TRADITIONAL POSTER - ismrm

Poster Sessions
1593. Maximum Likelihood Analysis Provides Accurate ADC Estimates from Diffusion-Weighted Prostate
Images Acquired with Multichannel Coils
Louisa Bokacheva 1 , Yousef Mazaheri 1,2 , Hedvig Hricak 2 , Jason Koutcher 1
1 Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, United States; 2 Department of Radiology,
Memorial Sloan-Kettering Cancer Center, New York, United States
Diffusion-weighted (DW) MR images are contaminated with Rician noise, which leads to bias in ADC estimates. We explore accuracy and precision of
calculating ADC from DW images acquired with multiple receiver channels using noise-corrected maximum likelihood estimation and uncorrected
nonlinear least-squares fitting and log-linear fitting. Using Monte Carlo simulations, phantom and in vivo imaging of human prostate we demonstrate that
accounting for Rician noise is important for images with variable SNR, for data acquired with phased arrays, and for achieving the maximum contrast
between tissues with low and high ADC, which is often required for discriminating cancer and benign tissues on ADC maps.
Diffusion-Based Segmentation
Hall B Thursday 13:30-15:30
1594. Validation of a Thalamus Segmentation Based on Local Difusion Information
Sarah Charlotte Mang 1,2 , Ania Busza, 2,3 , Susanne Reiterer 2 , Wolfgang Grodd 2 , Uwe Klose 2
1 SIDT, German Cancer Research Center, Heidelberg, Germany; 2 Section Experimental MR, Dept. of Neuroradiology, University
Hospital Tuebingen, Tuebingen, Germany; 3 MD/PhD Program, University of Massachusetts Medical School, Worcester, MA, United
States
Fast and accurate segmentation of thalamic nuclei is important for clinical applications. We validated a segmentation method that is based on the
classification of the local diffusion direction. We could show the correspondence between our segmentation results and anatomy known from a stereotactic
atlas by Morel et al. in a group study of 63 healthy subjects. To show the similarity of individual subject results we compared the center-of-mass coordinates
of the individual clusters and could show that they correspond well to each other.
1595. Parcelation of the Human Premotor Cortex with DTI Technique
Luca Nocetti 1 , Matteo Orlandi 2 , Davide Duzzi 2 , Patrizia Baraldi 2 , Carlo Adolfo Porro 2
1 Servizio Fisica Sanitaria, Az Osp.Univ. "Policlinico", Modena, Italy; 2 Dipartimento di Scienze Biomediche, Università di Modena e
Reggio Emilia
The human premotor cortex is likely to include a mosaic of anatomically and functionally distinct areas, as in non-human primates, but its functional
networks are only beginning to be understood. In this work we use the DTI technique to investigate the anatomical connectivity between the premotor cortex
and the other part of the brain. Data were processed using probabilistic tractography (FDT tool included in FSL package) Single subject analysis was
performed in different ways in order to check for repeatability. In particular we tested the eddy current correction step (ECC) as implemented in FSL
package and different paths of coregistration. Multi-subjects analysis was performed in a fashion based on the results of the single-subject analysis. Through
single-subject analysis an optimized processing procedure was defined. The multi-subject analysis revealed 4 main regions with different anatomical
connectivity
1596. Segmentation of Ischemic Lesion from Diffusion Weighted MRI and MR Apparent Diffusion
Coefficient Maps
yohan attal 1 , Charlotte Rosso 2 , Yves Samson 2 , Sylvain Baillet 3
1 CRICM - CNRS UMR7225, Paris, France, Metropolitan; 2 AP-HP-Urgences Cérébro-Vasculaires, Paris, France, Metropolitan; 3 MEG
Program, Department of Neurology, Medical College of Wisconsin-Froedtert Hospital, Milwaukee, US
We developed a fast and robust method to automatically segment ischemic lesions from a combination of acute diffusion-weighted MRI and apparent
diffusion coefficient image volumes. This new segmentation technique extracts the ischemic areas from standard, clinical DWI image volumes of patient
(N=40) with acute middle cerebral artery (MCA) stroke symptoms from the La Salpêtrière stroke center (Paris, France) database.
1597. TORTOISE: An Integrated Software Package for Processing of Diffusion MRI Data
Carlo Pierpaoli 1 , Lindsay Walker 1 , Mustafa Okan Irfanoglu 1 , Alan Barnett 1 , Peter Basser 1 , Lin-Ching
Chang 1 , Cheng Guan Koay 1 , Sinisia Pajevic 1 , Gustavo Rohde 1 , Joelle Sarlls 1 , Minjie Wu 1
1 NIH, Bethesda, MD, United States
TORTOISE is an integrated and flexible software package for processing of DTI data, and in general for the correction of diffusion weighted images to be
used for DTI and potentially for high angular resolution diffusion imaging (HARDI) analysis. It is non-commercial, and is freely available for download at
www.tortoisedti.org.
1598. Novel Whole Brain DTI Segmentation and Diffusion Colour Mapping Technique for Tumour
Diagnosis and Boundary Delineation
Timothy Lloyd Jones 1 , Ai Wern Chung 2 , B Anthony Bell 1 , Thomas Richard Barrick 2
1 Academic Neurosurgery Unit, St George's University of London, London, United Kingdom; 2 Centre for Clinical Neurosciences, St
George's University of London, London, United Kingdom
Accurate delineation of brain tumour boundaries is crucial for diagnosis, surveillance and treatment planning (e.g. image guided cyto-reductive surgery or
radiotherapy). We propose a novel whole brain k-medians diffusion tensor imaging (DTI) algorithm generating Diffusion Colour Maps (DCMs)
incorporating T2 relaxation, isotropic (p) and anisotropic (q) characteristics. In this study, we have applied our technique to a variety of intracranial