Du Xin-Hui, Wei Hua, Li Po, Yao Wei-Tao
Department of Orthopedics, Henan Cancer Hospital/Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China.
Department of Anesthesiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Front Oncol. 2020 Aug 4;10:1209. doi: 10.3389/fonc.2020.01209. eCollection 2020.
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.
由于解剖结构的复杂性和骨形状的不规则性，骨盆骨肿瘤手术极具挑战性。CT和MRI在临床上用于肿瘤评估，各有优缺点。将CT和MRI图像数据相结合可利用两种图像的优点，为术前评估提供更好的模型。我们利用人工智能（AI）辅助的CT/MRI图像融合技术，构建了用于术前肿瘤边缘评估的个性化三维模型。一名患有骨盆骨肉瘤的年轻女性患者，我们用新型图像融合三维模型对其进行评估，并与仅基于CT图像的三维模型进行比较。融合图像模型显示了更详细的解剖信息，并发现了多个先前被忽视的静脉内栓子。栓子的发现意味着预后极差，不鼓励在肿瘤切除后进行任何复杂重建的尝试。基于该骨盆骨肉瘤的经验我们认为，我们的图像融合模型对骨肿瘤具有很高的信息量。尽管需要大量临床病例进行进一步验证，但我们认为我们的模型有潜力在骨肿瘤的术前评估中使临床受益。
