UNASSIGNED: Effective discrimination of lung adenocarcinoma (LUAD) in situ (AIS) from benign pulmonary nodules (BPN) is critical for the early diagnosis of AIS. Our pilot study in a small cohort of 90 serum samples has shown that serum interleukin 6 (IL-6) detection can distinguish AIS from BPN and health controls (HC). In this study, we intend to comprehensively define the diagnostic value of individual and combined detection of serum IL-6 related to the traditional tumor markers carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA21-1) for AIS.
UNASSIGNED: The diagnostic performance of serum IL-6 along with CEA and CYFRA21-1 were evaluated in a large cohort of 300 serum samples by a chemiluminescence immunoassay and an electrochemiluminescence immunoassay. A training set comprised of 65 AIS, 65 BPN, and 65 HC samples was used to develop the predictive model for AIS. Data obtained from an independent validation set was applied to evaluate and validate the predictive model.
UNASSIGNED: In the training set, the levels of serum IL-6 and CEA in the AIS group were significantly higher than those in the BPN/HC group (P < 0.05). There was no significant difference in serum CYFRA21-1 levels between the AIS group and the BPN/HC group (P> 0.05). Serum IL-6 and CEA levels for AIS patients showed an area under the curve (AUC) of 0.622 with 23.1% sensitivity at 90.7% specificity, and an AUC of 0.672 with 24.6% sensitivity at 97.6% specificity, respectively. The combination of serum IL-6 and CEA presented an AUC of 0.739, with 60.0% sensitivity at 95.4% specificity. The combination of serum IL-6 and CEA showed an AUC of 0.767 for AIS patients, with 57.1% sensitivity at 91.4% specificity in the validation set.
UNASSIGNED: IL-6 shows potential as a prospective serum biomarker for the diagnosis of AIS, and the combination of serum IL-6 with CEA may contribute to increased accuracy in AIS diagnosis. However, it is worth noting that further research is still necessary to validate and optimize the diagnostic efficacy of these biomarkers and to address potential sensitivity limitations.

To investigate the application value of tumor abnormal protein in patients with type 2 diabetes mellitus complicated with lung adenocarcinoma in situ.
A total of 140 patients having type 2 diabetes mellitus complicated with lung adenocarcinoma in situ (Group A), 160 patients with type 2 diabetes mellitus (Group B), and 120 healthy controls (Group C) were enrolled in the Department of Thoracic Surgery of the First Affiliated Hospital of Soochow University from November 2021 to December 2022.
The total cholesterol level was higher in Group A than in Group B (p < 0.05) and Group C (p < 0.01), and it was higher in Group B than in Group C (p < 0.01). The comparison results of cholesterol level were similar to those of tumor abnormal protein, low-density lipoprotein cholesterol, and glycosylated hemoglobin among the three groups. The triglyceride level was higher in Group A than in Group B and Group C (both p < 0.01). Group A had a higher level of high-density lipoprotein cholesterol than Group C (p < 0.01). The fasting plasma glucose level was higher in Group A than in Group B and Group C (both, p < 0.01). These findings indicated that tumor abnormal protein, glycosylated hemoglobin, high-density lipoprotein cholesterol, and fasting plasma glucose were independent factors for patients having type 2 diabetes mellitus complicated with lung adenocarcinoma in situ.
Therefore, detecting tumor abnormal protein levels may help diagnose lung adenocarcinoma in situ in patients with type 2 diabetes mellitus.
The study found that tumor abnormal protein, glycosylated hemoglobin, high-density lipoprotein cholesterol, and fasting plasma glucose were independent factors for patients having type 2 diabetes mellitus complicated with lung adenocarcinoma in situ. Detecting tumor abnormal protein levels may help diagnose lung adenocarcinoma in situ in patients with type 2 diabetes mellitus.

UNASSIGNED: Lung adenocarcinoma is the most common type of lung cancer with highly incidence and mortality. Due to the overlap of morphological features, it is difficult to distinguish clinically between preinvasive lesions (in situ adenocarcinoma, AIS) and invasive lesions (minimally invasive adenocarcinoma, MIA), which appear as ground glass cloudy nodules. This study was performed to probe the application value of artificial intelligence (AI)-based dual source CT scanning in the differentiation of AIS as well as MIA.
UNASSIGNED: The clinical data of 136 patients in Shanghai Baoshan Hospital of Integrated Traditional Chinese and Western Medicine from January 2019 to January 2022 were retrospectively analyzed. The accuracy of AI in distinguishing lung AIS (n=76) and MIA (n=60) were analyzed. The effectiveness of AI in detecting nodules and its diagnostic efficacy for AIS and MIA were explored.
UNASSIGNED: The proportion of patients with clear and regular lesion boundaries in AIS was higher than that in MIA. The mean lesion diameter of AIS patients was shorter than MIA patients. There was no difference in the CT value between AIS and MIA in the ground glass nodule density area of pure ground glass nodule and mixed ground glass nodule, but the CT value of the solid nodule density area in AIS was lower. The occurrence of pulmonary vascular abnormality, air bronchogram sign, and pleural depression in AIS patients were lower than MIA patients. The detection rate of AI for lung adenocarcinoma with nodule diameter ≤ 5 mm, complete solid nodules and ground glass nodules was significantly higher than radiologists. The sensitivity, specificity, positive prediction rate, negative prediction rate and accuracy of AI detection were significantly higher than radiologists.
UNASSIGNED: AI-based dual source CT scanning can clearly show the morphological characteristics of lung adenocarcinoma, which is helpful for the differential diagnosis of lung AIS as well as MIA.