Segmentazione RM cerebrale basata sulla rilassometria

Segmentazione RM cerebrale basata sulla rilassometria
Responsabile: Marco Comerci, marco.comerci

ibb.cnr.it

Descrizione:
Sviluppo, messa a punto e sperimentazione di uno strumento software che calcola i rates (velocità) di rilassamento RM e densità protonica voxel per voxel (immagini QMCI), e segmenta la maggior parte dei tessuti del cervello, tra cui lesioni di sclerosi multipla.

La versione attuale, validata a 1 e 1. 5 Tesla, segmenta studi del cervello nei seguenti 18 compartimenti: Materia Grigia (GM); Sostanza bianca (WM); Demielinizzata / Bianca Anormale (AWM); Liquido Cerebrospinale (CSF); Globo Pallido; Putamen; Talamo; Nucleo Caudato; Sostanza Nigra; Nucleo Rosso; Nucleo Dentato; Muscolo, Grasso; Umor Vitreo; Tessuti Connettivi intra-cranici ed extra-cranici; Fluidi extra-cranici; e tessuti a bassa densità protonica. Il software produce informazioni volumetriche e rilassmetriche di ogni comparto.

Questa segmentazione basata su modello, utilizza velocità di rilassamento, densità protonica e informazioni anatomiche.

Il software è configurabile e può essere ottimizzato per varie situazioni ambientali, come diverse caratteristiche dello scanner e diverse regioni anatomiche (vedi anche Segmentazione RM arto basata sulla rilassometria).

Un modulo per la valutazione automatica di follow-up è stato inoltre sviluppato: allinea studi basali e di follow-up con coregistrazione rigida (basata sulla mutual information normalizzata del software SPM), taglia fuori i tessuti non comuni a tutti gli studi ed esegue l'analisi di Pearson su volumi e rates.

Applicazione per la ricerca neurologica: invecchiamento; Malattia di Alzheimer; Schizofrenia; malattie degenerative; correzione dell'effetto volume parziale per la PET e SPECT.

I miglioramenti attualmente in fase di test includono: segmentazione di studi cervello a 3T; correzione disomogeneità RM in ricezione e trasmissione (critico per studi 3T); Stima automatica del reale angolo di flip; registrazione di semi-serie disallineate. Registrazione affine di basale e dl follow-up per tener conto della deriva del gradiente MR; Miglioramento del modello anatomico e di segnale per gli studi del cervello.

I miglioramenti pianificati futuri sono: supporto fast spin Echo; supporto 3D FFE simil- T1w; Altre sequenze veloci 3D per le mappe rilassamento; Modello anatomico e di segnale ulteriormente migliorati per gli studi del cervello; segmentazione iterativa.

Aree di ricerca: Imaging Quantitativo,

Attori:
Arturo Brunetti,
Mario Quarantelli, quarante

unina.it,
Anna Prinster, anna.prinster

ibb.cnr.it,
Bruno Alfano,
Marco Comerci, marco.comerci

ibb.cnr.it,

Parole chiave: MRI, segmentation, relaxometry, SPM, followup, basal

Immagine QMCI e corrispondente immagine segmentata

Non disponibili.

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Ultima modifica di Marco Comerci in data Wednesday 27 April 2016, 11:36:26
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