Accuracy of the IASLC/ATS/ERS histological subtyping of stage I lung adenocarcinoma on intraoperative frozen sections

Deep-learning-based 3D super-resolution CT radiomics model: Predict the possibility of the micropapillary/solid component of lung adenocarcinoma

Objective

Invasive lung adenocarcinoma（ILA） with micropapillary (MPP)/solid (SOL) components has a poor prognosis. Preoperative identification is essential for decision-making for subsequent treatment. This study aims to construct and evaluate a super-resolution（SR） enhanced radiomics model designed to predict the presence of MPP/SOL components preoperatively to provide more accurate and individualized treatment planning.

Methods

Between March 2018 and November 2023, patients who underwent curative intent ILA resection were included in the study. We implemented a deep transfer learning network on CT images to improve their resolution, resulting in the acquisition of preoperative super-resolution CT (SR-CT) images. Models were developed using radiomic features extracted from CT and SR-CT images. These models employed a range of classifiers, including Logistic Regression (LR), Support Vector Machines (SVM), k-Nearest Neighbors (KNN), Random Forest, Extra Trees, Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Multilayer Perceptron (MLP). The diagnostic performance of the models was assessed by measuring the area under the curve (AUC).

Result

A total of 245 patients were recruited, of which 109 (44.5 %) were diagnosed with ILA with MPP/SOL components. In the analysis of CT images, the SVM model exhibited outstanding effectiveness, recording AUC scores of 0.864 in the training group and 0.761 in the testing group. When this SVM approach was used to develop a radiomics model with SR-CT images, it recorded AUCs of 0.904 in the training and 0.819 in the test cohorts. The calibration curves indicated a high goodness of fit, while decision curve analysis (DCA) highlighted the model's clinical utility.

Conclusion

The study successfully constructed and evaluated a deep learning（DL）-enhanced SR-CT radiomics model. This model outperformed conventional CT radiomics models in predicting MPP/SOL patterns in ILA. Continued research and broader validation are necessary to fully harness and refine the clinical potential of radiomics when combined with SR reconstruction technology.

Evaluation of the preoperative neutrophil-to-lymphocyte ratio as a predictor of the micropapillary component of stage IA lung adenocarcinoma

OBJECTIVE

To assess the ability of markers of inflammation to identify the solid or micropapillary components of stage IA lung adenocarcinoma and their effects on prognosis.

METHODS

We performed a retrospective study of clinicopathologic data from 654 patients with stage IA lung adenocarcinoma collected between 2013 and 2019. Logistic regression analysis was used to identify independent predictors of these components, and we also evaluated the relationship between markers of inflammation and recurrence.

RESULTS

Micropapillary-positive participants had high preoperative neutrophil-to-lymphocyte ratios. There were no significant differences in the levels of markers of systemic inflammation between the participants with or without a solid component. Multivariate analysis showed that preoperative neutrophil-to-lymphocyte ratio (odds ratio [OR] = 2.094; 95% confidence interval [CI], 1.668-2.628), tumor size (OR = 1.386; 95% CI, 1.044-1.842), and carcinoembryonic antigen concentration (OR = 1.067; 95% CI, 1.017-1.119) were independent predictors of a micropapillary component. There were no significant correlations between markers of systemic inflammation and the recurrence of stage IA lung adenocarcinoma.

CONCLUSIONS

Preoperative neutrophil-to-lymphocyte ratio independently predicts a micropapillary component of stage IA lung adenocarcinoma. Therefore, the potential use of preoperative neutrophil-to-lymphocyte ratio in the optimization of surgical strategies for the treatment of stage IA lung adenocarcinoma should be further studied.

Synchrotron Radiation Refraction-Contrast Computed Tomography Based on X-ray Dark-Field Imaging Optics of Pulmonary Malignancy: Comparison with Pathologic Examination

Refraction-contrast computed tomography based on X-ray dark-field imaging (XDFI) using synchrotron radiation (SR) has shown superior resolution compared to conventional absorption-based methods and is often comparable to pathologic examination under light microscopy. This study aimed to investigate the potential of the XDFI technique for clinical application in lung cancer diagnosis. Two types of lung specimens, primary and secondary malignancies, were investigated using an XDFI optic system at beamline BL14B of the High-Energy Accelerator Research Organization Photon Factory, Tsukuba, Japan. Three-dimensional reconstruction and segmentation were performed on each specimen. Refraction-contrast computed tomographic images were compared with those obtained from pathological examinations. Pulmonary microstructures including arterioles, venules, bronchioles, alveolar sacs, and interalveolar septa were identified in SR images. Malignant lesions could be distinguished from the borders of normal structures. The lepidic pattern was defined as the invasive component of the same primary lung adenocarcinoma. The SR images of secondary lung adenocarcinomas of colorectal origin were distinct from those of primary lung adenocarcinomas. Refraction-contrast images based on XDFI optics of lung tissues correlated well with those of pathological examinations under light microscopy. This imaging method may have the potential for use in lung cancer diagnosis without tissue damage. Considerable equipment modifications are crucial before implementing them from the lab to the hospital in the near future.

Predictive value of systemic immune-inflammation index in the high-grade subtypes components of small-sized lung adenocarcinoma

BACKGROUND

Identification of micropapillary and solid subtypes components in small-sized (≤ 2 cm) lung adenocarcinoma plays a crucial role in determining optimal surgical procedures. This study aims to propose a straightforward prediction method utilizing preoperative available indicators.

METHODS

From January 2019 to July 2022, 341 consecutive patients with small-sized lung adenocarcinoma who underwent curative resection in thoracic surgery department of Xuanwu Hospital, Capital Medical University were retrospectively analyzed. The patients were divided into two groups based on whether solid or micropapillary components ≥ 5% or not (S/MP5+ and S/MP5-). Univariate analysis and multivariate logistic regression analysis were utilized to identify independent predictors of S/MP5+. Then a nomogram was constructed to intuitively show the results. Finally, the calibration curve with a 1000 bootstrap resampling and the receiver operating characteristic (ROC) curve were depicted to evaluate its performance.

RESULTS

According to postoperative pathological results, 79 (23.2%) patients were confirmed as S/MP5+ while 262 (76.8%) patients were S/MP5-. Based on multivariate analysis, maximum diameter (p = 0.010), consolidation tumor ratio (CTR) (p < 0.001) and systemic immune-inflammation index (SII) (p < 0.001) were identified as three independent risk factors and incorporated into the nomogram. The calibration curve showed good concordance between the predicted and actual probability of S/MP5+. Besides, the model showed certain discrimination, with an area under ROC curve of 0.893.

CONCLUSIONS

The model constructed based on SII is a practical tool to predict high-grade subtypes components of small-sized lung adenocarcinoma preoperatively and contribute to determine the optimal surgical approach.

A combination of radiomic features, clinic characteristics, and serum tumor biomarkers to predict the possibility of the micropapillary/solid component of lung adenocarcinoma

BACKGROUND

Invasive lung adenocarcinoma with MPP/SOL components has a poor prognosis and often shows a tendency to recurrence and metastasis. This poor prognosis may require adjustment of treatment strategies. Preoperative identification is essential for decision-making for subsequent treatment.

OBJECTIVE

This study aimed to preoperatively predict the probability of MPP/SOL components in lung adenocarcinomas by a comprehensive model that includes radiomics features, clinical characteristics, and serum tumor biomarkers.

DESIGN

A retrospective case control, diagnostic accuracy study.

METHODS

This study retrospectively recruited 273 patients (males: females, 130: 143; mean age ± standard deviation, 63.29 ± 10.03 years; range 21-83 years) who underwent resection of invasive lung adenocarcinoma. Sixty-one patients (22.3%) were diagnosed with lung adenocarcinoma with MPP/SOL components. Radiomic features were extracted from CT before surgery. Clinical, radiomic, and combined models were developed using the logistic regression algorithm. The clinical and radiomic signatures were integrated into a nomogram. The diagnostic performance of the models was evaluated using the area under the curve (AUC). Studies were scored according to the Radiomics Quality Score and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines.

RESULTS

The radiomics model achieved the best AUC values of 0.858 and 0.822 in the training and test cohort, respectively. Tumor size (T_size), solid tumor size (ST_size), consolidation-to-tumor ratio (CTR), years of smoking, CYFRA 21-1, and squamous cell carcinoma antigen were used to construct the clinical model. The clinical model achieved AUC values of 0.741 and 0.705 in the training and test cohort, respectively. The nomogram showed higher AUCs of 0.894 and 0.843 in the training and test cohort, respectively.

CONCLUSION

This study has developed and validated a combined nomogram, a visual tool that integrates CT radiomics features with clinical indicators and serum tumor biomarkers. This innovative model facilitates the differentiation of micropapillary or solid components within lung adenocarcinoma and achieves a higher AUC, indicating superior predictive accuracy.

Optimal resection strategies for small-size lung cancer: Is a wedge enough? Is lobectomy too much?

Recently published large multicenter prospective clinical trials have demonstrated that sublobar resection is noninferior to lobectomy, the traditional treatment of choice, for peripherally located early-stage lung cancer. Most clinical trials and several retrospective studies published to date have used the consolidation-to-tumor ratio to define the indication for sublobar resection, as it is well known that the size of the solid portion seen on high-resolution computed tomography is highly correlated with pathologic invasiveness. However, it is difficult to accurately predict pathologic features that may increase the risk of locoregional recurrence, such as specific adenocarcinoma subtypes or spread through air spaces, based on imaging characteristics alone, and the location of the nodule also should be considered one of the important factors in obtaining an adequate parenchymal resection margin. In this article, we summarize the results of the most recently published clinical trials related to sublobar resection and discuss various factors that should be considered for optimal candidate selection for sublobar resection.

Computed tomography imaging and clinical characteristics of pulmonary ground-glass nodules ≤2 cm with micropapillary pattern

BACKGROUND

The aim of this study was to investigate the imaging features, lymph node metastasis, and genetic mutations in micropapillary lung adenocarcinoma (imaging with mixed ground-glass nodules) ≤2 cm, to provide a more precise and refined basis for the selection of lung segment resection.

METHODS

A retrospective analysis of 162 patients with surgically resected pathologically confirmed cancers ≤2.0 cm in diameter (50 cases of micropapillary mixed ground-glass nodules [mGGNs], 50 cases of nonmicropapillary mGGNs, and 62 cases of micropapillary SNs [solid nodules]) was performed. mGGNs were classified into five categories according to imaging features. The distribution of these five morphologies in micropapillary with mGGN and nonmicropapillary with mGGN was analyzed. The postoperative pathology and prognosis of lymph node metastasis were also compared between micropapillary mGGNs and micropapillary with SNs. After searching the TCGA database, we demonstrated heterogeneity, high malignancy and high risk of microcapillary lung cancer cancers.

RESULTS

Different pathological subtypes of mGGN differed in morphological features (p < 0.05). The rate of lymph node metastasis was significantly higher in micropapillary mGGNs than in nonmicropapillary mGGNs. In the TCGA database samples, lactate transmembrane protein activity, collagen transcription score, and fibroblast EMT score were remarkably higher in micropapillary adenocarcinoma. Other pathological subtypes had a better survival prognosis and longer disease-free survival compared with micropapillary adenocarcinoma.

CONCLUSION

mGGNs ≤2 cm with a micropapillary pattern have a higher risk of lymph node metastasis compared with SNs, and computed tomography (CT) imaging features can assist in their diagnosis.

Establishment and visualization of a model based on high-resolution CT qualitative and quantitative features for prediction of micropapillary or solid components in invasive lung adenocarcinoma

OBJECTIVE

To predict the existence of micropapillary or solid components in invasive adenocarcinoma, a model was constructed using qualitative and quantitative features in high-resolution computed tomography (HRCT).

METHODS

Through pathological examinations, 176 lesions were divided into two groups depending on the presence or absence of micropapillary and/or solid components (MP/S): MP/S- group (n = 128) and MP/S + group (n = 48). Multivariate logistic regression analyses were used to identify independent predictors of the MP/S. Artificial intelligence (AI)-assisted diagnostic software was used to automatically identify the lesions and extract corresponding quantitative parameters on CT images. The qualitative, quantitative, and combined models were constructed according to the results of multivariate logistic regression analysis. The receiver operating characteristic (ROC) analysis was conducted to evaluate the discrimination capacity of the models with the area under the curve (AUC), sensitivity, and specificity calculated. The calibration and clinical utility of the three models were determined using the calibration curve and decision curve analysis (DCA), respectively. The combined model was visualized in a nomogram.

RESULTS

The multivariate logistic regression analysis using both qualitative and quantitative features indicated that tumor shape (P =  0.029 OR =  4.89; 95% CI 1.175-20.379), pleural indentation (P = 0.039 OR =  1.91; 95% CI 0.791-4.631), and consolidation tumor ratios (CTR) (P < 0.001; OR = 1.05; 95% CI 1.036-1.070) were independent predictors for MP/S + . The areas under the curve (AUC) of the qualitative, quantitative, and combined models in predicting MP/S + were 0.844 (95% CI 0.778-0.909), 0.863 (95% CI 0.803-0.923), and 0.880 (95% CI 0.824-0.937). The combined model of AUC was the most superior and statistically better than qualitative model.

CONCLUSION

The combined model could assist doctors to evaluate patient's prognoses and devise personalized diagnostic and treatment protocols for patients.

Development of the semi-dry dot-blot method for intraoperative detecting micropapillary component in lung adenocarcinoma based on proteomics analysis

BACKGROUND

Micropapillary (MIP) component was a major concern in determining surgical strategy in lung adenocarcinoma (LUAD). We sought to develop a novel method for detecting MIP component during surgery.

METHODS

Differentially expressed proteins between MIP-positive and MIP-negative LUAD were identified through proteomics analysis. The semi-dry dot-blot (SDB) method which visualises the targeted protein was developed to detect MIP component.

RESULTS

Cellular retinoic acid-binding protein 2 (CRABP2) was significantly upregulated in MIP-positive LUAD (P < 0.001), and the high CRABP2 expression zone showed spatial consistency with MIP component. CRABP2 expression was also associated with decreased recurrence-free survival (P < 0.001). In the prospective cohort, the accuracy and sensitivity of detecting MIP component using SDB method by visualising CRABP2 were 82.2% and 72.7%, which were comparable to these of pathologist. Pathologist with the aid of SDB method would improve greatly in diagnostic accuracy (86.4%) and sensitivity (78.2%). In patients with minor MIP component (≤5%), the sensitivity of SDB method (63.6%) was significantly higher than pathologist (45.4%).

CONCLUSIONS

Intraoperative examination of CRABP2 using SDB method to detect MIP component reached comparable performance to pathologist, and SDB method had notable superiority than pathologist in detecting minor MIP component.

Frozen sections accurately predict the IASLC proposed grading system and prognosis in patients with invasive lung adenocarcinomas

INTRODUCTION

The International Association for the Study of Lung Cancer (IASLC) newly proposed grading system for lung adenocarcinomas (ADC) has been shown to be of prognostic significance. Hence, intraoperative consultation for the grading system was important regarding the surgical decision-making. Here, we evaluated the accuracy and interobserver agreement for IASLC grading system on frozen section (FS), and further investigated the prognostic performance.

METHODS

FS and final pathology (FP) slides were reviewed by three pathologists for tumor grading in 373 stage I lung ADC following surgical resection from January to June 2013 (retrospective cohort). A prospective multicenter cohort (January to June 2021, n = 212) were included to confirm the results.

RESULTS

The overall concordance rates between FS and FP were 79.1% (κ = 0.650) and 89.6% (κ = 0.729) with substantial agreement in retrospective and prospective cohorts, respectively. Presence of complex gland was the only independent predictor of discrepancy between FS and FP (presence versus. absence: odds ratio, 2.193; P = 0.015). The interobserver agreement for IASLC grading system on FS among three pathologists were satisfactory (κ = 0.672 for retrospective cohort; κ = 0.752 for prospective cohort). Moreover, the IASLC grading system by FS diagnosis could well predict recurrence-free survival and overall survival for patients with stage I invasive lung ADC.

CONCLUSIONS

Our results suggest that FS had high diagnostic accuracy and satisfactory interobserver agreement for IASLC grading system. Future prospective studies are merited to validate the feasibility of using FS to match patients into appropriate surgical type.

A novel nomogram to predict lymph node metastasis in cT1 non-small-cell lung cancer based on PET/CT and peripheral blood cell parameters

BACKGROUND

Accurately evaluating the lymph node status preoperatively is critical in determining the appropriate treatment plan for non-small-cell lung cancer (NSCLC) patients. This study aimed to construct a novel nomogram to predict the probability of lymph node metastasis in clinical T1 stage patients based on non-invasive and easily accessible indicators.

METHODS

From October 2019 to June 2022, the data of 84 consecutive cT1 NSCLC patients who had undergone PET/CT examination within 30 days before surgery were retrospectively collected. Univariate and multivariate logistic regression analyses were performed to identify the risk factors of lymph node metastasis. A nomogram based on these predictors was constructed. The area under the receiver operating characteristic (ROC) curve and the calibration curve was used for assessment. Besides, the model was confirmed by bootstrap resampling.

RESULTS

Four predictors (tumor SUVmax value, lymph node SUVmax value, consolidation tumor ratio and platelet to lymphocyte ratio) were identified and entered into the nomogram. The model indicated certain discrimination, with an area under ROC curve of 0.921(95%CI 0.866-0.977). The calibration curve showed good concordance between the predicted and actual possibility of lymph node metastasis.

CONCLUSIONS

This nomogram was practical and effective in predicting lymph node metastasis for patients with cT1 NSCLC. It could provide treatment recommendations to clinicians.

Preoperative levels of folate receptor-positive circulating tumor cells in different subtypes of early-stage lung adenocarcinoma: Predictive value for determining extent of surgical resection

Background

The objective was to measure the correlations of preoperative levels of folate receptor-positive circulating tumor cells (FR⁺CTCs) with clinical characteristics and histologic subtype in early-stage lung adenocarcinoma, and to determine the predictive value of FR⁺CTC level in preoperative determination of the extent of surgical resection.

Patients and methods

In this retrospective, single-institution, observational study, preoperative FR⁺CTC levels were measured via ligand-targeted enzyme-linked polymerization in patients with early-stage lung adenocarcinoma. Receiver operating characteristic (ROC) analysis was used to identify the optimal cutoff value of FR⁺CTC level for prediction of various clinical characteristics and histologic subtypes.

Results

No significant difference in FR⁺CTC level was observed among patients with adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) (P = 0.813). Within the non-mucinous adenocarcinoma group, no difference was observed among patients with tumors whose predominant growth patterns were lepidic, acinar, papillary, micropapillary, solid, and complex gland (P = 0.053). However, significant differences in FR⁺CTC level were observed between patients with and without the micropapillary subtype [11.21 (8.22-13.61) vs. 9.85 (7.43-12.63), P = 0.017], between those with and without the solid subtype [12.16 (8.27-14.90) vs. 9.87 (7.50-12.49), P = 0.022], and between those with any of the advanced subtypes (micropapillary, solid, or complex glands) vs. none of these [10.48 (7.83-13.67) vs. 9.76 (7.42-12.42), P = 0.032]. FR⁺CTC level was also correlated with degree of differentiation of lung adenocarcinoma (P = 0.033), presence of visceral pleural invasion (VPI) of lung carcinoma (P = 0.003), and lymph node metastasis of lung carcinoma (P = 0.035).

Conclusion

FR⁺CTC level is of potential predictive value in determining the presence of aggressive histologic patterns (micropapillary, solid, and advanced subtypes), degree of differentiation, and occurrence of VPI and lymph node metastasis in IAC. Measurement of FR⁺CTC level combined with intraoperative frozen sections may represent a more effective method of guiding resection strategy in cases of cT1N0M0 IAC with high-risk factors.

A Combination of Radiomic Features, Imaging Characteristics, and Serum Tumor Biomarkers to Predict the Possibility of the High-Grade Subtypes of Lung Adenocarcinoma

RATIONALE AND OBJECTIVES

Lung adenocarcinomas (LADC) containing high-grade subtypes have a poorer prognosis. And some studies have shown that high-grade subtypes have been identified as an independent predictor of local recurrence in patients treated with limited resection. The aim of this study was to construct a combined model based on radiomic features, imaging characteristics and serum tumor biomarkers to predict the possibility of preoperative high-grade subtypes.

MATERIALS AND METHODS

156 patients with LADC were retrospectively recruited in this study. These patients were randomly divided into training and validation cohorts. Radiomics features and imaging characteristics were extracted from plain CT images. A nomogram was developed in a training cohort by univariate and multivariate logistic analysis, and its performance was evaluated by receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) in the training and validation cohorts.

RESULTS

A total of 1316 radiomic features were extracted from the lesions in plain chest CT images. After applying the mRMR algorithm and the LASSO regression, 4 features were retained. Based on these radiomic features, Radiomic score (Radscore) was calculated for each patient. Spiculation, air bronchogram sign, CYFRA 21-1 and Radscore had been used in the construction of the combined model. The AUC of the combined model was respectively 0.88 (95% CI, 0.82-0.95) and 0.94 (95% CI, 0.86-1.00) in the training and validation cohorts.

CONCLUSION

The combined model based on CT images and serum tumor biomarkers, can predict the high-grade subtypes of LADC in a non-invasive manner, which may influence individual treatment planning, such as the choice of surgical approach and postoperative adjuvant therapy.

A deep-learning model for transforming the style of tissue images from cryosectioned to formalin-fixed and paraffin-embedded

Histological artefacts in cryosectioned tissue can hinder rapid diagnostic assessments during surgery. Formalin-fixed and paraffin-embedded (FFPE) tissue provides higher quality slides, but the process for obtaining them is laborious (typically lasting 12-48 h) and hence unsuitable for intra-operative use. Here we report the development and performance of a deep-learning model that improves the quality of cryosectioned whole-slide images by transforming them into the style of whole-slide FFPE tissue within minutes. The model consists of a generative adversarial network incorporating an attention mechanism that rectifies cryosection artefacts and a self-regularization constraint between the cryosectioned and FFPE images for the preservation of clinically relevant features. Transformed FFPE-style images of gliomas and of non-small-cell lung cancers from a dataset independent from that used to train the model improved the rates of accurate tumour subtyping by pathologists.

Protocol of an iterative qualitative study to develop a molecular testing decision aid for shared decision-making in patients with lung cancer after surgery

INTRODUCTION

Although molecular testing is crucial for many patients with lung cancer, the decision to carry out molecular testing is not easy to make in actual clinical scenarios. Using a specific decision aid (DA) to conduct shared decision-making (SDM) may help ameliorate this problem. However, no DA currently exists for lung cancer molecular testing (DA_LCMT). We aim to develop an evidence-based, iteratively refined DA, which may facilitate SDM and improve the quality of SDM.

METHODS AND ANALYSIS

After considering the Ottawa Decision Support Framework, International Patient Decision Aid Standards and Food and Drug Administration guidance about methods to identify what is important to patients, semistructured interviews with qualitative research methods will be used to generate the decision-making needs of patients with lung cancer diagnosed with lung adenocarcinoma by intraoperative frozen pathological sections. Input will be provided by patients and other stakeholders, including thoracic surgeons, nurses, hospital administrators, molecular testing company staff and insurance company staff. Then, a modified Delphi method will be used to develop the DA_LCMT V.1.0 (DA_LCMT 1.0). Structured interviews with qualitative research methods will be used in the cognitive debriefing (alpha tests) and field testing (beta tests) to revise and improve the DA_LCMT from version 1.0 to the final version, version 3.0. Descriptive statistics will be used to summarise the baseline characteristics of the patients and other stakeholders. Qualitative data will be analysed using the three steps of grounded theory: generate a codebook, update the codebook and create a comprehensive list of related items.

ETHICS AND DISSEMINATION

Ethics Committee for Medical Research and New Medical Technology of Sichuan Cancer Hospital approved this study. This protocol is based on the latest version 1.0, dated 31 October 2021. The study was also approved by the Ethics Committees of The Third People's Hospital of Chengdu, Zigong First People's Hospital and Jiangyou People's Hospital. The results of this study will be presented at medical conferences and published in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT05191485.

Radiomics for identifying lung adenocarcinomas with predominant lepidic growth manifesting as large pure ground-glass nodules on CT images

Purpose

To explore the value of radiomics in the identification of lung adenocarcinomas with predominant lepidic growth in pure ground-glass nodules (pGGNs) larger than 10 mm.

Methods

We retrospectively analyzed CT images of 204 patients with large pGGNs (≥ 10 mm) pathologically diagnosed as minimally invasive adenocarcinomas (MIAs), lepidic predominant adenocarcinomas (LPAs), and non-lepidic predominant adenocarcinomas (NLPAs). All pGGNs in the two groups (MIA/LPA and NLPA) were randomly divided into training and test cohorts. Forty-seven patients from another center formed the external validation cohort. Baseline features, including clinical data and CT morphological and quantitative parameters, were collected to establish a baseline model. The radiomics model was built with the optimal radiomics features. The combined model was developed using the rad_score and independent baseline predictors. The performance of the models was evaluated using the area under the receiver operating characteristic curve (AUC) and compared using the DeLong test. The differential diagnosis performance of the models was compared with three radiologists (with 20+, 10+, and 3 years of experience) in the test cohort.

Results

The radiomics (training AUC: 0.833; test AUC: 0.804; and external validation AUC: 0.792) and combined (AUC: 0.849, 0.820, and 0.775, respectively) models performed better for discriminating than the baseline model (AUC: 0.756, 0.762, and 0.725, respectively) developed by tumor location and mean CT value of the whole nodule. The DeLong test showed that the AUCs of the combined and radiomics models were significantly increased in the training cohort. The highest AUC value of the radiologists was 0.600.

Conclusion

The application of CT radiomics improved the identification performance of lung adenocarcinomas with predominant lepidic growth appearing as pGGNs larger than 10 mm.

Identification of Filigree Pattern Increases Diagnostic Accuracy of Micropapillary Pattern on Frozen Section for Lung Adenocarcinoma

INTRODUCTION

The presence of micropapillary (MIP) in early-stage lung adenocarcinoma was associated with a poorer prognosis, especially in patients undergoing sublobectomy. However, data on the sensitivity of frozen section (FS) evaluation of MIP was still limited. We included the concept of filigree pattern on FS to assess its effect on the diagnostic sensitivity and specificity of MIP, and verify its prognostic value in stage T1 lung adenocarcinoma.

METHODS

A panel of five pathologists evaluated 125 patients with T1 lung adenocarcinoma from January to February 2014 as a study cohort, and 151 patients from January to February 2020 as a validation cohort. The diagnostic accuracy of filigree and classical micropapillary (cMIP) pattern on FS was investigated.

RESULTS

Diagnostic sensitivity of MIP pattern on FS increased from 43.2% to 65.3% and 56.8% to 81.1% in the study cohort and validation cohort, and both with good specificity. Filigree not only increased the sensitivity of identifying MIP when absence of cMIP, but also increased the sensitivity when presence of minor amount of cMIP. The almost perfect agreement among five pathologists was reached on cMIP and substantial agreement was reached on the filigree in the two cohorts. Moreover, the cMIP and filigree were both correlated with poorer recurrence-free survival (p_cMIP = 0.003; p_filigree = 0.032) and overall survival (p_cMIP = 0.004; p_filigree = 0.005).

CONCLUSION

Identification of filigree may improve the diagnostic sensitivity of MIP pattern on FS. FS was feasible for the detection of filigree and cMIP patterns in stage T1 lung adenocarcinomas.

Quantifying invasiveness of clinical stage IA lung adenocarcinoma with computed tomography texture features

OBJECTIVES

The study objectives were to establish and validate a nomogram for pathological invasiveness prediction in clinical stage IA lung adenocarcinoma and to help identify those potentially unsuitable for sublobar resection-based computed tomography texture features.

METHOD

Patients with clinical stage IA lung adenocarcinoma who underwent surgery at Guangdong Provincial People's Hospital between January 2015 and October 2018 were retrospectively reviewed. All surgically resected nodules were pathologically classified into less-invasive and invasive cohorts. Each nodule was manually segmented, and its computerized texture features were extracted. Clinicopathological and computed tomographic texture features were compared between 2 cohorts. A nomogram for distinguishing the pathological invasiveness was established and validated.

RESULTS

Among 428 enrolled patients, 249 were diagnosed with invasive pathological subtypes. Smoking status (odds ratio, 2.906; 95% confidence interval, 1.285-6.579; P = .011), mean computed tomography attenuation value (odds ratio, 1.005, 95% confidence interval, 1.002-1.007; P < .001), and entropy (odds ratio, 8.536, 95% confidence interval, 3.478-20.951; P < .001) were identified as independent predictors for pathological invasiveness by multivariate logistics regression analysis. The nomogram showed good calibration (P = .182) with an area under the curve of 0.849 when validated with testing set data. Decision curve analysis indicated the potentially clinical usefulness of the model with respect to treat-all or treat-none scenario. Compared with intraoperative frozen-section, the nomogram performed better in pathological invasiveness diagnosis (area under the curve, 0.815 vs 0.670; P = .00095).

CONCLUSIONS

We established and validated a nomogram to compute the probability of invasiveness of clinical stage IA lung adenocarcinoma with great calibration, which may contribute to decisions related to resection extent.

Cryobiopsy as a reliable technique for the preoperative identification of micropapillary/solid components in early-stage lung adenocarcinoma

OBJECTIVES

Micropapillary (MIP) and solid (SOL) subtypes of early-stage lung adenocarcinomas are associated with lymph node metastasis and local recurrence after limited resection. Preoperative identification of these components may influence the decisions of treatment strategy, additional lymph node evaluation, indication for limited resection, and extent of lymph node dissection. However, conventional biopsy specimens are insufficient for identifying these subtypes, especially MIP components. Cryobiopsy can collect larger tissue samples with fewer crush artifacts than conventional forceps biopsy, which would be helpful for detecting MIP/SOL components. Thus, this study aimed to analyze the feasibility of using cryobiopsy for MIP/SOL subtype detection.

MATERIAL AND METHODS

Consecutive patients who underwent surgery for clinical IA lung cancer following a preoperative diagnosis of adenocarcinoma by cryobiopsy at our institution between October 2017 and July 2019 were retrospectively examined. The concordance rate of MIP/SOL subtypes between the specimens obtained by cryobiopsy and surgery was investigated.

RESULTS

In total, 115 patients were evaluated. There were 26 (22.6%) and 14 (12.2%) patients with MIP and SOL subtypes, respectively. For concordance of MIP/SOL subtypes, the sensitivity was 65.7% (95% confidence interval [CI]: 57.7-65.7%). For the primary or secondary predominant patterns, a more satisfactory concordance rate of 72.2% (95% CI: 52.6-86.2%) was obtained. On assessing each subtype, high sensitivity was noted in SOL-predominant patterns (85.7%, 95% CI: 56.5%-96.0%) and MIP-secondary predominant patterns (83.3%, 95% CI: 45.8-97.0%). However, SOL-secondary predominant patterns revealed low sensitivity (0%, 95% CI, 0-38.2%). Overall, the MIP subtypes had higher sensitivity than the SOL subtypes (65.4% vs. 50.0%).

CONCLUSION

Cryobiopsy could be reliable for identifying MIP/SOL components, especially the MIP component, in clinical stage IA adenocarcinomas.

Stain-free identification of tissue pathology using a generative adversarial network to infer nanomechanical signatures

Intraoperative frozen section analysis can be used to improve the accuracy of tumour margin estimation during cancer resection surgery through rapid processing and pathological assessment of excised tissue. Its applicability is limited in some cases due to the additional risks associated with prolonged surgery, largely from the time-consuming staining procedure. Our work uses a measurable property of bulk tissue to bypass the staining process: as tumour cells proliferate, they influence the surrounding extra-cellular matrix, and the resulting change in elastic modulus provides a signature of the underlying pathology. In this work we accurately localise atomic force microscopy measurements of human liver tissue samples and train a generative adversarial network to infer elastic modulus from low-resolution images of unstained tissue sections. Pathology is predicted through unsupervised clustering of parameters characterizing the distributions of inferred values, achieving 89% accuracy for all samples based on the nominal assessment (n = 28), and 95% for samples that have been validated by two independent pathologists through post hoc staining (n = 20). Our results demonstrate that this technique could increase the feasibility of intraoperative frozen section analysis for use during resection surgery and improve patient outcomes.

Managing screening-detected subsolid nodules-the Asian perspective

The broad application of low-dose computed tomography (CT) screening has resulted in the detection of many small pulmonary nodules. In Asia, a large number of these detected nodules with a radiological ground glass pattern are reported as lung adenocarcinomas or premalignant lesions, especially among female non-smokers. In this review article, we discuss controversial issues and conditions involving these subsolid pulmonary nodules that we often face in Asia, including a lack or insufficiency of current guidelines; the roles of preoperative biopsy and imaging; the location of lesions; appropriate selection of localization techniques; the roles of dissection and sampling of frozen sections and lymph nodes; multifocal lesions; and the roles of non-surgical treatment modalities. For these complex issues, we have tried to present up-to-date evidence and our own opinions regarding the management of subsolid nodules. It is our hope that this article helps surgeons and physicians to manage the complex issues involving ground glass nodules (GGNs) in a balanced manner in their daily practice and provokes further discussion towards better guidelines and/or algorithms.

Prediction of micropapillary and solid pattern in lung adenocarcinoma using radiomic values extracted from near-pure histopathological subtypes

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.

Procedure-specific prognostic impact of micropapillary subtype may guide resection strategy in small-sized lung adenocarcinomas: a multicenter study

Background:

Limited resection has gradually become an acceptable treatment for lung adenocarcinomas (ADCs) presenting as ground-glass nodules (GGNs). However, its role in lung ADCs presenting as pure solid nodules (PSN) remains unclear. In this study, we aimed to identify potential candidates for limited resection in lung ADCs presenting as PSN.

Methods:

We retrospectively reviewed 772 patients from seven hospitals with lung ADCs ⩽2 cm, presenting as PSN on computed tomography scans, who had undergone surgery between 2009 and 2013. Histological subtypes were listed in 5% increments. To investigate the value of histological subtypes in surgical decision making, five pathologists prospectively evaluated the feasibility of identifying histological subtypes using frozen section (FS) in two cohorts.

Results:

The percentage of micropapillary (MIP) subtype had a striking impact on recurrence-free survival (RFS) and overall survival (OS) for lung ADCs ⩽2 cm presenting as PSNs. In multivariable Cox analysis, segmentectomy was significantly associated with worse RFS and OS in patients with MIP >5% than lobectomy, but not in those with MIP ⩽5%. With wedge resection, worse RFS and OS were observed in patients with MIP >5% and those with MIP ⩽5% than lobectomy. The sensitivity and specificity for detecting MIP by FS were 74.2% and 85.6%, respectively, with substantial inter-rater agreement.

Conclusion:

Segmentectomy and lobectomy had similar oncological outcomes in patients with lung ADCs ⩽2 cm presenting as PSN with MIP ⩽5%. Randomized trials are necessary to validate the feasibility of intraoperative FS to choose candidates for segmentectomy.

High expression of CXCL14 is a biomarker of lung adenocarcinoma with micropapillary pattern

Lung adenocarcinoma with micropapillary pattern (MPP) has an aggressive malignant behavior. Limited resection should be avoided because of its high recurrence rate. If adenocarcinoma with MPP is diagnosed preoperatively, the selection of proper treatment is possible. To explore a preoperative biomarker for diagnosing MPP, we undertook RNA sequencing analysis of 25 clinical samples as the training set, including 6 MPP, 16 other adenocarcinoma subtypes, and 3 normal lung tissues. Unsupervised hierarchical clustering analysis suggested a presence of subgroup with MPP showing different gene expression phenotype. We extracted differentially expressed genes with high expression levels in MPP samples, and chose VSIG1, CXCL14, and BAMBI as candidate biomarkers for MPP. Reverse transcription-quantitative PCR analysis confirmed a significantly higher expression of VSIG1 (P = .03) and CXCL14 (P = .02) in MPP than others. In a validation set of 4 MPP and 4 non-MPP samples, CXCL14 expression was validated to be significantly higher in MPP than in non-MPP (P = .04). Comparing a total of 10 MPP and 20 non-MPP samples, the area under the curve of CXCL14 to distinguish MPP from others was 0.89. The threshold value was 0.0116, corresponding to sensitivity 80% and specificity 90%. In immunostaining of CXCL14, the staining score was significantly higher in MPP cases than others, where not only the MPP component but also other components showed heterogeneous staining in adenocarcinoma tissues with MPP. Moreover, a higher staining score of CXCL14 was significantly associated with poorer prognosis in all patients (P = .01) or within cases in stage I-III (P = .01). In summary, we identified CXCL14 as a possible diagnostic biomarker of MPP.

Deep learning combined with radiomics may optimize the prediction in differentiating high-grade lung adenocarcinomas in ground glass opacity lesions on CT scans

PURPOSE

Adenocarcinoma (ADC) is the most common histological subtype of lung cancers in non-small cell lung cancer (NSCLC) in which ground glass opacifications (GGOs) found on computed tomography (CT) scans are the most common lesions. However, the presence of a micropapillary or a solid component is identified as an independent predictor of prognosis, suggesting a more extensive resection. The purpose of our study is to explore imaging phenotyping using a method combining radiomics with deep learning (RDL) to predict high-grade patterns within lung ADC.

METHODS

Included in this study were 111 patients differentiated as having GGOs and pathologically confirmed ADC. Four different groups of methods were compared to classify the GGOs for the prediction of the pathological subtypes of high-grade lung ADCs in definitive hematoxylin and eosin stain, including radiomics with gray-level features, radiomics with textural features, deep learning method, and the RDL.

RESULTS

We evaluated the performance of different models on 111 NSCLC patients using 4-fold cross-validation. The proposed RDL has achieved an overall accuracy of 0.913, which significantly outperforms the other methods (p <  0.01, analysis of variation, ANOVA). In addition, we also verified the generality and practical effectiveness of these models on an independent validation dataset of 28 patients. The results showed that our RDL framework with an accuracy of 0.966 significantly surpassed other methods.

CONCLUSION

High-grade lung ADC based on histologic pattern spectrum in GGO lesions might be predicted by the framework combining radiomics with deep learning, which reveals advantage over radiomics alone.

CT-Guided Core Biopsy for Peripheral Sub-solid Pulmonary Nodules to Predict Predominant Histological and Aggressive Subtypes of Lung Adenocarcinoma

BACKGROUND

Adenocarcinoma is the most common type of lung cancer, and pre-operative biopsy plays an important role to determine its major subtypes. As proposed by the International Association for the Study of Lung Cancer (IASLC), American Thoracic Society (ATS), and European Respiratory Society (ERS) in 2011, the predominant histological subtype of adenocarcinoma is an indicator of outcomes and recurrence rate. However, the value of CT-guided core biopsy in predicting the predominant subtype and detecting the presence of an aggressive subtype of adenocarcinoma, peripheral sub-solid nodule, has less been discussed.

METHODS

We retrospectively reviewed 318 consecutive peripheral sub-solid nodules that underwent percutaneous CT-guided lung biopsy and surgical resection, between October 2015 and December 2018 and were diagnosed as adenocarcinoma with histological subtype. The subtyping results from biopsy and surgical pathology were compared to evaluate the concordance rate.

RESULTS

The overall concordance rate between biopsy and surgical pathology in determining the predominant histological subtype was 64%. Better concordance was found in small tumors (≤ 2 cm), in predicting either predominant histology (χ² = 7.091, P = 0.008) or high grade adenocarcinoma, micropapillary and/or solid subtype, MIP-SOL (χ² = 22.301, P < 0.001). The analysis of ground glass opacity (GGO) component (C/T ratio) obtained significantly higher accuracy in the pure GGO group than in the other two groups in predicting predominant histology or high grade adenocarcinoma (χ² = 17.560, P < 0.001 and χ² = 61.938, P < 0.001, respectively).

CONCLUSIONS

CT-guided core biopsies provide additional value in predicting the histological subtype of lung adenocarcinoma after surgical resection, especially in small tumors (≤ 2 cm) or an initially pure GGO group.

Classifying non-small cell lung cancer types and transcriptomic subtypes using convolutional neural networks

OBJECTIVE

Non-small cell lung cancer is a leading cause of cancer death worldwide, and histopathological evaluation plays the primary role in its diagnosis. However, the morphological patterns associated with the molecular subtypes have not been systematically studied. To bridge this gap, we developed a quantitative histopathology analytic framework to identify the types and gene expression subtypes of non-small cell lung cancer objectively.

MATERIALS AND METHODS

We processed whole-slide histopathology images of lung adenocarcinoma (n = 427) and lung squamous cell carcinoma patients (n = 457) in the Cancer Genome Atlas. We built convolutional neural networks to classify histopathology images, evaluated their performance by the areas under the receiver-operating characteristic curves (AUCs), and validated the results in an independent cohort (n = 125).

RESULTS

To establish neural networks for quantitative image analyses, we first built convolutional neural network models to identify tumor regions from adjacent dense benign tissues (AUCs > 0.935) and recapitulated expert pathologists' diagnosis (AUCs > 0.877), with the results validated in an independent cohort (AUCs = 0.726-0.864). We further demonstrated that quantitative histopathology morphology features identified the major transcriptomic subtypes of both adenocarcinoma and squamous cell carcinoma (P < .01).

DISCUSSION

Our study is the first to classify the transcriptomic subtypes of non-small cell lung cancer using fully automated machine learning methods. Our approach does not rely on prior pathology knowledge and can discover novel clinically relevant histopathology patterns objectively. The developed procedure is generalizable to other tumor types or diseases.

An effective inflation treatment for frozen section diagnosis of small-sized lesions of the lung

Background

The accuracy of intraoperative pathological diagnosis of small-sized pulmonary nodules including ground-glass opacity (GGO) is important for the surgeon to choose a suitable surgical procedure. Diagnosis of the small-sized lesions of the lung by frozen section (FS) is very difficult for the pathologist because of limited FS technology. Here we tested an effective inflation treatment for FS to improve the diagnostic accuracy of small-sized lung lesions.

Methods

The lung specimens were derived from 113 patients who underwent the surgery at Shanghai Chest Hospital in 2018–2019. The specimens were randomly divided into two groups—uninflated or inflated with diluted embedding medium (Tissue-Tek OCT; Sakura Finetek-USA, CA). The qualities of the FSs were compared with that of corresponding permanent paraffin sections. The FS diagnoses were compared with the final pathologic diagnoses of corresponding permanent sections.

Results

Our results showed that the quality of FS of lung tissue was excellent after inflation with diluted embedding medium (1:1). The total consistency between diagnosis of inflated FS and final pathological diagnosis was 85.7%. In control group, however, the consistency was only 70.2%. When the lesions were less than 1cm, the consistency between diagnosis of inflated FS and final pathological diagnosis was 90.3%, compared to 64.9% consistency in uninflated group (P=0.014, <0.05). When the lesions’ computed tomography (CT) measurement threshold ≤−350 HU, the consistency between diagnosis of inflated FS and final pathological diagnosis was 88% compared to 73.2% consistency in uninflated group (P=0.071, >0.05). Accuracy, sensitivity and specificity were observed about 90% for adenocarcinoma in situ (AIS), whereas it is drop to more than 80% for minimally invasive adenocarcinoma (MIA) in inflated FS.

Conclusions

Inflation with diluted embedding medium (1:1) could make lung tissue expand well during FS. By using this method, small-sized lesions (especially less than 1 cm) could be correctly diagnosed to enable adequate surgical procedure, and evaluation of which can be easily based on the intraoperative pathological diagnosis. The small lesions especially AIS could be readily identified on FS. Therefore, this method improves the diagnostic accuracy of FSs for small-sized lung lesions, and has important practical consequences for further therapy.

Analysis of Segmental Lymph Node Metastasis and Clinical Features in cT1N0M0 Lung Adenocarcinoma

The progression of lung adenocarcinoma through lymph node metastasis has been well established; however, the process of segmental lymph node (LSN) metastasis in cT1N0M0 lung adenocarcinoma remains unclear. We aimed to elucidate the markers of lymph node metastasis to different segments in early-stage lung adenocarcinoma and identify new indications for segmentectomy. A total of 200 patients were enrolled in this study. These patients were diagnosed with cT1N0M0 lung adenocarcinoma after positron emission tomography/computed tomography and received lobectomy and lymph node dissection surgeries. Lymph nodes retrieved from each station were sorted. The metastatic status of the isolated (i) LSNs and several characteristics were analyzed. Patients with ground-glass nodules (GGNs) (P=0.025), AIS/MIA/lepidic adenocarcinoma (P=0.038), nodules with a maximum diameter ≤1 cm (P=0.017), maximum standardized uptake value (SUV_max) < 2.5 (P=0.029), serum carcinoembryonic antigen (CEA) levels ≤4.5 ng/ml (P=0.036), and no N1 lymph nodes metastasis (P=0.036) had significantly lower iLSN metastasis rates than those without these characteristics. Pure GGNs, CEA levels ≤4.5 ng/ml, SUV_max < 2.5, tumors with a maximum diameter of ≤1 cm, or those confirmed to be adenocarcinoma in situ, minimally invasive adenocarcinoma, or invasive lepidic-predominant adenocarcinoma by frozen section may indicate segmentectomy. However, segmentectomy is not suitable for patients with metastasis to the N1 lymph nodes.

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

OBJECTIVES

The sensitivity for tumor spread through air space (STAS), an independent risk factor for locoregional recurrence after sublobar resection for lung cancer, has been relatively low in frozen sections. We aimed to determine predictors with high negative predictive value for the presence of STAS and to provide the flowchart in combination with these predictors for the decision-making for sublobar resection.

MATERIALS AND METHODS

Between July 2015 and December 2017, 387 patients who underwent surgery for non-small cell lung cancer (NSCLC) with pathologic findings of the total masses measuring ≤ 2 cm were enrolled. The lesions were divided into two groups according to presence of STAS. We compared the preoperative characteristics, operative data, and developed a flowchart for STAS prediction using receiver operator characteristic curve analysis and multivariable logistic regression.

RESULTS

The STAS-positive group (N = 111) had a significantly higher preoperative tumor size (1.70 [1.5] vs 1.50 [0.69], p < 0.001) and standardized uptake value tumor-to-liver (SUV T/L) ratio (1.40 [1.60] vs 0.60 [1.10], p < 0.001) and a significantly lower two-dimensional ground-glass opacity (GGO) percentage (35.86 [61.00] vs 78.14 [39.00], p < 0.001). Meanwhile, the STAS-negative group (N = 286) had higher lepidic predominance (41.6% vs. 1.8%, p < 0.001). We developed a flowchart for predicting STAS in combination with two-dimensional GGO percentage on computed tomography (CT), SUV T/L ratio on positron-emission CT, and lepidic predominant pattern. The sensitivity, specificity, and negative predictive value for STAS positivity were 79.3%, 68.5%, and 89.5%, respectively.

CONCLUSIONS

The stepwise flowchart using two-dimensional GGO percentage on CT, maximum SUV, and lepidic predominance might be helpful in selecting patients with early NSCLC for sublobar resection.

Advances In Research Of Spreading Through Air Spaces And The Effects On The Prognosis Of Lung Cancer

The concept of spread through air spaces (STAS) has been described as a new form of invasion in the lung in the 2015 WHO classification of Lung Tumors, namely invasion through alveolar spaces. STAS is a prognostic factor independent of growth pattern and tumor stage, and it is also an independent risk factor for unfavorable prognosis of stage I lung adenocarcinoma (ADC) and stage I lung squamous cell carcinoma (SCC). The pathological characteristics are different between ADC and SCC. STAS is not reported as routine, so setting a unified pathological reading standard, and hunting for STAS as a regular reading process is urgently advocated. We write this review to investigate the research progress of STAS and its effects on the prognosis of lung cancer.

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

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

[Progress on the Study of Tumor Spread Through Air Spaces in the Clinicopathological Characteristics of Lung Adenocarcinoma and Its Influence on the Surgical Treatment and Prognosis of Lung Cancer]

肿瘤肺泡腔内播散（tumor spread through air spaces, STAS）作为一种新的病理侵袭方式，与诸多临床病理因素紧密相关。在肺腺癌中，微乳头和实体型病理亚型与之关系最为密切；针对早期肺腺癌存在STAS，手术类型的治疗上肺叶切除似乎优于亚肺叶切除而获益，可能上调早期肺癌的病理分期；同时，STAS与鳞癌等非小细胞肺癌（non-small cell lung cancer, NSCLC）关系密切。此外，STAS的术中冰冻切片病理检测困难，亦有争议存在。STAS作为肿瘤复发的独立危险因素，亦是提示预后不良的重要因素，本文将STAS的研究现状和进展作一综述。

There Is High Sensitive and Specific Correlation Between Frozen and Permanent Sections in Renal Transplant Biopsies

INTRODUCTION

Frozen sections have been used for evaluating tumors and margins during daily practice in pathology with high specificity and sensitivity (>90% for both indices both at national level and in our department). The correlation between frozen section tissue for immunofluorescent (IF) studies and permanent sections for light microscopy, along with electron microscopy, is critical for constructing a final renal pathology diagnosis.

METHODS

We studied the correlation between the frozen sections for IF studies and separate fragments of tissue for permanent light microscopic sections in our renal transplant biopsies for purposes of quality control. Frozen sections for IF sections were compared with permanent sections for light microscopy in 122 renal transplant biopsies, using inflammation as the key criterion (63 with no inflammation and 59 with inflammation) to determine the correlation.

RESULTS

There was high sensitivity (94.9%) and specificity (92.1%) for the correlation between the frozen section and permanent sections.

CONCLUSIONS

Our data suggest that parts of renal transplant biopsy tissue dissected to freeze for IF studies and for light microscopy were highly correlated to ensure a high quality of renal tissue dissection for the final diagnosis in renal transplant biopsies.

Raman spectroscopy for cancer detection and cancer surgery guidance: translation to the clinics

Oncological applications of Raman spectroscopy have been contemplated, pursued, and developed at academic level for at least 25 years. Published studies aim to detect pre-malignant lesions, detect cancer in less invasive stages, reduce the number of unnecessary biopsies and guide surgery towards the complete removal of the tumour with adequate tumour resection margins. This review summarizes actual clinical needs in oncology that can be addressed by spontaneous Raman spectroscopy and it provides an overview over the results that have been published between 2007 and 2017. An analysis is made of the current status of translation of these results into clinical practice. Despite many promising results, most of the applications addressed in scientific studies are still far from clinical adoption and commercialization. The main hurdles are identified, which need to be overcome to ensure that in the near future we will see the first Raman spectroscopy-based solutions being used in routine oncologic diagnostic and surgical procedures.

Novel method for rapid identification of micropapillary or solid components in early-stage lung adenocarcinoma

OBJECTIVE

Sublobar resection may be insufficient for early-stage lung adenocarcinoma with micropapillary or solid components because of the associated higher incidence of locoregional recurrence. This study sought to establish a novel method for rapidly identifying their presence to facilitate decision making for sublobar resection.

METHODS

Antibody arrays of adhesion and apoptosis molecules were applied for adenocarcinomas with or without micropapillary/solid components to identify differentially expressed proteins. A semi-dry dot-blot system that visualizes the presence of target proteins was used to determine the presence of micropapillary or solid components in a prospective cohort of patients with clinical stage I who underwent operation. Sensitivity and specificity were calculated by comparing semi-dry dot-blot results with pathologic examinations.

RESULTS

Insulin-like growth factor-binding protein 2 and P-cadherin were found more frequently in the micropapillary or solid positive group, and these were used as the target proteins in the semi-dry dot-blot system for detection of micropapillary or solid components. A total of 68 nodules with a mean size of 2.3 ± 0.7 cm, including 13 (19.1%) with a micropapillary and 20 (29.4%) with a solid pattern, were recruited. Micropapillary or solid (+) lesions were more likely to have lymph node upstaging, greater diameter, and higher maximum standardized uptake value. The specificity and sensitivity for detecting the minor presence of micropapillary or solid component using the semi-dry dot-blot method were 94.4% (95% confidence interval, 81.3-99.3) and 65.6% (95% confidence interval, 46.8-81.4), respectively. The average test duration was 26.9 ± 2.5 minutes.

CONCLUSIONS

Detecting insulin-like growth factor-binding protein 2 and P-cadherin via the semi-dry dot-blot method could identify micropapillary or solid components in early-stage lung adenocarcinoma in a short processing time.

Spread through air spaces (STAS): a comprehensive update

The new concept of spread through air spaces (STAS) was introduced for pulmonary adenocarcinomas (ADC) in the 2015 World Health Organization (WHO) classification for lung cancer. Yet available data demonstrate that STAS is of high prognostic impact and associated with specific clinic-pathological characteristics. This article provides a comprehensive overview on recent developments in this field.

Histopathologic and molecular approach to staging of multiple lung nodules

Distinguishing multiple primary lung cancers from intrapulmonary metastases in patients with synchronous multifocal lung adenocarcinomas can be challenging. The most recent 8th edition American Joint Committee on Cancer staging manual (AJCC staging manual) distinguishes four disease patterns in patients with multiple lung nodules: (I) two or more distinct and histologically different masses (considered unrelated and staged as individual cancers); (II) multiple ground-glass or part-solid nodules, histologically of with lepidic growth pattern (considered separate tumors, T staged based on highest T stage lesion); (III) patchy areas of ground-glass and consolidations, histologically often invasive mucinous adenocarcinomas (considered single tumor with diffuse "pneumonic-type" involvement); and (IV) separate nodules with the same histologic features based on comprehensive histologic subtyping (considered intrapulmonary metastases). Histologic and molecular features, in conjunction with clinical and radiological information, can all be tools to assist with staging of multiple nodules. Histologic features of adenocarcinomas are best characterized using comprehensive histologic subtyping (percentage of lepidic, acinar, solid, papillary and micropapillary pattern). Genomic alterations are commonly assessed using fluorescence in-situ hybridization and next generation sequencing (NGS). The AJCC considers exactly matching breakpoints by comparative genomic hybridization (CGH) as the only evidence for intrapulmonary metastases, and clearly different histologic types or subtypes as the only evidence for separate primary tumors. Similar histologic subtypes or the same biomarker pattern are considered merely relative arguments in favor of a single tumor source. When assessing multifocal lung cancer, pathologists should consider, and carefully weigh the importance of, molecular testing results in addition to the tumor's histologic features. For many cases encountered in routine clinical practice, absolute certainty cannot be reached as to whether they represent multiple primary cancers or intrapulmonary metastases. Classification of difficult cases often benefits from multidisciplinary discussion.

Relationship of Lymph Node Micrometastasis and Micropapillary Component and Their Joint Influence on Prognosis of Patients With Stage I Lung Adenocarcinoma

This study aimed to investigate the relationship between lymph node micrometastasis and histologic patterns of adenocarcinoma, with a particular focus on their joint effect on prognosis. We retrospectively reviewed 235 patients with stage I adenocarcinoma from January 2009 to December 2009. Lymph node micrometastasis was evaluated by immunohistochemical staining for cytokeratin (AE1/AE3) and thyroid transcription factor-1. A logistic regression model was applied to confirm the predictive factors of micrometastasis. Survival analysis was performed to evaluate the effect of micrometastasis on prognosis. Lymph node micrometastasis was observed in 35 patients (15%). Patients with micrometastasis had significantly worse recurrence-free survival (P<0.001) and overall survival (P<0.001) compared with those without micrometastasis. Micropapillary component was confirmed as an independent predictor of increased frequency of micrometastasis (P<0.001). Among 62 patients with adenocarcinoma with a micropapillary component, 23 (37%) had lymph node micrometastasis. Micropapillary-positive/micrometastasis-positive patients had significantly worse survival compared with micropapillary-positive/micrometastasis-negative patients (RFS, P=0.039; OS, P=0.002) and micropapillary-negative patients (recurrence-free survival, P<0.001; overall survival, P<0.001). Moreover, the presence of micrometastasis correlated with a higher risk of locoregional recurrence (P=0.031) rather than distant recurrence (P=0.456) in micropapillary-positive patients. In summary, lymph node micrometastasis was more frequently observed in adenocarcinoma with a micropapillary component. Moreover, lymph node micrometastasis could provide helpful prognostic information in patients with resected stage I lung adenocarcinoma with a micropapillary component; thus, immunohistochemical detection of micrometastatic tumor cells in lymph nodes should be recommended.

Inaccuracy of lung adenocarcinoma subtyping using preoperative biopsy specimens

BACKGROUND

The prognostic significance of the new classification of lung adenocarcinoma proposed in the 2015 World Health Organization guideline has been validated. This study aimed to compare the preoperative classification of the adenocarcinoma subtype based on computed tomography-guided 18-gauge core needle biopsy (CTNB) or radial probe endobronchial ultrasound (R-EBUS) specimens, with the postoperative classification based on the resected specimens.

METHODS

We retrospectively analyzed a consecutive series of 128 patients (60 CTNB and 68 R-EBUS) who underwent surgery for preoperatively confirmed lung adenocarcinoma between 2010 and 2014. Comprehensive histological subtyping was performed according to the 2015 World Health Organization classification system. Diagnostic concordance of subtypes between small biopsy and resection specimens was assessed.

RESULTS

Concordant subtyping of adenocarcinomas between the predominant pattern on resections and biopsy sections was observed in 58.6% of cases (75 of 128; 95% confidence interval [CI], 49.9%-66.8%). Preoperative subtyping was accurate in only 30% of samples (3 of 10) with a predominance of solid patterns. None of the 5 micropapillary predominant cases was detected by CTNB or R-EBUS. For the concordance of the presence or absence of micropapillary/solid component, the sensitivity was as low as 16.5% (95% CI, 9.1%-26.5%). The detection rate by CTNB/R-EBUS increased with the increase in the percentage of micropapillary/solid component; however, even in the ≥40% micropapillary/solid group, only 24% of cases were detected by CTNB/R-EBUS.

CONCLUSIONS

The accuracy of the estimation of adenocarcinoma histological subtype based on preoperative biopsy sections was unsatisfactory.

Micropapillary histological subtype in lung adenocarcinoma of 2 cm or less: impact on recurrence and clinical predictors

OBJECTIVE

This study examined the clinical and radiological characteristics of adenocarcinoma having the micropapillary histological subtype.

METHODS

We included 233 patients who were operated from 2001 to 2012 for lung adenocarcinoma of 2 cm or less. The pathology was reviewed according to the 2015 WHO classification. We defined adenocarcinoma with a micropapillary component as adenocarcinoma in which the area of the micropapillary histological subtype exceeded 5% of the tumor. The difference in cumulative incidence of recurrence (CIR) in the presence of death as a competing risk between two groups was assessed using the methods of Gray.

RESULTS

Twenty-one cases (9.0%) had a micropapillary component. The micropapillary component was associated with a higher frequency of lymphatic invasion (28.6 vs. 7.5% in adenocarcinoma without a micropapillary component; P = 0.008) and vascular invasion (38.1 vs. 15.1%, P = 0.014) and lymph node metastasis (31.3 vs. 5.2%, P = 0.003). The median follow-up period was 6.5 years. CIR at 5 years was 23.8% [95% confidence interval (CI), 8.3-43.7%] for adenocarcinoma with a micropapillary component, and 11.4% (95% CI, 7.4-16.2%) for adenocarcinoma without a micropapillary component (P = 0.033). Adenocarcinoma with a micropapillary component was more frequent in solid nodules (17.8%, 16/90) on high-resolution computed tomography (HRCT) than in either ground-glass nodules (1.5%, 1/67) or part-solid nodules (5.3%, 4/76) (P = 0.001). The HRCT finding was the only preoperative factor that was associated with a micropapillary component in the multivariate analysis.

CONCLUSIONS

The micropapillary component in adenocarcinoma should be regarded as indicative of a high-grade malignancy and was associated with the HRCT finding.

Recent clinical innovations in thoracic surgery in Hong Kong

The concept of personalized medicine, which aims to provide patients with targeted therapies while greatly reducing surgical trauma, is gaining popularity among Asian clinicians. Single port video-assisted thoracic surgery (VATS) has rapidly gained popularity in Hong Kong for major lung resections, despite bringing new challenges such as interference between surgical instruments and insertion of the optical source through a single incision. Novel types of endocutters and thoracoscopes can help reduce the difficulties commonly encountered during single-port VATS. Our region has been the testing ground and has led the development of many of these innovations. Performing VATS, in particular single-port VATS in hybrid operating theatre helps to localise small pulmonary lesions with real-time images, thus increasing surgical accuracy and pushes the boundaries in treating subcentimeter diseases. Such approach may be assisted by use of electromagnetic navigational bronchoscopy in the same setting. In addition, sublobar resection can also be more individualised according to pathologic tumour subtype that require rapid intraoperative diagnostic test to guide appropriate surgical therapy. A focus on technology and innovation for large tumours that require chest wall resection and reconstructions have also been on going, with new materials and prostheses that may be tailored to each individual needs. The current paper reviews the literature pertaining to the above topics and discusses recent related innovations in Hong Kong, highlighting the study results and future perspectives.

Is there significance in identification of non-predominant micropapillary or solid components in early-stage lung adenocarcinoma?

A best evidence topic in thoracic surgery was written according to a structured protocol. The question addressed was 'in early-stage lung adenocarcinomas, does the presence of non-predominant micropapillary (MIP) or solid (SOL) growth component influence long-term survival and surgical strategy?'. Altogether, more than 600 papers were found using the reported search, of which 13 presented the best evidence to answer the clinical question. The authors, journal, date and country of publication, patient group, study type, relevant outcomes and results of these papers were tabulated. The data collected showed that non-predominant MIP or SOL components in early-stage lung adenocarcinoma can be up to 60.4 and 41.8%, respectively. MIP or SOL components were associated with significantly reduced period of disease-free or overall survival. One study also showed a higher incidence of occult lymph node metastasis in patients with a minor MIP component. Furthermore, the presence of an MIP/SOL component in early-stage adenocarcinomas (ADCs) could influence the oncological outcome following sublobar resection. We conclude that a non-predominant MIP/SOL pattern is a negative prognostic factor and an indicator of early recurrence after limited resection.