| 1. |
- af Bjerkén, Sara, et al.
(författare)
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Reliability and validity of visual analysis of [18F]FE-PE2I PET/CT in early Parkinsonian disease
- 2023
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Ingår i: Nuclear medicine communications. - : Wolters Kluwer. - 0143-3636 .- 1473-5628. ; 44:5, s. 397-406
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Tidskriftsartikel (refereegranskat)abstract
- Objective: [18F]FE-PE2I (FE-PE2I) is a new radiotracer for dopamine transporter (DAT) imaging with PET. The aim of this study was to evaluate the visual interpretation of FE-PE2I images for the diagnosis of idiopathic Parkinsonian syndrome (IPS). The inter-rater variability, sensitivity, specificity, and diagnostic accuracy for visual interpretation of striatal FE-PE2I compared to [123I]FP-CIT (FP-CIT) single-photon emission computed tomography (SPECT) was evaluated.Methods: Thirty patients with newly onset parkinsonism and 32 healthy controls with both an FE-PE2I and FP-CIT were included in the study. Four patients had normal DAT imaging, of which three did not fulfil the IPS criteria at the clinical reassessment after 2 years. Six raters evaluated the DAT images blinded to the clinical diagnosis, interpreting the image as being ‘normal’ or ‘pathological’, and assessed the degree of DAT-reduction in the caudate and putamen. The inter-rater agreement was assessed with intra-class correlation and Cronbach’s α. For calculation of sensitivity and specificity, DAT images were defined as correctly classified if categorized as normal or pathological by ≥4/6 raters.Results: The overall agreement in visual evaluation of the FE-PE2I- and FP-CIT images was high for the IPS patients (α = 0.960 and 0.898, respectively), but lower in healthy controls (FE-PE2I: α = 0.693, FP-CIT: α = 0.657). Visual interpretation gave high sensitivity (both 0.96) but lower specificity (FE-PE2I: 0.86, FP-CIT: 0.63) with an accuracy of 90% for FE-PE2I and 77% for FP-CIT.Conclusion: Visual evaluation of FE-PE2I PET imaging demonstrates high reliability and diagnostic accuracy for IPS.
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| 2. |
- Laiterä, Tiina, et al.
(författare)
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Effects of Alzheimer's Disease-Associated Risk Loci on Amyloid-β Accumulation in the Brain of Idiopathic Normal Pressure Hydrocephalus Patients
- 2017
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Ingår i: Journal of Alzheimer's Disease. - 1387-2877 .- 1875-8908. ; 55:3, s. 995-1003
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Idiopathic normal pressure hydrocephalus (iNPH) is a dementing condition featuring characteristic symptoms, ventriculomegaly, and normal or slightly elevated cerebrospinal fluid pressure. In Alzheimer's disease (AD) patients, diffuse aggregates of amyloid-β (Aβ) and neurofibrillary hyperphosphorylated tau are detected in the neocortex of the brain, while similar accumulation of Aβ is also detected in iNPH. Recent genome-wide association studies have identified several novel risk loci for AD, potentially affecting Aβ-related cellular processes. Apart from the apolipoprotein E ɛ4 allele (APOE4), the risk effect of single loci is low, emphasizing the importance of the polygenic risk score approach when assessing the combined effects.OBJECTIVE: To study the effects of AD-associated individual and polygenic risk score of single nucleotide polymorphisms (SNPs) on the accumulation of Aβ in the brain samples of iNPH patients.METHODS: A sample set of frontal cortex biopsies from 188 iNPH patients were divided into two groups according to the Aβ pathology. After the genotyping of the AD-associated risk loci, polygenic risk score was calculated for each iNPH patient and subsequently analyzed in relation to Aβ deposition.RESULTS: Apart from the APOE4, none of the SNPs revealed a statistically significant effect on the accumulation of Aβ in iNPH. Also, the non-APOE4 polygenic risk score did not associate with Aβ deposition.CONCLUSION: Novel AD-associated risk genes have no significant effect on Aβ accumulation in the brain of iNPH patients. However, APOE4 affects the Aβ deposition in the brain of iNPH and AD patients in a similar manner.
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| 3. |
- Luikku, Antti J., et al.
(författare)
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Multimodal analysis to predict shunt surgery outcome of 284 patients with suspected idiopathic normal pressure hydrocephalus
- 2016
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Ingår i: Acta Neurochirurgica. - : Springer Science and Business Media LLC. - 0001-6268 .- 0942-0940. ; 158:12, s. 2311-2319
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Tidskriftsartikel (refereegranskat)abstract
- Optimal selection of idiopathic normal pressure hydrocephalus (iNPH) patients for shunt surgery is challenging. Disease State Index (DSI) is a statistical method that merges multimodal data to assist clinical decision-making. It has previously been shown to be useful in predicting progression in mild cognitive impairment and differentiating Alzheimer's disease (AD) and frontotemporal dementia. In this study, we use the DSI method to predict shunt surgery response for patients with iNPH. In this retrospective cohort study, a total of 284 patients (230 shunt responders and 54 non-responders) from the Kuopio NPH registry were analyzed with the DSI. Analysis included data from patients' memory disorder assessments, age, clinical symptoms, comorbidities, medications, frontal cortical biopsy, CT/MRI imaging (visual scoring of disproportion between Sylvian and suprasylvian subarachnoid spaces, atrophy of medial temporal lobe, superior medial subarachnoid spaces), APOE genotyping, CSF AD biomarkers, and intracranial pressure. Our analysis showed that shunt responders cannot be differentiated from non-responders reliably even with the large dataset available (AUC = 0.58). Prediction of the treatment response in iNPH is challenging even with our extensive dataset and refined analysis. Further research of biomarkers and indicators predicting shunt responsiveness is still needed.
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| 4. |
- Luikku, Antti J., et al.
(författare)
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Predicting Development of Alzheimer's Disease in Patients with Shunted Idiopathic Normal Pressure Hydrocephalus
- 2019
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Ingår i: Journal of Alzheimer's Disease. - 1387-2877 .- 1875-8908. ; 71:4, s. 1233-1243
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Tidskriftsartikel (refereegranskat)abstract
- Background: Idiopathic normal pressure hydrocephalus (iNPH) patients often develop Alzheimer's disease (AD) related brain pathology. Disease State Index (DSI) is a method to combine data from various sources for differential diagnosis and progression of neurodegenerative disorders.Objective: To apply DSI to predict clinical AD in shunted iNPH-patients in a defined population.Methods: 335 shunted iNPH-patients (median 74 years) were followed until death (n = 185) or 6/2015 (n = 150). DSI model (including symptom profile, onset age of NPH symptoms, atrophy of medial temporal lobe in CT/MRI, cortical brain biopsy finding, and APOE genotype) was applied. Performance of DSI model was evaluated with receiver operating characteristic (ROC) curve analysis.Results: A total of 70 (21%) patients developed clinical AD during median follow-up of 5.3 years. DSI-model predicted clinical AD with moderate effectiveness (AUC= 0.75). Significant factors were cortical biopsy (0.69), clinical symptoms (0.66), and medial temporal lobe atrophy (0.66).Conclusion: We found increased occurrence of clinical AD in previously shunted iNPH patients as compared with general population. DSI supported the prediction of AD. Cortical biopsy during shunt insertion seems indicated for earlier diagnosis of comorbid AD.
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| 5. |
- Munoz-Ruiz, Miguel Angel, et al.
(författare)
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Using the Disease State Fingerprint Tool for Differential Diagnosis of Frontotemporal Dementia and Alzheimer's Disease
- 2016
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Ingår i: Dementia and Geriatric Cognitive Disorders Extra. - : S. Karger AG. - 1664-5464. ; 6:2, s. 313-329
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Tidskriftsartikel (refereegranskat)abstract
- Background: Disease State Index (DSI) and its visualization, Disease State Fingerprint (DSF), form a computer-assisted clinical decision making tool that combines patient data and compares them with cases with known outcomes. Aims: To investigate the ability of the DSI to diagnose frontotemporal dementia (FTD) and Alzheimer's disease (AD). Methods: The study cohort consisted of 38 patients with FTD, 57 with AD and 22 controls. Autopsy verification of FTD with TDP-43 positive pathology was available for 14 and AD pathology for 12 cases. We utilized data from neuropsychological tests, volumetric magnetic resonance imaging, single-photon emission tomography, cerebrospinal fluid biomarkers and the APOE genotype. The DSI classification results were calculated with a combination of leave-one-out cross-validation and bootstrapping. A DSF visualization of a FTD patient is presented as an example. Results: The DSI distinguishes controls from FTD (area under the receiver-operator curve, AUC = 0.99) and AD (AUC = 1.00) very well and achieves a good differential diagnosis between AD and FTD (AUC = 0.89). In subsamples of autopsy-confirmed cases (AUC = 0.97) and clinically diagnosed cases (AUC = 0.94), differential diagnosis of AD and FTD performs very well. Conclusions: DSI is a promising computer-assisted biomarker approach for aiding in the diagnostic process of dementing diseases. Here, DSI separates controls from dementia and differentiates between AD and FTD.
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