Radiologic Criteria in Predicting Pathologic Less Invasive Lung Cancer According to TNM 8th Edition

Preoperative CT-based radiomics nomogram to predict the micropapillary pattern in lung adenocarcinoma of size 2 cm or less

Purpose

To develop and validate a radiomics nomogram model for predicting the micropapillary pattern (MPP) in lung adenocarcinoma (LUAD) tumors of ≤2 cm in size.

Methods

In this study, 300 LUAD patients from our institution were randomly divided into the training cohort (n = 210) and an internal validation cohort (n = 90) at a ratio of 7:3, besides, we selected 65 patients from another hospital as the external validation cohort. The region of interest of the tumor was delineated on the computed tomography (CT) images, and radiomics features were extracted. A nomogram model was established using radiomics features, clinical features and conventional radiographic features. The nomogram model was compared with the radiomics model and the clinical model alone to test its diagnostic validity. Receiver operating characteristic (ROC) curves, areas under the ROC curves and decision curve analysis (DCA) results were plotted to evaluate the model performance and clinical application.

Results

The nomogram model exhibited superior performance, with an AUC of 0.905 (95% confidence interval [CI]: 0.857-0.951) in the training cohort, which decreased to 0.817 (95% CI: 0.698-0.936) in the external validation cohort. The clinical model had AUCs of 0.820 (95% CI: 0.753-0.886) and 0.730 (95% CI: 0.572-0.888) in the training and external validation cohorts, respectively. The radiomics model had AUCs of 0.895 (95% CI: 0.840-0.949) and 0.800 (95% CI: 0.675-0.924) for training and external validation, respectively. DCA confirmed that the nomogram model had the better clinical benefit.

Conclusions

The nomogram model achieved promising prediction efficiency for identifying the presence of the MPP in LUAD tumors ≤2 cm, allowing clinicians to develop more rational and efficacious personalized treatment strategies.

Prediction of Pleural Lavage Cytology According to Thin-Section Computed Tomography in Non-Small-Cell Lung Cancer

BACKGROUND

Although the positive rate of preresection pleural lavage cytology (PLC) is low, it is an important indicator of poor prognosis for non-small-cell lung cancer patients with frequent pleural dissemination (PD) recurrence. Thin-section computed tomography (TSCT) can reveal relationships between a primary tumor and the pleura at 1 to 2 mm intervals, and this is associated with visceral pleural invasion (VPI). However, its association with PLC remains unclear. Therefore, we aimed to improve PLC efficiency and predict PD recurrence by understanding the relationship between PLC and preoperative TSCT findings.

PATIENTS AND METHODS

Between January 2014 and December 2018, we reviewed 978 patients with non-small-cell lung cancer who underwent PLC tests during complete resection surgery. Preoperative TSCT findings were evaluated, and factors with the highest specificity (proportion of patients with radiologically to pathologically diagnosed positive PLC) were investigated. We also evaluated their relationships with VPI and PD recurrence.

RESULTS

PLC positive was identified in 55 (5.6%) of the 978 patients. The two TSCT findings predicting PLC results, "the absence of pleural findings," ie, tumor not attached to pleura or without pleural tag, and "consolidation-to-tumor ratio ≤0.5", had a specificity of 100% (95% confidence interval: 90.4%-100%); additionally, all cases with these findings were VPI negative and had no PD recurrence. And 24% of the cohort had either of these findings.

CONCLUSION

The absence of pleural findings and/or consolidation-to-tumor ratio ≤0.5 of primary tumor on preoperative TSCT can predict PLC negativity with very high probability; therefore, PLC can be omitted for such patients.

Comparative long-term prognosis of early surgery and surgery after surveillance for patients with ground-glass nodule adenocarcinomas

To compare the pathological results and long-term survival results of early surgery and surgery after at least one year follow-up for ground-glass component predominant lung adenocarcinoma patients. From January 1, 2013 to August 31, 2017, a total of 279 patients with ground-glass nodules (GGNs) undergoing surgical resection and pathologically proved to be pulmonary adenocarcinoma were included in this study. All patients were divided into early surgery group (ES Group) (210 cases) and surgery after follow-up group (FS Group) (69 cases). Patients in FS group experienced at least one year surveillance. Clinical and imaging features were analyzed by using univariate analysis. After analysis, there was no statistical difference in pathological results and long-term prognosis between the two groups. In the follow-up group, grown GGNs have proved to have more aggressive pathological results. The one-year follow-up may be a feasible management method for patients with ground-glass component predominant GGN.

A nomogram based on the quantitative and qualitative features of CT imaging for the prediction of the invasiveness of ground glass nodules in lung adenocarcinoma

PURPOSE

Based on the quantitative and qualitative features of CT imaging, a model for predicting the invasiveness of ground-glass nodules (GGNs) was constructed, which could provide a reference value for preoperative planning of GGN patients.

MATERIALS AND METHODS

Altogether, 702 patients with GGNs (including 748 GGNs) were included in this study. The GGNs operated between September 2020 and July 2022 were classified into the training group (n = 555), and those operated between August 2022 and November 2022 were classified into the validation group (n = 193). Clinical data and the quantitative and qualitative features of CT imaging were harvested from these patients. In the training group, the quantitative and qualitative characteristics in CT imaging of GGNs were analyzed by using performing univariate and multivariate logistic regression analyses, followed by constructing a nomogram prediction model. The differentiation, calibration, and clinical practicability in both the training and validation groups were assessed by the nomogram models.

RESULTS

In the training group, multivariate logistic regression analysis disclosed that the maximum diameter (OR = 4.707, 95%CI: 2.06-10.758), consolidation/tumor ratio (CTR) (OR = 1.027, 95%CI: 1.011-1.043), maximum CT value (OR = 1.025, 95%CI: 1.004-1.047), mean CT value (OR = 1.035, 95%CI: 1.008-1.063; P = 0.012), spiculation sign (OR = 2.055, 95%CI: 1.148-3.679), and vascular convergence sign (OR = 2.508, 95%CI: 1.345-4.676) were independent risk parameters for invasive adenocarcinoma. Based on these findings, we established a nomogram model for predicting the invasiveness of GGN, and the AUC was 0.910 (95%CI: 0.885-0.934) and 0.902 (95%CI: 0.859-0.944) in the training group and the validation group, respectively. The internal validation of the Bootstrap method showed an AUC value of 0.905, indicating a good differentiation of the model. Hosmer-Lemeshow goodness of fit test for the training and validation groups indicated that the model had a good fitting effect (P > 0.05). Furthermore, the calibration curve and decision analysis curve of the training and validation groups reflected that the model had a good calibration degree and clinical practicability.

CONCLUSION

Combined with the quantitative and qualitative features of CT imaging, a nomogram prediction model can be created to forecast the invasiveness of GGNs. This model has good prediction efficacy for the invasiveness of GGNs and can provide help for the clinical management and decision-making of GGNs.

CT-Based Deep-Learning Model for Spread-Through-Air-Spaces Prediction in Ground Glass-Predominant Lung Adenocarcinoma

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-DLwoSCG), 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-DLwoSCG 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.

Preoperative prognostic prediction for stage I lung adenocarcinomas: Impact of the computed tomography features associated with the new histological grading system

Objectives

This study aimed to identify the computed tomography (CT) features associated with the new International Association for the Study of Lung Cancer (IASLC) three-tiered grading system to improve the preoperative prediction of disease-free survival of stage I lung adenocarcinoma patients.

Methods

The study included 379 patients. Ordinal logistic regression analysis was used to identify the independent predictors of IASLC grades. The first multivariate Cox regression model (Model 1) was based on the significant factors from the univariate analysis. The second multivariate model (Model 2) excluded the histologic grade and based only on preoperative factors.

Results

Larger consolidation tumor ratio (OR=2.15, P<.001), whole tumor size (OR=1.74, P=.002), and higher CT value (OR=3.77, P=.001) were independent predictors of higher IASLC grade. Sixty patients experienced recurrences after 70.4 months of follow-up. Model 1 consisted of age (HR:1.05, P=.003), clinical T stage (HR:2.32, P<.001), histologic grade (HR:4.31, P<.001), and burrs sign (HR:5.96, P<.001). Model 2 consisted of age (HR,1.04; P=.015), clinical T stage (HR:2.49, P<.001), consolidation tumor ratio (HR:2.49, P=.016), whole tumor size (HR:2.81, P=.022), and the burrs sign (HR:4.55, P=.002). Model 1 had the best prognostic predictive performance, followed by Model 2, clinical T stage, and histologic grade.

Conclusion

CTR (cut-off values of <25% and ≥75%) and whole tumor size (cut-off value of 17 mm) could stratify patients into different prognosis and be used as preoperative surrogates for the IASLC grading system. Integrating these CT features with clinical T staging can improve the preoperative prognostic prediction for stage I lung adenocarcinoma patients.

Analysis on the Effects of CT- and Ultrasound-Guided Percutaneous Transthoracic Needle Biopsy Combined with Serum CA125 and CEA on the Diagnosis of Lung Cancer

The number of patients with lung cancer is difficultly diagnosed in the early stage. The purpose of the study was to investigate the effects of CT- and ultrasound-guided percutaneous transthoracic needle biopsy combined with serum CA125 and CEA on the diagnosis of lung cancer. 120 patients with suspected lung cancer admitted to our hospital from January 2019 to January 2020 were selected and divided into an ultrasound group (n = 60) and CT group (n = 60), according to different percutaneous transthoracic needle biopsy modalities. All patients received serum tumor markers detection, so as to compare the CT- and ultrasound-guided percutaneous transthoracic needle biopsy results and pathology results, levels of serum tumor markers among all patients and the patients with different lung cancer types, and diagnostic efficacy of tumor markers, as well as complication rate (CR) in patients. The sensitivity and specificity of ultrasound-guided percutaneous transthoracic needle biopsy were 0.880 and 0.800, respectively, while those of CT-guided percutaneous transthoracic needle biopsy were 0.909 and 0.625, respectively; the CA125 and CEA levels in the lung cancer group were higher than those in the benign group (P < 0.001); the CA125 and CEA levels of the patients with adenocarcinoma were higher than those with squamous carcinoma, and the CEA levels of the patients with small-cell carcinoma were lower than those with adenocarcinoma (P < 0.05); the sensitivity, specificity, and Youden indexes of CA125 were 0.638, 0.833, and 0.471, respectively, while those of CEA were 0.766, 0.778, and 0.544, respectively; there were no significant differences in CR between the two groups (P > 0.05). CT- and ultrasound-guided percutaneous transthoracic needle biopsy is a safe and feasible diagnostic modality for lung cancer, and its combination with serum CA125 and CEA can significantly improve the accuracy of the detection results, which is worthy of promotion and application in clinical practice.

Risk analysis in peripheral clinical T1 non-small cell lung cancer correlations between tumor-to-blood standardized uptake ratio on 18F-FDG PET-CT and primary tumor pathological invasiveness: a real-world observational study

BACKGROUND

Sublobar resection is not suitable for patients with pathological invasiveness [including lymph node metastasis (LNM), visceral pleural invasion (VPI), and lymphovascular invasion (LVI)] of peripheral clinical T1 (cT1) non-small cell lung cancer (NSCLC), while primary tumor maximum standardized uptake value (SUV_max) on ¹⁸F-FDG PET-CT is related to pathological invasiveness, the significance differed among different institutions is still challenging. This study explored the relationship between the tumor-to-blood standardized uptake ratio (SUR) of ¹⁸F-FDG PET-CT and primary tumor pathological invasiveness in peripheral cT1 NSCLC patients.

METHODS

This retrospective study included 174 patients with suspected lung neoplasms who underwent preoperative ¹⁸F-FDG PET-CT. We compared the differences of the clinicopathological variables, metabolic and morphological parameters in the pathological invasiveness and less-invasiveness group. We performed a trend test for these parameters based on the tertiles of SUR. The relationship between SUR and pathological invasiveness was evaluated by univariate and multivariate logistics regression models (included unadjusted, simple adjusted, and fully adjusted models), odds ratios (ORs), and 95% confidence intervals (95% CIs) were calculated. A smooth fitting curve between SUR and pathological invasiveness was produced by the generalized additive model (GAM).

RESULTS

Thirty-eight point five percent of patients had pathological invasiveness and tended to have a higher SUR value than the less-invasiveness group [6.50 (4.82-11.16) vs. 4.12 (2.04-6.61), P<0.001]. The trend of SUV_max, mean standardized uptake value (SUV_mean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), mean CT value (CT_mean), size of the primary tumor, neuron-specific enolase (NSE), the incidence of LNM, adenocarcinoma (AC), and poor differentiation in the tertiles of SUR value were statistically significant (P were <0.001, <0.001, 0.010, <0.001, <0.001, 0.002, 0.033, <0.001, 0.002, and <0.001, respectively). Univariate analysis showed that the risk of pathological invasiveness increased significantly with increasing SUR [OR: 1.13 (95% CI: 1.06-1.21), P<0.001], and multivariate analysis demonstrated SUR, as a continuous variable, was still significantly related to pathological invasiveness [OR: 1.09 (95% CI: 1.01-1.18), P=0.032] after adjusting for confounding covariates. GAM revealed that SUR tended to be linearly and positively associated with pathological invasiveness and E-value analysis suggested robustness to unmeasured confounding.

CONCLUSIONS

SUR is linearly and positively associated with primary tumor pathological invasiveness independent of confounding covariates in peripheral cT1 NSCLC patients and could be used as a supplementary risk maker to assess the risk of pathological invasiveness.

Preoperative CT-Based Radiomics Combined With Nodule Type to Predict the Micropapillary Pattern in Lung Adenocarcinoma of Size 2 cm or Less: A Multicenter Study

Purpose

To construct an optimal radiomics model for preoperative prediction micropapillary pattern (MPP) in adenocarcinoma (ADC) of size ≤ 2 cm, nodule type was used for stratification to construct two radiomics models based on high-resolution computed tomography (HRCT) images.

Materials and Methods

We retrospectively analyzed patients with pathologically confirmed ADC of size ≤ 2 cm who presented to three hospitals. Patients presenting to the hospital with the greater number of patients were included in the training set (n = 2386) and those presenting to the other two hospitals were included in the external validation set (n = 119). HRCT images were used for delineation of region of interest of tumor and extraction of radiomics features; dimensionality reduction was performed for the features. Nodule type was used to stratify the data and the random forest method was used to construct two models for preoperative prediction MPP in ADC of size ≤ 2 cm. Model 1 included all nodule types and model 2 included only solid nodules. The receiver operating characteristic curve was used to assess the prediction performance of the two models and independent validation was used to assess its generalizability.

Results

Both models predicted ADC with MPP preoperatively. The area under the curve (AUC) of prediction performance of models 1 and 2 were 0.91 and 0.78, respectively. The prediction performance of model 2 was lower than that of model 1. The AUCs in the external validation set were 0.81 and 0.72, respectively. The DeLong test showed statistically significant differences between the training and validation sets in model 1 (p = 0.0296) with weak generalizability. There was no statistically significant difference between the training and validation sets in model 2 (p = 0.2865) with some generalizability.

Conclusion

Nodule type is an important factor that affects the performance of radiomics predictor model for MPP with ADC of size ≤ 2 cm. The radiomics prediction model constructed based on solid nodules alone, can be used to evaluate MPP and may contribute to proper surgical planning in patients with ADC of size ≤ 2 cm.

Narrative review of optimal prognostic radiological tools using computed tomography for T1N0-staged non-small cell lung cancer

Various radiological tools can predict the prognosis of non-small cell lung cancer (NSCLC). In this study, we evaluated the prognostic effect of different radiological tools such as whole tumor size (WTS), consolidation size (CS), consolidation tumor ratio (CTR), tumor disappearance ratio (TDR), mediastinal diameter (MD), and ground glass opacity (GGO) using high-resolution computed tomography (HRCT). We reviewed recent retrospective studies on the predictive effect of these radiological tools on disease-free survival (DFS) and overall survival (OS) in patients with T1N0-staged NSCLC. We searched PubMed and the British Library databases for the English literature published from January 2010 to December 2020 and generated a total of 32 publications (NSCLC, n=16; adenocarcinoma, n=16). The TNM classification version 7 was used in 18 studies, and version 8 in 14 studies. The evaluated radiological parameters were WTS, CS including T category, CTR, TDR, MD, presence of GGO, GGO ratio, and pure GGO. This review suggested that CS, MD, and the presence of GGO are optimal prognostic radiological tools for cT1N0-Staged NSCLC. CTR or TDR for part solid nodules (PSNs) is not a well-accepted prognostic factor. Further investigations are required to differentiate between benign scars and malignant components on HRCT and evaluate the prognosis of PSNs (1< CS ≤2 cm) with large WTS in the future.

[Assessment of the Accuracy of Modified Inflation-deflation Methods for Distinguishing the Intersegmental Border]

背景与目的

对于早期肺癌，肺段切除术可以获得和肺叶切除术相同的肿瘤学疗效。肺段间交界面的精准界定是肺段手术的关键。本研究采用“改良膨胀萎陷法”行扩大肺段、亚段切除术治疗肺段间、亚段间磨玻璃结节（ground-glass nodules, GGN），评价“改良膨胀萎陷法”界定肺段交界面的精确性，和对扩大切除确保安全切缘宽度的有效性。

方法

回顾性分析本中心采用扩大肺段、亚段切除术治疗的患者83例。术前三维CT支气管血管成像（three-dimensional computed tomography bronchography and angiography, 3D-CTBA）显示结节累及段间静脉。根据三维重建设计手术，扩大切除结节所属的优势肺段或亚段，无法确定优势肺段、亚段时，选择较为简单的肺段、亚段切除方式。术中切断靶段血管、支气管后采用“改良膨胀萎陷法”确定肺段间或亚段间交界面，应用切割缝合器距离膨胀萎陷交界线2 cm-3 cm扩大切除部分相邻肺段或亚段肺组织。观察标本中膨胀萎陷交界线与结节的关系，测量切缘宽度，收集围术期临床资料。

结果

实施扩大肺段切除术56例，扩大肺亚段切除术27例，肺结节平均直径（0.9±0.3）cm。出现清晰可辨膨胀萎陷交界线79例，交界线形成时间（13.6±6.5）min。解剖标本观察发现，结节累及膨胀萎陷交界线55例，其余24例结节距交界线的最小距离（0.6±0.3）cm，平均切缘宽度（2.1±0.3）cm。无术后30 d死亡和重大并发症。

结论

改良膨胀萎陷法可有效界定肺段间、亚段间交界面，以此为标准可确保扩大肺段、亚段切除术治疗段间、亚段间小肺癌的安全切缘。

Pathological features and prognostic implications of ground-glass opacity components on computed tomography for clinical stage I lung adenocarcinoma

PURPOSE

To investigate the prognostic implications and pathological features of clinical stage I lung adenocarcinoma with ground-glass opacity (GGO) on computed tomography (CT).

METHODS

The subjects of this retrospective study were 1228 patients with lung adenocarcinoma classified as clinical stage I, who underwent complete resection by lobectomy. The patients were divided into four groups based on the presence and proportion of GGO according to the consolidation-to-tumor ratio (CTR); A, CTR ≤ 0.5; B, 0.5 < CTR ≤ 0.75; C, 0.75 < CTR ≤ 1.0 with GGO; D, without GGO (pure-solid). We compared overall survival, pathological findings (N/ly/v/STAS), and histological subtypes within each clinical stage among the four groups.

RESULTS

We found no significant differences among tumors with GGO (groups A, B and C) for prognosis or pathological findings in all the clinical stages. The prognoses of groups A, B and C were significantly better than that of group D for patients with clinical stages IA2-IB disease. Tumors without GGO on CT had a significantly larger number of positive N, ly, v and STAS in almost all stages than tumors with GGO on CT. Tumors without GGO on CT had significantly more solid predominant and less lepidic predominant adenocarcinoma.

CONCLUSION

Not the proportion of GGO, but its presence on CT, as well as the size of the solid component, were correlated significantly with pathological characteristics and survival.

Anatomical Pulmonary Sublobar Resection Based on Subsegment

The traditional segmentectomy involves each segment as the least surgical unit to preserve more pulmonary parenchyma than lobectomy, which is also excessive for small ground glass opacity-dominated lung cancer. We report a novel technique of sublobar resection based on subsegment. Under the guidance of three-dimensional computed tomography bronchography and angiography, the nodules were classified according to their subsegmental location and removed by individual sublobar resection. That assists in removing malignant nodules with safe margins and preserves more pulmonary parenchyma. However, the oncologic efficacy and pulmonary function protection warrant follow-up.

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.

WITHDRAWN: Dynamic Observation of Postoperative Infection and Neuron-specific Enolase Levels in Serum in Patients with Non-small Cell Lung Cancer According to Positron Emission Tomography-Computed Tomography

This article has been withdrawn at the request of the Editor-in-Chief. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal.

Sub-solid lung adenocarcinoma in Asian versus Caucasian patients: different biology but similar outcomes

Background

Asian and Caucasian patients with lung cancer have been compared in several database studies, with conflicting findings regarding survival. However, these studies did not include proportion of ground-glass opacity or mutational status in their analyses. Asian patients commonly develop sub-solid lung adenocarcinomas that harbor EGFR mutations, which have a better prognosis. We hypothesized that among patients undergoing surgery for sub-solid lung adenocarcinomas, Asian patients have better survival compared to Caucasian patients.

Methods

We identified Asian and Caucasian patients who underwent surgical resection for a sub-solid lung adenocarcinoma from 2002 to 2015 at our institution. Sub-solid was defined as ≥10% ground-glass opacity on preoperative CT scan or ≥10% lepidic component on surgical pathology. Time-to-event multivariable analysis was performed to determine which characteristics were associated with recurrence and survival.

Results

Two hundred twenty-four patients were included with median follow up 48 months. Asian patients were more likely to be never smokers (76.3% vs. 29.0%, P<0.01) and have an EGFR mutation (69.4% vs. 25.6% of those tested, P<0.01), while Caucasian patients were more likely to have a KRAS mutation (23.5% vs. 4.9% of those tested, P<0.01). There was a trend towards Asian patients having a higher proportion of ground-glass opacity (38.8% vs. 30.5%, P=0.11). Time-to-event multivariable analysis showed that higher proportion of ground-glass opacity was significantly associated with better recurrence-free survival (HR 0.76 per 20% increase, P=0.02). However, mutational status and race did not have a significant impact on recurrence-free or overall survival.

Conclusions

Asian and Caucasian patients with sub-solid lung adenocarcinoma have different tumor biology, but recurrence-free and overall survival after surgical resection is similar.

[Computed tomography findings, clinicopathological features, genetic characteristics and prognosis of in situ and minimally invasive lung adenocarcinomas]

OBJECTIVE

To investigate the computed tomography findings, clinicopathological features, genetic characteristics and prognosis of in situ adenocarcinoma (AIS) and minimally invasive adenocarcinoma (MIA) of the lung.

METHODS

We retrospectively analyzed the data including computed tomography (CT) images, histopathological findings, Ki-67 immunostaining, and genetic mutations in patients with lung adenocarcinoma undergoing surgery at our hospital between 2014 and 2019.

RESULTS

Of the total of 480 patients with lung adenocarcinoma we reviewed, 73 (15.2%) had AIS (n=28) or MIA (n=45) tumors. The age of the patients with MIA was significantly younger than that of patients with AIS (P &lt; 0.02). CT scans identified pure ground-glass nodules in 46.4% of AIS cases and in 44.4% of MIA cases. Multiple GGOs were more common in MIA than in AIS cases (P &lt; 0.05), and bluured tumor margins was less frequent in AIS cases (P &lt; 0.05). No significant difference was found in EGFR mutations between MIA and AIS cases. A Ki-67 labeling index (LI) value ≥2.8% did not differentiate MIA from AIS. The follow-up time in MIA group was significantly shorter than that in AIS group, but no recurrence or death occurred.

CONCLUSIONS

Despite similar surgical outcomes and favorable survival outcomes, the patients with AIS and MIA show differences in terms of age, CT findings, EGFR mutations and Ki-67 LI.