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Artificial Intelligence (AI) Assisted CT/MRI Image Fusion Technique in Preoperative Evaluation of a Pelvic Bone Osteosarcoma
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 th...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7417346/ https://www.ncbi.nlm.nih.gov/pubmed/32850355 http://dx.doi.org/10.3389/fonc.2020.01209 |
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author | Du, Xin-hui Wei, Hua Li, Po Yao, Wei-Tao |
author_facet | Du, Xin-hui Wei, Hua Li, Po Yao, Wei-Tao |
author_sort | Du, Xin-hui |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7417346 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74173462020-08-25 Artificial Intelligence (AI) Assisted CT/MRI Image Fusion Technique in Preoperative Evaluation of a Pelvic Bone Osteosarcoma Du, Xin-hui Wei, Hua Li, Po Yao, Wei-Tao Front Oncol Oncology 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. Frontiers Media S.A. 2020-08-04 /pmc/articles/PMC7417346/ /pubmed/32850355 http://dx.doi.org/10.3389/fonc.2020.01209 Text en Copyright © 2020 Du, Wei, Li and Yao. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Du, Xin-hui Wei, Hua Li, Po Yao, Wei-Tao Artificial Intelligence (AI) Assisted CT/MRI Image Fusion Technique in Preoperative Evaluation of a Pelvic Bone Osteosarcoma |
title | Artificial Intelligence (AI) Assisted CT/MRI Image Fusion Technique in Preoperative Evaluation of a Pelvic Bone Osteosarcoma |
title_full | Artificial Intelligence (AI) Assisted CT/MRI Image Fusion Technique in Preoperative Evaluation of a Pelvic Bone Osteosarcoma |
title_fullStr | Artificial Intelligence (AI) Assisted CT/MRI Image Fusion Technique in Preoperative Evaluation of a Pelvic Bone Osteosarcoma |
title_full_unstemmed | Artificial Intelligence (AI) Assisted CT/MRI Image Fusion Technique in Preoperative Evaluation of a Pelvic Bone Osteosarcoma |
title_short | Artificial Intelligence (AI) Assisted CT/MRI Image Fusion Technique in Preoperative Evaluation of a Pelvic Bone Osteosarcoma |
title_sort | artificial intelligence (ai) assisted ct/mri image fusion technique in preoperative evaluation of a pelvic bone osteosarcoma |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7417346/ https://www.ncbi.nlm.nih.gov/pubmed/32850355 http://dx.doi.org/10.3389/fonc.2020.01209 |
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