Surgically resected lung adenocarcinoma: do heterogeneous GGNs and part-solid nodules on thin-section CT show different prognosis?

Nomogram integrating clinical-radiological and radiomics features for differentiating invasive from non-invasive pulmonary adenocarcinomas presenting as ground-glass nodules

OBJECTIVE

To construct a nomogram incorporating clinical-radiological and radiomics features from computed tomography (CT) for distinguishing invasive adenocarcinoma (IAC) from adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) in ground-glass nodules (GGNs).

METHODS

This retrospective study included 473 GGN patients with postoperative pathological confirmation of AIS, MIA, or IAC. The training set comprised 257 patients from Yantaishan Hospital, while the test set, used for external validation, included 216 patients from the Affiliated Hospital of Binzhou Medical College. Radiomics features were selected, and a radiomics model was constructed using least absolute shrinkage and selection operator (LASSO) and minimum redundancy maximum relevance (mRMR) methods. A clinical-radiological model was developed using univariate and multivariate logistic regression. The nomogram was generated by combining the two models. Its performance was evaluated via receiver operating characteristic (ROC) curve analysis, calibration curve analysis, and decision curve analysis (DCA).

RESULTS

The radiomics model included 11 features, while the clinical-radiological model incorporated lobulation, age, and long diameter. The nomogram outperformed both individual models in terms of accuracy and area under the curve (AUC) in both the training and test sets. Calibration curve analysis confirmed good consistency between actual and predicted outcomes, and DCA indicated the nomogram's clinical utility.

CONCLUSION

The nomogram is a non-invasive, accurate tool for preoperative differentiation of GGN types, providing valuable guidance for clinicians in treatment planning.

The 2023 American Association for Thoracic Surgery (AATS) Expert Consensus Document: Management of subsolid lung nodules

OBJECTIVE

Lung cancers that present as radiographic subsolid nodules represent a subtype with distinct biological behavior and outcomes. The objective of this document is to review the existing literature and report consensus among a group of multidisciplinary experts, providing specific recommendations for the clinical management of subsolid nodules.

METHODS

The American Association for Thoracic Surgery Clinical Practice Standards Committee assembled an international, multidisciplinary expert panel composed of radiologists, pulmonologists, and thoracic surgeons with established expertise in the management of subsolid nodules. A focused literature review was performed with the assistance of a medical librarian. Expert consensus statements were developed with class of recommendation and level of evidence for each of 4 main topics: (1) definitions of subsolid nodules (radiology and pathology), (2) surveillance and diagnosis, (3) surgical interventions, and (4) management of multiple subsolid nodules. Using a modified Delphi method, the statements were evaluated and refined by the entire panel.

RESULTS

Consensus was reached on 17 recommendations. These consensus statements reflect updated insights on subsolid nodule management based on the latest literature and current clinical experience, focusing on the correlation between radiologic findings and pathological classifications, individualized subsolid nodule surveillance and surgical strategies, and multimodality therapies for multiple subsolid lung nodules.

CONCLUSIONS

Despite the complex nature of the decision-making process in the management of subsolid nodules, consensus on several key recommendations was achieved by this American Association for Thoracic Surgery expert panel. These recommendations, based on evidence and a modified Delphi method, provide guidance for thoracic surgeons and other medical professionals who care for patients with subsolid nodules.

Clinical Outcomes of Resected Pure Ground-Glass, Heterogeneous Ground-Glass, and Part-Solid Pulmonary Nodules

BACKGROUND. Increased (but not definitively solid) attenuation within pure ground-glass nodules (pGGNs) may indicate invasive adenocarcinoma and the need for resection rather than surveillance. OBJECTIVE. The purpose of this study was to compare the clinical outcomes among resected pGGNs, heterogeneous ground-glass nodules (GGNs), and part-solid nodules (PSNs). METHODS. This retrospective study included 469 patients (335 female patients and 134 male patients; median age, 68 years [IQR, 62.5-73.5 years]) who, between January 2012 and December 2020, underwent resection of lung adenocarcinoma that appeared as a subsolid nodule on CT. Two radiologists, using lung windows, independently classified each nodule as a pGGN, a heterogeneous GGN, or a PSN, resolving discrepancies through discussion. A heterogeneous GGN was defined as a GGN with internal increased attenuation not quite as dense as that of pulmonary vessels, and a PSN was defined as having an internal solid component with the same attenuation as that of the pulmonary vessels. Outcomes included pathologic diagnosis of invasive adenocarcinoma, 5-year recurrence rates (locoregional or distant), and recurrence-free survival (RFS) and overall survival (OS) over 7 years, as analyzed by Kaplan-Meier and Cox proportional hazards regression analyses, with censoring of patients with incomplete follow-up. RESULTS. Interobserver agreement for nodule type, expressed as a kappa coefficient, was 0.69. Using consensus assessments, 59 nodules were pGGNs, 109 were heterogeneous GGNs, and 301 were PSNs. The frequency of invasive adenocarcinoma was 39.0% in pGGNs, 67.9% in heterogeneous GGNs, and 75.7% in PSNs (for pGGNs vs heterogeneous GGNs, p < .001; for pGGNs vs PSNs, p < .001; and for heterogeneous GGNs vs PSNs, p = .28). The 5-year recurrence rate was 0.0% in patients with pGGNs, 6.3% in those with heterogeneous GGNs, and 10.8% in those with PSNs (for pGGNs vs heterogeneous GGNs, p = .06; for pGGNs vs PSNs, p = .02; and for heterogeneous GGNs vs PSNs, p = .18). At 7 years, RFS was 97.7% in patients with pGGNs, 82.0% in those with heterogeneous GGNs, and 79.4% in those with PSNs (for pGGNs vs heterogeneous GGNs, p = .02; for pGGNs vs PSNs, p = .006; and for heterogeneous GGNs vs PSNs, p = .40); OS was 98.0% in patients with pGGNs, 84.6% in those with heterogeneous GGNs, and 82.9% in those with PSNs (for pGGNs vs heterogeneous GGNs, p = .04; for pGGNs vs PSNs, p = .01; and for heterogeneous GGNs vs PSNs, p = .50). CONCLUSION. Resected pGGNs had excellent clinical outcomes. Heterogeneous GGNs had relatively worse outcomes, more closely resembling outcomes for PSNs. CLINICAL IMPACT. The findings support surveillance for truly homogeneous pGGNs versus resection for GGNs showing internal increased attenuation even if not having a true solid component.

Differentiation Between Heterogeneous GGN and Part-Solid Nodule Using 2 D Grayscale Histogram Analysis of Thin-Section CT Image

INTRODUCTION/BACKGROUND

To evaluate cases of surgically resected pulmonary adenocarcinoma (Ad) with heterogenous ground-glass nodules (HGGNs) or part-solid nodules (PSNs) and to clarify the differences between them, and between invasive adenocarcinoma (IVA) and minimally invasive adenocarcinoma (MIA) + adenocarcinoma in situ (AIS) using grayscale histogram analysis of thin-section computed tomography (TSCT).

MATERIALS AND METHODS

241 patients with pulmonary Ad were retrospectively classified into HGGNs and PSNs on TSCT by three thoracic radiologists. Sixty HGGNs were classified into 17 IVAs, 26 MIAs, and 17 AISs. 181 PSNs were classified into 114 IVAs, 55 MIAs, and 12 AISs.

RESULTS

We found significant differences in area (P = 0.0024), relative size of solid component (P <0.0001), circumference (P <0.0001), mean CT value (P <0.0001), standard deviation of the CT value (P <0.0001), maximum CT value (P <0.0001), skewness (P <0.0001), kurtosis (P <0.0001), and entropy (P <0.0001) between HGGNs and PSNs. In HGGNs, we found significant differences in relative size of solid component (P <0.0001), mean CT value (P = 0.0005), standard deviation of CT value (P = 0.0071), maximum CT value (P = 0.0237), and skewness (P = 0.0027) between IVAs and MIA+AIS lesions. In PSNs, we found significant differences in area (P = 0.0029), relative size of solid component (P = 0.0003), circumference (P = 0.0004), mean CT value (P = 0.0011), skewness (P = 0.0009), and entropy (P = 0.0002) between IVAs and the MIA+AIS lesions.

CONCLUSION

Quantitative evaluations using grayscale histogram analysis can clearly distinguish between HGGNs and PSNs, and may be useful for estimating the pathology of such lesions.