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27 settembre 2018
Emerging Technologies That Will Revolutionize Neurological Care
Prof. Paolo Manganotti
Neurology Clinic of Trieste University Hospital
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
3T MRI
Perfusion MRI high density EEG
ASL
Ischemic Volume and Neurological Deficit: Correlation ofCT 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 andbeta bands during immagination of movement. Blue color coding indicates maximal ERD. T-mapsof ERD/ERS in alpha and beta bands thresholded at p<0.005
Event-related power decrease during motor imagery task in alpha and beta was bilateral, localizedover both ipsilateral and contralateral motor cortical region.
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)
- Elettrodo in fibra di carbonio
- Utilizzazione soluzione acquosa e potassio
- Funzionamento ad alta impedenza
- Amplificatori a 32 – 64 - 128 – 256 canali
dedicati EGI
Geodesic 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
Geodesic Sensor Net
Multimodality approach
High density EEG 256 channels Anatomical MRI 3T
Time course of the EEG sourceRising phase
Time course of the EEG sourcePeak
fMRI measures the hemodynamic response related to neural activity in the brain. BOLD signal (Blood Oxygenation Level Dependent)
Standard EEG30 channels acquiredduring fMRI
EEG misures neuronal currents from the scalp with high temporal resolution (ms) but limited number of EEG channels
• fMRI: high spatial resolution• EEG: high temporal resolution
EEG-fMRI coregistration system
EEG-fMRI coregistration
EEG-fMRI coregistration system
EEG during fMRI EEG filtered
Regressor
fMRI map
EEG-fMRI: conventional analysis in epilepsy
Artifact subctraction
(Allen et al., 2000)
GLM
(Friston et al.,1995)
Mostra Desktop.scf
HRF
Visual detection
Reproducibility of EEG-fMRI results: overlapping regions were localized in thesame 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
Alternative splicing as a potential biomarker for Parkinson’s
disease
Valentina Tommasini
Prof. Paolo Manganotti
Prof. Emanuele Buratti
Prof. Maurizio Romano
Dott. Mauro Catalan
UNIVERSITA’ DEGLI STUDI DI TRIESTE
DIPARTIMENTO DI SCIENZE MEDICHE, CHIRURGICHE E
DELLA SALUTE
a-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 (alfa-
sinucleina)
Principale componente dei corpi di
Lewy
LRRK2(dardarina)
Causa più frequente di PD
autosomico dominante e
fattore di rischio per PD sporadico
PARK2(parkina)
50% dei PD autosomici
recessivi
Risultati
3) Splicing alternativo
ATXN2(atassina-2)
Responsabile della SCA-2 e
fattore di rischio per SLA
e PSP
HSPH1(heat-shock protein 1)
Folding proteico
LRRFIP1(leucine-rich repeat flightless-interacting
protein 1)
Risposta allo stress cellulare
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
GENETICA – BIOMARKERS – FARMOGENETICA