Tumor islands in resected early-stage lung adenocarcinomas are associated with unique clinicopathologic and molecular characteristics and worse prognosis

Tumor spread through air spaces in lung cancer: prospective analysis of the accuracy of intraoperative frozen section examination

OBJECTIVE

To establish the accuracy of frozen section examination in identifying tumor spread through air spaces (STAS), as well as to propose a reproducible technical methodology for frozen section analysis. We also aim to propose a method to be incorporated into the decision making about the need for conversion to lobectomy during sublobar resection.

METHODS

This was a nonrandomized prospective study of 38 patients with lung cancer who underwent surgical resection. The findings regarding STAS in the frozen section were compared with the definitive histopathological study of paraffin-embedded sections. We calculated a confusion matrix to obtain the positive predictive value (PPV), negative predictive value (NPV), sensitivity, specificity and accuracy.

RESULTS

The intraoperative frozen section analysis identified 7 STAS-positive cases that were also positive in the histopathological examination, as well as 3 STAS-negative cases that were positive in the in the histopathological examination. Therefore, frozen section analysis was determined to have a sensitivity of 70%, specificity of 100%, PPV of 100%, NPV of 90.3%, and accuracy of 92% for identifying STAS.

CONCLUSIONS

Frozen section analysis is capable of identifying STAS during resection in patients with lung cancer. The PPV, NPV, sensitivity, and specificity showed that the technique proposed could be incorporated at other centers and would allow advances directly linked to prognosis. In addition, given the high accuracy of the technique, it could inform intraoperative decisions regarding sublobar versus lobar resection.

STAS: New explorations and challenges for thoracic surgeons

Spread through air spaces (STAS) represents a relatively novel concept in the pathology of lung cancer, and it specifically refers to the dissemination of tumour cells into the parenchymal air spaces adjacent to the primary tumour. In 2015, the World Health Organization (WHO) classified STAS as a new invasive form of lung adenocarcinoma (LUAD). Many studies investigated the role of STAS and revealed its association with the prognosis of LUAD and its influence on the outcomes of other malignant pulmonary neoplasms. Additionally, the underlying mechanisms and predictive models of STAS have received considerable attention in recent years. This paper provides a comprehensive overview of the research advancements and prospects of STAS by examining it from multiple perspectives.

Preoperative predictors of spread through air spaces in lung cancer

OBJECTIVE

Spread through air spaces (STAS) is a new histologic feature of invasion of non-small cell lung cancer that lacks sensitivity and specificity on frozen sections and is associated with higher recurrence and worse survival with sublobar resections. Our objective is to identify preoperative characteristics that are predictive of STAS to guide operative decisions.

METHODS

From January 2018 through December 2021, 439 cT1-3N0 M0 patients with non-small cell lung cancer and a median age of 68 years, 255 (58%) women, who underwent primary surgery at our institution were included. Patients who received neoadjuvant therapy and whose STAS status was not documented were excluded. Age, sex, smoking status, tumor size, ground-glass opacities, maximum standardized uptake values, and molecular markers on preoperative biopsy were evaluated as preoperative markers. Comparisons between groups were conducted using standardized mean differences and random forest classification was used for prediction modeling.

RESULTS

Of the 439 patients, 177 had at least 1 STAS-positive tumor, and 262 had no STAS-positive tumors. Overall, 179 STAS tumors and 293 non-STAS tumors were evaluated. Younger age (50 years or younger), solid tumor, size ≥2 cm, and maximum standardized uptake value ≥2.5 were independently predictive of STAS with prediction probabilities of 50%, 40%, 38%, and 40%, respectively. STAS tumors were more likely to harbor KRAS mutations and be PD-L1 negative.

CONCLUSIONS

Young age (50 years or younger), larger (≥2 cm) solid tumors, high maximum standardized uptake values, and presence of KRAS mutation, are risk factors for STAS and can be considered for lobectomy. Smoking status and gender are still controversial risk factors for STAS.

Spread Through Air Spaces: Interresponder Agreement and Comparison Between Pulmonary and General Pathologists

Spread through air spaces (STAS), an important prognostic indicator included in the 2015 World Health Organization classification, is defined as micropapillary, solid, and/or single tumor cell clusters beyond the edge of the main mass and distinct from processing artifacts. This study aimed to assess the interresponder agreement on current STAS criteria vs artifacts, identify discrepancies, and compare responses between pulmonary and general pathologists. A multiple-choice online questionnaire illustrating multiple criteria for STAS vs artifacts was available internationally for 6 days to Pulmonary Pathology Society members, thoracic pathology course attendees, and International Association for the Study of Lung Cancer pathology committee members. Additional 4 questions gathered demographic and practice setting information. One hundred thirty-six unique responses were analyzed. The majority were from North America and Europe (42.6% and 30.2%), practicing pulmonary pathology (70.6%) in academia (64.7%), and with >20 years of experience (31.6%). Excluding trainees, the greatest overall agreement was in defining solid and micropapillary tumor clusters of STAS located ≥3 alveolar spaces from the main tumor edge (91.5%) and recognizing strips of ciliated cells as artifacts (97.7%). Lesser agreement on STAS was evident when tumor cell clusters were immediately adjacent to the tumor edge, a single tumor cell cluster was present at the tissue edge, tumor cell clusters were jagged edged, or tumor cell clusters were admixed with ciliated cell strips (artifacts). There was no significant difference in agreements on STAS for multiple criteria between pulmonary and general pathologists. Significant interresponder agreement on STAS vs artifacts was achieved only for a few criteria. To improve the reproducibility of STAS vs artifacts, areas of lesser agreement require further clarification.

Histology of Bronchiolar Tumor Spread Through Air Spaces

The clinical significance of lung tumor spread through air spaces (STAS) has been extensively studied, and is recognized as a unique pattern of invasion. Previous studies of STAS have focused primarily on STAS in alveolar spaces, whereas STAS in the bronchiolar spaces (bronchiolar STAS) has been described in only a few case reports only. Here, we examined 306 cases of primary lung adenocarcinoma and found that bronchiolar STAS was present in 18%. Bronchiolar STAS was associated with an inferior prognosis, more advanced stage, and higher histologic grade. No significant difference in clinicopathological factors or prognosis was observed between cases with bronchiolar STAS and those with alveolar STAS alone. Notably, bronchiolar STAS often occurred simultaneously with alveolar STAS and endobronchial spread of adenocarcinoma, particularly when bronchiolar STAS was present outside the main tumor. We also identified cases where bronchiolar STAS and endobronchial spread of adenocarcinoma occurred simultaneously in the same bronchi or bronchioles located outside the main tumor, as well as cases with bronchiolar STAS adjacent to intrapulmonary metastatic nodules. Our results highlight the significant role of bronchiolar STAS in the aerogenous spread of adenocarcinoma cells. Bronchiolar STAS can be regarded as a histologic variant of alveolar STAS. This study also supports the idea that STAS is not a tissue processing artifact, but a true biological process with clinical implications, offering histologic evidence of aerogenous spread in lung adenocarcinoma.

[Pathological Diagnostic Testing and Biomarkers for Perioperative System Therapy]

Optimal personalized treatment planning for resectable lung cancer requires quality-assured, standardized and prompt processing of tissue samples in pathological laboratories, as well as the determination of relevant predictive and prognostic biomarkers. Pathological diagnostic testing includes histological tumor typing, staging and tumor grading, resection status and, if necessary, regression grading after neoadjuvant systemic therapy. Histopathological typing is performed according to the current WHO classification and includes adenocarcinomas, squamous cell carcinomas, other non-small cell lung carcinomas (NSCLCs), carcinoids, small cell and large cell neuroendocrine carcinomas. Standardized tumor grading currently plays an important role in invasive non-mucinous adenocarcinoma in particular and enables prognostic risk assessment. The R classification and regression grading are also prognostically relevant. In the early stages of NSCLC, molecular biomarkers such as EGFR, ALK and PD-L1, are relevant for decisions on individual treatment. Testing is performed on FFPE tissue samples and must be carried out in a quality-assured manner and in accordance with international standards.

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.

CT-Based Super-Resolution Deep Learning Models with Attention Mechanisms for Predicting Spread Through Air Spaces of Solid or Part-Solid Lung Adenocarcinoma

RATIONALE AND OBJECTIVES

Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma (LUAD), and preoperative knowledge of STAS status is helpful in choosing an appropriate surgical approach.

MATERIALS AND METHODS

This retrospective study collected and analyzed 602 patients diagnosed with LUAD from two medical centers: center 1 was randomly partitioned into training (n = 358) and validation cohorts (n = 154) at a 7:3 ratio; and center 2 was the external test cohort (n = 90). Super resolution was performed on all images to acquire high-resolution images, which were used to train the SE-ResNet50 model, before creating an equivalent parameter ResNet50 model. Disparities were compared between the two models using receiver operating characteristic curves, area under the curve, accuracy, precision, sensitivity, and specificity.

RESULTS

In this study, 512 and 90 patients with LUAD were enrolled from centers 1 and 2, respectively. The curve values of the SE-ResNet50 and ResNet50 models were compared for training, validation, and test cohorts, resulting in values of 0.933 vs 0.909, 0.783 vs 0.728, and 0.806 vs 0.695, respectively. In the external test cohort, the accuracy of the SE-ResNet50 model demonstrated a 10% improvement over the ResNet50 model (82.2% vs 72.2%).

CONCLUSION

The SE-ResNet50 model based on computed tomography super-resolution has great potential for predicting STAS status in patients with solid or partially solid LUAD, with superior predictive performance compared to traditional deep learning models.

Does dual-layer spectral detector CT provide added value in predicting spread through air spaces in lung adenocarcinoma? A preliminary study

OBJECTIVES

To examine the predictive value of dual-layer spectral detector CT (DLCT) for spread through air spaces (STAS) in clinical lung adenocarcinoma.

METHODS

A total of 225 lung adenocarcinoma cases were retrospectively reviewed for demographic, clinical, pathological, traditional CT, and spectral parameters. Multivariable logistic regression analysis was carried out based on three logistic models, including a model using traditional CT features (traditional model), a model using spectral parameters (spectral model), and an integrated model combining traditional CT and spectral parameters (integrated model). Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were performed to assess these models.

RESULTS

Univariable analysis showed significant differences between the STAS and non-STAS groups in traditional CT features, including nodule density (p < 0.001), pleural indentation types (p = 0.006), air-bronchogram sign (p = 0.031), the presence of spiculation (p < 0.001), long-axis diameter of the entire nodule (LD) (p < 0.001), and consolidation/tumor ratio (CTR) (p < 0.001). Multivariable analysis revealed that LD > 20 mm (odds ratio [OR] = 2.271, p = 0.025) and CTR (OR = 24.208, p < 0.001) were independent predictors in the traditional model, while electronic density (ED) in the venous phase was an independent predictor in the spectral (OR = 1.062, p < 0.001) and integrated (OR = 1.055, p < 0.001) models. The area under the curve (AUC) for the integrated model (0.84) was the highest (spectral model, 0.83; traditional model, 0.80), and the difference between the integrated and traditional models was statistically significant (p = 0.015). DCA showed that the integrated model had superior clinical value versus the traditional model.

CONCLUSIONS

DLCT has added value for STAS prediction in lung adenocarcinoma.

CLINICAL RELEVANCE STATEMENT

Spectral CT has added value for spread through air spaces prediction in lung adenocarcinoma so may impact treatment planning in the future.

KEY POINTS

• Electronic density may be a potential spectral index for predicting spread through air spaces in lung adenocarcinoma. • A combination of spectral and traditional CT features enhances the performance of traditional CT for predicting spread through air spaces.

Significance of Spread Through Air Spaces and Vascular Invasion in Early-stage Adenocarcinoma Survival: A Comprehensive Clinicopathologic Study of 427 Patients for Precision Management

Spread through air spaces (STAS) is a novel invasive pattern of lung cancer associated with poor prognosis in non-small cell cancer (NSCLC). We aimed to investigate the incidence of STAS in a surgical series of adenocarcinomas (ADCs) resected in our thoracic surgery unit and to identify the association of STAS with other clinicopathological characteristics. We retrospectively enrolled patients with stage cT1a-cT2b who underwent resection between 2016 and 2022. For each case, a comprehensive pathologic report was accessible which included histotype, mitoses, pleural invasion, fibrosis, tumor infiltrating lymphocytes, necrosis, inflammation, vascular and perineural invasion, as well as STAS. PD-L1 expression was also investigated. A total of 427 patients with ADCs underwent surgery. Regarding overall survival (OS), no significant difference was observed between the STAS positive (STAS+) and STAS negative (STAS-) groups ( P =0.44). However, vascular invasion (VI) was associated with a poorer survival probability ( P =0.018). STAS+/VI+ patients had tendentially worse survival compared with STAS+/VI- ( P =0.089). ADCs with pathologic evidence of immune system (IS) activation (TILs>10% and PD-L1≥1) demonstrated significantly increased OS compared with ADCs with no IS and VI. In terms of recurrence rate, no statistical differences were found between the STAS+ and STAS- samples ( P =0.2). VI was also linked to a significantly elevated risk of recurrence ( P =0.0048). Our study suggests that in resected early-stage ADCs, STAS+ does not seem to influence recurrence or mortality. VI was instead an adverse pathologic prognostic factor for both survival and recurrence, whereas IS seemed to be protective.

Mean computed tomography value to predict spread through air spaces in clinical N0 lung adenocarcinoma

BACKGROUND

The aim of this study was to assess the ability of radiologic factors such as mean computed tomography (mCT) value, consolidation/tumor ratio (C/T ratio), solid tumor size, and the maximum standardized uptake (SUVmax) value by F-18 fluorodeoxyglucose positron emission tomography to predict the presence of spread through air spaces (STAS) of lung adenocarcinoma.

METHODS

A retrospective study was conducted on 118 patients those diagnosed with clinically without lymph node metastasis and having a pathological diagnosis of adenocarcinoma after undergoing surgery. Receiver operating characteristics (ROC) analysis was used to assess the ability to use mCT value, C/T ratio, tumor size, and SUVmax value to predict STAS. Univariate and multiple logistic regression analyses were performed to determine the independent variables for the prediction of STAS.

RESULTS

Forty-one lesions (34.7%) were positive for STAS and 77 lesions were negative for STAS. The STAS positive group was strongly associated with a high mCT value, high C/T ratio, large solid tumor size, large tumor size and high SUVmax value. The mCT values were - 324.9 ± 19.3 HU for STAS negative group and - 173.0 ± 26.3 HU for STAS positive group (p < 0.0001). The ROC area under the curve of the mCT value was the highest (0.738), followed by SUVmax value (0.720), C/T ratio (0.665), solid tumor size (0.649). Multiple logistic regression analyses using the preoperatively determined variables revealed that mCT value (p = 0.015) was independent predictive factors of predicting STAS. The maximum sensitivity and specificity were obtained at a cutoff value of - 251.8 HU.

CONCLUSIONS

The evaluation of mCT value has a possibility to predict STAS and may potentially contribute to the selection of suitable treatment strategies.

Prognosis of spread through air spaces in invasive mucinous lung adenocarcinoma after curative surgery

INTRODUCTION

The purpose of this study is to investigate the prognostic impact of spread through air spaces (STAS) in invasive mucinous adenocarcinoma (IMA).

MATERIALS AND METHODS

From 2015 to 2019, patients who underwent complete resection of IMA were extracted from the prospective database. Multivariable Cox-regression analysis and inverse probability of treatment weight (IPTW) - adjusted log-rank test for 5-year recurrence-free survival (RFS) were performed.

RESULTS

STAS was observed in 39.1% (53 out of 133). The STAS (+) group shows larger tumor size (2.9 ± 2.4 cm vs 3.8 ± 2.4 cm, p = 0.031) and higher incidence of lympho-vascular invasion (6 [7.5%] vs 18 [34.0%], p < 00.001) compared to the STAS (-) group. The 5-year RFS was 66.1% in the STAS (+) group and 91.8% in the STAS (-) group (p < 00.001), and the incidence of locoregional recurrence was significantly higher in the STAS (+) group than the STAS (-) group (1 [1.2%] vs 12 [22.6%], p < 00.001). Multivariable analysis revealed that STAS was associated with poor prognosis for all-recurrence (hazard ratio 2.81, 95% confidence interval 1.01-7.81, p = 0.048). After IPTW adjustment, 5-year RFS was 66.3% in the STAS (+) group and 92.9% in the STAS (-) group (p = 0.007), and risk for locoregional recurrence was greater in the STAS (+) group than the STAS (-) group (1.1 [0.9%] vs 20.8 [16.6%], p < 00.001).

CONCLUSIONS

STAS showed negative prognostic impact on all-recurrence, especially due to locoregional recurrence, after curative resection of IMA.

Human Tumor-Associated Macrophages and Neutrophils Regulate Antitumor Antibody Efficacy through Lethal and Sublethal Trogocytosis

The clinical benefits of tumor-targeting antibodies (tAb) are modest in solid human tumors. The efficacy of many tAbs is dependent on Fc receptor (FcR)-expressing leukocytes that bind Fc fragments of tAb. Tumor-associated macrophages (TAM) and neutrophils (TAN) represent the majority of FcR+ effectors in solid tumors. A better understanding of the mechanisms by which TAMs and TANs regulate tAb response could help improve the efficacy of cancer treatments. Here, we found that myeloid effectors interacting with tAb-opsonized lung cancer cells used antibody-dependent trogocytosis (ADT) but not antibody-dependent phagocytosis. During this process, myeloid cells "nibbled off" tumor cell fragments containing tAb/targeted antigen (tAg) complexes. ADT was only tumoricidal when the tumor cells expressed high levels of tAg and the effectors were present at high effector-to-tumor ratios. If either of these conditions were not met, which is typical for solid tumors, ADT was sublethal. Sublethal ADT, mainly mediated by CD32hiCD64hi TAM, led to two outcomes: (i) removal of surface tAg/tAb complexes from the tumor that facilitated tumor cell escape from the tumoricidal effects of tAb; and (ii) acquisition of bystander tAgs by TAM with subsequent cross-presentation and stimulation of tumor-specific T-cell responses. CD89hiCD32loCD64lo peripheral blood neutrophils (PBN) and TAN stimulated tumor cell growth in the presence of the IgG1 anti-EGFR Ab cetuximab; however, IgA anti-EGFR Abs triggered the tumoricidal activity of PBN and negated the stimulatory effect of TAN. Overall, this study provides insights into the mechanisms by which myeloid effectors mediate tumor cell killing or resistance during tAb therapy.

SIGNIFICANCE

The elucidation of the conditions and mechanisms by which human FcR+ myeloid effectors mediate cancer cell resistance and killing during antibody treatment could help develop improved strategies for treating solid tumors.

Imaging phenotyping using 18F-FDG PET/CT radiomics to predict micropapillary and solid pattern in lung adenocarcinoma

OBJECTIVES

To develop and validate a machine learning model using 18F-FDG PET/CT radiomics signature and clinical features to predict the presence of micropapillary and solid (MP/S) components in lung adenocarcinoma.

METHODS

Eight hundred and forty-six patients who underwent preoperative PET/CT with pathologically confirmed adenocarcinoma were enrolled. After segmentation, 1688 radiomics features were extracted from PET/CT and selected to construct predictive models. Then, we developed a nomogram based on PET/CT radiomics integrated with clinical features. Receiver operating curves, calibration curves, and decision curve analysis (DCA) were performed for diagnostics assessment and test of the developed models for distinguishing patients with MP/S components from the patients without.

RESULTS

PET/CT radiomics-clinical combined model could well distinguish patients with MP/S components from those without MP/S components (AUC = 0.87), which performed better than PET (AUC = 0.829, p < 0.05) or CT (AUC = 0.827, p < 0.05) radiomics models in the training cohort. In test cohorts, radiomics-clinical combined model outperformed the PET radiomics model in test cohort 1 (AUC = 0.859 vs 0.799, p < 0.05) and the CT radiomics model in test cohort 2 (AUC = 0.880 vs 0.829, p < 0.05). Calibration curve indicated good coherence between all model prediction and the actual observation in training and test cohorts. DCA revealed PET/CT radiomics-clinical model exerted the highest clinical benefit.

CONCLUSION

18F-FDG PET/CT radiomics signatures could achieve promising prediction efficiency to identify the presence of MP/S components in adenocarcinoma patients to help the clinician decide on personalized treatment and surveillance strategies. The PET/CT radiomics-clinical combined model performed best. CRITICAL RELEVANCE STATEMENT: 18F-FDG PET/CT radiomics signatures could achieve promising prediction efficiency to identify the presence of micropapillary and solid components in adenocarcinoma patients to help the clinician decide on personalized treatment and surveillance strategies.

Updates on lung adenocarcinoma: invasive size, grading and STAS

Advancements in the classification of lung adenocarcinoma have resulted in significant changes in pathological reporting. The eighth edition of the tumour-node-metastasis (TNM) staging guidelines calls for the use of invasive size in staging in place of total tumour size. This shift improves prognostic stratification and requires a more nuanced approach to tumour measurements in challenging situations. Similarly, the adoption of new grading criteria based on the predominant and highest-grade pattern proposed by the International Association for the Study of Lung Cancer (IASLC) shows improved prognostication, and therefore clinical utility, relative to previous grading systems. Spread through airspaces (STAS) is a form of tumour invasion involving tumour cells spreading through the airspaces, which has been highly researched in recent years. This review discusses updates in pathological T staging, adenocarcinoma grading and STAS and illustrates the utility and limitations of current concepts in lung adenocarcinoma.

Prognostic significance of limited resection in pathologic stage I lung adenocarcinoma with spread through air spaces

Background

Tumor spread through air spaces (STAS) is now recognized as tumor invasion. However, the association between STAS and procedure-specific outcomes (limited resection and lobectomy) in patients with pathologic stage I lung adenocarcinoma (ADC) is still under investigation.

Methods

To investigate whether limited resection predicts poorer survival in such patients, we retrospectively analyzed the clinicopathologic features of a large cohort of 1,566 patients with stage I ADC from 2017 to 2020 and classified them according to STAS status and surgical method. Kaplan-Meier, Cox hazard proportional regression, and propensity score matching (PSM) were adopted for prognostic evaluation.

Results

STAS-positive patients had worse recurrence-free survival (RFS) (P<0.001). There was no significant difference in RFS and overall survival (OS) between limited resection and lobectomy, neither for the STAS-negative nor STAS-positive group before matching. After matching, limited resection was found to achieve comparable RFS to lobectomy in STAS-positive patients with pathologic I, IA, or IB stage tumor, (P=0.816, P=0.576, P=0.281, respectively), but worse OS in stage I and stage IB patients (P=0.029, P=0.010, respectively). Furthermore, in multivariable analysis, limited resection was not an independent prognostic factor of RFS or OS. Instead, the high-grade histological subtype was the only independent prognostic factor for RFS (P=0.001). In the subgroup analysis, adjuvant chemotherapy (ACT) did not improve the outcomes of stage IB STAS-positive patients.

Conclusions

Limited resection was associated with worse survival than lobectomy in stage I STAS-positive patients, but not in stage IA STAS-positive patients.

Spread through Air Spaces (STAS) in Solitary Pulmonary Metastases from Colorectal Cancer (CRC)

BACKGROUND

Spread through air spaces (STAS) is a recently described route of tumor invasion associated with poor prognosis in primary lung cancer. Aim of this study was to investigate the presence of STAS and to assess its prognostic significance in patients undergoing pulmonary metastasectomy (PM) for solitary metastases from colorectal cancer (CRC).

MATERIALS AND METHODS

All 49 CRC patients (30 male and 19 female, median age 66 years) who underwent PM between January 2008 and December 2015 were retrospectively analyzed.

RESULTS

STAS was identified in 26.5% (n = 13) of resected specimens. Location of pulmonary lesions (central vs. peripheral) was assessed based on the available computed tomography imaging (n = 47, 96%). STAS was detected in all five patients with central metastases (100%) versus 7 of 42 (17%) with peripheral metastases (p = 0.0001). Locoregional recurrence occurred in STAS-positive patients (n = 4 of 13 vs. n = 0 of 36), all STAS-negative patients remained recurrence-free (p = 0.003). Median number of alveoli with STAS involvement was four (range from 2 to 9). There was statistically positive relationship between the number of alveoli invaded with STAS and locoregional recurrence of metastases (p = 0.0001). The presence of STAS is not a factor affecting the 5-year overall survival rate (p = 0.6651).

CONCLUSION

We identified STAS as a frequent finding in resected CRC lung metastases and found insignificant association with outcome.

Fluid-sensitive migration mechanisms predict association between metastasis and high interstitial fluid pressure in pancreatic cancer

A remarkable feature in pancreatic cancer is the propensity to metastasize early, even for small, early stage cancers. We use a computer-based pancreatic model to simulate tumor progression behavior where fluid-sensitive migration mechanisms are accounted for as a plausible driver for metastasis. The model has been trained to comply with in vitro results to determine input parameters that characterize the migration mechanisms. To mimic previously studied preclinical xenografts we run the computer model informed with an ensemble of stochastic-generated realizations of unknown parameters related to tumor microenvironment only constrained such that pathological realistic values for interstitial fluid pressure (IFP) are obtained. The in silico model suggests the occurrence of a steady production of small clusters of cancer cells that detach from the primary tumor and form isolated islands and thereby creates a natural prerequisite for a strong invasion into the lymph nodes and venous system. The model predicts that this behavior is associated with high interstitial fluid pressure (IFP), consistent with published experimental findings. The continuum-based model is the first to explain published results for preclinical models which have reported associations between high IFP and high metastatic propensity and thereby serves to shed light on possible mechanisms behind the clinical aggressiveness of pancreatic cancer.

Comprehensive analysis for clarifying transcriptomics landscapes of spread through air spaces in lung adenocarcinoma

Patients with spread through air spaces (STAS) have worse postoperative survival and a higher recurrence rate in lung adenocarcinoma, even in the earliest phases of the disease. At present, the molecular pathogenesis of STAS is not well understood. Therefore, to illustrate the underlying pathogenic mechanism of STAS, we accomplished a comprehensive analysis of a microarray dataset of STAS. Differential expression analysis revealed 841 differentially expressed genes (DEGs) between STAS_positive and STAS_negative groups. Additionally, we acquired two hub genes associated with survival. Gene set variation analysis (GSVA) confirmed that the main differential signaling pathways between the two groups were hypoxia VHL targets, PKC, and pyrimidine metabolism pathways. Analysis of immune activity showed that the increased expression of MHC-class-Ⅰ was observed in the STAS_positive group. These findings provided novel insights for a better knowledge of pathogenic mechanisms and potential therapeutic markers for STAS treatment.

Retrospective analysis of the prognostic implications of tumor spread through air spaces in lung adenocarcinoma patients treated with surgery

Background

Tumor spread through air spaces (STAS) in lung adenocarcinoma is a novel mechanism of invasion. STAS has been proposed as an independent predictor of poor prognosis. The aim of this study was to evaluate the correlations between STAS status and other clinicopathologic variables and to assess the prognostic implications of STAS and the distance from the edge of the tumor to the farthest STAS in patients with resected lung adenocarcinoma.

Material and methods

This is a single-institution retrospective observational study. We included all patients with resected lung adenocarcinoma from January 2017 to December 2018 at La Paz University Hospital. The cut-off for the distance from the edge of the tumor to the farthest STAS was 1.5 mm and was assessed by the area under the receiver operating characteristic curve.

Results

A total of 73 patients were included. STAS was found in 52 patients (71.2%). Histological grade 3 (P = 0.035) and absence of lepidic pattern (P = 0.022) were independently associated with the presence of STAS. The median recurrence-free survival (RFS) was 48.06 months [95% confidence interval (CI) 33.58 months to not reached]. STAS-positive patients had shorter median RFS [39.23 months (95% CI 29.34-49.12 months)] than STAS-negative patients (not reached) (P = 0.04). STAS-positive patients with a distance from the edge of the tumor to the farthest STAS ≥1.5 mm had an even shorter median RFS [37.63 months (95% CI 28.14-47.11 months)]. For every 1 mm increase in distance, the risk of mortality increased by 1.26 times (P = 0.04).

Conclusions

Histological grade 3 and absence of lepidic pattern were independently associated with the presence of STAS. STAS was associated with a higher risk of recurrence. The distance from the edge of the tumor to the farthest STAS also had an impact on overall survival.

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Lung adenocarcinoma patients with STAS had higher risk of recurrence.

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Patients with STAS and a distance from the edge of the tumor to the farthest STAS ≥1.5 mm had an even shorter RFS.

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The distance from the edge of the tumor to the farthest STAS also had an impact on overall survival.

The Value of CT-Based Radiomics for Predicting Spread Through Air Spaces in Stage IA Lung Adenocarcinoma

Objectives

Spread through air spaces (STAS), a new invasive pattern in lung adenocarcinoma (LUAD), is a risk factor for poor outcome in early-stage LUAD. This study aimed to develop and validate a CT-based radiomics model for predicting STAS in stage IA LUAD.

Methods

A total of 395 patients (169 STAS positive and 226 STAS negative cases, including 316 and 79 patients in the training and test sets, respectively) with stage IA LUAD before surgery were retrospectively included. On all CT images, tumor size, types of nodules (solid, mix ground-glass opacities [mGGO] and pure GGO [pGGO]), and GGO percentage were recorded. Region of interest (ROI) segmentation was performed semi-automatically, and 1,037 radiomics features were extracted from every segmented lesion. Intraclass correlation coefficients (ICCs), Pearson’s correlation analysis and least absolute shrinkage and selection operator (LASSO) penalized logistic regression were used to filter unstable (ICC &lt; 0.75) and redundant features (r &gt; 0.8). A temporary model was established by multivariable logistic regression (LR) analysis based on selected radiomics features. Then, seven radiomics features contributing the most were selected for establishing the radiomics model. We then built two predictive models (clinical-CT model and MixModel) based on clinical and CT features only, and the combination of clinical-CT and Rad-score, respectively. The performances of these three models were assessed.

Results

The radiomics model achieved good performance with an area under of curve (AUC) of 0.812 in the training set, versus 0.850 in the test set. Furthermore, compared with the clinical-CT model, both radiomics model and MixModel showed higher AUC and better net benefit to patients in the training and test cohorts.

Conclusion

The CT-based radiomics model showed satisfying diagnostic performance in early-stage LUAD for preoperatively predicting STAS, with superiority over the clinical-CT model.

Peritumoral radiomics features on preoperative thin-slice CT images can predict the spread through air spaces of lung adenocarcinoma

The spread through air spaces (STAS) is recognized as a negative prognostic factor in patients with early-stage lung adenocarcinoma. The present study aimed to develop a machine learning model for the prediction of STAS using peritumoral radiomics features extracted from preoperative CT imaging. A total of 339 patients who underwent lobectomy or limited resection for lung adenocarcinoma were included. The patients were randomly divided (3:2) into training and test cohorts. Two prediction models were created using the training cohort: a conventional model based on the tumor consolidation/tumor (C/T) ratio and a machine learning model based on peritumoral radiomics features. The areas under the curve for the two models in the testing cohort were 0.70 and 0.76, respectively (P = 0.045). The cumulative incidence of recurrence (CIR) was significantly higher in the STAS high-risk group when using the radiomics model than that in the low-risk group (44% vs. 4% at 5 years; P = 0.002) in patients who underwent limited resection in the testing cohort. In contrast, the 5-year CIR was not significantly different among patients who underwent lobectomy (17% vs. 11%; P = 0.469). In conclusion, the machine learning model for STAS prediction based on peritumoral radiomics features performed better than the C/T ratio model.

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.

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.

Assessment of the feasibility of frozen sections for the detection of spread through air spaces (STAS) in pulmonary adenocarcinoma

Spread through air spaces (STAS) is reportedly associated with worse prognosis in sublobar resections of lung adenocarcinoma. Recently, it was proposed that STAS detected on frozen sections can be an indication for lobectomy instead of sublobar resection. We undertook this study to evaluate the reliability of STAS assessment on frozen sections compared to permanent sections, as well as the associations among STAS, tumor grade, and recurrence-free survival (RFS) after sublobar resection. A total of 163 stage I lung adenocarcinoma resections with frozen sections were identified retrospectively. For each case, and for frozen and permanent sections separately, the presence or absence of STAS, as well as the tumor grade, were recorded. Compared to permanent sections, STAS detection on frozen sections had low sensitivity (55%), low positive predictive value (48%), and fair agreement (K = 0.34), whereas there was higher specificity (80%) and negative predictive value (85%). Accuracy was 74%. Tumor grade assessment on frozen sections showed higher sensitivity (77%), positive predictive value (90%), agreement (K = 0.72), specificity (94%), and accuracy (87%), and the same negative predictive value (85%). High-grade histology on frozen sections was associated with shorter RFS (p = 0.02), whereas STAS on frozen sections was not (p = 0.47). Our results suggest that the intraoperative detection of STAS has low sensitivity and positive predictive value. False-positive results may lead to overtreatment of patients with lung cancer. The determination of tumor grade on frozen sections offers better sensitivity and specificity, plus it is associated with RFS, whereas STAS on frozen sections is not. Further study is needed to explore the utility of assessing tumor grade on frozen sections.

[Research Progress on Spread Through Air Spaces of Lung Cancer]

The concept of spread through air spaces (STAS) was first proposed in the World Health Organization (WHO) Classification of Tumors of the Lung, Pleura, Thymus and Heart (version 2015). STAS is defined as the micropapillary clusters, solid nests or single cells of tumor that exist in the air spaces of the surrounding lung parenchyma beyond the edge of the main tumor. Meanwhile, apart from the traditional invasion modes of lung adenocarcinoma (interstitial, visceral pleura and lym-phovascular invasion), STAS has been identified as the fourth invasion mode of lung adenocarcinoma. In recent years, the research on STAS has been a hot spot in the field of lung adenocarcinoma. The existence of STAS is related to lung cancer histopathology, gene mutation and other factors, and many studies have also confirmed that it can be used as an independent factor for tumor recurrence and prognosis. However, according to some studies, human factors can cause morphological artifacts of STAS, which still needs to be distinguished in clinical work. This paper reviews the research progress of STAS classification, related pathological features, genetic status changes, and human factors that may cause STAS artifacts.
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The Lymphatic Spread of Lung Cancer: An Investigation of the Anatomy of the Lymphatic Drainage of the Lungs and Preoperative Mediastinal Staging

The knowledge of lymphatic spread of lung cancer permitted the study of anatomy of lymphatic drainage of the lungs. The history of anatomy of lymphatic drainage of the lungs began in the 15th century. In the human, pulmonary lymph flows to the lymph nodes around the lobar bronchi and thence to extrapulmonary lymph nodes located around the main bronchi and trachea and its bifurcation (tracheobronchial lymph nodes). These send their efferents to a right and left mediastinal lymph trunks, which may join the thoracic duct, but usually drain opening directly into the brachiocephalic vein of their own side.

Aerogenous Metastasis and Spread Through the Air Spaces - Distinct Entities or Spectrum of the Same Process?

Clinicopathological and imaging studies indicate that metastatic spread of cancer cells through the airways may occur in primary lung cancer. The term aerogenous metastasis was been proposed years before the concept of spread through the airspaces (STAS) was introduced in the current World Health Organization classification. The pathogenesis of STAS has not been fully elucidated. The current definition of STAS is controversial and limited to early stage adenocarcinomas. In this article, existing knowledge on the pathogenesis, histology, imaging findings, and clinical and prognostic significance of these 2 entities is presented.

Meta-analysis of Lobectomy and Sublobar Resection for Stage I Non-small Cell Lung Cancer With Spread Through Air Spaces

Surgery is the preferred treatment for early-stage non-small cell lung cancer (NSCLC). Numerous studies have shown that spread through air spaces (STAS) can predict the survival of patients with stage I NSCLC. However, for stage I NSCLC, it is not known whether sublobar resection or lobectomy should be performed if STAS is present. In the present study, we compared the survival outcomes of patients with STAS who underwent lobectomy versus those who underwent sublobar resection. A search was performed on the PubMed, Cochrane Library and EMBASE on March 6, 2021 to identify relevant studies. Predetermined criteria were utilized to screen studies. A meta-analysis was performed using hazard ratio (HR). In total, 13 studies involving 5947 patients were included in the meta-analysis. It was found that STAS was significantly correlated with worse RFS (HR = 2.58, 95% CI: 2.16-3.07) and OS (HR = 2.41, 95% CI: 1.97-2.95) in patients with stage I NSCLC. Lobectomy resulted in a longer RFS (HR = 2.59, 95% CI: 1.99-3.37) and OS (HR = 2.78, 95% CI: 1.92-4.02) than sublobar resection in stage I NSCLC patients with STAS. STAS is an independent prognostic factor in NSCLC. Lobectomy may be more effective for stage I NSCLC patients who underwent sublobar resection previously if STAS is present.

Radiomic values from high-grade subtypes to predict spread through air spaces in lung adenocarcinoma

BACKGROUND

We aimed to establish a radiomic prediction model for tumor spread through air spaces (STAS) in lung adenocarcinoma using radiomic values from high-grade subtypes (solid and micropapillary).

METHODS

We retrospectively reviewed 327 patients with lung adenocarcinoma from two institutes (Cohort 1: 227 patients; Cohort 2: 100 patients) between March 2017 and March 2019. STAS was identified in 113 (34.6%) patients. A high-grade likelihood prediction model was constructed based on a historical cohort of 82 patients with "near-pure" pathological subtype. The STAS prediction model based on the patch-wise mechanism identified the high-grade likelihood area for each voxel within the internal border of the tumor. STAS presence was indirectly predicted by a volume percentage threshold of the high-grade likelihood area. Performance was evaluated by receiver operating curve analysis with 10-repetition, 3-fold cross-validation in Cohort 1, and was individually tested in Cohort 2.

RESULTS

Overall, 227 patients (STAS-positive: 77 [33.9%]) were enrolled for cross-validation (Cohort 1) while 100 (STAS-positive: 36 [36.0%]) underwent individual testing (Cohort 2). The gray level co-occurrence matrix (variance) and histogram (75^th percentile) features were selected to construct the high-grade likelihood prediction model, which was used as the STAS prediction model. The proposed model achieved good performance in Cohort 1 with an area under the curve, sensitivity, and specificity, of 81.44%, 86.75%, and 62.60%, respectively, and correspondingly, in Cohort 2, they were 83.16%, 83.33%, and 63.90%, respectively.

CONCLUSIONS

The proposed computed tomography-based radiomic prediction model could help guide preoperative prediction of STAS in early-stage lung adenocarcinoma and relevant surgeries.

[Pathological and Molecular Features of Lung Micropapillary Adenocarcinoma]

肺微乳头腺癌作为高级别肺腺癌，具频发转移、淋巴结浸润、复发率高和总体生存率低的临床特征。该亚型肿瘤中存在特征致癌因子通路的激活和肿瘤免疫微环境的建立。本文拟对近年来微乳头腺癌的病理学表现及分子学特征研究进展作一综述，旨在加深对微乳头型病变的认识，进而为制定特异性治疗策略奠定基础。

The prediction of spread through air spaces with preoperative 18F-FDG PET/CT in cases with primary lung adenocarcinoma, its effect on the decision for an adjuvant treatment and its prognostic role

PURPOSE

In lung adenocarcinoma cases, 'spread through air spaces' (STAS) is a new indicator of invasion and directly related to disease survival. The aim of our study is to establish whether a preoperatively performed 18F-Fluorodeoxyglucose (FDG) PET/computed tomography (CT) imaging data can predict the presence of STAS in cases with lung adenocarcinoma and thus predict the decision for the type of surgery and adjuvant chemotherapy.

MATERIALS AND METHODS

Between 2000 and 2019, we retrospectively analyzed 63 patients with lung adenocarcinoma cases that had undergone lobectomy or pneumonectomy. Semiquantitative parameters were calculated and metabolic tumor volume (MTV)/CT volume (CTV) ratio was recorded from FDG PET/CT data. The pathological samples from these patients were evaluated for STAS. All these values were evaluated for their correlation with the alveolar spread.

RESULTS

There was no statistically significant correlation to be found between CTV, MTV, total lesion glycolysis (TLG), standardized uptake value (SUV)max, SUVmean and STAS (P > 0.05). However, MTV/CTV ratio above 1 had statistically more alveolar spread. In the group with an MTV ratio above 1, STAS positivity was 27 (75%), and 9 (25%) did not have STAS, whereas these were 6 (22.2%) patients who had STAS, and 21 (77.8%) did not have STAS in the group with below 1 (P < 0.001).

CONCLUSIONS

In the preoperative PET study inoperable lung adenocarcinoma cases, MTV/CTV ratio higher than 1 was found to predict STAS positivity. As a result, it was found that it provided significant clinical additional information regarding the need for a surgical approach (lobar resection instead of sublobar) and adjuvant chemotherapy.

Clinical implication of tumour spread through air spaces in pathological stage I lung adenocarcinoma treated with lobectomy

OBJECTIVES

The aim of this study was to evaluate the clinical implication of tumour spread through air spaces (STAS) as a prognostic factor in pathological stage I lung adenocarcinoma treated with lobectomy and to identify related parameters.

METHODS

Medical records of patients who underwent pulmonary lobectomy for stage I (American Joint Committee on Cancers eighth edition) lung adenocarcinomas between 2012 and February 2018 at our institutions were reviewed retrospectively. Patients with minimally invasive adenocarcinomas and tumours ≥3 cm in size were excluded. Included patients were classified into STAS (+) and STAS (-) groups. Clinical implications of STAS and recurrence in patients were investigated.

RESULTS

A total of 109 patients was analysed: 41 (37.6%) in the STAS (+) and 68 (62.4%) in the STAS (-) group. STAS was associated with larger consolidation diameter on chest tomography (≥1.5 cm; P = 0.006) or a higher invasive ratio (≥85%; P = 0.012) and presence of a micropapillary pattern in multivariable analysis (P = 0.003) The recurrence-free survival curve showed statistical difference (P = 0.008) with 3-year survival rates of 73.0% (9 patients) and 96.8% (2 patients) in the STAS (+) and STAS (-) group, respectively. However, no statistical significance was observed in the lung cancer-related survival curve (P = 0.648). The presence of STAS was an independent risk factor for recurrence in multivariable analysis (hazard ratio = 5.9, P = 0.031).

CONCLUSIONS

The presence of STAS could be an important risk factor for recurrence in patients with early-stage invasive lung adenocarcinoma treated with pulmonary lobectomy.

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.

Radiomics is feasible for prediction of spread through air spaces in patients with nonsmall cell lung cancer

Tumor spread through air spaces (STAS) in non-small-cell lung cancer (NSCLC) is known to influence a poor patient outcome, even in patients presenting with early-stage disease. However, the pre-operative diagnosis of STAS remains challenging. With the progress of radiomics-based analyses several attempts have been made to predict STAS based on radiological findings. In the present study, patients with NSCLC which is located peripherally and tumors ≤ 2 cm in size on computed tomography (CT) that were potential candidates for sublobar resection were enrolled in this study. The radiologic features of the targeted tumors on thin-section CT were extracted using the PyRadiomics v3.0 software package, and a predictive model for STAS was built using the t-test and XGBoost. Thirty-five out of 226 patients had a STAS histology. The predictive model of STAS indicated an area under the receiver-operator characteristic curve (AUC) of 0.77. There was no significant difference in the overall survival (OS) for lobectomy between the predicted-STAS (+) and (−) groups (p = 0.19), but an unfavorable OS for sublobar resection was indicated in the predicted-STAS (+) group (p < 0.01). These results suggest that radiomics with machine-learning helped to develop a favorable model of STAS (+) NSCLC, which might be useful for the proper selection of candidates who should undergo sublobar resection.

Comparison of Diagnostic Performance of Spread Through Airspaces of Lung Adenocarcinoma Based on Morphological Analysis and Perinodular and Intranodular Radiomic Features on Chest CT Images

Object

STAS is associated with poor differentiation, KRAS mutation and poor recurrence-free survival. The aims of this study are to evaluate the ability of intra- and perinodular radiomic features to distinguish STAS at non-contrast CT.

Patients and Methods

This retrospective study included 216 patients with pathologically confirmed lung adenocarcinoma (STAS+, n = 56; STAS-, n = 160). Texture-based features were extracted from intra- and perinodular regions of 2, 4, 6, 8, 10, and 20 mm distances from the tumor edge using an erosion and expansion algorithm. Traditional radiologic features were also analyzed including size, consolidation tumor ratio (CTR), density, shape, vascular change, cystic airspaces, tumor-lung interface, lobulation, spiculation, and satellite sign. Nine radiomic models were established by using the eight separate models and a total of the eight VOIs (eight-VOI model). Then the prediction efficiencies of the nine radiomic models were compared to predict STAS of lung adenocarcinomas.

Results

Among the traditional radiologic features, CTR, unclear tumor-lung interface, and satellite sign were found to be associated with STAS significantly, and the AUCs were 0.796, 0.677, and 0.606, respectively. Radiomic model of combined tumor bodies and all the distances of perinodular areas (eight-VOI model) had better predictive efficiency for predicting STAS+ lung adenocarcinoma. The AUCs of the eight-VOI model in the training and verification sets were 0.907 (95%CI, 0.862-0.947) in the training set, and 0.897 (95%CI, 0.784-0.985) in the testing set, and 0.909 (95%CI, 0.863-0.949) in the external validation set, and the diagnostic accuracy in the external validation set was 0.849.

Conclusion

Radiomic features from intra- and perinodular regions of nodules can best distinguish STAS of lung adenocarcinoma.

In silico investigations of intratumoral heterogeneous interstitial fluid pressure

Recent preclinical studies have shown that interstitial fluid pressure (IFP) within tumors can be heterogeneous Andersen et al. (2019). In that study tumors of two xenograft models, respectively, HL-16 cervical carcinoma and Panc-1 pancreatic carcinoma, were investigated. Significant heterogeneity in IFP was reported and it was proposed that this was associated with division of tissue into compartments separated by thick connective tissue bands for the HL-16 tumors and with dense collagen-rich extracellular matrix for the Panc-1 tumors. The purpose of the current work is to explore these experimental observations by using in silico generated tumor models. We consider a mathematical multiphase model which accounts for tumor cells, fibroblasts and interstitial fluid. The model has been trained to comply with experimental in vitro results reported in Shieh et al. (2011) which has identified autologous chemotaxis, ECM remodeling, and cell-fibroblast interaction as drivers for invasive tumor cell behavior. The in silico model is informed with parameters that characterize the leaky intratumoral vascular network, the peritumoral lymphatics which collect the fluid, and the density of ECM as represented through the hydraulic conductivity of the interstitial space. Heterogeneous distribution of solid stress may result in heterogeneous compression of blood vessels and, thus, heterogeneous vascular density inside the tumor. To mimic this we expose the in silico tumor to an intratumoral vasculature whose net effect of density of blood vesssels and vessel wall conductivity is varied through a 2D Gaussian variogram constrained such that the resulting IFPs lie within the range as reported from the preclinical study. The in silico cervical carcinoma model illustrates that sparse ECM was associated with uniform intratumoral IFP in spite of heterogeneous microvascular network, whereas compartment structures resulted in more heterogeneous IFP. Similarly, the in silico pancreatic model shows that heterogeneity in the microvascular network combined with dense ECM structure prevents IFP to even out and gives rise to heterogeneous IFP. The computer model illustrates how a heterogeneous invasive front might form where groups of tumor cells detach from the primary tumor and form isolated islands, a behavior which is natural to associate with metastatic propensity. However, unlike experimental studies, the current version of the in silico model does not show an association between metastatic propensity and elevated IFP.

Current status and perspectives of spread through air spaces in lung cancer

According to the World Health Organization classification of 2015, spread through air spaces (STAS) is a newly recognized pattern of invasion in lung adenocarcinoma. Many researchers have reported that STAS is recognized in all histological subtypes, and there is a strong association between STAS and prognosis in lung cancer. However, there are several technical issues associated with STAS, such as distinction between the actual in vivo phenomenon and an artifact, difficulty in assessing STAS in frozen specimens, and establishing the relationship between morphological and molecular properties of STAS. This review focuses on the current state of knowledge and the outlook of the STAS phenomenon from the perspective of surgeons, pathologists, and radiologists.

Morphological Subtypes of Tumor Spread Through Air Spaces in Non-Small Cell Lung Cancer: Prognostic Heterogeneity and Its Underlying Mechanism

Background

Tumor spread through air spaces (STAS) has three morphologic subtypes: single cells, micropapillary clusters, and solid nests. However, whether their respective clinical significance is similar remains unclear.

Methods

We retrospectively reviewed 803 patients with resected non-small cell lung cancer (NSCLC) from January to December 2009. Recurrence-free survival (RFS) and overall survival (OS) were compared among patients stratified by STAS subtypes. We also performed a prospective study of NSCLC resection specimens to evaluate the influence of a prosecting knife on the presence of STAS subtypes during specimen handling (83 cases).

Results

STAS was found in 370 NSCLCs (46%), including 47 single cell STAS (13%), 187 micropapillary cluster STAS (50%), and 136 solid nest STAS (37%). STAS-negative patients had significantly better survival than patients with micropapillary cluster STAS (RFS: P < 0.001; OS: P < 0.001) and solid nest STAS (RFS: P < 0.001; OS: P < 0.001), but similar survival compared with those with single cell STAS (RFS: P = 0.995; OS: P = 0.71). Multivariate analysis revealed micropapillary cluster (RFS: P < 0.001; OS: P < 0.001) and solid nest STAS (RFS: P = 0.001; OS: P = 0.003) to be an independent prognostic indicator, but not for single cell STAS (RFS: P = 0.989; OS: P = 0.68). Similar results were obtained in subgroup analysis of patients with adenocarcinoma. The prospective study of NSCLC specimens suggested that 18 cases were considered as STAS false-positive, and most were singe cell pattern (13/18, 72%).

Conclusions

Single cell STAS was the common morphologic type of artifacts produced by a prosecting knife. A precise protocol of surgical specimen handling is required to minimize artifacts as much as possible.

Tumor spread through air spaces (STAS): prognostic significance of grading in non-small cell lung cancer

Tumor spread through air spaces (STAS) is an invasive pattern of lung cancer that was recently described. In this study, we investigated the association between the extent of STAS and clinicopathological characteristics and patient outcomes in resected non-small cell lung cancers (NSCLCs). STAS has been prospectively described from 2008 and graded its extent with a two-tiered system (STAS I: <2500 μm [one field of ×10 objective lens] from the edge of tumor and STAS II: ≥2500 μm from the edge of tumor) from 2011 in Seoul National University Bundang Hospital. We retrospectively analyzed the correlations between the extent of STAS and clinicopathologic characteristics and prognostic significance in 1869 resected NSCLCs. STAS was observed in 765 cases (40.9%) with 456 STAS I (24.4%) and 309 STAS II (16.5%). STAS was more frequently found in patients with adenocarcinoma (ADC) (than squamous cell carcinoma), pleural invasion, lymphovascular invasion, and/or higher pathologic stage. In ADC, there were significant differences in recurrence free survival (RFS), overall survival (OS), and lung cancer specific survival (LCSS) according to the extent of STAS. In stage IA non-mucinous ADC, multivariate analysis revealed that STAS II was significantly associated with shorter RFS and LCSS (p < 0.001 and p = 0.006, respectively). In addition, STAS II was an independent poor prognostic factor for recurrence in both limited and radical resection groups (p = 0.001 and p = 0.023, respectively). In conclusion, presence of STAS II was an independent poor prognostic factor in stage IA non-mucinous ADC regardless of the extent of resection.

Gross Specimen Handling Procedures Do Not Impact the Occurrence of Spread Through Air Spaces (STAS) in Lung Cancer

Spread Through Air Spaces (STAS) is a form of invasion characterized by neoplastic cell dissemination in the lung parenchyma surrounding the outer edge of the tumor. Its possible artifactual origin is widely debated in the literature. The aim of this study is to investigate the potential impact of gross sampling procedures in causing STAS. A prospective series of 51 surgical lung specimens was collected (35 adenocarcinomas, 68.6%; 13 squamous cell carcinomas, 25.5%; 2 large-cell neuroendocrine carcinomas, 3.9%; 1 atypical carcinoid, 2%). The fresh tissue was sectioned with a new and clean blade for each cut, to obtain a tissue slice comprising the upper lung parenchyma, the tumor, and the lower parenchyma. This slice was cut in half and separately processed. The same procedure was repeated in the residual (specular) specimen after formalin fixation. STAS was identified in 33/51 (64.7%) cases, the predominant pattern being cluster formation (29 cases, 87.9%), the remaining 4 cases having single-cell invasion. Comparing STAS detection in upper and lower lung parenchyma areas (ie, before and after the blade crossed the tumor), no significant preferential STAS distribution was observed, indeed being almost overlapping (60.6% and 63.6% for fresh and 61.3% and 65.6% for fixed tissues, respectively). There was no difference between STAS occurrence in freshly cut and fixed corresponding samples. These findings indicate that STAS is not a pathologist-related artifactual event because of knife transportation of tumor cells during gross specimen handling and support the notion that it is a phenomenon preexisting to surgical tissue processing.

[Investigation and Analysis of Primary Lung Cancer with Endotracheal and Endobronchial Metastases]

背景与目的

气管支气管转移（endotracheal and endobronchial metastases, EEM）在肺癌中罕见，国外文献报道可发生于手术切除后，但国内目前尚未见相关报道，本研究旨在总结和分析肺癌发生EEM的临床特征。

方法

回顾2015年1月-2018年12月于北京大学第三医院确诊原发性肺癌并行支气管镜的患者，同时检索截至2020年2月PubMed检索系统中的病例，采集并比较两组患者的临床、病理、影像、支气管镜和预后等资料。

结果

我院共有6例肺癌伴EEM入选，发生率为0.62%（6/967），均为初诊为肺癌时即伴有EEM。鳞癌4例，腺癌1例，小细胞肺癌1例。Ⅲb期1例，Ⅳ期5例。中央型肺癌5例，周围型1例。EEM在支气管镜下表现为肺癌原发灶之外的气道黏膜结节或息肉性病变5例、局灶性黏膜异常1例。转移至对侧支气管5例，至同侧支气管和气管各1例。中位总生存期为7.5个月。从PubMed数据库共检索到13例，其中12例为肺癌术后随诊胸部计算机断层扫描（computed tomography, CT）异常继而确诊为EEM。中央型9例，鳞癌8例，EEM在CT上表现为腔内结节10例，气管壁局限增厚2例，支气管镜下均表现为气道黏膜结节或息肉样病变。转移至气管10例，至对侧支气管5例，至同侧支气管1例。

结论

EEM是原发性肺癌罕见的转移方式，可发生于初诊时，也可发生于术后，多见于晚期中央型鳞癌，预后差。

Accuracy and Reproducibility of Intraoperative Assessment on Tumor Spread Through Air Spaces in Stage 1 Lung Adenocarcinomas

INTRODUCTION

Tumor spread through air spaces (STAS) is associated with worse prognosis in early-stage lung adenocarcinomas, particularly in sublobar resection. Intraoperative consultation for STAS has been advocated to guide surgical management. However, data on accuracy and reproducibility of intraoperative assessment of STAS remain limited. We evaluated diagnostic yield, interobserver agreement (IOA), and intraobserver agreement (ITA) for STAS detection on frozen section (FS).

METHODS

A panel of three pathologists evaluated stage 1 lung adenocarcinomas (n = 100) for the presence or absence of STAS and artifacts as reference. Five pulmonary pathologists independently reviewed all cases in two rounds, detecting STAS and artifacts in FS and the corresponding FS permanent and non-FS permanent, with a consensus conference between rounds.

RESULTS

The FS had low sensitivity (44%), high specificity (91%), relatively high accuracy (71%), and overall area under the receiver operating characteristic curve of 0.67 for detecting STAS. The average ITA was moderate for both STAS (κ_mean: 0.598) and artifact (κ_mean: 0.402) detection on FS. IOA was moderate for STAS (κ_round-1: 0.453; κ_round-2: 0.506) and fair for artifact (κ_round-1: 0.300; κ_round-2: 0.204) detection on FS. IOA for STAS improved in FS permanent and non-FS permanent, whereas ITA was similar across section types. On multivariable logistic regression, the only significant predictor of diagnostic discordance was the presence of artifacts.

CONCLUSIONS

FS is highly specific but not sensitive for STAS detection in stage 1 lung adenocarcinomas. IOA on STAS is moderate in FS and improved only marginally after a consensus conference, raising concerns regarding global implementation of intraoperative assessment of STAS and warranting more precise criteria for STAS and artifacts.

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.

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.

Meta-analysis of association between CT-based features and tumor spread through air spaces in lung adenocarcinoma

Objective

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 after sublobar resection. The aims of this study are to evaluate the association between computed tomography (CT)-based features and STAS for preoperative prediction of STAS in lung adenocarcinoma, eventually, which could help us choose appropriate surgical type.

Methods

Systematic research was conducted to search for studies published before September 1, 2019. The association between CT-based features of radiological tumor size>2 cm、pure solid nodule、 part-solid nodule or Percentage of solid component (PSC)>50% and STAS was evaluated. According to rigorous inclusion and exclusion criteria. Eight studies including 2385 patients published between 2015 and 2018 were finally enrolled in our meta-analysis.

Results

Our results clearly depicted that there is no significant relationship between radiological tumor size>2 cm and STAS with the combined OR of 1.47(95% CI:0.86–2.51). Meta-analysis of 3 studies showed that pure solid nodule in CT image were more likely to spread through air spaces with pooled OR of 3.10(95%CI2.17–4.43). Meta-analysis of 5 studies revealed the part-solid nodule in CT image may be more likely to appear STAS in adenocarcinoma (ADC) (combined OR:3.10,95%CI:2.17–4.43). PSC>50% in CT image was a significant independent predictor in the diagnosis of STAS in ADC from our meta-analysis with combined OR of 2.95(95%CI:1.88–4.63).

Conclusion

In conclusion, The CT-based features of pure solid nodule、part-solid nodule、PSC>50% are promising imaging biomarkers for predicting STAS in ADC and may substantially influence the choice of surgical type. In future, more studies with well-designed and large-scale are needed to confirm the conclusion.

Solid Nodule Appearance as a Predictor of Tumor Spread Through Air Spaces in Patients with Lung Adenocarcinoma: A Propensity Score Matching Study

OBJECTIVE

Spread through air spaces (STAS) has been reported to be an invasive histological pattern with poor prognosis in lung cancer; however, little is known about its intrinsic risk factors. This work analyzed the correlation between pathological and radiological features and STAS in resected lung adenocarcinomas.

PATIENTS AND METHODS

We retrospectively reviewed 1821 consecutive surgically treated patients with histologically diagnosed lung adenocarcinoma (174 positive for STAS and 1647 negative for STAS) from December 2017 to November 2018 at our institution. Propensity score matching identified 170 well-balanced pairs of patients. The correlations between pathological and radiological features and the presence of STAS were analyzed.

RESULTS

Before propensity matching, the incidence rate of STAS was 9.6% in all patients. In matched cohorts, multivariate analysis showed that the presence of STAS was significantly correlated with pure solid nodules (SNs) (p = 0.001) and solid/micropapillary patterns (SMPs) (p = 0.002). The odds ratio for STAS in SN-positive and SMP-positive adenocarcinoma against that in SN-negative and SMP-negative adenocarcinoma was 10.922 (95% confidence interval, 5.826-20.475; p < 0.001). Tumor differentiation, visceral pleural invasion (VPI), lymphovascular invasion (LVI), invasive adenocarcinoma, and non-lepidic subtype were significantly associated with STAS in the univariate analysis (p < 0.05); however, the differences failed to reach a significant level in the multivariate analysis.

CONCLUSION

We found that STAS was significantly correlated with several invasive clinicopathological patterns. The presence of SNs and SMPs were revealed as independent predictors for STAS, which could offer clinicians clues to identify STAS-positive adenocarcinoma.

Novel imprint cytological classification is correlated with tumor spread through air spaces in lung adenocarcinoma

OBJECTIVES

Spread through air spaces (STAS) is a risk factor for local recurrence after sublobar resection in lung cancer patients. We recently proposed the novel Nakayama-Higashiyama imprint cytological classification (N-H classification) based on small-sized lung adenocarcinoma surgical specimens, which correlated with histological patterns and nodal involvement. This study aimed to evaluate the correlation between STAS and the N-H classification and to validate the N-H classification as an intraoperative predictor of the presence of STAS.

MATERIALS AND METHODS

We retrospectively analyzed 164 intraoperative imprint cytologies and their paired histologic specimens from patients undergoing surgical resection for lung adenocarcinoma in our institute in 2017-2019. Using the NH classification, imprint cytological findings were classified into 5 groups (Groups I to V) based on cell cluster shape, cell and nucleus size, and the existence of necrosis. We examined the characteristics of imprint cytology and STAS in the resected tissues and analyzed the relationship between them.

RESULTS

Tumor STAS was observed in 29 (17.7 %) cases. The presence of STAS was significantly associated with the NH classification (P < 0.0001). STAS was present in 6 of 57 cases (10.5 %) in NH classification Group II, 11 of 42 cases (26.2 %) in Group III, and 12 of 28 cases (42.9 %) in Group IV/V; STAS was not observed in any case in Group I. Logistic regression analysis revealed that tumors with a ground glass opacity rate of <50 % on computed tomography (P = 0.00867) and Groups III-V of the NH classification (P = 0.00201) were significant independent predictors for STAS.

CONCLUSION

Intraoperative imprint cytology with the N-H classification for lung adenocarcinoma is well correlated with the STAS status of the tumor and might have applications as an intraoperative predictive marker of STAS. This classification may be useful for intraoperative detection of STAS and in the decision-making process for the surgical procedure.