Visceral Pleural Invasion: Pathologic Criteria and Use of Elastic Stains: Proposal for the 7th Edition of the TNM Classification for Lung Cancer

Prediction of visceral pleural invasion of clinical stage I lung adenocarcinoma using thoracoscopic images and deep learning

PURPOSE

To develop deep learning models using thoracoscopic images to identify visceral pleural invasion (VPI) in patients with clinical stage I lung adenocarcinoma, and to verify if these models can be applied clinically.

METHODS

Two deep learning models, one based on a convolutional neural network (CNN) and the other based on a vision transformer (ViT), were applied and trained via 463 images (VPI negative: 269 images, VPI positive: 194 images) captured from surgical videos of 81 patients. Model performances were validated via an independent test dataset containing 46 images (VPI negative: 28 images, VPI positive: 18 images) from 46 test patients.

RESULTS

The areas under the receiver operating characteristic curves of the CNN-based and ViT-based models were 0.77 and 0.84 (p = 0.304), respectively. The accuracy, sensitivity, specificity, and positive and negative predictive values were 73.91, 83.33, 67.86, 62.50, and 86.36% for the CNN-based model and 78.26, 77.78, 78.57, 70.00, and 84.62% for the ViT-based model, respectively. These models' diagnostic abilities were comparable to those of board-certified thoracic surgeons and tended to be superior to those of non-board-certified thoracic surgeons.

CONCLUSION

The deep learning model systems can be utilized in clinical applications via data expansion.

Preoperative evaluation of visceral pleural invasion in peripheral lung cancer utilizing deep learning technology

PURPOSE

This study aimed to assess the efficiency of artificial intelligence (AI) in the detection of visceral pleural invasion (VPI) of lung cancer using high-resolution computed tomography (HRCT) images, which is challenging for experts because of its significance in T-classification and lymph node metastasis prediction.

METHODS

This retrospective analysis was conducted on preoperative HRCT images of 472 patients with stage I non-small cell lung cancer (NSCLC), focusing on lesions adjacent to the pleura to predict VPI. YOLOv4.0 was utilized for tumor localization, and EfficientNetv2 was applied for VPI prediction with HRCT images meticulously annotated for AI model training and validation.

RESULTS

Of the 472 lung cancer cases (500 CT images) studied, the AI algorithm successfully identified tumors, with YOLOv4.0 accurately localizing tumors in 98% of the test images. In the EfficientNet v2-M analysis, the receiver operating characteristic curve exhibited an area under the curve of 0.78. It demonstrated powerful diagnostic performance with a sensitivity, specificity, and precision of 76.4% in VPI prediction.

CONCLUSION

AI is a promising tool for improving the diagnostic accuracy of VPI for NSCLC. Furthermore, incorporating AI into the diagnostic workflow is advocated because of its potential to improve the accuracy of preoperative diagnosis and patient outcomes in NSCLC.

Spread Through Air Spaces in Stage I to III Resected Lung Adenocarcinomas: Should the Presence of Spread Through Air Spaces Lead to an Upstaging?

In recent years, the concept of spread through air spaces (STAS) has been discussed as an adverse prognostic factor for lung cancer. The aim of our study is to clarify the prognostic role of STAS in relation to the main recognized prognostic factors in a retrospective cohort of 330 European patients who underwent stages I to III lung adenocarcinoma resection. On univariate analysis, the presence of STAS was related to progression-free survival (PFS; hazard ratio [HR]: 1.48; 95% CI: 1.02-2.19; P = 0.038) and overall survival (OS; HR: 1.61; 95% CI: 1.03-2.52; P = 0.50). On multivariate analysis, STAS was related to PFS (HR: 1.51; 95% CI: 1.00-2.17; P = 0.050) and to OS (HR: 1.67; 95% CI: 1.00-2.81; P = 0.050). We showed that the presence of STAS was associated with lower PFS, equivalent to the next pathologic T stage, especially the median PFS of T3 stages without STAS was at 62.8 months while the median PFS of T3 stages with STAS was at 15.7 months, closer to the median PFS of 17.4 months in T4 stages. To conclude, STAS is an independent prognostic factor of PFS in this European cohort and is close to significance for OS. We suggest that the presence of STAS might lead to an upstaging of lung adenocarcinoma.

Prediction of Pleural Lavage Cytology According to Thin-Section Computed Tomography in Non-Small-Cell Lung Cancer

BACKGROUND

Although the positive rate of preresection pleural lavage cytology (PLC) is low, it is an important indicator of poor prognosis for non-small-cell lung cancer patients with frequent pleural dissemination (PD) recurrence. Thin-section computed tomography (TSCT) can reveal relationships between a primary tumor and the pleura at 1 to 2 mm intervals, and this is associated with visceral pleural invasion (VPI). However, its association with PLC remains unclear. Therefore, we aimed to improve PLC efficiency and predict PD recurrence by understanding the relationship between PLC and preoperative TSCT findings.

PATIENTS AND METHODS

Between January 2014 and December 2018, we reviewed 978 patients with non-small-cell lung cancer who underwent PLC tests during complete resection surgery. Preoperative TSCT findings were evaluated, and factors with the highest specificity (proportion of patients with radiologically to pathologically diagnosed positive PLC) were investigated. We also evaluated their relationships with VPI and PD recurrence.

RESULTS

PLC positive was identified in 55 (5.6%) of the 978 patients. The two TSCT findings predicting PLC results, "the absence of pleural findings," ie, tumor not attached to pleura or without pleural tag, and "consolidation-to-tumor ratio ≤0.5", had a specificity of 100% (95% confidence interval: 90.4%-100%); additionally, all cases with these findings were VPI negative and had no PD recurrence. And 24% of the cohort had either of these findings.

CONCLUSION

The absence of pleural findings and/or consolidation-to-tumor ratio ≤0.5 of primary tumor on preoperative TSCT can predict PLC negativity with very high probability; therefore, PLC can be omitted for such patients.

Clinical Utility of a CT-based AI Prognostic Model for Segmentectomy in Non-Small Cell Lung Cancer

Background Currently, no tool exists for risk stratification in patients undergoing segmentectomy for non-small cell lung cancer (NSCLC). Purpose To develop and validate a deep learning (DL) prognostic model using preoperative CT scans and clinical and radiologic information for risk stratification in patients with clinical stage IA NSCLC undergoing segmentectomy. Materials and Methods In this single-center retrospective study, transfer learning of a pretrained model was performed for survival prediction in patients with clinical stage IA NSCLC who underwent lobectomy from January 2008 to March 2017. The internal set was divided into training, validation, and testing sets based on the assignments from the pretraining set. The model was tested on an independent test set of patients with clinical stage IA NSCLC who underwent segmentectomy from January 2010 to December 2017. Its prognostic performance was analyzed using the time-dependent area under the receiver operating characteristic curve (AUC), sensitivity, and specificity for freedom from recurrence (FFR) at 2 and 4 years and lung cancer-specific survival and overall survival at 4 and 6 years. The model sensitivity and specificity were compared with those of the Japan Clinical Oncology Group (JCOG) eligibility criteria for sublobar resection. Results The pretraining set included 1756 patients. Transfer learning was performed in an internal set of 730 patients (median age, 63 years [IQR, 56-70 years]; 366 male), and the segmentectomy test set included 222 patients (median age, 65 years [IQR, 58-71 years]; 114 male). The model performance for 2-year FFR was as follows: AUC, 0.86 (95% CI: 0.76, 0.96); sensitivity, 87.4% (7.17 of 8.21 patients; 95% CI: 59.4, 100); and specificity, 66.7% (136 of 204 patients; 95% CI: 60.2, 72.8). The model showed higher sensitivity for FFR than the JCOG criteria (87.4% vs 37.6% [3.08 of 8.21 patients], P = .02), with similar specificity. Conclusion The CT-based DL model identified patients at high risk among those with clinical stage IA NSCLC who underwent segmentectomy, outperforming the JCOG criteria. © RSNA, 2024 Supplemental material is available for this article.

Diagnostic performance and prognostic value of CT-defined visceral pleural invasion in early-stage lung adenocarcinomas

OBJECTIVES

To analyze the diagnostic performance and prognostic value of CT-defined visceral pleural invasion (CT-VPI) in early-stage lung adenocarcinomas.

METHODS

Among patients with clinical stage I lung adenocarcinomas, half of patients were randomly selected for a diagnostic study, in which five thoracic radiologists determined the presence of CT-VPI. Probabilities for CT-VPI were obtained using deep learning (DL). Areas under the receiver operating characteristic curve (AUCs) and binary diagnostic measures were calculated and compared. Inter-rater agreement was assessed. For all patients, the prognostic value of CT-VPI by two radiologists and DL (using high-sensitivity and high-specificity cutoffs) was investigated using Cox regression.

RESULTS

In 681 patients (median age, 65 years [interquartile range, 58-71]; 382 women), pathologic VPI was positive in 130 patients. For the diagnostic study (n = 339), the pooled AUC of five radiologists was similar to that of DL (0.78 vs. 0.79; p = 0.76). The binary diagnostic performance of radiologists was variable (sensitivity, 45.3-71.9%; specificity, 71.6-88.7%). Inter-rater agreement was moderate (weighted Fleiss κ, 0.51; 95%CI: 0.43-0.55). For overall survival (n = 680), CT-VPI by radiologists (adjusted hazard ratio [HR], 1.27 and 0.99; 95%CI: 0.84-1.92 and 0.63-1.56; p = 0.26 and 0.97) or DL (HR, 1.44 and 1.06; 95%CI: 0.86-2.42 and 0.67-1.68; p = 0.17 and 0.80) was not prognostic. CT-VPI by an attending radiologist was prognostic only in radiologically solid tumors (HR, 1.82; 95%CI: 1.07-3.07; p = 0.03).

CONCLUSION

The diagnostic performance and prognostic value of CT-VPI are limited in clinical stage I lung adenocarcinomas. This feature may be applied for radiologically solid tumors, but substantial reader variability should be overcome.

CLINICAL RELEVANCE STATEMENT

Although the diagnostic performance and prognostic value of CT-VPI are limited in clinical stage I lung adenocarcinomas, this parameter may be applied for radiologically solid tumors with appropriate caution regarding inter-reader variability.

KEY POINTS

• Use of CT-defined visceral pleural invasion in clinical staging should be cautious, because prognostic value of CT-defined visceral pleural invasion remains unexplored. • Diagnostic performance and prognostic value of CT-defined visceral pleural invasion varied among radiologists and deep learning. • Role of CT-defined visceral pleural invasion in clinical staging may be limited to radiologically solid tumors.

EGFR mutation impacts recurrence in high-risk early-stage lung adenocarcinoma in the IASLC grading system

INTRODUCTION

The developments of perioperative treatments for patients with high-risk early-stage lung cancer are ongoing, however, real-world data and evidence of clinical significance of genetic aberration are lacking in this population. This study aimed to identify patients with early-stage lung adenocarcinoma at high risk for recurrence based on pathological indicators of poor prognosis, including the International Association for the Study of Lung Cancer (IASLC) grade, and elucidate the prognostic impact of epidermal growth factor receptor mutation (EGFRm) status.

METHODS

This retrospective study included 494 consecutive patients who underwent complete resection for pathological stage I lung adenocarcinoma between 2011 and 2016. The patients were evaluated for EGFRm and IASLC grade. Multivariable analysis was used to identify pathological factors for poor prognosis associated with recurrence-free survival (RFS) and overall survival (OS). Patients with any one of these factors were classified into the high-risk group. The prognostic impact of EGFRm was evaluated using RFS, OS, and cumulative recurrence proportion.

RESULTS

Multivariable analysis for RFS and OS revealed that IASLC grade 3, pathological invasion size>2 cm, and presence of lymphovascular invasion were indicators of poor prognosis. EGFRm-positive patients had a higher incidence of all types of recurrence, including central nervous system (CNS) metastasis and distant metastasis in high-risk group, but not in low-risk group.

CONCLUSIONS

This study provides evidence that patients with EGFRm-positive stage I lung adenocarcinoma in the high-risk group have an increased risk of recurrence, including CNS metastasis. These findings highlight the need for development of adjuvant treatment in this population.

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.

Pleural Carcinoembryonic Antigen and Maximum Standardized Uptake Value as Predictive Indicators of Visceral Pleural Invasion in Clinical T1N0M0 Lung Adenocarcinoma

Background

Visceral pleural invasion (VPI) is a poor prognostic factor that contributes to the upstaging of early lung cancers. However, the preoperative assessment of VPI presents challenges. This study was conducted to examine intraoperative pleural carcinoembryonic antigen (pCEA) level and maximum standardized uptake value (SUVmax) as predictive markers of VPI in patients with clinical T1N0M0 lung adenocarcinoma.

Methods

A retrospective review was conducted of the medical records of 613 patients who underwent intraoperative pCEA sampling and lung resection for non-small cell lung cancer. Of these, 390 individuals with clinical stage I adenocarcinoma and tumors ≤30 mm were included. Based on computed tomography findings, these patients were divided into pleural contact (n=186) and non-pleural contact (n=204) groups. A receiver operating characteristic (ROC) curve was constructed to analyze the association between pCEA and SUVmax in relation to VPI. Additionally, logistic regression analysis was performed to evaluate risk factors for VPI in each group.

Results

ROC curve analysis revealed that pCEA level greater than 2.565 ng/mL (area under the curve [AUC]=0.751) and SUVmax above 4.25 (AUC=0.801) were highly predictive of VPI in patients exhibiting pleural contact. Based on multivariable analysis, pCEA (odds ratio [OR], 3.00; 95% confidence interval [CI], 1.14-7.87; p=0.026) and SUVmax (OR, 5.25; 95% CI, 1.90-14.50; p=0.001) were significant risk factors for VPI in the pleural contact group.

Conclusion

In patients with clinical stage I lung adenocarcinoma exhibiting pleural contact, pCEA and SUVmax are potential predictive indicators of VPI. These markers may be helpful in planning for lung cancer surgery.

Predicting visceral pleural invasion in lung adenocarcinoma presenting as part-solid density utilizing a nomogram model combined with radiomics and clinical features

BACKGROUND

To develop and validate a preoperative nomogram model combining the radiomics signature and clinical features for preoperative prediction of visceral pleural invasion (VPI) in lung nodules presenting as part-solid density.

METHODS

We retrospectively reviewed 156 patients with pathologically confirmed invasive lung adenocarcinomas after surgery from January 2016 to August 2019. The patients were split into training and validation sets by a ratio of 7:3. The radiomic features were extracted with the aid of FeAture Explorer Pro (FAE). A CT-based radiomics model was constructed to predict the presence of VPI and internally validated. Multivariable regression analysis was conducted to construct a nomogram model, and the performance of the models were evaluated with the area under the receiver operating characteristic curve (AUC) and compared with each other.

RESULTS

The enrolled patients were split into training (n = 109) and validation sets (n = 47). A total of 806 features were extracted and the selected 10 optimal features were used in the construction of the radiomics model among the 707 stable features. The AUC of the nomogram model was 0.888 (95% CI: 0.762-0.961), which was superior to the clinical model (0.787, 95% CI: 0.643-0.893; p = 0.049) and comparable to the radiomics model (0.879, 95% CI: 0.751-0.965; p > 0.05). The nomogram model achieved a sensitivity of 90.5% and a specificity of 76.9% in the validation dataset.

CONCLUSIONS

The nomogram model could be considered as a noninvasive method to predict VPI with either highly sensitive or highly specific diagnoses depending on clinical needs.

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.

The International Association for the Study of Lung Cancer Thymic Epithelial Tumor Staging Project: Proposal for the T Component for the Forthcoming (Ninth) Edition of the TNM Classification of Malignant Tumors

INTRODUCTION

A TNM-based stage classification system of thymic epithelial tumors was adopted for the eighth edition of the stage classification of malignant tumors. The Thymic Domain of the Staging and Prognostics Factor Committee of the International Association for the Study of Lung Cancer developed a new database with the purpose to make proposals for the ninth edition stage classification system. This article outlines the proposed definitions for the T categories for the ninth edition TNM stage classification of thymic malignancies.

METHODS

A worldwide collective database of 11,347 patients with thymic epithelial tumors was assembled. Analysis was performed on 9147 patients with available survival data. Overall survival, freedom-from-recurrence, and cumulative incidence of recurrence were used as outcome measures. Analysis was performed separately for thymomas, thymic carcinomas, and neuroendocrine thymic tumors.

RESULTS

Proposals for the T categories include the following: T1 category is divided into T1a (≤5 cm) and T1b (>5 cm), irrespective of mediastinal pleura invasion; T2 includes direct invasion of the pericardium, lung, or phrenic nerve; T3 denotes direct invasion of the brachiocephalic vein, superior vena cava, chest wall, or extrapericardial pulmonary arteries and veins; and T4 category remains the same as in the eighth edition classification, involving direct invasion of the aorta and arch vessels, intrapericardial pulmonary arteries and veins, myocardium, trachea, or esophagus.

CONCLUSIONS

The proposed T categories for the ninth edition of the TNM classification provide good discrimination in outcome for the T component of the TNM-based stage system of thymic epithelial tumors.

Artificial intelligence-based recurrence prediction outperforms classical histopathological methods in pulmonary adenocarcinoma biopsies

INTRODUCTION

Between 10 and 50% of early-stage lung adenocarcinoma patients experience local or distant recurrence. Histological parameters such as a solid or micropapillary growth pattern are well-described risk factors for recurrence. However, not every patient presenting with such a pattern will develop recurrence. Designing a model which can more accurately predict recurrence on small biopsy samples can aid the stratification of patients for surgery, (neo-)adjuvant therapy, and follow-up.

MATERIAL AND METHODS

In this study, a statistical model on biopsies fed with histological data from early and advanced-stage lung adenocarcinomas was developed to predict recurrence after surgical resection. Additionally, a convolutional neural network (CNN)-based artificial intelligence (AI) classification model, named AI-based Lung Adenocarcinoma Recurrence Predictor (AILARP), was trained to predict recurrence, with an ImageNet pre-trained EfficientNet that was fine-tuned on lung adenocarcinoma biopsies using transfer learning. Both models were validated using the same biopsy dataset to ensure that an accurate comparison was demonstrated.

RESULTS

The statistical model had an accuracy of 0.49 for all patients when using histology data only. The AI classification model yielded a test accuracy of 0.70 and 0.82 and an area under the curve (AUC) of 0.74 and 0.87 on patch-wise and patient-wise hematoxylin and eosin (H&E) stained whole slide images (WSIs), respectively.

CONCLUSION

AI classification outperformed the traditional clinical approach for recurrence prediction on biopsies by a fair margin. The AI classifier may stratify patients according to their recurrence risk, based only on small biopsies. This model warrants validation in a larger lung biopsy cohort.

Development and validation of 18F-FDG PET/CT radiomics-based nomogram to predict visceral pleural invasion in solid lung adenocarcinoma

OBJECTIVES

This study aimed to establish a radiomics model based on 18F-FDG PET/CT images to predict visceral pleural invasion (VPI) of solid lung adenocarcinoma preoperatively.

METHODS

We retrospectively enrolled 165 solid lung adenocarcinoma patients confirmed by histopathology with 18F-FDG PET/CT images. Patients were divided into training and validation at a ratio of 0.7. To find significant VPI predictors, we collected clinicopathological information and metabolic parameters measured from PET/CT images. Three-dimensional (3D) radiomics features were extracted from each PET and CT volume of interest (VOI). Receiver operating characteristic (ROC) curve was performed to determine the performance of the model. Accuracy, sensitivity, specificity and area under curve (AUC) were calculated. Finally, their performance was evaluated by concordance index (C-index) and decision curve analysis (DCA) in training and validation cohorts.

RESULTS

165 patients were divided into training cohort (n = 116) and validation cohort (n = 49). Multivariate analysis showed that histology grade, maximum standardized uptake value (SUVmax), distance from the lesion to the pleura (DLP) and the radiomics features had statistically significant differences between patients with and without VPI (P < 0.05). A nomogram was developed based on the logistic regression method. The accuracy of ROC curve analysis of this model was 75.86% in the training cohort (AUC: 0.867; C-index: 0.867; sensitivity: 0.694; specificity: 0.889) and the accuracy rate in validation cohort was 71.55% (AUC: 0.889; C-index: 0.819; sensitivity: 0.654; specificity: 0.739).

CONCLUSIONS

A PET/CT-based radiomics model was developed with SUVmax, histology grade, DLP, and radiomics features. It can be easily used for individualized VPI prediction.

Predictive value of SUVmax in visceral pleural invasive lung adenocarcinoma with different diameters

OBJECTIVES

This study aimed to investigate predictive visceral pleural invasion (VPI) occurrence value of the maximum standardized uptake value (SUVmax) in patients with lung adenocarcinoma (LA).

PATIENTS AND METHODS

A total of 388 LA patients were divided into D1ab, D1c, D1, D2, D2a, D2b, D3, and all patient groups based on their tumor diameter (D). Patients were also classified into negative VPI (VPI-n) and positive VPI (VPI-p) groups according to VPI presence. SUVmax of patients was measured with 18F-fluorodeoxyglucose (FDG) by PET/computed tomography (18F-PET/CT). Receiver operating characteristic (ROC) analysis and the area under curve (AUC) of SUVmax were applied to determine optimal cut-off value for predicting VPI occurrence.

RESULTS

There were significant differences in SUVmax between VPI-n and VPI-p groups ( P  < 0.05) at the same tumor diameter. SUVmax cut-off value and sensitivity (Se,%) of VPI occurrence in each group were following: D1ab was 3.79 [AUC = 0.764, P  < 0.001], Se86.11%; D1c was 5.47 (AUC = 0.706, P  < 0.001), Se 93.75%; D1 was 5.49 (AUC = 0.731, P  < 0.001), Se 79.76%; D2 was 7.36 (AUC = 0.726, P  < 0.001), Se81.67%. All patient group was 7.26 (AUC = 0.735, P  < 0.001), Se74.19%.

CONCLUSION

In LA patients with the same diameter, SUVmax of the VPI-p group was significantly higher than that of the VPI-n group. The cut-off value of SUVmax for predicting VPI of T1 stage, T1 substages, and T2 stage LA could be determined through ROC curve. SUVmax measurement by PET/CT scan in stratified tumor size is helpful for predicting VPI occurrences of the physician.

Upstaged from cT1a-c to pT2a lung cancer, related to visceral pleural invasion patients, after segmentectomy: is it an indication to complete resection to lobectomy?

OBJECTIVES

Segmentectomy may be indicated for T1a-cN0 non-small-cell lung cancer. However, several patients are upstaged pT2a at final pathological examination due to visceral pleural invasion (VPI). As resection is usually not completed to lobectomy, this may raise issue of potential worse prognosis. The aim of this study is to compare prognosis of VPI upstaged cT1N0 patients operated on by segmentectomy or lobectomy.

METHODS

Data of patients from 3 centres were analysed. This was a retrospective study, of patients operated on from April 2007 to December 2019. Survival and recurrence were assessed by Kaplan-Meier method and cox regression analysis.

RESULTS

Lobectomy and segmentectomy were performed in 191 (75.4%) and in 62 (24.5%) patients, respectively. No difference in 5-year disease-free survival rate between lobectomy (70%) and segmentectomy (64.7%) was observed. There was no difference in loco-regional recurrence, nor in ipsilateral pleural recurrence. The distant recurrence rate was higher (P = 0.027) in the segmentectomy group. Five-year overall survival rate was similar for both lobectomy (73%) and segmentectomy (75.8%) groups. After propensity score matching, there was no difference in 5-year disease-free survival rate (P = 0.27) between lobectomy (85%) and segmentectomy (66.9%), and in 5-year overall survival rate (P = 0.42) between the 2 groups (lobectomy 76.3% vs segmentectomy 80.1%). Segmentectomy was not impacting neither recurrence, nor survival.

CONCLUSIONS

Detection of VPI (pT2a upstage) in patients who underwent segmentectomy for cT1a-c non-small-cell lung cancer does not seem to be an indication to extend resection to lobectomy.

Predicting pleural invasion of invasive lung adenocarcinoma in the adjacent pleura by imaging histology

The aim of the present study was to develop a non-invasive method based on histological imaging and clinical features for predicting the preoperative status of visceral pleural invasion (VPI) in patients with lung adenocarcinoma (LUAD) located near the pleura. VPI is associated with a worse prognosis of LUAD; therefore, early and accurate detection is critical for effective treatment planning. A total of 112 patients with preoperative computed tomography presentation of adjacent pleura and postoperative pathological findings confirmed as invasive LUAD were retrospectively enrolled. Clinical and histological imaging features were combined to develop a preoperative VPI prediction model and validate the model's efficacy. Finally, a nomogram for predicting LUAD was established and validated using a logistic regression algorithm. Both the clinical signature and radiomics signature (Rad signature) exhibited a perfect fit in the training cohort. The clinical signature was overfitted in the testing cohort, whereas the Rad signature showed a good fit. To combine clinical and radiomics signatures for optimal performance, a nomogram was created using the logistic regression algorithm. The results indicated that this approach had the highest predictive performance, with an area under the curve of 0.957 for the clinical signature and 0.900 for the Rad signature. In conclusion, histological imaging and clinical features can be combined in columnar maps to predict the preoperative VPI status of patients with adjacent pleural infiltrative lung carcinoma.

A Novel Systematic Oxidative Stress Score Predicts the Survival of Patients with Early-Stage Lung Adenocarcinoma

This study aimed to construct an effective nomogram based on the clinical and oxidative stress-related characteristics to predict the prognosis of stage I lung adenocarcinoma (LUAD). A retrospective study was performed on 955 eligible patients with stage I LUAD after surgery at our hospital. The relationship between systematic-oxidative-stress biomarkers and the prognosis was analyzed. The systematic oxidative stress score (SOS) was established based on three biochemical indicators, including serum creatinine (CRE), lactate dehydrogenase (LDH), and uric acid (UA). SOS was an independent prognostic factor for stage I LUADs, and the nomogram based on SOS and clinical characteristics could accurately predict the prognosis of these patients. The nomogram had a high concordance index (C-index) (0.684, 95% CI, 0.656–0.712), and the calibration curves for recurrence-free survival (RFS) probabilities showed a strong agreement between the nomogram prediction and actual observation. Additionally, the patients were divided into two groups according to the cut-off value of risk points based on the nomogram, and a significant difference in RFS was observed between the high-risk and low-risk groups (p < 0.0001). SOS is an independent prognostic indicator for stage I LUAD. These things considered, the constructed nomogram based on SOS could accurately predict the survival of those patients.

Tumour-pleura relationship on CT is a risk factor for occult lymph node metastasis in peripheral clinical stage IA solid adenocarcinoma

OBJECTIVES

To investigate whether the tumour-pleura relationship on computed tomography (CT) is a risk factor for occult lymph node metastasis (OLNM) in peripheral clinical stage IA solid adenocarcinoma.

METHODS

A total of 232 patients were included in the study. The tumour-pleura relationship was divided into four types: type 1, the tumour was unrelated to the pleura; type 2, the tumour was not in contact with the pleura, and one or more linear or striated pleural tags were visible; type 3, the tumour was not in contact with the pleura, and one or more linear or striated pleural tags with soft tissue component at the pleural end were visible; and type 4, the tumour was in contact with the pleura. Univariate and multivariate logistic regression analyses were used to identify the predictive factors, including the tumour-pleura relationship, clinical factors, conventional CT findings, and pathology-reported visceral pleural invasion, for OLNM.

RESULTS

Type 3 and 4 tumour-pleura relationships were more likely to have visceral pleural invasion than type 1 and 2 tumour-pleura relationships (p < 0.001). Univariate and multivariate logistic regression analyses revealed that the type 3 or 4 tumour-pleura relationship (OR: 3.261, p = 0.026), carcinoembryonic antigen level (OR: 3.361, p = 0.006), cytokeratin 19 fragments level (OR: 2.539, p = 0.025), and mediastinal window tumour size (OR: 1.078, p = 0.020) were predictive factors for OLNM.

CONCLUSIONS

The type 3 or 4 tumour-pleura relationship is correlated with a greater risk of OLNM in peripheral clinical stage IA solid adenocarcinoma.

KEY POINTS

• The tumour-pleura relationship on CT is a risk factor for occult lymph node metastasis in peripheral clinical stage IA solid adenocarcinoma. • Other risk factors for OLNM include CEA level, CYFRA level, and mediastinal window tumour size. • Pathology-reported visceral pleural invasion is not a risk factor for OLNM.

The location of visceral pleural invasion in stage IB patients with non-small cell lung cancer: Comparison and prognosis

OBJECTIVES

Recently, early-stage lung cancer has been drawing more attention, especially in screening and treatment. Visceral pleural invasion in stage IB cancer is considered as risk factor for poor prognosis. Herein, we aimed to study the distinction between the different locations of visceral pleural invasion.

METHODS

In this retrospective cohort study, we summarized 58,242 patient cases that underwent surgery from 2015 to 2018 at Shanghai Chest Hospital. Of those patients, 389 met the inclusion criteria. Patients with PL3 pleural invasion were excluded. The patients were dichotomized into the interlobar pleural and peripheral pleural groups. The outcomes measured were overall survival (OS) and recurrence-free survival (RFS) rates.

RESULTS

According to the initial analysis, the baseline characteristics of the two groups were largely balanced. In multivariate Cox analyses, we found that the location of visceral pleural invasion was not a risk factor for prognosis in the overall population (RFS: P = 0.726, OS: P = 0.599). However, we discovered that relative to patients with peripheral pleura invasion, those with interlobar pleura invasion, PL1 invasion, lesions with greater than 3 cm solid components, and those who underwent segmentectomy had a compromised prognosis. Additionally, tumors larger than 3 cm in size with interlobar pleura invasion showed poor prognosis in patients who underwent postoperative chemotherapy.

CONCLUSIONS

In most cases, the location of tumor invasion did not worsen the postoperative prognosis of stage IB non-small cell lung cancer patients with visceral pleural invasion. However, interlobar pleural invasion still had some potential risks compared to that of peripheral pleural invasion.

Lipid biomarkers that reflect postoperative recurrence risk in lung cancer patients who smoke: a case-control study

BACKGROUND

The risk of postoperative recurrence is higher in lung cancer patients who smoke than non-smokers. However, objective evaluation of the postoperative recurrence risk is difficult using conventional pathological prognostic factors because of their lack of reproducibility. Consequently, novel objective biomarkers that reflect postoperative risk in lung cancer patients who smoke must be identified. Because cigarette smoking and oncogenesis alter lipid metabolism in lung tissue, we hypothesized that the lipid profiles in lung cancer tissues are influenced by cigarette smoking and can reflect the postoperative recurrence risk in smoking lung cancer patients. This study aimed to identify lipid biomarkers that reflect the smoking status and the postoperative recurrence risk.

METHODS

Primary tumor tissues of lung adenocarcinoma (ADC) (n = 26) and squamous cell carcinoma (SQCC) (n = 18) obtained from surgery were assigned to subgroups according to the patient's smoking status. The ADC cohort was divided into never smoker and smoker groups, while the SQCC cohort was divided into moderate smoker and heavy smoker groups. Extracted lipids from the tumor tissues were subjected to liquid chromatography-tandem mass spectrometry analysis. Lipids that were influenced by smoking status and reflected postoperative recurrence and pathological prognostic factors were screened.

RESULTS

Two and 12 lipid peaks in the ADC and SQCC cohorts showed a significant positive correlation with the Brinkman index, respectively. Among them, in the ADC cohort, a higher lipid level consisted of three phosphatidylcholine (PC) isomers, PC (14:0_18:2), PC (16:1_16:1), and PC (16:0_16:2), was associated with a shorter recurrence free period (RFP) and a greater likelihoods of progressed T-factor (≥ pT2) and pleural invasion. In the SQCC cohort, a lower m/z 736.5276 level was associated with shorter RFP and greater likelihood of recurrence.

CONCLUSIONS

From our data, we propose three PC isomers, PC (14:0_18:2), PC (16:1_16:1), and PC (16:0_16:2), and a lipid peak of m/z 736.5276 as novel candidate biomarkers for postoperative recurrence risk in lung ADC and SQCC patients who are smokers.

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.

Feline pulmonary carcinoma: Gross, histological, metastatic, and immunohistochemical aspects

Feline pulmonary carcinoma (FPC) is an uncommon neoplasm with unique morphological features. We describe the gross, histological, metastatic, and immunohistochemical aspects of FPC, based on postmortem examinations from an 11-year retrospective study. Thirty-nine cases were selected. Predispositions were observed in senior (P < .001) and Persian (P = .039) cats. There were three gross patterns of the pulmonary tumors: (a) a large nodule and additional smaller nodules, (b) a solitary nodule, and (c) small, multifocal to coalescent nodules. Extrapulmonary metastases were present in 22/39 cases (56.4%), mainly in the regional lymph nodes (17/39, 43.5%), skeletal muscles (9/39, 23%), kidneys (6/39, 15.3%), and parietal pleura (4/39, 10.2%). The primary tumor size was correlated with the occurrence of extrapulmonary metastases (P = .002). Histologically, the tumors were classified as papillary adenocarcinoma (19/39, 48.7%), adenosquamous carcinoma (ADS) (8/39, 20.5%), acinar adenocarcinoma (6/39, 15.3%), solid adenocarcinoma (3/39, 7.6%), lepidic adenocarcinoma (2/39, 5.1%), and micropapillary adenocarcinoma (1/39, 2.5%). By immunohistochemistry, 39/39 cases (100%) were positive for pancytokeratin, 34/39 (87.1%) for thyroid transcription factor-1, and 8/39 (20.5%) for vimentin. Immunoreactivity for p40 was detected in the squamous component of all ADSs (8/8, 100%) and occasionally in the glandular component of adenocarcinomas (10/31, 32.2%). Napsin A expression was absent in all feline tissue tested. The results indicate that a modified and simplified histological classification based on current human and domestic animal systems is appropriate for cats. Additionally, this study highlights the utility of p40 as an immunohistochemical marker for the diagnosis of FPC with squamous differentiation.

[Research Progress of Relationship between Pleural Deformation and Visceral Pleural Invasion in Lung Cancer Manifesting as Ground-glass Opacity]

Visceral pleural invasion (VPI) is one of the negative prognostic factors of non-small cell lung cancer (NSCLC). With the popularization of computed tomography (CT) screening for lung cancer, more and more ground-glass nodule (GGN) have been found. However, it remains unclear whether the relationship between the pleural deformation of lung cancer manifesting as ground-glass opacity (GGO) and VPI affects the effect of sub-lobectomy, which is reviewed in this paper.
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Prognostic value of elastic lamina staining in patients with stage III colon cancer

OBJECTIVE

The objectives of this study were to analyze the difference between the preoperative radiological and postoperative pathological stages of colorectal cancer (CRC) and explore the feasibility of elastic lamina invasion (ELI) as a prognostic marker for patients with stage III colon cancer.

METHODS

A total of 105 consecutive patients underwent radical surgery (R0 resection) for stage III colon cancer at the Cancer Hospital of China Medical University between January 2015 and December 2017. Clinicopathological features, including radiological stage and elastic lamina staining, were analyzed for prognostic significance in stage III colon cancer.

RESULTS

A total of 105 patients with stage III colon cancer who met the criteria and had complete data available were included. The median follow-up period of survivors was 41 months. During the follow-up period, 33 (31.4%) patients experienced recurrence after radical resection, and the 3-year disease-free survival (DFS) rate was 64.8%. The consistency between preoperative radiological and postoperative pathological staging was poor (κ = 0.232, P < 0.001). The accuracy of ≤ T2 stage diagnoses was 97.1% (102/105), that of T3 stage was 60.9% (64/105), that of T4a stage was 68.6% (72/105) and that of T4b stage was 91.4% (96/105). The DFS rate of T3 ELI (+) patients was significantly lower than that of both T3 ELI (-) patients (P = 0.000) and pT4a patients (P = 0.013). The DFS rate of T3 ELI (-) patients was significantly higher than that of pT4b patients (P=0.018). T3 ELI (+) (HR (Hazard ratio), 8.444 [95% CI, 1.736-41.067]; P = 0.008), T4b (HR, 57.727[95% CI, 5.547-600.754]; P = 0.001), N2 stage (HR, 10.629 [95% CI, 3.858-29.286]; P < 0.001), stage III (HR, 0.136 [95% CI, 0.31-0.589]; P = 0.008) and perineural invasion (PNI) (HR, 8.393 [95% CI, 2.094-33.637]; P = 0.003) were independent risk factors for postoperative recurrence of stage III colon cancer.

CONCLUSIONS

The consistency between preoperative radiological and postoperative pathological staging was poor, especially for tumors located in the ascending colon and descending colon. Elastic lamina staining is expected to become a stratified indicator of recurrence risk for patients with stage III colon cancer and a guide for individualized adjuvant chemotherapy, thus improving patient prognosis.

Prognostic value of CD4+ T lymphopenia in non-small cell lung Cancer

BACKGROUND

There is a paucity of data regarding the prognostic influence of peripheral blood CD4+ T lymphopenia in non-small cell lung cancer (NSCLC). Therefore, we investigated the prognostic value of T lymphopenia in NSCLC.

MATERIALS

Treatment-naive patients with a pathological diagnosis of NSCLC, at clinical stage I to IV were included in the prospective TELOCAP1 study. Lymphocytes count was evaluated in peripheral blood by flow cytometry. CD4+ and CD8+ T lymphopenia were defined as an absolute count of < 500/μL and < 224/μL respectively. The prognostic value of T lymphopenia was analyzed in the whole population, in local/loco-regional (stage I-IIIB) and in advanced (stage IV) NSCLC disease, using the Kaplan-Meier method and Cox regression models for survival curves and multivariate analysis, respectively.

RESULTS

Between July 2010 and January 2014, 169 evaluable patients with clinical stage I to IV NSCLC were prospectively enrolled. The prevalence of CD4+ and CD8+ T lymphopenia was similar in the study population (around 29%). Patients with CD4+ T lymphopenia showed lower overall survival than those with CD4+ T lymphocytes count > 500/μL (median overall survival (OS) 16.1 versus 21.7 months, hazard ratio (HR): 1.616 [95% CI: 1.1-2.36], p = 0.012). This association with OS was especially marked in local/loco-regional NSCLC stages (median OS, 21.8 versus 72 months, respectively, HR: 1.88 [95% CI: 0.9-3.8], p = 0.035). Multivariate analysis confirmed the worse prognosis associated with CD4+ T lymphopenia in local/loco-regional NSCLC, but not in metastatic patients (HR 2.028 [95% CI = 1.065-3.817] p = 0.02). Restricted cubic spline analysis showed that patients with CD4+ T lymphocytes count ≤500/μL displayed a high risk of death regardless of NSCLC clinical stage. There was no obvious relationship between CD8+ T lymphopenia and clinical outcome.

CONCLUSION

We identified CD4+ T lymphopenia as an independent prognostic factor in local/loco-regional stages of NSCLC and CD4+ T lymphopenia is also associated with a high risk of death, regardless of NSCLC clinical stage.

TRIAL REGISTRATION

EUDRACT: 2009-A00642-55.

Non-small Cell Lung Cancer Surpassing the Elastic Layer Should Remain Classified as pT2a

We aimed to evaluate the prognostic value of visceral pleural invasion on the survival of node-negative non-small cell lung cancer ≤3 cm using a large cohort. The Kaplan-Meier method was used to compare overall survival (OS); competing risk analysis with Fine-Gray's test was used to compare cancer- specific survival between groups. The least absolute shrinkage and selection operator penalized Cox regression model was used to identify prognostic factors. In total, 9725 eligible cases were included in this study, and they were separated into 3 groups: tumor invasion beneath the elastic layer (PL0), 8837 cases; tumor invasion surpassing the elastic layer (PL1), 505 cases; and tumor invasion to the visceral pleural surface (PL2), 383 cases. Visceral pleural invasion was more likely to occur in poorly differentiated and larger-sized tumors. Survival curves displayed that PL0 conferred better survival rates than PL1 and PL2, and PL1 achieved outcomes equivalent to those of PL2. Tumor size and histology subset analyses further corroborated this conclusion. Least absolute shrinkage and selection operator -penalized Cox regression analysis confirmed that PL status was an independent prognostic factor for both OS and cancer- specific survival. This study supported the notion that in node-negative non-small cell lung cancer ≤3 cm, PL1 patients should remain classified as pT2a, which could improve staging accuracy.

Spread Through Air Spaces (STAS) Is an Independent Prognostic Factor in Resected Lung Squamous Cell Carcinoma

Objective: There is no histoprognostic grading for lung squamous cell carcinoma (LUSC). Different prognostic factors have been described in the recent literature and are not always studied in parallel. Our objective was to search for morphological histopathological prognostic factors in LUSC. Materials and Methods: In this single-center retrospective study of 241 patients, all patients with LUSC who underwent surgical excision over a 12-year period were included. The primary endpoint was 5-year overall survival. Results: STAS was present in 86 (35.7%) patients. The presence of Spread Through Air Spaces (STAS) was correlated with tumor location (p < 0.001), pathological stage (p = 0.039), tumor differentiation (p = 0.029), percentage of necrosis (p = 0.004), presence of vascular and/or lymphatic emboli, budding (p = 0.02), single cell invasion (p = 0.002) and tumor nest size (p = 0.005). The percentage of tumor necrosis was correlated with the overall survival at 5 years: 44.6% of patients were alive when the percentage of necrosis was ≥50%, whereas 68.5% were alive at 5 years when the necrosis was <30% (p < 0.001). When vasculolymphatic emboli were present, the percentage of survival at 5 years was 42.5% compared to 65.5% when they were absent (p = 0.002). The presence of isolated cell invasion was correlated with a lower 5-year survival rate: 51.1% in the case of presence, versus 66% in the case of absence (p = 0.02). In univariate analysis, performance status, pathological stage pT or pN, pleural invasion, histopathological subtype, percentage of tumor necrosis, vasculolymphatic invasion, single-cell invasion, budding and tumor nest size correlated with the percentage of survival at 5 years. On multivariate analysis, only STAS > 3 alveoli (HR, 2.74; 95% CI, 1.18−6.33) was related to overall survival. Conclusion: In conclusion, extensive STAS is an independent factor of poor prognosis in LUSC. STAS is correlated with the presence of other poor prognostic factors such as emboli and pleural invasion and would reflect greater tumor aggressiveness.

Role of visceral pleural invasion and tumor sizing at CT of resected NSCLC in clinical-radiological and pathological T agreement

OBJECTIVE

To describe in non-small cell lung cancer (NSCLC) the impact of visceral pleural invasion (VPI) and of tumor sizing assessed at computed tomography (CT) on the agreement between clinical-radiological and pathological T staging and its prognostic value.

METHODS

Patients affected by NSCLC treated by surgery in the period from January 2017 to September 2020 were retrospectively evaluated. Exclusion criteria were: (1) baseline CT not performed in our hospital; (2) failure of software segmentation at CT of the primary lesion. Clinical-radiological T (cT) was assessed at baseline CT, evaluating in particular T size by semi-automatic tool and VPI (cVPI) visually. Pathological T (pT) and VPI (pVPI) were recorded by pathological report and obtained after formalin-fixation and eventual elastic stain on surgical specimen. The agreement between cT and pT was evaluated by calculating the weighted kappa by Cohen (κ_w); the association between progression free survival (PFS) with both cT and pT was assessed by the Cox regression analysis.

RESULTS

The study included 84 NSCLC in 82 patients (median age 71 years, IQR 63-76 years; females 22/82, 27%). The agreement between cT and pT was poor (κ_w 0.302, 95%CI 0.158-0.447). The main causes of disagreement were CT oversizing (21%) and false positive cVPI (29%). A significant association was found between PFS and pT2-T3 (HR 2.75, 95%CI 1.21-6.25, p=0.015) but not with cT2-T3 (not retained in the model).

CONCLUSIONS

False positive cVPI and oversizing at CT are causes of disagreement between cT and pT in around one-third of resected NSCLC. PFS was significantly associated with pT but not with cT.

Updated Prognostic Factors in Localized NSCLC

Lung cancer is the most common cause of cancer mortality worldwide, and non-small cell lung cancer (NSCLC) represents 80% of lung cancer subtypes. Patients with localized non-small cell lung cancer may be considered for upfront surgical treatment. However, the overall 5-year survival rate is 59%. To improve survival, adjuvant chemotherapy (ACT) was largely explored and showed an overall benefit of survival at 5 years < 7%. The evaluation of recurrence risk and subsequent need for ACT is only based on tumor stage (TNM classification); however, more than 25% of patients with stage IA/B tumors will relapse. Recently, adjuvant targeted therapy has been approved for EGFR-mutated resected NSCLC and trials are evaluating other targeted therapies and immunotherapies in adjuvant settings. Costs, treatment duration, emergence of resistant clones and side effects stress the need for a better selection of patients. The identification and validation of prognostic and theranostic markers to better stratify patients who could benefit from adjuvant therapies are needed. In this review, we report current validated clinical, pathological and molecular prognosis biomarkers that influence outcome in resected NSCLC, and we also describe molecular biomarkers under evaluation that could be available in daily practice to drive ACT in resected NSCLC.

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 clinical prognostic factors of patients with stage IB lung adenocarcinoma

Background

Lung adenocarcinoma (ADC) at stage IB has its own prognostic characteristics. This study aimed to investigate the clinical factors that may affect the prognosis of patients with stage IB ADC.

Methods

The data of ADC cases were selected from the Surveillance, Epidemiology, and End Results (SEER) database (2010–2016) and patients in Zhongshan Hospital, Fudan University (Department of Thoracic Surgery, 2015–2016). Kaplan-Meier method was used to obtain the overall survival (OS). Factors that significantly related to the prognosis were evaluated by univariate and multivariate analysis (UVA, MVA) using the Cox model. A nomogram was developed and validated to predict the 3-year OSs of those patients.

Results

7,605 patients with stage IB ADC were included ultimately and were divided into two groups, a training cohort (n=5,324) and a test cohort (n=2,281). Besides, there was a validation cohort (n=272) for the verification of the nomogram model. Those with significantly older age, male, the white race, lower grades of tumor differentiation, larger tumor size (31–40 mm) without pleural layer (PL) invasion as well as receiving sublobectomy suffered from poorer survival (P<0.001), which were identified as independent factors for stage IB ADC (P<0.001), and according to which, a nomogram model was created.

Conclusions

Age, sex, race, histological grade, surgery to the primary site, and tumor size combined with PL invasion were independent risk factors for stage IB ADC, based on which a nomogram was constructed to predict the prognosis.

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.

Pleural Invasion Depth of Disseminated Nodules in Patients with Stage IVa or Recurrent Thymoma: Assessment, Curative Impact, and Surgical Outcomes

BACKGROUND

Thymoma patients with pleural dissemination are difficult to manage, and their treatment strategy remains undefined. This study aimed to investigate the clinicopathologic features of these patients, focusing on the association between the depth of pleural invasion and prognosis.

METHODS

Between 2003 and 2019, the study identified 120 disseminated lesions in 20 thymoma patients. Seven patients had de novo stage IVa thymoma and 13 were recurrent cases. Extrapleural pneumonectomy was performed for 8 patients and debulking surgery for 12 patients. Invasion depth of pleural tumors was classified into two groups: when the disseminated tumors invaded the pleura beneath the elastic layer, the tumor was diagnosed as Da, and when the disseminated tumors invaded the pleura beyond the elastic layer, the tumor was diagnosed as Db.

RESULTS

Of 120 nodules, 31 (26%), found in eight patients with recurrent malignancies, were classified as Db. The pathologic status of the surgical margin (PSM) was positive in eight patients, seven of whom had Db nodules. The 5-year overall survival (OS) rate was 100% in the Da group and 75% in the Db group (P = 0.02). The 5-year progression-free survival (PFS) rate was 66.7% in the Da group and 25% in the Db group (P = 0.02). Cox univariate analysis showed that PFS was significantly influenced by the depth of invasion (P = 0.04) and PSM (P = 0.03).

CONCLUSION

Depth of pleural invasion may influence survival outcomes for thymoma patients with pleural dissemination. The patients in this study with Da-disseminated nodules had an increased probability of a longer OS and PFS and tended to achieve negative PSM compared with the patients with Db.

Prognostic relevance of pleural invasion for resected NSCLC patients undergoing adjuvant treatments: A propensity score-matched analysis of SEER database

BACKGROUND

Adjuvant chemotherapy demonstrated a clear benefit in resected non-small cell lung cancer (NSCLC) with nodal disease (stages II-III), and a minimal benefit in tumors >4 cm (stage II, TNM 8th edition). Pleural invasion (PL), classified as visceral pleural invasion (VPI, which includes PL1 and PL2, and parietal pleural invasion (PL3), is an established negative prognostic factor. However, whether PL should influence the decisional algorithm of postoperative chemotherapy is controversial.

METHODS

A survival analysis of NSCLC patients who underwent radical surgery between 2010 and 2015 included in the SEER database was performed. Tumor stage and size, number of examined and positive nodes, histology, PL, and treatment data were extracted. Propensity score matching was performed. The benefit of chemotherapy was analyzed in two subgroups: standard of care (SOC), including patients with positive nodes or tumors ≥ 4 cm; non-SOC, including patients with tumors < 4 cm and negative nodes.

RESULTS

Records of 30,858 patients were extracted. 11,708 patients were included in the propensity score-matched analysis. In the SOC subgroup, including 8089 patients, all pleural invasion degrees were associated with progressively increased risk for death and shorter overall survival (OS), independently from chemotherapy administration. However, chemotherapy significantly improved the median OS regardless of the extent of PL. In the non-SOC subgroup, including 3619 patients, only PL3 was associated with increased mortality. The administration of chemotherapy did not improve survival outcomes.

CONCLUSION

Chemotherapy should be strongly recommended in patients in the SOC-subgroup with pleural invasion. VPI is not associated with unfavorable prognosis in the non-SOC subgroup.

Modification of Pathologic T Classification for Non-small Cell Lung Cancer With Visceral Pleural Invasion: Data From 1,055 Cases of Cancers ≤ 3 cm

BACKGROUND

Visceral pleural invasion (VPI) with PL1 or PL2 increases the T classification from T1 to T2 in non-small cell lung cancers (NSCLCs) ≤ 3 cm. We proposed a modified T classification based on VPI to guide adjuvant therapy.

RESEARCH QUESTION

Is it reasonable to upstage PL1-positive cases from T1 to T2 for NSCLCs ≤ 3 cm?

STUDY DESIGN AND METHODS

In total, 1,055 patients with resected NSCLC were retrospectively included. Tumor sections were restained with hematoxylin and eosin stain and Victoria blue elastic stain for the elastic layer. Disease-free survival (DFS) and overall survival (OS) were calculated by the Kaplan-Meier method. Subgroup analysis and a Cox proportional hazards model were used to further determine the impact of VPI on survival.

RESULTS

The extent of VPI was diagnosed as PL0 in 824 patients, PL1 in 133 patients, and PL2 in 98 patients. The 5-year DFS rates of patients with PL0, PL1, and PL2 were 62.6%, 60.2%, and 28.8% (P < .01), whereas the corresponding 5-year OS rates were 78.6%, 74.4%, and 50.0% (P < .01), respectively. As predicted, the DFS and OS of patients with PL2 were much worse than those of patients with PL0 (P < .01) and PL1 (P < .01). However, both the DFS and OS of patients with PL0 and PL1 were comparable (DFS: P = .198; OS: P = .150). For node-negative cases, the DFS and OS of patients with PL0 and PL1 were also comparable (DFS: P = .468; OS: P = .388), but patients with PL2 had much worse DFS and OS than patients with PL0 (P < .01) and PL1 (P < .01). Multivariable analyses suggested that PL2, together with node positivity and poor cell differentiation, was an independent adverse prognostic factor.

INTERPRETATION

In NSCLCs ≤ 3 cm, tumors with PL1 should remain defined as T1, not T2. Overtreatment by adjuvant chemotherapy in node-negative NSCLCs ≤ 3 cm might be avoided in PL1 cases.

Pleural invasion, epidermal growth factor receptor mutation and carcinoembryonic antigen level affect pleural lavage cytology-positive status in non-small-cell lung cancer

OBJECTIVES

Pleural invasion (pl) is strongly associated with the pleural lavage cytology (PLC) status. We analysed tumours with pl and evaluated the relationship between the PLC status and pl.

METHODS

We retrospectively reviewed 428 surgically treated patients who had been diagnosed with non-small-cell lung cancer with pl and had their PLC status examined between 2000 and 2016. We investigated the influence of a PLC-positive status on the prognosis and searched for the factors predictive of a PLC-positive status.

RESULTS

Seventy-eight (18%) patients were PLC positive. The recurrence-free survival of PLC-positive patients was significantly worse than that of PLC-negative patients in pl1 and pl2, but not in pl3 (5-year recurrence-free survival rate, PLC positive versus PLC negative: pl1, 22.0% vs 60.0%, P = 0.002; pl2, 30.4% vs 59.7%, P = 0.015; pl3, 50.0% vs 59.6%, P = 0.427). A multivariable analysis showed that the degree of pl (pl2-3 versus pl1) [odds ratio (OR) 5.34, P < 0.001] was an independent predictive factor for PLC positivity. Epidermal growth factor receptor (EGFR) mutation positivity (OR 5.48, P = 0.042) and carcinoembryonic antigen (CEA) ≥5 ng/ml (OR 3.78, P = 0.042) were associated with a PLC-positive status in patients with pl2-3. We found that the PLC-positive rate in patients with pl2-3 was 35.6%; however, if the tumour was EGFR mutation positive and had CEA ≥5 ng/ml, the PLC-positive rate increased to 77%.

CONCLUSIONS

If a tumour was suspected of being pl2-3 and had EGFR mutation positivity and CEA ≥5 ng/ml, the PLC-positive rate was extremely high.

CLINICAL TRIAL REGISTRATION NUMBER

Hyogo Cancer Center, G-138.

The modification of T description according to visceral pleural invasion and tumor size from 3.1 cm to 4.0 cm in non-small cell lung cancer: A retrospective analysis based on the SEER database

OBJECTIVES

As a poor prognostic factor, visceral pleural invasion (VPI) was incorporated into non-small cell lung cancer (NSCLC) staging system. For modifying the T description of NSCLC, the prognostic value of VPI was assessed.

MATERIALS AND METHODS

From 2010-2015, data on stage pT2N0M0 NSCLC patients with tumor size (TS) from 3.1 cm to 5.0 cm who received surgery from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled retrospectively. Propensity score matching was utilized to balance the baseline factors according to different TS intervals. Overall survival (OS) was assessed by the Kaplan-Meier method and log-rank test. Univariate and multivariate analysis were applied to identify the prognostic factors. The risk factors of VPI were calculated by logistic regression model.

RESULT

The sum of 4005 resected stage pT2N0M0 NSCLC patients with TS from 3.1 cm to 5.0 cm were recruited, which had 1084 patients with VPI and 2921 patients without VPI respectively. As TS interval of 3.1-4.0 cm, the 5-year OS of patients without VPI was significantly better than those with VPI (62.6 % vs 58.7 %, P = 0.015), while the 5-year OS of patients with VPI and TS interval of 3.1-4.0 cm had no significant difference compared with patients whose TS interval of 4.1-5.0 cm (58.7 % vs 58.8 %, P = 0.918). Logistic regressive analysis manifested that older age, female, worse differentiation grade and larger TS had higher incidence of VPI (OR = 1.01, 1.25, 1.25, 1.16, respectively; P < 0.05 for all).

CONCLUSION

This study underlined the prognostic effect of VPI and suggested that early-stage NSCLC with VPI and TS interval of 3.1-4.0 cm could be appropriately upstaged from pT2a (stage pIB) to pT2b (modified stage pIIA).

Nomogram for Predicting the Relationship between the Extent of Visceral Pleural Invasion and Survival in Non-Small-Cell Lung Cancer

Objective

Although visceral pleural invasion (VPI) has already been incorporated into the TNM staging system, few studies have been conducted to evaluate the prognostic value of the extent of VPI for the survival of non-small-cell lung cancer (NSCLC) patients. Thus, we utilized the Surveillance, Epidemiology, and End Results (SEER) database to assess the correlation between the extent of VPI and survival in NSCLC.

Methods

We identified and incorporated the extent of VPI to build a prognostic nomogram in this study. Patients in the SEER database diagnosed with NSCLC (n = 87,045) from 2010 to 2015 were further analyzed and randomly assigned into either the training group (n = 60,933) or validation group (n = 26,112). Clinical variables were calculated by means of multivariate Cox regressions and incorporated into the predictive model. Subsequently, the accuracy and discrimination of nomogram were further assessed through the concordance index (C-index), calibration curves, and Kaplan–Meier curves.

Results

Multivariate analysis demonstrated that the extent of visceral pleural invasion was an independent and unfavorable prognostic factor. The C-indexes of the training and validation groups were 0.772 (95% CI: 0.770–0.774) and 0.769 (95% CI: 0.765–0.773), respectively, which revealed that the nomogram had sufficient credibility and stable predictive accuracy. The calibration curve displayed consistency between the actual and predictive values in both training and validation groups.

Conclusion

The prognostic nomogram with the extent of VPI could offer an accurate risk evaluation for patients with NSCLC. Independent external validation of this research should be conducted in the future.

Discriminating Small-Sized (2 cm or Less), Noncalcified, Solitary Pulmonary Tuberculoma and Solid Lung Adenocarcinoma in Tuberculosis-Endemic Areas

Background. Pulmonary tuberculoma can mimic lung malignancy and thereby pose a diagnostic dilemma to clinicians. The purpose of this study was to establish an accurate, convenient, and clinically practical model for distinguishing small-sized, noncalcified, solitary pulmonary tuberculoma from solid lung adenocarcinoma. Methods. Thirty-one patients with noncalcified, solitary tuberculoma and 30 patients with solid adenocarcinoma were enrolled. Clinical characteristics and CT morphological features of lesions were compared between the two groups. Multivariate logistic regression analyses were applied to identify independent predictors of pulmonary tuberculoma and lung adenocarcinoma. Receiver operating characteristic (ROC) analysis was performed to investigate the discriminating efficacy. Results. The mean age of patients with tuberculoma and adenocarcinoma was 46.8 ± 12.3 years (range, 28–64) and 61.1 ± 9.9 years (range, 41–77), respectively. No significant differences were observed concerning smoking history and smoking index, underlying disease, or tumor markers between the two groups. Univariate and multivariate analyses showed age and lobulation combined with pleural indentation demonstrated excellent discrimination. The sensitivity, specificity, accuracy, and the area under the ROC curve were 87.1%, 93.3%, 90.2%, and 0.956 (95% confidence interval (CI), 0.901–1.000), respectively. Conclusion. The combination of clinical characteristics and CT morphological features can be used to distinguish noncalcified, solitary tuberculoma from solid adenocarcinoma with high diagnostic performance and has a clinical application value.

Future Perspectives on the TNM Staging for Lung Cancer

Since its conception by Pierre Denoix in the mid-20th century, the tumor, node, and metastasis (TNM) classification has undergone seven revisions. The North American database managed by Clifton Mountain was used to inform the 2nd to the 6th editions, and an international database collected by the International Association for the Study of Lung Cancer, promoted by Peter Goldstraw, was used to inform the 7th and the 8th editions. In these two latest editions, it was evident that the impact of tumor size was much greater than it was suggested in previous editions; that the amount of nodal disease had prognostic relevance; and that the number and location of the distant metastases had prognostic implications. However, the TNM classification is not the only prognostic factor. Data are being collected now to inform the 9th edition of the TNM classification, scheduled for publication in 2024. Patient-, environment-, and tumor-related factors, including biomarkers (genetic biomarkers, copy number alterations, and protein alterations) are being collected to combine them in prognostic groups to enhance the prognosis provided by the mere anatomic extent of the tumor, and to offer a more personalized prognosis to an individual patient. International collaboration is essential to build a large and detailed database to achieve these objectives.

Imaging Assessment of Visceral Pleural Surface Invasion by Lung Cancer: Comparison of CT and Contrast-Enhanced Radial T1-Weighted Gradient Echo 3-Tesla MRI

Objective

To compare the diagnostic performance of contrast-enhanced radial T1-weighted gradient-echo 3-tesla (3T) magnetic resonance imaging (MRI) and computed tomography (CT) for the detection of visceral pleural surface invasion (VPSI). Visceral pleural invasion by non-small-cell lung cancer (NSCLC) can be classified into two types: PL1 (without VPSI), invasion of the elastic layer of the visceral pleura without reaching the visceral pleural surface, and PL2 (with VPSI), full invasion of the visceral pleura.

Materials and Methods

Thirty-three patients with pathologically confirmed VPSI by NSCLC were retrospectively reviewed. Multidetector CT and contrast-enhanced 3T MRI with a free-breathing radial three-dimensional fat-suppressed volumetric interpolated breath-hold examination (VIBE) pulse sequence were compared in terms of the length of contact, angle of mass margin, and arch distance-to-maximum tumor diameter ratio. Supplemental evaluation of the tumor-pleura interface (smooth versus irregular) could only be performed with MRI (not discernible on CT).

Results

At the tumor-pleura interface, radial VIBE MRI revealed a smooth margin in 20 of 21 patients without VPSI and an irregular margin in 10 of 12 patients with VPSI, yielding an accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F-score for VPSI detection of 91%, 83%, 95%, 91%, 91%, and 87%, respectively. The McNemar test and receiver operating characteristics curve analysis revealed no significant differences between the diagnostic accuracies of CT and MRI for evaluating the contact length, angle of mass margin, or arch distance-to-maximum tumor diameter ratio as predictors of VPSI.

Conclusion

The diagnostic performance of contrast-enhanced radial T1-weighted gradient-echo 3T MRI and CT were equal in terms of the contact length, angle of mass margin, and arch distance-to-maximum tumor diameter ratio. The advantage of MRI is its clear depiction of the tumor-pleura interface margin, facilitating VPSI detection.

Inclusion of multiple high-risk histopathological criteria improves the prediction of adjuvant chemotherapy efficacy in lung adenocarcinoma

Aims

The decision to consider adjuvant chemotherapy (AC) for non‐small cell lung cancer is currently governed by clinical stage. This study aims to assess other routinely collected pathological variables related to metastasis and survival for their ability to predict the efficacy of AC in lung adenocarcinoma.

Methods and results

A retrospective single‐centre series of 620 resected lung non‐mucinous adenocarcinoma cases from 2005 to 2015 was used. Digital images of all slides were subjected to central review, and data on tumour histopathology, AC treatment and patient survival were compiled. A statistical case matching approach was used to counter selection bias. Several high‐risk pathological criteria predict both pathological nodal involvement and early death: positive vascular invasion status (VI+) (HR = 2.10, P < 0.001), positive visceral pleural invasion status (VPI+) (HR = 2.16, P < 0.001), and solid/micropapillary‐predominant WHO tumour type (SPA/MPPA) (HR = 3.29, P < 0.001). Crucially, these criteria also identify patient groups benefiting from AC (VI + HR = 0.69, P = 0.167, VPI + HR = 0.44, P = 0.004, SPA/MPPA HR = 0.36, P = 0.006). Cases showing VI+/VPI+/SPA/MPPA histology in the absence of AC stage criteria were common (170 of 620 total), and 8 had actually received AC. This group showed much better outcomes than equivalent untreated cases in matched analysis (3‐year OS 100.0% versus 31.3%). Inclusion of patients with VI+/VPI+/SPA/MPPA histology would increase AC‐eligible patients from 51.0% to 84.0% of non‐mucinous tumours in our cohort.

Conclusions

Our data provide preliminary evidence that the consideration of AC in patients with additional high‐risk pathological indicators may significantly improve outcomes in operable lung adenocarcinoma, and that AC may be currently underused.

A prognostic score for non-small cell lung cancer resected after neoadjuvant therapy in comparison with the tumor-node-metastases classification and major pathological response

Studies validating the prognostic accuracy of the tumor-node-metastases (TNM) classification in patients with lung cancer treated by neoadjuvant therapy are scarce. Tumor regression, particularly major pathological response (MPR), is an acknowledged prognostic factor in this setting. We aimed to validate a novel combined prognostic score. This retrospective single-center study was conducted on 117 consecutive patients with non-small cell lung cancer resected after neoadjuvant treatment at a Swiss University Cancer Center between 2000 and 2016. All cases were clinicopathologically re-evaluated. We assessed the prognostic performance of a novel prognostic score (PRSC) combining T-category, lymph node status, and MPR, in comparison with the eighth edition of the TNM classification (TNM8), the size adapted TNM8 as proposed by the International Association for the Study of Lung Cancer (IASLC) and MPR alone. The isolated ypT-category and the combined TNM8 stages accurately differentiated overall survival (OS, stage p = 0.004) and disease-free survival (DFS, stage p = 0.018). Tumor regression had a prognostic impact. Optimal cut-offs for MPR emerged as 65% for adenocarcinoma and 10% for non-adenocarcinoma and were statistically significant for survival (OS p = 0.006, DFS p < 0.001). The PRSC differentiated between three prognostic groups (OS and DFS p < 0.001), and was superior compared to the stratification using MPR alone or the TNM8 systems, visualized by lower Akaike (AIC) and Bayesian information criterion (BIC) values. In the multivariate analyses, stage III tumors (HR 4.956, p = 0.003), tumors without MPR (HR 2.432, p = 0.015), and PRSC high-risk tumors (HR 5.692, p < 0.001) had significantly increased risks of occurring death. In conclusion, we support 65% as the optimal cut-off for MPR in adenocarcinomas. TNM8 and MPR were comparable regarding their prognostic significance. The novel prognostic score performed distinctly better regarding OS and DFS.

Clinical Value of 18F-FDG PET/CT in Prediction of Visceral Pleural Invasion of Subsolid Nodule Stage I Lung Adenocarcinoma

RATIONALE AND OBJECTIVES

This study investigated the utility of ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) for predicting visceral pleural invasion (VPI) of subsolid nodule (SSN) stage I lung adenocarcinoma.

MATERIALS AND METHODS

A retrospective analysis of ¹⁸F-FDG PET/CT data from 65 postsurgical cases with surgical pathology-confirmed SSN lung adenocarcinoma identified significant VPI predictors using multivariate logistic regression.

RESULTS

Nodule and solid component sizes, solid component-to-tumor ratios, pleural indentations, distances between nodules and pleura, and maximum standardized uptake values (SUVmax) differed significantly between VPI-positive (n = 30) and VPI-negative (n = 35) cases on univariate analysis. The distance between the nodule and pleura and SUVmax were significant independent VPI predictors on multivariate analysis. Areas under the curve of the distance between the nodule and pleura and SUVmax on receiver operating characteristic curves were 0.76 and 0.79, respectively; both factors were 0.90. The area under the curve of combined predictors was significantly superior to the distance between the nodule and pleura only but not SUVmax alone. The threshold of the distance between the nodule and pleura, to predict VPI was 4.50 mm, with 96.67% sensitivity, and 57.14% specificity. The threshold of SUVmax to predict VPI was 1.05, with 100% sensitivity and 60% specificity. The sensitivity and specificity of model 2 using the independent predictive factors were 96.67%, and 71.43%, respectively.

CONCLUSION

Distance between the nodule and pleura and SUVmax are independent predictors of VPI in SSN stage I lung adenocarcinoma. Further, combining these factors improves their predictive ability.

Prediction of visceral pleural invasion in lung cancer on CT: deep learning model achieves a radiologist-level performance with adaptive sensitivity and specificity to clinical needs

OBJECTIVES

To develop and validate a preoperative CT-based deep learning model for the prediction of visceral pleural invasion (VPI) in early-stage lung cancer.

METHODS

In this retrospective study, dataset 1 (for training, tuning, and internal validation) included 676 patients with clinical stage IA lung adenocarcinomas resected between 2009 and 2015. Dataset 2 (for temporal validation) included 141 patients with clinical stage I adenocarcinomas resected between 2017 and 2018. A CT-based deep learning model was developed for the prediction of VPI and validated in terms of discrimination and calibration. An observer performance study and a multivariable regression analysis were performed.

RESULTS

The area under the receiver operating characteristic curve (AUC) of the model was 0.75 (95% CI, 0.67-0.84), which was comparable to those of board-certified radiologists (AUC, 0.73-0.79; all p > 0.05). The model had a higher standardized partial AUC for a specificity range of 90 to 100% than the radiologists (all p < 0.05). The high sensitivity cutoff (0.245) yielded a sensitivity of 93.8% and a specificity of 31.2%, and the high specificity cutoff (0.448) resulted in a sensitivity of 47.9% and a specificity of 86.0%. Two of the three radiologists provided highly sensitive (93.8% and 97.9%) but not specific (48.4% and 40.9%) diagnoses. The model showed good calibration (p > 0.05), and its output was an independent predictor for VPI (adjusted odds ratio, 1.07; 95% CI, 1.03-1.11; p < 0.001).

CONCLUSIONS

The deep learning model demonstrated a radiologist-level performance. The model could achieve either highly sensitive or highly specific diagnoses depending on clinical needs.

KEY POINTS

• The preoperative CT-based deep learning model demonstrated an expert-level diagnostic performance for the presence of visceral pleural invasion in early-stage lung cancer. • Radiologists had a tendency toward highly sensitive, but not specific diagnoses for the visceral pleural invasion.

Programmed death ligand-1 expression levels, clinicopathologic features, and survival in surgically resected sarcomatoid lung carcinoma

AIM

To determine the programmed death ligand-1 (PD-L1) expression rates in sarcomatoid lung carcinomas and to compare clinicopathologic features and survival rates of PD-L1-positive and negative patients.

METHODS

PD-L1 expression was evaluated in 65 surgically resected sarcomatoid carcinomas. The clinicopathologic features of cases with PD-L1-positive and negative tumors were compared. Kaplan-Meier survival analysis was performed. Multiple Cox proportional hazard regression analysis was performed to determine independent predictors of overall survival.

RESULTS

PD-L1 antibody positivity was found in 72.3% of surgically resected sarcomatoid lung carcinomas. Regarding histopathologic subtypes, PD-L1 expression was positive in 80.4% of pleomorphic carcinomas, 62.5% of spindle- and/or giant-cell carcinomas, and 16.7% of carcinosarcomas. Pleural invasion was observed in 68.1% of PD-L1-positive cases and 27.8% of PD-L1-negative cases (P = 0.008). No difference in survival was found between PD-L1-positive and -negative tumors. The only factor significantly associated with poor survival was the pathological stage of the tumor.

CONCLUSIONS

This study reveals a high rate of PD-L1 positivity in a large number of sarcomatoid lung carcinoma cases with pleomorphic carcinoma, spindle- and/or giant-cell carcinoma, and carcinosarcoma subtypes. The only significantly different clinicopathologic feature in PD-L1-positive cases is pleural invasion. PD-L1 positivity is not a significant predictor of survival in sarcomatoid lung carcinomas.

Prognostic value of visceral pleural invasion in pure-solid and part-solid lung cancer patients

OBJECTIVE

Visceral pleural invasion (VPI) indicates poor prognosis in non-small cell lung cancer (NSCLC), and is defined as a T2 descriptor for T1-sized tumor. However, whether its prognostic impact differs between pure-solid and part-solid tumors as preoperative diagnostic imaging is controversial. We aimed to elucidate the prognostic difference of VPI in cT1-sized NSCLC according to radiological tumor type (pure-solid or part-solid).

METHODS

We retrospectively reviewed 498 NSCLC patients who underwent complete anatomical lung resection between 2009 and 2014. Patients with node-negative, cT1-sized (consolidation size, ≤ 3 cm) NSCLCs were included. VPI included pathological PL1 and PL2. The prognostic impact of VPI according to radiological tumor type was assessed using multivariate Cox regression analyses.

RESULTS

We evaluated 227 pure-solid and 271 part-solid tumors; median follow-up period was 57 months. VPI was found in 40 (17.6%) and 15 (5.5%) patients with pure-solid and part-solid tumors, respectively (p < 0.001). In pure-solid group, VPI patients showed significantly poorer overall survival (OS) rates than non-VPI patients (p = 0.003). In part-solid group, OS rates did not differ significantly according to VPI (p = 0.770). Multivariate analysis revealed that the adjusted hazard ratio (95% confidence interval) for poor OS was 2.129 (1.048-4.132, p = 0.037) for pure-solid tumors with VPI compared to pure-solid tumors without VPI, and 0.925 (0.050-4.920, p = 0.941) for part-solid tumors with VPI compared to part-solid tumors without VPI.

CONCLUSIONS

VPI had a negative prognostic impact on cT1-sized pure-solid tumors but not on part-solid tumors. Upstaging of the T-category by VPI in cT1-sized NSCLCs may be considered for pure-solid tumors.