Survival with Parenchymal and Pleural Invasion of Non-Small Cell Lung Cancers Less than 30 mm

Mechanisms of Astragalus membranaceus (Fisch.) Bge. var. mongholicus (Bge.) Hsiao (huang qi) and Angelica sinensis (Oliv.) Diels (dang gui) in Ameliorating Hypoxia and Angiogenesis to Delay Pulmonary Nodule Malignant Transformation

Screening for pulmonary nodules (PN) using low-dose CT has proven effective in reducing lung cancer (LC) mortality. However, current treatments relying on follow-up and surgical excision fail to fully address clinical needs. Pathological angiogenesis plays a pivotal role in supplying oxygen necessary for the progression of PN to LC. The interplay between hypoxia and angiogenesis establishes a vicious cycle, rendering anti-angiogenesis therapy alone insufficient to prevent PN to LC transformation. In traditional Chinese medicine (TCM), PN is referred to as "Feiji," which is mainly attributed to Qi and blood deficiency, correspondingly, the most commonly prescribed medicines are Astragalus membranaceus (Fisch.) Bge. var. mongholicus (Bge.) Hsiao (huang qi) (AR) and Angelica sinensis (Oliv.) Diels (dang gui) (ARS). Modern pharmacological studies have demonstrated that AR and ARS possess immune-enhancing, anti-tumor, anti-inflammatory, and anti-angiogenic properties. However, the precise mechanisms through which AR and ARS exert anti-angiogenic effects to delay PN progression to LC remain inadequately understood. This review explores the critical roles of hypoxia and angiogenesis in the transition from PN to LC. It emphasizes that, compared to therapies targeting angiogenic growth factors alone, AR, ARS, and their compound-based prescriptions offer additional benefits. These include ameliorating hypoxia by restoring blood composition, enhancing vascular structure, accelerating circulation, promoting vascular normalization, and blocking or inhibiting various pro-angiogenic expressions and receptor interactions. Collectively, these actions inhibit angiogenesis and delay the PN-to-LC transformation. Finally, this review summarizes recent advancements in related research, identifies existing limitations and gaps in knowledge, and proposes potential strategies and recommendations to address these challenges.

CT Predictors of Angiolymphatic Invasion in Non-Small Cell Lung Cancer 30 mm or Smaller

Background Angiolymphatic invasion (ALI) is an important prognostic indicator in non-small cell lung cancer (NSCLC). However, few studies focus on radiologic features for predicting ALI in patients with early-stage NSCLCs 30 mm or smaller. Purpose To identify radiologic features for predicting ALI in NSCLCs 30 mm or smaller in maximum diameter. Materials and Methods This study was a secondary review of pathologic and CT findings from an integrated health care system between January 2016 and November 2023 for participants in the prospective study Initiative for Early Lung Cancer Research on Treatment, or IELCART. Preoperative diagnostic radiologic features possibly related to ALI, volume doubling time (VDT), and PET maximum standardized uptake value were evaluated. Multivariable logistic regression analysis, adjusted for sex, age, nodule size, and smoking status, was used to determine predictors of ALI. Model performance was analyzed with the area under the receiver operating characteristic curve (AUC). Results Of 778 resected NSCLCs 30 mm or smaller (median patient age, 69 years [IQR, 63-76 years]; 458 female patients), 715 (92%) were solid, 41 (5%) were part-solid, and 22 (3%) were nonsolid. ALI was documented in 271 (35%) resected NSCLCs, all in solid NSCLCs, representing 37.9% (95% CI: 34.4, 41.5) of solid NSCLCs. None of the 63 subsolid NSCLCs had ALI (0% [95% CI: 0, 5.75]). For the 715 solid NSCLCs (median patient age, 69 years [IQR, 63-76 years]; 420 female patients), multivariable logistic regression analysis showed that lollipop sign (odds ratio [OR] = 4.12 [95% CI: 2.82, 6.04]; P < .001) and spiculation (OR = 2.05 [95% CI: 1.42, 2.97]; P < .001) were independent predictors of ALI (AUC = 0.77 [95% CI: 0.73, 0.80]). Considering only the 474 patients in whom VDT could be calculated based on CT scans, VDT was also an independent predictor for ALI (OR = 0.96 [95% CI: 0.94, 0.98]; P < .001). Incorporating VDT into the model improved ALI prediction (AUC = 0.82 [95% CI: 0.77, 0.86]; P < .001). Conclusion For patients with NSCLCs 30 mm or smaller, ALI was present in 37.9% of solid NSCLCs and none of the 63 subsolid NSCLCs. Among solid NSCLCs, lollipop sign, spiculation, and VDT were independent radiologic predictors of ALI. © RSNA, 2025 Supplemental material is available for this article. See also the editorial by Czum in this issue.

Peritumoral and intratumoral radiomics for predicting visceral pleural invasion in lung adenocarcinoma based on preoperative computed tomography (CT)

AIM

To evaluate the prediction of peritumoral and intratumoral radiomics for visceral pleural invasion (VPI) in lung adenocarcinoma cancer (LAC) based on preoperative computed tomography (CT) radiomics.

MATERIALS AND METHODS

In total, 350 patients with LAC confirmed by surgery pathology were enrolled in The Second Hospital of Hebei Medical University, including 281 VPI negative patients and 69 VPI positive patients, were divided into the training cohort (n = 280) and validation cohort (n=70) at random with a ratio of 8:2. We extracted the radiomics features from the 3 region of interest (ROI), including gross tumor volume (GTV), the gross peritumoral tumor volume (GPTV) and the gross volume of the tumor rim (included the outer 4 mm of the tumor and 4mm of the tumor adjacent lung tissue on either side of the tumor contour boundary, GTR).The maximal redundancy minimal relevance (mMRM) algorithm and the least absolute shrinkage and selection operator (LASSO) was performed to reduce feature dimensionality and the radiomics score (Rad score) of the best radiomics model was combined with CT morphological characteristics with statistical significance in the univariable analysis to construct the combined model. The performance of the models was evaluated based on receiver operating characteristics (ROC) curve, calibration, and clinical usefulness. DeLong's test was used to assess differences in area under curve (AUC) between different models.

RESULTS

There were no statistically significant differences in patient's gender, age, and BMI between the VPI positive group and VPI negative group (all p＞0.05). There were statistically significant differences in the tumor maximum diameter, tumor CT image type, vacuole sign, and pleural indentation sign between the VPI positive group and VPI negative group (all p < 0.05). The models of radiomics of GTV, GPTV, and GTR showed high predictive value in the training cohort (All AUC > 0.75). Compared with GTV, GTR radiomics models, the GPTV radiomics model constructed via the logistic regression (LR) method exhibited better prediction performance with the AUCs of 0.819, 0.827; accuracy of 0.757,0.743; sensitivity of 0.800,0.786; specificity of 0.747,0.732 in the training and validation cohorts, respectively. The LR model of GPTV radiomics was defined as the optimal model for predicting VPI, since its excellent performance in both ROC, calibration curve and decision curve analysis (DCA).

CONCLUSION

Preoperative CT-based radiomics models can predict VPI in patients with LAC; the LR algorithm combined the GPTV radiomics was the optimal choice, demonstrating high sensitivity, specificity, accuracy and clinical usefulness.

Predicting Lymphovascular Invasion in Non-small Cell Lung Cancer Using Deep Convolutional Neural Networks on Preoperative Chest CT

RATIONALE AND OBJECTIVES

Lymphovascular invasion (LVI) plays a significant role in precise treatments of non-small cell lung cancer (NSCLC). This study aims to build a non-invasive LVI prediction diagnosis model by combining preoperative CT images with deep learning technology.

MATERIALS AND METHODS

This retrospective observational study included a series of consecutive patients who underwent surgical resection for non-small cell lung cancer (NSCLC) and received pathologically confirmed diagnoses. The cohort was randomly divided into a training group comprising 70 % of the patients and a validation group comprising the remaining 30 %. Four distinct deep convolutional neural network (DCNN) prediction models were developed, incorporating different combination of two-dimensional (2D) and three-dimensional (3D) CT imaging features as well as clinical-radiological data. The predictive capabilities of the models were evaluated by receiver operating characteristic curves (AUC) values and confusion matrices. The Delong test was utilized to compare the predictive performance among the different models.

RESULTS

A total of 3034 patients with NSCLC were recruited in this study including 106 LVI+ patients. In the validation cohort, the Dual-head Res2Net_3D23F model achieved the highest AUC of 0.869, closely followed by the models of Dual-head Res2Net_3D3F (AUC, 0.868), Dual-head Res2Net_3D (AUC, 0.867), and EfficientNet-B0_2D (AUC, 0.857). There was no significant difference observed in the performance of the EfficientNet-B0_2D model when compared to the Dual-head Res2Net_3D3F and Dual-head Res2Net_3D23F.

CONCLUSION

Findings of this study suggest that utilizing deep convolutional neural network is a feasible approach for predicting pathological LVI in patients with NSCLC.

Diagnostic performance and prognostic value of CT-defined visceral pleural invasion in early-stage lung adenocarcinomas

OBJECTIVES

To analyze the diagnostic performance and prognostic value of CT-defined visceral pleural invasion (CT-VPI) in early-stage lung adenocarcinomas.

METHODS

Among patients with clinical stage I lung adenocarcinomas, half of patients were randomly selected for a diagnostic study, in which five thoracic radiologists determined the presence of CT-VPI. Probabilities for CT-VPI were obtained using deep learning (DL). Areas under the receiver operating characteristic curve (AUCs) and binary diagnostic measures were calculated and compared. Inter-rater agreement was assessed. For all patients, the prognostic value of CT-VPI by two radiologists and DL (using high-sensitivity and high-specificity cutoffs) was investigated using Cox regression.

RESULTS

In 681 patients (median age, 65 years [interquartile range, 58-71]; 382 women), pathologic VPI was positive in 130 patients. For the diagnostic study (n = 339), the pooled AUC of five radiologists was similar to that of DL (0.78 vs. 0.79; p = 0.76). The binary diagnostic performance of radiologists was variable (sensitivity, 45.3-71.9%; specificity, 71.6-88.7%). Inter-rater agreement was moderate (weighted Fleiss κ, 0.51; 95%CI: 0.43-0.55). For overall survival (n = 680), CT-VPI by radiologists (adjusted hazard ratio [HR], 1.27 and 0.99; 95%CI: 0.84-1.92 and 0.63-1.56; p = 0.26 and 0.97) or DL (HR, 1.44 and 1.06; 95%CI: 0.86-2.42 and 0.67-1.68; p = 0.17 and 0.80) was not prognostic. CT-VPI by an attending radiologist was prognostic only in radiologically solid tumors (HR, 1.82; 95%CI: 1.07-3.07; p = 0.03).

CONCLUSION

The diagnostic performance and prognostic value of CT-VPI are limited in clinical stage I lung adenocarcinomas. This feature may be applied for radiologically solid tumors, but substantial reader variability should be overcome.

CLINICAL RELEVANCE STATEMENT

Although the diagnostic performance and prognostic value of CT-VPI are limited in clinical stage I lung adenocarcinomas, this parameter may be applied for radiologically solid tumors with appropriate caution regarding inter-reader variability.

KEY POINTS

• Use of CT-defined visceral pleural invasion in clinical staging should be cautious, because prognostic value of CT-defined visceral pleural invasion remains unexplored. • Diagnostic performance and prognostic value of CT-defined visceral pleural invasion varied among radiologists and deep learning. • Role of CT-defined visceral pleural invasion in clinical staging may be limited to radiologically solid tumors.

Prospective Cohort Study to Compare Long-Term Lung Cancer-Specific and All-Cause Survival of Clinical Early Stage (T1a-b; ≤20 mm) NSCLC Treated by Stereotactic Body Radiation Therapy and Surgery

INTRODUCTION

We aimed to compare outcomes of patients with first primary clinical T1a-bN0M0 NSCLC treated with surgery or stereotactic body radiation therapy (SBRT).

METHODS

We identified patients with first primary clinical T1a-bN0M0 NSCLCs on last pretreatment computed tomography treated by surgery or SBRT in the following two prospective cohorts: International Early Lung Cancer Action Program (I-ELCAP) and Initiative for Early Lung Cancer Research on Treatment (IELCART). Lung cancer-specific survival and all-cause survival after diagnosis were compared using Kaplan-Meier analysis. Propensity score matching was used to balance baseline demographics and comorbidities and analyzed using Cox proportional hazards regression.

RESULTS

Of 1115 patients with NSCLC, 1003 had surgery and 112 had SBRT; 525 in I-ELCAP in 1992 to 2021 and 590 in IELCART in 2016 to 2021. Median follow-up was 57.6 months. Ten-year lung cancer-specific survival was not significantly different: 90% (95% confidence interval: 87%-92%) for surgery versus 88% (95% confidence interval: 77%-99%) for SBRT, p = 0.55. Cox regression revealed no significant difference in lung cancer-specific survival for the combined cohorts (p = 0.48) or separately for I-ELCAP (p = 1.00) and IELCART (p = 1.00). Although 10-year all-cause survival was significantly different (75% versus 45%, p < 0.0001), after propensity score matching, all-cause survival using Cox regression was no longer different for the combined cohorts (p = 0.74) or separately for I-ELCAP (p = 1.00) and IELCART (p = 0.62).

CONCLUSIONS

This first prospectively collected cohort analysis of long-term survival of small, early NSCLCs revealed that lung cancer-specific survival was high for both treatments and not significantly different (p = 0.48) and that all-cause survival after propensity matching was not significantly different (p = 0.74). This supports SBRT as an alternative treatment option for small, early NSCLCs which is especially important with their increasing frequency owing to low-dose computed tomography screening. Furthermore, treatment decisions are influenced by many different factors and should be personalized on the basis of the unique circumstances of each patient.

Prognostic value of CT-defined ground-glass opacity in early-stage lung adenocarcinomas: a single-center study and meta-analysis

OBJECTIVES

The prognostic value of ground-glass opacity at preoperative chest CT scans in early-stage lung adenocarcinomas is a matter of debate. We aimed to clarify the existing evidence through a single-center, retrospective cohort study and to quantitatively summarize the body of literature by conducting a meta-analysis.

METHODS

In a retrospective cohort study, patients with clinical stage I lung adenocarcinoma were identified, and the prognostic value of ground-glass opacity was analyzed using multivariable Cox regression. Commercial artificial intelligence software was adopted as the second reader for the presence of ground-glass opacity. The primary end points were freedom from recurrence (FFR) and lung cancer-specific survival (LCSS). In a meta-analysis, we systematically searched Embase and OVID-MEDLINE up to December 30, 2021, for the studies based on the eighth-edition staging system. The pooled hazard ratios (HRs) of solid nodules (i.e., absence of ground-glass opacity) for various end points were calculated with a multi-level random effects model.

RESULTS

In a cohort of 612 patients, solid nodules were associated with worse outcomes for FFR (adjusted HR, 1.98; 95% CI: 1.17-3.51; p = 0.01) and LCSS (adjusted HR, 1.937; 95% CI: 1.002-4.065; p = 0.049). The artificial intelligence assessment and multiple sensitivity analyses revealed consistent results. The meta-analysis included 13 studies with 12,080 patients. The pooled HR of solid nodules was 2.13 (95% CI: 1.69-2.67; I2 = 30.4%) for overall survival, 2.45 (95% CI: 1.52-3.95; I2 = 0.0%) for FFR, and 2.50 (95% CI: 1.28-4.91; I2 = 30.6%) for recurrence-free survival.

CONCLUSIONS

The absence of ground-glass opacity in early-stage lung adenocarcinomas is associated with worse postoperative survival.

CLINICAL RELEVANCE STATEMENT

Early-stage lung adenocarcinomas manifesting as solid nodules at preoperative chest CT, which indicates the absence of ground-glass opacity, were associated with poor postoperative survival. There is room for improvement of the clinical T categorization in the next edition staging system.

KEY POINTS

• In a retrospective study of 612 patients with stage I lung adenocarcinoma, solid nodules were associated with shorter freedom from recurrence (adjusted hazard ratio [HR], 1.98; p = 0.01) and lung cancer-specific survival (adjusted HR, 1.937; p = 0.049). • Artificial intelligence-assessed solid nodules also showed worse prognosis (adjusted HR for freedom from recurrence, 1.94 [p = 0.01]; adjusted HR for lung cancer-specific survival, 1.93 [p = 0.04]). • In meta-analyses, the solid nodules were associated with shorter freedom from recurrence (HR, 2.45) and shorter overall survival (HR, 2.13).

Diagnosis, treatment, and prognosis of stage IB non-small cell lung cancer with visceral pleural invasion

With the increasing implementation of early lung cancer screening and the increasing emphasis on physical examinations, the early-stage lung cancer detection rate continues to rise. Visceral pleural invasion (VPI), which denotes the tumor's breach of the elastic layer or reaching the surface of the visceral pleura, stands as a pivotal factor that impacts the prognosis of patients with non-small cell lung cancer (NSCLC) and directly influences the pathological staging of early-stage cases. According to the latest 9th edition of the TNM staging system for NSCLC, even when the tumor diameter is less than 3 cm, the final T stage remains T2a if VPI is present. There is considerable controversy within the guidelines regarding treatment options for stage IB NSCLC, especially among patients exhibiting VPI. Moreover, the precise determination of VPI is important in guiding treatment selection and prognostic evaluation in individuals with NSCLC. This article aims to provide a comprehensive review of the current status and advancements in studies pertaining to stage IB NSCLC accompanied by VPI.

Preoperative CT Radiomics Nomogram for Predicting Microvascular Invasion in Stage I Non-Small Cell Lung Cancer

RATIONALE AND OBJECTIVES: This study aims to develop and validate a nomogram integrating clinical-CT and radiomic features for preoperative prediction of microvascular invasion (MVI) in patients with stage I non‑small cell lung cancer (NSCLC).

MATERIALS AND METHODS

This retrospective study analyzed 188 cases of stage I NSCLC (63 MVI positives and 125 negatives), which were randomly assigned to training (n = 133) and validation cohorts (n = 55) at a ratio of 7:3. Preoperative non-contrast and contrast-enhanced CT (CECT) images were used to analyze computed tomography (CT) features and extract radiomics features. The student's t-test, the Mann-Whitney-U test, the Pearson correlation, the least absolute shrinkage and selection operator, and multivariable logistic analysis were used to select the significant CT and radiomics features. Multivariable logistic regression analysis was performed to build the clinical-CT, radiomics, and integrated models. The predictive performances were evaluated through the receiver operating characteristic curve and compared with the DeLong test. The integrated nomogram was analyzed regarding discrimination, calibration, and clinical significance.

RESULTS

The rad-score was developed with one shape and four textural features. The integrated nomogram incorporating radiomics score, spiculation, and the number of tumor-related vessels (TVN) demonstrated better predictive efficacy than the radiomics and clinical-CT models in the training cohort (area under the curve [AUC], 0.893 vs 0.853 and 0.828, and p = 0.043 and 0.027, respectively) and validation cohort (AUC, 0.887 vs 0.878 and 0.786, and p = 0.761 and 0.043, respectively). The nomogram also demonstrated good calibration and clinical usefulness.

CONCLUSION

The radiomics nomogram integrating the radiomics with clinical-CT features demonstrated good performance in predicting MVI status in stage I NSCLC. The nomogram may be a useful tool for physicians in improving personalized management of stage I NSCLC.

Radiologic Features of Nodules Attached to the Mediastinal or Diaphragmatic Pleura at Low-Dose CT for Lung Cancer Screening

Background Pulmonary noncalcified nodules (NCNs) attached to the fissural or costal pleura with smooth margins and triangular or lentiform, oval, or semicircular (LOS) shapes at low-dose CT are recommended for annual follow-up instead of immediate workup. Purpose To determine whether management of mediastinal or diaphragmatic pleura-attached NCNs (M/DP-NCNs) with the same features as fissural or costal pleura-attached NCNs at low-dose CT can follow the same recommendations. Materials and Methods This retrospective study reviewed chest CT examinations in participants from two databases. Group A included 1451 participants who had lung cancer that was first present as a solid nodule with an average diameter of 3.0-30.0 mm. Group B included 345 consecutive participants from a lung cancer screening program who had at least one solid nodule with a diameter of 3.0-30.0 mm at baseline CT and underwent at least three follow-up CT examinations. Radiologists reviewed CT images to identify solid M/DP-NCNs, defined as nodules 0 mm in distance from the mediastinal or diaphragmatic pleura, and recorded average diameter, margin, and shape. General descriptive statistics were used. Results Among the 1451 participants with lung cancer in group A, 163 participants (median age, 68 years [IQR, 61.5-75.0 years]; 92 male participants) had 164 malignant M/DP-NCNs 3.0-30.0 mm in average diameter. None of the 164 malignant M/DP-NCNs had smooth margins and triangular or LOS shapes (upper limit of 95% CI of proportion, 0.02). Among the 345 consecutive screening participants in group B, 146 participants (median age, 65 years [IQR, 59-71 years]; 81 female participants) had 240 M/DP-NCNs with average diameter 3.0-30.0 mm. None of the M/DP-NCNs with smooth margins and triangular or LOS shapes were malignant after a median follow-up of 57.8 months (IQR, 46.3-68.1 months). Conclusion For solid M/DP-NCNs with smooth margins and triangular or LOS shapes at low-dose CT, the risk of lung cancer is extremely low, which supports the recommendation of Lung Imaging Reporting and Data System version 2022 for annual follow-up instead of immediate workup. © RSNA, 2024 See also the editorial by Goodman and Baruah in this issue.

Using CT imaging features to predict visceral pleural invasion of non-small-cell lung cancer

AIM

To examine the diagnostic performance of different models based on computed tomography (CT) imaging features in differentiating the invasiveness of non-small-cell lung cancer (NSCLC) with multiple pleural contact types.

MATERIALS AND METHODS

A total of 1,573 patients with NSCLC (tumour size ≤3 cm) were included retrospectively. The clinical and pathological data and preoperative imaging features of these patients were investigated and their relationships with visceral pleural invasion (VPI) were compared statistically. Multivariate logistic regression was used to eliminate confounding factors and establish different predictive models.

RESULTS

By univariate analysis and multivariable adjustment, surgical history, tumour marker (TM), number of pleural tags, length of solid contact and obstructive inflammation were identified as independent risk predictors of pleural invasiveness (p=0.014, 0.003, <0.001, <0.001, and 0.017, respectively). In the training group, comparison of the diagnostic efficacy between the combined model including these five independent predictors and the image feature model involving the latter three imaging predictors were as follows: sensitivity of 88.9% versus 77% and specificity of 73.5% versus 84.1%, with AUC of 0.868 (95% CI: 0.848-0.886) versus 0.862 (95% CI: 0.842-0.880; p=0.377). In the validation group, the sensitivity and specificity of these two models were as follow: the combined model, 93.5% and 74.3%, the imaging feature model, 77.4% and 81.3%, and their areas under the curve (AUCs) were both 0.884 (95% CI: 0.842-0.919). The best cut-off value of length of solid contact was 7.5 mm (sensitivity 68.9%, specificity 75.5%).

CONCLUSIONS

The image feature model showed great potential in predicting pleural invasiveness, and had comparable diagnostic efficacy compared with the combined model containing clinical data.

Investigation of Early-Stage Non-Small Cell Lung Cancer Patients with Different T2 Descriptors: Real Word Data From a Large Database

INTRODUCTION

The current study evaluated a large cohort of T2N0M0 NSCLC patients with different T2 descriptors to investigate the prognostic disparities and further externally validate the T category of these patients.

METHODS

The Kaplan-Meier Method with the log-rank test was used to plot survival curves. The propensity score matching (PSM) method was used to reduce bias. Univariable and multivariable Cox analyses were used to determine prognostic factors.

RESULTS

A total of 13,015 eligible T2N0M0 NSCLC patients were included. There were 5,287, 2,577 and 5,151 patients in the T2a, T2b and non-sized determined T2N0M0 (T2non-sized) groups, respectively. Before PSM, the survival of T2non-sized patients was comparable to that of T2a patients (P = 0.080) but was superior to that of T2b patients (P < 0.001). After PSM, the survival of T2non-sized patients was inferior to that of T2a patients (P = 0.028) but was similar to that of T2b patients (P = 0.325). The T category was further subdivided based on the specific non-sized T2 descriptors and tumor size. The results of the multivariate Cox analysis found that the prognosis of T2 tumors with visceral pleural invasion (size: 0-30 mm) was better than that of T2a tumors, and the prognosis of T2 tumors with visceral pleural invasion (size: 30-40 mm) was inferior to that of T2a tumors but comparable to that of T2b tumors.

CONCLUSION

T2 tumors with visceral pleural invasion (size: 30-40 mm) should be assigned to the T2b category, and those with a size interval of 0-30 mm should be assigned to a better prognostic T2a category.

Oncologic outcomes of segmentectomy for stage IA radiological solid-predominant lung cancer >2 cm in maximum tumour size

OBJECTIVES

We aimed to compare the outcomes of segmentectomy with those of lobectomy in clinical-stage IA radiological solid-predominant non-small-cell lung cancer (NSCLC) >2 cm in maximum tumour size.

METHODS

A retrospective review was performed for radiological solid-predominant NSCLC >2-3 cm in maximum tumour size with a ground-glass opacity component on thin-section computed tomography. Multivariable or propensity score-matched analyses were performed to control for confounders for survival. Overall survival (OS) was analysed using a Kaplan-Meier estimation.

RESULTS

Of the 215 eligible cases, segmentectomy and lobectomy were performed in 46 and 169 patients. Multivariable analysis revealed that standardized uptake value (hazard ratio: 1.148, 95% confidence interval: 1.032-1.276, P = 0.011) was an independently significant prognosticators of OS, while the operative mode was not associated (hazard ratio: 0.635, 95% confidence interval: 0.132-3.049, P = 0.570). The 5 y-OS was excellent and did not differ significantly between segmentectomy and lobectomy (95.5% vs 90.2%; P = 0.697), which was also shown in the propensity score analysis (96.8% vs 94.0%; P = 0.406), with a median follow-up time of 5.2 years. Locoregional recurrence was found in 2 (4.3%) segmentectomy and 13 (7.7%) lobectomy (P = 0.443). In the subgroup analysis stratified by solid component size, the 5 y-OS was similar between segmentectomy and lobectomy in the c-T1b and c-T1c groups, respectively [c-T1b (n = 163): 94.1% vs 91.8%; P = 0.887 and c-T1c (n = 52): 100% vs 84.9%; P = 0.197].

CONCLUSIONS

Segmentectomy showed similar oncological results compared to lobectomy in solid-predominant NSCLC with a ground-glass opacity component >2-3 cm in maximum tumour size. More prospective randomized trials are needed to adequately expand the indication of anatomic segmentectomy for early-stage NSCLC.

Rethinking the Selection of Pathological T-Classification for Non-Small-Cell Lung Cancer in Varying Degrees of Visceral Pleural Invasion: A SEER-Based Study

Background

The T classification of non-small-cell lung cancer (NSCLC) was upgraded from T1 to T2 when accompanied by visceral pleural invasion (VPI). However, the association between VPI and prognostic outcomes was obscure in NSCLC patients with ≤3 cm tumor size (TS), which leaded the controversy of selection of T classification. The goal was to evaluate the effect of VPI on the prognosis of NSCLC with ≤ 3cm TS and present a modified T classification.

Methods

A total of 14,934 NSCLC patients without distant metastasis were recruited through a retrospective study in the SEER database. The effect of VPI on lung cancer specific survival (LCSS) was evaluated using survival curve and COX regression analysis in NSCLC patients with ≤3 cm TS.

Results

Although there was no difference of the LCSS of PL0 and PL1 patients with ≤2 cm TS in patients without lymph node (LN) metastasis, the LCSS was lower in PL2 patients than those in PL0 (T1a: p < 0.001; T1b: p = 0.001). Moreover, the LCSS was decreased in PL1 and PL2 patients with 2-3 cm TS compared with PL0 (T1c: PL1, p < 0.001; PL2, p = 0.009) of patients without LN metastasis. No difference of LCSS was observed in patients with LN metastasis between PL0 with PL1 and PL2.

Conclusion

In NSCLC patients without LN metastasis and TS ≤ 2 cm, tumor with PL1 should remain defined as T1, tumor with PL2 should be defined as T2. However, 2-3 cm TS patients with PL1 or PL2 should both defined as T2. Meanwhile, ≤3 cm TS patients with LN metastasis can be regarded as T1, whether NSCLC patients accompanied with PL1 or PL2.

The value of CT radiomics features to predict visceral pleural invasion in ≤3 cm peripheral type early non-small cell lung cancer

OBJECTIVE

To investigate predictive value of CT-based radiomics features on visceral pleural invasion (VPI) in ≤3.0 cm peripheral type early non-small cell lung cancer (NSCLC).

METHODS

A total of 221 NSCLC cases were collected. Among them, 115 are VPI-positive and 106 are VPI-negative. Using a stratified random sampling method, 70% cases were assigned to training dataset (n = 155) and 30% cases (n = 66) were assigned to validation dataset. First, CT findings, imaging features, clinical data and pathological findings were retrospectively analyzed, the size, location and density characteristics of nodules and lymph node status, the relationship between lesions and pleura (RAP) were assessed, and their mean CT value and the shortest distance between lesions and pleura (DLP) were measured. Next, the minimum redundancy-maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) features were extracted from the imaging features. Then, CT imaging prediction model, texture feature prediction model and joint prediction model were built using multifactorial logistic regression analysis method, and the area under the ROC curve (AUC) was applied to evaluate model performance in predicting VPI.

RESULTS

Mean diameter, density, fractal relationship with pleura, and presence of lymph node metastasis were all independent predictors of VPI. When applying to the validation dataset, the CT imaging model, texture feature model, and joint prediction model yielded AUC = 0.882, 0.824 and 0.894, respectively, indicating that AUC of the joint prediction model was the highest (p < 0.05).

CONCLUSION

The study demonstrates that the joint prediction model containing CT morphological features and texture features enables to predict the presence of VPI in early NSCLC preoperatively at the highest level.

Pre-surgical assessment of mediastinal lymph node metastases in patients having ≥ 30 mm non-small-cell lung cancers

INTRODUCTION

Computed tomography (CT) and fluorodeoxyglucose-positron-emission-tomography (FDG-PET) measurements of mediastinal lymph nodes (MLNs) of patients with non-small-cell-lung-cancers (NSCLCs) ≤ 30 mm in maximum diameter are recommended for pre-surgical prediction of MLN metastases.

METHODS

We reviewed all patients at Mount Sinai Health System enrolled in the Initiative for Early Lung Cancer Research on Treatment (IELCART), prospective cohort between 2016 and 2020, who had pre-surgical FDG-PET and underwent surgery with MLN resection and/or pre-operative endobronchial ultrasound (EBUS) for a first primary NSCLC ≤ 30 mm in maximum diameter on pre-surgical CT.

RESULTS

Among 470 patients, none with part-solid (n = 63) or nonsolid (n = 23) NSCLCs had MLN metastases. Solid NSCLCs were identified in 384 patients, none in typical carcinoid (n = 48) or NSCLC ≤ 10 mm in maximum diameter (n = 47, including 8 typical carcinoids) had MLN metastases. Among the remaining 297 patients with solid NSCLCs 10.1-30.0 mm, 7 (2.4%) had MLN metastases. Area-under-the-curve (AUC) for predicting MLN metastases in solid NSCLCs 10.1-30.0 mm, using the CT maximum short-axis MLN diameter was 0.62 (95% CI:0.44-0.81, p = 0.18) and using the highest SUVmax of any MLN, AUC was 0.58 (95% CI:0.39-0.78,p = 0.41). Neither AUCs were significantly different from chance alone. Optimal cutoff for prediction of MLN metastases was ≥ 18.9 mm for CT maximum short-axis diameter [sensitivity 14.3% (95%CI:0.0%-57.9%); specificity 100.0% (95%CI:98.9%-100.0%)] and for highest SUVmax was ≥ 11.7 [sensitivity 14.3% (95%CI:0.0%-57.9%) and specificity 99.7% (95%CI:98.3%-100.0%)].

CONCLUSIONS

CT and SUVmax had low sensitivity but high specificity for predicting MLN metastases in solid NSCLCs 10.1-30.0 mm. Clinical Stage IA NSCLCs ≤ 30 mm should be based on CT maximum tumor diameter and MLN maximum short-axis diameter ≤ 20 mm.

Characterization of Newly Detected Costal Pleura-attached Noncalcified Nodules at Annual Low-Dose CT Screenings

Background Solid costal pleura-attached noncalcified nodules (CP-NCNs) less than 10.0 mm with lentiform, oval, or semicircular (LOS) or triangular shapes and smooth margins on baseline low-dose CT scans from the Mount Sinai Early Lung and Cardiac Action Program (MS-ELCAP) were reviewed, and it was determined that they can be followed up at the first annual screening rather than having a shorter-term work-up. Purpose To determine whether the same criteria could be used for solid CP-NCNs newly identified at annual screening examinations. Materials and Methods With use of the same MS-ELCAP database, all new solid CP-NCNs measuring 30.0 mm or less were identified at 4425 annual screening examinations between 2010 and 2019. In addition, to ensure that no malignant CP-NCNs met the criteria, all solid malignant CP-NCNs of 30.0 mm or less in the International Early Lung Cancer Action Program, or I-ELCAP, database of 111 102 annual screening examinations from the 76 participating institutions between 1992 and 2019 were identified; Mount Sinai is one of these institutions. All identified solid CP-NCNs were reviewed-with the radiologists blinded to diagnosis-for shape (triangular, LOS, polygonal, round, or irregular), margin (smooth or nonsmooth), pleural attachment (broad or narrow), and the presence of emphysema and/or fibrosis within 10.0 mm of each CP-NCN. Intra- and interreader readings were performed, and agreements were determined by using the B-statistic. Results Of the 76 new solid CP-NCNs, 21 were lung cancers. Benign CP-NCNs were smaller than malignant ones (median diameter, 4.2 mm vs 11 mm; P < .001), had a different shape distributions, more frequently had smooth margins (67% vs 14%; P < .001), and less frequently had emphysema (38% vs 81%; P = .003) or fibrosis (3.6% vs 19%; P = .045) within a 10.0 mm radius. All 22 solid CP-NCNs less than 10.0 mm in average diameter with triangular or LOS shapes and smooth margins were benign, and none of the 21 solid malignant CP-NCNs had these characteristics. Intra- and interobserver agreement for triangular or LOS-shaped CP-NCNs with smooth margins was almost perfect (0.77 and 0.69, respectively). Conclusion The same follow-up recommendation developed for baseline costal pleura-attached noncalcified nodules (CP-NCNs) can be used for CP-NCNs newly identified at annual screening rounds. © RSNA, 2021.

Improving the accuracy of prognosis for clinical stage I solid lung adenocarcinoma by radiomics models covering tumor per se and peritumoral changes on CT

OBJECTIVES

To assess methods to improve the accuracy of prognosis for clinical stage I solid lung adenocarcinoma using radiomics based on different volumes of interests (VOIs).

METHODS

This retrospective study included patients with postoperative clinical stage I solid lung adenocarcinoma from two hospitals, center 1 and center 2. Three databases were generated: dataset A (training set from center 1), dataset B (internal test set from center 1), and dataset C (external validation test from center 2). Disease-free survival (DFS) data were collected. CT radiomics models were constructed based on four VOIs: gross tumor volume (GTV), 3 mm external to the tumor border (peritumoral volume [PTV]_0~+3), 6 mm crossing tumor border (PTV_-3~+3), and 6 mm external to the tumor border (PTV_0~+6). The area under the receiver operating characteristic curve (AUC) was used to compare the model accuracies.

RESULTS

A total of 334 patients were included (204 and 130 from centers 1 and 2). The model using PTV_-3~+3 (AUC 0.81 [95% confidence interval {CI}: 0.75, 0.94], 0.81 [0.63, 0.90] for datasets B and C) outperformed the other three models, GTV (0.73 [0.58, 0.81], 0.73 [0.58, 0.83]), PTV_0~+3 (0.76 [0.52, 0.87], 0.75 [0.60, 0.83]), and PTV_0~+6 (0.72 [0.60, 0.81], 0.69 [0.59, 0.81]), in datasets B and C, all p < 0.05.

CONCLUSIONS

A radiomics model based on a VOI of 6 mm crossing tumor border more accurately predicts prognosis of clinical stage I solid lung adenocarcinoma than that based on VOIs including overall tumor or external rims of 3 mm and 6 mm.

KEY POINTS

• Radiomics is a useful approach to improve the accuracy of prognosis for stage I solid adenocarcinoma. • The radiomics model based on VOIs that includes 3 mm within and external to the tumor border (peritumoral volume [PTV]_-3~+3) outperformed models that included either only the tumor itself or those that only included the peritumoral volume.

Assessing the predictive accuracy of lung cancer, metastases, and benign lesions using an artificial intelligence-driven computer aided diagnosis system

Background

Artificial intelligence (AI) products have been widely used for the clinical detection of primary lung tumors. However, their performance and accuracy in risk prediction for metastases or benign lesions remain underexplored. This study evaluated the accuracy of an AI-driven commercial computer-aided detection (CAD) product (InferRead CT Lung Research, ICLR) in malignancy risk prediction using a real-world database.

Methods

This retrospective study assessed 486 consecutive resected lung lesions, including 320 adenocarcinomas, 40 other malignancies, 55 metastases, and 71 benign lesions, from September 2015 to November 2018. The malignancy risk probability of each lesion was obtained using the ICLR software based on a 3D convolutional neural network (CNN) with DenseNet architecture as a backbone (without clinical data). Two resident doctors independently graded each lesion using patient clinical history. One doctor (R1) has 3 years of chest radiology experience, and the other doctor (R2) has 3 years of general radiology experience. Cochran's Q test was used to assess the performances of the AI compared to the radiologists.

Results

The accuracy of malignancy-risk prediction using the ICLR for adenocarcinomas, other malignancies, metastases, and benign lesions was 93.4% (299/320), 95.0% (38/40), 50.9% (28/55), and 40.8% (29/71), respectively. The accuracy was significantly higher in adenocarcinomas and other malignancies compared to metastases and benign lesions (all P<0.05). The overall accuracy of risk prediction for R1 was 93.6% (455/486) and 87.4% for R2 (425/486), both of which were higher than the 81.1% accuracy obtained with the ICLR (394/486) (R1 vs. ICLR: P<0.001; R2 vs. ICLR: P=0.001), especially in assessing the risk of metastases (P<0.05). R1 performed better than R2 at risk prediction (P=0.001).

Conclusions

The accuracy of the ICLR for risk prediction is very high for primary lung cancers but poor for metastases and benign lesions.

Prognostic impact of tumour spread through air space in radiological subsolid and pure solid lung adenocarcinoma

OBJECTIVES

The aim of the study was to investigate the relationship between ground-glass opacity (GGO) and tumour spread through air space (STAS), as well as their joint influence on the prognosis of stage I lung adenocarcinoma.

METHODS

A total of 620 consecutive patients with surgically resected lung adenocarcinoma between January 2011 and December 2012 were reviewed retrospectively. The relevance of STAS and GGO was analysed by logistic regression, and their prognostic significance was investigated via the Kaplan-Meier method and Cox regression models. Furthermore, to determine the magnitude of the prognostic impact of GGO and STAS, we respectively performed survival analysis in subgroups according to the presence of STAS and GGO.

RESULTS

Of all 620 cases, 26.7% were positive for STAS, and 32.9% had a GGO component. STAS was present in 10.8% of part-solid lesions and 34.9% of pure solid nodules (P < 0.001). Lepidic-predominant histologic subtype, GGO component and pathological T stage exhibited significant relevance to the presence of STAS. For the whole population, STAS and GGO component were each revealed as independent predictors for overall survival and recurrence-free survival (each with P < 0.001). Interestingly, in the GGO-present subgroup, STAS failed to significantly stratify prognosis. However, in the STAS-positive subgroup, the presence of a GGO component was independently associated with favourable oncological results.

CONCLUSIONS

STAS is associated with a GGO component, and each factor was a significant predictor for the prognosis of stage I lung adenocarcinoma. Moreover, the favourable prognostic impact of a GGO component was greater than the adverse prognostic influence of STAS, indicating that GGO is a more reliable prognostic predictor in stage I lung adenocarcinoma.

The modification of T description according to visceral pleural invasion and tumor size from 3.1 cm to 4.0 cm in non-small cell lung cancer: A retrospective analysis based on the SEER database

OBJECTIVES

As a poor prognostic factor, visceral pleural invasion (VPI) was incorporated into non-small cell lung cancer (NSCLC) staging system. For modifying the T description of NSCLC, the prognostic value of VPI was assessed.

MATERIALS AND METHODS

From 2010-2015, data on stage pT2N0M0 NSCLC patients with tumor size (TS) from 3.1 cm to 5.0 cm who received surgery from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled retrospectively. Propensity score matching was utilized to balance the baseline factors according to different TS intervals. Overall survival (OS) was assessed by the Kaplan-Meier method and log-rank test. Univariate and multivariate analysis were applied to identify the prognostic factors. The risk factors of VPI were calculated by logistic regression model.

RESULT

The sum of 4005 resected stage pT2N0M0 NSCLC patients with TS from 3.1 cm to 5.0 cm were recruited, which had 1084 patients with VPI and 2921 patients without VPI respectively. As TS interval of 3.1-4.0 cm, the 5-year OS of patients without VPI was significantly better than those with VPI (62.6 % vs 58.7 %, P = 0.015), while the 5-year OS of patients with VPI and TS interval of 3.1-4.0 cm had no significant difference compared with patients whose TS interval of 4.1-5.0 cm (58.7 % vs 58.8 %, P = 0.918). Logistic regressive analysis manifested that older age, female, worse differentiation grade and larger TS had higher incidence of VPI (OR = 1.01, 1.25, 1.25, 1.16, respectively; P < 0.05 for all).

CONCLUSION

This study underlined the prognostic effect of VPI and suggested that early-stage NSCLC with VPI and TS interval of 3.1-4.0 cm could be appropriately upstaged from pT2a (stage pIB) to pT2b (modified stage pIIA).

Extent of mediastinal nodal dissection in stage I non-small cell lung cancer with a radiological pure-solid appearance

BACKGROUND

Radiological pure-solid lung cancer denotes a high invasive nature compared to one that is part-solid. Mediastinal lymph nodal dissection (mLND) is a standard surgical procedure for nodal management in lung cancer surgery, however, the prognostic impact of the extent of mLND in pure-solid lung cancer is still unknown.

METHODS

We reviewed 459 patients with c-stage I radiological pure-solid lung cancer that underwent pulmonary lobectomy with mLND. Pure-solid was defined as a tumor showing only a consolidation without any ground glass opacity. The extent of mLND was classified into lobe-specific (L-mLND) and systematic (S-mLND). Prognostic significance of mLND was assessed by a multivariable analysis using propensity-score matching. Survivals were calculated by Kaplan-Meier methods using log-rank test.

RESULTS

Pathological nodal metastasis was found in 127 (27.6%) patients (hilar: 52 (11.3%), mediastinal: 75 (16.3%)). L-mLND was performed in 278 (61%) patients. A multivariable analysis did not show the survival difference for the extent of mLND (p = 0.266). The 5-year overall survival (OS) was not significantly different between S-mLND and L-mLND (74.3% vs. 72.7%, p = 0.712), which was similar even in 114 propensity-score matched pairs (78.8% vs. 79.9%, p = 0.665). While S-mLND showed a trend for survival benefit compared to L-mLND provided that the tumor showed higher standardized uptake value (SUVmax) (5y-OS: 70.0% vs. 59.2%, p = 0.093).

CONCLUSIONS

Prognostic impact of L-mLND was similar to S-mLND in c-stage I radiological pure-solid lung cancers in the propensity-score matched comparison. Among them, higher SUVmax value might be a promising indicator to decide the extent of mediastinal lymphadenectomy.

The Regimen of Computed Tomography Screening for Lung Cancer: Lessons Learned Over 25 Years From the International Early Lung Cancer Action Program

We learned many unanticipated and valuable lessons since we started planning our study of low-dose computed tomography (CT) screening for lung cancer in 1991. The publication of the baseline results of the Early Lung Cancer Action Project (ELCAP) in Lancet 1999 showed that CT screening could identify a high proportion of early, curable lung cancers. This stimulated large national screening studies to be quickly started. The ELCAP design, which provided evidence about screening in the context of a clinical program, was able to rapidly expand to a 12-institution study in New York State (NY-ELCAP) and to many international institutions (International-ELCAP), ultimately working with 82 institutions, all using the common I-ELCAP protocol. This expansion was possible because the investigators had developed the ELCAP Management System for screening, capturing data and CT images, and providing for quality assurance. This advanced registry and its rapid accumulation of data and images allowed continual assessment and updating of the regimen of screening as advances in knowledge and new technology emerged. For example, in the initial ELCAP study, introduction of helical CT scanners had allowed imaging of the entire lungs in a single breath, but the images were obtained in 10 mm increments resulting in about 30 images per person. Today, images are obtained in submillimeter slice thickness, resulting in around 700 images per person, which are viewed on high-resolution monitors. The regimen provides the imaging acquisition parameters, imaging interpretation, definition of positive result, and the recommendations for further workup, which now include identification of emphysema and coronary artery calcifications. Continual updating is critical to maximize the benefit of screening and to minimize potential harms. Insights were gained about the natural history of lung cancers, identification and management of nodule subtypes, increased understanding of nodule imaging and pathologic features, and measurement variability inherent in CT scanners. The registry also provides the foundation for assessment of new statistical techniques, including artificial intelligence, and integration of effective genomic and blood-based biomarkers, as they are developed.

Pre-surgical assessment of mediastinal lymph node metastases in Stage IA non-small-cell lung cancers

OBJECTIVE

Evaluation of sensitivity and specificity of CT and fluorodeoxyglucose-positron emission tomography for pre-surgical staging of mediastinal lymph node metastases (N2/N3) of non-small-cell-lung-cancers ≤30 mm.

METHODS

We reviewed a total of 263 patients from a prospective cohort study, who underwent resection including mediastinal lymph nodes, for first primary non-small-cell-lung-cancer ≤30 mm in maximum diameter on pre-surgical CT. Cutoff criteria for short-axis diameter on CT of the largest N2/N3 node of 10, 15, and 20 mm and positron emission uptake of 2.5, 3.0, and 4.0 were evaluated using Area-Under-the-Curve (AUC) assessment. Accuracy criterion was used to determine the optimal cutoffs.

RESULTS

Of 263 patients, 9 had nonsolid, 42 part-solid, and 212 solid non-small-cell-lung-cancers. Post-surgically, none of the 51 patients with nonsolid or part-solid cancers had mediastinal lymph node metastases. Among the 212 patients with solid cancers, 23 had N2 node metastases. For the 212 patients with solid cancers, the AUC for CT lymph node measurements was 0.67 (95% CI: 0.57-0.77), significantly higher (p = 0.001) than chance alone, while the AUC for SUVmax measurements, 0.56 (95% CI: 0.48-0.65), was not (p = 0.13). Optimal CT cutoff was >20 mm had low sensitivity of 30.4% (95% CI: 11.6%-49.2%) but high specificity of 99.5% (95% CI: 98.4%-100.0%).

CONCLUSION

Based on these results, clinical Stage IA for non-small-cell-lung-cancers with nonsolid, part-solid, or solid consistency should be based on pre-surgical CT maximum tumor diameter and lymph node short-axis measurements on CT ≤20 mm. Further prospective evaluation of these clinical Stage IA staging criteria is needed.

A modified T categorization for part-solid lesions in Chinese patients with clinical stage I Non-small cell lung cancer

OBJECTIVES

We evaluated the prognostic impact of the presence of ground glass opacity (GGO) component and compared a modified clinical T categorization (cT_m) with the current 8th classification (cT₈) for survival prediction in Chinese patients with clinical stage I non-small cell lung cancer (NSCLC).

METHODS

According to cT_m and cT₈ classifications, we retrospectively evaluated 1461 patients with part-solid or pure-solid lesions. The recurrence-free survival (RFS) and overall survival (OS) were analyzed by Kaplan-Meier method and Cox proportional hazard model. The concordance index (C- index), reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA) were performed to estimate reclassification net benefits of cT_m for survival prediction.

RESULTS

The cT₈ classification clearly stratifies the survival outcomes in solid tumors but not in part-solid tumors. The presence of GGO components was an independent prognostic factor for both RFS and OS (p < 0.001), indicating a better outcome in each clinical T stage. The C-index was significantly improved from 0.650 to 0.730 for RFS (p < 0.001) and 0.647 to 0.730 for OS (p < 0.001) after reclassifying by cT_m categorization. The DCA, NRI (RFS: 0.342, OS: 0.302), and IDI (RFS: 0.070, OS: 0.054) demonstrated that the cT_m classification provided more net benefit in the survival prediction compared with the current cT₈ classification.

CONCLUSIONS

The current cT₈ classification may not be appropriate for part-solid lesions because the presence of GGO components is associated with excellent prognosis despite clinical stage. Also, the cT_m classification for part-solid lesions showed an improvement in survival prediction.

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

OBJECTIVE

We performed a validation study to confirm the prognostic importance of the presence of a ground-glass opacity component based on data of the Japan Clinical Oncology Group study, JCOG0201, which was a prospective observational study to predict the pathological noninvasiveness of clinical stage IA lung cancer in Japan.

METHODS

Among the 811 patients registered in JCOG0201, 671 were confirmed eligible by study monitoring and a central review of computed tomography. Registered c-stage IA lung cancer was less than 30 mm in maximum tumor size, which was classified into a with ground-glass opacity group (pure ground-glass opacity and part-solid tumor) or solid group based on the status of a ground-glass opacity component. T staging was reassigned in accordance with the 8th edition of the TNM staging system. To validate the prognostic impact, overall survival was estimated.

RESULTS

Of the cases, 432 (64%) were in the with ground-glass opacity group and 239 (36%) were in the solid group with a median follow-up time of 10.1 years. The 5-year overall survival was significantly different between the with ground-glass opacity group and solid group (95.1% vs 81.1%). The 5-year overall survival was excellent regardless of the solid component size in the with ground-glass opacity group (c-T1a or less: 97.2%, c-T1b: 93.4%, c-T1c: 91.7%). In contrast, prognostic impact of the tumor size was definitive in the solid group (c-T1a: 87.5%, c-T1b: 85.9%, c-T1c: 73.7%).

CONCLUSIONS

Favorable prognostic impact of the presence of a ground-glass opacity component was demonstrated in JCOG0201. The presence or absence of a ground-glass opacity should be considered as an important parameter in the next clinical T classification.

Sublobectomy versus lobectomy for long-term survival outcomes of early-stage non-small cell lung cancer with a tumor size ≤2 cm accompanied by visceral pleural invasion: a SEER population-based study

Background

The optimal surgical strategy for early-stage non-small cell lung cancer (NSCLC) with visceral pleural invasion (VPI) remains unclear. Due to limited prospective comparative data for these surgical modalities, the objective of the current study was to compare the long-term survival outcomes of sublobectomy (Sub) versus lobectomy (Lob) for NSCLC with a tumor size ≤2 cm and VPI.

Methods

Patients with early-stage NSCLC characterized by VPI diagnosed between 2004 and 2013 were identified from the Surveillance, Epidemiology, and End Results (SEER) program. The baseline demographic and cancer characteristics, treatment information as well as survival outcome data were extracted from the SEER database, and confounders were balanced by propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) analyses. Lung disease-specific survival (DSS) and overall survival (OS) rates were compared with Cox proportional hazards (PH) regression models based on the unmatched cohort, the propensity-based matched cohort, and the IPTW cohort.

Results

Of the 1,386 patients enrolled, 1,000 (72.15%) and 386 (27.85%) underwent lobectomy and sublobectomy, respectively. The 5-year DSS rate was 78.64% for the lobectomy group and 59.47% for the sublobectomy group. Cox regression models demonstrated that the operation type (Sub vs. Lob) was an independent prognostic factor for early-stage NSCLC with VPI based on the three different cohorts. Patients who underwent lobectomy showed better long-term DSS and OS rates than those treated with sublobectomy after PSM [DSS: hazard ratio (HR) 0.689, 95% confidence interval (CI): 0.490–0.968, P=0.032; OS: HR 0.723, 95% CI: 0.549–0.953, P=0.021]. The IPTW analysis yielded similar results.

Conclusions

Lobectomy showed superior long-term survival compared with sublobectomy in patients with early-stage NSCLC with a tumor size ≤2 cm and VPI.

Visceral Pleural Invasion in Pulmonary Adenocarcinoma: Differences in CT Patterns between Solid and Subsolid Cancers

PURPOSE

To analyze the incidence and CT patterns of visceral pleural invasion (VPI) in adenocarcinomas on the basis of their CT presentation as solid or subsolid nodules.

MATERIALS AND METHODS

A total of 286 adenocarcinomas in direct contact with a pleural surface, resected at an institution between 2005 and 2016, were included in this retrospective, institutional review board-approved study. CT size and longest contact length with a pleural surface were measured and their ratios computed. Pleural deviation, pleural thickening, spiculations, different pleural tag types, pleural effusion, and the CT appearance of transgression into an adjacent lobe or infiltration of surrounding tissue were evaluated. Fisher exact tests and simple and multiple logistic regression models were used.

RESULTS

Of the 286 nodules, 179 of 286 (62.6%) were solid and 107 of 286 (37.4%) were subsolid. VPI was present in 49 of 286 (17.1%) nodules and was significantly more frequent in solid (44 of 179; 24.6%) than in subsolid nodules (five of 107; 4.7%; P < .001). In solid nodules, multiple regression analysis showed an association of higher contact length-to-size ratio (adjusted odds ratio [OR], 1.02; P = .007) and the presence of multiple pleural tag types (adjusted OR, 5.88; P = .002) with VPI. In subsolid nodules, longer pleural contact length of the solid nodular component (adjusted OR, 1.27; P = .017) and the CT appearance of transgression or infiltration (adjusted OR, 10.75; P = .037) were associated with VPI.

CONCLUSION

During preoperative evaluation of adenocarcinomas for the likelihood of VPI, whether a tumor manifests as a solid or a subsolid nodule is important to consider because the incidence of VPI is significantly higher in solid than in subsolid nodules. In addition, this study showed that the CT patterns associated with VPI differ between solid and subsolid nodules.© RSNA, 2019Supplemental material is available for this article.See also the commentary by Elicker in this issue.