Highlights
- •We have developed a new method to track tumor position using fluoroscopic images.
- •Tracking accuracy averaged over seven liver cases was 1.30 ± 0.54 mm.
- •Computation time was < 33 ms for a pair of fluoroscopic images.
Abstract
Purpose
We have developed a new method to track tumor position using fluoroscopic images,
and evaluated it using hepatocellular carcinoma case data.
Methods
Our method consists of a training stage and a tracking stage. In the training stage,
the model data for the positional relationship between the diaphragm and the tumor
are calculated using four-dimensional computed tomography (4DCT) data. The diaphragm
is detected along a straight line, which was chosen to avoid 4DCT artifact. In the
tracking stage, the tumor position on the fluoroscopic images is calculated by applying
the model to the diaphragm. Using data from seven liver cases, we evaluated four metrics:
diaphragm edge detection error, modeling error, patient setup error, and tumor tracking
error. We measured tumor tracking error for the 15 fluoroscopic sequences from the
cases and recorded the computation time.
Results
The mean positional error in diaphragm tracking was 0.57 ± 0.62 mm. The mean positional
error in tumor tracking in three-dimensional (3D) space was 0.63 ± 0.30 mm by modeling
error, and 0.81–2.37 mm with 1–2 mm setup error. The mean positional error in tumor
tracking in the fluoroscopy sequences was 1.30 ± 0.54 mm and the mean computation
time was 69.0 ± 4.6 ms and 23.2 ± 1.3 ms per frame for the training and tracking stages,
respectively.
Conclusions
Our markerless tracking method successfully estimated tumor positions. We believe
our results will be useful in increasing treatment accuracy for liver cases.
Keywords
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Article info
Publication history
Published online: February 08, 2020
Accepted:
February 1,
2020
Received in revised form:
December 27,
2019
Received:
May 17,
2019
Identification
Copyright
© 2020 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
