that the ventral pathway represents a continuum. The three tracts merge seamlessly and streamlines showed considerable overlap in their anterior and posterior course. Terminal maps identified prefrontal cortex in the frontal lobe and association cortices in temporal, occipital and parietal lobes as streamline endings. This anatomical substrate potentially facilitates the prefrontal cortex to integrate information across different domains and modalities.
Hino T, Hida RY, Nishino M, Lu J, Putman RK, Gudmundsson EF, Estepar RS. Progression of traction bronchiectasis/bronchiolectasis in interstitial lung abnormalities is associated with increased all-cause mortality: Age Gene/Environment Susceptibility-Reykjavik Study. Eur J Radiol Open. 2021;8 :100334.Abstract

Purpose: The aim of this study is to assess the role of traction bronchiectasis/bronchiolectasis and its progression as a predictor for early fibrosis in interstitial lung abnormalities (ILA).

Methods: Three hundred twenty-seven ILA participants out of 5764 in the Age, Gene/Environment Susceptibility (AGES)-Reykjavik Study who had undergone chest CT twice with an interval of approximately five-years were enrolled in this study. Traction bronchiectasis/bronchiolectasis index (TBI) was classified on a four-point scale: 0, ILA without traction bronchiectasis/bronchiolectasis; 1, ILA with bronchiolectasis but without bronchiectasis or architectural distortion; 2, ILA with mild to moderate traction bronchiectasis; 3, ILA and severe traction bronchiectasis and/or honeycombing. Traction bronchiectasis (TB) progression was classified on a five-point scale: 1, Improved; 2, Probably improved; 3, No change; 4, Probably progressed; 5, Progressed. Overall survival (OS) among participants with different TB Progression Score and between the TB progression group and No TB progression group was also investigated. Hazard radio (HR) was estimated with Cox proportional hazards model.

Results: The higher the TBI at baseline, the higher TB Progression Score (P < 0.001). All five participants with TBI = 3 at baseline progressed; 46 (90 %) of 51 participants with TBI = 2 progressed. TB progression was also associated with shorter OS with statistically significant difference (adjusted HR = 1.68, P < 0.001).

Conclusion: TB progression was visualized on chest CT frequently and clearly. It has the potential to be the predictor for poorer prognosis of ILA.

Keywords: AGES-Reykjavik Study, Age Gene/Environment Susceptibility-Reykjavik Study; Age Gene/Environment Susceptibility-Reykjavik Study; BMI, body mass index; HR, hazard ratio; ILA, interstitial lung abnormalities; ILD, interstitial lung disease; Interstitial lung abnormality; OS, overall survival; Pulmonary fibrosis; TB, traction bronchiectasis; TBI, traction bronchiectasis/bronchiolecetasis index; TBI-R2, traction bronchiectasis/bronchiolecetasis index on Round 2; Traction bronchiectasis; Usual interstitial pneumonia.

Zhang F, Breger A, Cho KIK, Ning L, Westin C-F, O'Donnell LJ, Pasternak O. Deep Learning Based Segmentation of Brain Tissue from Diffusion MRI. Neuroimage. 2021 :117934.Abstract
Segmentation of brain tissue types from diffusion MRI (dMRI) is an important task, required for quantification of brain microstructure and for improving tractography. Current dMRI segmentation is mostly based on anatomical MRI (e.g., T1- and T2-weighted) segmentation that is registered to the dMRI space. However, such inter-modality registration is challenging due to more image distortions and lower image resolution in dMRI as compared with anatomical MRI. In this study, we present a deep learning method for diffusion MRI segmentation, which we refer to as DDSeg. Our proposed method learns tissue segmentation from high-quality imaging data from the Human Connectome Project (HCP), where registration of anatomical MRI to dMRI is more precise. The method is then able to predict a tissue segmentation directly from new dMRI data, including data collected with different acquisition protocols, without requiring anatomical data and inter-modality registration. We train a convolutional neural network (CNN) to learn a tissue segmentation model using a novel augmented target loss function designed to improve accuracy in regions of tissue boundary. To further improve accuracy, our method adds diffusion kurtosis imaging (DKI) parameters that characterize non-Gaussian water molecule diffusion to the conventional diffusion tensor imaging parameters. The DKI parameters are calculated from the recently proposed mean-kurtosis-curve method that corrects implausible DKI parameter values and provides additional features that discriminate between tissue types. We demonstrate high tissue segmentation accuracy on HCP data, and also when applying the HCP-trained model on dMRI data from other acquisitions with lower resolution and fewer gradient directions.
Kaufmann D, Sollmann N, Kaufmann E, Veggeberg R, Tripodis Y, Wrobel PP, Kochsiek J, Martin BM, Lin AP, Coleman MJ, et al. Age at First Exposure to Tackle Football is Associated with Cortical Thickness in Former Professional American Football Players. Cereb Cortex. 2021.Abstract
Younger age at first exposure (AFE) to repetitive head impacts while playing American football increases the risk for later-life neuropsychological symptoms and brain alterations. However, it is not known whether AFE is associated with cortical thickness in American football players. Sixty-three former professional National Football League players (55.5 ± 7.7 years) with cognitive, behavioral, and mood symptoms underwent neuroimaging and neuropsychological testing. First, the association between cortical thickness and AFE was tested. Second, the relationship between clusters of decreased cortical thickness and verbal and visual memory, and composite measures of mood/behavior and attention/psychomotor speed was assessed. AFE was positively correlated with cortical thickness in the right superior frontal cortex (cluster-wise P value [CWP] = 0.0006), the left parietal cortex (CWP = 0.0003), and the occipital cortices (right: CWP = 0.0023; left: CWP = 0.0008). A positive correlation was found between cortical thickness of the right superior frontal cortex and verbal memory (R = 0.333, P = 0.019), and the right occipital cortex and visual memory (R = 0.360, P = 0.012). In conclusion, our results suggest an association between younger AFE and decreased cortical thickness, which in turn is associated with worse neuropsychological performance. Furthermore, an association between younger AFE and signs of neurodegeneration later in life in symptomatic former American football players seems likely.
Ye H, Zalesky A, Lv J, Loi SM, Cetin-Karayumak S, Rathi Y, Tian Y, Pantelis C, Di Biase MA. Network Analysis of Symptom Comorbidity in Schizophrenia: Relationship to Illness Course and Brain White Matter Microstructure. Schizophr Bull. 2021.Abstract
INTRODUCTION: Recent network-based analyses suggest that schizophrenia symptoms are intricately connected and interdependent, such that central symptoms can activate adjacent symptoms and increase global symptom burden. Here, we sought to identify key clinical and neurobiological factors that relate to symptom organization in established schizophrenia. METHODS: A symptom comorbidity network was mapped for a broad constellation of symptoms measured in 642 individuals with a schizophrenia-spectrum disorder. Centrality analyses were used to identify hub symptoms. The extent to which each patient's symptoms formed clusters in the comorbidity network was quantified with cluster analysis and used to predict (1) clinical features, including illness duration and psychosis (positive symptom) severity and (2) brain white matter microstructure, indexed by the fractional anisotropy (FA), in a subset (n = 296) of individuals with diffusion-weighted imaging (DWI) data. RESULTS: Global functioning, substance use, and blunted affect were the most central symptoms within the symptom comorbidity network. Symptom profiles for some patients formed highly interconnected clusters, whereas other patients displayed unrelated and disconnected symptoms. Stronger clustering among an individual's symptoms was significantly associated with shorter illness duration (t = 2.7; P = .0074), greater psychosis severity (ie, positive symptoms expression) (t = -5.5; P < 0.0001) and lower fractional anisotropy in fibers traversing the cortico-cerebellar-thalamic-cortical circuit (r = .59, P < 0.05). CONCLUSION: Symptom network structure varies over the course of schizophrenia: symptom interactions weaken with increasing illness duration and strengthen during periods of high positive symptom expression. Reduced white matter coherence relates to stronger symptom clustering, and thus, may underlie symptom cascades and global symptomatic burden in individuals with schizophrenia.
Avila RS, Fain SB, Hatt C, Armato SG, Mulshine JL, Gierada D, Silva M, Lynch DA, Hoffman EA, Ranallo FN, et al. QIBA guidance: Computed tomography imaging for COVID-19 quantitative imaging applications. Clin Imaging. 2021;77 :151-157.Abstract
As the COVID-19 pandemic impacts global populations, computed tomography (CT) lung imaging is being used in many countries to help manage patient care as well as to rapidly identify potentially useful quantitative COVID-19 CT imaging biomarkers. Quantitative COVID-19 CT imaging applications, typically based on computer vision modeling and artificial intelligence algorithms, include the potential for better methods to assess COVID-19 extent and severity, assist with differential diagnosis of COVID-19 versus other respiratory conditions, and predict disease trajectory. To help accelerate the development of robust quantitative imaging algorithms and tools, it is critical that CT imaging is obtained following best practices of the quantitative lung CT imaging community. Toward this end, the Radiological Society of North America's (RSNA) Quantitative Imaging Biomarkers Alliance (QIBA) CT Lung Density Profile Committee and CT Small Lung Nodule Profile Committee developed a set of best practices to guide clinical sites using quantitative imaging solutions and to accelerate the international development of quantitative CT algorithms for COVID-19. This guidance document provides quantitative CT lung imaging recommendations for COVID-19 CT imaging, including recommended CT image acquisition settings for contemporary CT scanners. Additional best practice guidance is provided on scientific publication reporting of quantitative CT imaging methods and the importance of contributing COVID-19 CT imaging datasets to open science research databases.
Reymbaut A, Caron AV, Gilbert G, Szczepankiewicz F, Nilsson M, Warfield SK, Descoteaux M, Scherrer B. Magic DIAMOND: Multi-fascicle diffusion compartment imaging with tensor distribution modeling and tensor-valued diffusion encoding. Med Image Anal. 2021;70 :101988.Abstract
Diffusion tensor imaging provides increased sensitivity to microstructural tissue changes compared to conventional anatomical imaging but also presents limited specificity. To tackle this problem, the DIAMOND model subdivides the voxel content into diffusion compartments and draws from diffusion-weighted data to estimate compartmental non-central matrix-variate Gamma distributions of diffusion tensors. It models each sub-voxel fascicle separately, resolving crossing white-matter pathways and allowing for a fascicle-element (fixel) based analysis of microstructural features. Alternatively, specific features of the intra-voxel diffusion tensor distribution can be selectively measured using tensor-valued diffusion-weighted acquisition schemes. However, the impact of such schemes on estimating brain microstructural features has only been studied in a handful of parametric single-fascicle models. In this work, we derive a general Laplace transform for the non-central matrix-variate Gamma distribution, which enables the extension of DIAMOND to tensor-valued encoded data. We then evaluate this "Magic DIAMOND" model in silico and in vivo on various combinations of tensor-valued encoded data. Assessing uncertainty on parameter estimation via stratified bootstrap, we investigate both voxel-based and fixel-based metrics by carrying out multi-peak tractography. We demonstrate using in silico evaluations that tensor-valued diffusion encoding significantly improves Magic DIAMOND's accuracy. Most importantly, we show in vivo that our estimated metrics can be robustly mapped along tracks across regions of fiber crossing, which opens new perspectives for tractometry and microstructure mapping along specific white-matter tracts.
Chad JA, Pasternak O, Chen JJ. Orthogonal moment diffusion tensor decomposition reveals age-related degeneration patterns in complex fiber architecture. Neurobiol Aging. 2021;101 :150-159.Abstract
Diffusion tensor imaging (DTI) consistently detects increased mean diffusivity and decreased fractional anisotropy with advancing age in regions of primarily single white matter (WM) fiber populations, but findings have been inconsistent in regions of more complex fiber architecture. Given that DTI remains more common for characterizing aging WM than advanced diffusion MRI models due to DTI's simplicity, robustness, and efficiency, it is critical to strive to maximize the information extracted from DTI across the entire WM. The present study uses an orthogonal diffusion tensor decomposition based on the 3 eigenvalue moments (mean diffusivity, norm of anisotropy, and mode of anisotropy), yielding clear voxelwise degeneration patterns across the WM, including regions of complex fiber architecture. This indicates that the previous challenges of DTI in these regions were due to the choice of tensor decomposition rather than the DTI model itself. This study therefore presents a revised view of DTI of aging WM and indicates how age-related degeneration in complex fiber architecture can manifest in forms other than decreased fractional anisotropy.
Pistenmaa CL, Nardelli P, Ash SY, Come CE, Diaz AA, Rahaghi FN, Barr RG, Young KA, Kinney GL, Simmons JP, et al. Pulmonary Arterial Pruning and Longitudinal Change in Percent Emphysema and Lung Function: the COPDGene Study. Chest. 2021.Abstract
BACKGROUND: Pulmonary endothelial damage has been shown to preceed the development of emphysema in animals, and vascular changes in humans have been observed in COPD and emphysema. RESEARCH QUESTION: Is intraparenchymal vascular pruning associated with longitudinal progression of emphysema on CT or decline in lung function over 5 years? STUDY DESIGN AND METHODS: The COPDGene Study enrolled ever-smokers with and without COPD in 2008-2011. The percent of emphysema-like lung was assessed at baseline and after 5 years on non-contrast CT as the percentage of lung voxels <-950 Hounsfield units. An automated CT-based tool assessed and classified intrapulmonary arteries and veins. Spirometry measures are post-bronchodilator. Pulmonary arterial pruning was defined as a lower ratio of small artery volume (<5mm cross sectional area) to total lung artery volume. Mixed linear models included demographics, anthropomorphics, smoking and COPD; with emphysema models also adjusting for CT scanner and lung function models adjusting for clinical center and baseline percent emphysema. RESULTS: At baseline the 4,227 participants were 60±9 years old, 50% female, 28% black, 47% current smokers and 41% had COPD. Median percent emphysema was 2.1 (IQR: 0.6, 6.3) and progressed 0.24 percentage points/year (95% CI: 0.22, 0.26) over 5.6 years. Mean FEV/FVC was 68.5±14.2% and declined 0.26%/year (95% CI: -0.30, -0.23). Greater pulmonary arterial pruning was associated with more rapid progression of percent emphysema (0.11 percentage points/year per SD arterial pruning, 95% CI: 0.09, 0.16), including after adjusting for baseline percent emphysema and FEV. Arterial pruning was also associated with a faster decline in FEV/FVC (-0.04%/year per SD arterial pruning, 95% CI: -0.008, -0.001). INTERPRETATION: Pulmonary arterial pruning was associated with faster progression of percent emphysema and more rapid decline in FEV/FVC over 5 years in ever-smokers, suggesting pulmonary vascular differences may be relevant in disease progression.
Ratti E, Domoto-Reilly K, Caso C, Murphy A, Brickhouse M, Hochberg D, Makris N, Cudkowicz ME, Dickerson BC. Regional prefrontal cortical atrophy predicts specific cognitive-behavioral symptoms in ALS-FTD. Brain Imaging Behav. 2021.Abstract
Amyotrophic Lateral Sclerosis-Frontotemporal Dementia (ALS-FTD) may present typical behavioral variant FTD symptoms. This study aims to determine whether profile and severity of cognitive-behavioral symptoms in ALS/ALS-FTD are predicted by regional cortical atrophy. The hypothesis is that executive dysfunction can be predicted by dorsolateral prefrontal cortical (dlPFC) atrophy, apathy by dorsomedial PFC (dmPFC) and anterior cingulate cortical (ACC) atrophy, disinhibition by orbitofrontal cortical (OFC) atrophy. 3.0 Tesla MRI scans were acquired from 22 people with ALS or ALS-FTD. Quantitative cortical thickness analysis was performed with FreeSurfer. A priori-defined regions of interest (ROI) were used to measure cortical thickness in each participant and calculate magnitude of atrophy in comparison to 115 healthy controls. Spearman correlations were used to evaluate associations between frontal ROI cortical thickness and cognitive-behavioral symptoms, measured by Neuropsychiatric Inventory Questionnaire (NPI-Q) and Clinical Dementia Rating (CDR) scale. ALS-FTD participants exhibited variable degrees of apathy (NPI-Q/apathy: 1.6 ± 1.2), disinhibition (NPI-Q/disinhibition: 1.2 ± 1.2), executive dysfunction (CDR/judgment-problem solving: 1.7 ± 0.8). Within the ALS-FTD group, executive dysfunction correlated with dlPFC atrophy (ρ:-0.65;p < 0.05); similar trends were seen for apathy with ACC (ρ:-0.53;p < 0.10) and dmPFC (ρ:-0.47;p < 0.10) atrophy, for disinhibition with OFC atrophy (ρ:-0.51;p < 0.10). Compared to people with ALS, those with ALS-FTD showed more diffuse atrophy involving precentral gyrus, prefrontal, temporal regions. Profile and severity of cognitive-behavioral symptoms in ALS-FTD are predicted by regional prefrontal atrophy. These findings are consistent with established brain-behavior models and support the role of quantitative MRI in diagnosis, management, counseling, monitoring and prognostication for a neurodegenerative disorder with diverse phenotypes.
Ash SY, San José Estépar R, Fain SB, Tal-Singer R, Stockley RA, Nordenmark LH, Rennard S, Han MLK, Merrill D, Humphries SM, et al. Relationship between Emphysema Progression at CT and Mortality in Ever-Smokers: Results from the COPDGene and ECLIPSE Cohorts. Radiology. 2021 :203531.Abstract
Background The relationship between emphysema progression and long-term outcomes is unclear. Purpose To determine the relationship between emphysema progression at CT and mortality among participants with emphysema. Materials and Methods In a secondary analysis of two prospective observational studies, COPDGene (, NCT00608764) and Evaluation of Chronic Obstructive Pulmonary Disease Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE; , NCT00292552), emphysema was measured at CT at two points by using the volume-adjusted lung density at the 15th percentile of the lung density histogram (hereafter, lung density perc15) method. The association between emphysema progression rate and all-cause mortality was analyzed by using Cox regression adjusted for ethnicity, sex, baseline age, pack-years, and lung density, baseline and change in smoking status, forced expiratory volume in 1 second, and 6-minute walk distance. In COPDGene, respiratory mortality was analyzed by using the Fine and Gray method. Results A total of 5143 participants (2613 men [51%]; mean age, 60 years ± 9 [standard deviation]) in COPDGene and 1549 participants (973 men [63%]; mean age, 62 years ± 8) in ECLIPSE were evaluated, of which 2097 (40.8%) and 1179 (76.1%) had emphysema, respectively. Baseline imaging was performed between January 2008 and December 2010 for COPDGene and January 2006 and August 2007 for ECLIPSE. Follow-up imaging was performed after 5.5 years ± 0.6 in COPDGene and 3.0 years ± 0.2 in ECLIPSE, and mortality was assessed over the ensuing 5 years in both. For every 1 g/L per year faster rate of decline in lung density perc15, all-cause mortality increased by 8% in COPDGene (hazard ratio [HR], 1.08; 95% CI: 1.01, 1.16; = .03) and 6% in ECLIPSE (HR, 1.06; 95% CI: 1.00, 1.13; = .045). In COPDGene, respiratory mortality increased by 22% (HR, 1.22; 95% CI: 1.13, 1.31; < .001) for the same increase in the rate of change in lung density perc15. Conclusion In ever-smokers with emphysema, emphysema progression at CT was associated with increased all-cause and respiratory mortality. © RSNA, 2021 See also the editorial by Lee and Park in this issue.
Alves L, Medronho B, Filipe A, Romano A, Rasteiro MG, Lindman B, Topgaard D, Davidovich I, Talmon Y. Revisiting the dissolution of cellulose in HPO(aq) through cryo-TEM, PTssNMR and DWS. Carbohydr Polym. 2021;252 :117122.Abstract
Cellulose can be dissolved in concentrated acidic aqueous solvents forming extremely viscous solutions, and, in some cases, liquid crystalline phases. In this work, the concentrated phosphoric acid aqueous solvent is revisited implementing a set of advanced techniques, such as cryo-transmission electronic microscopy (cryo-TEM), polarization transfer solid-state nuclear magnetic resonance (PTssNMR), and diffusing wave spectroscopy (DWS). Cryo-TEM images confirm that this solvent system is capable to efficiently dissolve cellulose. No cellulose particles, fibrils, or aggregates are visible. Conversely, PTssNMR revealed a dominant CP signal at 25 °C, characteristic of C-H bond reorientation with correlation time longer than 100 ns and/or order parameter above 0.5, which was ascribed to a transient gel-like network or an anisotropic liquid crystalline phase. Increasing the temperature leads to a gradual transition from CP to INEPT-dominant signal and a loss of birefringence in optical microscopy, suggesting an anisotropic-to-isotropic phase transition. Finally, an excellent agreement between optical microrheology and conventional mechanical rheometry was also obtained.
Synn AJ, Li W, Hunninghake GM, Washko GR, San José Estépar R, O'Connor GT, Kholdani CA, Hallowell RW, Bankier AA, Mittleman MA, et al. Vascular Pruning on CT and Interstitial Lung Abnormalities in the Framingham Heart Study. Chest. 2021;159 (2) :663-672.Abstract
BACKGROUND: Pulmonary vascular disease is associated with poor outcomes in individuals affected by interstitial lung disease. The pulmonary vessels can be quantified with noninvasive imaging, but whether radiographic indicators of vasculopathy are associated with early interstitial changes is not known. RESEARCH QUESTION: Are pulmonary vascular volumes, quantified from CT scans, associated with interstitial lung abnormalities (ILA) in a community-based sample with a low burden of lung disease? STUDY DESIGN AND METHODS: In 2,386 participants of the Framingham Heart Study, we used CT imaging to calculate pulmonary vascular volumes, including the small vessel fraction (a surrogate of vascular pruning). We constructed multivariable logistic regression models to investigate associations of vascular volumes with ILA, progression of ILA, and restrictive pattern on spirometry. In secondary analyses, we additionally adjusted for diffusing capacity and emphysema, and performed a sensitivity analysis restricted to participants with normal FVC and diffusing capacity. RESULTS: In adjusted models, we found that lower pulmonary vascular volumes on CT were associated with greater odds of ILA, antecedent ILA progression, and restrictive pattern on spirometry. For example, each SD lower small vessel fraction was associated with 1.81-fold greater odds of ILA (95% CI, 1.41-2.31; P < .0001), and 1.63-fold greater odds of restriction on spirometry (95% CI, 1.18-2.24; P = .003). Similar patterns were seen after adjustment for diffusing capacity for carbon monoxide, emphysema, and among participants with normal lung function. INTERPRETATION: In this cohort of community-dwelling adults not selected on the basis of lung disease, more severe vascular pruning on CT was associated with greater odds of ILA, ILA progression, and restrictive pattern on spirometry. Pruning on CT may be an indicator of early pulmonary vasculopathy associated with interstitial lung disease.
Schlachter A, Juvenal F, Kinghat Tangou R, Khatyr A, Guyon F, Karsenti P-L, Strohmann C, Kubicki MM, Rousselin Y, Harvey PD, et al. 2-Azabutadiene complexes of rhenium(I): S,N-chelated species with photophysical properties heavily governed by the ligand hidden traits. Dalton Trans. 2021;50 (8) :2945-63.Abstract
The reaction of [Re(CO)3(THF)(μ-Br)]2 or [Re(CO)5X] (X = Cl, Br, I) with the diaryl-2-azabutadienes [(RS)2C[double bond, length as m-dash]C(H)-N[double bond, length as m-dash]CAr2] containing two thioether arms at the 4,4-position forms the luminescent S,N-chelate complexes fac-[(OC)3ReX{(RS)2C[double bond, length as m-dash]C(H)-N[double bond, length as m-dash]CAr2}] (1a-h). The halide abstraction by silver triflate converts [(OC)3ReCl{(PhS)2C[double bond, length as m-dash]C(H)-N[double bond, length as m-dash]CPh2}] (1c) to [(OC)3Re(OS([double bond, length as m-dash]O)2CF3){(PhS)2C[double bond, length as m-dash]C(H)-N[double bond, length as m-dash]CPh2}] (1j) bearing a covalently bound triflate ligand. The cyclic voltammograms reveal reversible S^N ligand-centred reduction and irreversible oxidation waves for all complexes. The crystal structures of nine octahedral complexes have been determined along with that of (NaphtylS)2C[double bond, length as m-dash]C(H)-N[double bond, length as m-dash]CPh2 (L6). A rich system of weak non-covalent intermolecular secondary interactions through CHX(Cl, Br)Re, CHO, COπ(Ph), CHπCO, CHO and CHS contacts has been evidenced. The photophysical properties have been investigated by steady-state and time-resolved absorption (fs transient absorption, fs-TAS) and emission (ns-TCSPC and ps-Streak camera) spectroscopy in 2-MeTHF solution at 298 and 77 K. The emission bands are composed of either singlet (450 < λmax < 535 nm) and/or triplet emissions (at 77 K only, λmax < 640 nm, or appearing as a tail at λ > 600 nm), which decay in a multiexponential manner for the fluorescence (short ps (i.e.
Mason SE, Moreta-Martinez R, Labaki WW, Strand M, Baraghoshi D, Regan EA, Bon J, San Jose Estepar R, Casaburi R, McDonald M-LN, et al. Respiratory exacerbations are associated with muscle loss in current and former smokers. Thorax. 2021.Abstract
OBJECTIVES: Muscle wasting is a recognised extra-pulmonary complication in chronic obstructive pulmonary disease and has been associated with increased risk of death. Acute respiratory exacerbations are associated with reduction of muscle function, but there is a paucity of data on their long-term effect. This study explores the relationship between acute respiratory exacerbations and long-term muscle loss using serial measurements of CT derived pectoralis muscle area (PMA). DESIGN AND SETTING: Participants were included from two prospective, longitudinal, observational, multicentre cohorts of ever-smokers with at least 10 pack-year history. PARTICIPANTS: The primary analysis included 1332 (of 2501) participants from Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) and 4384 (of 10 198) participants from Genetic Epidemiology of COPD (COPDGene) who had complete data from their baseline and follow-up visits. INTERVENTIONS: PMA was measured on chest CT scans at two timepoints. Self-reported exacerbation data were collected from participants in both studies through the use of periodic longitudinal surveys. MAIN OUTCOME MEASURES: Age-related and excess muscle loss over time. RESULTS: Age, sex, race and body mass index were associated with baseline PMA. Participants experienced age-related decline at the upper end of reported normal ranges. In ECLIPSE, the exacerbation rate over time was associated with an excess muscle area loss of 1.3% (95% CI 0.6 to 1.9, p<0.001) over 3 years and in COPDGene with an excess muscle area loss of 2.1% (95% CI 1.2 to 2.8, p<0.001) over 5 years. Excess muscle area decline was absent in 273 individuals who participated in pulmonary rehabilitation. CONCLUSIONS: Exacerbations are associated with accelerated skeletal muscle loss. Each annual exacerbation was associated with the equivalent of 6 months of age-expected decline in muscle mass. Ameliorating exacerbation-associated muscle loss represents an important therapeutic target.
Rahaghi FN, Hilton JF, Corrêa RA, Loureiro C, Ota-Arakaki JS, Verrastro CGY, Lee MH, Mickael C, Nardelli P, Systrom DA, et al. Arterial Vascular Volume Changes with Hemodynamics in Schistosomiasis Pulmonary Arterial Hypertension. Eur Respir J. 2021 :2003914.
Sedghi A, O'Donnell LJ, Kapur T, Learned-Miller E, Mousavi P, Wells WM. Image registration: Maximum likelihood, minimum entropy and deep learning. Med Image Anal. 2021;69 :101939.Abstract
In this work, we propose a theoretical framework based on maximum profile likelihood for pairwise and groupwise registration. By an asymptotic analysis, we demonstrate that maximum profile likelihood registration minimizes an upper bound on the joint entropy of the distribution that generates the joint image data. Further, we derive the congealing method for groupwise registration by optimizing the profile likelihood in closed form, and using coordinate ascent, or iterative model refinement. We also describe a method for feature based registration in the same framework and demonstrate it on groupwise tractographic registration. In the second part of the article, we propose an approach to deep metric registration that implements maximum likelihood registration using deep discriminative classifiers. We show further that this approach can be used for maximum profile likelihood registration to discharge the need for well-registered training data, using iterative model refinement. We demonstrate that the method succeeds on a challenging registration problem where the standard mutual information approach does not perform well.
Palotai M, Small C, Makris N, Somes NG, Pinzon AM, Rathi Y, Marzullo A, Levitt JJ, Bakshi R, Chitnis T, et al. Microstructural Changes in the Left Mesocorticolimbic Pathway are Associated with the Comorbid Development of Fatigue and Depression in Multiple Sclerosis. J Neuroimaging. 2021.Abstract
BACKGROUND AND PURPOSE: Lower reward responsiveness has been associated with fatigue in multiple sclerosis (MS). However, association of MS-related fatigue with damage to the mesocorticolimbic reward pathway (superolateral medial forebrain bundle [slMFB]) has not been assessed. We investigated the association of fatigue and depression with slMFB damage in MS patients stratified based on longitudinal fatigue patterns. METHODS: Patient stratification: 1. Sustained Fatigue (SF): latest two Modified Fatigue Impact Scale (MFIS) ≥ 38 (n = 26); 2. Reversible Fatigue (RF): latest MFIS < 38, and at least one previous MFIS ≥ 38 (n = 25); 3. Never Fatigued (NF): ≥ 5 consecutive MFIS < 38 (n = 42); 4. Healthy Controls (n = 6). Diffusion MRI-derived measures of fractional anisotropy (FA), axial (AD), mean (MD), and radial diffusivity (RD) of the slMFB were compared between the groups. Depression was assessed using the Center for Epidemiologic Studies-Depression Scale (CES-D). RESULTS: Depressed (CES-D ≥ 16) SF patients showed significantly higher MD and RD than nondepressed SF and RF, and depressed RF patients, and significantly lower FA than nondepressed SF and depressed RF patients in their left slMFB. Depressed SF patients showed significantly higher left slMFB MD and AD than healthy controls. CONCLUSION: Microstructural changes to the left slMFB may play a role in the comorbid development of fatigue and depression in MS.
Liu D, Zhang D, Song Y, Zhang F, O'Donnell L, Huang H, Chen M, Cai W. PDAM: A Panoptic-Level Feature Alignment Framework for Unsupervised Domain Adaptive Instance Segmentation in Microscopy Images. IEEE Trans Med Imaging. 2021;40 (1) :154-165.Abstract
In this work, we present an unsupervised domain adaptation (UDA) method, named Panoptic Domain Adaptive Mask R-CNN (PDAM), for unsupervised instance segmentation in microscopy images. Since there currently lack methods particularly for UDA instance segmentation, we first design a Domain Adaptive Mask R-CNN (DAM) as the baseline, with cross-domain feature alignment at the image and instance levels. In addition to the image- and instance-level domain discrepancy, there also exists domain bias at the semantic level in the contextual information. Next, we, therefore, design a semantic segmentation branch with a domain discriminator to bridge the domain gap at the contextual level. By integrating the semantic- and instance-level feature adaptation, our method aligns the cross-domain features at the panoptic level. Third, we propose a task re-weighting mechanism to assign trade-off weights for the detection and segmentation loss functions. The task re-weighting mechanism solves the domain bias issue by alleviating the task learning for some iterations when the features contain source-specific factors. Furthermore, we design a feature similarity maximization mechanism to facilitate instance-level feature adaptation from the perspective of representational learning. Different from the typical feature alignment methods, our feature similarity maximization mechanism separates the domain-invariant and domain-specific features by enlarging their feature distribution dependency. Experimental results on three UDA instance segmentation scenarios with five datasets demonstrate the effectiveness of our proposed PDAM method, which outperforms state-of-the-art UDA methods by a large margin.

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