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

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.

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.

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.

Advances in diagnosis and prediction for aggression of pure solid T1 lung cancer

A growing number of early-stage lung cancers presenting as malignant pulmonary nodules have been diagnosed because of the increased adoption of low-dose spiral computed tomography. But pure solid T1 lung cancer with ≤3 cm in the greatest dimension is not always at an early stage, despite its small size. This type of cancer can be highly aggressive and is associated with pathological involvement, metastasis, postoperative relapse, and even death. However, it is easily misdiagnosed or delay diagnosed in clinics and thus poses a serious threat to human health. The percentage of nodal or extrathoracic metastases has been reported to be >20% in T1 lung cancer. As such, understanding and identifying the aggressive characteristics of pure solid T1 lung cancer is crucial for prevention, diagnosis, and therapeutic strategies, and beneficial to improving the prognosis. With the widespread of lung cancer screening, these highly invasive pure solid T1 lung cancer will become the main advanced lung cancer in future. However, there is limited information regarding precision medicine on how to identify these "early-stage" aggressive lung cancers. To provide clinicians with new insights into early recognition and intervention of the highly invasive pure solid T1 lung cancer, this review summarizes its clinical characteristics, imaging, pathology, gene alterations, immune microenvironment, multi-omics, and current techniques for diagnosis and prediction.

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.

[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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Decreased TSPAN14 Expression Contributes to NSCLC Progression

Tspan14 is a transmembrane protein of the tetraspanin (Tspan) protein family. Different members of the Tspan family can promote or suppress tumor progression. The exact role of Tspan14 in tumor cells is unknown. Earlier, mutational inactivation of the TSPAN14 gene has been proposed to coincide with a low survival rate in NSCLC patients. This study aimed to investigate the correlation of TSPAN14 lack of function with clinicopathological features of NSCLC patients, and to elucidate the role TSPAN14 might have in NSCLC progression. TSPAN14 expression was lower in tumor cells than non-tumor cells in NSCLC patients’ samples. The decreased gene expression was correlated with a low survival rate of patients and was more frequent in patients with aggressive, invasive tumor types. Additionally, the role of decreased TSPAN14 expression in the metastatic potential of cancer cells was confirmed in NSCLC cell lines. The highly invasive NSCLC cell line (NCI-H661) had the lowest TSPAN14 gene and protein expression, whereas the NSCLC cell line with the highest TSPAN14 expression (NCI-H460) had no significant metastatic potential. Finally, silencing of TSPAN14 in these non-metastatic cancer cells caused an increased expression of matrix-degrading enzymes MMP-2 and MMP-9, followed by an elevated capacity of cancer cells to degrade gelatin. The results of this study propose TSPAN14 expression as an indicator of NSCLC metastatic potential and progression.

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.