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  • 1
    In: NeuroImage, Elsevier BV, Vol. 271 ( 2023-05), p. 119985-
    Type of Medium: Online Resource
    ISSN: 1053-8119
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 1471418-8
    SSG: 5,2
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  • 2
    In: Stroke, Ovid Technologies (Wolters Kluwer Health), Vol. 50, No. 3 ( 2019-03), p. 602-609
    Abstract: Poststroke fatigue affects a large proportion of stroke survivors and is associated with a poor quality of life. In a recent trial, modafinil was shown to be an effective agent in reducing poststroke fatigue; however, not all patients reported a significant decrease in fatigue with therapy. We sought to investigate clinical and radiological predictors of fatigue reduction with modafinil therapy in a stroke survivor cohort. Methods— Twenty-six participants with severe fatigue (multidimensional fatigue inventory–20 ≥60) underwent magnetic resonance imaging at baseline and during the last week of a 6-week treatment period of 200 mg modafinil taken daily. Resting-state functional magnetic resonance imaging and high-resolution structural imaging data were obtained, and functional connectivity and regional brain volumes within the fronto-striato-thalamic network were obtained. Linear regression analysis was used to identify predictors of modafinil-induced fatigue reduction. Results— Multiple regression analysis showed that baseline multidimensional fatigue inventory–20 score (β=0.576, P =0.006) and functional connectivity between the dorsolateral prefrontal cortex and the caudate nucleus (β=−0.424, P =0.008) were significant predictors of modafinil-associated decreases in poststroke fatigue (adjusted r 2 =0.52, area under the receiver operator characteristic curve=0.939). Conclusions— Fronto-striato-thalamic functional connectivity predicted modafinil response for poststroke fatigue. Fatigue in other neurological disease has been attributed to altered function of the fronto-striato-thalamic network and may indicate that poststroke fatigue has a similar mechanism to other neurological injury related fatigue. Self-reported fatigue in patients with normal fronto-striato-thalamic functional connectivity may have a different mechanism and require alternate therapeutic approaches. Clinical Trial Registration— URL: https://www.clinicaltrials.gov . Unique identifier: ACTRN12615000350527.
    Type of Medium: Online Resource
    ISSN: 0039-2499 , 1524-4628
    RVK:
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2019
    detail.hit.zdb_id: 1467823-8
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  • 3
    Online Resource
    Online Resource
    Frontiers Media SA ; 2023
    In:  Frontiers in Neurology Vol. 14 ( 2023-2-23)
    In: Frontiers in Neurology, Frontiers Media SA, Vol. 14 ( 2023-2-23)
    Abstract: Computed tomography perfusion (CTP) imaging is widely used in cases of suspected acute ischemic stroke to positively identify ischemia and assess suitability for treatment through identification of reversible and irreversible tissue injury. Traditionally, this has been done via setting single perfusion thresholds on two or four CTP parameter maps. We present an alternative model for the estimation of tissue fate using multiple perfusion measures simultaneously. Methods We used machine learning (ML) models based on four different algorithms, combining four CTP measures (cerebral blood flow, cerebral blood volume, mean transit time and delay time) plus 3D-neighborhood (patch) analysis to predict the acute ischemic core and perfusion lesion volumes. The model was developed using 86 patient images, and then tested further on 22 images. Results XGBoost was the highest-performing algorithm. With standard threshold-based core and penumbra measures as the reference, the model demonstrated moderate agreement in segmenting core and penumbra on test images. Dice similarity coefficients for core and penumbra were 0.38 ± 0.26 and 0.50 ± 0.21, respectively, demonstrating moderate agreement. Skull-related image artefacts contributed to lower accuracy. Discussion Further development may enable us to move beyond the current overly simplistic core and penumbra definitions using single thresholds where a single error or artefact may lead to substantial error.
    Type of Medium: Online Resource
    ISSN: 1664-2295
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2564214-5
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  • 4
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2019
    In:  Scientific Reports Vol. 9, No. 1 ( 2019-07-04)
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 9, No. 1 ( 2019-07-04)
    Abstract: Post-stroke fatigue has a significant impact on stroke survivors’ mental and physical well-being. Our recent clinical trial showed significant reduction of post-stroke fatigue with modafinil treatment, however functional connectivity changes in response to modafinil have not yet been explored in stroke survivors with post-stroke fatigue. Twenty-eight participants (multidimensional fatigue inventory-20 ≥ 60) had MRI scans at baseline, and during modafinil and placebo treatment. Resting-state functional MRI data were obtained, and independent component analysis was used to extract functional networks. Resting-state functional connectivity (rsFC) was examined between baseline, modafinil and placebo treatment using permutation testing with threshold-free cluster enhancement. Overall twenty-eight participants (mean age: 62 ± 14.3, mean baseline MFI-20: 72.3 ± 9.24) were included. During modafinil treatment, increased rsFC was observed in the right hippocampus (p = 0.004, 11 voxels) compared to placebo. This coincided with lower rsFC in the left frontoparietal (inferior parietal lobule, p = 0.023, 13 voxels), somatosensory (primary somatosensory cortex; p = 0.009, 32 voxels) and mesolimbic network (temporal pole, p = 0.016, 35 voxels). In conclusion, modafinil treatment induces significant changes in rsFC in post-stroke fatigue. This modulation of rsFC may relate to a reduction of post-stroke fatigue; however, the relationship between sensory processing, neurotransmitter expression and fatigue requires further exploration.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
    detail.hit.zdb_id: 2615211-3
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  • 5
    In: Physical Therapy Reviews, Informa UK Limited, Vol. 24, No. 3-4 ( 2019-07-04), p. 100-117
    Type of Medium: Online Resource
    ISSN: 1083-3196 , 1743-288X
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2019
    SSG: 31
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  • 6
    In: International Orthopaedics, Springer Science and Business Media LLC, Vol. 35, No. 5 ( 2011-5), p. 767-776
    Type of Medium: Online Resource
    ISSN: 0341-2695 , 1432-5195
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2011
    detail.hit.zdb_id: 1459230-7
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  • 7
    In: Stroke, Ovid Technologies (Wolters Kluwer Health), Vol. 52, No. 1 ( 2021-01), p. 339-343
    Abstract: Lacunar syndromes correlate with a lacunar stroke on imaging in 50% to 60% of cases. Computed tomography perfusion (CTP) is becoming the preferred imaging modality for acute stroke triage. We aimed to estimate the sensitivity, specificity, and predictive values for noncontrast computed tomography and CTP in lacunar syndromes, and for cortical, subcortical, and posterior fossa regions. Methods: A retrospective analysis of confirmed ischemic stroke patients who underwent acute CTP and follow-up magnetic resonance imaging between 2010 and 2018 was performed. Brain noncontrast computed tomography and CTP were assessed independently by 2 stroke neurologists. Receiver operating characteristic curve analysis was performed to estimate sensitivity, specificity, and area under the curve (AUC) for the detection of strokes in patients with lacunar syndromes using different CTP maps. Results: We found 106 clinical lacunar syndromes, but on diffusion-weighted imaging, these consisted of 59 lacunar, 33 cortical, and 14 posterior fossa strokes. The discrimination of ischemia identification was very poor using noncontrast computed tomography in all 3 regions, but good for cortical (AUC, 0.82) and poor for subcortical and posterior regions (AUCs, 0.55 and 0.66) using automated core-penumbra maps. The addition of delay time and mean transient time maps substantially increased subcortical (AUC, 0.80) and slightly posterior stroke detection (AUC, 0.69). Conclusions: Analysis of mean transient time and delay time maps in combination with core-penumbra maps improves detection of subcortical and posterior strokes.
    Type of Medium: Online Resource
    ISSN: 0039-2499 , 1524-4628
    RVK:
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2021
    detail.hit.zdb_id: 1467823-8
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  • 8
    In: Stroke, Ovid Technologies (Wolters Kluwer Health), Vol. 55, No. Suppl_1 ( 2024-02)
    Abstract: Background: Lacunar stroke is a common form of ischaemic stroke with mechanisms poorly understood compared to large vessel stroke. Access to gold standard MRI is often limited in the acute setting. Acute diagnosis of lacunar stroke is difficult with conventional CT, as non-contrast CT and CT angiography have poor sensitivity. Previous studies have demonstrated only low to moderate sensitivity of CT perfusion (CTP). Aims: To test the accuracy of thin-slice CTP to detect lacunar stroke and compare the clinical and radiological characteristics to better understand the limitations of CTP for diagnosis of lacunar stroke. Methods: We reviewed thin-slice CTP (slice thickness 〈 =3mm) of cases presenting with an acute lacunar syndrome without large/medium vessel occlusion, or perfusion lesion detected by automated analysis. Cases presented to two comprehensive stroke centres in Sydney and Newcastle, NSW, Australia, between 2019 and 2022. CTP was reviewed by two independent reviewers, blinded to follow-up MRI but not the clinical syndrome. CTP and DWI were registered to a standard template and DWI lesions were manually segmented. CTP was further reviewed adjacent to DWI, and raw CTP values within the lesion was calculated. Results: We reviewed 394 cases of acute lacunar syndrome including 82 stroke mimics, 48 infratentorial and 250 supratentorial infarcts. Overall sensitivity was 76% and varied by infarct location. Sensitivity was lowest for brainstem (46%), moderate for thalamic (69%) and high for infarcts within the lenticulostriate perforator territory (84%). Factors associated with reduced sensitivity include small infarct volume, increased noise, or artefact, and infratentorial location. Conclusion: Thin-slice CTP has high sensitivity for detection of supratentorial lacunar infarcts however is more susceptible to noise and imaging artefact than larger infarcts. Advanced processing techniques show promise to improve overall diagnosis of lacunar stroke.
    Type of Medium: Online Resource
    ISSN: 0039-2499 , 1524-4628
    RVK:
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2024
    detail.hit.zdb_id: 1467823-8
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  • 9
    In: Journal of Neuroimaging, Wiley, Vol. 29, No. 1 ( 2019-01), p. 111-118
    Abstract: Degeneration of gray matter and subcortical structures after ischemic stroke has been well described. However, little is known about white matter degeneration after stroke. It is unclear whether white matter degeneration occurs throughout the whole brain, or whether patterns of degeneration occur more in specific brain areas. METHODS We prospectively collected National Institutes of Health Stroke Scale (NIHSS) scores and diffusion tensor imaging (DTI) in patients with acute ischemic stroke within the first week after onset (baseline), and at 1 and 3 months. DTI was processed to produce maps of fractional anisotropy, apparent diffusion coefficients, and axial and radial diffusivity. DTI parameters in specified regions‐of‐interest corresponding to items on the NIHSS were calculated and changes over time were assessed using linear mixed‐effect modeling. RESULTS Seventeen patients were included in the study. Mean age (SD) was 71 (11.7) years, and median (IQR) baseline NIHSS 9 (5‐13.3). Changes over time were observed in both visual cortices, contralesional primary motor cortex, premotor cortex, and superior temporal gyrus ( P 〈 .05). Changes in the ipsilesional motor cortex and inferior parietal lobule were only seen in patients with scores on the respective NIHSS‐items ( P 〈 .05). No significant changes in global white matter diffusivity parameters were identified ( P 〉 .05). CONCLUSION White matter changes after stroke may be localized rather than a global phenomenon.
    Type of Medium: Online Resource
    ISSN: 1051-2284 , 1552-6569
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 2035400-9
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  • 10
    In: Frontiers in Neurology, Frontiers Media SA, Vol. 15 ( 2024-2-15)
    Abstract: In acute stroke, identifying early changes (parenchymal hypodensity) on non-contrast CT (NCCT) can be challenging. We aimed to identify whether the accuracy of clinicians in detecting acute hypodensity in ischaemic stroke patients on a non-contrast CT is improved with the use of an Artificial Intelligence (AI) based, automated hypodensity detection algorithm (HDT) using MRI-DWI as the gold standard. Methods The study employed a case-crossover within-clinician design, where 32 clinicians were tasked with identifying hypodensity lesions on NCCT scans for five a priori selected patient cases, before and after viewing the AI-based HDT. The DICE similarity coefficient (DICE score) was the primary measure of accuracy. Statistical analysis compared DICE scores with and without AI-based HDT using mixed-effects linear regression, with individual NCCT scans and clinicians as nested random effects. Results The AI-based HDT had a mean DICE score of 0.62 for detecting hypodensity across all NCCT scans. Clinicians’ overall mean DICE score was 0.33 (SD 0.31) before AI-based HDT implementation and 0.40 (SD 0.27) after implementation. AI-based HDT use was associated with an increase of 0.07 (95% CI: 0.02–0.11, p = 0.003) in DICE score accounting for individual scan and clinician effects. For scans with small lesions, clinicians achieved a mean increase in DICE score of 0.08 (95% CI: 0.02, 0.13, p = 0.004) following AI-based HDT use. In a subgroup of 15 trainees, DICE score improved with AI-based HDT implementation [mean difference in DICE 0.09 (95% CI: 0.03, 0.14, p = 0.004)]. Discussion AI-based automated hypodensity detection has potential to enhance clinician accuracy of detecting hypodensity in acute stroke diagnosis, especially for smaller lesions, and notably for less experienced clinicians.
    Type of Medium: Online Resource
    ISSN: 1664-2295
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2024
    detail.hit.zdb_id: 2564214-5
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