What CT characteristics of lepidic predominant pattern lung adenocarcinomas correlate with invasiveness on pathology?

CTR > 0.7 predicts the subgroup of lung adenocarcinomas ≤ 2 cm at risk of poor outcome treated by sublobar resection compared to lobar resection

BACKGROUND

A standard surgical procedure for patients with small early-stage lung adenocarcinomas remains unknown. Hence, we aim in this study to assess the clinical utility of the consolidation-to-tumor ratio (CTR) when treating patients with small (2 cm) early stage lung cancers.

METHODS

A retrospective cohort of 298 sublobar resection and 266 lobar resection recipients for early stage lung adenocarcinoma ≤ 2 cm was assembled from the First Affiliated Hospital of Chongqing Medical University between 2016 and 2019. To compare survival rates among the different groups, Kaplan-Meier curves were calculated, and the log-rank test was used. A multivariate Cox proportional hazard model was constructed utilizing variables that were significant in univariate analysis of survival.

RESULTS

In the study, 564 patients were included, with 298 patients (52.8%) undergoing sublobar resection and 266 patients (47.2%) undergoing lobar resection. Regarding survival results, there was no significant difference in the 5-year overall survival (OS, P = 0.674) and 5-year recurrence-free survival (RFS, P = 0.253) between the two groups. Cox regression analyses showed that CTR ≥ 0.75(P < 0.001), age > 56 years (P = 0.007), and sublobar resection(P = 0.001) could predict worse survival. After examining survival results based on CTR categorization, we segmented the individuals into three categories: CTR<0.7, 0.7 ≤ CTR<1, and CTR = 1.The lobar resection groups had more favorable clinical outcomes than the sublobar resection groups in both the 0.7 ≤ CTR < 1(RFS: P < 0.001, OS: P = 0.001) and CTR = 1(RFS: P = 0.001, OS: P = 0.125). However, for patients with 0 ≤ CTR < 0.7, no difference in either RFS or OS was found between the lobar resection and sublobar resection groups, all of which had no positive events. Patients with a CTR between 0.7 and 1 who underwent lobar resection had similar 5-year RFS and OS rates compared to those with a CTR between 0 and 0.7 who underwent sublobar resection (100% vs. 100%). Nevertheless, a CTR of 1 following lobar resection resulted in notably reduced RFS and OS when compared to a CTR between 0.7 and 1 following lobar resection (P = 0.005 and P = 0.016, respectively).

CONCLUSION

Lobar resection is associated with better long-term survival outcomes than sublobar resection for small lung adenocarcinomas ≤ 2 cm and CTR ≥ 0.7.

The Prognostic Impact of Epidermal Growth Factor Receptor Mutation in Clinical Stage I Lung Adenocarcinoma

BACKGROUND

This study investigated the prognostic impact of epidermal growth factor receptor (EGFR) mutation in clinical stage I lung adenocarcinoma patients.

METHODS

Data for 952 patients who received surgical resection and underwent detection of oncogenic driver mutations were retrospectively collected. Recurrence-free survival (RFS) and overall survival (OS) were estimated by the Kaplan-Meier method and compared using the log-rank test. The adjusted hazard ratio (aHR) with 95% CI of the prognosticator was calculated by Cox proportional hazards model, and cumulative incidence function was measured by competing risk regression model.

RESULTS

EGFR mutation was detected in 581 patients (61.0%) and was more frequent in women (63.9%), nonsmokers (85.5%), and those with ground-glass nodules (GGNs; 56.6%). EGFR mutation was not associated with recurrence and death in the entire cohort or GGN cohort. However, for patients with radiologic pure-solid appearance, EGFR mutation was an independent risk factor for RFS (aHR, 1.623; 95% CI, 1.192-2.210) and distant recurrence (aHR, 1.863; 95% CI, 1.311-2.650), but not OS. Subsequently, subgroup analysis based on EGFR mutation subtypes, including exon 19 deletions (19-Del), exon 21 L858R substitution (L858R), and rare mutations in patients with radiologic pure-solid appearance, revealed that all 3 subtypes have poorer RFS (19-Del: aHR, 1.424; 95% CI, 0.991-2.047; L858R: aHR, 1.708; 95% CI, 1.172-2.490; rare mutations: aHR, 2.500; 95% CI, 1.400-4.465) and higher prevalent distant recurrence (19-Del: aHR, 1.595; 95% CI, 1.061-2.400; L858R: aHR, 2.073; 95% CI, 1.371-3.140; rare mutations: aHR, 2.657; 95% CI, 1.397-5.050) compared with wild-type.

CONCLUSIONS

In clinical stage I lung adenocarcinoma, EGFR mutation was associated with worse RFS and higher prevalent distant recurrence in patients with radiologic pure-solid appearance but not in patients with GGN.

Intratumoural and peritumoural CT-based radiomics for diagnosing lepidic-predominant adenocarcinoma in patients with pure ground-glass nodules: a machine learning approach

AIM

To develop and validate a diagnostic model utilising machine-learning algorithms that differentiates lepidic predominant adenocarcinoma (LPA) from other pathological subtypes in patients with pure ground-glass nodules (pGGNs).

MATERIALS AND METHODS

This bicentric study was conducted across two medical centres and included 151 patients diagnosed with lung adenocarcinoma based on histopathological confirmation of pGGNs. The training cohort consisted of 99 patients from Institution 1, while the test cohort included 52 patients from Institution 2. Radiomics features were extracted from both tumours and the 2 mm peritumoural parenchyma. The tumoural and peritumoural radiomics were designated as Modeltumoural and Modelperitumoural, respectively. The diagnostic efficacy of various models was evaluated through the receiver operating characteristic (ROC) curve analysis. Subsequently, a machine-learning-based prediction model that combined Modeltumoural, Modelperitumoural, and Modelclinical-radiological was developed to differentiate LPA from other pathological subtypes in patients with pGGNs.

RESULTS

Modeltumoural achieved area under the curve (AUC) values of 0.762 and 0.783 in the training and validation sets, respectively. Modelperitumoural attained AUCs of 0.742 and 0.667, and Modelclinical-radiological generated an AUC of 0.727 and 0.739 in the training and validation sets, respectively. Among the machine-learning models evaluated, gradient boosting machines demonstrated the best diagnostic efficacy, with accuracy, AUC, F1 score, and log loss values of 0.885, 0.956, 0.943, and 0.260, respectively.

CONCLUSION

The combined model based on machine learning that incorporated tumour and peritumoural parenchyma, as well as clinical and imaging characteristics, may offer benefits in assessing the pathological subtype of pGGNs.

Detection of early (T1) lung cancers and lepidic adenocarcinomas in sputum and bronchial cytology

BACKGROUND

The lung is an extensively epithelialized organ, producing ample exfoliated material for sputum and bronchial cytology. In view of the updates in the World Health Organization classification of early (T1/≤ 3 cm) lung cancer with respect to adenocarcinomas with lepidic pattern, this study retrospectively reviews sputum and bronchial cytology paired with resection-confirmed lung cancers.

METHODS

A computerized search for all lung resection specimens of carcinomas over a 20-year period was performed. Cytologic diagnoses of corresponding sputum and bronchial cytology were classified into five-tiered categories (C1-insufficient/inadequate, C2-benign, C3-atypia, C4-suspicious and C5-malignant). Reports and slides of the resection specimen were reviewed for reclassification of T1 cancers.

RESULTS

Totally 472 and 383 sputum and bronchial cytology specimens respectively were included. Sensitivity for T1 lesions on sputum cytology were 10.6 %, 2.1 % and 0.5 % at cutoffs of atypia/C3, suspicious/C4 and malignant/C5 categories, lower than bronchial cytology (35.1 %, 15.5 %, 8.1 %; p < 0.001). T1 lesions correlated with lower detection rates, whereas squamous cell carcinoma histology, larger size and bronchial invasion were associated with increased detection rates in sputum and bronchial cytology (p < 0.050). Detection rates for abrasive bronchial cytology (brushing) were overall higher (p = 0.018- < 0.001), but on subgroup comparison, non-abrasive (aspiration, lavage and washing) cytology demonstrated favorable trends (p = 0.063-0.088) in detecting T1 lesions. Adenocarcinomas with lepidic pattern had lower suspicious/C4 (p = 0.040) or above and malignant/C5 (p = 0.019), but not atypia/C3 or above (p = 0.517) rates.

CONCLUSIONS

Most adenocarcinomas with lepidic pattern are only diagnosed as atypia/C3 on cytology. With its modest sensitivity, interpretation of negative and indeterminate cytology results mandates caution.

Growth characteristics of early-stage (IA) lung adenocarcinoma and its value in predicting lymph node metastasis

BACKGROUND

We aim to compare the differences in growth characteristics between part-solid and solid lung adenocarcinoma, and to investigate the value of volume doubling time (VDT) or mass doubling time (MDT) in predicting lymph node (LN) metastasis and preoperative evaluation in patients of early-stage (IA) non-small cell lung cancer (NSCLC).

METHOD

We reviewed 8,653 cases of surgically resected stage IA lung adenocarcinoma between 2018 and 2022, with two follow-up visits at least 3 months apart, comparing diameter, volume, and mass growth of pSN and SN. VDT and MDT calculations for nodules with a volume change of at least 25%. Univariable or multivariable analysis was used to identify the risk factors. The area under the curve (AUC) for the receiver operating characteristic (ROC) curves was used to evaluate the diagnostic value.

RESULTS

A total of 144 patients were included 114 with solid nodules (SN) and 25 with part-solid nodules (pSN). During the follow-up period, the mean VDTt and MDTt of SN were shorter than those of pSN, 337 vs. 541 days (p = 0.005), 298 vs. 458 days (p = 0.018), respectively. Without considering the ground-glass component, the mean VDTc and MDTc of SN were shorter than the solid component of pSN, 337 vs. 498 days (p = 0.004) and 298 vs. 453 days (p = 0.003), respectively. 27 nodules were clinically and pathologically diagnosed as N1/N2. Logistic regression identified initial diameter (p < 0.001), consolidation increase (p = 0.019), volume increase (p = 0.020), mass increase (p = 0.021), VDTt (p = 0.002), and MDTt (p = 0.004) were independent factors for LN metastasis. The ROC curves showed that the AUC for VDTt was 0.860 (95% CI, 0.778-0.943; p < 0.001) and for MDTt was 0.848 (95% CI, 0.759-0.936; p < 0.001).

CONCLUSIONS

Our study showed significant differences in the growth characteristics of pSN and SN, and the application of VDT and MDT could be a valid predictor LN metastasis in patients with early-stage NSCLC.

Lepidic growth component as a favorable prognostic factor in non-small cell lung cancer of ≤3 cm

BACKGROUND

Many non-small cell lung cancer (NSCLC) tumors present complex histology with various components. The effects of the lepidic growth component (LGC) on the prognosis of NSCLC have not been investigated. Here, we investigated whether an LGC is a relevant prognostic factor for NSCLC.

METHODS

This study retrospectively investigated the clinicopathologic characteristics of 379 patients with NSCLC ≤3 cm who underwent complete surgical resection between 2004 and 2016 at the University of Yamanashi Hospital. The histologic subtypes were classified into NSCLC with or without an LGC. We evaluated the effect of an LGC on the clinicopathologic features and 5-year overall survival of patients with NSCLC.

RESULTS

On final pathology, 214 (56%) of 379 patients had an LGC, and 165 (44%) did not. Sex, smoking history, ground-glass opacity component, pathologic invasive size, lymph node metastasis, pleural invasion, vessel invasion, pathologic stage, and histologic type were significantly different between the groups. Multivariate analysis of 5-year overall survival, identified age (hazard ratio [HR], 1.07; 95% confidence interval [CI], 1.035-1.105; p < 0.001), pathologic invasive size (HR, 1.548; 95% CI, 1.088-2.202; p = 0.015) and LGC (HR, 2.11; 95% CI, 1.099-4.051; p = 0.025) as independent prognostic factors. When the pathologic invasive size was matched, the 5-year overall survival of the LGC and non-LGC groups was 93% and 77%, respectively (p = 0.006).

CONCLUSIONS

LGC is a significantly favorable prognostic factor for NSCLC with a pathologic invasive size of ≤3 cm.

Establishment of a malignancy and benignancy prediction model of sub-centimeter pulmonary ground-glass nodules based on the inflammation-cancer transformation theory

Background

In recent years, Chinese clinicians are frequently encountered by patients with multiple lung nodules and these intensity ground-glass nodules (GGNs) are usually small in size and some of them have no spicule sign. In addition, early lung cancer is diagnosed in large numbers of non-heavy smokers and individuals with no caner history. Obviously, the Mayo model is not applicable to these patients. The aim of the present study is to develop a new and more applicable model that can predict malignancy or benignancy of pulmonary GGNs based on the inflammation-cancer transformation theory.

Materials and methods

Included in this study were patients who underwent surgical resection or lung puncture biopsy of GGNs in Shanghai 10th People’s Hospital between January 1, 2018 and May 31, 2021 with the inclusion criterion of the maximum diameter of GGN < 1.0 cm. All the included patients had their pulmonary GGNs diagnosed by postoperative pathology. The patient data were analyzed to establish a prediction model and the predictive value of the model was verified.

Results

Altogether 100 GGN patients who met the inclusion criteria were included for analysis. Based on the results of logistic stepwise regression analysis, a mathematical predication equation was established to calculate the malignancy probability as follows: Malignancy probability rate (p) = ex/(1 + ex); p > 0.5 was considered as malignant and p ≤ 0.5 as benign, where x = 0.9650 + [0.1791 × T helper (Th) cell] + [0.2921 × mixed GGN (mGGN)] + (0.4909 × vascular convergence sign) + (0.1058 × chronic inflammation). According to this prediction model, the positive prediction rate was 73.3% and the negative prediction rate was 100% versus the positive prediction rate of 0% for the Mayo model.

Conclusion

By focusing on four major factors (chronic inflammation history, human Th cell, imaging vascular convergence sign and mGGNs), the present prediction model greatly improves the accuracy of malignancy or benignancy prediction of sub-centimeter pulmonary GGNs. This is a breakthrough innovation in this field.

Consolidation radiographic morphology can be an indicator of the pathological basis and prognosis of partially solid nodules

Background

Part-solid nodules (PSNs) have gradually shifted to defining special clinical subtypes. Commonly, the solid portions of PSNs show various radiological morphologies, of which the corresponding pathological basis and prognosis are unclear. We conducted a radiological–pathological evaluation to determine the histopathologic basis of different consolidation radiographic morphologies related to prognosis.

Materials and methods

A cohort of 275 patients with a surgical pathological diagnosis of lung adenocarcinoma were enrolled. Preoperative computed tomography (CT) images of the PSNs were recorded and assessed. A panel of 103 patients with complete pathological specimens was selected to examine the radiological–pathological associations, and follow-up was performed to identify the prognosis.

Results

Of the 275 patients, punctate consolidation was observed radiologically in 43/275 (15.7%), stripe consolidation in 68/275 (24.7%), and irregular consolidation in 164/275 (59.6%) patients. The radiological morphology of the solid components was significantly associated with the histopathological subtypes (P < 0.001). Visual punctate solid components on CT correlated with tertiary lymphoid structures, stripe solid components on CT correlated with fibrotic scar, and irregular solid components on CT correlated with invasion. PSNs with regular consolidation had a better prognosis than those with irregular consolidation.

Conclusion

Radiological morphology of solid components in PSNs can indicate the pathological basis and is valuable for prognosis. In particular, irregular solid components in PSNs usually indicate serious invasive growth, which should be taken with caution during assessment.

Characteristics and Prognostic Nomogram for Primary Lung Lepidic Adenocarcinoma

Background

Lepidic adenocarcinoma (LPA) is an infrequent subtype of invasive pulmonary adenocarcinoma (ADC). However, the clinicopathological features and prognostic factors of LPA have not been elucidated.

Methods

Data from the Surveillance, Epidemiology, and End Results (SEER) database of 4191 LPA patients were retrospectively analyzed and compared with non-LPA pulmonary ADC to explore the clinicopathological and prognosis features of LPA. Univariate and multivariate Cox proportional hazard models were performed to identify independent survival predictors for further nomogram development. The nomograms were validated using the concordance index, receiver operating characteristic curves, and calibration plots, as well as decision curve analysis, in both the training and validation cohorts.

Results

Compared with non-LPA pulmonary ADC patients, those with LPA exhibited unique clinicopathological features, including more elderly and female patients, smaller tumor size, less pleural invasion, and lower histological grade and stage. Multivariate analyses showed that age, sex, race, tumor location, primary tumor size, pleural invasion, histological grade, stage, primary tumor surgery, and chemotherapy were independently associated with overall survival (OS) and cancer-specific survival (CSS) in patients with LPA. The nomograms showed good accuracy compared with the actual observed results and demonstrated improved prognostic capacity compared with the TNM stage.

Conclusions

LPA is more frequently diagnosed in older people and women. LPA was inclined to be smaller in tumor size and lower in tumor grade and staging, which may indicate a favorable prognosis. The constructed nomograms accurately predict the long-term survival of LPA patients.

Relationship between consolidation tumor ratio and tumor-infiltrating lymphocytes in small-sized lung adenocarcinoma

Background

Consolidation tumor ratio (CTR) is associated with cancer progression and histological invasiveness in lung adenocarcinoma (LAD). However, little is known about the association between CTR and immune‐related factors, including tumor‐infiltrating lymphocytes (TILs) density or tumor expression of programmed death ligand 1 (PD‐L1) and indoleamine 2,3‐dioxygenase 1 (IDO1) in small‐sized LAD.

Methods

This study included 258 patients with LAD (<3 cm) who underwent surgery. Patients were assigned to four groups: CTR = 0; 0 < CTR <0.5; 0.5 ≤ CTR <1 (ground‐glass opacity [GGO] group); and CTR = 1 (pure‐solid group). CD4⁺, CD8⁺, and FoxP3⁺ TIL density and PD‐L1 and IDO1 tumor expression were assessed by immunohistochemistry.

Results

Among the GGO group, CD8⁺ and FoxP3⁺ TIL density increased significantly with increasing CTR (p < 0.001 and p < 0.001, respectively). Moreover, PD‐L1 and IDO1 expression was significantly higher in the pure‐solid group than in the GGO group (p < 0.001 and p < 0.001, respectively).

Conclusions

CTR was correlated with the abundance of CD8⁺ and FoxP3⁺ TILs in the GGO group. PD‐L1 and IDO1 positivity rates were significantly higher in the pure‐solid group than in the GGO group. Increased CTR may be correlated with immunosuppressive condition.

Three-Dimensional Convolutional Neural Network-Based Prediction of Epidermal Growth Factor Receptor Expression Status in Patients With Non-Small Cell Lung Cancer

Objectives

EGFR testing is a mandatory step before targeted therapy for non-small cell lung cancer patients. Combining some quantifiable features to establish a predictive model of EGFR expression status, break the limitations of tissue biopsy.

Materials and Methods

We retrospectively analyzed 1074 patients of non-small cell lung cancer with complete reports of EGFR gene testing. Then manually segmented VOI, captured the clinicopathological features, analyzed traditional radiology features, and extracted radiomic, and deep learning features. The cases were randomly divided into training and test set. We carried out feature screening; then applied the light GBM algorithm, Resnet-101 algorithm, logistic regression to develop sole models, and fused models to predict EGFR mutation conditions. The efficiency of models was evaluated by ROC and PRC curves.

Results

We successfully established Model_clinical, Model_radiomic, Model_CNN (based on clinical-radiology, radiomic and deep learning features respectively), Model_{radiomic+clinical} (combining clinical-radiology and radiomic features), and Model_{CNN+radiomic+clinical} (combining clinical-radiology, radiomic, and deep learning features). Among the prediction models, Model_{CNN+radiomic+clinical} showed the highest performance, followed by Model_CNN, and then Model_{radiomic+clinical}. All three models were able to accurately predict EGFR mutation with AUC values of 0.751, 0.738, and 0.684, respectively. There was no significant difference in the AUC values between Model_{CNN+radiomic+clinical} and Model_CNN. Further analysis showed that Model_{CNN+radiomic+clinical} effectively improved the efficacy of Model_{radiomic+clinical} and showed better efficacy than Model_CNN. The inclusion of clinical-radiology features did not effectively improve the efficacy of Model_radiomic.

Conclusions

Either deep learning or radiomic signature-based models can provide a fairly accurate non-invasive prediction of EGFR expression status. The model combined both features effectively enhanced the performance of radiomic models and provided marginal enhancement to deep learning models. Collectively, fusion models offer a novel and more reliable way of providing the efficacy of currently developed prediction models, and have far-reaching potential for the optimization of noninvasive EGFR mutation status prediction methods.

Latest Clinical Evidence and Operative Strategy for Small-Sized Lung Cancers

Many thoracic surgeons revealed that consolidation tumor ratio or solid component size on thin-section computed tomography has been considered more prognostic than maximum tumor size in non-small cell lung cancer (NCSLC). According to the results, the 8th TNM classification drastically changed the staging system, i.e., clinical T category was determined based on the invasive or solid component size excluding a ground-glass opacity (GGO). However, several debates are arising over the application of radiological solid size for the clinical T staging. Meanwhile, recent several institutional reports have noticed a significantly simple fact that the presence of a GGO denotes an influence on the favorable prognosis of NSCLC. More important, radiologic pure-solid lung cancers without a GGO exhibit more malignant behaviors with regard to both the clinical and pathological aspects, and show several histologic types that have a poorer prognosis than radiologic part-solid lung cancer. In contrast, favorable prognostic impact of the presence of a GGO component was demonstrated, which was irrespective of the solid component size in cases in which the tumor showed a GGO component. Recently, this concept has been gradually noticed on a nationwide level. Obvious distinctions regarding the several baseline characteristics between the tumor with/without GGO component is a fundamental biological feature of early-stage lung cancer, which would result in a big difference in prognosis, modes of recurrence, overall behavior, and appropriate operative strategies. As a future perspective, the presence or absence of a GGO should be considered as an important parameter in the next clinical T classification.

Investigating the association between ground-glass nodules glucose metabolism and the invasive growth pattern of early lung adenocarcinoma

Background

To explore the association between the glucose metabolism level of lung ground-glass nodules (GGNs), as revealed by ¹⁸F-flurodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) imaging, and the invasive pathological growth pattern of early lung adenocarcinoma.

Methods

We retrospectively analyzed patients who underwent PET/CT examination and surgical resection due to persistent GGNs, which were confirmed to be early lung adenocarcinoma by postoperative pathology examination. After adjusting for confounding factors and performing stratified analysis, we explored the association between the maximum standard uptake value of PET (SUVmax) and the invasive pathological growth pattern of early stage lung adenocarcinoma.

Results

The proportions of invasive adenocarcinoma (INV) in the SUVmax of Tertile 1, Tertile 2, and Tertile 3 were 52.7%, 73.3%, and 87.1%, respectively. After adjusting for potential confounding factors, the risk of INV gradually increased as the GGN SUVmax increased [odds ratio (OR): 1.520, 95% confidence interval (CI): 1.044-2.213, P=0.029]. This trend was statistically significant (OR: 1.678, 95% CI: 1.064-2.647, P=0.026), especially in Tertile 3 vs. Tertile 1 (OR: 4.879, 95% CI: 1.349-17.648, P=0.016). Curve fitting showed that the SUVmax and INV risk were linearly and positively associated. The association was consistent in different subgroups based on GGN number, type, shape, edge, bronchial sign, vacuole sign, pleural depression sign, diameters, and consolidation-to-tumor ratio, suggesting that there was no significant interaction between different grouping parameters and the association (P for interaction range = 0.129-0.909).

Conclusions

In FDG PET, the glucose metabolism level (SUVmax) of lung GGNs is independently associated with INV risk, and this association is linear and positive.

Subsolid Lung Adenocarcinomas: Radiological, Clinical and Pathological Features and Outcomes

Lung adenocarcinomas manifesting as subsolid nodules usually have a favorable prognosis. This study aimed to have a comprehensive investigation of the radiological and clinicopathologic features and oncological outcomes of subsolid nodules. Between March 2010 and December 2015, 865 patients with surgically resected clinical IA subsolid lung adenocarcinoma were retrospectively reviewed. Patients were classified into the pure ground-glass nodules (GGN) (pGGN [n = 358], without solid component on lung and mediastinal windows), heterogeneous GGN (hGGN [n = 65], only with solid components on lung window), and real part-solid nodule (rPSN [n = 442], with solid component on both lung and mediastinal windows) groups. The clinicopathological features and survival time of the three groups were compared between groups. There was a significant increase in median tumor size (P < 0.001), solid component size measured at lung window (LW-SCS) (P < 0.001), and the proportion of invasive adenocarcinoma subtypes (P < 0.001) from pGGNs to hGGNs to rPSNs. After adjustment for LW-SCS, adenocarcinomas with predominant lepidic patterns were still more common in hGGNs than in rPSNs (P = 0.009). Patients with rPSNs had a significantly worse recurrence-free survival (RFS) than those with pGGNs and hGGNs (5-year: 91.9% versus 100% versus 100%, P < 0.001). Multivariate Cox analyses revealed that gender (both P < 0.05) and clinical T category (based on lung window [LW-cT] [P = 0.002] or mediastinal window [MW-cT] [P < 0.001]) were independent prognostic factors of RFS in the rPSN group. HGGNs represented as an intermediate subtype between pGGNs and rPSNs. Both pGGNs and hGGNs had excellent outcomes, while rPSNs exhibited a worse prognosis than them. Clinical T category and gender had prognostic implications for rPSNs.

Clinical impact of a small component of ground-glass opacity in solid-dominant clinical stage IA non-small cell lung cancer

OBJECTIVE

Non-small cell lung cancers with a ground-glass opacity component have better prognosis than those with solid nodules of equivalent consolidation size. However, the impact of small ground-glass opacity components on prognosis is unknown. Therefore, we aimed to evaluate the significance of a small ground-glass opacity component in solid-dominant clinical stage IA non-small cell lung cancers.

METHODS

We reviewed the cases of 543 surgically resected solid-dominant c-stage IA non-small cell lung cancers, which was defined as a tumor with consolidation tumor ratio of 0.75 or more on computed tomography. The patients were classified into 2 groups: 0.75 or less consolidation tumor ratio less than 1 (n = 126) and consolidation tumor ratio of 1 (n = 417). The prognoses were compared between the 2 groups.

RESULTS

Among the 543 cases, multivariable analyses revealed that pure-solid appearance was a predictor of worse overall survival (hazard ratio, 2.051; 95% confidence interval, 1.044-4.028). Compared with the part-solid group, the pure-solid group was associated with poor survival in c-stages IA2 (5-year overall survival: 91.5% vs 76.8%, hazard ratio, 2.942; 95% confidence interval, 1.402-6.173; recurrence-free survival: 89.0% vs 68.8%, hazard ratio, 3.439; 95% confidence interval, 1.776-6.669) and IA3 (5-year overall survival: 93.5% vs 63.0%, hazard ratio, 5.110; 95% confidence interval, 1.607-16.241; recurrence-free survival: 80.5% vs 54.1%, hazard ratio, 2.789; 95% confidence interval, 1.290-6.027). The T categories significantly affected 5-year overall survival only in the pure-solid group (cT1a, 89.3%; cT1b, 76.8%; cT1c, 63.0%).

CONCLUSIONS

A small ground-glass opacity component has an impact on the prognosis of patients with solid-dominant c-stage IA non-small cell lung cancer. Therefore, c-stage IA non-small cell lung cancers should be evaluated separately for tumors with ground-glass opacity and pure-solid tumors.

Predicting malignancy: subsolid nodules detected on LDCT in a surgical cohort of East Asian patients

Background

Due to widespread use of low-dose computed tomography (LDCT) screening, increasing number of patients are found to have subsolid nodules (SSNs). The management of SSNs is a clinical challenge and primarily depends on CT imaging. We seek to identify risk factors that may help clinicians determine an optimal course of management.

Methods

We retrospectively reviewed the characteristics of 83 SSN lesions, including 48 pure ground-glass nodules and 35 part-solid nodules, collected from 83 patients who underwent surgical resection.

Results

Of the 83 SSNs, 16 (19.28%) were benign and 67 (80.72%) were malignant, including 23 adenocarcinomas in situ (AIS), 16 minimally invasive adenocarcinomas (MIA), and 28 invasive adenocarcinomas (IA). Malignant lesions were found to have significantly larger diameters (P<0.05) with an optimal cut-off point of 9.24 mm. Significant indicators of malignancy include female sex (P<0.05), air bronchograms (P<0.001), spiculation (P<0.05), pleural tail sign (P<0.05), and lobulation (P<0.05). When compared with AIS/MIA combined, IA lesions were found to be larger (P<0.05) with an optimal cut-off of 12 mm, and have a higher percentage of part-solid nodules (P<0.001), pleural tail sign (P<0.001), air bronchograms (P<0.05), and lobulation (P<0.05). Further multivariate analysis found that lesion size and spiculation were independent factors for malignancy while part-solid nodules were associated with IA histology.

Conclusions

East Asian females are at risk of presenting with a malignant lesion even without history of heavy smoking or old age. Nodule features associated with malignancy include larger size, air bronchograms, lobulation, pleural tail sign, spiculation, and solid components. A combination of patient characteristic and LDCT features can be effectively used to guide management of patients with SSNs.

New revisions and current issues in the eighth edition of the TNM classification for non-small cell lung cancer

In the eighth edition of the TNM classification of lung cancer, the prognostic impact of tumor size is emphasized as a descriptor of all T categories. Especially in lung cancer where tumor size is 5 cm or less, the 1-cm cutoff point significantly differentiated the survival outcome. In addition, the new staging categories were assigned, namely, Tis (adenocarcinoma in situ) and T1mi (minimally invasive adenocarcinoma). Furthermore, the measurement of a radiological solid component size excluding the ground glass opacity component or pathological invasive size without a lepidic component was proposed for deciding the cT/pT categories for lung adenocarcinoma. The N descriptors were kept the same as in the eventh edition on the whole, however, quantification of nodal disease had a prognostic impact based on the number of nodal stations involved in the eighth edition, i.e. N1a as a single N1 station, N1b as a multiple N1 station, N2a1 as a single N2 station without N1 (skip metastasis), N2a2 as a single N2 station with N1 disease, and N2b as a multiple N2 station. In the M descriptors, subclassification was performed based on the location or numbers of distantly metastatic lesions, i.e. M1a as any intrathoracic metastases, M1b as a single distant metastatic lesion in one organ, and M1c as multiple distant metastases in either a single organ or multiple organs. Survival analysis of the eighth edition of the TNM classification clearly separated the distinct groups, however, unsolved issues still remain that should be discussed and further revised for the forthcoming TNM staging system.

Gross handling of pulmonary resection specimen: maintaining the 3-dimensional orientation

There is limited literature on the gross handling of lung resection specimens. Microscopic examination of the specimen, TNM staging and predictive biomarker testing are fully dependent on an adequate gross handling. In this paper, we present a 3-dimensional (3D) grossing method of oncological lung resection specimens, which ensures proper fixation of the tumor tissue, but also enables accurate correlation with the pre-surgical imaging.

Invasive Pulmonary Adenocarcinoma with Lepidic Growth Pattern in a Pregnant Patient

Among the differential diagnoses that should be considered in acute respiratory failure (ARF) are infectious processes, autoimmune diseases, interstitial pulmonary fibrosis, and pulmonary neoplasia. Timely diagnosis of lung neoplasia is complicated in the early stages. An opportune diagnosis, as well as the specific treatment, decrease mortality. ARF occurs 1 in 500 pregnancies and is most common during the postpartum period. Among the specific etiologies that cause ARF during pregnancy that must be considered are: (1) preeclampsia; (2) embolism of amniotic fluid; (3) peripartum cardiomyopathy; and (4) trophoblastic embolism. The case of a 36-year-old patient with a 33-week pregnancy and ARF is presented. The patient presented dyspnea while exerting moderate effort that progressed to orthopnea and type 1 respiratory insufficiency. Imaging studies showed bilateral alveolar infiltrates and predominantly right areas of consolidation. Blood cultures, a galactomannan assay and IgG antibodies against mycoplasma pneumoniae, were reported as negative. Autoimmune etiology was ruled out through an immunoassay. A percutaneous pulmonary biopsy was performed and an invasive pulmonary adenocarcinoma with lepidic growth pattern (i.e. lepidic pulmonary adenocarcinoma, LPA) result was reported. This etiology is rare and very difficult to recognize in acute respiratory failure cases. After infectious, autoimmune and interstitial lung fibrosis have been excluded the clinician must suspect of lung cancer in a patient with acute respiratory failure and chest imaging compatible with the presence of ground-glass nodular opacities, a solitary nodule or mass with bronchogram, and lung consolidation. In the presence of acute respiratory failure, the suspicion of pulmonary neoplasia in an adult of reproductive age must be timely. Failure to recognize this etiology can lead to fatal results.