Publications by Year: 2021

Bonkhoff AK, Schirmer MD, Bretzner M, Etherton M, Donahue K, Tuozzo C, Nardin M, Giese A-K, Wu O, Calhoun VD, Grefkes C, Rost NS. Abnormal dynamic functional connectivity is linked to recovery after acute ischemic stroke. Hum Brain Mapp 2021;42(7):2278-2291.Abstract
The aim of the current study was to explore the whole-brain dynamic functional connectivity patterns in acute ischemic stroke (AIS) patients and their relation to short and long-term stroke severity. We investigated resting-state functional MRI-based dynamic functional connectivity of 41 AIS patients two to five days after symptom onset. Re-occurring dynamic connectivity configurations were obtained using a sliding window approach and k-means clustering. We evaluated differences in dynamic patterns between three NIHSS-stroke severity defined groups (mildly, moderately, and severely affected patients). Furthermore, we built Bayesian hierarchical models to evaluate the predictive capacity of dynamic connectivity and examine the interrelation with clinical measures, such as white matter hyperintensity lesions. Finally, we established correlation analyses between dynamic connectivity and AIS severity as well as 90-day neurological recovery (ΔNIHSS). We identified three distinct dynamic connectivity configurations acutely post-stroke. More severely affected patients spent significantly more time in a configuration that was characterized by particularly strong connectivity and isolated processing of functional brain domains (three-level ANOVA: p < .05, post hoc t tests: p < .05, FDR-corrected). Configuration-specific time estimates possessed predictive capacity of stroke severity in addition to the one of clinical measures. Recovery, as indexed by the realized change of the NIHSS over time, was significantly linked to the dynamic connectivity between bilateral intraparietal lobule and left angular gyrus (Pearson's r = -.68, p = .003, FDR-corrected). Our findings demonstrate transiently increased isolated information processing in multiple functional domains in case of severe AIS. Dynamic connectivity involving default mode network components significantly correlated with recovery in the first 3 months poststroke.
Bretzner M, Bonkhoff AK, Schirmer MD, Hong S, Dalca AV, Donahue KL, Giese A-K, Etherton MR, Rist PM, Nardin M, Marinescu R, Wang C, Regenhardt RW, Leclerc X, Lopes R, Benavente OR, Cole JW, Donatti A, Griessenauer CJ, Heitsch L, Holmegaard L, Jood K, Jimenez-Conde J, Kittner SJ, Lemmens R, Levi CR, McArdle PF, McDonough CW, Meschia JF, Phuah C-L, Rolfs A, Ropele S, Rosand J, Roquer J, Rundek T, Sacco RL, Schmidt R, Sharma P, Slowik A, Sousa A, Stanne TM, Strbian D, Tatlisumak T, Thijs V, Vagal A, Wasselius J, Woo D, Wu O, Zand R, Worrall BB, Maguire JM, Lindgren A, Jern C, Golland P, Kuchcinski G, Rost NS. MRI Radiomic Signature of White Matter Hyperintensities Is Associated With Clinical Phenotypes. Front Neurosci 2021;15:691244.Abstract
Objective: Neuroimaging measurements of brain structural integrity are thought to be surrogates for brain health, but precise assessments require dedicated advanced image acquisitions. By means of quantitatively describing conventional images, radiomic analyses hold potential for evaluating brain health. We sought to: (1) evaluate radiomics to assess brain structural integrity by predicting white matter hyperintensities burdens (WMH) and (2) uncover associations between predictive radiomic features and clinical phenotypes. Methods: We analyzed a multi-site cohort of 4,163 acute ischemic strokes (AIS) patients with T2-FLAIR MR images with total brain and WMH segmentations. Radiomic features were extracted from normal-appearing brain tissue (brain mask-WMH mask). Radiomics-based prediction of personalized WMH burden was done using ElasticNet linear regression. We built a radiomic signature of WMH with stable selected features predictive of WMH burden and then related this signature to clinical variables using canonical correlation analysis (CCA). Results: Radiomic features were predictive of WMH burden (R 2 = 0.855 ± 0.011). Seven pairs of canonical variates (CV) significantly correlated the radiomics signature of WMH and clinical traits with respective canonical correlations of 0.81, 0.65, 0.42, 0.24, 0.20, 0.15, and 0.15 (FDR-corrected p-values CV 1 - 6 < 0.001, p-value CV 7 = 0.012). The clinical CV1 was mainly influenced by age, CV2 by sex, CV3 by history of smoking and diabetes, CV4 by hypertension, CV5 by atrial fibrillation (AF) and diabetes, CV6 by coronary artery disease (CAD), and CV7 by CAD and diabetes. Conclusion: Radiomics extracted from T2-FLAIR images of AIS patients capture microstructural damage of the cerebral parenchyma and correlate with clinical phenotypes, suggesting different radiographical textural abnormalities per cardiovascular risk profile. Further research could evaluate radiomics to predict the progression of WMH and for the follow-up of stroke patients' brain health.
Etherton MR, Wu O, Giese A-K, Rost NS. Normal-appearing white matter microstructural injury is associated with white matter hyperintensity burden in acute ischemic stroke. Int J Stroke 2021;16(2):184-191.Abstract
BACKGROUND: White matter hyperintensity of presumed vascular origin is a risk factor for poor stroke outcomes. In patients with acute ischemic stroke, however, the in vivo mechanisms of white matter microstructural injury are less clear. AIMS: To characterize the directional diffusivity components in normal-appearing white matter and white matter hyperintensity in acute ischemic stroke patients. METHODS: A retrospective analysis was performed on a cohort of patients with acute ischemic stroke and brain magnetic resonance imaging with diffusion tensor imaging sequences acquired within 48 h of admission. White matter hyperintensity volume was measured in a semi-automated manner. Median fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity values were calculated within normal-appearing white matter and white matter hyperintensity in the hemisphere contralateral to the acute infarct. Linear regression analysis was performed to evaluate predictors of white matter hyperintensity volume and normal-appearing white matter diffusivity metrics. RESULTS: In 319 patients, mean age was 64.9 ± 15.9 years. White matter hyperintensity volume was 6.33 cm3 (interquartile range 3.0-12.6 cm3). Axial and radial diffusivity were significantly increased in white matter hyperintensity compared to normal-appearing white matter. In multivariable linear regression, age (β = 0.20, P = 0.003) and normal-appearing white matter axial diffusivity (β = 37.9, P < 0.001) were independently associated with white matter hyperintensity volume. Subsequent analysis demonstrated that increasing age (β = 0.004, P < 0.001) and admission diastolic blood pressure (β = 0.001, P = 0.02) were independent predictors of normal-appearing white matter axial diffusivity in multivariable linear regression. CONCLUSIONS: Normal-appearing white matter axial diffusivity increases with age and is an independent predictor of white matter hyperintensity volume in acute ischemic stroke.
Bonkhoff AK, Schirmer MD, Bretzner M, Hong S, Regenhardt RW, Brudfors M, Donahue KL, Nardin MJ, Dalca AV, Giese A-K, Etherton MR, Hancock BL, Mocking SJT, McIntosh EC, Attia J, Benavente OR, Bevan S, Cole JW, Donatti A, Griessenauer CJ, Heitsch L, Holmegaard L, Jood K, Jimenez-Conde J, Kittner SJ, Lemmens R, Levi CR, McDonough CW, Meschia JF, Phuah C-L, Rolfs A, Ropele S, Rosand J, Roquer J, Rundek T, Sacco RL, Schmidt R, Sharma P, Slowik A, Söderholm M, Sousa A, Stanne TM, Strbian D, Tatlisumak T, Thijs V, Vagal A, Wasselius J, Woo D, Zand R, McArdle PF, Worrall BB, Jern C, Lindgren AG, Maguire J, Bzdok D, Wu O, Rost NS. Outcome after acute ischemic stroke is linked to sex-specific lesion patterns. Nat Commun 2021;12(1):3289.Abstract
Acute ischemic stroke affects men and women differently. In particular, women are often reported to experience higher acute stroke severity than men. We derived a low-dimensional representation of anatomical stroke lesions and designed a Bayesian hierarchical modeling framework tailored to estimate possible sex differences in lesion patterns linked to acute stroke severity (National Institute of Health Stroke Scale). This framework was developed in 555 patients (38% female). Findings were validated in an independent cohort (n = 503, 41% female). Here, we show brain lesions in regions subserving motor and language functions help explain stroke severity in both men and women, however more widespread lesion patterns are relevant in female patients. Higher stroke severity in women, but not men, is associated with left hemisphere lesions in the vicinity of the posterior circulation. Our results suggest there are sex-specific functional cerebral asymmetries that may be important for future investigations of sex-stratified approaches to management of acute ischemic stroke.