Person:

Hata, Nobuhiko

Our purpose was to develop temperature sensitive MR sequences and image-processing techniques to asses their potential of monitoring interstitial laser therapy (ILT) in brain tumors (n = 3) and liver tumors (n = 7). ILT lasted 2 to 26 minutes, while images from T1-weighted Fast-Spin-Echo (FSE)- or Spoiled Gradient-Recalled (SPGR) sequences were acquired within 5 - 13 seconds.

Pixel subtraction and visualization of T1-weighted images or optical flow computation was done within less than 110 msec. Alternating, phase-mapping of real- and imaginary components of SPGR sequences was performed within 220 msec.

Pixel subtraction of T1-weighted images identified thermal changes in liver and brain tumors but could not evaluate the temperature values as chemical-shift based imaging, which was however, more affected by susceptibility effects and motion. Optical flow computation displayed the predicted course of thermal changes and revealed that the rate of heat deposition can be anisotropic, which may be related to heterogeneous tumor structure and/or vascularization.

Purpose To develop and evaluate an approach to estimate the respiratory-induced motion of lesions in the chest and abdomen. Materials and methods The proposed approach uses the motion of an initial reference needle inserted into a moving organ to estimate the lesion (target) displacement that is caused by respiration. The needles position is measured using an inertial measurement unit (IMU) sensor externally attached to the hub of an initially placed reference needle. Data obtained from the IMU sensor and the target motion are used to train a learning-based approach to estimate the position of the moving target. An experimental platform was designed to mimic respiratory motion of the liver. Liver motion profiles of human subjects provided inputs to the experimental platform. Variables including the insertion angle, target depth, target motion velocity and target proximity to the reference needle were evaluated by measuring the error of the estimated target position and processing time. Results: The mean error of estimation of the target position ranged between 0.86 and 1.29 mm. The processing maximum training and testing time was 5 ms which is suitable for real-time target motion estimation using the needle position sensor. Conclusion: The external motion of an initially placed reference needle inserted into a moving organ can be used as a surrogate, measurable and accessible signal to estimate in real-time the position of a moving target caused by respiration; this technique could then be used to guide the placement of subsequently inserted needles directly into the target.