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Objectives: With the increasing popularity of CT screening, more cases of early-stage lung cancer are being diagnosed. However, 24.5% of stage I non-small-cell lung cancer (NSCLC) patients still experience treatment failure post-surgery. Biomarkers to predict lung cancer patients at high risk of recurrence are needed., Materials and Methods: We collected protein mass spectrometry data from the Taiwan Lung Cancer Moonshot Project and performed bioinformatics analysis on proteins with differential expressions between tumor and adjacent normal tissues in 74 stage I lung adenocarcinoma (LUAD) cases, aiming to explore the tumor microenvironment related prognostic biomarkers. Findings were further validated in 6 external cohorts., Results: The analysis of differentially expressed proteins revealed that the most enriched categories of diseases and biological functions were cellular movement, immune cell trafficking, and cancer. Utilizing proteomic profiling of the tumor microenvironment, we identified five prognostic biomarkers (ADAM10, MIF, TEK, THBS2, MAOA). We then developed a risk score model, which independently predicted recurrence-free survival and overall survival in stage I LUAD. Patients with high risk scores experienced worse recurrence-free survival (adjusted hazard ratio = 8.28, p < 0.001) and overall survival (adjusted hazard ratio = 6.88, p = 0.013). Findings had been also validated in the external cohorts., Conclusion: The risk score model derived from proteomic profiling of tumor microenvironment can be used to predict recurrence risk and prognosis of stage I LUAD., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objectives: Invasive adenocarcinomas (IADs) have been identified among nonsolid nodules (NSNs) assigned as Lung Imaging Reporting and Data System (Lung-RADS) category 2. This study used visual assessment for differentiating IADs from noninvasive lesions (NILs) in this category., Methods: This retrospective study included 222 patients with 242 NSNs, which were resected after preoperative computed tomography (CT)-guided dye localization. Visual assessment was performed by using the lung and bone window (BW) settings to classify NSNs into BW-visible (BWV) and BW-invisible (BWI) NSNs. In addition, nodule size, shape, border, CT attenuation, and location were evaluated and correlated with histopathological results. Logistic regression was performed for multivariate analysis. A p value of < 0.05 was considered statistically significant., Results: A total of 242 NSNs (mean diameter, 7.6 ± 2.8 mm), including 166 (68.6%) BWV and 76 (31.4%) BWI NSNs, were included. IADs accounted for 31% (75) of the nodules. Only 4 (5.3%) IADs were identified in the BWI group and belonged to the lepidic-predominant (n = 3) and acinar-predominant (n = 1) subtypes. In univariate analysis for differentiating IADs from NILs, the nodule size, shape, CT attenuation, and visual classification exhibited statistical significance. Nodule size and visual classification were the significant predictors for IAD in multivariate analysis with logistic regression (p < 0.05). The sensitivity, specificity, positive predictive value, and negative predictive value of visual classification in IAD prediction were 94.7%, 43.1%, 42.8%, and 94.7%, respectively., Conclusions: The window-based visual classification of NSNs is a simple and objective method to discriminate IADs from NILs., Clinical Relevance Statement: The present study shows that using the bone window to classify nonsolid nodules helps discriminate invasive adenocarcinoma from noninvasive lesions., Key Points: • Evidence has shown the presence of lung adenocarcinoma in Lung-RADS category 2 nonsolid nodules. • Nonsolid nodules are classified into the bone window-visible and the bone window-invisible nonsolid nodules, and this classification differentiates invasive adenocarcinoma from noninvasive lesions. • The Lung-RADS category 2 nonsolid nodules are unlikely invasive adenocarcinoma if they show nonvisualization in the bone window., (© 2023. The Author(s), under exclusive licence to European Society of Radiology.)

Background: Sublobar resection is strongly associated with poor prognosis in early-stage lung adenocarcinoma, with the presence of tumor spread through air spaces (STAS). Thus, preoperative prediction of STAS is important for surgical planning. This study aimed to develop a STAS deep-learning (STAS-DL) prediction model in lung adenocarcinoma with tumor smaller than 3 cm and a consolidation-to-tumor (C/T) ratio less than 0.5., Methods: The study retrospectively enrolled of 581 patients from two institutions between 2015 and 2019. The STAS-DL model was developed to extract the feature of solid components through solid components gated (SCG) for predicting STAS. The STAS-DL model was assessed with external validation in the testing sets and compared with the deep-learning model without SCG (STAS-DL woSCG ), the radiomics-based model, the C/T ratio, and five thoracic surgeons. The performance of the models was evaluated using area under the curve (AUC), accuracy and standardized net benefit of the decision curve analysis., Results: The study evaluated 458 patients (institute 1) in the training set and 123 patients (institute 2) in the testing set. The proposed STAS-DL yielded the best performance compared with the other methods in the testing set, with an AUC of 0.82 and an accuracy of 74%, outperformed the STAS-DL woSCG with an accuracy of 70%, and was superior to the physicians with an AUC of 0.68. Moreover, STAS-DL achieved the highest standardized net benefit compared with the other methods., Conclusion: The proposed STAS-DL model has great potential for the preoperative prediction of STAS and may support decision-making for surgical planning in early-stage, ground glass-predominant lung adenocarcinoma., (© 2023. Society of Surgical Oncology.)

Background: No published studies to date have evaluated the detailed pathologic and genetic features of lung adenocarcinoma after epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) therapy and salvage surgery. We aimed to evaluate the pathologic and genetic changes of tumors in patients with advanced lung adenocarcinoma treated with EGFR TKI therapy and salvage surgery., Methods: This study retrospectively collected data from 29 advanced lung adenocarcinoma patients who underwent EGFR TKI therapy, followed by salvage operation, between January 2010 and December 2018. All patients had partial response or stable disease without evidence of progressive disease. Next-generation sequencing was used to determine whether acquired resistant mutations in morphologically treatment-sensitive and morphologically treatment-resistant regions of tumor existed., Results: There were 3, 22, and 4 patients with clinical stage IIIB, IVA, and IVB, respectively. After a mean TKI treatment duration of 134 days, 27 patients had partial response, 2 had stable disease, and 27.6% of patients were downstaged before salvage surgery. All patients had residual viable tumor cells in their tumor bed; 5 patients (17.2%) had a major pathologic response. Acquired T790M mutations (n = 4), histologic transformations (n = 2), and acquired T790M mutation with histologic transformation (n = 1) were identified in the morphologically treatment-resistant regions of tumors. The 3-year overall survival was 75.9%., Conclusions: The presence of morphologically treatment-resistant tumor regions with acquired T790M mutations and histologic transformations demonstrate the existence of resistant subclones in TKI-treated tumors before disease progression. Salvage surgery performed in selected patients before disease progression may improve survival by removing TKI-resistant subclones., (Copyright © 2023 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)

Background: High-grade adenocarcinoma subtypes (micropapillary and solid) treated with sublobar resection have an unfavorable prognosis compared with those treated with lobectomy. We investigated the potential of incorporating solid attenuation component masks with deep learning in the prediction of high-grade components to optimize surgical strategy preoperatively., Methods: A total of 502 patients with pathologically confirmed high-grade adenocarcinomas were retrospectively enrolled between 2016 and 2020. The SACs attention DL model was developed to apply solid-attenuation-component-like subregion masks (tumor area ≥ - 190 HU) to guide the DL model for predicting high-grade subtypes. The SACA-DL was assessed using 5-fold cross-validation and external validation in the training and testing sets, respectively. The performance, which was evaluated using the area under the curve (AUC), was compared between SACA-DL and the DL model without SACs attention (DL woSACs ), the prior radiomics model, or the model based on the consolidation/tumor (C/T) diameter ratio., Results: We classified 313 and 189 patients into training and testing cohorts, respectively. The SACA-DL achieved an AUC of 0.91 for the cross-validation, which was significantly superior to those of the DL woSACs (AUC = 0.88; P = 0.02), prior radiomics model (AUC = 0.85; P = 0.004), and C/T ratio (AUC = 0.84; P = 0.002). An AUC of 0.93 was achieved for external validation in the SACA-DL and was significantly better than those of the DL woSACs (AUC = 0.89; P = 0.04), prior radiomics model (AUC = 0.85; P < 0.001), and C/T ratio (AUC = 0.85; P < 0.001)., Conclusions: The combination of solid-attenuation-component-like subregion masks with the DL model is a promising approach for the preoperative prediction of high-grade adenocarcinoma subtypes., (© 2022. Society of Surgical Oncology.)

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 2 institutions (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" pathologic 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 cooccurrence matrix (variance) and histogram (75th 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., (Copyright © 2022 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)

Objectives: We aimed at investigating whether serum exosomal miR-16-5p could be utilized as an immunotherapy biomarker in lung adenocarcinoma (LUAD) patients administered by programmed cell death ligand-1 (PD-L1) inhibitors, and to evaluate its functions in LUAD progression., Methods: Sixty LUAD sufferers and 20 healthy controls (HCs) were covered in this work. We applied both IHC and WB to examine PD-L1 level in clinical tissue samples and utilized WB to quantify PD-L1 expression in LUAD cells and LUAD xenograft tissues, respectively. Transmission electron microscopy (TEM), WB, and nanoparticle tracking analysis (NTA) were executed to confirm the exosomes isolated from serum specimens and cell culture media. To quantify of exosomal miR-16-5p level from serum and culture medium of cultured cell, qRT-PCR experiment was utilized. The connection between tissue PD-L1 level and serum exosomal miR-16-5p expression in PD-L1-positive sufferers administered by PD-L1 inhibitors was verified using Spearman correlation coefficient analysis. In addition, the overall survival (OS) and progression-free survival (PFS) rates among PD-L1 inhibitor managed sufferers were acquired through a follow-up visit. Finally, we used a group of assays, including 5-bromo-2'-dexoyuridine (BrdU) and colony formation test, wound healing experiment, flow cytometry, and nude mice xenograft experiment, to explore the functions of circulating exosomal miR-16-5p on LUAD cell proliferation, apoptosis, and migration, as well as tumor development, respectively., Results: PD-L1 expression was positively related to T stage (tumor size stage), and PD-L1 inhibitor treatment reduced the PD-L1 expression and mitigated T stage in PD-L1-positive LUAD sufferers. For PD-L1-positive LUAD sufferers, elevated PD-L1 expression or reduced serum exosomal miR-16-5p level were linked to longer PFS and OS upon PD-L1 inhibitor treatment. The number of exosomes in patient's serum was more than that in the serum of healthy individuals, and PD-L1 inhibitor treatment decreased the number of serum-derived exosomes in PD-L1-positive LUAD sufferers. Exosome-derived miR-16-5p was downregulated in patient's serum and cell culture medium, and this was negatively linked to tumor stage and PD-L1 expression. Meanwhile, PD-L1 inhibitor treatment could increase the serum exosomal miR-16-5p expression, and the expression change of serum exosomal miR-16-5p was diametrically related to PD-L1 after the treatment. Moreover, the overexpression of PD-L1 accelerated tumor growth and decreased the exosomal miR-16-5p content in cell culture media, while exosomal miR-16-5p overexpression in cell culture media inhibited tumor development by decreasing the PD-L1 expression. Exosomal miR-16-5p overexpression in cell culture media also depressed LUAD cell proliferation and migration, and stimulated cell apoptosis, especially in the cells which cultured in the mediums with PD-L1 inhibitor in vitro., Conclusions: Serum exosomal miR-16-5p may be a latent tumor inhibitor and a new biomarker for PD-L1 inhibitor-dependent immunotherapy in LUAD by regulating the PD-L1 expression., (© 2022 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Objectives: Solitary pulmonary capillary haemangioma (SPCH) is a benign lung tumour that presents as ground-glass nodules on computed tomography (CT) images and mimics lepidic-predominant adenocarcinoma. This study aimed to establish a discriminant model using a radiomic feature analysis to distinguish SPCH from lepidic-predominant adenocarcinoma., Methods: In the adenocarcinoma group, all tumours were of the lepidic-predominant subtype with high purity (>70%). A classification model was proposed based on a two-level decision tree and 26 radiomic features extracted from each segmented lesion. For comparison, a baseline model was built with the same 26 features using a support vector machine as the classifier. Both models were assessed by the leave-one-out cross-validation method., Results: This study included 13 and 49 patients who underwent complete resection for SPCH and adenocarcinoma, respectively. Two sets of features were identified for discrimination between the 2 different histology types. The first set included 2 principal components corresponding to the 2 largest eigenvalues for the root node of the two-level decision tree. The second set comprised 4 selected radiomic features. The area under the receiver operating characteristic curve, accuracy, sensitivity, specificity were 0.954, 91.9%, 92.3% and 91.8% in the proposed classification model, and were 0.805, 85.5%, 61.5% and 91.8% in the baseline model, respectively. The proposed classification model significantly outperformed the baseline model (P < 0.05)., Conclusions: The proposed model could differentiate the 2 different histology types on CT images, and this may help surgeons to preoperatively discriminate SPCH from adenocarcinoma., (© The Author(s) 2021. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery.)

The 2021 WHO classification proposed a pattern-based grading system for early-stage invasive non-mucinous lung adenocarcinoma. Lung adenocarcinomas with high-grade patterns have poorer outcomes than those with lepidic-predominant patterns. This study aimed to establish genetic prognostic signatures by comparing differences in gene expression profiles between low- and high-grade adenocarcinomas. Twenty-six (9 low- and 17 high-grade adenocarcinomas) patients with histologically "near-pure" patterns (predominant pattern comprising >70% of tumor areas) were selected retrospectively. Using RNA sequencing, gene expression profiles between the low- and high-grade groups were analyzed, and genes with significantly different expression levels between these two groups were selected for genetic prognostic signatures. In total, 196 significant candidate genes (164 upregulated and 32 upregulated in the high- and low-grade groups, respectively) were identified. After intersection with The Cancer Genome Atlas-Lung Adenocarcinoma prognostic genes, three genes, exonuclease 1 (EXO1), family with sequence similarity 83, member A (FAM83A), and disks large-associated protein 5 (DLGAP5), were identified as prognostic gene signatures. Two independent cohorts were used for validation, and the areas under the time-dependent receiver operating characteristic were 0.784 and 0.703 in the GSE31210 and GSE30219 cohorts, respectively. Our result showed the feasibility and accuracy of this novel three-gene prognostic signature for predicting the clinical outcomes of lung adenocarcinoma.

Background: The choice between wedge resection and segmentectomy as a sublobar resection method for patients with cT1N0 lung cancer remains debatable. This study aimed to evaluate the clinical outcomes after wedge resection and segmentectomy for patients with cT1N0 lung adenocarcinoma., Methods: The study enrolled 1002 consecutive patients with cT1N0 lung adenocarcinoma who underwent sublobar resection at the authors' institution between 2011 and 2017. A propensity score-matching analysis was used to compared the clinical outcomes between the wedge resection and segmentectomy groups., Results: Wedge resection was performed for 810 patients (80.8%), and segmentectomy was performed for 192 patients (19.2%). Wedge resection resulted in better perioperative outcomes than segmentectomy. The multivariate analysis showed that the significant risk factors for poor disease-free survival (DFS) were elevated preoperative serum carcinoembryonic antigen levels, total tumor diameter greater than 2 cm, and a consolidation-to-tumor (C/T) ratio higher than 50%. After propensity-matching, no differences in overall survival or DFS were noted between the two matched groups. However, subgroup analysis showed that segmentectomy was associated with better DFS than wedge resection (p = 0.039) for the patients with a tumor diameter greater than 2 cm and a C/T ratio higher than 50%., Conclusion: Segmentectomy is the appropriate surgical method for sublobar resection in cT1N0 lung adenocarcinoma patients with a tumor diameter greater than 2 cm and a C/T ratio higher than 50%. Wedge resection may be a safe and feasible sublobar resection method for patients with a tumor diameter of 2 cm or smaller or a C/T ratio of 50% or lower., (© 2021. Society of Surgical Oncology.)

Objectives: Near-pure lung adenocarcinoma (ADC) subtypes demonstrate strong stratification of radiomic values, providing basic information for pathological subtyping. We sought to predict the presence of high-grade (micropapillary and solid) components in lung ADCs using quantitative image analysis with near-pure radiomic values., Methods: Overall, 103 patients with lung ADCs of various histological subtypes were enrolled for 10-repetition, 3-fold cross-validation (cohort 1); 55 were enrolled for testing (cohort 2). Histogram and textural features on computed tomography (CT) images were assessed based on the "near-pure" pathological subtype data. Patch-wise high-grade likelihood prediction was performed for each voxel within the tumour region. The presence of high-grade components was then determined based on a volume percentage threshold of the high-grade likelihood area. To compare with quantitative approaches, consolidation/tumour (C/T) ratio was evaluated on CT images; we applied radiological invasiveness (C/T ratio > 0.5) for the prediction., Results: In cohort 1, patch-wise prediction, combined model (C/T ratio and patch-wise prediction), whole-lesion-based prediction (using only the "near-pure"-based prediction model), and radiological invasiveness achieved a sensitivity and specificity of 88.00 ± 2.33% and 75.75 ± 2.82%, 90.00 ± 0.00%, and 77.12 ± 2.67%, 66.67% and 90.41%, and 90.00% and 45.21%, respectively. The sensitivity and specificity, respectively, for cohort 2 were 100.0% and 95.35% using patch-wise prediction, 100.0% and 95.35% using combined model, 75.00% and 95.35% using whole-lesion-based prediction, and 100.0% and 69.77% using radiological invasiveness., Conclusion: Using near-pure radiomic features and patch-wise image analysis demonstrated high levels of sensitivity and moderate levels of specificity for high-grade ADC subtype-detecting., Key Points: • The radiomic values extracted from lung adenocarcinoma with "near-pure" histological subtypes provide useful information for high-grade (micropapillary and solid) components detection. • Using near-pure radiomic features and patch-wise image analysis, high-grade components of lung adenocarcinoma can be predicted with high sensitivity and moderate specificity. • Using near-pure radiomic features and patch-wise image analysis has potential role in facilitating the prediction of the presence of high-grade components in lung adenocarcinoma prior to surgical resection.

Recent studies revealed the role of dynamin-related protein 1 (DRP1), encoded by the DNM1L gene, in regulating the growth of cancer cells of various origins. However, the regulation, function, and clinical significance of DRP1 remain undetermined in lung adenocarcinoma. Our study shows that the expression and activation of DRP1 are significantly correlated with proliferation and disease extent, as well as an increased risk of postoperative recurrence in stage I to stage IIIA lung adenocarcinoma. Loss of DRP1 in lung adenocarcinoma cell lines leads to an altered mitochondrial morphology, fewer copies of mitochondrial DNA, decreased respiratory complexes, and impaired oxidative phosphorylation. Additionally, the proliferation and invasion are both suppressed in DRP1-depleted lung adenocarcinoma cell lines. Our data further revealed that DRP1 activation through serine 616 phosphorylation is regulated by ERK/AKT and CDK2 in lung adenocarcinoma cell lines. Collectively, we propose the multikinase framework in activating DRP1 in lung adenocarcinoma to promote the malignant properties. Biomarkers related to mitochondrial reprogramming, such as DRP1, can be used to evaluate the risk of postoperative recurrence in early-stage lung adenocarcinoma., (© 2020 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

Background: The optimal surgical method for cT1N0 lung adenocarcinoma remains controversial., Objective: The aim of this study was to evaluate the differences in clinical outcomes of sublobar resection and lobectomy for cT1N0 lung adenocarcinoma patients., Methods: We included 1035 consecutive patients with cT1N0 lung adenocarcinoma who underwent surgery at our institute from January 2011 to December 2016. The surgical approach, either sublobar resection or lobectomy, was determined at the discretion of each surgeon. A propensity-matched analysis incorporating total tumor diameter, solid component diameter, consolidation-to-tumor (C/T) ratio, and performance status was used to compare the clinical outcomes of the sublobar resection and lobectomy groups., Results: Sublobar resection and lobectomy were performed for 604 (58.4%; wedge resection/segmentectomy: 470/134) and 431 (41.6%) patients, respectively. Patients in the sublobar resection group had smaller total tumor diameters, smaller solid component diameters, lower C/T ratios, and better performance status. More lymph nodes were dissected in the lobectomy group. Patients in the sublobar resection group had better perioperative outcomes. A multivariable analysis revealed that the solid component diameter and serum carcinoembryonic antigen level are independent risk factors for tumor recurrence. After propensity matching, 284 paired patients in each group were included. No differences in overall survival (OS; p = 0.424) or disease-free survival (DFS; p = 0.296) were noted between the two matched groups., Conclusions: Sublobar resection is not inferior to lobectomy regarding both DFS and OS for cT1N0 lung adenocarcinoma patients. Sublobar resection may be a feasible surgical method for cT1N0 lung adenocarcinoma.

Objectives: Lung cancers have various acquired resistance mechanisms that lead to treatment failure and disease progression, including secondary epidermal growth factor receptor (EGFR) exon 20 T790 M mutations, EGFR downstream or bypass pathway activation, and histologic transformation from adenocarcinoma to small cell carcinoma, squamous cell carcinoma, or sarcomatoid carcinoma., Materials and Methods: This study compared the pathological and immunohistochemical characteristics before and after sarcomatoid transformation. Six advanced cases of lung adenocarcinoma that developed sarcomatoid transformation after treatment were collected., Results: Five cases had classic EGFR mutations and one had a ROS1 rearrangement. The interval from initial diagnosis to sarcomatoid transformation ranged from 9 to 88 mo (median of 31.5 mo). The median survival after sarcomatoid transformation was 2.5 mo (1-16 mo). Before sarcomatoid transformation, all cases demonstrated typical adenocarcinoma features, including acinar, micropapillary, or solid/cribriform patterns, negative or weak focal vimentin staining, and strong E-cadherin expression. Histologic features of sarcomatoid transformation included giant cell features (6/6), loose cellular cohesion (6/6), strong staining for vimentin (6/6), decreased or lost E-cadherin expression (5/6), and high PD-L1 expression (5/6; one case demonstrated high PD-L1 staining at initial diagnosis). High MET expression and MET copy number gain (two samples with high polysomy and three with true amplification) were observed in five cases with EGFR mutation treated with tyrosine kinase inhibitors (TKI). One case exhibited MET amplification prior to the start of TKI treatment., Conclusion: Sarcomatoid transformation is a type of lung cancer histologic evolution with a poor prognosis and a high proportion of cases with aberrant MET activation and PD-L1 expression., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Introduction: Histological subtypes of lung adenocarcinomas (ADCs) classified by the International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society (IASLC/ATS/ERS) system have been investigated using radiomic approaches. However, the results have had limitations since <80% of invasive lung ADCs were heterogeneous, with two or more subtypes. To reduce the influence of heterogeneity during radiomic analysis, computed tomography (CT) images of lung ADCs with near-pure ADC subtypes were analyzed to extract representative radiomic features of different subtypes., Methods: We enrolled 95 patients who underwent complete resection for lung ADC and a pathological diagnosis of a "near-pure" (≥70%) IASLC/ATS/ERS histological subtype. Conventional histogram/morphological features and complex radiomic features (grey-level-based statistical features and component variance-based features) of thin-cut CT data of tumor regions were analyzed. A prediction model based on leave-one-out cross-validation (LOOCV) and logistic regression (LR) was used to classify all five subtypes and three pathologic grades (lepidic, acinar/papillary, micropapillary/solid) of ADCs. The validation was performed using 36 near-pure ADCs in a later cohort., Results: A total of 31 lepidic, 14 papillary, 32 acinar, 10 micropapillary, and 8 solid ADCs were analyzed. With 21 conventional and complex radiomic features, for 5 subtypes and 3 pathological grades, the prediction models achieved accuracy rates of 84.2% (80/95) and 91.6% (87/95), respectively, while accuracy was 71.6% and 85.3%, respectively, if only conventional features were used. The accuracy rate for the validation set (n = 36) was 83.3% (30/36) and 94.4% (34/36) in 5 subtypes and 3 pathological grades, respectively, using conventional and complex features, while it was 66.7% and 77.8% only using conventional features, respectively., Conclusion: Lung ADC with high purity pathological subtypes demonstrates strong stratification of radiomic values, which provide basic information for accurate pathological subtyping and image parcellation of tumor sub-regions., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Objective: To evaluate whether main tumor resection improves survival compared with pleural biopsy alone in patients with lung adenocarcinoma with intraoperatively diagnosed pleural seeding., Methods: Forty-three patients with lung adenocarcinoma with pleural seeding diagnosed unexpectedly during surgery performed between January 2006 and December 2014 were included in this retrospective study using a prospectively collected lung cancer database. Each surgeon decided whether to perform main tumor resection or pleural biopsy alone., Results: Main tumor and visible pleural nodule resection was performed in 30 patients (tumor resection group). The remaining 13 patients underwent pleural nodule biopsy alone (open-close group). The clinical T stage was higher in the open-close group than in the tumor resection group (P = .02). The tumor resection group had longer operative times compared with the open-close group (mean, 141.8 vs 80.3 minutes). There were no other statistically significant differences in perioperative parameters. The surgical method was the sole statistically significant prognostic factor. Patients in the tumor resection group had better progression-free survival (3-year survival: 44.5% vs 0%; P = .009) and overall survival (3-year survival: 82.9% vs 38.5%; P = .013) than did the open-close group. There was no significant survival difference between sublobar resection and lobectomy for the main tumor resection., Conclusions: Our study demonstrated improved progression-free and overall survival after main tumor and visible pleural nodule resection in patients with lung adenocarcinoma with intraoperatively diagnosed pleural seeding. Further randomized trials are needed to define the role of main tumor resection in these patients., (Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.)