University of Wisconsin–Madison

Monitoring of Tumor Ablation Using Ultrasonic Imaging Methods

January 2012 to January 2014

Radiofrequency (RF) ablation (increase in temperature causing cell death) and Cryoablation (Cryo) of liver tumors is becoming an accepted and widely used method for increasing life expectancy in patients with primary or metastatic cancer of the liver. This technique is significantly less invasive than conventional surgery, and patients can often go home the same day of the procedure. The main limitation of RF or Cryo is that a large number (30-50%) of tumors treated have incomplete cell death with residual tumor left behind. This residual disease is very hard to treat. Therefore, any method which makes the original treatment more effective would represent a major advance. The objective of our research is to develop sensitive techniques focused on noninvasive in-vivo ultrasound based strain and temperature imaging that will allow in-vivo visualization of thermal lesions generated by RF ablation. This research will develop and evaluate ultrasound-based in-vivo strain and temperature imaging for seeing treated regions during and after thermal therapy. It will also assess whether strain and temperature images provide useful clinical information on the extent of the treated region. Currently, local recurrence rates after RF ablative therapy are as high as 55%, and this is believed to be due in part to the inability to accurately visualize the zone of dead tissue (treated region), leading to incomplete cell death in the tumor, generally areas near the tumor edges. Conventional ultrasound imaging during RF ablation generally is not sufficiently accurate in predicting the treated region. However, strain imaging or elastography enables seeing this zone of treatment by imaging the stiffness of the treated tissue. Thus, the significance of the work to be done under this protocol is that it may lead to a new and very effective ultrasound-based method for monitoring minimally invasive cancer treatments.

This project led by: Thomas Varghese, PhD