| 31. |
- Groot, Colin, et al.
(författare)
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Latent atrophy factors related to phenotypical variants of posterior cortical atrophy
- 2020
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Ingår i: Neurology. - 1526-632X. ; 95:12, s. 1672-1685
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: To determine whether atrophy relates to phenotypical variants of posterior cortical atrophy (PCA) recently proposed in clinical criteria (i.e., dorsal, ventral, dominant-parietal, and caudal) we assessed associations between latent atrophy factors and cognition. METHODS: We employed a data-driven Bayesian modeling framework based on latent Dirichlet allocation to identify latent atrophy factors in a multicenter cohort of 119 individuals with PCA (age 64 ± 7 years, 38% male, Mini-Mental State Examination 21 ± 5, 71% β-amyloid positive, 29% β-amyloid status unknown). The model uses standardized gray matter density images as input (adjusted for age, sex, intracranial volume, MRI scanner field strength, and whole-brain gray matter volume) and provides voxelwise probabilistic maps for a predetermined number of atrophy factors, allowing every individual to express each factor to a degree without a priori classification. Individual factor expressions were correlated to 4 PCA-specific cognitive domains (object perception, space perception, nonvisual/parietal functions, and primary visual processing) using general linear models. RESULTS: The model revealed 4 distinct yet partially overlapping atrophy factors: right-dorsal, right-ventral, left-ventral, and limbic. We found that object perception and primary visual processing were associated with atrophy that predominantly reflects the right-ventral factor. Furthermore, space perception was associated with atrophy that predominantly represents the right-dorsal and right-ventral factors. However, individual participant profiles revealed that the large majority expressed multiple atrophy factors and had mixed clinical profiles with impairments across multiple domains, rather than displaying a discrete clinical-radiologic phenotype. CONCLUSION: Our results indicate that specific brain behavior networks are vulnerable in PCA, but most individuals display a constellation of affected brain regions and symptoms, indicating that classification into 4 mutually exclusive variants is unlikely to be clinically useful.
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| 32. |
- Haller, Sven, et al.
(författare)
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Arterial Spin Labeling Perfusion of the Brain : Emerging Clinical Applications
- 2016
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Ingår i: Radiology. - : Radiological Society of North America (RSNA). - 0033-8419 .- 1527-1315. ; 281:2, s. 337-356
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Forskningsöversikt (refereegranskat)abstract
- Arterial spin labeling (ASL) is a magnetic resonance (MR) imaging technique used to assess cerebral blood flow noninvasively by magnetically labeling inflowing blood. In this article, the main labeling techniques, notably pulsed and pseudocontinuous ASL, as well as emerging clinical applications will be reviewed. In dementia, the pattern of hypoperfusion on ASL images closely matches the established patterns of hypometabolism on fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) images due to the close coupling of perfusion and metabolism in the brain. This suggests that ASL might be considered as an alternative for FDG, reserving PET to be used for the molecular disease-specific amyloid and tau tracers. In stroke, ASL can be used to assess perfusion alterations both in the acute and the chronic phase. In arteriovenous malformations and dural arteriovenous fistulas, ASL is very sensitive to detect even small degrees of shunting. In epilepsy, ASL can be used to assess the epileptogenic focus, both in peri- and interictal period. In neoplasms, ASL is of particular interest in cases in which gadolinium-based perfusion is contraindicated (eg, allergy, renal impairment) and holds promise in differentiating tumor progression from benign causes of enhancement. Finally, various neurologic and psychiatric diseases including mild traumatic brain injury or posttraumatic stress disorder display alterations on ASL images in the absence of visualized structural changes. In the final part, current limitations and future developments of ASL techniques to improve clinical applicability, such as multiple inversion time ASL sequences to assess alterations of transit time, reproducibility and quantification of cerebral blood flow, and to measure cerebrovascular reserve, will be reviewed.
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| 33. |
- Haller, Sven, et al.
(författare)
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Cerebral Microbleeds : Imaging and Clinical Significance
- 2018
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Ingår i: Radiology. - : Radiological Society of North America (RSNA). - 0033-8419 .- 1527-1315. ; 287:1, s. 11-28
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Forskningsöversikt (refereegranskat)abstract
- Cerebral microbleeds (CMBs), also referred to as microhemorrhages, appear on magnetic resonance (MR) images as hypointense foci notably at T2*-weighted or susceptibility-weighted (SW) imaging. CMBs are detected with increasing frequency because of the more widespread use of high magnetic field strength and of newer dedicated MR imaging techniques such as three-dimensional gradient-echo T2*-weighted and SW imaging. The imaging appearance of CMBs is mainly because of changes in local magnetic susceptibility and reflects the pathologic iron accumulation, most often in perivascular macrophages, because of vasculopathy. CMBs are depicted with a true-positive rate of 48%–89% at 1.5 T or 3.0 T and T2*-weighted or SW imaging across a wide range of diseases. False-positive “mimics” of CMBs occur at a rate of 11%–24% and include microdissections, microaneurysms, and microcalcifications; the latter can be differentiated by using phase images. Compared with postmortem histopathologic analysis, at least half of CMBs are missed with premortem clinical MR imaging. In general, CMB detection rate increases with field strength, with the use of three-dimensional sequences, and with postprocessing methods that use local perturbations of the MR phase to enhance T2* contrast. Because of the more widespread availability of high-field-strength MR imaging systems and growing use of SW imaging, CMBs are increasingly recognized in normal aging, and are even more common in various disorders such as Alzheimer dementia, cerebral amyloid angiopathy, stroke, and trauma. Rare causes include endocarditis, cerebral autosomal dominant arteriopathy with subcortical infarcts, leukoencephalopathy, and radiation therapy. The presence of CMBs in patients with stroke is increasingly recognized as a marker of worse outcome. Finally, guidelines for adjustment of anticoagulant therapy in patients with CMBs are under development.
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| 34. |
- Haller, Sven, et al.
(författare)
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Interaction of Vascular Damage and Alzheimer Dementia : Focal Damage and Disconnection
- 2017
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Ingår i: Radiology. - : Radiological Society of North America (RSNA). - 0033-8419 .- 1527-1315. ; 282:2, s. 311-313
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Tidskriftsartikel (refereegranskat)abstract
- Dementia is a major health and socioeconomic problem with ever-increasing prevalence due to the increasing age of the population (1). Alzheimer disease (AD) and vascular dementia are both common disorders in the elderly, and although they are commonly co-occurring, they are generally considered to be separate nosologic entities. Neuroimaging biomarkers have evolved considerably over the past decade and demonstrate new insights into disease mechanisms in dementia. Of particular interest is the evolving view of interaction between pathophysiological mechanisms in AD and vascular dementia, as demonstrated with neuroimaging.
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| 35. |
- Haller, Sven, et al.
(författare)
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Neuroimaging in Dementia : A Clinical Approach
- 2018
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Ingår i: Clinical Neuroradiology. - Cham : Springer. - 9783319614236
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Bokkapitel (refereegranskat)abstract
- Dementia is not a diagnosis or a specific disease entity but a syndrome that describes a wide range of symptoms leading to a decline in mental ability severe enough to interfere with daily life.Neurodegenerative disorders including dementing disorders and movement disorders may present with overlapping clinical symptoms. Likewise, the underlying molecular and cellular pathology may be overlapping. Consequently, dementia syndromes and movement disorders may be considered as a spectrum of diseases, and symptoms may vary over time. Moreover, there is no direct link between clinical symptoms and imaging findings: the same degree of brain atrophy or metabolic abnormality may be associated to a variable degree of cognitive impairment, or from the other perspective, the same degree of cognitive impairment may be associated with variable level of brain atrophy or metabolic abnormality. Finally, it is not uncommon to have coexisting pathology, for example, Alzheimer type neurodegeneration and a vascular contribution.In the first part, we review basic clinical presentations of dementia syndromes. In the second part, we review the radiological techniques and typical clinical neuroradiology findings of the various types of dementia, including Alzheimer dementia (hippocampal atrophy, hypometabolism/hypoperfusion in posterior cingulate and bilateral parietal areas), vascular dementia (small and large vessel disease), fronto-temporal lobar degeneration (fronto-temporal/peri-insular atrophy and hypometabolism/hypoperfusion), and dementia with Lewy Bodies (reduced dopamine uptake in striatum, abnormality of the nigrosome1). Additionally, we review unusual clinical presentations of dementia, including young-onset dementia and rapidly progressive dementia. Finally, we briefly discuss the overlapping clinical presentation and underlying pathology between dementia and movement disorders.
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| 36. |
- Haller, Sven, et al.
(författare)
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Neuroimaging in Dementia : More than Typical Alzheimer Disease
- 2023
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Ingår i: Radiology. - : Radiological Society of North America (RSNA). - 0033-8419 .- 1527-1315. ; 308:3
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Tidskriftsartikel (refereegranskat)abstract
- Alzheimer disease (AD) is the most common cause of dementia. The prevailing theory of the underlying pathology assumes amyloid accumulation followed by tau protein aggregation and neurodegeneration. However, the current antiamyloid and antitau treatments show only variable clinical efficacy. Three relevant points are important for the radiologic assessment of dementia. First, besides various dementing disorders (including AD, frontotemporal dementia, and dementia with Lewy bodies), clinical variants and imaging subtypes of AD include both typical and atypical AD. Second, atypical AD has overlapping radiologic and clinical findings with other disorders. Third, the diagnostic process should consider mixed pathologies in neurodegeneration, especially concurrent cerebrovascular disease, which is frequent in older age. Neuronal loss is often present at, or even before, the onset of cognitive decline. Thus, for effective emerging treatments, early diagnosis before the onset of clinical symptoms is essential to slow down or stop subsequent neuronal loss, requiring molecular imaging or plasma biomarkers. Neuroimaging, particularly MRI, provides multiple imaging parameters for neurodegenerative and cerebrovascular disease. With emerging treatments for AD, it is increasingly important to recognize AD variants and other disorders that mimic AD. Describing the individual composition of neurodegenerative and cerebrovascular disease markers while considering overlapping and mixed diseases is necessary to better understand AD and develop efficient individualized therapies.
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| 37. |
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| 38. |
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| 39. |
- Haller, Sven, et al.
(författare)
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Susceptibility-weighted Imaging : Technical Essentials and Clinical Neurologic Applications
- 2021
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Ingår i: Radiology. - : RADIOLOGICAL SOC NORTH AMERICA. - 0033-8419 .- 1527-1315. ; 299:1, s. 3-26
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Tidskriftsartikel (refereegranskat)abstract
- Susceptibility-weighted imaging (SWI) evolved from simple two-dimensional T2*-weighted sequences to three-dimensional sequences with improved spatial resolution and enhanced susceptibility contrast. SWI is an MRI sequence sensitive to compounds that distort the local magnetic field (eg, calcium and iron), in which the phase information can differentiate. But the term SWI is colloquially used to denote high-spatial-resolution susceptibility-enhanced sequences across different MRI vendors and sequences even when phase information is not used. The imaging appearance of SWI and related sequences strongly depends on the acquisition technique. Initially, SWI and related sequences were mostly used to improve the depiction of findings already known from standard two-dimensional T2*-weighted neuroimaging: more microbleeds in patients who are aging or with dementia or mild brain trauma; increased conspicuity of superficial siderosis in Alzheimer disease and amyloid angiopathy; and iron deposition in neurodegenerative diseases or abnormal vascular structures, such as capillary telangiectasia. But SWI also helps to identify findings not visible on standard T2*-weighted images: the nigrosome 1 in Parkinson disease and dementia with Lewy bodies, the central vein and peripheral rim signs in multiple sclerosis, the peripheral rim sign in abscesses, arterial signal loss related to thrombus, asymmetrically prominent cortical veins in stroke, and intratumoral susceptibility signals in brain neoplasms. (C) RSNA, 2021
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| 40. |
- Helland, Ragnhild Holden, et al.
(författare)
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Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networks.
- 2023
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Ingår i: Scientific reports. - 2045-2322. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Extent of resection after surgery is one of the main prognostic factors for patients diagnosed with glioblastoma. To achieve this, accurate segmentation and classification of residual tumor from post-operative MR images is essential. The current standard method for estimating it is subject to high inter- and intra-rater variability, and an automated method for segmentation of residual tumor in early post-operative MRI could lead to a more accurate estimation of extent of resection. In this study, two state-of-the-art neural network architectures for pre-operative segmentation were trained for the task. The models were extensively validated on a multicenter dataset with nearly 1000 patients, from 12 hospitals in Europe and the United States. The best performance achieved was a 61% Dice score, and the best classification performance was about 80% balanced accuracy, with a demonstrated ability to generalize across hospitals. In addition, the segmentation performance of the best models was on par with human expert raters. The predicted segmentations can be used to accurately classify the patients into those with residual tumor, and those with gross total resection.
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