Radiographic predictors of resectability in thymic carcinoma Journal Article
| Authors: | Hayes, S. A.; Huang, J.; Golia Pernicka, J.; Cunningham, J.; Zheng, J.; Moskowitz, C. S.; Ginsberg, M. S. |
| Article Title: | Radiographic predictors of resectability in thymic carcinoma |
| Abstract: | Background: The aim of this study was to assess preoperative computed tomography characteristics of thymic carcinomas and to investigate which features could predict an incomplete surgical resection. A secondary aim was to correlate preoperative imaging features with Masaoka stage. Methods: In this study, approved by our Institutional Review Board, two readers retrospectively reviewed preoperative computed tomography scans at our tertiary referral oncology center between 1994 and 2014. Imaging features analyzed included tumor morphology, infiltration of surrounding mediastinal fat, loss of surrounding fat plane, degree of contact between tumor and great vessels, and associated pulmonary or pleural abnormality. Surgical and pathologic records were reviewed for completeness of surgical resection and Masaoka stage. Results: Forty-one patients were included, with Masaoka stage I (n = 3), stage II (n = 4), stage III (n = 12), and stage IV (n = 22). Twenty-one patients (51%) had a complete surgical resection. Ten had microscopic residual disease (R1) with involved surgical margins at pathology, and 10 patients had macroscopic residual disease (R2) at surgery. In addition to lesion size, the feature associated with incomplete surgical resection was the degree of tumor contact with adjacent mediastinal vessels on the preoperative computed tomography image (p = 0.038). Many of the more common features associated with incomplete resection were also more likely to be present in patients with late Masaoka stage (III/IV), including infiltration of the mediastinal fat, which was present in all 34 patients with Masaoka stage III/IV compared with 5 patients (71%) with stage I/II (p = 0.03). Conclusions: Preoperative computed tomography imaging features may help to identify patients at risk for an incomplete surgical resection. © 2018 The Society of Thoracic Surgeons |
| Journal Title: | Annals of Thoracic Surgery |
| Volume: | 106 |
| Issue: | 1 |
| ISSN: | 0003-4975 |
| Publisher: | Elsevier Science, Inc. |
| Date Published: | 2018-07-01 |
| Start Page: | 242 |
| End Page: | 248 |
| Language: | English |
| DOI: | 10.1016/j.athoracsur.2018.02.019 |
| PROVIDER: | scopus |
| PUBMED: | 29534953 |
| DOI/URL: | |
| Notes: | Article -- Export Date: 2 July 2018 -- Source: Scopus |
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