Microscopic Disease Extension in Three Dimensions for Non-Small-Cell Lung Cancer: Development of a Prediction Model Using Pathology-Validated Positron Emission Tomography and Computed Tomography Features
- Department of Radiation Oncology, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam (Netherlands)
- Department of Pathology, Onze Lieve Vrouwe Gasthuis, Amsterdam (Netherlands)
- Department of Pathology, Maastricht University Medical Centre, Maastricht (Netherlands)
- Department of Radiation Oncology (Maastro Clinic), GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht (Netherlands)
- Department of Thoracic Surgery, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam (Netherlands)
- Department of Nuclear Medicine, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam (Netherlands)
- Department of Pulmonology, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam (Netherlands)
- Department of Radiology, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam (Netherlands)
Purpose: One major uncertainty in radiotherapy planning of non-small-cell lung cancer concerns the definition of the clinical target volume (CTV), meant to cover potential microscopic disease extension (MDE) around the macroscopically visible tumor. The primary aim of this study was to establish pretreatment risk factors for the presence of MDE. The secondary aim was to establish the impact of these factors on the accuracy of positron emission tomography (PET) and computed tomography (CT) to assess the total tumor-bearing region at pathologic examination (CTV{sub path}). Methods and Materials: 34 patients with non-small-cell lung cancer who underwent CT and PET before lobectomy were included. Specimens were examined microscopically for MDE. The gross tumor volume (GTV) on CT and PET (GTV{sub CT} and GTV{sub PET}, respectively) was compared with the GTV and the CTV at pathologic examination, tissue deformations being taken into account. Using multivariate logistic regression, image-based risk factors for the presence of MDE were identified, and a prediction model was developed based on these factors. Results: MDE was found in 17 of 34 patients (50%). The MDE did not exceed 26 mm in 90% of patients. In multivariate analysis, two parameters (mean CT tumor density and GTV{sub CT}) were significantly associated with MDE. The area under the curve of the two-parameter prediction model was 0.86. Thirteen tumors (38%, 95% CI: 24-55%) were identified as low risk for MDE, being potential candidates for reduced-intensity therapy around the GTV. In the low-risk group, the effective diameter of the GTV{sub CT/PET} accurately represented the CTV{sub path}. In the high-risk group, GTV{sub CT/PET} underestimated the CTV{sub path} with, on average, 19.2 and 26.7 mm, respectively. Conclusions: CT features have potential to predict the presence of MDE. Tumors identified as low risk of MDE show lower rates of disease around the GTV than do high-risk tumors. Both CT and PET accurately visualize the CTV{sub path} in low-risk tumors but underestimate it in high-risk tumors.
- OSTI ID:
- 22055977
- Journal Information:
- International Journal of Radiation Oncology, Biology and Physics, Vol. 82, Issue 1; Other Information: Copyright (c) 2012 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA); ISSN 0360-3016
- Country of Publication:
- United States
- Language:
- English
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