A Method for Extracting and Processing PET/CT and Radiation Dose Images of Lung Tumor Target Regions
Abstract
Purpose
The purpose of this research is to develop a method for extracting and processing PET/CT and planning CT (pCT) with dose distribution. This method aims to address the challenge of co-registering data from different imaging modalities into a unified coordinate system, which is essential for subsequent analysis of tumor response to radiotherapy.
Methods
1) Extracting the target volume contouring from the pre-radiotherapy (pre-RT) pCT, as delineated by the radiation oncologist. 2) Matching each pixel point in the tumor volume on the pCT to the corresponding pixel point of dose distribution in the same CT image. 3) Co-registering the coordinate framework between the pCT and the pre-RT whole lung PET/CT. 4) Matching each pixel point in the tumor volume on the pCT with the corresponding pixel point of standardized uptake value (SUV) in the pre-RT whole lung PET/CT image. The process includes transforming the coordinates of the target volume between the pCT or PET/CT device coordinate system and image space. OpenCV is used for contour filling, while trilinear interpolation and nearest neighbor matching methods are utilized to achieve precise data co-registration.
Results
The proposed method successfully extracted the tumor volume from the pre-RT pCT and aligned data from different devices (such as pre-RT whole lung PET/CT image) into a common coordinate system. This alignment provided a foundational dataset for subsequent research on tumor response to radiotherapy.
Conclusion
The developed method effectively addresses the challenge of extracting and processing PET/CT and pCT. By converting data taken from multiple devices to a unified coordinate framework, the method sets the foundation for further studies on the effectiveness of lung tumor radiotherapy. The method's effectiveness has been validated through testing, and it offers a valuable tool for medical image processing in oncology.