Abstract
Background: Volumetric parameters based on 3-dimensional reconstruction have recently been introduced for cancer staging. We aimed to improve the ability to diagnose hilar lymph node metastasis in patients with non-small cell lung cancer. Methods: We evaluated 142 patients with non-small cell lung cancer who underwent right upper lobectomy and radical lymph node dissection. Metastatic involvement of right upper lobar lymph nodes was assessed using high-resolution computed tomography (HRCT) and 18F-2-floro-2-deoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT). Results: On receiver operating characteristic (ROC) curve analysis, the area under the curves (AUC) for short axis, maximum of standardized uptake value (SUVmax), total lesion glycolysis (TLG) and modified TLG (mTLG) were 0.79, 0.77, 0.76, and 0.87, respectively. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of mTLG, using the optimal cut off value (2.45), for diagnosis of lobar lymph node metastasis were 71%, 88%, 44%, and 96%, respectively. Hilar asymmetric uptake (HAU) of FDG was larger in true-positive cases than in false-negative cases (P<0.01). Furthermore, the size of metastatic foci in the lymph node was smaller in false-negative cases (P=0.012). Conclusions: Modified TLG is a good parameter to diagnose metastatic right upper lobar lymph nodes. Micrometastasis in the lymph node is difficult to predict using the current diagnostic method. However, more careful evaluation is required in patients with symmetric FDG accumulation at hilar region because hilar lymph nodes respond to various causes such as benign pulmonary diseases.
| Original language | English |
|---|---|
| Pages (from-to) | 6932-6941 |
| Number of pages | 10 |
| Journal | Journal of Thoracic Disease |
| Volume | 10 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - 01-12-2018 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Pulmonary and Respiratory Medicine
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