HRCT findings of small cell lung cancer measuring 30 mm or less located in the peripheral lung

Significance of marginal vessels in differentiating peripheral small-cell lung cancer and benign lung tumor

BACKGROUND

Some peripheral small cell lung cancers (pSCLCs) and benign lung tumors (pBLTs) have similar morphological features but different treatment and prognosis.

PURPOSE

To determine the significance of marginal vessels in differentiating pSCLCs and pBLTs.

MATERIAL AND METHODS

A total of 57 and 95 patients with pathological confirmed nodular (≤3 cm) pSCLC and pBLT with similar morphological features were enrolled in this study retrospectively. The patients' clinical characteristics and computed tomography (CT) features of tumors and marginal vessels (vessels connecting with tumors) were analyzed and compared.

RESULTS

Compared with pBLTs, pSCLCs had a larger diameter (P = 0.001) but lower enhancement (P = 0.015) and fewer had calcification (P = 0.013). Compared with pBLTs, more lesions had proximal (70.2% vs. 22.1%) and distal (59.6% vs. 4.2%) marginal vessels in pSCLCs (each P < 0.0001). In addition, in pSCLCs, the numbers of proximal (1.3 ± 1.4 vs. 0.3 ± 0.6), distal (2.4 ± 3.1 vs. 0.1 ± 0.5), and total (3.6 ± 3.5 vs. 0.4 ± 1.0) marginal vessels were all more than those in pBLTs (each P < 0.001). Receiver operating characteristic curve analysis revealed the positive distal marginal vessel sign had the highest specificity (95.8%), and the number of total marginal vessels had the best performance in discriminating pSCLC from pBLT (cutoff value = 1.5, AUC = 0.80, 95% CI = 0.72-0.89, sensitivity = 70.2%, and specificity = 91.6%).

CONCLUSION

For peripheral solid nodules similar to pBLTs but without any calcification, the possibility of pSCLC should be considered if they have multiple marginal vessels (≥2), especially the distal ones.

Observational Study of the Natural Growth History of Peripheral Small-Cell Lung Cancer on CT Imaging

BACKGROUND

This study aimed to investigate the natural growth history of peripheral small-cell lung cancer (SCLC) using CT imaging.

METHODS

A retrospective study was conducted on 27 patients with peripheral SCLC who underwent at least two CT scans. Two methods were used: Method 1 involved direct measurement of nodule dimensions using a calliper, while Method 2 involved tumour lesion segmentation and voxel volume calculation using the "py-radiomics" package in Python. Agreement between the two methods was assessed using the intraclass correlation coefficient (ICC). Volume doubling time (VDT) and growth rate (GR) were used as evaluation indices for SCLC growth, and growth distribution based on GR and volume measurements were depicted. We collected potential factors related to imaging VDT and performed a differential analysis. Patients were classified into slow-growing and fast-growing groups based on a VDT cut-off point of 60 days, and univariate analysis was used to identify factors influencing VDT.

RESULTS

Median VDT calculated by the two methods were 61 days and 71 days, respectively, with strong agreement. All patients had continuously growing tumours, and none had tumours that decreased in size or remained unchanged. Eight patients showed possible growth patterns, with six possibly exhibiting exponential growth and two possibly showing Gompertzian growth. Tumours deeper in the lung grew faster than those adjacent to the pleura.

CONCLUSIONS

Peripheral SCLC tumours grow rapidly and continuously without periods of nongrowth or regression. Tumours located deeper in the lung tend to grow faster, but further research is needed to confirm this finding.

Bronchovascular bundle thickening on CT as a predictor of survival and brain metastasis in patients with stage IA peripheral small cell lung cancer

AIM

To determine if bronchovascular bundle (BVB) thickening on pretreatment computed tomography (CT) images helps predict survival in patients with peripheral small cell lung cancer (pSCLC) ≤3 cm.

MATERIALS AND METHODS

The pretreatment CT examinations of 79 histopathologically proven pSCLC ≤3 cm (TNM stage I, 21; II, 13; III, 22; IV, 23) were reviewed retrospectively. The CT characteristics of the nodule and associated findings, including BVB thickening, were evaluated. Progression-free survival (PFS), overall survival (OS), and brain metastasis-free survival were compared with the presence of BVB thickening using Kaplan-Meier and Cox regression analysis.

RESULTS

Among the 79 patients, 34 (43%) had BVB thickening. BVB thickening was prevalent in patients with mediastinal lymph node metastasis (50.9% versus 22.7%; p=0.024) and distant metastasis (60.9% versus 35.7%; p=0.049). Out of the 21 patients with TNM stage IA disease, the 16 patients (76.2%) without BVB thickening showed better PFS, OS, and brain metastasis-free survival (mean, 1,762 versus 483 days; p=0.019: 2,243 versus 1,328 days; p=0.038: 2,274 versus 1,287 days; p=0.038, respectively). Multivariate Cox regression analysis showed that the absence of BVB thickening (hazard ratio [HR], 7.806; 95% CI, 1.241-49.091; p=0.029) and surgery (HR, 0.075; 95% CI, 0.008-0.746; p=0.027) were independent and useful prognostic factors for PFS.

CONCLUSIONS

BVB thickening was found more frequently in patients with advanced-stage pSCLC ≤3 cm, and the PFS was more favourable in patients without BVB thickening, with a similar tendency to that of OS and brain metastasis-free survival, in stage IA pSCLC.

Diagnostic accuracy of computed tomography imaging for the detection of differences between peripheral small cell lung cancer and peripheral non-small cell lung cancer

Background

To evaluate the computed tomography features of peripheral small cell lung cancer and non-small cell lung cancer and to establish a predictive model to conveniently distinguish between them.

Materials and methods

We retrospectively reviewed the computed tomography features of 51 patients with peripheral small cell lung cancer and 207 patients with peripheral non-small cell lung cancer after pathological diagnosis. Thirteen computed tomography morphologic findings were included and analyzed statistically. Meaningful features were analyzed by logistic regression for multivariate analysis. We then used β-coefficients as the basis to establish an image scoring prediction model.

Result

The meaningful morphologic features for distinguishing between peripheral small cell lung cancer and other tumor types are multinodular shape and lymphadenectasis, with scores of 12 and 11, respectively. The scores ranged from −51 to 23, and the most reasonable cut-off was −24. The available area under the curve was 0.834 (95% confidence interval [CI] 0.783–0.877). Sensitivity and specificity were 86.3% (95% CI 0.737–0.943) and 69.6% (95% CI 0.628–0.758), respectively.

Conclusion

The image scoring predictive model that we constructed provides a simple and economical noninvasive method for distinguishing between peripheral small cell lung cancer and peripheral non-small cell lung cancer.