Updates on spread through air spaces (STAS) in lung cancer.

Air space invasion of tumours, particularly spread through air spaces (STAS), is a relatively recent concept that has been identified as a novel mechanism of invasion. It has predominantly been described in lung adenocarcinoma, although it may be seen in other primary lung malignancies as well. STAS in lung cancer has been reported to have numerous associations with poor survival. The objective of this article was to review the concept of air space invasion, update findings regarding its clinical impact, and discuss controversies in the field. With this aim, we performed a PubMed search of the English-language literature. STAS has been introduced as a novel mechanism of invasion that is important for pathologists to recognise. There is a compelling body of evidence associating the presence of STAS with lower survival and suggesting that STAS is an independent prognostic factor, regardless of the stage of tumour. The standard of care for lung adenocarcinomas with STAS irrespective of size of tumour and nodal metastasis may be lobectomy rather than sublobar resection, owing to the risk of locoregional recurrence. Emerging data suggest that more work should be performed to improve consensus on and identification of STAS, including at frozen section.

Prognostic impact of spread through air spaces in patients with ≤2 cm stage IA lung adenocarcinoma.

Background: In 2015, the World Health Organization (WHO) included spread through air space (STAS) as a new invasive mode of lung cancer. As a new mode of lung cancer dissemination, STAS has a significant and negative impact on patient prognosis. The surgical approach as well as lymph node dissection (LND) for STAS-positive patients is currently unclear. The aim of this study was to investigate the impact of different surgical approaches to STAS and LND on the prognosis of patients with ≤2 cm stage IA lung adenocarcinoma (LUAD). This study also investigated the possible relationship between STAS and the micropapillary histological subtype and its impact on patient prognosis. Methods: A total of 212 patients with LUAD were included in this study from January 2016 to December 2017, and the overall survival (OS) of the patients was compared. The chi-square test and t-test were applied to compare the clinicopathological data of the patients, and the Cox model was used for the multivariate survival analysis. Results: Of the 212 patients, 93 (43.9%) were STAS positive. The univariate analysis showed that the surgical approach, LND type, micropapillary pattern (MP), solid pattern, and STAS were risk factors for OS. The multivariate analysis showed that the surgical approach, MP, and STAS were risk factors for OS. The STAS-positive patients who underwent lobectomy had a better prognosis than those who underwent sublobar resection; however, there was no significant difference between the two surgical procedures in the STAS-negative group. Additionally, the STAS-positive patients who underwent systematic lymph node dissection (SLND) had a better prognosis than those who underwent limited lymph node dissection (LLND); however, there was no significant difference between the two LNDs in the STAS-negative group. Conclusions: STAS plays an important role in patient prognosis and is an independent risk factor for OS of patients with ≤2 cm stage IA LUAD. When STAS is positive, the choice of lobectomy with SLND may result in a better long-term prognosis for patients.

A validated model to predict spread through air space in lung adenocarcinoma.

Background: Spread through air space (STAS) is currently considered to be a significant predictor of a poor outcome of pulmonary adenocarcinoma. Preoperative prediction of STAS is of great importance for treatment planning. The aim of the present study was to establish a nomogram based on computed tomography (CT) features for predicting STAS in lung adenocarcinoma and to assess the prognosis of the patients with STAS. Methods: A retrospective cohort study was performed in Wuhan Union Hospital from December 2015 to March 2021. The sample was divided into training and testing cohorts. Clinicopathologic and radiologic variables were recorded. The independent risk factors for STAS were determined by stepwise regression and then incorporated into the nomogram. Receiver operating characteristic (ROC) curves and calibration curves analysed by the Hosmer-Lemeshow test were used to evaluate the performance of the model. Decision curve analysis (DCA) was conducted to determine the clinical value of the nomogram. The Kaplan-Meier method was used for survival analysis and the multivariable Cox proportional hazards regression model was used to identify independent predictors for recurrence-free survival (RFS) and overall survival (OS). Results: The sample included 244 patients who underwent surgical resection for primary lung adenocarcinoma. The training cohort included 199 patients (68 STAS-positive and 131 STAS-negative patients), and the testing cohort included 45 patients (15 STAS-positive and 30 STAS-negative patients). The preoperative CT features associated with STAS were shape, ground-glass opacity (GGO) ratio and spicules. The nomogram including these three factors had good discriminative power, and the areas under the ROC curve were 0.875 and 0.922 for the training and testing data sets, respectively, with well-fitted calibration curves. DCA showed that the nomogram was clinically useful. STAS-positive patients had significantly worse OS and RFS than STAS-negative patients (both P<0.01). OS and RFS at 5-year for STAS-positive patients were 63.1% and 59.5%, respectively. Multivariate analysis showed that age [hazard ratio (HR), 1.1; 95% confidence interval (CI): 1.035-1.169; P=0.002], diameter (HR, 1.06; 95% CI: 1.04-1.11; P=0.03) and surgical margin (HR, 32.8; 95% CI: 6.8-158.3; P<0.001) were independent risk factors for OS. Adjuvant therapy (HR, 7.345; 95% CI: 2.52-21.41; P<0.001), N stage (N2) (HR, 0.239; 95% CI: 0.069-0.828; P=0.02) and surgical margin (HR, 15.6; 95% CI: 5.9-41.1; P<0.001) were found to be independent risk factors for RFS. Conclusions: The outcome of STAS-positive patients was worse. The nomogram incorporating the identified CT features could be applied to facilitate individualized preoperative prediction of STAS and selection of rational therapy.

Evaluation of the novel International Association for the Study of Lung Cancer grading system in adenocarcinoma with spread through air space.

Background: The International Association for the Study of Lung Cancer (IASLC) pathology panel has proposed a new grading system for invasive lung adenocarcinoma (LADC). This study aims to validate this novel grading system for invasive LADC using propensity score matching (PSM), with a specific focus on patients exhibiting spread through air space (STAS). Methods: We retrospectively analyzed the clinicopathologic features of a large cohort of 910 non-mucinous LADCs with STAS from 2017 to 2020 and classified them according to the novel grading system. We applied PSM to adjust for potential confounders between the grading groups. Kaplan-Meier and Cox proportional hazards models were adopted for prognostic evaluation. Results: The results showed that the IASLC grading system (grades 2 and 3) stratified well in terms of recurrence-free survival (RFS) and overall survival (OS) (P=0.02 and P=0.02, respectively) after matching, with Grade 3 being an independent predictor of RFS [hazard ratio (HR), 1.533; P=0.02] and OS (HR, 2.765; P=0.02) in multivariable models. The concordance index (C-index) and area under the curve (AUC) of the IASLC system were 0.719 and 0.754 for recurrence and 0.844 and 0.891 for death, respectively. In addition, anaplastic lymphoma kinase (ALK) fusion and tumor protein p53 (TP53) mutations were detected more frequently in grade 3 tumors, while epidermal growth factor receptor (EGFR) mutations were more prevalent in grade 2 tumors. The IASLC grade did not predict the benefit of adjuvant chemotherapy (ACT). Conclusions: This study suggests that the new IASLC grading system is a valuable prognostic tool for patients with STAS-positive LADC.

Deep Learning Analysis for Predicting Tumor Spread through Air Space in Early-Stage Lung Adenocarcinoma Pathology Images.

The presence of spread through air spaces (STASs) in early-stage lung adenocarcinoma is a significant prognostic factor associated with disease recurrence and poor outcomes. Although current STAS detection methods rely on pathological examinations, the advent of artificial intelligence (AI) offers opportunities for automated histopathological image analysis. This study developed a deep learning (DL) model for STAS prediction and investigated the correlation between the prediction results and patient outcomes. To develop the DL-based STAS prediction model, 1053 digital pathology whole-slide images (WSIs) from the competition dataset were enrolled in the training set, and 227 WSIs from the National Taiwan University Hospital were enrolled for external validation. A YOLOv5-based framework comprising preprocessing, candidate detection, false-positive reduction, and patient-based prediction was proposed for STAS prediction. The model achieved an area under the curve (AUC) of 0.83 in predicting STAS presence, with 72% accuracy, 81% sensitivity, and 63% specificity. Additionally, the DL model demonstrated a prognostic value in disease-free survival compared to that of pathological evaluation. These findings suggest that DL-based STAS prediction could serve as an adjunctive screening tool and facilitate clinical decision-making in patients with early-stage lung adenocarcinoma.

Association between tumor cell in air space and treatment outcomes in early-stage lung cancer treated with stereotactic body radiation therapy.

Background and purpose: Spread-through air space (STAS) is an unfavorable factor in patients with lung cancer treated with surgery. However, the relationship between the treatment outcomes of stereotactic body radiation therapy (SBRT) for lung cancer and STAS has not been adequately investigated. This study aimed to evaluate the impact of tumor cells in the air space (TCIAS), which show a STAS burden, on treatment outcomes in patients with early-stage lung cancer treated with SBRT. Materials and methods: Data of patients who underwent SBRT for early-stage lung cancer treated with SBRT were retrospectively reviewed. The influence of the TCIAS status on local progression-free (LPF), regional failure-free (RFF), distant failure-free (DFF), progression-free survival (PFS), and overall survival (OS) rates was assessed using univariate and multivariate analyses. Results: Overall, 68 patients were included. The median follow-up time was 24.3 months. For patients positive/negative for TCIAS, the 2-year LPF, RFF, DFF, PFS, and OS rates were 81.4 %/91.1 %, 73.7 %/96.2 %, 55.9 %/75.3 %, 55.0 %/84.6 %, and 67.8 %/92.2 %, respectively. In the multivariate analysis, TCIAS-positive was a significant unfavorable factor for RFF (hazard ratio [HR]: 4.10; 95 % confidence interval [CI]: 1.04-16.16, p = 0.04), DFF (HR: 2.61, 95 % CI: 1.03-6.57, p = 0.04), and PFS (HR: 2.36; 95 % CI: 1.05-5.30, p = 0.04). By contrast, TCIAS-positive was not a significant risk factor for LPF and OS. Conclusion: TCIAS-positive is an unfavorable factor for regional and distant failure after SBRT. TCIAS status may be useful in predicting the treatment outcome of SBRT for early-stage lung cancer.

CT-based radiomics model to predict spread through air space in resectable lung cancer.

BACKGROUND: Spread through air space (STAS) has been identified as a pathological pattern associated with lung cancer progression. Patients with STAS were related to a worse prognosis compared with patients without STAS. The objective of this study was to establish a radiomics model capable of forecasting STAS before surgery, which can assist surgeons in selecting the most appropriate operation type for patients with STAS. METHOD: There were 537 eligible patients retrospectively included in this study. ROI segmentation was performed manually on all CT images to identify the region of interest. From each segmented lesion, a total of 1688 features were extracted. The tumor size, maximum tumor diameters, and tumor type were also recorded. Using Spearman's correlation coefficient to calculate the correlation and redundancy of elements, and redundant features less than 0.80 were removed. In order to reduce the level of overfitting and avoid statistical biases, a dimension reduction process of the dataset was conducted to decrease the number of features. Finally, a radiomics model included 44 features was established to predict STAS. To evaluate the performance of the model, the receiver operating characteristic (ROC) curve was used, and the area under the curve (AUC) was calculated, and the accuracy of the model was verified by 10-fold cross-validation. RESULTS: The incidence of STAS was 38.2% (205/537). The tumor type, maximum tumor diameters, and consolidation tumor ratio were significantly different between STAS group and non-STAS group. The training group included 430 patients, while the test group was consisted with 107. The training group achieved an AUC of 0.825 (sensitivity, 0.875; specificity, 0.621; and accuracy, 0.749) and the test group had an AUC of 0.802 (sensitivity, 0.797; specificity,0.688; and accuracy, 0.748). The 10-fold cross-validation had an AUC of 0.834. CONCLUSION: CT-based radiomic model can predict STAS effectively, which is of great importance to guide the selection of operation types before surgery.

Micropapillary Pattern in Invasive Mucinous Adenocarcinoma of the Lung: Comparison With Invasive Non-Mucinous Adenocarcinoma.

Background. The presence of a micropapillary pattern is associated with poor outcomes in lung adenocarcinoma. This study aimed to assess the clinicopathological features of micropapillary pattern in mucinous adenocarcinoma of the lung. Methods. The patients were stratified into three groups: the invasive mucinous adenocarcinoma group (60 patients), the mixed invasive mucinous adenocarcinoma group (33 patients), and the invasive non-mucinous adenocarcinoma group (237 patients). The presence of micropapillary pattern and its clinicopathological features were analyzed and compared between the three groups. Results. Compared to mixed invasive mucinous adenocarcinoma, invasive mucinous adenocarcinoma had lower frequencies of micropapillary pattern (28.3% vs 87.9%, respectively; P < .001) and lymph node metastasis (00.0% vs 15.1%, respectively; P = .005). The frequency of tumor spread through air space (STAS) in invasive mucinous adenocarcinoma (23.3%) was higher than that in invasive non-mucinous adenocarcinoma (6.3%; P < .001), while lower than that in mixed invasive mucinous adenocarcinoma (60.6%; P < .001). When the three groups were all accompanied by micropapillary pattern, there was no obvious difference in STAS between invasive mucinous adenocarcinoma with micropapillary pattern and mixed mucinous adenocarcinoma with micropapillary pattern (P > .05). No filigree pattern occurred in invasive mucinous adenocarcinoma with micropapillary pattern. Conclusions. The micropapillary pattern is frequently observed in invasive mucinous adenocarcinoma and has a better prognosis compared to mixed invasive mucinous adenocarcinoma and invasive non-mucinous adenocarcinoma. However, the malignancy of the micropapillary pattern in mixed mucinous adenocarcinoma was similar to that in invasive non-mucinous adenocarcinoma, even with the presence of mucus. These findings suggest that the development mechanisms of the micropapillary pattern in invasive mucinous adenocarcinoma and mixed mucinous adenocarcinoma may differ.

Significance of spread through air spaces in small cell lung cancer.

PURPOSE: Tumor spread through air space (STAS) is a novel pattern of invasion related to poor prognosis in non-small cell cancer (NSCLC). Nevertheless, little is known about the role of STAS in small cell lung cancer (SCLC). We sought to determine whether STAS has a significant effect on recurrence among SCLC patients. METHODS: We collected clinical and follow-up information from 181 resected stage I-III SCLC patients and compared overall survival (OS) and disease-free survival (DFS) between the patients with or without STAS using the Kaplan‒Meier method. To explore the effect of STAS on recurrence, a competing-risk analysis was conducted. RESULTS: Among 181 SCLC patients, STAS was observed in 56 (30.94%) patients, and 125 (69.06%) patients did not have STAS. Furthermore, 33 (18.23%) patients had recurrence, including 12 patients with brain metastases. Patients with STAS had worse DFS. The cumulative incidence of any recurrence was higher in patients with STAS than in those without STAS. Univariate and multivariate competing-risk regression analyses revealed that sublobar resection and STAS were independent risk factors for SCLC recurrence (p = 0.009 and p = 0.029 for multivariate analysis, respectively). CONCLUSION: SCLC patients with STAS have worse DFS than SCLC patients without STAS. STAS is an independent prognostic factor in SCLC patients.

The prognostic significance of tumor spread through air space in stage I lung adenocarcinoma.

AIM: There are still patients of stage I lung adenocarcinoma (ADC) suffering from local or distant recurrence. Herein we conducted a meta-analysis to investigate the prognostic value of tumor spread through air space (STAS), a new form of invasion pattern, in patients with pathologically confirmed stage I lung ADC. METHODS: Related literature was searched using PubMed, Embase, Cochrane Library, and Web of Science databases from the inception dates to September 4, 2021. Recurrence-free survival (RFS) and overall survival (OS) were set as primary outcome endpoints. In addition, subgroup analyses on operation mode, edition of the American Joint Committee on Cancer TNM staging, sample size, and research regions were also investigated. RESULTS: A total of 17 studies involving 9785 patients were included. The presence of STAS was detected in 31.2% of patients and was associated with poor RFS (adjusted hazard ratio [HR] = 1.93, p < 0.001) and OS (HR = 2.02, p < 0.001). In subgroup analysis on operation mode, the prognostic value of STAS was prominently shown in patients who underwent limited resection (RFS: HR = 3.58, p < 0.001; OS: HR = 3.37, p < 0.001), while for patients who underwent lobectomy, adverse impact of STAS on RFS was observed (HR = 1.60, p = 0.019), but no significant difference was observed on OS (HR = 1.56, p = 0.061). The results fluctuated in different regions while other factors did not alter the independent predictive value of STAS. CONCLUSION: Tumor STAS should be considered as an adverse prognostic indicator for patients with stage I lung ADC, especially for those under limited resection. More intensive medical care for those patients needs to be investigated in further studies.

The differential prognostic impact of spread through air spaces in early-stage lung adenocarcinoma after lobectomy according to the pT descriptor.

OBJECTIVES: We evaluated the differential prognostic impact of spread through air spaces (STAS) in early-stage lung adenocarcinoma after lobectomy according to the pT descriptor. METHODS: The study population included 506 patients who underwent lobectomy with mediastinal lymph node dissection for pT1b, pT1c, and pT2a adenocarcinoma between 2011 and 2016. We divided the study population into 2 groups according to STAS status, ie, STAS (+) versus STAS (-), and stratified them according to the pT descriptor. A Cox proportional hazard model and inverse probability of treatment weight-adjusted Kaplan-Meier curves were used to evaluate the prognostic impact of STAS on recurrence-free survival (RFS) and its independency in each stratum. RESULTS: Multivariable Cox proportional hazard regression analysis demonstrated that in pT1b and pT1c strata, STAS (+) patients had a 7.02-fold and 2.89-fold greater risk of recurrence than STAS (-) patients, respectively. However, in the pT2a stratum, STAS did not affect RFS. And the RFS of the STAS (+) pT1b/c strata was similar to that of the pT2a stratum. In the pT1b/c strata, inverse probability of treatment weighting-adjusted Kaplan-Meier curves also showed that RFS was significantly worse when STAS was present. Furthermore, the risks for locoregional and distant recurrence were both greater when STAS was present. CONCLUSIONS: The presence of STAS increased the risk of recurrence independently from other poor prognostic factors in patients with pT1b/cN0M0 adenocarcinoma who underwent lobectomy, but not in pT2a patients. The presence of STAS in pT1b/cN0M0 adenocarcinoma was associated with a similar risk of recurrence to that of pT2aN0M0 adenocarcinoma.

Role of radiomics in predicting lung cancer spread through air spaces in a heterogeneous dataset.

Background: Spread through air spaces (STAS) has been reported as a negative prognostic factor in patients with lung cancer undergoing sublobar resection. Radiomics has been recently proposed to predict STAS using preoperative computed tomography (CT). However, limitations of previous studies included the strict selection of imaging acquisition protocols, leading to results hardly applicable to daily clinical practice. The aim of this study is to test a radiomics-based prediction model of STAS in a practice-based dataset. Methods: A training cohort of 99 consecutive patients (65 STAS+ and 34 STAS-) with resected lung adenocarcinoma (ADC) was retrospectively collected. Preoperative CT images were collected from different centers regardless model and scanner manufacture, acquisition and reconstruction protocol, contrast phase and pixel size. Radiomics features were selected according to separation power and P value stability within different preprocessing setups and bootstrapping resampling. A prospective cohort of 50 patients (33 STAS+ and 17 STAS-) was enrolled for the external validation. Results: Only the five features with the highest stability were considered for the prediction model building. Radiomics, radiological and mixed radiomics-radiological prediction models were created, showing an accuracy of 0.66±0.02 after internal validation and reaching an accuracy of 0.78 in the external validation. Conclusions: Radiomics-based prediction models of STAS may be useful to properly plan surgical treatment and avoid oncological ineffective sublobar resections. This study supports a possible application of radiomics-based models on data with high variance in acquisition, reconstruction and preprocessing, opening a new chance for the use of radiomics in the prediction of STAS. Trial Registration: ClinicalTrials.gov identifier: NCT04893200.

Clinicopathological and CT features of tumor spread through air space in invasive lung adenocarcinoma.

Objective: Tumor spread through air spaces (STAS) has recently been reported as a novel invasive pattern in lung adenocarcinoma. Thus, this study aimed to investigate the clinicopathological and radiological features in invasive lung adenocarcinoma with tumor STAS. Methods: Data of 503 invasive lung adenocarcinoma patients who underwent surgery between 1 January 2015 and 31 December 2021 were collected. The correlations between STAS presence and clinicopathological and radiological characteristics were analyzed. Statistical analysis was performed using SPSS 22.0. Results: Among the 503 patients with invasive adenocarcinoma, 247 (47.9%) and 262 (52.1%) patients were positive and negative for STAS, respectively. Compared to STAS-negative adenocarcinoma, STAS was more common in papillary, micropapillary, and solid tumors (p < 0.01); STAS was associated with advanced pT (p = 0.024), pN (p < 0.001), and pTNM (p < 0.001) stage, more lymph node metastases (p < 0.01), more pleural invasion (p < 0.01), and more neurovascular invasion (p = 0.025). The maximum diameter (p < 0.01), the maximum diameters of the solid component (p < 0.01), and the consolidation/tumor ratio (CTR, p < 0.01) were significantly larger in STAS-positive than in STAS-negative adenocarcinoma. Other common computed tomography (CT) features of adenocarcinomas, i.e., lobulation (p < 0.01), spiculation (p < 0.01), vacuole (p < 0.01), air bronchogram (p = 0.020), vascular convergence (p < 0.01), and pleural indentation (p < 0.01) were significantly associated with STAS. In a multivariable analysis, the maximal diameter of the solid component (odds ratio [OR], 2.505; 95% confidence interval [CI], 1.886-3.329), vacuole (OR, 3.301; 95% CI, 1.822-5.980), and spiculation (OR, 2.162; 95% CI, 1.221-3.829) were independent predictors of STAS. The area under the curve (AUC) of the maximal diameter of the solid component was 0.757 (95% CI, 0.714-0.799; p < 0.001), the sensitivity was 73.9%, and the specificity was 69.1% at a cutoff value of 1.18 cm. Conclusion: STAS was significantly correlated with several invasive clinicopathological and radiological characteristics, and the maximal diameter was an independent predictor of STAS. These results will prove helpful in identifying STAS-positive adenocarcinoma by CT before surgical resection.

Clinicopathological Impact of the Spread through Air Space in Non-Small Cell Lung Cancer: A Meta-Analysis.

This study aimed to elucidate the clinicopathological significance of spread through air space (STAS) in non-small cell lung cancer (NSCLC) through a meta-analysis. Using 47 eligible studies, we obtained the estimated rates of STAS in various histological subtypes of NSCLC and compared the clinicopathological characteristics and prognosis between NSCLC with and without STAS. The estimated STAS rate was 0.368 (95% confidence interval [CI], 0.336-0.0.401) in patients with NSCLC. Furthermore, the STAS rates for squamous cell carcinoma and adenocarcinoma were 0.338 (95% CI, 0.273-0.411) and 0.374 (95% CI, 0.340-0.409), respectively. Among the histological subtypes of adenocarcinoma, micropapillary-predominant tumors had the highest rate of STAS (0.719; 95% CI, 0.652-0.778). The STAS rates of solid- and papillary-predominant adenocarcinoma were 0.567 (95% CI, 0.478-0.652) and 0.446 (95% CI, 0.392-0.501), respectively. NSCLCs with STAS showed a higher visceral pleural, venous, and lymphatic invasion than those without STAS. In addition, anaplastic lymphoma kinase mutations and ROS1 rearrangements were significantly more frequent in NSCLCs with STAS than in those without STAS. The presence of STAS was significantly correlated with worse overall and recurrence-free survival (hazard ratio, 2.119; 95% CI, 1.811-2.480 and 2.372; 95% CI, 2.018-2.788, respectively). Taken together, the presence of STAS is useful in predicting the clinicopathological significance and prognosis of patients with NSCLC.

Integration of clinicopathological and mutational data offers insight into lung cancer with tumor spread through air spaces.

BACKGROUND: Tumor spread through air spaces (STAS) was defined as a unique tumor invasion pattern in adenocarcinoma (ADC) by The World Health Organization Classification of Lung Tumors in 2015. Since then, STAS had been shown to be associated with local recurrence and poor survival results, as the typical signature and potential mechanisms of STAS remained unclear. Our objectives were to comprehensively demonstrate the clinicopathological and genetic signatures in STAS-positive lung cancer patients. METHODS: The clinicopathological and gene alteration characteristics of 878 STAS-positive lung cancer patients were presented. Associations between parameters were evaluated using the Chi-square test, Fisher's exact test, and logistic regression. The capture-based targeted next generation sequencing (NGS) with a platform of 68 lung cancer-related genes was conducted in 139 cases, and the mutational spectrum was summarized. RESULTS: STAS was identified in 391 female and 481 male patients, of which ADC accounted for the majority of cases (92.6%). The concomitant solid or micropapillary subtype was observed in 92.12% patients with ADC. Poorly differentiated histological subtypes were more frequent and negatively correlated with tumor size in smaller tumor cases (P=0.036, Pearson's R=-0.075). Furthermore, in the subgroup of nodules within 3 cm, the distribution of the solid and micropapillary subtypes were significantly frequent in lymph node-positive patients (P<0.001). Tumor protein p53 (TP53) alterations were more frequent in smoking patients (27.6%, P=0.007), human epidermal growth factor receptor 2 (HER2) alterations were more common in female (10.8%, P=0.025), while Kirsten rat sarcoma viral oncogene (KRAS) (20.3%, P=0.024) and TP53 (45.9%, P=0.003) were more prevalent in males. CONCLUSIONS: Poorly differentiated histological subtypes likely played a crucial role in promoting the invasiveness of STAS, especially in small tumor-size cases. Epidermal growth factor receptor (EGFR), TP53, KARS, anaplastic lymphoma kinase (ALK), and ROS proto-oncogene 1 (ROS1) were the five most frequent alterations in STAS-positive ADC.

Prognostic impact of tumour spread through air space in radiological subsolid and pure solid lung adenocarcinoma.

OBJECTIVES: The aim of the study was to investigate the relationship between ground-glass opacity (GGO) and tumour spread through air space (STAS), as well as their joint influence on the prognosis of stage I lung adenocarcinoma. METHODS: A total of 620 consecutive patients with surgically resected lung adenocarcinoma between January 2011 and December 2012 were reviewed retrospectively. The relevance of STAS and GGO was analysed by logistic regression, and their prognostic significance was investigated via the Kaplan-Meier method and Cox regression models. Furthermore, to determine the magnitude of the prognostic impact of GGO and STAS, we respectively performed survival analysis in subgroups according to the presence of STAS and GGO. RESULTS: Of all 620 cases, 26.7% were positive for STAS, and 32.9% had a GGO component. STAS was present in 10.8% of part-solid lesions and 34.9% of pure solid nodules (P < 0.001). Lepidic-predominant histologic subtype, GGO component and pathological T stage exhibited significant relevance to the presence of STAS. For the whole population, STAS and GGO component were each revealed as independent predictors for overall survival and recurrence-free survival (each with P < 0.001). Interestingly, in the GGO-present subgroup, STAS failed to significantly stratify prognosis. However, in the STAS-positive subgroup, the presence of a GGO component was independently associated with favourable oncological results. CONCLUSIONS: STAS is associated with a GGO component, and each factor was a significant predictor for the prognosis of stage I lung adenocarcinoma. Moreover, the favourable prognostic impact of a GGO component was greater than the adverse prognostic influence of STAS, indicating that GGO is a more reliable prognostic predictor in stage I lung adenocarcinoma.

Predictive value of radiological features on spread through air space in stage cIA lung adenocarcinoma.

BACKGROUND: Spread through air space (STAS) is a risk factor for disease recurrence in patients with stage IA lung adenocarcinoma (LUAD) who undergo limited resection. Preoperative prediction of STAS could help intraoperative surgical decision-making in small LUAD patients. The aim of the study was to evaluate the predictive value of radiological features on STAS in stage cIA LUAD. METHODS: A case-control study was designed through retrospective analysis of the radiological features of patients who underwent curative surgery for LUAD with a clinical tumor size ≤3 cm. Univariable and multivariable analyses were used to identify the independent risk factors for STAS. The predicted probability of STAS was calculated by a specific formula. Receiver operating characteristic (ROC) curves were used to determine a cut-off value with appropriate specificity while maintaining high sensitivity for STAS positivity. RESULTS: STAS was frequently observed in acinar predominant (P<0.001), micropapillary predominant (P<0.001) and solid predominant (P<0.001) tumors and was significantly associated with larger pT size (P<0.001), presence of micropapillary component (P<0.001), lymphovascular invasion (LVI) (P<0.001), visceral pleura invasion (VPI) (P<0.001), both N1 and N2 lymph node metastasis (P<0.001) and ALK rearrangement (P<0.001). STAS-positivity was significantly associated with the presence of cavitation (P=0.047), lobulation (P=0.009), air bronchogram (P<0.001), and vascular convergence (P=0.016) and was also associated with greater maximum tumor diameter (P<0.001), maximum solid component diameter (P<0.001), maximum tumor area (P<0.001), consolidation/tumor ratio (CTR) (P<0.001), tumor disappearance ratio (TDR) (P<0.001) and computed tomography (CT) value (P<0.001). Multivariable analysis showed that STAS was associated with air bronchogram (P=0.042), maximum tumor diameter (P=0.015), maximum solid component diameter (P=0.022) and CTR (P<0.001). The ROC curve showed that the area under the curve (AUC) was 0.726 in the model for predicting STAS, with a sensitivity and specificity of 95.2% and 36.8%, respectively. CONCLUSIONS: STAS-positive LUAD was associated with air bronchogram, maximum tumor diameter, maximum solid component diameter and CTR. These radiological features could predict STAS with excellent sensitivity but inferior specificity.

A CT-based logistic regression model to predict spread through air space in lung adenocarcinoma.

BACKGROUND: Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma and is also a risk factor for recurrence and worse prognosis of lung adenocarcinoma. This study aimed to develop and validate a computed tomography (CT)-based logistic regression model to predict STAS in lung adenocarcinoma. METHODS: This retrospective study was approved by the institutional review board of two centers and included 578 patients (462 from center I and 116 from center II) with pathologically confirmed lung adenocarcinoma. STAS was identified from 90 center I patients (19.5%) and 28 center II patients (24.1%) from. The maximum diameter, nodule area, and area of solid components in part-solid nodules were measured. Twenty-one semantic characteristics were assessed. Univariate analysis was used to select CT characteristics, which were associated with STAS in the patient cohort of center I. Multivariable logistic regression was used to develop a CT characteristics-based model on those variables with statistical significance. The model was validated in the validation cohort and then tested in the external test cohort (patients from center II). The diagnostic performance of the model was measured by area under the curve (AUC) of receiver operating characteristic (ROC). RESULTS: At univariate analysis, age and 11 CT characteristics, including the maximum diameter of the tumor, the maximum area of the tumor, the area and ratio of the solid component, nodule type, pleural thickening, pleural retraction, mediastinal lymph node enlargement, vascular cluster sign, and lobulation, specula were found to be significantly associated with STAS. The optimal logistic regression model included age, maximum diameter and ratio of solid component with odds ratio (OR) value of 0.967 (95% CI: 0.944-0.988), 1.027 (95% CI: 1.008-1.046) and 5.14 (95% CI: 2.180-13.321), respectively. This model achieved an AUC of 0.801 (95% CI: 0.709-0.892) and 0.692 (95% CI: 0.518-0.866) in the validation cohort and the external test cohort, respectively. The difference was not statistically significant (P=0.280). CONCLUSIONS: CT-based logistic regression machine learning model could preoperatively predict STAS in lung adenocarcinoma with excellent diagnosis performance, which could be supplementary to routine CT interpretation.

Stepwise flowchart for decision making on sublobar resection through the estimation of spread through air space in early stage lung cancer1.

OBJECTIVES: The sensitivity for tumor spread through air space (STAS), an independent risk factor for locoregional recurrence after sublobar resection for lung cancer, has been relatively low in frozen sections. We aimed to determine predictors with high negative predictive value for the presence of STAS and to provide the flowchart in combination with these predictors for the decision-making for sublobar resection. MATERIALS AND METHODS: Between July 2015 and December 2017, 387 patients who underwent surgery for non-small cell lung cancer (NSCLC) with pathologic findings of the total masses measuring ≤ 2 cm were enrolled. The lesions were divided into two groups according to presence of STAS. We compared the preoperative characteristics, operative data, and developed a flowchart for STAS prediction using receiver operator characteristic curve analysis and multivariable logistic regression. RESULTS: The STAS-positive group (N = 111) had a significantly higher preoperative tumor size (1.70 [1.5] vs 1.50 [0.69], p < 0.001) and standardized uptake value tumor-to-liver (SUV T/L) ratio (1.40 [1.60] vs 0.60 [1.10], p < 0.001) and a significantly lower two-dimensional ground-glass opacity (GGO) percentage (35.86 [61.00] vs 78.14 [39.00], p < 0.001). Meanwhile, the STAS-negative group (N = 286) had higher lepidic predominance (41.6% vs. 1.8%, p < 0.001). We developed a flowchart for predicting STAS in combination with two-dimensional GGO percentage on computed tomography (CT), SUV T/L ratio on positron-emission CT, and lepidic predominant pattern. The sensitivity, specificity, and negative predictive value for STAS positivity were 79.3%, 68.5%, and 89.5%, respectively. CONCLUSIONS: The stepwise flowchart using two-dimensional GGO percentage on CT, maximum SUV, and lepidic predominance might be helpful in selecting patients with early NSCLC for sublobar resection.

Challenges for real-time intraoperative diagnosis of high risk histology in lung adenocarcinoma: A necessity for sublobar resection.

Recently, the incidence of small, peripheral lung adenocarcinoma has been increasing as lung cancer screening with radiologic examination is more widely performed. Tumor size is one of the determinants of the prognostic outcome in clinically node-negative lung adenocarcinoma. Sublobar resection has been proposed as one of the minimally invasive surgical options for small-sized adenocarcinomas. Despite the lack of robust clinical trial evidence, sublobar resection has become more popular, especially in developed countries where less extensive surgery may be of benefit in a population where the age of the elderly is growing. However, high risk histologic features such as micropapillary subtype and tumor spread through air space (STAS) have been associated with a significantly higher risk of local recurrence after sublobar resection, but not after lobectomy. Surgical decision-making based on frozen section diagnosis of high risk histologic features may be useful to prevent local control failure after sublobar resection. At the present time, there is little evidence to demonstrate the diagnostic accuracy of identifying high risk histologic features on frozen section. One study has so far demonstrated that diagnostic accuracy of identifying STAS is higher than that of identifying the micropapillary subtype. Additionally, the presence of STAS has been found to be more strongly associated with local recurrence in patients who had undergone sublobar resection. Although further investigation is required for validation of this finding, STAS diagnosis on frozen section may shed further light on intraoperative surgical decision-making during sublobar resection. To this end, we review the recently published data on the intraoperative identification of high risk features.