Principal component analysis modeling of Head-and-Neck anatomy using daily Cone Beam-CT images
| Autor: | Benjamin Movsas, Christian A Hvid, Hassan Bagher-Ebadian, Stephen L. Brown, Indrin J. Chetty, Chang Liu, Joshua P. Kim, Farzan Siddiqui, Panagiotis Tsiamas |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
education.field_of_study
Head and neck anatomy Principal Component Analysis business.industry Population Cbct image General Medicine Cone-Beam Computed Tomography Volumetric modulated arc therapy Confidence interval 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Head and Neck Neoplasms 030220 oncology & carcinogenesis Principal component analysis Image Processing Computer-Assisted Medicine Humans In patient Nuclear medicine business education Cone beam ct |
| Zdroj: | Medical physics. 45(12) |
| ISSN: | 2473-4209 |
| Popis: | PURPOSE To model Head-and-Neck anatomy from daily Cone Beam-CT (CBCT) images over the course of fractionated radiotherapy using principal component analysis (PCA). METHODS AND MATERIALS Eighteen oropharyngeal Head-and-Neck cancer patients, treated with volumetric modulated arc therapy (VMAT), were included in this retrospective study. Normal organs, including the parotid and submandibular glands, mandible, pharyngeal constrictor muscles (PCMs), and spinal cord were contoured using daily CBCT image datasets. PCA models for each organ were developed for individual patients (IP) and the entire patient cohort/population (PP). The first 10 principal components (PCs) were extracted for all models. Analysis included cumulative and individual PCs for each organ and patient, as well as the aggregate organ/patient population; comparisons were made using the root-mean-square (RMS) of the percentage predicted spatial displacement for each PC. RESULTS Overall, spatial displacement prediction was achieved at the 95% confidence level (CL) for the first three to four PCs for all organs, based on IP models. For PP models, the first four PCs predicted spatial displacement at the 80%-89% CL. Differences in percentage predicted spatial displacement between mean IP models for each organ ranged from 2.8% ± 1.8% (1st PC) to 0.6% ± 0.4% (4th PC). Differences in percentage predicted spatial displacement between IP models vs the mean IP model for each organ based on the 1st PC were |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Plný text