Image Analysis Applications
Monday 3 May 2010
Room A7 11:00-13:00 Moderators: Claudia Lenz and Simon K. Warfield

11:00 53.

Automatic Computational Method for the Measurement of Neuronal Cell Loss in Transgenic Mouse Model of AD
George Iordanescu1,2, Palamadai Venkatasubramanian1,2, Alice Wyrwicz1,3
1Center for Basic MR Research, Northshore University HealthSystem, Evanston, IL, United States; 2Pritzker School of Medicine, University of Chicago, Chicago, IL, United States; 3Biomedical Engineering, Northwestern University, Evanston, IL, United States

Loss of neurons and synapses is a key features that characterize Alzheimer’s disease (AD). A novel semi-automatic segmentation method is used to quantify the neuronal loss in the pyramidal cell layer in hippocampal CA1 subfield (PLCA1) in a very rapid progression AD model. The proposed method uses unsupervised support vector machines. The resulting distance to the classification hyperplane combines all classification features and measures the neuronal cell loss as indicated by the MR contrast. The distribution of the neuronal cell loss within the PLCA1 may be a useful tool to understand the mechanism of cell loss in AD.

     
11:12   54.

Analysis of MRI Data Monitoring the Treatment of Polycystic Kidney Disease in a Preclinical Mouse Model
Stathis Hadjidemetriou1, Wilfried Reichardt1, Juergen Hennig1, Martin Buechert2, Dominik von Elverfeldt1
1Department of Diagnostic Radiology, University Hospital Freiburg, Freiburg, Germany; 2MRDAC, Freiburg, Germany

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by the growth of kidney cysts and the eventual kidney failure in humans. A treatment for ADPKD is not yet available. Treatment development involves preclinical studies with a mouse ADPKD model. Such mice have been monitored longitudinally with high field animal MRI. In this work the mouse kidneys are segmented with an unsupervised, reliable, and reproducible method. A region of interest is identified and analyzed for its statistics and for kidney geometry. This information is incorporated into the graph cuts algorithm that delineates the kidneys. Extensive validation is presented.

     
11:24 55. 

Effects of Smoking on Mouse Adipose Tissue Volumes Measured by IDEAL at 11.7T - not available
David Johnson1, Jiarui Lian1, Mohamed El-Mahdy1, Jay L. Zweier1
1Heart and Lung Research Institute, Ohio State University, Columbus, OH, United States

An imaging technique was developed to produce uniform, robust fat-water separation in mice at 11.7T using Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation method (IDEAL). Cigarette smoking (CS) C57BL/6 mice had less body weight and subcutaneous adipose tissue volumes as compared to controls. The volumes of muscle and other non-adipose tissues were not different between CS and control mice, supporting the hypothesis of a selective reduction in fat storage due to smoking.

     
11:36 56. 

T2* Evaluation of Iron Overload at 3T and Comparison  with 1.5 T
Daniele De Marchi1, Antonella Meloni1, Alessia Pepe1, Vincenzo Positano1, Luca Menichetti1, Petra Keilberg1, Chiara Ardenghi1, Federico Vivarini1, Saveria Campisi2, Massimo Lombardi1
1MRI Lab, “G. Monasterio Foundation” and Institute of Clinical Physiology, CNR, Pisa, Italy; 2A.O.  Umberto I, Siracusa, Italy

The relationship between T2* values at 3T and 1.5T over the range of clinical interest of tissue iron concentrations was evaluated by GRE multiecho sequences on a dedicated phantom and on thalassemia patients. A strongly significant linear relationship between T2* values at 1.5T and at 3T was found for both liver and phantoms data. The slope was about 0.6, with a negligible intercept. The distribution of T2* values in heart did not allow to establish the relationship between T2* values at 1.5T and at 3T in heart.

     
11:48 57.  

Accuracy of Wholebody Fat Quantification with MRI: A Comparison to Air-Displacement Plethysmography
Florian Klausmann1, Ute Ludwig1, Matthias Honal1, Daniel König2, Peter Deibert2, Sandra Huff1
1Department of Diagnostic Radiology, Medical Physics, University Hospital Freiburg, Freiburg, Germany; 2Department for Rehabilitation, Prevention and Sports Medicine, University Hospital Freiburg, Freiburg, Germany

Besides the total amount of adipose tissue, its distribution has recently been recognized as an important factor in the pathogenesis of metabolic diseases like diabetes mellitus. MRI is capable for space-resolved imaging of fat distributions in the human body. In this study, we present a fully automatic algorithm for fat quantification in MRI two-point Dixon data which considers partial volume effects of fat voxels, compensates B1-inhomogeneities in the MR images and separates subcutaneous and inner fat in the abdomen. MR quantification results were compared to air-displacement plethysmography measurements, which served as the standard of reference.

     
12:00 58. 

Fat Quantitation Using Chemical Shift Imaging and 1H-MRS in Vitro Phantom Model
Shenghong Ju1, Xingui Peng1, Fang Fang1, Gaojun Teng1
1Radiology, Zhongda Hospital, Southeast University, Nanjing, Jiangsu, China

Present study aims to evaluate the accuracy of CSI and MRS in fat quantification and composition by using phantom model at high field 7.0 Tesla MR.The ability for quantitative fat measurement is verified in phantoms. They are promising for further application in vivo quantitation of fat composition.

     
12:12  59. 

An Integrated Approach for Perfusion Lesion Segmentation Using MR Perfusion for Acute Ischemic Stroke - not available
Dattesh D. Shanbhag1, Rakesh Mullick1, Sumit K. Nath1, Catherine Oppenheim2, Marie Luby3, Katherine D. Ku3, Lawrence L. Latour3, Steven Warach3, - NINDS Natural History of Stroke Investigators3
1Imaging Technologies, GE Global Research, Bangalore, Karnataka, India; 2Department of Neuroradiology, Université Paris-Descartes, Paris, France; 3NINDS, NIH, Bethesda, MD, United States

In this work, we demonstrate a fully automated, fast and robust analysis pipeline for segmenting the perfusion lesion on different PWI maps (MTT, Tmax, TTP) and mismatch in acute ischemic stroke setting. The automatically segmented perfusion lesion and mismatch volume showed a strong correlation of 0.9 and 0.88 respectively, when compared to manually segmented PWI lesion on MTT maps. Variability for perfusion lesion volume estimates were lower compared to manual inter-rater variability, but was higher for mismatch estimates. Overall, Tmax PWI lesion had a lower volume compared to MTT PWI lesion.

     
12:24   60. 

Quantitative Imaging of Cortical Abnormalities in Extratemporal Epilepsy
Heath Richard Pardoe1, Graeme D. Jackson1,2

1Brain Research Institute, Florey Neuroscience Institutes, Melbourne, Victoria, Australia; 2Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia

In this study software-based analysis of structural MRI was used to map the thickness of the cortex in extratemporal epilepsy subjects with radiologically observable lesions. The technique was used to identify cortical abnormalities in the epilepsy patients. Non-rigid registration of the patient group and an age-matched group of controls to a custom template allowed voxel-wise comparison of the cortical thickness in each epilepsy subject with the control group using a standard score. Thresholds for the objective identification of cortical abnormalities were empirically determined by investigating the relationship between standard score and number of voxels exterior to manually delineated lesions.

     
12:36 61.

3D Visualization and Quantification of Subdural Electrode Shift Due to Craniotomy Opening
Peter Sherman LaViolette1, Alastair Hoyt2, Scott D. Rand3, Kathleen M. Schmainda1, Wade M. Mueller2
1
Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States; 2Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States; 3Radiology, Medical College of Wisconsin, Milwaukee, WI, United States

Epileptic patients with medically intractable seizure disorders are subject to implantation of subdural electrodes for the purpose of seizure localization.  It is assumed that these electrodes remain stationary during the reopening of the craniotomy defect at the time of resective surgery.  This study shows that brain compression changes and general grid shift both occur and move electrodes in non-trivial amounts.  This study builds a case for adoption of electrode/brain model reliance for electrode position determination instead of traditional visual assessment at the reopening of the craniotomy.

     
12:48 62.

Localization of Subdural Electrodes on MRI Cortical Surface Images for Evaluation of Epilepsy Patients - not available
Boklye Kim1, Jack Parent1, Oren Sagher1, Karen Kluin1, Charles R. Meyer1
1University of MIchigan, Ann Arbor, MI, United States

Presurgical evaluation of surgical treatment of epilepsy patients often requires implantation of subdural grid electrodes on the cortex. The exact locations of implanted electrodes are essential to evaluate cortical lesions related to seizure onsets and delineate eloquent brain areas. The process requires registration via multi-modality image warping and correction of post-craniotomy brain deformation. The loss of CSF fluid the presence of epidural or subdural hematoma from open craniotomy cause brain shifts. This work presents an mapping of electrodes from post-implant CT data to pre- or post surgery MRI by intermodality image warping to determine accurate positions involved in electrocortical stimulation.

     

 

Back to Main Meeting

Back to Home