3D Elastography

1
3D Elastography
Enabling Technology to Better Segment Isoechoic
Lesions

• Harish Krishnaswamy, Parker Wilson
• Mentor Emad Boctor, Dr. Russell Taylor

2
Introduction

• 3D elastography has emerged as a viable solution
  for tracking of liver lesions during thermal
  ablation.
• Ultrasound is used to collect raw RF data that is
  then converted into strain fields.

3
Project Goals

• Liver phantoms can be used to simulate isoechoic
  lesions and are imaged in the laboratory using
  US.
• Implementation of a time-efficient 3D strain
  algorithm is important to generate strain fields
  from raw RF data.
• Optimization of the algorithm is important to
  reduce decorrelation noise.

4
Ultrasound Theory

• The ultrasound machine transmits high-frequency
  (1 to 5 megahertz) sound pulses into your body
  using a probe.
• The sound waves travel into your body and hit a
  boundary between tissues (e.g. between fluid and
  soft tissue, soft tissue and bone).
• Some of the sound waves get reflected back to the
  probe, while some travel on further until they
  reach another boundary and get reflected.
• The reflected waves are picked up by the probe
  and relayed to the machine.
• The machine calculates the distance from the
  probe to the tissue or organ (boundaries) using
  the speed of sound in tissue (5,005 ft/s or1,540
  m/s) and the time of the each echo's return
  (usually on the order of millionths of a second).
  
• The machine displays the distances and
  intensities of the echoes on the screen, forming
  a two dimensional image like the one shown below.
  
• http//www.howstuffworks.com/ultrasound.htm

5
Picture by howstuffworks.com
6
Transducer Construction

• The transducer probe generates and receives sound
  waves using a principle called the piezoelectric
  (pressure electricity) effect
• In the probe, there are one or more quartz
  crystals called piezoelectric crystals. When an
  electric current is applied to these crystals,
  they change shape rapidly. The rapid shape
  changes, or vibrations, of the crystals produce
  sound waves that travel outward. Conversely, when
  sound or pressure waves hit the crystals, they
  emit electrical currents.
• The same crystals can be used to send and receive
  sound waves.
• The probe also has a sound absorbing substance to
  eliminate back reflections from the probe itself,
  and an acoustic lens to help focus the emitted
  sound waves.

7
B-Mode Image 1

• Initial Cross Section Image of the Phantom.
• Region where Lesion does not exist.

Picture By Emad
8
B-Mode Image 2

• Middle Cross Section Image of the phantom
• Region of Max Lesion
• Note the isoechoic behavior of the lesion and
  background tissue

Picture By Emad
9
Displacement Field Image 1

• Displacement fields are layered and uniform
• Due to non uniformity of the phantom
• Shows no layer of lesion

Picture By Emad
10
Displacement Field Image 2

• Displacement field shows a rectangular cross
  section
• Represents the cross section of a cylindrical
  layer of lesion

Picture By Emad
11
Technical Progress

• Completed basis of Ophirs and Lorenzs Strain
  Algorithms
• Need to Implement interpolation method to
  displacement fields
• Optimize Algorithims using Log compression and
  temporal stretch
• Construct a new phantom and complete several new
  data protocols to ensure a robust data set before
  the probe returns to the manufacturer.

12
Improvement

• Linear Interpolation
• Spline Interpolation
• Low Pass Filter
• Log Compression
• Temporal Stretch

13
Dependencies

• Ultra Sound Machine
• Needs to be returned on April 20th
• Our Solution
• Build a better phantom
• Collect as much data before machine is returned

14
Updated Plan

• April 12 Complete building new phantom
• April 18 Complete Data Collection
• April 24 Complete Improvement to Strain
  Code
• May 1 Complete Testing and Optimization
  of Code
• May 11 Complete abstract for Ultrasound
  IEEE Convention

15
References

• Nakakura EK, Choti MA Management of
  hepatocellular carcinoma. Oncology (Huntingt).
  2000 Jul14(7)1085-98 discussion 1098-102.
  Review.
• Buscarini L, Rossi S Technology for
  radiofrequency thermal ablation of liver
  tu-mors.Semin Laparosc Surg 1997496101.
• Emad M. Boctor, Gregory Fischer, Michael A.
  Choti, Gabor Fichtinger, Russell H. Taylor A
  Dual-Armed Robotic System for Intraoperative
  Ultrasound Guided Hepatic Ablative TherapyA
  Prospective Study. Accepted ICRA 2004.
• Graham SJ, Stanisz GJ, Kecojevic A, Bronskill MJ,
  Henkelman RM Analysis of changes in MRI
  properties of tissues after heat treatment. Magn
  Reson Med 199942(6)1061-71.
• Wu T, Felmlee JP, Greenleaf JF, Riederer SJ,
  Ehman RL Assessment of thermal tissue ablation
  with MR elastography. Magn Reson Med 2001
  Jan45(1)80-7.
• Alexander F. Kolen, Jeffrey C. Bamber, Eltayeb E.
  Ahmed Analysis of cardiovascular-induced liver
  motion for application to elasticity imaging of
  the liver in vivo. MIUA 2002.
• Ophir J., Céspedes E.I., Ponnekanti H., Yazdi Y.,
  Li X Elastography a quantitative method for
  imaging the elasticity of biological tissues.
  Ultrasonic Imag.,13111134, 1991
• Lubinski M.A., Emelianov S.Y., ODonnell M
  Speckle tracking methods for ultrasonic
  elasticity imaging using short time correlation.
  IEEE Trans. Ultrason., Ferroelect., Freq.,
  Contr., 4682-96, 1999.
• Pesavento A., Perrey C., Krueger M., Ermert H A
  Time Efficient and Accurate Strain Es-timation
  Concept for Ultrasonic Elastography Using
  Iterative Phase Zero Estimation. IEEE Trans.
  Ultrason., Ferroelect., Freq., Contr.,
  46(5)1057-1067, 1999.
• Alam S.K., Ophir J Reduction of signal
  decorrelation from mechanical compression of
  tissues by temporal stretching applications to
  elastography. US Med. Biol., 2395105, 1997.
• Alam S.K., Ophir J., Konofagou E.E An adaptive
  strain estimator for elastography. IEEE Trans.
  Ultrason. Ferroelec. Freq. Cont., 45461472,
  1998.
• Fahey BJ, Nightingale KR, Wolf P and Trahey GE
  ARFI Imaging of Thermal Lesions in Ex Vivo and In
  Vivo Soft Tissues. Proceedings of the 2003 IEEE
  US Symposium. 2003.
• Wen-Chun Yeh, Pai-Chi Li, Yung-Ming Jeng, Hey-Chi
  Hsu, Po-Ling Kuo, Meng-Lin Li, Pei-Ming Yang and
  Po Huang Lee Elastic modulus measurements of
  human liver and correlation with pathology. US in
  Med. Biol. 28(4), 467-474, 2002.
• M.M. Doyley, J.C. Bamber, P.M. Meany, F.G.
  Fuechsel, N.L. Bush, and N.R. Miller
  Re-constructing Youngs modulus distributions
  within soft tissues from freehand elastograms.
  Acoustical Imaging, volume 25, pp 469-476 2000.
• Taylor RH, Funda J, Eldridge B, Gruben K, LaRose
  D, Gomory S, Talamini M, Kavoussi LA, and
  Anderson JH A Telerobotic Assistant for
  Laparoscopic Surgery. IEEE EMBS Magazine Special
  Issue on Robotics in Surgery. 1995. pp. 279-291
• Moddemeijer, R., Delay-Estimation with
  Application to Electroencephalograms in Epi-lepsy
  (Phd-thesis), Universiteit Twente, 1989, Enschede
  (NL), ISBN 90-9002668-1
• Kallel, F., Stafford, R.J., Price, R. E.,
  Righetti, R., Ophir, J. and Hazle, J.D. The
  Feasibility of Elastographic Visualization of
  HIFU-Induced Thermal Lesions in Soft-Tissue.
  Ultras. Med. and Biol., Vol 25(4), pp.641-647,
  1999.