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Purpose: To evaluate the frequency of tumor thrombus in the large veins draining primary pelvic osteosarcoma on early cross-sectional imaging studies and its effect on patient survival., Materials and Methods: Our retrospective study included all patients with primary pelvic osteosarcoma treated at our facility between January 2000 and May 2014, who were ≤ 45 years of age, and had adequate imaging studies and clinical follow up. Four radiologists evaluated for tumor in the large draining veins on initial CT, MRI and PET/CTs. A consensus evaluation by the four radiologists together with findings on operative reports, pathology reports or follow-up imaging was used as the reference standard., Results: Thirty-nine patients with primary pelvic osteosarcoma met final inclusion criteria. Tumor thrombus was identified in the large draining veins in 10 of the 22 (45%) patients who underwent tumor resection and 10 of the 17 (59%) who did not. In the 22 patients who underwent tumor resection, tumor thrombus was significantly associated with worse overall survival (p = 0.03)., Conclusions: Tumor thrombus in the large draining veins is identified in a significant proportion of initial imaging studies in patients with pelvic osteosarcoma, and is associated with worse overall survival in patients who undergo tumor resection., (Copyright © 2018 Elsevier B.V. All rights reserved.)

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. [ABSTRACT FROM AUTHOR]