2020
DOI: 10.1007/s00401-020-02168-0
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Prion propagation estimated from brain diffusion MRI is subtype dependent in sporadic Creutzfeldt–Jakob disease

Abstract: Sporadic Creutzfeldt-Jakob disease (sCJD) is a transmissible brain proteinopathy. Five main clinicopathological subtypes (sCJD-MM(V)1,-MM(V)2C,-MV2K,-VV1, and-VV2) are currently distinguished. Histopathological evidence suggests that the localisation of prion aggregates and spongiform lesions varies among subtypes. Establishing whether there is an initial site with detectable imaging abnormalities (epicentre) and an order of lesion propagation would be informative for disease early diagnosis, patient staging, … Show more

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Cited by 35 publications
(45 citation statements)
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“…In the longitudinal component of this study, we have shown that signal abnormality on DWI extends to new brain regions in the first 3 months after symptom onset. In a prior cross‐sectional MRI study, we demonstrated that the disease process is first detected in one distinct anatomical region or epicenter, and propagates along different trajectories that are subtype specific in subsequent stages 33 . The present study brings to the fore the impact that the appearance of new DWI hyperintensities associated with distinct stages of the disease may have on MRI diagnostic accuracy.…”
Section: Discussionmentioning
confidence: 50%
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“…In the longitudinal component of this study, we have shown that signal abnormality on DWI extends to new brain regions in the first 3 months after symptom onset. In a prior cross‐sectional MRI study, we demonstrated that the disease process is first detected in one distinct anatomical region or epicenter, and propagates along different trajectories that are subtype specific in subsequent stages 33 . The present study brings to the fore the impact that the appearance of new DWI hyperintensities associated with distinct stages of the disease may have on MRI diagnostic accuracy.…”
Section: Discussionmentioning
confidence: 50%
“…The early diagnosis of sCJD subtypes is clinically relevant not only because the subtypes significantly differ as to survival time and lesion propagation in the brain, 33 but also because evidence indicates that subtypes may respond differently to drug treatment 36,37 . This notion implies that, once treatments become available, they may have to be tailored to the sCJD subtype.…”
Section: Discussionmentioning
confidence: 99%
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“…Different α-Syn fibril strains [15,[23][24][25][26][27][28] could affect the characteristics of every single step [15,29,30]. Thus, just as different prion strains cause different human disease phenotypes [31], distinct α-Syn fibril strains could be at the origin of PD, DLB and MSA [32].…”
Section: Introductionmentioning
confidence: 99%
“…There is a vast literature on very recent applications of the Bhattacharyya coefficient, for instance it appears exemplarily in Peng & Li [289] for object tracking from successive video frames, Ayed et al [26] for efficient graph cut algorithms, Patra et al [287] for collaborative filtering in sparse data, El Merabet et al [119] for region classification in intelligent transport systems in order to compensate the lack of performance of Global Navigation Satellites Systems, Chiu et al [86] for the design of interactive mobile augmented reality systems, Noh et al [274] for dimension reduction in interacting fluid flow models, Bai et al [29] for material defect detection through ultrasonic array imaging, Dixit & Jain [115] for the design of recommender systems on highly sparse context aware datasets, Guan et al [143] for visible light positioning methods based on image sensors, Lin et al [220] for probabilistic representation of color image pixels, Chen et al [80] for distributed compressive video sensing, Jain et al [162] for the enhancement of multistage user-based collaborative filtering in recommendation systems, Pascuzzo et al [285] for brain-diffusion-MRI based early diagnosis of the sporadic Creutzfeldt-Jakob disease, Sun et al [351] for the design of automatic detection methods multitemporal (e.g. landslide) point clouds, Valpione et al [377] for the investigation of T cell dynamics in immunotherapy, Wang et al [387] for the tracking and prediction of downbursts from meteorological data, Xu et al [403] for adaptive distributed compressed video sensing for coal mine monitoring, Zhao et al [424] for the shared sparse machine learning of the affective content of images, Chen et al [82] for image segmentation and domain partitioning, De Oliveira et al [105] for the prediction of cell-penetrating peptides, Eshaghi et al [122] for the identification of multiple sclerosis subtypes through machine learning of brain MRI scans, Feng et al [125] for improvements of MRI-based detection of epilepsy-causing cortical malformations, Hanli et al [153] for designing pilot protection schemes for transmission lines, Jiang et al [170] for flow-assisted visual tracking through event cameras, Lysiak & Szmajda …”
Section: ) Construction Principle For the Estimation Of The Minimum D...mentioning
confidence: 99%