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Reproducibility of Laplacian Wall Thickness Measurements of the Gallbladder with Varying CT Slice Thickness

M. N. PrasadContact Information, M. S. BrownContact Information, C. NiContact Information, D. MargolisContact Information, M. DouekContact Information, S. RamanContact Information, D. LuContact Information, J. G. GoldinContact Information and S. K. WarfieldContact Information

(1)  Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
(2)  Department of Radiology, Children’s Hospital Boston, 300 Longwood Avenue, Boston, MA, USA

Received: 12 January 2008  Revised: 27 February 2008  Accepted: 4 April 2008  Published online: 3 June 2008

Abstract  In measuring changes of gallbladder wall thickness using CT, robustness to differences in acquisition protocols including slice thickness can be important. We have developed an automated technique based on Laplace’s equation to measure the gallbladder wall thickness using computer tomography (CT). The purpose of this work is to investigate the usefulness of the Laplacian technique in obtaining gallbladder wall thickness measurements that are reproducible with variations in CT slice thickness. This study included 2D (2D) and 3D (3D) wall thickness measurements using Laplace’s equation. Ten subjects who had 5 mm (thick) and 2.5 mm (thin) reconstruction (from a single set of raw data) through the abdomen were randomly selected from a research database. Their volumetric CT images were acquired using a multidetector GE MEDICAL SYSTEMS–LightSpeed 16 scanner at 120 KVP, ~250 mAs, with standard filter reconstruction algorithm and manually segmented on all CT cross sections by a radiologist. The inner and outer boundaries of the gallbladder wall were obtained from the segmentation. The thickness of the wall was quantified by computing the distance between the boundaries for each scan and over the entire volume using Laplace’s equation from mathematical physics. The distance between the surfaces is found by computing normalized gradients that form a vector field. The vector fields represent tangent vectors along field lines connecting both boundaries. The Laplacian technique was compared with the conventional Euclidean distance transformation (EDT) technique using coefficient of variation. EDT results in an Euclidean distance mapping between the two extracted surfaces. Both techniques were compared in 2D and 3D. For the 2D and 3D wall thickness measurements, a mean difference of 0.35 and 0.25 mm between thin and thick reconstruction was found respectively using Laplace’s equation. EDT resulted in a higher mean difference for both 2D and 3D. In addition, a significant difference in thickness between the Laplacian technique and EDT techniques (p < 0.001) were obtained. The Laplacian measurement of gallbladder wall showed significantly lower variation compared to EDT on different CT slice thickness for both 2D and 3D techniques. Hence, proving to be an important technique for obtaining reproducible wall thickness measurements of the gallbladder using CT.

Keywords  CT - Ultrasound - Laplace’s equation - Thickness - Reproducibility


Contact Information M. N. Prasad (Corresponding author)
Email: mithunp@cse.unsw.edu.au

Contact Information M. S. Brown
Email: MBrown@mednet.ucla.edu

Contact Information C. Ni
Email: CNi@mednet.ucla.edu

Contact Information D. Margolis
Email: DMargolis@mednet.ucla.edu

Contact Information M. Douek
Email: MDouek@mednet.ucla.edu

Contact Information S. Raman
Email: SRaman@mednet.ucla.edu

Contact Information D. Lu
Email: DLu@mednet.ucla.edu

Contact Information J. G. Goldin
Email: JGoldin@mednet.ucla.edu

Contact Information S. K. Warfield
Email: simon.warfield@childrens.harvard.edu

Mithun Prasad   received his Ph.D. from the University of New South Wales, Sydney, Australia in 2006. He was a postdoctoral scholar at the University of California, Los Angeles. His research interests are computer aided diagnosis and computer vision.
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Matthew S. Brown, Ph.D.   After receiving his doctorate in Computer Science from the University of New South Wales in his native Australia, he joined the UCLA Department of Radiological Sciences Faculty where he is currently an Associate Professor in the Section of Thoracic Imaging. His research focuses include computer-aided diagnosis and computer vision.
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Dr. Chiayi Ni   has recently graduated from Ross University School of Medicine, Dominica. She is currently working as a Staff Research Associate in the Thoracic Imaging Research Group, Department of Radiological Sciences at UCLA. Her research interests focus on CT assessment of thoracic and abdominal imaging on patients with advanced solid tumors.
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Daniel J A Margolis, M.D.   was awarded the National Cancer Institute Fellowship in Advanced Cancer Imaging at Stanford University in 2003, after finishing medical school at the University of Southern California and residency at UCLA. He returned to UCLA in 2006 as an Assistant Professor of Abdominal Imaging in the Department of Radiology, with an interest in cancer characterization, focusing on prostate, colon, renal, and pancreas.
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Michael Douek, M.D., M.B.A   received his Bachelor of Arts degree in Environmental Sciences from the University of California at Berkeley. He subsequently graduated from the University of California, Los Angeles School of Medicine, concurrently receiving his M.B.A. at the Anderson School of Management at UCLA in 2000, and continued on to residency in Diagnostic Radiology at UCLA. He also completed a fellowship in Abdominal Imaging at UCLA. He is currently an Assistant Clinical Professor of Radiological Sciences in the Multi-specialty Division and Abdominal Imaging Sections in the Department of Radiology at the David Geffen School of Medicine at UCLA.
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Steven S. Raman, M.D.   is an Associate Professor of Radiology at the David Geffen School of Medicine at UCLA. His expertise is in the subspecialty field of abdominal imaging and interventions. He is actively involved in research regarding thermal ablation of hepatic and renal malignancies. He is also director of the Abdominal Imaging Fellowship program.
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David Lu, M.D.   graduated from McGill University, Canada and did his medicine internship and residency in Royal Victoria Hospital, Canada. He then completed his residency in radiology in the University of Toronto and fellowship at Mass. General Hospital in abdominal imaging and intervention. He currently is faculty at UCLA.
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Jonathan Goldin   trained at the University of Cape Town Medical School obtaining his M.B.Ch.B. in 1983. After completing his Ph.D., he then completed his postgraduate training in Diagnostic Radiology at the St. Bartholomew’s Hospital in London, England and his fellowship in Thoracic Radiology at the UCLA. He is currently a Professor of Radiology at the David Geffen School of Medicine at UCLA.
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Simon Warfield   was awarded Ph.D. at the School of Computer Science and Engineering of the University of New South Wales, in Sydney, Australia. He is the Director of the Computational Radiology Laboratory (CRL) in the Department of Radiology at Children’s Hospital Boston, a Research Affiliate of CSAIL at Massachusetts Institute of Technology and an Associate Professor of Radiology at Harvard Medical School.
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