Image similarity evaluation of the bulk-density-assigned synthetic CT derived from MRI of intracranial regions for radiation treatment

• Published in: PloS one Vol. 12; no. 9; p. e0185082
• Main Authors: Kim, Shin-Wook, Shin, Hun-Joo, Hwang, Jin-Ho, Shin, Jin-Sol, Park, Sung-Kwang, Kim, Jin-Young, Kim, Ki-Jun, Kay, Chul-Seung, Kang, Young-Nam
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 19-09-2017; Public Library of Science (PLoS)
• Subjects: Accuracy; Algorithms; Anatomy; Biology and Life Sciences; Biomedical engineering; Bone and Bones - anatomy & histology; Bone and Bones - diagnostic imaging; Brain; Brain - anatomy & histology; Brain - diagnostic imaging; Brain cancer; Brain Neoplasms - diagnostic imaging; Brain Neoplasms - radiotherapy; Brain stem; Bulk density; Cancer; Cancer therapies; Coefficients; Computed tomography; Density; Dosimetry; Drug dosages; Evaluation; Eye lens; Humans; Image processing; Image segmentation; Magnetic resonance; Magnetic resonance imaging; Magnetic Resonance Imaging - standards; Mathematical analysis; Medical imaging; Medicine; Medicine and Health Sciences; Methods; Motivation; Neuroimaging; NMR; Nuclear magnetic resonance; Oncology; Patients; Physical Sciences; Prostate cancer; Radiation; Radiation therapy; Radiotherapy Planning, Computer-Assisted - standards; Registration; Research and Analysis Methods; Researchers; Retrospective Studies; Segmentation; Similarity; Studies; Tomography; Tomography, X-Ray Computed; Tumors; Ventricle; Ventricles (cerebral)
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0185082

Various methods for radiation-dose calculation have been investigated over previous decades, focusing on the use of magnetic resonance imaging (MRI) only. The bulk-density-assignment method based on manual segmentation has exhibited promising results compared to dose-calculation with computed tomography (CT). However, this method cannot be easily implemented in clinical practice due to its time-consuming nature. Therefore, we investigated an automatic anatomy segmentation method with the intention of providing the proper methodology to evaluate synthetic CT images for a radiation-dose calculation based on MR images.
CT images of 20 brain cancer patients were selected, and their MR images including T1-weighted, T2-weighted, and PETRA were retrospectively collected. Eight anatomies of the patients, such as the body, air, eyeball, lens, cavity, ventricle, brainstem, and bone, were segmented for bulk-density-assigned CT image (BCT) generation. In addition, water-equivalent CT images (WCT) with only two anatomies-body and air-were generated for a comparison with BCT. Histogram comparison and gamma analysis were performed by comparison with the original CT images, after the evaluation of automatic segmentation performance with the dice similarity coefficient (DSC), false negative dice (FND) coefficient, and false positive dice (FPD) coefficient.
The highest DSC value was 99.34 for air segmentation, and the lowest DSC value was 73.50 for bone segmentation. For lens segmentation, relatively high FND and FPD values were measured. The cavity and bone were measured as over-segmented anatomies having higher FPD values than FND. The measured histogram comparison results of BCT were better than those of WCT in all cases. In gamma analysis, the averaged improvement of BCT compared to WCT was measured. All the measured results of BCT were better than those of WCT. Therefore, the results of this study show that the introduced methods, such as histogram comparison and gamma analysis, are valid for the evaluation of the synthetic CT generation from MR images.
The image similarity results showed that BCT has superior results compared to WCT for all measurements performed in this study. Consequently, more accurate radiation treatment for the intracranial regions can be expected when the proper image similarity evaluation introduced in this study is performed.