Transcriptome- and metabolome-based candidate mechanism of BCR-ABL-independent resistance to olverembatinib in Philadelphia chromosome-positive acute lymphoblastic leukemia.

Olverembatinib represents the third-generation breakpoint cluster region protein-Abelson-murine leukemia 1 (BCR-ABL1) tyrosine kinase inhibitor with oral bioavailability, which can be used to overcome the T315I mutation in Philadelphia chromosome-positive (Ph +) leukemia. BCR-ABL-independent resistance to olverembatinib has been reported among patients in various clinical cases. However, the mechanism of olverembatinib resistance has rarely been reported. This study has illustrated bone marrow cell transcriptome and metabolome profiles among Ph + acute lymphoblastic leukemias (ALL) cases pre- and post-olverembatinib resistance. The transcriptome studies demonstrated that PI3K/AKT, purine metabolism, and other signaling pathways could play a vital role in olverembatinib resistance. As suggested by metabolomics, olverembatinib resistance in Ph + ALL was associated with purine metabolism alterations. Subsequently, high-performance liquid chromatography along with real-time quantitative PCR was utilized to measure purine metabolism-related mRNA levels and metabolism expression levels between olverembatinib resistance and sensitive cell lines. Our results elucidate the mechanism of olverembatinib resistance in Ph + ALL at transcriptome and metabolome levels, which facilitate a better understanding of olverembatinib resistance and hence may prove crucial in identifying novel drugs to tackle this conundrum.

Electrochemiluminescent CdS Quantum Dots Biosensor for Cancer Mutation Detection at Different Positions on Linear DNA Analytes.

PCR-based techniques routinely employed for the detection of mutated linear DNA molecules, including circulating tumor DNA (ctDNA), require large nucleotide sections on both sides of the mutation for primer annealing. This means that DNA fragments with a mutation positioned closer to the extremities are unlikely to be detected. Thus, sensors capable of recognizing linear DNA with characteristic mutations closer to the ends would be advantageous over the state-of-the-art approaches. Here, an electrochemiluminescence-resonance energy transfer (ECL-RET) biosensor comprising capped CdS quantum dots and hairpin DNA probes labeled with Au nanoparticles was developed for the detection of epidermal growth factor receptor (EGFR) ctDNA carrying the critical T790M lung cancer mutation. The ECL-RET system detected different DNA molecules including single-stranded 18-nucleotides (nt) and 40-nt as well as double-stranded 100-nt with the single nucleotide polymorphism (SNP) coding for T790M located either in the middle or only 7 nt from one end. For all target DNA, the sensor's limits of detection (LODs) were in the aM range, with excellent selectivity. It was the case of 100-nt target linear ctDNA fragments with LODs of 8.1 and 3.4 aM when the EGFR T790M SNP was either in the middle or at the end, respectively. These results show that ECL-RET systems can sense mutations in DNA fragments that would remain undetected by standard techniques.

The diagnostic value of CT-guided percutaneous puncture biopsy of pulmonary ground-glass nodules: a meta-analysis.

BACKGROUND: More and more pulmonary ground-glass nodules (GGNs) are screened with the extensive usage of low-dose computed tomography (CT). The need of CT-guided percutaneous puncture biopsy of GGN remains controversial. PURPOSE: To explore the diagnostic accuracy of CT-guided percutaneous puncture biopsy of GGNs. MATERIAL AND METHODS: We searched PubMed, EMBASE, the Cochrane Library, and CNKI. Included studies reported the puncture biopsy results of pulmonary GGNs, including the number of true positive (TP), false positive (FP), true negative (TN), and false negative (FN) cases. After evaluating the studies, statistical analysis, and quality assessment, the pooled diagnostic sensitivity (SEN), specificity (SPE), and diagnostic odds ratio (DOR) were calculated. The summary receiver operating characteristic (SROC) curve was constructed and the area under the curve (AUC) was calculated. Subgroup analysis was performed according to whether spiral CT or fluoroscopy-guided CT was used in the study. RESULTS: This meta-analysis included 14 studies with a total of 759 patients (702 samples). The pooled SEN, SPE, and DOR of CT-guided puncture biopsy of pulmonary GGNs were 0.91 (95% confidence interval [CI] = 0.89-0.94), 0.99 (95% CI = 0.95-1.00), and 138.72 (95% CI = 57.98-331.89), respectively. The AUC was 0.97. CONCLUSION: Our results indicated that CT-guided puncture biopsy of GGNs has high SEN, SPE, and DOR, which proved that CT-guided puncture biopsy was a good way to determine the pathological nature of GGN.

Bioinformatics Analysis and Experimental Study of Exonuclease 1 Gene in Lung Adenocarcinoma.

The objective of this study is to examine the role of Human Exonuclease 1(EXO1) gene in the diagnosis and prognosis of lung adenocarcinoma (LUAD), and predict the signal pathways EXO1 involved in. The clinical parameters and EXO1 expression datasets of LUAD patients were obtained from The Cancer Genome Atlas (TCGA), Oncomine and Gene Expression Omnibus (GEO) database. Wilcoxon rank-sum test was performed to determine whether EXO1 expression was upregulated in LUAD. The correlation between EXO1 expression and clinicopathological parameters was analyzed by Chi-square test, and Kaplan-Meier survival analysis and COX regression models were adopted to analyze and verify the correlation of EXO1 expression with OS of LUAD patients for the exploration of prognostic value of EXO1 in LUAD patients. The signaling pathway related to EXO1 was predicted by gene set enrichment analysis (GSEA). In addition, sera from LUAD patients and healthy subjects were collected, and real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) was conducted to detect EXO1 expression. EXO1 expression was upregulated in LUAD patients with respect to normal individuals. EXO1 expression was negatively correlated with the prognosis and thus could independently predict the prognosis of LUAD patients. EXO1 gene was involved in 128 signal pathways, of which 9 pathways may be closely related. EXO1 was highly expressed in the blood of LUAD patients. High EXO1 expression can serve as an independent risk factor for poor prognosis, and the expression of serum EXO1 has certain diagnostic value for LUAD.

Pathological study of the 2019 novel coronavirus disease (COVID-19) through postmortem core biopsies.

Data on pathologic changes of the 2019 novel coronavirus disease (COVID-19) are scarce. To gain knowledge about the pathology that may contribute to disease progression and fatality, we performed postmortem needle core biopsies of lung, liver, and heart in four patients who died of COVID-19 pneumonia. The patients' ages ranged from 59 to 81, including three males and one female. Each patient had at least one underlying disease, including immunocompromised status (chronic lymphocytic leukemia and renal transplantation) or other conditions (cirrhosis, hypertension, and diabetes). Time from disease onset to death ranged from 15 to 52 days. All patients had elevated white blood cell counts, with significant rise toward the end, and all had lymphocytopenia except for the patient with leukemia. Histologically, the main findings are in the lungs, including injury to the alveolar epithelial cells, hyaline membrane formation, and hyperplasia of type II pneumocytes, all components of diffuse alveolar damage. Consolidation by fibroblastic proliferation with extracellular matrix and fibrin forming clusters in airspaces is evident. In one patient, the consolidation consists of abundant intra-alveolar neutrophilic infiltration, consistent with superimposed bacterial bronchopneumonia. The liver exhibits mild lobular infiltration by small lymphocytes, and centrilobular sinusoidal dilation. Patchy necrosis is also seen. The heart shows only focal mild fibrosis and mild myocardial hypertrophy, changes likely related to the underlying conditions. In conclusion, the postmortem examinations show advanced diffuse alveolar damage, as well as superimposed bacterial pneumonia in some patients. Changes in the liver and heart are likely secondary or related to the underlying diseases.

COVID-19 in Hemodialysis Patients: A Report of 5 Cases.

In December 2019, an outbreak of coronavirus disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began in China and spread rapidly worldwide. It is unknown whether hemodialysis patients represent a distinct group of patients with certain characteristics that may make them susceptible to infection or severe disease. In this case report, we describe the clinical and epidemiologic features of COVID-19 infection in 201 maintenance hemodialysis patients in Zhongnan Hospital of Wuhan University, including 5 maintenance hemodialysis patients who contracted COVID-19 infection. Of the 5 patients with COVID-19 infection, one had a definite history of contact with an infected person. The age range of the patients was 47 to 67 years. Diarrhea (80%), fever (60%), and fatigue (60%) were the most common symptoms. Lymphopenia occurred in all patients. Computed tomography of the chest showed ground glass opacity in the lungs of all patients. Up to February 13, 2020, none of the patients had developed severe complications (acute respiratory distress syndrome, shock, or multiple organ dysfunction) or died.

Subclassification of BI-RADS 4 Magnetic Resonance Lesions: A Systematic Review and Meta-Analysis.

OBJECTIVE: This research aims to investigate and evaluate the diagnostic efficacy of magnetic resonance imaging (MRI) in classifying Breast Imaging Reporting and Data System (BI-RADS) 4 lesions into subcategories: 4a, 4b, and 4c, so as to limit biopsies of suspected lesions in the breast. METHODS: The PubMed, Web of Science, Embase, and Cochrane Library foreign language databases were searched for literature published between January 2000 and July 2018. After analyzing the selection, data extraction, and quality assessment, a meta-analysis was performed, including data pooling, heterogeneity testing, and meta-regression. RESULTS: Fourteen articles, including 18 studies, met the inclusion criteria. The diagnostic efficacy of MRI for BI-RADS 4-weighted summary assay sensitivity and specificity were estimated at 0.95 [95% confidence interval (CI), 0.89-0.98] and 0.87 (95% CI, 0.81-0.91), respectively. The positive and negative likelihood ratios were 7.1 (95% CI, 4.7-10.7) and 0.06 (95% CI, 0.02-0.14), respectively. The diagnostic odds ratio was 126 (95% CI, 37-426), and the area under the receiver operating characteristic curve was 0.95 (95% CI, 0.93-0.97). The malignancy ratio of BI-RADS 4a, 4b, and 4c and malignancy range were 2.5% to 18.3%, 23.5% to 57.1%, and 58.0% to 95.2%, respectively. CONCLUSION: Risk stratification of suspected lesions (BI-RADS categories 4a, 4b, and 4c) can be achieved by MRI. The MRI is an effective auxiliary tool to further subclassify BI-RADS 4 lesions and prevent unnecessary biopsy of BI-RADS 4a lesions.

Magnetic Resonance Imaging Texture Analysis in Differentiating Benign and Malignant Breast Lesions of Breast Imaging Reporting and Data System 4: A Preliminary Study.

RATIONALE AND OBJECTIVES: This novel study aims to investigate texture parameters in distinguishing malignant and benign breast lesions classified as Breast Imaging Reporting and Data System 4 in dynamic contrast-enhanced magnetic resonance imaging (MRI). MATERIALS AND METHODS: This retrospective study included 203 patients with 136 breast cancer and 67 benign lesions who underwent breast MRI between November 23, 2016, and August 27, 2018. Co-occurrence matrix-based texture features were extracted from each lesion on T1-weighted contrast-enhanced MRI using MatLab software. The association between texture parameters and breast lesions was analyzed, and the diagnostic model for breast cancer was created. Classification performance was evaluated by the area under the receiver operating characteristic curve, sensitivity, and specificity. RESULTS: Significant differences were seen between malignant and benign lesions for a number of textural features, including contrast, correlation, autocorrelation, dissimilarity, cluster shade, and cluster performance (P < 0.05). After the analysis of the multicollinearity, 5 texture features (contrast, correlation, dissimilarity, cluster shade, and cluster performance) were included for the next principal component analysis. The differentiation accuracy of breast cancer based on the diagnostic model was 0.948 (95% confidence interval, 0.908-0.974). CONCLUSIONS: Texture features that measure randomness, heterogeneity, or homogeneity may reflect underlying growth patterns of breast lesions and show great difference in malignant and benign lesions. Therefore, texture analysis may be a valuable assisted tool for diagnostic analysis on breast.

CT and clinical characteristics that predict risk of EGFR mutation in non-small cell lung cancer: a systematic review and meta-analysis.

INTRODUCTION: To systematically analyze CT and clinical characteristics to find out the risk factors of epidermal growth factor receptor (EGFR) mutation in non-small cell lung cancer (NSCLC). Then the significant characteristics were used to set up a mathematic model to predict EGFR mutation in NSCLC. MATERIALS AND METHODS: PubMed, Web of Knowledge and EMBASE up to August 17, 2018 were systematically searched for relevant studies that investigated the evidence of association between CT and clinical characteristics and EGFR mutation in NSCLC. After study selection, data extraction, and quality assessment, the pooled odds ratios (ORs) were calculated. Then from May 2017 to August 2018, all NSCLC received EGFR mutation examination and CT examination in our hospital were chosen to test the prediction model by receiver operating characteristic (ROC) curves. RESULTS: Seventeen original studies met the inclusion criteria. The results showed that the ORs of ground-glass opacity (GGO), air bronchogram, pleural retraction, vascular convergence, smoking history, female gender were, respectively, 1.93 (P = 0.003), 2.09 (P = 0.03), 1.59 (P < 0.01), 1.61 (P = 0.001), 0.28 (P < 0.01), 0.35 (P < 0.01). The result of speculation, cavitation/bubble-like lucency, lesion shape, margin, pathological stage were, respectively, 1.19 (P = 0.32), 0.99 (P = 0.97), 0.82 (P = 0.42), 1.02 (P = 0.90), 0.77 (P = 0.30). 121 NSCLC received EGFR mutation test were included to test the prediction model. The mathematical model based on the results of meta-analysis was: 0.74 × air bronchogram + 0.46 × pleural retraction + 0.48 × vascular convergence - 1.27 × non-smoking history - 1.05 × female. The area under the ROC curve was 0.68. CONCLUSION: Based on the current evidence, GGO presence, air bronchogram, pleural retraction, vascular convergence were significant risk factors of EGFR mutation in NSCLC. And the prediction model can help to predict EGFR mutation status.

Associations between clinical data and computed tomography features in patients with epidermal growth factor receptor mutations in lung adenocarcinoma.

BACKGROUND: To analyse the differences in computed tomography (CT) features between patients with lung adenocarcinoma who have epidermal growth factor receptor (EGFR) mutations and those who have wild-type EGFR. METHODS: Patients with lung adenocarcinoma (n = 156) were enrolled from October 2013 to March 2016, including 56 patients with wild-type EGFR and 100 patients with EGFR mutations. Two independent radiologists evaluated patient characteristics and imaging features. Chi-squared test, Fisher's exact test or ANOVA was applied to discriminate clinical and CT characteristics between the genotypes. A prediction tool for EGFR mutation was devised from principal component analysis. RESULTS: The proportion of females and non-smokers in the exon 19 deletion and exon 21 missense groups was higher than in the wild-type group (P < 0.01). Severe emphysema was higher in the wild-type group than in the exon 19 deletion group (P < 0.01). The maximum diameter in the mediastinal window (MaxDmediastinal) in the wild-type group was longer than in the exon 19 deletion and exon 21 missense groups. The minimum diameter in the mediastinal window (MinDmediastinal) in the wild-type group was also longer than in the exon 21 missense group, with a significant difference (P < 0.05). The tumor shadow disappearance rate (TDR) in the exon 19 deletion group was higher than in the wild-type group. Ground glass opacity (GGO) appeared to be more common in the exon 19 deletion group (P = 0.010). The prediction score for exon 19 deletion mutation was: 0.305 × gender + 0.254 × smoking history + 0.198 × MaxDmediastinal + TDR × 0.254 + 0.280 × GGO + 0.095 × emphysema. The sensitivity and specificity for predicting exon 19 deletion were 59.09 and 76.79%, respectively. The prediction score for the exon 21 missense mutation was: 0.354 × gender + 0.291 × smoking history + 0.410 × MaxDmediastinal + 0.408 × MinDmediastinal. The sensitivity and specificity for predicting exon 21 missense mutation were 72.34 and 78.57%, respectively. CONCLUSION: As well as gender, smoking history and GGO, adenocarcinomas with EGFR mutation were significantly associated with emphysema, TDR, and the diameter in the mediastinal window. As exon 19 deletion and 21 missense mutations might be predicted by those features, the scoring system might be valuable for clinical diagnosis.

Prognostic value of the maximum standardized uptake value of pre-treatment primary lesions in small-cell lung cancer on 18F-FDG PET/CT: a meta-analysis.

Background 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) has been widely used in clinical practice. However, the prognostic value of the pre-treatment standardized uptake value (SUV) for patients with small-cell lung cancer (SCLC) remains controversial. Purpose To investigate the prognostic role of pre-treatment 18F-FDG PET on SCLC patients by meta-analysis. Material and Methods Extensive literature searches of the PubMed, EMBASE, Web of Science, and Cochrane Library databases were conducted to identify literature published until 5 May 2017. Comparative analyses of the pooled hazard ratios (HRs) for event-free survival (EFS) and overall survival (OS) were performed to assess their correlations with the pre-treatment maximum SUV (SUVmax). Either the fixed- or the random-effects model was adopted, depending on the heterogeneity observed across the studies. Subgroup analyses were performed to assess the robustness of the results. Results Twelve studies with 1062 patients were included. The pooled HR for OS of 11 studies was 1.13 (95% confidence interval [CI] = 1.05-1.22; P = 0.001; I2 = 0%) and the pooled HR for EFS of nine studies was 1.09 (95% CI = 1.02-1.17; P = 0.014; I2 = 0%), indicating that patients with high SUVs may have poorer prognoses. Begg's test detected no significant publication bias. The prognostic role of the SUVmax remained similar in the subgroup analyses. Conclusion Our meta-analysis indicated that the pre-treatment SUVmax of primary lesions can be an important prognostic factor for OS and EFS in patients with SCLC. A high SUVmax may indicate poorer prognosis.

Measurements of myocardial bridges on computed tomography predict presence of clinical symptoms and outcomes of adverse heart events: a retrospective study in a large population from China.

Background Clinical-radiological correlation of myocardial bridge (MB) remains unclear. Purpose To correlate clinical symptoms and outcomes of MBs with computed tomography (CT) coronary angiography findings. Material and Methods A total of 2092 patients with CT coronary angiography were collected. Patients were divided into symptomatic and asymptomatic groups, adverse heart events (AHE) and non-AHE groups, MB and non-MB groups, as well as left anterior descending (LAD)-MB and non-LAD-MB groups. Statistical analyses were performed to identify inter-group differences, and clinical-radiological correlations of MBs or mural coronary arteries (MCAs). Results The prevalence of MB, the MCA stenosis either in systole or in diastole, and the ratio of LAD-MB were significantly higher in the symptomatic group than in the asymptomatic group, and higher in the AHE group than in the non-AHE group ( P all <0.05). MB thickness, systolic MCA stenosis, and diastolic MCA stenosis were independent variables predicting clinical symptoms ( P < 0.05), with diastolic MCA stenosis having the highest diagnostic performance, when cutting at 24.6%. The corresponding sensitivity and specificity were 87.8% and 90.6%, respectively. Diastolic MCA stenosis independently indicated outcome of AHE (odds ratio, 1.047; P < 0.001). Conclusion Measurements of MB-MCA by CT predict the presence of clinical symptoms and outcomes of AHE, with diastolic MCA stenosis possessing the greatest performance.

Ultrasound, computed tomography or magnetic resonance imaging - which is preferred for acute appendicitis in children? A Meta-analysis.

BACKGROUND: There is no established consensus about the relative accuracies of US, CT and MRI in childhood appendicitis. OBJECTIVE: To compare, through meta-analysis, the accuracies of US, CT and MRI for clinically suspected acute appendicitis in children. MATERIALS AND METHODS: PubMed, Embase, Web of Science and the Cochrane Library were searched. After study selection, data extraction and quality assessment, the sensitivity, specificity and the area under the curve of summary receiver operating characteristic were calculated and compared. RESULTS: Twenty-seven articles including 29 studies met the inclusion criteria, including 19 studies (9,170 patients) of US, 6 studies (928 patients) of CT and 4 studies (990 patients) of MRI. The analysis showed that the area under the receiver operator characteristics curve of MRI (0.995) was a little higher than that of US (0.987) and CT (0.982; P > 0.05). CONCLUSION: US, CT and MRI have high diagnostic accuracies of clinically suspected acute appendicitis in children overall with no significant difference.

Sagittal-lung CT measurements in the evaluation of asthma-COPD overlap syndrome: a distinctive phenotype from COPD alone.

OBJECTIVES: This study aimed at investigating the capability of sagittal-lung computed tomography (CT) measurements in differentiating chronic obstructive pulmonary disease (COPD) and asthma-COPD overlap syndrome (ACOS). METHODS: Clinical and high-resolution CT of 229 patients including 123 pure COPD patients and 106 ACOS patients were included. Sagittal-lung CT measurements in terms of bilateral lung height (LH), anterior-posterior lung diameter (APLD), diaphragm height (DH), and anterior sterno-diaphragmatic angle (ASDA), as well as inter-pulmonary septum length (IPSL) on axial images were measured both before and after bronchodilator (BD) administration. Comparisons of clinical characteristics and CT measurements between patient groups were performed. RESULTS: All pre-BD quantitative sagittal features measuring diaphragm flattening and hyperinflation were not significantly different between patients with COPD and patients with ACOS (P values all >0.05). Following BD administration, the ACOS patients exhibited lower left LH, bilateral APLD, and bilateral ASDA, but higher right DH, compared to pure COPD patients (P values all <0.05). Right LH, left DH and IPSL were not significantly different between patient groups. Besides, variations of all sagittal-lung CT measurements were significantly larger in patients with ACOS than in patients with pure COPD (P values all <0.001) and showed high performance in differentiating these two kinds of patient, with diagnostic sensitivities ranging from 76.4 to 97.2%, specificities ranging from 86.2 to 100.0%, and accuracies ranging from 80.9 to 90.7%. CONCLUSIONS: Sagittal-lung CT measurements allow for differentiating patients with ACOS from those with pure COPD. The ACOS patients had larger post-BD variations of sagittal-lung CT measurements than patients with pure COPD.

Correlation between carcinoembryonic antigen (CEA) expression and EGFR mutations in non-small-cell lung cancer: a meta-analysis.

OBJECTIVES: The purpose of this meta-analysis was to investigate the relationship between serum carcinoembryonic antigen (CEA) expression and epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC). METHODS: Databases such as PubMed, Cochrane, EMBASE and Google Scholar were systematically searched to identify studies assessing the association of serum CEA expression with EGFR mutations. Across 19 studies, 4168 patients were included between CEA expression and EGFR mutations odds ratio (OR) conjoint analysis of correlations. RESULTS: Compared with CEA-negative NSCLC, CEA-positive tumors had an increased EGFR mutation rate (OR = 1.85, 95% confidence interval: 1.48-2.32, P < 0.00001). This association was observed in both stage IIIB/IV patients (OR = 1.60, 95% CI: 1.18-2.15, P = 0.002) and stage I-IIIA (OR = 1.67, 95% CI: 1.01-2.77, P = 0.05) patients. In addition, CEA expression was associated with exon 19 (OR = 1.97, 95% CI: 1.25-3.11, P = 0.003) and exon 21 (OR = 1.51, 95% CI: 1.07-2.12, P = 0.02) EGFR mutations. In ADC pathological type had also showed the correlation (OR = 1.84, 95% CI: 1.31-2.57, P = 0.0004). CONCLUSIONS: This meta-analysis indicated that serum CEA expression was associated with EGFR mutations in NSCLC patients. The results of this study suggest that CEA level may play a predictive role in the EGFR mutation status of NSCLC patients. Detecting serum CEA expression levels can give a good suggestion to those patients who are confused about whether to undergo EGFR mutation tests. Moreover, it may help better plan of the follow-up treatment.

Risk factors for air embolism following computed tomography-guided percutaneous transthoracic needle biopsy: a systematic review and meta-analysis

To quantitatively analyze the risk factors for air embolism following computed tomography (CT)-guided percutaneous transthoracic needle biopsy (PTNB) and qualitatively review their characteristics. The databases of PubMed, Embase, Web of Science, Wanfang Data, VIP information, and China National Knowledge Infrastructure were searched on January 4, 2021, for studies reporting the occurrence of air embolisms following CT-guided PTNB. After study selection, data extraction, and quality assessment, the characteristics of the included cases were qualitatively and quantitatively analyzed. A total of 154 cases of air embolism following CT-guided PTNB were reported. The reported incidence was 0.06% to 4.80%, and 35 (22.73%) patients were asymptomatic. An unconscious or unresponsive state was the most common symptom (29.87%). Air was most commonly found in the left ventricle (44.81%), and 104 (67.53%) patients recovered without sequelae. Air location (P < 0.001), emphysema (P = 0.061), and cough (P = 0.076) were associated with clinical symptoms. Air location (P = 0.015) and symptoms (P < 0.001) were significantly associated with prognosis. Lesion location [odds ratio (OR): 1.85, P = 0.017], lesion subtype (OR: 3.78, P = 0.01), pneumothorax (OR: 2.16, P = 0.003), hemorrhage (OR: 3.20, P < 0.001), and lesions located above the left atrium (OR: 4.35, P = 0.042) were significant risk factors for air embolism. Based on the current evidence, a subsolid lesion, being located in the lower lobe, the presence of pneumothorax or hemorrhage, and lesions located above the left atrium were significant risk factors for air embolism.

Predicting N2 lymph node metastasis in presurgical stage I-II non-small cell lung cancer using multiview radiomics and deep learning method.

BACKGROUND: Accurate diagnosis of N2 lymph node status of the resectable stage I-II non-small cell lung cancer (NSCLC) before surgery is crucial, while there is lack of corresponding method clinically. PURPOSE: To develop and validate a model to quantitively predict the N2 lymph node metastasis in presurgical clinical stage I-II NSCLC using multiview radiomics and deep learning method. METHODS: In this study, 140 NSCLC patients were enrolled and randomly divided into training and test sets. Univariate and multiple analysis method were used step by step to establish the clinical model; Then a multiview radiomics modeling scheme was designed, in which the optimal input feature set was determined by subcategorizing radiomics features (C1: original; C2: LoG and C3: wavelet) and comparison of corresponding radiomics model. The minimum-redundancy maximum-relevance (mRMR) selection and the least absolute shrinkage and selection operator (LASSO) algorithm were used for the feature selection and construction of each radiomics model (Rad). Next, an end-to-end ResNet18 architecture and transfer learning techniques were designed to construct a deep learning model (DL). Subsequently, the screened clinical risk factors and constructed Rad and DL models were combined and compared and a nomogram was constructed. Finally, the diagnostic performance of all constructed models were evaluated and compared using receiver operating characteristic curve (ROC) analysis, Delong test, Calibration analysis, Hosmer-Lemeshow test, and decision curves, respectively. RESULTS: Carcinoma embryonic antigen (CEA) level and spiculation were screened to make up the Clinical model, while seven radiomics features in the optimal input feature set C2 + C3 were selected to construct the Rad. DL was constructed by training on 1.8 million natural images and small sample data of our N2 lymph node volume of interest (VOI) images. Except for the Clinical model, all other models showed good predictive accuracy and consistency in both training set and test set. DL (area under curve (AUC): 0.83) was better than Rad (AUC: 0.76) in predictive accuracy, but their difference was not significant (p = 0.45). The combined models showed better diagnostic performance than the model only clinical or image risk factors were used (AUC for Clinical, Rad + DL, Rad + Clinical, DL + Clinical, and Rad + DL + Clinical were respectively 0.66, 0.86, 0.82, 0.86, and 0.88). Finally, the Rad + DL + Clinical model with the best diagnostic performance was selected to draw the final nomogram for clinical use. CONCLUSION: This study proposes a nomogram based on multiview radiomics, deep learning, and clinical features that can be efficiently used to quantitively predict presurgical N2 diseases in patients with clinical stage I-II NSCLC.

CT radiomics model combined with clinical and radiographic features for discriminating peripheral small cell lung cancer from peripheral lung adenocarcinoma.

Purpose: Exploring a non-invasive method to accurately differentiate peripheral small cell lung cancer (PSCLC) and peripheral lung adenocarcinoma (PADC) could improve clinical decision-making and prognosis. Methods: This retrospective study reviewed the clinicopathological and imaging data of lung cancer patients between October 2017 and March 2022. A total of 240 patients were enrolled in this study, including 80 cases diagnosed with PSCLC and 160 with PADC. All patients were randomized in a seven-to-three ratio into the training and validation datasets (170 vs. 70, respectively). The least absolute shrinkage and selection operator regression was employed to generate radiomics features and univariate analysis, followed by multivariate logistic regression to select significant clinical and radiographic factors to generate four models: clinical, radiomics, clinical-radiographic, and clinical-radiographic-radiomics (comprehensive). The Delong test was to compare areas under the receiver operating characteristic curves (AUCs) in the models. Results: Five clinical-radiographic features and twenty-three selected radiomics features differed significantly in the identification of PSCLC and PADC. The clinical, radiomics, clinical-radiographic and comprehensive models demonstrated AUCs of 0.8960, 0.8356, 0.9396, and 0.9671 in the validation set, with the comprehensive model having better discernment than the clinical model (P=0.036), the radiomics model (P=0.006) and the clinical-radiographic model (P=0.049). Conclusions: The proposed model combining clinical data, radiographic characteristics and radiomics features could accurately distinguish PSCLC from PADC, thus providing a potential non-invasive method to help clinicians improve treatment decisions.

Primary pulmonary cryptococcosis: evaluation of CT characteristics in 26 immunocompetent Chinese patients.

BACKGROUND: Discrepancies still exist in the diagnosis of primary pulmonary cryptococcosis in immunocompetent patients. PURPOSE: To describe and evaluate radiological manifestations of pulmonary cryptococcosis in immunocompetent patients. MATERIAL AND METHODS: Twenty-six histopathologically confirmed cases of pulmonary cryptococcosis were analyzed for clinical, pathological, and CT characteristics. Necessary statistical tests for differences in CT presentations and correlation analysis between clinical and CT characteristics were performed. RESULTS: The patients' ages ranged from 24 to 79 years, with 20 men and six women. Eighteen patients were symptomatic, with cough as the most common symptom (n = 14, 53.8%). Nodules (n = 21, 80.8%) were the most common CT findings. Eight cases presented with solitary and nine with multiple nodules, while 13 cases presented with irregular and 19 with ill-defined nodules. The halo sign was demonstrated, encompassing nodules in 14 of the 21 patients. Lesions were mainly localized in the lower lobes of the lungs (n = 15, 57.7%) with peripheral distribution (n = 18, 69.2%). Ground-glass opacities (GGOs) were more easily detected in older patients (66.7%, P <0.01). No significant differences in CT abnormalities were found between male and female patients. CONCLUSION: Primary pulmonary cryptococcosis in immunocompetent patients exhibits certain CT characteristics. The typical presentation includes multiple nodules with the halo sign scattered in the peripheral field in the lower lobes of the bilateral lungs. This could contribute to diagnosis of the disease entity. However, vigilance should be exercised when facing GGOs, with or without nodules, in older patients.