Evaluation Methodology for Respiratory Signal Extraction from Clinical Cone-Beam CT (CBCT) using Data-Driven Methods

Authors

  • Adam Tan Mohd Amin Universiti Kebangsaan Malaysia
  • Siti Salasiah Mokri Universiti Kebangsaan Malaysia
  • Rozilawati Ahmad Universiti Kebangsaan Malaysia
  • Fuad Ismail Universiti Kebangsaan Malaysia Medical Centre
  • Ashrani Aizzuddin Abd Rahni Universiti Kebangsaan Malaysia

Keywords:

Cone-beam CT, image-guided radiotherapy treatment, data-driven methods, respiratory motion, internal motion

Abstract

The absence of a ground truth for internal motion in clinical studies has always been a challenge to evaluate developed methods to extract respiratory motion especially during a 60-second cone-beam CT (CBCT) scan in Image-Guided Radiotherapy Treatment (IGRT). The unavailability of a gold standard has led this study to present a methodology to manually track respiratory motion on a clinically acquired CBCT projection data set over a 360° view angle. The tracked signal is then used as a reference to assess the performance of four data-driven methods in respiratory motion extraction, namely: the Amsterdam Shroud (AS), Local Principal Component Analysis (LPCA), Intensity Analysis (IA), and Fourier Transform (FT)-based methods that do not require additional equipment nor protocol to the existing treatment delivery. The assessment using this reference signal includes both quantitative and qualitative analysis. It is found out quantitatively that all four methods managed to extract respiratory signals that are highly correlated with the reference signal, with the LPCA method displaying the highest correlation coefficient value at 0.9108. Furthermore, the normalized root-mean-squared amplitude error of detected peaks and troughs within the signal from the LPCA method is also lowest at 1.6529 % compared to the other methods. This result is further supported by qualitative analysis via visual inspection of each extracted signal plotted with the reference signal on the same axes.

Downloads

Download data is not yet available.

Downloads

Published

19-05-2021

How to Cite

Mohd Amin, A. T. ., Mokri, S. S. ., Ahmad, R. ., Ismail, F. ., & Abd Rahni, A. A. . (2021). Evaluation Methodology for Respiratory Signal Extraction from Clinical Cone-Beam CT (CBCT) using Data-Driven Methods. International Journal of Integrated Engineering, 13(5), 1–8. Retrieved from https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/8589