Application and progress of non-invasive imaging in predicting lung invasive non-mucinous adenocarcinoma under the new IASLC grading guidelines.

Lung cancer is the leading cause of cancer-related deaths worldwide, with invasive non-mucinous adenocarcinoma (INMA) being the most common type and carrying a poor prognosis. In 2020, the International Association for the Study of Lung Cancer (IASLC) pathology committee proposed a new histological grading system, which offers more precise prognostic assessments by combining the proportions of major and high-grade histological patterns. Accurate identification of lung INMA grading is crucial for clinical diagnosis, treatment planning, and prognosis evaluation.

PET/CT radiomics and deep learning in the diagnosis of benign and malignant pulmonary nodules: progress and challenges.

Lung cancer is currently the leading cause of cancer-related deaths, and early diagnosis and screening can significantly reduce its mortality rate. Since some early-stage lung cancers lack obvious clinical symptoms and only present as pulmonary nodules (PNs) in imaging examinations, accurately determining the benign or malignant nature of PNs is crucial for improving patient survival rates. F-FDG PET/CT is important in diagnosing PNs, but its specificity needs improvement.

Metabolic tumour area: a novel prognostic indicator based on F-FDG PET/CT in patients with diffuse large B-cell lymphoma in the R-CHOP era.

Background: The metabolic tumour area (MTA) was found to be a promising predictor of prostate cancer. However, the role of MTA based on F-FDG PET/CT in diffuse large B-cell lymphoma (DLBCL) prognosis remains unclear. This study aimed to elucidate the prognostic significance of MTA and evaluate its incremental value to the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) for DLBCL patients treated with first-line R-CHOP regimens.

Transfer learning-based PET/CT three-dimensional convolutional neural network fusion of image and clinical information for prediction of EGFR mutation in lung adenocarcinoma.

Background: To introduce a three-dimensional convolutional neural network (3D CNN) leveraging transfer learning for fusing PET/CT images and clinical data to predict EGFR mutation status in lung adenocarcinoma (LADC).

Methods: Retrospective data from 516 LADC patients, encompassing preoperative PET/CT images, clinical information, and EGFR mutation status, were divided into training (n = 404) and test sets (n = 112). Several deep learning models were developed utilizing transfer learning, involving CT-only and PET-only models.

New research progress on 18F-FDG PET/CT radiomics for EGFR mutation prediction in lung adenocarcinoma: a review.

Lung cancer, the most frequently diagnosed cancer worldwide, is the leading cause of cancer-associated deaths. In recent years, significant progress has been achieved in basic and clinical research concerning the epidermal growth factor receptor (EGFR), and the treatment of lung adenocarcinoma has also entered a new era of individualized, targeted therapies. However, the detection of lung adenocarcinoma is usually invasive.

F-FDG PET-CT for the prediction of mortality in patients with dermatomyositis and without malignant tumors: a pilot study.

Background: F-fluorodeoxyglucose positron emission tomography-computed tomography (F-FDG PET-CT) is typically used to screen malignancy in patients with dermatomyositis (DM). The aim of this study was to investigate the value of using PET-CT in assessing the prognosis of patients with DM and without malignant tumors.

Methods: A total of 62 patients with DM who underwent F-FDG PET-CT were enrolled in the retrospective cohort study.

Quantitative evaluation of acute myocardial infarction by feature-tracking cardiac magnetic resonance imaging.

Objective: To assess the value of feature-tracking cardiac magnetic resonance (FT-CMR) imaging in the quantitative evaluation of acute myocardial infarction (AMI).

Methods: We retrospectively analyzed medical records of patients with acute myocardial infarction (AMI) diagnosed in the Department of Cardiology of Hubei No.3 People's Hospital of Jianghan University from April 2020 to April 2022, who underwent feature-tracking cardiac magnetic resonance (FT-CMR) examination.

Predicting the negative conversion time of nonsevere COVID-19 patients using machine learning methods.

Based on the patient's clinical characteristics and laboratory indicators, different machine-learning methods were used to develop models for predicting the negative conversion time of nonsevere coronavirus disease 2019 (COVID-19) patients. A retrospective analysis was performed on 376 nonsevere COVID-19 patients admitted to Wuxi Fifth People's Hospital from May 2, 2022, to May 14, 2022. The patients were divided into training set (n = 309) and test set (n = 67).

The predictive value of [F]FDG PET/CT radiomics combined with clinical features for EGFR mutation status in different clinical staging of lung adenocarcinoma.

Background: This study aims to construct radiomics models based on [F]FDG PET/CT using multiple machine learning methods to predict the EGFR mutation status of lung adenocarcinoma and evaluate whether incorporating clinical parameters can improve the performance of radiomics models.

Methods: A total of 515 patients were retrospectively collected and divided into a training set (n = 404) and an independent testing set (n = 111) according to their examination time. After semi-automatic segmentation of PET/CT images, the radiomics features were extracted, and the best feature sets of CT, PET, and PET/CT modalities were screened out.

Association Analysis of Maximum Standardized Uptake Values Based on F-FDG PET/CT and EGFR Mutation Status in Lung Adenocarcinoma.

(1) Background: To investigate the association between maximum standardized uptake value (SUV) based on F-FDG PET/CT and EGFR mutation status in lung adenocarcinoma. (2) Methods: A total of 366 patients were retrospectively collected and divided into the EGFR mutation group ( = 228) and EGFR wild-type group ( = 138) according to their EGFR mutation status. The two groups' general information and PET/CT imaging parameters were compared.

Association between squamous cell carcinoma antigen level and EGFR mutation status in Chinese lung adenocarcinoma patients.

Background: To investigate the association between squamous cell carcinoma antigen (SCCAg) level and epidermal growth factor receptor (EGFR) mutation status in Chinese lung adenocarcinoma patients.

Methods: We retrospectively analyzed 293 patients with lung adenocarcinoma, divided into EGFR mutant group (n = 178) and EGFR wild-type group (n = 115). The general data and laboratory parameters of the two groups were compared.

Risk analysis in peripheral clinical T1 non-small cell lung cancer correlations between tumor-to-blood standardized uptake ratio on F-FDG PET-CT and primary tumor pathological invasiveness: a real-world observational study.

Background: Sublobar resection is not suitable for patients with pathological invasiveness [including lymph node metastasis (LNM), visceral pleural invasion (VPI), and lymphovascular invasion (LVI)] of peripheral clinical T1 (cT1) non-small cell lung cancer (NSCLC), while primary tumor maximum standardized uptake value (SUV) on F-FDG PET-CT is related to pathological invasiveness, the significance differed among different institutions is still challenging. This study explored the relationship between the tumor-to-blood standardized uptake ratio (SUR) of F-FDG PET-CT and primary tumor pathological invasiveness in peripheral cT1 NSCLC patients.

Methods: This retrospective study included 174 patients with suspected lung neoplasms who underwent preoperative F-FDG PET-CT.

Maximum Standardized Uptake Value of F-deoxyglucose PET Imaging Increases the Effectiveness of CT Radiomics in Differentiating Benign and Malignant Pulmonary Ground-Glass Nodules.

To investigate whether the maximum standardized uptake value (SUVmax) of F-deoxyglucose (FDG) PET imaging can increase the diagnostic efficiency of CT radiomics-based prediction model in differentiating benign and malignant pulmonary ground-glass nodules (GGNs). We retrospectively collected 190 GGNs from 165 patients who underwent F-FDG PET/CT examination from January 2012 to March 2020. Propensity score matching (PSM) was performed to select GGNs with similar baseline characteristics.

The relationship between brain glucose metabolism and insulin resistance in subjects with normal cognition - a study based on 18F-FDG PET.

Objective: Insulin resistance can increase the risk of cognitive dysfunction and dementia. Our purpose is to use 18F-FDG PET imaging to explore the effect of insulin resistance on brain glucose metabolism in cognitively normal subjects.

Methods: A total of 189 cognitively normal subjects who underwent PET examinations were enrolled.

Application of dual-stream 3D convolutional neural network based on F-FDG PET/CT in distinguishing benign and invasive adenocarcinoma in ground-glass lung nodules.

Purpose: This work aims to train, validate, and test a dual-stream three-dimensional convolutional neural network (3D-CNN) based on fluorine 18 (F)-fluorodeoxyglucose (FDG) PET/CT to distinguish benign lesions and invasive adenocarcinoma (IAC) in ground-glass nodules (GGNs).

Methods: We retrospectively analyzed patients with suspicious GGNs who underwent F-FDG PET/CT in our hospital from November 2011 to November 2020. The patients with benign lesions or IAC were selected for this study.

A negative association between low-density lipoprotein cholesterol level and infection risk in elderly stage 5 chronic kidney disease patients.

Background: To explore the relationship between low-density lipoprotein cholesterol (LDL-C) level and infection risk in elderly stage 5 kidney disease (CKD) patients.

Methods: This study retrospectively analyzed all 378 patients with grade 5 CKD over 60 years old treated in the Nephrology Department of our hospital from February 2014 to July 2019, including 286 cases with infection and 92 cases without. According to LDL-C levels, the patients were divided into three groups (Tertile 1-Tertile 3).

Association Analysis of Insulin Resistance and Osteoporosis Risk in Chinese Patients with T2DM.

Background: To explore the relationship between insulin resistance and osteoporosis risk in Chinese patients with type 2 diabetes mellitus (T2DM).

Methods: A total of 234 T2DM patients were retrospectively analyzed, and their lumbar bone mineral density (BMD) and insulin resistance using C-peptide-based homeostasis model of insulin resistance [HOMA-IR (CP)] were assessed. Univariate and multivariable logistic regression methods were used to evaluate the association between HOMA-IR (CP) and osteoporosis, and subgroup analysis was performed on female and male patients.

Investigating the association between ground-glass nodules glucose metabolism and the invasive growth pattern of early lung adenocarcinoma.

Background: To explore the association between the glucose metabolism level of lung ground-glass nodules (GGNs), as revealed by F-flurodeoxyglucose positron emission tomography/computed tomography (F-FDG PET/CT) imaging, and the invasive pathological growth pattern of early lung adenocarcinoma.

Methods: We retrospectively analyzed patients who underwent PET/CT examination and surgical resection due to persistent GGNs, which were confirmed to be early lung adenocarcinoma by postoperative pathology examination. After adjusting for confounding factors and performing stratified analysis, we explored the association between the maximum standard uptake value of PET (SUVmax) and the invasive pathological growth pattern of early stage lung adenocarcinoma.

Preoperative 18F-FDG SUVmax >6.3 or Size >2.3 cm of primary lesions predict lymph nodes metastasis with higher negative predictive value in peripheral cT1 non-small-cell lung cancer.

Background: Sublobar resection is suitable for peripheral cT1N0M0 non-small-cell lung cancer (NSCLC). The traditional PET-CT criterion (lymph node size ≥1.0 cm or SUVmax ≥2.

[The value of circulating microRNA-1 in the early diagnosis of coronary atherosclerotic plaque rupture in patients with stable coronary heart disease].

Objective: To evaluate the diagnostic value of circulating microRNA-1 (miR-1) in early coronary artery plaque rupture in patients with stable coronary artery disease (SCAD).

Methods: A prospective cohort study was conducted. Sixty-seven patients with SCAD admitted to the department of cardiology of the Third Affiliated Hospital of Soochow University from January to June in 2019 were enrolled.

Establishment and verification of a prediction model based on clinical characteristics and positron emission tomography/computed tomography (PET/CT) parameters for distinguishing malignant from benign ground-glass nodules.

Background: To develop and verify a prediction model for distinguishing malignant from benign ground-glass nodules (GGNs) combined with clinical characteristics and F-fluorodeoxyglucose (FDG) positron emission tomography-computed tomography (PET/CT) parameters.

Methods: We retrospectively analyzed 170 patients (56 males and 114 females) with GGNs who underwent PET/CT and high-resolution CT examination in our hospital from November 2011 to December 2019. The clinical and imaging data of all patients were collected, and the nodules were randomly divided into a derivation set and a validation set.

Association Between F-FDG PET/CT-Based SUV Index and Malignant Status of Persistent Ground-Glass Nodules.

To explore the association between F-FDG PET/CT-based SUV index and malignant risk of persistent ground-glass nodules (GGNs). We retrospectively analyzed a total of 166 patients with GGN who underwent PET/CT examination from January 2012 to October 2019. There were 113 women and 53 men, with an average age of 60.

FGD5‑AS1 promotes cisplatin resistance of human lung adenocarcinoma cell via the miR‑142‑5p/PD‑L1 axis.

Previous studies have reported that long non‑coding (lnc) RNA FGD5‑antisense 1 (FGD5‑AS1) promotes tumor proliferation, migration and invasion. Therefore, the present study aimed to elucidate the biological role and underlying molecular mechanisms of FGD5‑AS1 in cisplatin (DDP) resistance of lung adenocarcinoma (LAD) cells. The results demonstrated that FGD5‑AS1 was highly expressed in DDP‑resistant LAD tissues and cells.

Application of a Prediction Model Based on the Laboratory Index Score in Prelabor Rupture of Membranes with Histologic Chorioamnionitis During Late Pregnancy.

BACKGROUND This study aimed to establish a prediction model based on the maternal laboratory index score (Lab-score) for histologic chorioamnionitis (HCA) in patients with prelabor rupture of membranes (PROM) during late pregnancy. MATERIAL AND METHODS Sixty-nine cases of pregnant women with PROM were retrospectively analyzed. The general information and laboratory indicators were compared between the HCA (n=22) and non-HCA (n=47) groups.