Computed tomography radiomics study of invasion and instability of lung adenocarcinoma manifesting as ground glass nodule.

Background: Ground-glass nodule (GGN) is the most common manifestation of lung adenocarcinoma on computed tomography (CT). Clinically, the success rate of preoperative diagnosis of GGN by puncture biopsy and other means is still low. The aim of this study is to investigate the clinical and radiomics characteristics of lung adenocarcinoma presenting as GGN on CT images using radiomics analysis methods, establish a radiomics model, and predict the classification of pathological tissue and instability of GGN type lung adenocarcinoma. Methods: This study retrospectively collected 249 patients with 298 GGN lesions who were pathologically confirmed of having lung adenocarcinoma. The images were imported into the Siemens scientific research prototype software to outline the region of interest and extract the radiomics features. Logistic model A (a radiomics model to identify the infiltration of lung adenocarcinoma manifesting as GGNs) was established using features after the dimensionality reduction process. The receiver operating characteristic (ROC) curve of the model on training set and the verification set was drawn, and the area under the curve (AUC) was calculated. Second, a total of 112 lesions were selected from 298 lesions originating from CT images of at least two occasions, and the time between the first CT and the preoperative CT was defined as not less than 90 days. The mass doubling time (MDT) of all lesions was calculated. According to the different MDT diagnostic thresholds instability was predicted. Finally, their AUCs were calculated and compared. Results: There were statistically significant differences in age and lesion location distribution between the "noninvasive" lesion group and the invasive lesion group (P<0.05), but there were no statistically significant differences in sex (P>0.05). Model A had an AUC of 0.89, sensitivity of 0.75, and specificity of 0.86 in the training set and an AUC of 0.87, sensitivity of 0.63, and specificity of 0.90 in the validation set. There was no significant difference statistically in MDT between "noninvasive" lesions and invasive lesions (P>0.05). The AUCs of radiomics models B1, B2 and B3 were 0.89, 0.80, and 0.81, respectively; the sensitivities were 0.71, 0.54, and 0.76, respectively; the specificities were 0.83, 0.77, and 0.60, respectively; and the accuracies were 0.78, 0.65, and 0.69, respectively. Conclusions: There were statistically significant differences in age and location of lesions between the "noninvasive" lesion group and the invasive lesion group. The radiomics model can predict the invasiveness of lung adenocarcinoma manifesting as GGNs. There was no significant difference in MDT between "noninvasive" lesions and invasive lesions. The radiomics model can predict the instability of lung adenocarcinoma manifesting as GGN. When the threshold of MDT was set at 813 days, the model had higher specificity, accuracy, and diagnostic efficiency.

Relationships between the coronary fat attenuation index for patients with heart-related disease measured automatically on coronary computed tomography angiography and coronary adverse events and degree of coronary stenosis.

Background: Pericoronary artery coronary tissue (PACT) is a type of epicardial fat that can reflect the state of the coronary artery (inflammation, etc.). However, it cannot be reasonably and efficiently utilized in routine computed tomography (CT) examination. The aim of this study was to use artificial intelligence (AI) software to analyze coronary computed tomography angiography (CCTA) and measure the coronary perivascular fat attenuation index (FAI) of patients. The relationship between FAI and the occurrence of coronary adverse events and the degree of coronary stenosis were further analyzed. Methods: This study involved patients who experienced CCTA in West China Hospital, Sichuan University, from January 2012 to December 2012. These patients were followed up to 2020 and classified according to the occurrence of coronary adverse events and the degree of stenosis of the lumen. For all patients, AI software was used to analyze the CCTA images of patients, and the FAI of 3 coronary arteries, the left anterior descending artery (LAD), the left circumflex artery (LCX), and the right coronary artery (RCA), was measured. Moreover, the relationship between FAI and patients with different degrees of coronary stenosis and adverse coronary events was determined. Results: Comparisons between any 2 groups showed that the differences in the FAI among the 4 groups for the LAD were significant (all P values <0.05). There were no significant differences between the group with less-than-moderate stenosis (Mb) without adverse events and the group with moderate-or-above stenosis (M) with no adverse events for the LCX (P>0.05). For the remaining groups, FAI values exhibited statistically significant differences (P<0.05). According to the degree of lumen stenosis, the patients were divided into groups according to LAD, LCX, and RCA and the sum of the 3 vessels. There were significant differences in coronary FAI among the groups with different degrees of lumen stenosis for the sum of the 3 vessels, the LAD, and the LCX (P<0.05). Conclusions: FAI can reflect the state of the coronary artery, which is related to inflammation of the coronary lumen. Moreover, there is a relationship between FAI and the degree of stenosis in the coronary lumen: the narrower the coronary lumen is, the higher the FAI around the lumen.

Clinical characterization of EFHD2 (swiprosin-1) in Glioma-associated macrophages and its role in regulation of immunosuppression.

Glioblastoma has been extensively studied due to its high mortality and short survival. The evolution mechanism of tumor-associated macrophages (TAMs) to Glioma-associated microglia and macrophages (GAMs) in the tumor microenvironment (TME) remains to be elucidated. The tumor cell-to-cell interaction patterns have not been well defined yet. The EF-Hand Domain Family Member D2 (EFHD2) has been reported to be differentially expressed as an immunomodulatory molecule in a variety of cancers. But large-scale clinical data from multiple ethnic communities have not been used to investigate the role of EFHD2 in glioma. RNA-seq data from 313 or 657 glioma patients from the Chinese Glioma Genome Atlas (CGGA) database and 603 glioma patients from the Cancer Genome Atlas (TCGA) database were analyzed retrospectively. Cell localization was performed using single-cell sequencing data from the CGGA database and the GSE131928 dataset. Mouse glioma cell lines and primary macrophages isolated from Efhd2 knockout mice were co-cultured to validate the immunomodulatory effects of EFHD2 on macrophages and the remodeling of TME of glioblastoma. EFHD2 is enriched in high-grade gliomas, isocitrate dehydrogenase wild-type, and 1p/19q non-co-deficient gliomas. It is a potential biomarker of glioma-proneuronal subtypes and an independent prognostic factor for overall survival in patients with malignant glioblastoma. EFHD2 regulates the monocyte-macrophage system function and positively correlates with immunosuppressive checkpoints. Further experimental data demonstrates that Efhd2 influences the polarization state of GAMs and inhibits the secretion of TGF-ß1. In vitro experiments have revealed that macrophages lacking Efhd2 suppress the vitality of two glioma cell lines and decelerate the growth of glioma xenografts. In conclusion, EFHD2 promises to be a key target for TME-related immunotherapy.

Case report: A double pathogenic mutation in a patient with late-onset MELAS/PEO overlap syndrome.

Mitochondrial encephalopathy, lactic acidosis, and stroke-like episodes (MELAS) and progressive external ophthalmoplegia (PEO) are established phenotypes of mitochondrial disorders. They are maternally-inherited, multisystem disorder that is characterized by variable clinical, biochemical, and imaging features. We described the clinical and genetic features of a Chinese patient with late-onset MELAS/PEO overlap syndrome, which has rarely been reported. The patient was a 48-year-old woman who presented with recurrent ischemic strokes associated with characteristic brain imaging and bilateral ptosis. We assessed her clinical characteristics and performed mutation analyses. The main manifestations of the patient were stroke-like episodes and seizures. A laboratory examination revealed an increased level of plasma lactic acid and a brain MRI showed multiple lesions in the cortex. A muscle biopsy demonstrated ragged red fibers. Genetic analysis from a muscle sample identified two mutations: TL1 m.3243A>G and POLG c.3560C>T, with mutation loads of 83 and 43%, respectively. This suggested that mitochondrial disorders are associated with various clinical presentations and an overlap between the syndromes and whole exome sequencing is important, as patients may carry multiple mutations.