Artificial Intelligence (AI) Assisted CT/MRI Image Fusion Technique in Preoperative Evaluation of a Pelvic Bone Osteosarcoma
| Autor: | Hua Wei, Po Li, Wei-Tao Yao, Xin-hui Du |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Cancer Research Multiple emboli Tumor resection Case Report Bone Osteosarcoma lcsh:RC254-282 image fusion 03 medical and health sciences 0302 clinical medicine Tumor margin medicine Fusion image Image fusion business.industry tumor margin lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens medicine.disease artificial intelligence 030104 developmental biology medicine.anatomical_structure Oncology 030220 oncology & carcinogenesis Irregular bone Osteosarcoma Artificial intelligence irregular bone business pelvic osteosarcoma |
| Zdroj: | Frontiers in Oncology Frontiers in Oncology, Vol 10 (2020) |
| ISSN: | 2234-943X |
| DOI: | 10.3389/fonc.2020.01209 |
| Popis: | Surgeries of pelvic bone tumors are very challenging due to the complexity of anatomical structures and the irregular bone shape. CT and MRI are used in clinic for tumor evaluation, each with its own advantages and shortcomings. Combining the data of both CT and MRI images would take advantage of the merits of both images and provide better model for preoperative evaluation. We utilized an artificial intelligence (AI)-assisted CT/MRI image fusion technique and built a personalized 3-D model for preoperative tumor margin assessment. A young female patient with pelvic osteosarcoma was evaluated with our novel image fusion 3-D model in comparison with the 3-D model based solely on CT images. The fusion image model showed more detailed anatomical information and discovered multiple emboli within veins which were previously neglected. The discovery of emboli implied abysmal prognosis and discouraged any attempts for complex reconstruction after tumor resection. Based on the experience with this pelvic osteosarcoma, we believe that our image fusion model can be very informative with bone tumors. Though further validation with a large number of clinical cases is required, we propose that our model has the potential to benefit the clinic in the preoperative evaluation of bone tumors. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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