Emerging Technologies That Will Revolutionize Neurological Care Prof. Paolo Manganotti Neurology Clinic of Trieste University Hospital 27 ...
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Emerging Technologies That Will
Revolutionize Neurological Care
Prof. Paolo Manganotti
Neurology Clinic of Trieste University Hospital
27 settembre 2018
Emerging Technologies That Will
Revolutionize Neurological Care
Neuroimaging for Neurodegenerative Disorders and Stoke
Early Diagnosis and Treatment of Alzheimer’s
Disease
The Promise of Brain and genetic Biomarkers
Healing the Brain with
Neuromodulation
Innovative Pharmacological and genetic Therapy
Robotics for Neuro Rehabilitation
Digital health and sensors for Acute and Chronic Care
Neuroimaging biomarkers, correlation with CFS biomarkers
and joint analysis with high density EEG in early diagnosis
and prognosis of Dementias
Perfusion MRI
high density EEG
ASL
3T MRI
Ischemic Volume and Neurological Deficit: Correlation of CT Perfusion with the NIHSS Score in Acute Ischemic Stroke G. Furlanis, M. Ajčević ,P. Maganotti - Journal of Stroke and Cerebrovascular Diseases, 2018
Brain Oscillatory Activity and CT Perfusion in Hyper-
Acute
Ischemic Stroke
L. Stragapede, M. Ajčević ,P. Maganotti - Journal of Stroke and Cerebrovascular Diseases, 2018
MeMoRi NET
Network for Mental Rehabilitation and Motors of the
Ictus
The MEMORI-net project is a joint effort to improve rehabilitation
strategies for patients who have suffered a stroke
Rehabilitation and Cognitive performance with app
Neurophysiological mechanisms underlying
underwater Parkinson’s disease rehabilitation
……..
Robotic bed for acute neurological rehabilitation-BTS
EEG findings Topographic maps showing ERD and t values. Grand average maps of ERD/ERS in alpha and beta bands during immagination of movement. Blue color coding indicates maximal ERD. T-maps of ERD/ERS in alpha and beta bands thresholded at p
High density EEG system EEG cap with 256 channels (Electrical Geodesics Inc. Eugene,OR, USA) Elastic tension structure and electrolyte solution Ag/AgCl electrodes Application time of 10-15 minutes Rate of acquisition (until 20 kHz)
Geodesic Sensor Net
- Elettrodo in fibra di carbonio
- Utilizzazione soluzione acquosa e potassio
- Funzionamento ad alta impedenza
- Amplificatori a 32 – 64 - 128 – 256 canali
dedicati EGIGeodesic Sensor Net - Utilizzazione soluzione conduttiva acqua e potassio - Spugna SuperDry ad elevata capacità di assorbimenteo acqua - Microclima di mantenimento umidità che sfrutta il calore corporeo; cica 2 ore
Multimodality approach High density EEG 256 channels Anatomical MRI 3T
Time course of the EEG source Rising phase
Time course of the EEG source Peak
EEG-fMRI coregistration
fMRI
measures the hemodynamic Standard EEG
response related to neural activity 30 channels acquired
in the brain. BOLD signal (Blood during fMRI
Oxygenation Level Dependent)
EEG misures neuronal currents from the
EEG-fMRI coregistration system
scalp with high temporal resolution (ms)
but limited number of EEG channels
• fMRI: high spatial resolution
• EEG: high temporal resolutionEEG-fMRI coregistration system
EEG-fMRI: conventional analysis in epilepsy
EEG during fMRI EEG filtered
Artifact Visual
subctraction detection
(Allen et al., 2000)
HRF
fMRI map
GLM Regressor
(Friston et al.,1995)
Mostra Desktop.scfReproducibility of EEG-fMRI results: overlapping regions were localized in the same Brodmann areas with 1762 common voxels in area 40 and in area 21.
•Synchronization of Neuronal Activity in the Human Primary Motor Cortex •by Transcranial magnetic stimulation: An EEG Study. Paus et al. 2001
Hd EEG and TMS
UNIVERSITA’ DEGLI STUDI DI TRIESTE
DIPARTIMENTO DI SCIENZE MEDICHE, CHIRURGICHE E
DELLA SALUTE
Alternative splicing as a potential
biomarker for Parkinson’s
disease
Prof. Paolo Manganotti
Valentina Tommasini Prof. Emanuele Buratti
Prof. Maurizio Romano
Dott. Mauro Catalana-sinucleina La Malattia di Parkinson è una sinucleinopatia
Obiettivo dello studio Identificare biomarcatori nel sangue dei pazienti affetti da Malattia di Parkinson Ricercare variazioni dello splicing alternativo nell’RNA leucocitario
Risultati
2) Espressione genica
SNCA LRRK2 PARK2
(alfa- (dardarina) (parkina)
sinucleina)
Causa più 50% dei PD
Principale frequente di PD autosomici
componente autosomico recessivi
dei corpi di dominante e
Lewy fattore di rischio
per PD sporadicoRisultati
3) Splicing alternativo
ATXN2 HSPH1 LRRFIP1
(atassina-2) (heat-shock (leucine-rich repeat
protein 1) flightless-interacting
Responsabile protein 1)
della SCA-2 e
Folding proteico
fattore di Risposta allo stress
rischio per SLA cellulare
e PSP
Henderson-Smith, A. et al. Next-generation profiling to identify the molecular etiology of
Parkinson dementia. Neurol Genet (2016).Linee di sviluppo applicative in
Neurologia CLINICA
DEVICE WIRELSS E SENSORI IN FASE ACUTA E
DOMOTICA
DEVICE ROBOTICI E NEURO-PROTESI
BIOIMAGING E NEUROFISIOLOGIA
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