[Research Advances and Obstacles of CT-based Radiomics in Diagnosis and Treatment of Lung Cancer]

[Progress in Diagnosis and Treatment of Lung Cancer Associated with Cystic Airspaces]

Lung cancer associated with cystic airspaces (LCCA) is a type of lung cancer characterized by the presence of cystic cavities in or around the tumor on imaging. Due to its high potential for misdiagnosis or underdiagnosis, the prognosis of LCCA patients is poor, necessitating further large-scale clinical studies to elucidate its characteristics. Currently, four imaging classification systems exist, and there has been a progressive increase in attention towards LCCA, particularly with regard to the study of its imaging features. The results indicate a correlation between the pathological features and imaging findings of LCCA; however, research on driver gene mutations and molecular subtyping associated with lung cancer remains insufficient. Due to the challenges associated with early diagnosis and the poorer prognosis compared to general types of lung cancer, this paper comprehensively reviews the research progress on LCCA, including its definition, etiology, pathogenesis, imaging features, histological and pathological features, treatment, and prognosis, aiming to serve as a valuable resource for clinical decision-making.
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Prognostic significance of TG/HDL-C and non-HDL-C/HDL-C ratios in patients with non-small cell lung cancer: a retrospective study

OBJECTIVE

Lung cancer is a malignancy with high a mortality rate that threatens human health. This study is aimed to explore the correlation among the triglyceride/high-density lipoprotein ratio (TG/HDL-C), non-high-density lipoprotein/high-density lipoprotein ratio (non-HDL-C/HDL-C) and survival of patients with non-small cell lung cancer (NSCLC) undergoing video-associated thoracic surgery (VATS).

METHODS

This retrospective study analyzed 284 patients with NSCLC who underwent VATS at Hebei General Hospital, Shijiazhuang, China. The time-dependent receiver operating characteristic curve was used to determine the optimal cutoff value and evaluate the area under the curve. Kaplan-Meier and Cox regression analyses were performed to determine the prognostic effect.

RESULTS

The median overall survival (OS) was 46 months. Patients with low TG/HDL-C and low non-HDL-C/HDL-C had a longer OS. The low non-HDL-C/HDL-C group showed a longer mean survival time (59.00 vs. 52.35 months). Multivariate analysis revealed that TG/HDL-C and non-HDL-C/HDL-C were significantly correlated with OS.

CONCLUSIONS

TG/HDL-C and non-HDL-C/HDL-C are associated with the prognosis of patients with NSCLC who received VATS. Preoperative serum TG/HDL-C and non-HDL-C/HDL-C may be effective independent prognostic factors for predicting the outcomes of patients with NSCLC.

Interventions of Advanced Lung Cancer Patient Receiving Chemotherapy by Computed Tomography Image Information Data Analysis-Based Soothing Care Plans

The objective of this study was to investigate the intervention effect of computed tomography (CT) image information data on patients with advanced lung cancer treated with chemotherapy under palliative care program. The research subjects were 60 patients with advanced lung cancer who received palliative care in our hospital from January 1, 2019, to January 1, 2021. All patients were grouped according to the evaluation criteria of solid tumor efficacy, including 28 patients in the remission group and 32 patients in the nonremission group. Texture analysis was performed on the CT images of the two groups of patients. The gray-scale cooccurrence matrix parameters, the maximum diameter of the lesion, and the CT value of the CT images of the two groups of patients before and after palliative care were compared. The results showed that after the palliative care, the combined mean, combined energy, and inverse moment of the three gray cooccurrence matrix parameters of the two groups of patients were decreased, and the combined entropy and contrast were increased. The absolute value of the gray-scale cooccurrence matrix Δ parameter of the patients in the remission group was greater than that in the nonremission group. The Δ combined entropy, Δ contrast, and Δ correlation of the two groups of patients were significantly different, and the difference in Δ contrast was the largest. It suggested that the gray-scale cooccurrence matrix parameter can evaluate the effect of soothing care, and the contrast was the best evaluation parameter. The maximum diameter of the lesions in the remission group before and after palliative care was reduced by 1.23 cm, and the degree of reduction was significantly better. The CT value was reduced by 6.22 HU, and the degree of reduction was significantly higher than that in the nonremission group. There was a significant difference in the data between the two groups (P < 0.05). Therefore, the CT image information data had a better evaluation effect on patients with advanced lung cancer under the palliative care program and can be applied to the clinical evaluation of the palliative care effect, which had good clinical value.

Assessment and Prognostic Value of Immediate Changes in Post-Ablation Intratumor Density Heterogeneity of Pulmonary Tumors via Radiomics-Based Computed Tomography Features

Objectives

To retrospectively observe the instantaneous changes in intratumor density heterogeneity after microwave ablation (MWA) of lung tumors and to determine their prognostic value in predicting treatment response and local tumor progression (LTP).

Methods

Pre- and post-MWA computed tomography (CT) images of 50 patients (37-males; 13-females; mean-age 65.9 ± 9.7y, 39 primary and 11 metastasis) were analyzed to evaluate changes in intratumor density. Global, regional, and local scale radiomics features were extracted to assess intratumor density heterogeneity. In four to six weeks, chest enhanced CT was used as the baseline evaluation of treatment response. The correlations between the parametric variation immediately after ablation and the visual score of ablation response (Rvisu) were analyzed by nonparametric Spearman correlation analysis. The 1-year LTP discrimination power was assessed using the area under the receiver operating characteristic (ROC) curves. A Cox proportional hazards regression model was used to identify the independent prognostic features.

Results

Although no significant volume changes were observed after ablation, the radiomics parameters changed in different directions and degrees. The mean intensity value from baseline CT image was 30.3 ± 23.2, and the post-MWA CT image was -60.9 ± 89.8. The ratio of values change was then calculated by a unified formulation. The largest increase (522.3%) was observed for cluster prominence, while the mean CT value showed the largest decline (321.4%). The pulmonary tumors had a mean diameter of 3.4 ± 0.8 cm. Complete ablation was documented in 36 patients. Significant correlations were observed between Rvisu and quantitative features. The highest correlations were observed for changes in local features after MWA, with r ranging from 0.594 to 0.782. LTP developed in 22 patients. The Cox regression model revealed Δcontrast% and response score as independent predictors (Δcontrast%: odds ratio [OR]=5.61, p=0.001; Rvisu: OR=1.73, p=0019). ROC curve analysis showed that Δcontrast% was a better predictor of 1-year LTP. with higher sensitivity (83.5% vs. 71.2%) and specificity (87.1% vs. 76.8%) than those for Rvisu.

Conclusions

The changes in intratumor density heterogeneity after MWA could be characterized by analysis of radiomics features. Real-time density changes could predict treatment response and LTP in patients with pulmonary tumors earlier, especially for tumors with larger diameters.