Risk analysis in peripheral clinical T1 non-small cell lung cancer correlations between tumor-to-blood standardized uptake ratio on 18F-FDG PET-CT and primary tumor pathological invasiveness: a real-world observational study

Preoperative nomogram for predicting spread through air spaces in clinical-stage IA non-small cell lung cancer using 18F-fluorodeoxyglucose positron emission tomography/computed tomography

PURPOSE

This study aims to assess the predictive value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) radiological features and the maximum standardized uptake value (SUVmax) in determining the presence of spread through air spaces (STAS) in clinical-stage IA non-small cell lung cancer (NSCLC).

METHODS

A retrospective analysis was conducted on 180 cases of NSCLC with postoperative pathological assessment of STAS status, spanning from September 2019 to September 2023. Of these, 116 cases from hospital one comprised the training set, while 64 cases from hospital two formed the testing set. The clinical information, tumor SUVmax, and 13 related CT features were analyzed. Subgroup analysis was carried out based on tumor density type. In the training set, univariable and multivariable logistic regression analyses were employed to identify the most significant variables. A multivariable logistic regression model was constructed and the corresponding nomogram was developed to predict STAS in NSCLC, and its diagnostic efficacy was evaluated in the testing set.

RESULTS

SUVmax, consolidation-to-tumor ratio (CTR), and lobulation sign emerged as the best combination of variables for predicting STAS in NSCLC. Among these, SUVmax and CTR were identified as independent predictors for STAS prediction. The constructed prediction model demonstrated area under the curve (AUC) values of 0.796 and 0.821 in the training and testing sets, respectively. Subgroup analysis revealed a 2.69 times higher STAS-positive rate in solid nodules compared to part-solid nodules. SUVmax was an independent predictor for predicting STAS in solid nodular NSCLC, while CTR and an emphysema background were independent predictors for STAS in part-solid nodular NSCLC.

CONCLUSION

Our nomogram based on preoperative 18F-FDG PET/CT radiological features and SUVmax effectively predicts STAS status in clinical-stage IA NSCLC. Furthermore, our study highlights that metabolic parameters and CT variables associated with STAS differ between solid and part-solid nodular NSCLC.

The correlation between tumor radiological features and spread through air spaces in peripheral stage IA lung adenocarcinoma: a propensity score-matched analysis

BACKGROUND

The consolidation tumor ratio (CTR) is a predictor of invasiveness in peripheral T1N0M0 lung adenocarcinoma. However, its association with spread through air spaces (STAS) remains largely unexplored. We aimed to explore the correlation between the CTR of primary tumors and STAS in peripheral T1N0M0 lung adenocarcinoma.

METHODS

We collected data from patients who underwent surgery for malignant lung neoplasms between January and November 2022. Univariate and multivariate analyses following propensity-score matching with sex, age, BMI, were performed to identify the independent risk factors for STAS. The incidence of STAS was compared based on pulmonary nodule type. A smooth fitting curve between CTR and STAS was produced by the generalized additive model (GAM) and a multiple regression model was established using CTR and STAS to determine the dose-response relationship and calculate the odds ratio (OR) and 95% confidence interval (CI).

RESULTS

17 (14.5%) were diagnosed with STAS. The univariate analysis demonstrated that the history of the diabetes, size of solid components, spiculation, pleural indentation, pulmonary nodule type, consolidation/tumor ratio of the primary tumor were statistically significant between the STAS-positive and STAS-negative groups following propensity-score matching(p = 0.047, 0.049, 0.030, 0.006, 0.026, and < 0.001, respectively), and multivariate analysis showed that the pleural indentation was independent risk factors for STAS (with p-value and 95% CI of 0.043, (8.543-68.222)). Moreover, the incidence of STAS in the partially solid nodule was significantly different from that in the solid nodule and ground-glass nodule (Pearson Chi-Square = 7.49, p = 0.024). Finally, the smooth fitting curve showed that CTR tended to be linearly associated with STAS by GAM, and the multivariate regression model based on CTR showed an OR value of 1.24 and a p-value of 0.015.

CONCLUSIONS

In peripheral stage IA lung adenocarcinoma, the risk of STAS was increased with the solid component of the primary tumor. The pleural indentation of the primary tumor could be used as a predictor in evaluating the risk of the STAS.

Risk analysis of visceral pleural invasion in malignant solitary pulmonary nodules that appear touching the pleural surface

BACKGROUND

The preoperative determination of visceral pleural invasion (VPI) in patients with malignant solitary pulmonary nodules (SPNs) is essential for determining the surgical range and selecting adjuvant chemotherapy.

OBJECTIVES

This study aimed to systematically investigate risk factors of VPI in patients with SPN and construct a preoperative predictive model for such patients.

DESIGN

This is a retrospective study. The clinical, radiological, and pathological characteristics of study subjects were reviewed, and the groups with and without VPI were compared.

METHODS

Multivariate logistic analysis was utilized to identify independent risk factors for VPI. Moreover, a predictive nomogram was constructed to assess the likelihood of VPI occurrence.

RESULTS

Of the 364 enrolled cases, SPNs adjacent to the pleura with VPI were found in 110 (30.2%) patients. By incorporating four preoperative variables, including tumor diameter (>2 cm), maximum computed tomography value (>200 Hu), air bronchogram sign, and age, a preoperative predictive nomogram was constructed. The nomogram demonstrated good discriminative ability, with a C-index of 0.736 (95% CI (0.662-0.790)). Furthermore, our data indicated that the air bronchogram sign (odd ratio (OR) 1.81, 95% CI (0.99-3.89), p = 0.048), a maximum diameter >2 cm (OR 24.48, 95% CI (8.43-71.07), p < 0.001), pathological type (OR 5.01, 95% CI (2.61-9.64), p < 0.001), and Ki-67 >30% (OR 2.95, 95% CI (1.40-6.21), p = 0.004) were overall independent risk factors for VPI.

CONCLUSION

This study investigated the risk factors for VPI in malignant SPNs touching the pleural surface. Additionally, a nomogram was developed to predict the likelihood of VPI in such patients, facilitating informed decision-making regarding surgical approaches and treatment protocols.

Predictive value of metabolic parameters derived from preoperative 18F-FDG positron emission tomography/computed tomography for brain metastases in patients with surgically resected non-small cell lung cancer

Background

Brain metastases (BMs) are common complications in patients with non-small cell lung cancer (NSCLC). The purpose of this study was to investigate whether the metabolic parameters derived from preoperative 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) can predict BM development in patients with surgically resected NSCLC.

Methods

We retrospectively reviewed 128 consecutive patients with stage I-IIIA NSCLC who underwent 18F-FDG PET/CT before curative surgery at The First Affiliated Hospital of Jinan University between November 2012 and October 2021. By drawing a volume of interest (VOI), the maximum standardized uptake values (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary tumor as well as the mean SUV (SUVmean) of the liver and arterial blood were measured. The tumor-to-liver SUV ratio (TLR) and tumor-to-blood SUV ratio (TBR) were also calculated. Receiver operating characteristic curve analysis was used to determine the best cut-off values for positron emission tomography (PET) parameters to predict BM-free survival, and Cox proportional hazards regression analysis was used to assess the predictive value of clinical variables and PET parameters.

Results

The median follow-up duration for survival patients was 23.4 months, and 15 patients (11.7%) experienced BM as the initial relapse site. The cumulative rates of BM over the course of 1, 2, and 5 years were 4.5%, 10.5%, and 17.5%, respectively. The optimal cut-off values for the prediction of BM-free survival were 7.7, 4.9, and 4.5 for SUVmax, TLR, and TBR, and 5.5 mL and 16.1 for MTV and TLG, respectively. In the Cox proportional hazards model, the risk of BM was significantly associated with TLR [hazard ratio (HR) =10.712; 95% confidence interval (CI): 2.958-38.801; P<0.001] and MTV (HR =3.150; 95% CI: 0.964-10.293; P=0.020) after adjusting for tumor stage, clinicopathological factors, and other PET parameters.

Conclusions

Preoperative TLR and MTV of the primary tumor may be helpful in predicting BM development in patients with surgically resected NSCLC. Tumor metabolic parameters may potentially be used to stratify the risk of BM and determine individualized surveillance strategies.

A preliminary study on the effect of renal function on the metabolism of 18F-FDG in the human cerebellum

Background

The cerebellum is less affected by normal aging or neurodegenerative diseases, the aim of this paper is to investigate the effect of renal function status on uptake of 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) in human cerebellum based on independent creatinine (CRE) or blood urea nitrogen (BUN) levels.

Methods

A total of 253 patients who underwent 18F-FDG PET/CT scans were included. The patients were divided into groups according to renal function status: 201 patients with normal renal function, 16 patients with increase CRE, 36 patients with decrease CRE, and 31 patients with abnormal BUN. The maximum standardized uptake values were obtained in regions of interest (ROIs) for multiple tissue types (right cerebellum, right lobe of liver, right lung, bone marrow and psoas muscle at the level of the fourth lumbar vertebra). Moreover, the selected normal CRE groups were pair-matched with CRE decrease group with respect to age, sex, body mass index and glucose, respectively.

Results

Among 253 patients who met the inclusion/exclusion criteria, the final analysis included 967 ROIs (244 cerebellum, 191 lungs, 230 muscles, 145 bone marrow, and 157 liver) from 18F-FDG PET/CT scans. Among patients grouped by CRE or BUN levels, the uptake of 18F-FDG by cerebellum was significantly decreased in patients with CRE decrease level (P=0.001). There were no statistically significant differences between the other groups. Matched-pair analysis indicated there were no significant changes in outcomes between the CRE decrease group and the age-, sex-, BMI-, and glucose-matched controls compared to pre-matching.

Conclusions

In patients with normal renal function and reduced CRE concentration, decrease cerebellar glucose metabolism was observed; however, no abnormal uptake of 18F-FDG was found in the cerebellum and other normal tissues of patients with impaired renal function. Consequently, in the study of cerebellar 18F-FDG metabolism, it may be necessary to consider the influence of blood CRE level.

Multivariate analysis based on the maximum standard unit value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography and computed tomography features for preoperative predicting of visceral pleural invasion in patients with subpleural clinical stage IA peripheral lung adenocarcinoma

PURPOSE

Preoperative prediction of visceral pleural invasion (VPI) is important because it enables thoracic surgeons to choose appropriate surgical plans. This study aimed to develop and validate a multivariate logistic regression model incorporating the maximum standardized uptake value (SUVmax) and valuable computed tomography (CT) signs for the non-invasive prediction of VPI status in subpleural clinical stage IA lung adenocarcinoma patients before surgery.

METHODS

A total of 140 patients with subpleural clinical stage IA peripheral lung adenocarcinoma were recruited and divided into a training set (n = 98) and a validation set (n = 42), according to the positron emission tomography/CT examination temporal sequence, with a 7:3 ratio. Next, VPI-positive and VPI-negative groups were formed based on the pathological results. In the training set, the clinical information, the SUVmax, the relationship between the tumor and the pleura, and the CT features were analyzed using univariate analysis. The variables with significant differences were included in the multivariate analysis to construct a prediction model. A nomogram based on multivariate analysis was developed, and its predictive performance was verified in the validation set.

RESULTS

The size of the solid component, the consolidation-to-tumor ratio, the solid component pleural contact length, the SUVmax, the density type, the pleural indentation, the spiculation, and the vascular convergence sign demonstrated significant differences between VPI-positive (n = 40) and VPI-negative (n = 58) cases on univariate analysis in the training set. A multivariate logistic regression model incorporated the SUVmax [odds ratio (OR): 1.753, P = 0.002], the solid component pleural contact length (OR: 1.101, P = 0.034), the pleural indentation (OR: 5.075, P = 0.041), and the vascular convergence sign (OR: 13.324, P = 0.025) as the best combination of predictors, which were all independent risk factors for VPI in the training group. The nomogram indicated promising discrimination, with an area under the curve value of 0.892 [95% confidence interval (CI), 0.813-0.946] in the training set and 0.885 (95% CI, 0.748-0.962) in the validation set. The calibration curve demonstrated that its predicted probabilities were in acceptable agreement with the actual probability. The decision curve analysis illustrated that the current nomogram would add more net benefit.

CONCLUSION

The nomogram integrating the SUVmax and the CT features could non-invasively predict VPI status before surgery in subpleural clinical stage IA lung adenocarcinoma patients.

A predictive nomogram for lymph node metastasis in part-solid invasive lung adenocarcinoma: A complement to the IASLC novel grading system

Background

The International Association for the Study of Lung Cancer (IASLC) proposed a novel grading system for invasive lung adenocarcinoma, but lymphatic invasion was not evaluated. Meanwhile, the scope of lymph node dissection in part-solid invasive lung adenocarcinoma (PSILA) is still controversial. Therefore, this study aims to explore preoperative risk factors for lymph node metastasis in PSILA, to provide reference for intraoperative dissection of lymph nodes.

Methods

From 2018 to 2020, clinical data of patients (stage cN0) consecutively diagnosed as PSILA were retrospectively analyzed and classified according to the novel grading system. Logistic regression was conducted to screen the clinicopathological factors of lymph node metastasis in PSILA.

Results

A large cohort of 960 patients with PSILA who underwent lobectomy or sub-lobectomy were enrolled. By logistic regression analyses, solid part size, bronchial cutoff sign, spiculation, and carbohydrate antigen 199 (CA199) were eventually identified as independent risk factors for lymph node metastasis, based on which a nomogram was built to preoperatively predict the risk of lymph node metastasis [area under the receiver operating characteristic curve (AUC)=0.858; concordance index = 0.857; best cutoff, 0.027]. This suggests that intraoperative systematic lymph node dissection is recommended when the predicted risk value exceeds 0.027. Reproducibility of the novel grading system was verified.

Conclusions

The novel IASLC grading system was applicative in real world. The nomogram for preoperative prediction of lymph node metastasis may provide reference for the lymph node dissection strategy during PSILA surgeries.