Can computed tomography differentiate adenocarcinoma in situ from minimally invasive adenocarcinoma?

Evaluating the necessity of lymph node sampling in lung adenocarcinoma with ground glass opacities

BACKGROUND

Ground glass opacity is observed frequently in the early stages of lung adenocarcinoma and is associated with a favorable prognosis and a low incidence of lymph node metastasis. However, the necessity of lymph node sampling in these patients is questionable, although current guidelines still recommend it.

METHODS

Radiologic and clinical data were retrospectively collected and analyzed for 2,298 patients with lung cancer who underwent surgical resection for lesions ≤15 mm during 2022. Based on the consolidation tumor ratios, patients were categorized into 4 groups (pure ground glass opacity, ground glass opacity-predominant, solid-predominant, and pure solid). The incidence of lymph node metastasis in each group was examined.

RESULTS

A total of 2,298 patients with a median age of 54.0 years were enrolled in this study. Tumors were categorized into 4 types: 1,427 (62.1%) were pure ground glass opacity, which constituted the majority, while 421 (18.3%) were ground glass opacity-predominant, 330 (14.4%) were solid-predominant, and the remaining 120 (5.2%) were pure solid. Significant positive correlations were revealed between the consolidation tumor ratio group and pathologic grade (P < .001, ρ = 0.307), T stage (P < .001, ρ = 0.270), and N stage (P < .001, ρ = 0.105). Among the included cases, only 7 cases with metastasis were in the pure solid group. Within this group, 113 cases (94.2%) were N0, 5 cases (4.2%) were N1, and 2 cases (1.7%) were N2.

CONCLUSION

Lymph node metastasis exclusively occurred in the pure solid group, suggesting that for nodules <15 mm, lymph node sampling may be crucial for pure solid nodules but less so for those containing ground glass opacities.

Correlation Analysis of Computed Tomography Features and Pathological Types of Multifocal Ground-Glass Nodular Lung Adenocarcinoma

To investigate the correlation between computed tomography (CT) image characteristics of multiple lung ground-glass nodules (GGNs) and pathological classification, the CT image data of multiple lung GGN patients confirmed by pathology (n = 132) in our hospital were collected. The imaging features of GGNs were analyzed by qualified physicians, including lesion size (diameter, volume, and mass), location, CT values (mean and relative CT values), lesion morphology (round and irregular), marginal structure (pagination and burr), internal structure (bronchial inflation sign), and adjacent structure (pleural depression). CT imaging analysis was performed for the subtype of infiltrating adenocarcinoma (IAC). In CT findings, GGNs were greatly different from adenomatous hyperplasia (AAH), pure GGN adenocarcinoma in situ (AIS), and microinvasive adenocarcinoma (MIA) in terms of marginal structure, lesion morphology, internal structure, adjacent structure, and size (P < 0.05). The mean and relative CT values of mural adenocarcinoma, acinar adenocarcinoma, and papillary adenocarcinoma of IAC subtypes were greatly different from those of AAH/AIS/MIA (P < 0.05). In summary, the CT images of GGNs can be used as the basis for the differentiation of AAH, AIS, and MIA early noninvasive types and IAC invasive types, and the CT value of the IAC subtype can be used as the basis for the classification and differentiation of IAC pathological subtypes.

Computed Tomography-Guided Transthoracic Needle Biopsy: Predictors for Diagnostic Failure and Tissue Adequacy for Molecular Testing

Background: Adequate and representative tissue from lung tumor is important in the era of precision medicine. The aim of this study is to identify detailed procedure-related variables and factors influencing diagnostic success and tissue adequacy for molecular testing in CT-guided TTNB.

Methods: Consecutive patients undergoing CT-guided TTNB were retrospectively enrolled between January 2013 and May 2020. Multivariate analysis was performed for predictors for diagnostic accuracy and tissue adequacy for molecular testing. Logistic regression was used to identify risk factors for procedure-related complications.

Results: A total of 2,556 patients undergoing CT-guided TTNB were enrolled and overall success rate was 91.5% (2,338/2,556). For lung nodules ≤3 cm, predictors for diagnostic success included coaxial needle use [OR = 0.34 (0.16–0.71), p = 0.004], CT scan slice thickness of 2.5 mm [OR = 0.42 (0.15–0.82), p = 0.011] and additional prefire imaging [OR = 0.31 (0.14–0.68), p = 0.004]. For lung tumor >3 cm, ground glass opacity part more than 50% [OR = 7.53 (2.81–20.23), p < 0.001] or presence of obstructive pneumonitis [OR = 2.31 (1.53–3.48), p < 0.001] had higher risk of diagnostic failure. For tissue adequacy, tissue submitted in two cassettes (98.9 vs. 94.9%, p = 0.027) was a positive predictor; while male (5.7 vs. 2.5%, p = 0.032), younger age (56.61 ± 11.64 vs. 65.82 ± 11.98, p < 0.001), and screening for clinical trial (18.5 vs. 0.7%, p < 0.001) were negative predictors.

Conclusions: Using a coaxial needle, with thin CT slice thickness (2.5 mm), and obtaining additional prefire imaging improved diagnostic success, while obtaining more than two tissue cores and submitting in two cassettes improved tissue adequacy for molecular testing.

Can computed tomography differentiate adenocarcinoma in situ from minimally invasive adenocarcinoma?

BACKGROUND

Given the subtle pathological signs of adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA), effective differentiation between the two entities is crucial. However, it is difficult to predict these conditions using preoperative computed tomography (CT) imaging. In this study, we investigated whether histological diagnosis of AIS and MIA using quantitative three-dimensional CT imaging analysis could be predicted.

METHODS

We retrospectively analyzed the images and histopathological findings of patients with lung cancer who were diagnosed with AIS or MIA between January 2017 and June 2018. We used Synapse Vincent (v. 4.3) (Fujifilm) software to analyze the CT attenuation values and performed a histogram analysis.

RESULTS

There were 22 patients with AIS and 22 with MIA. The ground-glass nodule (GGN) rate was significantly higher in patients with AIS (p < 0.001), whereas the solid volume (p < 0.001) and solid rate (p = 0.001) were significantly higher in those with MIA. The mean (p = 0.002) and maximum (p = 0.025) CT values were significantly higher in patients with MIA. The 25th, 50th, 75th, and 97.5th percentiles (all p < 0.05) for the CT values were significantly higher in patients with MIA.

CONCLUSIONS

We demonstrated that quantitative analysis of 3D-CT imaging data using software can help distinguish AIS from MIA. These analyses are useful for guiding decision-making in the surgical management of early lung cancer, as well as subsequent follow-up.