Impact of visceral pleural invasion on the association of extent of lymphadenectomy and survival in stage I non-small cell lung cancer

Explainable PET-based intratumoral and peritumoral machine learning model for predicting visceral pleural invasion in clinical-stage IA non-small cell lung cancer: A two-center study

AIM

The aim of this study was to develop a PET-based machine learning model for predicting visceral pleural invasion (VPI) in patients with clinical stage IA non-small cell lung cancer.

MATERIALS AND METHODS

A total of 294 patients and 69 patients from two institutions who underwent the 18F-FDG-PET scan were retrospectively analyzed. We extracted PET-based radiomics features from the gross tumor volume (GTV) and gross tumor volume incorporating peritumoral 4, 8 and 12 mm regions (GPTV4, GPTV8, GPTV12), respectively. Then four models were respectively established by using machine learning algorithms. The performance of the models was assessed by the receiver operating characteristic (ROC) curve and decision curve analyses (DCA). Shapley additive explanation (SHAP) was employed to explain the machine learning (ML) models and visualize variable predictions.

RESULTS

Compared with GTV, GPTV4, and GPTV12 radiomics models, the radiomics model based on GPTV8 using random forest (RF) among the 10 features demonstrated better prediction performance, with the AUC of 0.879, 0.846, and 0.745 in the training, internal validation, and external validation sets, respectively. The results of the SHAP method showed that the GLRLM_ShortRunLowGreyLevel Emphasis features were the most important factors in VPI. At the patient level, SHAP force plots provided a deep understanding for predicting VPI.

CONCLUSION

The PET-based intratumoral and peritumoral model based on machine learning offers an innovative tool for preoperative prediction of VPI in patients with lung adenocarcinoma. By employing the SHAP method, clinicians may gain a clearer insight into the factors contributing to VPI, which could enhance clinical decision-making of prognosis assessment.

Predicting Visceral Pleural Invasion in Resected Lung Adenocarcinoma via Computed Tomography

BACKGROUND/OBJECTIVES

For thoracic surgeons, the extent of visceral pleural invasion is a crucial consideration in the surgical approach to adenocarcinoma; this invasion may influence the extent of surgical resection and predict prognosis. With advances in preoperative imaging technology, predicting visceral pleural invasion via computed tomography (CT) characteristics may be feasible. The aim of this study was to evaluate the association between CT characteristics and visceral pleural invasion in patients with surgically resected lung adenocarcinoma.

METHODS

Patients with lung adenocarcinoma who underwent curative lung tumor resection (n = 643) were retrospectively included in this study between January 2011 and December 2015. Basic demographic CT images were analyzed by experienced thoracic surgeons and radiologists. Postoperative pathology reports were confirmed by experienced pathologists. Univariate and multivariate analyses were performed for potential prognostic factors.

RESULTS

Potential visceral pleural invasion characteristics of preoperative CT included tumor size (cm), solid part size, pleural contact of arch distance, ground glass opacity (%), tumor shape, border type, distance from visceral pleura, depth, and invasion site. In addition, solid part size, ground glass opacity (%), consolidation to tumor ratio (%), tumor shape, border type, distance from visceral pleura, and invasion site showed statistical significance for prognosis.

CONCLUSIONS

Increased precision of image interpretation may provide more predictive clues to improve the identification of visceral pleural invasion before operations. The extent of surgical resection may be more accurately determined, and systemic treatment may be administered earlier for those with poor prognostic factors.

Prediction of visceral pleural invasion of clinical stage IA lung adenocarcinoma based on computed tomography features

Background

In lung cancer, preoperative prediction of visceral pleural invasion (VPI) is helpful for choosing the best treatment plan and improving the prognosis of patients. This study aimed to investigate the usefulness of computed tomography (CT) features in predicting VPI in clinical stage IA peripheral lung adenocarcinoma (LUAD) with pleural contact.

Methods

This study divided the type of contact between tumor and pleura into indirect and direct contacts. This study retrospectively analyzed patients with clinical stage IA peripheral LUAD in three hospitals and enrolled 485 patients. The CT features of lesions were analyzed to predict VPI, including relative pleural features, tumor signs, and characteristics between the tumor and pleura. Univariate and multivariate logistic regression analyses were used to select the best combination of variables to predict VPI, and the prediction models were developed.

Results

The multivariate logistic regression analysis identified solid component size, pleural tag type, and vascular convergence sign to be independent risk factors for VPI in indirect pleural contact type. The area under curve (AUC) values of the model for predicting VPI in the training, internal validation, and external validation sets were 0.887, 0.799, and 0.862, respectively. Solid component size and pleural indentation sign were identified as independent risk factors for predicting VPI in direct pleural contact type. The AUC values of the model for predicting VPI in the training, internal validation, and external validation sets were 0.903, 0.848, and 0.842, respectively.

Conclusions

CT predictors associated with VPI differ based on the type of contact with the pleura. The multivariate logistic regression models utilizing CT features demonstrates acceptable diagnostic accuracy in predicting VPI in clinical stage IA LUAD with pleural contact.

Survival Analysis of Early-Stage NSCLC Patients Following Lobectomy: Impact of Surgical Techniques and Other Variables on Long-Term Outcomes

BACKGROUND

Surgical resection is a frontline management option for early-stage non-small cell lung cancer (NSCLC). Evolving techniques may be refining patient outcomes. This study compares the long-term survival of patients undergoing lobectomy for a primary NSCLC between video-assisted thoracoscopic surgery (VATS) and open thoracotomy (OT). The secondary aim of this study is to identify the variables that influence immediate and long-term patient outcomes.

METHOD

This is a single-centre retrospective cohort analysis spanning 20 years. The study reports on the outcomes of 743 patients who underwent lobectomy for primary NSCLC. There are 598 VATS cases and 145 OT cases. Variables likely to influence long-term survival were assessed with Kaplan-Meier survival analysis. The effect of VATS on long-term survival was assessed using a propensity-adjusted analysis.

RESULTS

Chronic obstructive pulmonary disease, history of other cancers, coronary artery disease, type 2 diabetes, and emphysema were the most common comorbidities reported in this cohort. The VATS technique showed shorter postoperative length of stay and fewer surgical complications compared with OT. There were no differences between VATS and OT in early mortality or completeness of the resection. Additionally, 32% of patients showed variable visceral pleural invasion (P1-P2), and their 5-year survival was significantly worse compared with P0 patients (18.75% and 36.85%, respectively). Major pulmonary complications were responsible for prolonging the length of hospital stay after index surgery and it was inversely related to the survival at 5 and 10 years (p<0.0004). Lymph node involvement was an important predictor for long-term survival (50% overall survival rate was 9.4 years, 4.5 years and 4.2 years for N0, N1, and N2, respectively). We observed longer median survival in the VATS group (10.04 years vs 8.99 years) and a lower risk of mortality after propensity analysis (odds ratio 0.86; 95% confidence interval 0.67-1.11), but neither observation was statistically significant.

CONCLUSIONS

Early surgical outcomes were significantly better in the VATS group, whereas long-term outcomes were not notably different between the groups. Regardless of the surgical techniques used, positive surgical margins, visceral pleural invasion, larger tumours, positive lymph nodes, age >70 years, and prolonged hospital stay were common variables responsible for the poor overall long-term survival.

Tumour-pleura relationship on computed tomography (CT) provides effective risk stratification for peripheral pulmonary nodules with Lung Imaging Reporting and Data System (Lung-RADS) score of 4X

Background

Pulmonary nodules with Lung Imaging Reporting and Data System (Lung-RADS) 4X are of greater clinical significance, and accurate differentiation of pathological types and visceral pleural invasion (VPI) of Lung-RADS 4X peripheral pulmonary nodules before treatment can aid in stratification. This study set out to investigate whether the tumour-pleura relationship on computed tomography (CT) can provide effective risk stratification for peripheral pulmonary nodules with Lung-RADS 4X.

Methods

This was a single institution, retrospective study of 482 consecutive patients with Lung-RADS score 4X, who were pathologically diagnosed with tuberculous granuloma and adenocarcinoma from January 2019 to December 2023. We assessed clinical factors (baseline characteristics and tumour markers) and CT findings. Univariate and multivariate logistic regression analyses were used to determine the classification of pulmonary nodules and predictors of VPI.

Results

Multivariate analysis revealed that gender [odds ratio (OR) =0.392; P<0.001], carcinoembryonic antigen (CEA) level (OR =8.331; P<0.001), type of nodules (OR =13.551 and 7.478; P<0.001 and P=0.016) and maximum base width of soft tissue component on the pleura side (OR =0.857; P=0.005) were significant independent factors for distinguishing tuberculous granuloma from adenocarcinoma. And the type of linear connection between lesion and pleura (OR =3.936; P<0.001), and the maximum base width of soft tissue components on the pleura side (OR =1.359; P=0.001) were correlated independently with VPI. The area under the curve (AUC) for predicting pulmonary nodules classification was 82.60% [95% confidence interval (CI): 78.85-86.35%), and the AUC for predicting VPI was 76.10% (95% CI: 69.83-82.38%).

Conclusions

The tumour-pleura relationship will be helpful in further risk stratification for peripheral pulmonary nodules with a score of Lung-RADS 4X.

Nomogram using intratumoral and peritumoral radiomics for the preoperative prediction of visceral pleural invasion in clinical stage IA lung adenocarcinoma

BACKGROUND

Accurate prediction of visceral pleural invasion (VPI) in lung adenocarcinoma before operation can provide guidance and help for surgical operation and postoperative treatment. We investigate the value of intratumoral and peritumoral radiomics nomograms for preoperatively predicting the status of VPI in patients diagnosed with clinical stage IA lung adenocarcinoma.

METHODS

A total of 404 patients from our hospital were randomly assigned to a training set (n = 283) and an internal validation set (n = 121) using a 7:3 ratio, while 81 patients from two other hospitals constituted the external validation set. We extracted 1218 CT-based radiomics features from the gross tumor volume (GTV) as well as the gross peritumoral tumor volume (GPTV5, 10, 15), respectively, and constructed radiomic models. Additionally, we developed a nomogram based on relevant CT features and the radscore derived from the optimal radiomics model.

RESULTS

The GPTV10 radiomics model exhibited superior predictive performance compared to GTV, GPTV5, and GPTV15, with area under the curve (AUC) values of 0.855, 0.842, and 0.842 in the three respective sets. In the clinical model, the solid component size, pleural indentation, solid attachment, and vascular convergence sign were identified as independent risk factors among the CT features. The predictive performance of the nomogram, which incorporated relevant CT features and the GPTV10-radscore, outperformed both the radiomics model and clinical model alone, with AUC values of 0.894, 0.828, and 0.876 in the three respective sets.

CONCLUSIONS

The nomogram, integrating radiomics features and CT morphological features, exhibits good performance in predicting VPI status in lung adenocarcinoma.

Research progress in predicting visceral pleural invasion of lung cancer: a narrative review

Background and Objective

In lung cancer, visceral pleural invasion (VPI) affects the selection of surgical methods, the scope of lymph node dissection and the need for adjuvant chemotherapy. Preoperative or intraoperative prediction and diagnosis of VPI of lung cancer is helpful for choosing the best treatment plan and improving the prognosis of patients. This review aims to summarize the research progress of the clinical significance of VPI assessment, the intraoperative diagnosis technology of VPI, and various imaging methods for preoperative prediction of VPI. The diagnostic efficacy, advantages and disadvantages of various methods were summarized. The challenges and prospects for future research will also be discussed.

Methods

A comprehensive, non-systematic review of the latest literature was carried out in order to investigate the progress of predicting VPI. PubMed database was being examined and the last run was on 4 August 2022.

Key Content and Findings

The pathological diagnosis and clinical significance of VPI of lung cancer were discussed in this review. The research progress of prediction and diagnosis of VPI in recent years was summarized. The results showed that preoperative imaging examination and intraoperative freezing pathology were of great value.

Conclusions

VPI is one of the adverse prognostic factors in patients with lung cancer. Accurate prediction of VPI status before surgery can provide guidance and help for the selection of clinical operation and postoperative treatment. There are some advantages and limitations in predicting VPI based on traditional computed tomography (CT) signs, 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/CT and magnetic resonance imaging (MRI) techniques. As an emerging technology, radiomics and deep learning show great potential and represent the future research direction.

Diagnosis, treatment, and prognosis of stage IB non-small cell lung cancer with visceral pleural invasion

With the increasing implementation of early lung cancer screening and the increasing emphasis on physical examinations, the early-stage lung cancer detection rate continues to rise. Visceral pleural invasion (VPI), which denotes the tumor's breach of the elastic layer or reaching the surface of the visceral pleura, stands as a pivotal factor that impacts the prognosis of patients with non-small cell lung cancer (NSCLC) and directly influences the pathological staging of early-stage cases. According to the latest 9th edition of the TNM staging system for NSCLC, even when the tumor diameter is less than 3 cm, the final T stage remains T2a if VPI is present. There is considerable controversy within the guidelines regarding treatment options for stage IB NSCLC, especially among patients exhibiting VPI. Moreover, the precise determination of VPI is important in guiding treatment selection and prognostic evaluation in individuals with NSCLC. This article aims to provide a comprehensive review of the current status and advancements in studies pertaining to stage IB NSCLC accompanied by VPI.

CT-based radiomics nomogram for predicting visceral pleural invasion in peripheral T1-sized solid lung adenocarcinoma

The preoperative assessment of visceral pleural invasion (VPI) in patients with early lung adenocarcinoma is vital for surgical treatment. This study aims to develop and validate a CT-based radiomics nomogram to predict VPI in peripheral T1-sized solid lung adenocarcinoma. A total of 203 patients were selected as subjects, and were divided into a training cohort (n=141; scanned with Brilliance iCT256, Brilliance 64, Somatom Force, and Optima CT660) and a test cohort (n=62; scanned with Somatom Definition AS+). Radiomics characteristics were extracted from CT images. Variance thresholding, SelectKBest, and least absolute shrinkage and selection operator (LASSO) method were applied to determine optimum characteristics to construct the radiomic signature (radscore). After multivariate logistic regression analysis, a nomogram was structured regarding clinical factors, conventional CT features, and radscore. The nomogram property was tested based on its area under the curve (AUC). The nomogram based on the radscore and two conventional CT features (tumor pleura relationship and lymph node enlargement) showed high discrimination with an AUC of 0.877 (95% CI: 0.820-0.935) and 0.837 (95% CI: 0.737-0.937) in the training and test cohorts, respectively. The calibration curve and decision curve analysis showed good consistency and high clinical value of the nomogram. In conclusion, The CT-based radiomics nomogram was helpful in predicting VPI in peripheral T1-sized solid lung adenocarcinoma.

Using CT imaging features to predict visceral pleural invasion of non-small-cell lung cancer

AIM

To examine the diagnostic performance of different models based on computed tomography (CT) imaging features in differentiating the invasiveness of non-small-cell lung cancer (NSCLC) with multiple pleural contact types.

MATERIALS AND METHODS

A total of 1,573 patients with NSCLC (tumour size ≤3 cm) were included retrospectively. The clinical and pathological data and preoperative imaging features of these patients were investigated and their relationships with visceral pleural invasion (VPI) were compared statistically. Multivariate logistic regression was used to eliminate confounding factors and establish different predictive models.

RESULTS

By univariate analysis and multivariable adjustment, surgical history, tumour marker (TM), number of pleural tags, length of solid contact and obstructive inflammation were identified as independent risk predictors of pleural invasiveness (p=0.014, 0.003, <0.001, <0.001, and 0.017, respectively). In the training group, comparison of the diagnostic efficacy between the combined model including these five independent predictors and the image feature model involving the latter three imaging predictors were as follows: sensitivity of 88.9% versus 77% and specificity of 73.5% versus 84.1%, with AUC of 0.868 (95% CI: 0.848-0.886) versus 0.862 (95% CI: 0.842-0.880; p=0.377). In the validation group, the sensitivity and specificity of these two models were as follow: the combined model, 93.5% and 74.3%, the imaging feature model, 77.4% and 81.3%, and their areas under the curve (AUCs) were both 0.884 (95% CI: 0.842-0.919). The best cut-off value of length of solid contact was 7.5 mm (sensitivity 68.9%, specificity 75.5%).

CONCLUSIONS

The image feature model showed great potential in predicting pleural invasiveness, and had comparable diagnostic efficacy compared with the combined model containing clinical data.

Multi-dimensional radiomics analysis to predict visceral pleural invasion in lung adenocarcinoma of ≤3 cm maximum diameter

AIM

To explore the value of radiomics analysis in preoperatively predicting visceral pleural invasion (VPI) of lung adenocarcinoma (LAC) with ≤3 cm maximum diameter and to compare the performance of two-dimensional (2D) and three-dimensional (3D) computed tomography (CT) radiomics models.

MATERIALS AND METHODS

A total of 391 LAC patients were enrolled retrospectively, of whom 142 were VPI (+) and 249 were VPI (-). Radiomics features were extracted from 2D and 3D regions of interest (ROIs) of tumours in CT images. 2D and 3D radiomics models were developed combining the optimal radiomics features by using the logistic regression machine-learning method and radiomics scores (rad-scores) were calculated. Nomograms were constructed by integrating independent risk factors and rad-scores. The performance of each model was evaluated by using the receiver operator characteristic (ROC) curve, decision curve analysis (DCA), clinical impact curve (CIC), and calculating the area under the curve (AUC).

RESULTS

There was no difference in the VPI prediction between 2D and 3D radiomics models (training group: 2D AUC=0.835, 3D AUC=0.836, p=0.896; validation group: 2D AUC=0.803, 3D AUC=0.794, p=0.567). The 2D and 3D nomograms performed similarly regarding discrimination (training group: 2D AUC=0.867, 3D AUC=0.862, p=0.409, validation group: 2D AUC=0.835, 3D AUC=0.827, p=0.558), and outperformed their corresponding radiomics models and the clinical model. DCA and CIC revealed that the 2D nomogram had slightly better clinical utility.

CONCLUSION

The 2D radiomics model has a similar discrimination capability compared with the 3D radiomics model. The 2D nomogram performs slightly better for individual VPI prediction in LAC.

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.

Effect of pleural invasion on survival of patients with small cell lung cancer: Propensity score analysis and nomogram establishment based on the SEER database

Objectives

Pleural invasion (PI) is identified as an adverse prognostic factor for non-small cell lung cancer (NSCLC), but its value in small cell lung cancer (SCLC) remains unclear. We aimed to evaluate the survival effect of PI on overall survival (OS) in SCLC, meanwhile, we established a predictive nomogram based on related risk factors for OS in SCLC patients with PI.

Methods

We extracted the data of patients diagnosed with primary SCLC between 2010 and 2018 from the Surveillance, Epidemiology, and End Results (SEER) database. The propensity score matching (PSM) method was used to minimize the baseline difference between the non-PI and PI groups. Kaplan-Meier curves and the log-rank test were used for survival analysis. Univariate and multivariate Cox regression analyses were applied to identify the independent prognostic factors. Randomly divided the patients with PI into training (70%) and validation (30%) cohorts. A prognostic nomogram was established based on the training cohort and was evaluated in the validation cohort. The C-index, receiver operating characteristic curves (ROC), calibration curves, and decision curve analysis (DCA) were applied to assess the performance of the nomogram.

Results

A total of 1,770 primary SCLC patients were enrolled, including1321patients with non-PI and 449 patients with PI. After PSM, the 387 patients in the PI group matched the 387 patients in the non-PI group. By Kaplan-Meier survival analysis, we observed the exact beneficial effect of non-PI on OS in both original and matched cohorts. Multivariate Cox analysis showed similar results to demonstrate a statistically significant benefit for patients with non-PI in both original and matched cohorts. Age, N stage, M stage, surgery, radiotherapy, and chemotherapy were independent prognostic factors for SCLC patients with PI. The C-index of the nomogram in the training and validation cohort was 0.714 and 0.746, respectively. The ROC curves, calibration curves, and DCA curves also demonstrated good predictive performance in the training and validation cohorts of the prognostic nomogram.

Conclusion

Our study shows that PI is an independent poor prognostic factor for SCLC patients. The nomogram is a useful and reliable tool to predict the OS in SCLC patients with PI. The nomogram can provide strong references to clinicians to facilitate clinic decisions.

An initial study on the comparison of diagnostic performance of 18F-FDG PET/MR and 18F-FDG PET/CT for thoracic staging of non-small cell lung cancer: Focus on pleural invasion

OBJECTIVE

To compare the diagnostic performance of ¹⁸F-FDG PET/MR and PET/CT preliminarily for the thoracic staging of non-small cell lung cancer (NSCLC) with a special focus on pleural invasion evaluation.

METHODS

52 patients with pathologically confirmed NSCLC were included and followed for another year. Whole-body ¹⁸F-FDG PET/CT and subsequent thoracic PET/MR were performed for initial thoracic staging. Thoracic (simultaneous) PET/MR acquired PET images and MRI sequences including T2 weighted imaging, with and without fat saturation, T1 weighted imaging, and diffusion weighted imaging (DWI). Two radiologists independently assessed the thoracic T, N staging and pleural involvement. The McNemar Chi-square test was used to compare the differences between PET/CT and PET/MR in the criteria. The area under the receiver-operating-characteristic curves (AUC) was calculated.

RESULTS

Compared to PET/CT, PET/MR exhibited higher sensitivity, specificity in the detection of pleural invasion; 82 % vs. 64% (p = 0.625), 98 % vs. 95% (p = 1.000), PET/MR to PET/CT respectively. The receiver-operating-characteristic analysis results of PET/CT vs PET/MR for the pleural invasion were as follow: AUC_PET/CT = 0.79, AUC_PET/MR = 0.90, p = 0.21. Both T staging results and N staging results were approximately identical in PET/CT and PET/MR. Differences between PET/CT and PET/MR in T staging, N staging as well as pleural invasion accuracy were not statistically significant (p > 0.05, each).

CONCLUSION

PET/MR and PET/CT demonstrated equivalent performance about the evaluation of preoperative thoracic staging of NSCLC patients. PET/MR may have greater potential in pleural invasion evaluation for NSCLC, especially for solid nodules, crucial to clinical decision-making, though our results did not demonstrate statistical significance.

The role of ipsilateral mediastinal lymph node dissection in treatment of patients with non-small-cell lung cancer

Background. Lung cancer occupies the leading place in the structure of cancer incidence and death rate. Treatment results are still not satisfactory. Five-year postsurgical survival rate is 24–30%. Patients die in different periods of time from local recurrences and distant metastases. To this day, there is no unambiguous attitude towards ipsilateral mediastinal lymph node dissection in surgical treatment of patients with lung cancer. Despite the oncologic relevance of the abovementioned lymph node dissection, there are still concerns on worsening of recovery conditions of bronchial stump, increase in the amount of lymphorrhea and additional injury rate of the surgery. There is also an opinion that the risk of development of postsurgical complications, and, as a result, the increase in lethality rate, outweigh the positive impact of ipsilateral mediastinal lymph node dissection on radicality and long-term treatment results. Purpose – to study the impact of ipsilateral mediastinal lymph node dissection on the course of postsurgical period in patients with lung cancer, clarifying diagnostics of spread of tumor process and survival rate of the patients. Materials and methods. Treatment results of 187 patients with non-small-cell lung cancer with different clinical stages from T1-3N0 M0 to T1-2N1 M0 were analyzed. The patients were divided into two groups: the first group (comparison group) consisted of 72 patients, who underwent radical operations with selective lymph node dissection. The patients of the second group, the study group (115 patients), obligatorily underwent ipsilateral mediastinal lymph node dissection. The number of removed lymph nodes in one patient ranged from 5 to 10 in the first group and from 18 to 25 in the second one. In the cases when no cancer cells were found in lymph nodes, they were managed with monoclonal antibodies to cytokeratins, expressed with cancer cells, with further microscopic evaluation. During the postsurgical period the following values were studied: duration of the surgery, the volume of intraoperative blood loss, the amount and duration of exudation, frequency and character of postsurgical complications. Comparison of survival rates of the patients was performed with the test of statistical significance of differences by χ2 criterion. Methods of non-parametric statistical estimate were used for statistical analysis of the results by the means of Statistica 6.0, SPSS 17.0 software. Results. Adding ipsilateral mediastinal lymph node dissection to surgical interference increased its duration by 30 minutes on average. An increase in the volume of exudate by 136,2 ± 18,4 ml was observed in early postsurgical period. Structure and frequency of postsurgical complications in both groups was similar. In most cases heart rhythm disorder, namely ciliary arrhythmia, was observed in the first days after the surgery. Postsurgical lethality rate in both groups was caused by various factors and equaled 1,4% in the first, and 0,8% in the second one. Additional usage of immunohistochemicalanalysis of lymph nodes with monoclonal antibodies to tumoral cytokeratins in patients after performing ipsilateral mediastinal lymph node dissection led to their lesion being found more frequently. Indeed, metastases were detected in 21% of 19 patients, in which N0 status was previously established in light microscopy. Also, a significant increase in three-year survival rate by 15,3% (p=0,042) was observed in patients with lung cancer, who underwent ipsilateral mediastinal lymph node dissection and had no signs of mediastinal lymph nodes lesion, and 23,2% (p=0,014) in patients with the signs of the lesion. Conclusions. Performing ipsilateral mediastinal lymph node dissection in patients with lung cancer during surgical interference does not have an impact on postsurgical lethality rate and frequency and structure of complications. During the study of lymph nodes, which, according to light microscopy, were considered unaffected by cancer, additional lymphogland metastases were found in 20,7% of the patients by the means of monoclonal antibodies to cytokeratins. It allows the stage of the disease to be more accurately determined and optimal type of adjuvant therapy to be chosen. Detection rate of metastases in regional lymph nodes significantly increases from 51,4% to 67,8% in patients with lung cancer after radical operations with additional ipsilateral mediastinal lymph node dissection. Obligatory ipsilateral mediastinal lymph node dissection in surgeries for lung cancer increases overall three-year survival rate, especially in patients with affected lymph nodes by 16,3%.

Exploration of the optimal number of regional lymph nodes removed for resected N0 NSCLC patients: A population-based study

Background

The aim of our study was to explore the optimal number of regional lymph nodes removed (LNRs) in resected N0 non-small cell lung cancer (NSCLC) patients and identify potential risk factors.

Methods

Included in this study were 55,024 N0 NSCLC patients between 2004 and 2015 based on the Surveillance, Epidemiology, and End Results database (SEER). All the patients were divided into No LNR group (57.8%), 1-3 LNRs group (8.1%) and ≥4 LNRs group (31.4%). Relevant clinical and patient parameters including overall survival (OS), lung cancer-specific survival (LCSS), gender, race, year of diagnosis, primary site, T stage, AJCC stage, laterality, histological type, lymphadenectomy, radiation, chemotherapy, age at diagnosis, insurance status, marital status, family income.

Results

Kaplan-Meier analysis demonstrated LNRs had significantly better OS and LCSS than No LNRs in all the N0 NSCLC patients with different T stages (Logrank p<.001). Univariate and multivariate analysis showed that both OS and LCSS in ≥ 4 LNRs group were better than those in <1-3 LNRs group (OS: ≥4 LNRs group: HR, 0.583; 95%CI, 0.556-0.610; P<.001 vs.1-3 LNRs group: HR, 0.726; 95%CI, 0.687-0.769; P<.001; LCSS: ≥4 LNRs group: HR, 0.514; 95%CI, 0.480-0.550; P<.001 vs.1-3 LNRs group: HR, 0.647; 95%CI, 0.597-0.702; P<.001). In addition, whites, males, not upper lobe, large cell carcinoma and others, advance T stage or AJCC stage, no surgery, no LNR, no radiation, no chemotherapy, elder age at diagnosis, singled marital status and low family income had negative impact on prognosis of N0 NSCLC patients.

Conclusions

Our study suggests that ≥ 4 LNRs can yield better survival outcomes compared with 1-3 LNRs in N0 NSCLC patients.

A Population-Based Study on the Prognostic factors and Efficacy of Adjuvant Chemotherapy in the Postoperative Stage for Patients with Stage IIA Non-Small Cell Lung Cancer

Objective

This study aimed to design a nomogram survival prediction by means of the figures retrieved from the Surveillance, Epidemiology, and End Results (SEER) source bank, and to predict the overall survival (OS) of patients with stage IIA non-small cell lung cancer (NSCLC) after surgery.

Methods

Data for 4511 patients who had been diagnosed with postoperative stage IIA NSCLC were collected from the SEER databank, while information on 528 patients was acquired from the Chongqing University Cancer Hospital for the external validation cohort. The independent risk factors that affected the prognosis were identified using a multivariate Cox proportional hazards regression model (also used to conduct a nomogram). A survival analysis between the low- and the high-risk groups was performed using the Kaplan-Meier method. Furthermore, a subgroup analysis was conducted of the two groups using the Kaplan-Meier method to determine whether the patients had received adjuvant chemotherapy.

Results

The following five variables were integrated into the nomogram: sex (female: HR 1.73, 95% CI 0.64-0.83), age (≥60: HR 1.61, 95% CI 1.39-1.87), differentiation grade (grade II: HR 2.19, 95% CI 1.66-2.88; grade III: HR 2.65, 95% CI 2.00-3.51; grade IV: HR 3.17, 95% CI 1.99-5.03), surgery (lobectomy: HR 0.72, 95% CI 0.59-0.86), and lymph node resection (>12: HR 0.82, 95% CI 0.70-0.96). Furthermore, the patients selected were categorized into high- and low-risk groups. The OS rate was significantly lower in the high-risk group than in the low-risk group (P < 0.001). Finally, adjuvant chemotherapy was highly correlated with OS in the high-risk set (P = 0.035); however, adjuvant chemotherapy was not related to OS in the low-risk set.

Conclusion

A nomogram was created as a reliable, convenient scheme that could predict OS, and it was determined that the high-risk feature patients identified by the nomogram gained benefits from adjuvant chemotherapy.

Rethinking the Selection of Pathological T-Classification for Non-Small-Cell Lung Cancer in Varying Degrees of Visceral Pleural Invasion: A SEER-Based Study

Background

The T classification of non-small-cell lung cancer (NSCLC) was upgraded from T1 to T2 when accompanied by visceral pleural invasion (VPI). However, the association between VPI and prognostic outcomes was obscure in NSCLC patients with ≤3 cm tumor size (TS), which leaded the controversy of selection of T classification. The goal was to evaluate the effect of VPI on the prognosis of NSCLC with ≤ 3cm TS and present a modified T classification.

Methods

A total of 14,934 NSCLC patients without distant metastasis were recruited through a retrospective study in the SEER database. The effect of VPI on lung cancer specific survival (LCSS) was evaluated using survival curve and COX regression analysis in NSCLC patients with ≤3 cm TS.

Results

Although there was no difference of the LCSS of PL0 and PL1 patients with ≤2 cm TS in patients without lymph node (LN) metastasis, the LCSS was lower in PL2 patients than those in PL0 (T1a: p < 0.001; T1b: p = 0.001). Moreover, the LCSS was decreased in PL1 and PL2 patients with 2-3 cm TS compared with PL0 (T1c: PL1, p < 0.001; PL2, p = 0.009) of patients without LN metastasis. No difference of LCSS was observed in patients with LN metastasis between PL0 with PL1 and PL2.

Conclusion

In NSCLC patients without LN metastasis and TS ≤ 2 cm, tumor with PL1 should remain defined as T1, tumor with PL2 should be defined as T2. However, 2-3 cm TS patients with PL1 or PL2 should both defined as T2. Meanwhile, ≤3 cm TS patients with LN metastasis can be regarded as T1, whether NSCLC patients accompanied with PL1 or PL2.

Is lobectomy superior to sub-lobectomy in non-small cell lung cancer with pleural invasion? A population-based competing risk analysis

Background

Pleural invasion (PL) has been regarded as an unfavorable prognostic factor for non-small cell lung cancer (NSCLC). But there was no agreement on the optimal surgical extent in NSCLC patients with PL. We aimed to compare the survival outcomes of lobectomy and sub-lobectomy in these patients.

Method

2717 patients were included in the Surveillance, Epidemiology, and End Results (SEER) database and divided into the lobectomy and sub-lobectomy groups. The propensity score matching (PSM) and competing risk analysis were implemented. Then the predictive nomogram was constructed and validated.

Results

2230 Patients received lobectomy while the other 487 patients underwent sub-lobectomy. After 1:1 PSM, the cumulative incidence of cancer-specific death (CSD) was lower in the lobectomy group compared with the sub-lobectomy group (1-year: 12% vs. 15%; 3-year: 30% vs. 37%, 5-year: 34% vs. 45%, P = 0.04). According to the subgroup analysis, the patients who underwent lobectomy suffered lower CSD in the N0–1 stage, adenocarcinoma, and PL-2 cohort (p < 0.05). And there was a significant relationship between the sub-lobectomy group and CSD in the multivariate competing risks regression analysis (HR, 1.26; 95%CI, 1.02–1.56; P = 0.034). Furthermore, a competing event nomogram was constructed to assess the 1-, 3-, and 5-year chances of CSD based on the variables from the multivariate analysis. The 1-, 3-, 5-year area under the receiver operating characteristic curve (AUC) values were 0.720, 0.706, and 0.708 in the training cohort, and 0.738, 0.696, 0.680 in the validation cohorts, respectively. And calibration curves demonstrated ideal consistency between the predicted and observed probabilities of CSD.

Conclusion

Lobectomy should be considered the preferred surgery compared to sub-lobectomy for NSCLC patients with PL. The proposed nomograms presented great prediction ability for these patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09634-w.

Prognostic significance of visceral pleural invasion in patients with surgically resected small-cell lung cancer: a population-based study

OBJECTIVE

Visceral pleural invasion is an adverse prognostic factor in non-small-cell lung cancer, but its value in small-cell lung cancer remains unclear. Thus, we investigated the prognostic impact of visceral pleural invasion in patients with surgically resected small-cell lung cancer.

METHODS

We queried the Surveillance, Epidemiology and End Results Program database for patients diagnosed with stages I-III (excluding N3 and nodal metastasis cannot be evaluated (NX)) small-cell lung cancer from 2004 to 2016, who underwent surgery. To minimize unbalanced baseline characteristics between the visceral pleural invasion and non-visceral pleural invasion groups, one-to-one propensity score matching was employed. A Kaplan-Meier curve was used to compare the overall survival of the two cohorts. A Cox proportional hazards model was adopted to determine the impact of visceral pleural invasion on survival.

RESULTS

Of the 1416 patients included, 372 (26.27%) presented with visceral pleural invasion. Patients with visceral pleural invasion showed significantly worse overall survival (P < 0.001) both before and after propensity score matching. Multivariable analysis indicated that visceral pleural invasion was an independent adverse factor affecting survival. Patients with visceral pleural invasion showed poorer overall survival (hazard ratio: 1.44; 95% confidence interval: 1.17-1.76; P < 0.001). Subgroup analyses revealed that the non-visceral pleural invasion group was associated with favourable overall survival in N0 patients (P = 0.003) but not in N1 or N2 patients (P = 0.774 and 0.248, respectively). Patients diagnosed at younger ages, females, lower N stage, resection with a lobectomy and adjuvant chemotherapy were associated with improved overall survival in the visceral pleural invasion group.

CONCLUSIONS

Visceral pleural invasion was an indicator of a poor prognosis for small-cell lung cancer, especially in those with N0 disease. Adjuvant chemotherapy significantly improves patient outcomes for patients with visceral pleural invasion.

Treatment Modality for Stage IB Peripheral Non-Small Cell Lung Cancer With Visceral Pleural Invasion and ≤3 cm in Size

Purpose

To compare the survival difference among lobectomy, segmentectomy, and wedge resection and investigate the role of adjuvant chemotherapy for early-stage small-sized non-small cell lung cancer (NSCLC) with visceral pleural invasion (VPI).

Methods

Patients diagnosed with stage IB peripheral NSCLC with VPI and ≤3 cm in size in the Surveillance, Epidemiology, and End Results database between 2004 and 2015 were included, and the pleural layer (PL) invasion status was identified to recognize the tumors with VPI, including PL1 and PL2. We conducted Cox proportional hazards model in multivariable analysis and subgroup analysis via propensity score matching (PSM) method and Cox regression method to figure out the optimal therapy for these patients.

Results

A total of 1,993 patients were included, all of whom received surgery, and the median follow-up was 33 months (range, 1–83 months). In multivariable analysis, age, gender, histology, pathological grade, lymph node examination, surgical approaches, and radiotherapy were independent prognostic factors for overall survival (OS). Lobectomy was superior to sublobar resection [hazard ratio (HR) = 1.41; 95% CI, 1.08–1.83], and wedge resection was associated with impaired survival compared to lobectomy (HR = 1.64; 95% CI, 1.22–2.20) in PSM analyses. In subgroup analysis, lobectomy was superior to sublobar resection among those aged <70 years (HR = 1.81; 95% CI, 1.13–2.90), female (HR = 1.75; 95% CI, 1.21–2.53), and 1–20 mm in size (HR = 1.61; 95% CI, 1.11–2.33). No survival benefit was observed for adjuvant chemotherapy.

Conclusions

Lobectomy was superior to wedge resection and comparable with segmentectomy for stage IB NSCLC (≤3 cm) with VPI, and adjuvant chemotherapy could not benefit these patients, even in those with sublobar resection. The preferred surgical procedure remains to be studied in prospective controlled trials.

The combination of computed tomography features and circulating tumor cells increases the surgical prediction of visceral pleural invasion in clinical T1N0M0 lung adenocarcinoma

Background

Visceral pleural invasion (VPI) is a clinical manifestation associated with a poor prognosis, and diagnosing it preoperatively is highly imperative for successful sublobar resection of these peripheral tumors. We evaluated the roles of computed tomography (CT) features and circulating tumor cells (CTCs) for improving VPI detection in patients with clinical T1N0M0 invasive lung adenocarcinoma.

Methods

Three hundred and ninety-one patients were reviewed retrospectively in this study, of which 234 presented with a pleural tag or pleural contact on CT images. CTCs positive for the foliate receptors were enriched and analyzed prior to surgery. Logistic regression analyses were performed to assess the association of CT features and CTCs with VPI, and the receiver operating characteristic (ROC) curve was generated to compare the predictive power of these variables.

Results

Patients mostly underwent either segmentectomies (18.9%) or lobectomies (79.0%). Only 49 of the 234 patients with pleural involvement on CT showed pathologically confirmed VPI. Multivariate logistic regression analysis revealed that CTC level ≥10.42 FU/3 mL was a significant VPI risk factor for invasive adenocarcinoma cases ≤30 mm [adjusted odds ratio (OR) =4.62, 95% confidence interval (CI): 2.05–10.44, P<0.001]. Based on CT features, subgroup analyses showed that the solid portion size was a statistically significant independent predictor of VPI for these peripheral nodules with pleural tag, while the solid portion length of the interface was an independent predictor of pleural contact. The receiver operating curve analyses showed that the combination of CTC and CT features were highly predictive of VPI [area under the curve (AUC) =0.921 for pleural contact and 0.862 for the pleural tag, respectively].

Conclusions

CTC, combined with CT features of pleural tag or pleural contact, could significantly improve VPI detection in invasive lung adenocarcinomas at clinical T1N0M0 stage prior to the patient’s surgery.

CT texture analysis-based nomogram for the preoperative prediction of visceral pleural invasion in cT1N0M0 lung adenocarcinoma: an external validation cohort study

AIM

To develop a nomogram based on computed tomography (CT) texture analysis for the preoperative prediction of visceral pleural invasion in patients with cT1N0M0 lung adenocarcinoma.

MATERIALS AND METHODS

A dataset of chest CT containing lung nodules was collected from two institutions, and all surgically resected nodules were classified pathologically based on the presence of visceral pleural invasion. Each nodule on the CT image was segmented automatically by artificial-intelligence software and its CT texture features were extracted. The dataset was divided into training and external validation cohorts according to the institution, and a nomogram for predicting visceral pleural invasion was developed and validated.

RESULTS

Of a total of 313 patients enrolled from two independent institutions, 63 were diagnosed with visceral pleural invasion. Three-dimensional (3D) CT long diameter, skewness, and sphericity, and chronic obstructive pulmonary disease were identified as independent predictors for visceral pleural invasion by multivariable logistic regression. The nomogram based on multivariable logistic regression showed great discriminative ability, as indicated by a C-index of 0.890 (95% confidence interval [CI]: 0.867-0.914) and 0.864 (95% CI: 0.817-0.911) for the training and external validation cohorts, respectively. Additionally, calibration of the nomogram revealed good predictive ability, as indicated by the Brier score (0.108 and 0.100 for the training and external validation cohorts, respectively).

CONCLUSIONS

A nomogram was developed that could compute the probability of visceral pleural invasion in patients with cT1N0M0 lung adenocarcinoma with good calibration and discrimination. The nomogram has potential as a reliable tool for clinical evaluation and decision-making.

Survival Nomogram for Stage IB Non-Small-Cell Lung Cancer Patients, Based on the SEER Database and an External Validation Cohort

OBJECTIVE

This study aimed to construct a nomogram to effectively predict the overall survival (OS) of patients with stage IB non-small-cell lung cancer (NSCLC).

METHODS

In total, 5513 patients with stage IB NSCLC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and used as the training cohort. We enrolled 440 patients from the Cancer Hospital, Chinese Academy of Medical Sciences, for the external validation cohort. A nomogram was constructed based on the risk factors affecting prognosis using a Cox proportional hazards regression model. The discrimination and calibration of the nomogram were evaluated by C-indexes and calibration curves.

RESULTS

Six independent risk factors for OS were identified and integrated into the nomogram. The discrimination of the nomogram revealed good prognostic accuracy and clinical applicability as indicated by C-index values of 0.637 (95% CI 0.634-0.641) and 0.667 (95% CI 0.656-0.678) for the training cohort and the external validation cohort, respectively. Additionally, the patients were divided into two groups according to risk (sum-score > 185), and significant differences in OS were observed between the high-risk and low-risk groups in the training and external validation cohorts (P < 0.001). Finally, chemotherapy was significantly associated with OS in patients with differentiation grades II-IV (P = 0.004) and patients with adenocarcinoma (P = 0.005).

CONCLUSION

This nomogram provides a convenient and reliable tool for individual evaluations and clinical decision-making for patients with stage IB NSCLC; among these patients, those with differentiation grades II-IV or adenocarcinoma could benefit from chemotherapy.

Accessory and Incomplete Lung Fissures: Clinical and Histopathologic Implications

OBJECTIVE

This article reviews the anatomy, histology, and disease processes of pulmonary fissures, with emphasis on clinical implications of accessory and incomplete fissures.

CONCLUSION

Accessory and incomplete pulmonary fissures are often overlooked during routine imaging but can have profound clinical importance. Knowledge of fissure anatomy could improve diagnostic accuracy and inform prognosis for oncologists, interventional pulmonologists, and thoracic surgeons.

Sublobectomy versus lobectomy for long-term survival outcomes of early-stage non-small cell lung cancer with a tumor size ≤2 cm accompanied by visceral pleural invasion: a SEER population-based study

Background

The optimal surgical strategy for early-stage non-small cell lung cancer (NSCLC) with visceral pleural invasion (VPI) remains unclear. Due to limited prospective comparative data for these surgical modalities, the objective of the current study was to compare the long-term survival outcomes of sublobectomy (Sub) versus lobectomy (Lob) for NSCLC with a tumor size ≤2 cm and VPI.

Methods

Patients with early-stage NSCLC characterized by VPI diagnosed between 2004 and 2013 were identified from the Surveillance, Epidemiology, and End Results (SEER) program. The baseline demographic and cancer characteristics, treatment information as well as survival outcome data were extracted from the SEER database, and confounders were balanced by propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) analyses. Lung disease-specific survival (DSS) and overall survival (OS) rates were compared with Cox proportional hazards (PH) regression models based on the unmatched cohort, the propensity-based matched cohort, and the IPTW cohort.

Results

Of the 1,386 patients enrolled, 1,000 (72.15%) and 386 (27.85%) underwent lobectomy and sublobectomy, respectively. The 5-year DSS rate was 78.64% for the lobectomy group and 59.47% for the sublobectomy group. Cox regression models demonstrated that the operation type (Sub vs. Lob) was an independent prognostic factor for early-stage NSCLC with VPI based on the three different cohorts. Patients who underwent lobectomy showed better long-term DSS and OS rates than those treated with sublobectomy after PSM [DSS: hazard ratio (HR) 0.689, 95% confidence interval (CI): 0.490–0.968, P=0.032; OS: HR 0.723, 95% CI: 0.549–0.953, P=0.021]. The IPTW analysis yielded similar results.

Conclusions

Lobectomy showed superior long-term survival compared with sublobectomy in patients with early-stage NSCLC with a tumor size ≤2 cm and VPI.

Impact of visceral pleural invasion on the association of extent of lymphadenectomy and survival in stage I non-small cell lung cancer

Visceral pleural invasion (VPI) has been identified as an adverse prognostic factor for non‐small cell lung cancer (NSCLC). Accurate nodal staging for NSCLC correlates with improved survival, but it is unclear whether tumors with VPI require a more extensive lymph nodes (LNs) dissection to optimize survival. We aimed to evaluate the impact of VPI status on the optimal extent of LNs dissection in stage I NSCLC, using the Surveillance, Epidemiology, and End Results (SEER) database. We identified 9297 surgically treated T1‐2aN0M0 NSCLC patients with at least one examined LNs. Propensity score matching was conducted to balance the baseline clinicopathologic characteristics between the VPI group and non‐VPI group. Log‐rank tests along with Cox proportional hazards regression methods were performed to evaluate the impact of extent of LNs dissection on survival. VPI was correlated with a significant worse survival, but there was no significant difference in survival rate between PL1 and PL2. Patients who underwent sublobectomy had slightly decreased survival than those who underwent lobectomy. Pathologic LNs examination was significantly correlated with survival. Examination of 7‐8 LNs and 14‐16 LNs conferred the lowest hazard ratio for T1‐sized/non‐VPI tumors (stage IA) and T1‐sized/VPI tumors (stage IB), respectively. The optimal extent of LNs dissection varied by VPI status, with T1‐sized/VPI tumors (stage IB) requiring a more extensive LNs dissection than T1‐sized/non‐VPI tumors (stage IA). These results might provide guidelines for surgical procedure in early stage NSCLC.