Abstract
Accurate tracking and modeling of internal and external respiratory motion in the thoracic and abdominal regions of a human body is a highly discussed topic in external beam radiotherapy treatment. Errors in target/normal tissue delineation and dose calculation and the increment of the healthy tissues being exposed to high radiation doses are some of the unsolicited problems caused due to inaccurate tracking of the respiratory motion. Many related works have been introduced for respiratory motion modeling, but a majority of them highly depend on radiography/fluoroscopy imaging, wearable markers or surgical node implanting techniques. We, in this article, propose a new respiratory motion tracking approach by exploiting the advantages of an RGB-D camera. First, we create a patient-specific respiratory motion model using principal component analysis (PCA) removing the spatial and temporal noise of the input depth data. Then, this model is utilized for real-time external respiratory motion measurement with high accuracy. Additionally, we introduce a marker-based depth frame registration technique to limit the measuring area into an anatomically consistent region that helps to handle the patient movements during the treatment. We achieved a 0.97 correlation comparing to a spirometer and 0.53 mm average error considering a laser line scanning result as the ground truth. As future work, we will use this accurate measurement of external respiratory motion to generate a correlated motion model that describes the movements of internal tumors.
Highlights
Radiotherapy is one of the highly-discussed topics in the modern medical field
We investigate the feasibility of using a commercial RGB-D camera as a non-contact, non-invasive and whole-field respiratory motion-measuring device, which will enhance the patient comfort
We compared our method with bilateral filtering and conducted isovolume maneuver to show the advantages of the proposed method over existing ones
Summary
Radiotherapy is one of the highly-discussed topics in the modern medical field. It has been widely used in cancer treatments to remove tumors without causing any damages to the neighboring healthy tissues. Inaccurate system setups, anatomical motion and deformation and tissue delineation errors lead to inconsistencies in radiotherapy approaches. Respiratory-based anatomical motion and deformation largely cause errors in both radiotherapy planning and delivery processes in thoracic and abdominal regions [1,2]. Inaccurate respiratory motion estimations directly effect tissue delineation errors, dose miss-calculations, exposure of healthy tissues to high doses and erroneous dose coverage for the clinical target volume [7,8,9,10,11]
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