Med Phys. 2021 Aug 21. doi: 10.1002/mp.15174. Online ahead of print.
ABSTRACT
PURPOSE: The substitution of Computerized Tomography with Magnetic Resonance Imaging has been investigated for external radiotherapy treatment planning. The present study aims to use Pseudo-CT images created by MRI images to calculate the dose distribution for facilitating in the treatment planning process.
METHODS: In this work, following image segmentation with a fuzzy clustering algorithm, an adaptive neuro-fuzzy algorithm was utilized to design the Hounsfield Unit conversion model based on the features vector of MRI images. The model was generated on the set of extracted features from gray level co-occurrence matrices, and the gray level run length matrices for 14 arbitrarily selected patients with brain malady. The performance of the algorithm was investigated on a blind datasets through dose-volume histogram and isodose curve evaluations, using the RayPlan treatment planning system, along with the gamma analysis and statistical indices.
RESULTS: In the proposed approach the mean absolute error within the range of 45.4 HU (Hounsfield unit) was found among the test data. Also, the relative dose difference between the planning target volume region of the CT and the Pseudo-CT was 0.5%, and the best gamma pass rate for 3%/3mm was 97.2%.
CONCLUSION: The proposed method provides a satisfactory average error rate for the generation of Pseudo-CT data in the different parts of the brain region from a collection of MRI series. Also, dosimetric parameters evaluation shows good agreement between reference CT and related Pseudo-CT images. This article is protected by copyright. All rights reserved.
PMID:34418104 | DOI:10.1002/mp.15174
