Correlating Chest Surface Motion to Motion of the Liver Using ε-SVR – A Porcine Study

Abstract

Abstract. In robotic radiosurgery, the compensation of motion of internal organs is vital. This is currently done in two phases: an external surrogate signal (usually active optical markers placed on the patient's chest) is recorded and subsequently correlated to an internal motion signal obtained using stereoscopic X-ray imaging. This internal signal is sampled very infrequently to minimise the patient's exposure to radiation. We have investigated the correlation of the external signal to the motion of the liver in a porcine study using ε-support vector regression. IR LEDs were placed on the swines' chest. Gold fiducials were placed in the swines' livers and were recorded using a two-plane X-ray system. The results show that a very good correlation model can be built using ε-SVR, in this test clearly outperforming traditional polynomial models by at least 45 and as much as 74 %. Using multiple markers simultaneously can increase the new model's accuracy.

Respiratory motion estimation of the liver with abdominal motion as a surrogate

“…Furthermore, higher order models did not improve the overall fit of the data. The results show that using only one marker would result in a lower accuracy than using two markers, confirming the results of Ernst et al Moreover, the location of the marker affects the estimation accuracy: the closer the marker was to the umbilicus the higher the estimation accuracy. The results also illustrated the accuracy of the estimated SI liver motion; the MAE ranged between 0.8 mm and 1.9 mm for the 3 regression models.…”

“…However, since shrinkage methods might outperform MVR in the case of high dimensional data, using more than two markers will increase the system dimensionality and thus might improve the estimation accuracy in Ridge and Lasso. In fact, multiple markers have been used in previous studies, which indicated that their use will increase the system dimensionality and might capture more complex breathing patterns …”

“…The features could be numeric values of the input signals (the positions of the markers) or polynomial representations of the input signals (quadratic, cubic or higher order) . In the context of RME, the features can be the derivative(s) of the input signals or a signal indicating inhalation/exhalation …”

“…For example, Beddar et al used the Real‐time Position Management System (RPM, Varian Medical Systems, Palo Alto, CA), which had a reflective marker placed on the human's abdomen and tracked using an IR camera, and also showed that the motion is well correlated with the internal motion of the liver . Vedam et al studied the same effect but for internal motion of the diaphragm, and Ernst et al studied the correlation between multiple external IR‐reflective LEDs and the internal liver motion of a swine; both obtained similar correlation results to Beddar et al Henningsson et al and Wasza et al stated that using external markers is advantageous due to its high temporal and spatial resolution, whereas Wilms et al elaborated that by using optical tracking, multiple markers could be advantageous since the dimensionality of the system will increase without adding extra cost to the setup …”

Tracking Lung Tumors in Orthogonal X-Rays

“…It is also possible to apply correspondence models between external markers (chest and abdominal area pointers) and internal fiducials to indirectly estimate tumor position in optical images [3, 4]. Yet, the correlation between external markers and tumor position may be violated easily as a result of complex respiratory biomechanics [5].…”