An accurate prediction of negative lymph node metastasis with consideration of glucose metabolism in early-stage non-small cell lung cancer.

OBJECTIVE: We aimed to identify risk factors in lymph node metastasis in early-stage non-small cell lung cancer (NSCLC) and predict lymph node metastasis. METHODS: A total of 416 patients with clinical stage IA2-3 NSCLC who underwent lobectomy and lymph node dissection between July 2016 and December 2020 at National Cancer Center Hospital East were included. Multivariable logistic regression was performed to develop a model for predicting lymph node metastasis. Leave-one-out cross-validation was performed to evaluate the developing prediction model, and sensitivity, specificity, and concordance statistics were calculated to evaluate its diagnostic performance. RESULTS: The formula for calculating the probability of pathological lymph node metastasis included SUVmax of the primary tumor and serum CEA level. The concordance statistics was 0.7452. When the cutoff value associated with the risk of incorrectly predicting pathological lymph node metastasis was 7.2%, the diagnostic sensitivity and specificity for predicting metastasis were 96.4% and 38.6%, respectively. CONCLUSIONS: We created a prediction model for lymph node metastasis in NSCLC by combining the SUVmax of the primary tumor and serum CEA levels, which showed a particularly strong association. This model is clinically useful as it successfully predicts negative lymph node metastasis in patients with clinical stage IA2-3 NSCLC.

Optimization of injection dose in 18F-FDG PET/CT based on the 2020 national diagnostic reference levels for nuclear medicine in Japan.

OBJECTIVE: Recently, the national diagnostic reference levels (DRLs) in Japan were revised as the DRLs 2020, wherein the body weight-based injection dose optimization in positron emission tomography/computed tomography using 18F-fluoro-2-deoxy-D-glucose (18F-FDG PET/CT) was first proposed. We retrospectively investigated the usefulness of this optimization method in improving image quality and reducing radiation dose. METHODS: A total of 1,231 patients were enrolled in this study. A fixed injection dose of 240 MBq was administered to 624 patients, and a dose adjusted to 3.7 MBq/kg body weight was given to 607 patients. The patients with body weight-based injection doses were further divided according to body weight: group 1 (≤ 49 kg), group 2 (50-59 kg), group 3 (60-69 kg), and group 4 (≥ 70 kg). The effective radiation dose of FDG PET was calculated using the conversion factor of 0.019 mSv/MBq, per the International Commission on Radiological Protection publication 106. Image quality was assessed using noise equivalent count density (NECdensity), which was calculated by excluding the counts of the brain and bladder. The usefulness of the injection dose optimization in terms of radiation dose and image quality was analyzed. RESULTS: The body weight-based injection dose optimization significantly decreased the effective dose by 11%, from 4.54 ± 0.1 mSv to 4.05 ± 0.8 mSv (p < 0.001). Image quality evaluated by NECdensity was also significantly improved by 10%, from 0.39 ± 0.1 to 0.43 ± 0.2 (p < 0.001). In no case did NECdensity deteriorate when the effective dose was decreased. In group 1, the dose decreased by 32%, while there was no significant deterioration in NECdensity (p = 0.054). In group 2, the dose decreased by 17%, and the NECdensity increased significantly (p < 0.01). In group 3, the dose decreased by 3%, and the NECdensity increased significantly (p < 0.01). In group 4, the dose increased by 14%, but there was no significant change in the NECdensity (p = 0.766). CONCLUSION: Body weight-based FDG injection dose optimization contributed to not only the reduction of effective dose but also the improvement of image quality in patients weighing between 50 and 69 kg.