Lung Cancer Lesions Research Articles

Lung adenocarcinoma: selection of surgical approaches in solid adenocarcinoma from the viewpoint of clinicopathologic features and tumor microenvironmental heterogeneity.

Solid adenocarcinoma represents a notably aggressive subtype of lung adenocarcinoma. Amidst the prevailing inclination towards conservative surgical interventions for diminutive lung cancer lesions, the critical evaluation of this subtype's malignancy and heterogeneity stands as imperative for the formulation of surgical approaches and the prognostication of long-term patient survival. A retrospective dataset, encompassing 2406 instances of non-solid adenocarcinoma (comprising lepidic, acinar, and papillary adenocarcinoma) and 326 instances of solid adenocarcinoma, was analyzed to ascertain the risk factors concomitant with diverse histological variants of lung adenocarcinoma. Concurrently, RNA-sequencing data delineating explicit pathological subtypes were extracted from 261 cases in the TCGA database and 188 cases in the OncoSG database. This data served to illuminate the heterogeneity across lung adenocarcinoma (LUAD) specimens characterized by differential histological features. Solid adenocarcinoma is associated with an elevated incidence of pleural invasion, microscopic vessel invasion, and lymph node metastasis, relative to other subtypes of lung adenocarcinoma. Furthermore, the tumor microenvironment (TME) in solid pattern adenocarcinoma displayed suboptimal oxygenation and acidic conditions, concomitant with augmented tumor cell proliferation and invasion capacities. Energy and metabolic activities were significantly upregulated in tumor cells of the solid pattern subtype. This subtype manifested robust immune tolerance and capabilities for immune evasion. This present investigation identifies multiple potential metrics for evaluating the invasive propensity, metastatic likelihood, and immune resistance of solid pattern adenocarcinoma. These insights may prove instrumental in devising surgical interventions that are tailored to patients diagnosed with disparate histological subtypes of LUAD, thereby offering valuable directional guidance.

Image-Guided VATS in the Hybrid Operation Room Facilitates Early Diagnosis and Concurrent Treatment of Subcentimeter Nonpalpable Lung Nodules.

As lung cancer screening increases, the detection of small, nonpalpable lung lesions is on the rise. The hybrid operation room (OR), which combines percutaneous or endobronchial fiducial placement with on-table computed tomography (CT) and fluoroscopic guidance, improves localization and facilitates the diagnosis and treatment of smaller, nonpalpable lung nodules with greater accuracy. In 35 consecutive months, 55 veterans underwent 60 image-guided video-assisted thoracic surgery procedures for lesion resection. Of the cases, 36% were found during lung cancer screening. All patients received their care in the hybrid OR, where cone-beam CT scan technology was used to place an average of 1.6 fiducials percutaneously (n = 55) or via augmented navigational bronchoscopy (n = 5). A total of 66 lesions were resected. The median lesion size was 8 mm with an interquartile range of 6 to 14. The patients underwent nonanatomical resection with lymph node dissection using radiologic guidance. When indicated, an anatomical resection was subsequently performed. Of 47 total non-small cell lung cancer lesions, 83% were diagnosed at stage IA1 or IA2. The median surgical margin was 15 mm; the margin was usually 1.5 times as wide as the lesion. The hybrid OR technology gives a 3-dimensional assessment of the small lung lesions, allowing for a tissue-saving resection while achieving good surgical margins. During lung cancer screening, smaller, nonpalpable lung nodules are frequently found. This technology allows resection of subcentimeter lesions, which would otherwise be unresectable at this early stage, possibly improving survival.

Correlation between iron metabolism indicators and programmed death ligand 1 expression in advanced non-small cell lung cancer.

The dysregulation of iron metabolism is closely linked to the onset and progression of lung cancer. This study aimed to explore the association between iron metabolism indicators (serum iron, transferrin, ferritin) and the expression level of programmed death factor ligand 1 in primary lesions of advanced non-small cell lung cancer. A cohort of 62 patients, including 42 men and 20 women, was recruited from October 2022 to July 2023, all diagnosed with advanced non-small cell lung cancer, confirmed through radiographic imaging and histopathological analysis. Comprehensive clinical data (such as gender, age, familial lung cancer history, smoking history, pathological classification, clinical stage, etc.) and concentrations of fasting serum iron, transferrin, and ferritin were collected. Patients were categorized into PD-L1 negative (<1% expression) and programmed death ligand 1 (PD-L1) positive (≥1% expression) groups based on PD-L1 expression levels in tumor tissues. Subsequently, the correlation between levels of serum iron, transferrin, ferritin, and PD-L1 expression in advanced non-small cell lung cancer were examined. Patients in the PD-L1 positive group exhibited lower levels of peripheral serum iron and transferrin compared to those in the PD-L1 negative group (P<0.05). For patients exhibiting positive PD-L1 expression, a negative correlation was observed between PD-L1 expression and both serum iron and transferrin levels (r = -0.465, P=0.003; r = -0.447, P=0.005), and a positive correlation was noted between PD-L1 expression and ferritin levels (r=0.393, P=0.015). We conclude that in In patients with advanced non-small cell lung cancer, serum iron and transferrin levels can serve as partial predictors of PD-L1 expression; among those positive for PD-L1, a significant association exists between indicators of iron metabolism and PD-L1 expression.

Chinese expert consensus: multidisciplinary diagnosis and treatment of multiple ground-glass nodule like lung cancer (2024 edition)

Multiple ground glass nodules (GGN) like lung cancer is a special type of synchronous multiple primary lung cancer, with two or more lesions present simultaneously. It has characteristics such as"indolent"development, less lymph node or distant metastasis, identical or different pathological stages, differential driving gene mutations, diverse imaging manifestations, and good prognosis. In order to standardize the diagnosis and treatment behavior of multiple GGN-like lung cancer, reduce issues such as over diagnosis and insufficient treatment, relevant domestic experts are organized by The Lung Cancer Medical Education Committee of the Chinese Medical Education Association, Lung Cancer Alliance of Chinese Thoracic Surgery, the Society of Tumor Ablation Therapy of the Chinese Anti-Cancer Association, the Tumor Ablation Expert Committee of the Chinese Society of Clinical Oncology, the Tumor Ablation Expert Group of the Chinese College of Interventionalists, The Chinese Expert Consensus:Multidisciplinary Diagnosis and Treatment of Multiple Ground-Glass Nodule Like Lung Cancer (2024 Edition) was discussed and formulated. The main content includes: follow-up strategies, differential diagnosis, diagnosis and staging, treatment methods, and post treatment follow-up for multiple GGN-like lung cancer.

GAN-based medical image small region forgery detection via a two-stage cascade framework.

Using generative adversarial network (GAN) Goodfellow et al. (2014) for data enhancement of medical images is significantly helpful for many computer-aided diagnosis (CAD) tasks. A new GAN-based automated tampering attack, like CT-GAN Mirsky et al. (2019), has emerged. It can inject or remove lung cancer lesions to CT scans. Because the tampering region may even account for less than 1% of the original image, even state-of-the-art methods are challenging to detect the traces of such tampering. This paper proposes a two-stage cascade framework to detect GAN-based medical image small region forgery like CT-GAN. In the local detection stage, we train the detector network with small sub-images so that interference information in authentic regions will not affect the detector. We use depthwise separable convolution and residual networks to prevent the detector from over-fitting and enhance the ability to find forged regions through the attention mechanism. The detection results of all sub-images in the same image will be combined into a heatmap. In the global classification stage, using gray-level co-occurrence matrix (GLCM) can better extract features of the heatmap. Because the shape and size of the tampered region are uncertain, we use hyperplanes in an infinite-dimensional space for classification. Our method can classify whether a CT image has been tampered and locate the tampered position. Sufficient experiments show that our method can achieve excellent performance than the state-of-the-art detection methods.

Pulmonary Tuberculosis and Lung Cancer – Innate Immunity and the Evolutionary Links of Microbe-induced Inflammation with Cancer: A Case Series

Lung cancer is a chronic inflammatory disease. Postprimary tuberculosis (PPTb) is also a manifestation of chronic lung inflammation induced by Mycobacterium tuberculosis. Both acute and chronic inflammation are macrophage-mediated responses. Persistent lung lesions of both PPTb and lung cancer result from chronic nonresolving inflammation. Metabolic adaptation of macrophages through evolutionarily conserved pathways is termed as macrophage polarization. Progressive inflammation induced by microbes activates metabolic alterations in the tissue microenvironment and consequent tumorigenesis by M2-polarized macrophages. The M2 macrophages are poorly bactericidal, permitting intracellular microbial persistence. Both host and microbes undergo metabolic adaptations through hypoxia-inducible factor-induced gene induction. Three cases of PPTb progressing to lung cancer are presented. All cases were initially smear positive for acid-fast bacilli, and progressed to lung cancer while on antituberculosis treatment. Progressive lung inflammation in these cases induced by M. tuberculosis resulted in the progression of infection-induced inflammation to cancer. Smoking and diabetes were risk factors for progression to lung cancer.

Characteristics of whole-body dynamic 18F-FDG PET/CT Patlak multi-parametric imaging in lung cancer and the influence of different delineation methods on quantitative parameters.

Dynamic course of flourine-18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) Patlak muti-parametric imaging spatial distribution in the targeted tissues may reveal highly useful clinical information about the tissue's metabolic properties. The characteristics of the Patlak multi-parametric imaging in lung cancer and the influence of different delineation methods on quantitative parameters may provide reference for the clinical application of this new technology. A total of 27 patients with pathologically diagnosed lung cancer underwent whole-body dynamic 18F-FDG PET/CT examination before treatment. Parametric images of metabolic rate of FDG (MRFDG) and Patlak intercept (or distribution volume; DV) were generated using Patlak reconstruction. The values of primary lung cancer lesions, target-to-background ratio (TBR), and contrast-to-noise ratio (CNR) were investigated using contour delineation and boundary delineation. Statistical analysis was performed to analyze the relationship between multi-parametric images and clinicopathological features, and to compare the effects of contour delineation and boundary delineation on quantitative parameters. MRFDG images showed higher TBR and CNR than did standardized uptake value (SUV) images. There were significant differences in MRFDG-max, MRFDG-mean, and MRFDG-peak among groups with different tumor diameters and pathology types (P<0.05). Moreover, the metabolic parameters of MRFDG were higher in patients with tumor diameters ≥3 cm and squamous carcinoma. The differences of the maximum and peak values of MRFDG and DV were not statistically significant in the different outlining method subgroups (all P>0.05). However, the difference of the mean values of MRFDG and DV were statistically significant in the different outline method groupings (all P<0.05). Dynamic 18F-FDG PET/CT Patlak multi-parametric imaging can obtain quantitative values for lung cancer with high TBR and CNR. Moreover, the multi-parameters are various from different pathology types to tumor size. Different delineation methods have a greater influence on the mean value of quantitative parameters.

10022-MET-2 CLINICAL FEATURES OF RENAL CELL CARCINOMA BRAIN METASTASES COMPARED WITH OTHER CARCINOMAS

Abstract INTRODUCTION In recent years, the positioning of surgical treatment for metastatic brain tumors has changed. To extract conditions suitable for surgical treatment, the background factors for each primary lesion were verified by retrospective analysis of our case. SUBJECTS AND METHODS From 2014 to 2022, 425 patients with metastatic brain tumors diagnosed and treated at our university were included. There were 219 lung cancers, 46 breast cancers, 64 gastrointestinal cancers, 26 renal cell carcinomas, and 70 others. First, the tumor volume and edema volume were measured, and the ROC curve was drawn for the presence or absence of symptoms to determine the cutoff value. After that, statistical analysis was performed on the following items for each primary lesion. The items were tumor volume (T), edema volume (E), tumor edema ratio (E/T), age, KPS, hemorrhage, cyst formation, meningitis, metastasis to other organs, posterior fossa, simultaneous detection, and single tumor. RESULTS The symptomatic cutoff was 1514mm3 for tumor volume (sensitivity 0.86 specificity 0.74) and 15616 mm3 for edema volume (sensitivity 0.85 specificity 0.85). The tumor edema ratio was significantly higher in renal cell carcinoma. Factors with significant differences were older age and multiple lesions in lung cancer, younger age and posterior fossa in breast cancer, lower KPS in gastrointestinal cancer, and solitary cases and bleeding in renal cell carcinoma. DISCUSSION/CONCLUSION In this analysis, many cases of brain metastasis from renal cell carcinoma are solitary, and because they exhibit extensive edema that seems to be affected by VEGF, they tend to develop symptoms while they are small, and they are characterized by hemorrhage easily during the course. These findings suggest that patients with brain metastases from renal cell carcinoma should be given priority for surgical treatment.

Abstract C110: Mobile low dose computerized tomographic (LDCT) scanning program identifies pre-malignant lung cancer lesions in a Native American population: A study of Indian Health Service and Levine Cancer Institute

Abstract BACKGROUND: Native Americans (NA) are an under-served population for healthcare, including lung cancer screening. Randomized trials have shown LDCT screening for lung cancer improves survival but with severe under-representation of NA due to financial and insurance constraints, geography and lack of access. They are over-represented in national statistics of presentation with advanced disease and lung cancer deaths. In our region, the Indian Health Service (IHS) has recorded less than 5% of eligible heavy smokers from the Catawba and other tribes have undergone LDCT lung screening. We previously reported that a free, mobile LDCT unit achieved a shift to earlier diagnosis in African Americans (AAs) and other under-served groups with improved 4 year survival and reduced costs of care (1).We adapted our initial trial to include a structured evaluation of efficacy and utility of mobile LDCT in heavy smokers in our NA population. We hypothesized that mobile LDCT would overcome key obstructions to lung cancer screening in NA. METHODS: We used a coach fitted with a portable 32 slice low-dose CT scanner; all films were reviewed by a central panel via the LUNGRADS protocol (1). Eligible subjects were invited to participate by IHS staff. Levine Cancer Institute committed to treat any identified cancers, irrespective of insurance status to avoid delay. Technical details of the unit have been reported (1). RESULTS: 91 heavy smokers have been screened, representing 60% participation rate, with the following characteristics: M:F=1:1; median age 61 years (44-77 years); 68% had some form of health insurance which did not cover lung cancer screening (termed "under-insured") and 32% were uninsured; 73% still smoking; median pack year history 48 (range 22-98). No lung cancers were identified but 10% had LUNGRADS 3-4 (moderate-high risk) lesions, 36% had LUNGRADS 2 lesions and 20% had scattered, non-diagnostic lung lesions; patients with LUNGRADS 4 lesions were offered biopsy to define whether cancer was present. All subjects have been recruited into ongoing follow up LDCT and smoking cessation programs. DISCUSSION: NA traditionally have had the highest level of advanced lung cancer at presentation with high mortality rate from lung cancer. We have increased participation in LDCT lung cancer screening from 5% to 60% of eligible heavy smokers, and have identified a unique sub-population of 10% with potentially premalignant disease that will require meticulous follow-up to achieve early diagnosis of lung cancer. Our previous studies in impoverished AAs and other under-served groups have identified a shift from 20% to 60% early stage cancer at diagnosis; similar benefits are expected in NAs. This is the first such study in NAs and suggests mobile LDCT should be considered by health services responsible for their care. Studies of the science of cancer in the under-served should also focus on pragmatic solutions with potential for early improvement in outcome. REFERENCES: 1. Raghavan D et al, The Oncologist, 2020, 25: e777-e781. Citation Format: Kia Dungan, Hollis Reed, Darcy Doege, Daniel Carrizosa, Melissa Wheeler, Derek Raghavan. Mobile low dose computerized tomographic (LDCT) scanning program identifies pre-malignant lung cancer lesions in a Native American population: A study of Indian Health Service and Levine Cancer Institute [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr C110.

Development and validation of a nomogram for predicting the overall survival in non-small cell lung cancer patients with liver metastasis.

Among all metastatic lesions in non-small cell lung cancer (NSCLC), liver metastasis (LM) is the most lethal site with a median survival of less than 5 months. Few studies exclusively report on prognostic factors for these unique patients. We aimed to construct and validate a practical model to predict the prognosis of NSCLC patients with LM. Cases of NSCLC with LM diagnosed between 2010 and 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database, and were randomly split into training and validation cohort (7:3). The overall survival (OS) was measured from diagnosis until date of death or last follow-up. Cox regression analyses were performed to identify potential predictors of the model. A nomogram incorporating those independent factors was constructed and validated by the concordance index (C-index) and calibration plots. The decision curve analysis (DCA) and a risk stratification system were used to evaluate its clinical value. A total of 2,367 cases were selected for analysis and randomized to the training cohort (n=1,677) and the validation cohort (n=690). The patients were mainly male (59.3%), married (83.1%) and White (77.3%). Apart from LM, 54.2%, 26.7%, and 36.7% of patients also present with bone, brain, and lung metastases, respectively. The median follow-up was 4.0 months for all patients and 23 months for alive cases. The median OS was 5 months [interquartile range (IQR), 2-11 months]. Sex, age, race, grade, T stage, bone metastasis, brain metastasis, surgery, and chemotherapy were identified as the independent risk factors of the OS and used to develop the nomogram. The calibration curves exhibited excellent agreement between the predicted and actual survival in both the training and validation set, with a C-index of 0.700 [95% confidence interval (CI): 0.684-0.716] and 0.677 (95% CI: 0.653-0.701), respectively. The DCA and the risk classification system further supported that the prediction model was clinically effective. This is the first study to build a prediction model for NSCLC patients with LM. It aids in treatment decisions, focused care, and physician-patient communication. The global prospective data is needed to further improve this model.

Should sampling of three N2 stations be a quality metric for curative resection of stage I lung cancer?

ObjectiveIn 2022, the American College of Surgeons Commission on Cancer issued standard 5.8 quality metric for curative lung cancer resections requiring nodal resection from 3 N2 stations. In this report, we compare oncologic outcomes after resection of 3 N2 stations versus 2 N2 stations in stage I non–small cell lung cancer. MethodsA retrospective review from a single institution database was conducted from 2011 to 2020 to identify patients with clinical stage I non–small cell lung cancer. Patients with a history of lung cancer, carcinoid tumors, and ground-glass lesions less than 50% solid component were excluded. The primary outcome was overall survival. Secondary outcomes included disease-free survival, recurrence patterns, and nodal upstaging. ResultsA total of 581 patients were identified and divided into 2 groups based on the number of N2 stations examined: Group A had 2 N2 stations examined (364 patients), and group B had 3 or more N2 stations examined (217 patients). Baseline demographic and clinical characteristics were similar between groups. In group A, N1 and N2 positive nodal stations were present in 8.2% (30/364) and 5.2% (19/364) of patients versus 7.4% (16/217) and 5.5% (12/217), respectively, in group B. Five-year overall survival and disease-free survival were 89% and 74% in group A versus 88% and 78% in group B, respectively. Recurrence occurred in 56 patients (15.4%) in group A (6.6% local and 8.8% distant) and 29 patients (13.4%) in group B (5.1% local and 8.3% distant; P = .73). ConclusionsThere was no significant difference in oncological outcomes in stage I non–small cell lung cancer resections that included 2 N2 stations compared with at least 3 N2 stations examined.

Feasibility analysis of low-dose CT with asynchronous quantitative computed tomography to assess vBMD

BackgroundTo explore the feasibility of low-dose computed tomography (LDCT) with asynchronous quantitative computed tomography (asynchronous QCT) for assessing the volumetric bone mineral density (vBMD).Methods416 women patients, categorized into 4 groups, were included and underwent chest CT examinations combined with asynchronous QCT, and CT scanning dose protocols (LDCT or CDCT) were self-determined by the participants. Radiation dose estimations were retrieved from patient protocols, including volume CT dose index (CTDIvol) and dose-length-product (DLP), and then calculated effective dose (ED). Delimiting ED by 1.0 mSv, chest CT examinations were categorized into 2 groups, LDCT group and CDCT group. vBMD of T12-L2 was obtained by transferring the LDCT and CDCT images to the QCT workstation, without extra radiation.ResultsThere was no difference of vBMD among 4 age groups in LDCT group (P = 0.965), and no difference in CDCT group (P = 0.988). In LDCT group and CDCT group, vBMD was not correlated to mAs, CTDIvol and DLP (P > 0.05), respectively. Between LDCT group and CDCT group, there was no difference of vBMD (P ≥ 0.480), while differences of mAs, CTDIvol and DLP.ConclusionThere was no difference of vBMD between LDCT group and CDCT group and vBMD was not correlated to mAs. While screening for diseases such as lung cancer and mediastinal lesions, LDCT combined with asynchronous QCT can be also used to assess vBMD simultaneously with no extra imaging equipment, patient visit time, radiation dose and no additional economic cost.

MicroRNA biomarkers and their use in evaluating the prognosis of lung cancer.

We aim to use the microRNA (miRNA, micro-ribonucleic acid) data of lung cancer tissues to establish a miRNA biomarker database for lung cancer that can be used for marker screening and analysis of lung cancer prognosis. We obtained lung cancer-related data from The Cancer Genome Atlas (TCGA) and analyzed the miRNA expression profiles of lung cancer tissues and normal tissues using bioinformatics techniques to develop a new composite miRNA-based model for the prognostic assessment of lung cancer. The predictive power of this model was verified and evaluated based on grouping of data. We also performed RT-qPCR using lung cancer tissues from patients diagnosed with lung cancer. There was a significant difference between the miRNA expression profiles of lung cancer tissues and normal tissues adjacent to the cancerous lesions. The prognostic survival of patients with lung cancer was closely related to onset age and staging (p = 0.012) but was not related to gender (p = 0.39) and race (p = 0.51). Using three methods of survival model construction, we identified three miRNA composites, namely hsa-mir-21, hsa-mir-141, and has-mir-490, as markers for the prognosis of lung cancer. As confirmed by RT-qPCR, the expressions of hsa-miR-21-5p and hsa-miR-141-5p were upregulated, whereas hsa-miR-490-3p expression was downregulated in lung cancer lesion tissues. The three miRNA composites identified, namely hsa-mir-21, hsa-mir-141, and hsa-mir-490, have the potential to serve as novel prognostic biomarkers and therapeutic targets for lung cancer.

3D unsupervised anomaly detection through virtual multi-view projection and reconstruction: Clinical validation on low-dose chest computed tomography

Computer-aided diagnosis for low-dose computed tomography (CT) based on deep learning has recently attracted attention as a first-line automatic testing tool because of its high accuracy and low radiation exposure. We propose a method based on a deep neural network for computer-aided diagnosis called virtual multi-view projection and reconstruction for unsupervised anomaly detection (VMPR-UAD) in low-dose chest CT. Presumably, this is the novel method that only requires data from healthy patients for training to identify three-dimensional (3D) regions containing any anomalies. The method has three key components. Unlike existing computer-aided diagnosis tools that use conventional CT slices as the network input, our method (1) improves the recognition of 3D lung structures by virtually projecting an extracted 3D lung region to obtain two-dimensional (2D) images from diverse views to serve as network inputs, (2) accommodates the input diversity gain for accurate anomaly detection, and (3) achieves 3D anomaly/disease localization through a novel 3D map restoration method using multiple 2D anomaly maps. The proposed method based on unsupervised learning showed a high performance in pneumonia, tuberculosis, and both diseases with patient-level anomaly detection performance of 0.965 area under the curve (AUC) (95% confidence interval (CI); (0.955, 0.972)), 0.948 AUC (95% CI; (0.928, 0.966)), and 0.963 AUC (95% CI; (0.955, 0.970)), respectively. Additionally, our technology visualizes anomalous regions in the 3D perspective. This achieved 93% accuracy in visualizing the location of lung cancer lesions through external validation. These results highlight the potential of a new AI methodology without utilizing disease data learning; this can secure AI model prediction stability by reducing the false negative rate that occurs in various patterns of diseases.

Performance of [18F]FDG PET/CT versus FAPI PET/CT for lung cancer assessment: a systematic review and meta-analysis.

This article aims to compare the diagnostic performance of 18-fluorodeoxyglucose ([18F]FDG) PET/CT and fibroblast activating protein inhibitor (FAPI) PET/CT in the assessment of primary tumors, lymph nodes, and distant metastases in lung cancer patients. A systematic search was conducted on the Cochrane Library, Embase, and PubMed/MEDLINE databases from inception until November 1, 2022. Included studies assessed the use of FAPI PET/CT and [18F]FDG PET/CT in patients with lung cancer. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to evaluate the risk of bias. A random variable model was used to analyze the diagnostic tests of the two imaging modalities. The sensitivity of FAPI PET/CT in detecting primary lung cancer lesions was 0.98 (95% CI: 0.88-1.00), while the sensitivity of [18F]FDG PET/CT was 0.99 (95% CI: 0.74-1.00). For the detection of metastatic lesions (lymph node metastases and distant metastases), FAPI PET/CT had a sensitivity of 0.99 (95% CI: 0.90-1.00), while the sensitivity of [18F]FDG PET/CT was 0.77 (95% CI: 0.66-0.85). However, the specificity of the two imaging modalities could not be assessed due to the lack of sufficient information on pertinent true negatives. In the diagnosis of metastatic lung cancer lesions, FAPI PET/CT demonstrated a higher sensitivity compared to [18F]FDG PET/CT. Therefore, FAPI PET/CT may be considered an alternative imaging modality for the assessment of primary lung cancer tumors, lymph node metastases, and distant metastases. FAPI may be an alternative to [18F]FDG in the assessment of primary lung cancer tumors, lymph node metastases, and distant metastases, which plays a very important role in treatment. • This article is to compare the performance of [18F]FDG PET/CT withFAPI PET/CT in the assessment of primary tumors, lymph nodes, and distant metastases in lung cancer. • However,FAPI PET/CT has a higher sensitivity for the diagnostic assessment of metastatic lung cancer lesions.

Anti-Cancer Effect of Neural Stem Cells Transfected with Carboxylesterase and sTRAIL Genes in Animals with Brain Lesions of Lung Cancer.

A metastatic brain tumor is the most common type of malignancy in the central nervous system, which is one of the leading causes of death in patients with lung cancer. The purpose of this study is to evaluate the efficacy of a novel treatment for metastatic brain tumors with lung cancer using neural stem cells (NSCs), which encode rabbit carboxylesterase (rCE) and the secretion form of tumor necrosis factor-related apoptosis-inducing ligand (sTRAIL). rCE and/or sTRAIL were transduced in immortalized human fetal NSCs, HB1.F3. The cytotoxic effects of the therapeutic cells on human lung cancer cells were evaluated in vitro with the ligands and decoy receptor expression for sTRAIL in the presence of CPT-11. Human NSCs encoding rCE (F3.CE and F3.CE.sTRAIL) significantly inhibited the growth of lung cancer cells in the presence of CPT-11 in vitro. Lung cancer cells were inoculated in immune-deficient mice, and therapeutic cells were transplanted systematically through intracardiac arterial injection and then treated with CPT-11. In resting state, DR4 expression in lung cancer cells and DcR1 in NSCs increased to 70% and 90% after CPT-11 addition, respectively. The volumes of the tumors in immune-deficient mice were reduced significantly in mice with F3.CE.sTRAIL transplantation and CPT-11 treatment. The survival was also significantly prolonged with treatment with F3.sTRAIL and F3.CE plus CPT-11 as well as F3.CE.sTRAIL plus CPT-11. NSCs transduced with rCE and sTRAIL genes showed a significant anti-cancer effect on brain metastatic lung cancer in vivo and in vitro, and the effect may be synergistic when rCE/CPT-11 and sTRAIL are combined. This stem-cell-based study using two therapeutic genes of different biological effects can be translatable to clinical application.

Review on Lung Cancer Lesion Detection and Segmentation Methods

Lung cancer itself and relevant detection and segmentation methods, in the modern society, becomes increasingly popular and significant topics. Scientists believe that people smoke positively may deteriorate their body health themselves, and people who breathe it in second hand may also suffer from this harmful environment. To help people with lung cancer lesions, there are several methods used for cancer treatment. Automated CT imaging can encircle suggested segmentation areas in a 3-D version, and it provides convenience with users when they feel tired after diagnosing for a whole day. Semi-automated CT deep learning model is another technique to detect particular regions in the lung by adjusting pixels. Additionally, few-shot learning based on advanced learning algorithm is an efficient method for lung cancer lesion detection, and Generative Adversarial Networks(GAN) can be used for lung cancer detection by using a small number of medical images as train datasets. However, CNN model cannot obtain global information; therefore, the integration of 2dcnn and 3dcnn solves this limitation in an effective approach.

Clinical and neuroelectrophysiological characteristics of primary peripheral nerve hyperexcitability syndrome

Objective: To investigate the clinical and neuroelectrophysiological characteristics of patients with primary peripheral nerve hyperexcitability syndrome (PNHS). Methods: The clinical data of 20 patients who were diagnosed with PNHS in Beijing Tiantan Hospital from April 2016 to January 2023 were retrospectively collected. All patients underwent neuroelectrophysiological examinations. Clinical and electrophysiological characteristics were compared between the antibody positive and antibody negative groups, according to serum and cerebrospinal fluid anti-contactin-associated protein-like 2 (CASPR2) and/or anti-leucine-rich glioma-inactivated protein 1 (LGI-1) antibodies. Results: There were 12 males and 8 females, with a mean age of (44.0±17.2) years and the disease course of [M (Q1, Q3)] 2.3 (1.1, 11.5) months. Motor symptoms included fasciculations, myokymia, muscle pain, cramps, and stiffness. These symptoms were commonly seen in the lower limbs (17 patients), followed by upper limbs (11 patients), face (11 patients) and trunk (9 patients). Nineteen (19/20) patients had sensory abnormalities and/or autonomic dysfunction, 13 patients had central nervous system involvement, and 5 patients had concomitant lung cancer or thymic lesions. The characteristic spontaneous potentials on needle electromyography (EMG) were myokymia potential (19 patients), fasciculation potential (12 patients), spastic potential (3 patients), neuromyotonic potential (1 patients), etc, which were commonly seen in the lower limb muscles, especially the gastrocnemius muscle(12 patients). After-discharge potential was found in 8 patients, and 7 were in the tibial nerve. Seven patients had positive serum anti-CASPR2 antibodies, and 3 of them had concomitant anti-LGI1 antibodies. And 1 patient had positive serum anti-LGI1 antibody alone. Compared with patients in the antibody negative group (n=12), the patients who had anti-VGKC complex antibodies (n=8) had a shorter course of disease [M (Q1, Q3): 1.8 (1, 2) months vs 9.5 (3.3, 20.3) months, P=0.012], higher incidence of after-discharge potential (6/8 vs 2/12, P=0.019). The immunotherapy regimen (multi-dru, single-drug, no immunotherapy: 6, 2, 0 patients) in antibody-positive patients was different from the antibody-negative group (3, 6, 3 patients, U=21.00, P=0.023). Conclusions: The symptoms of motor nerve hyperexcitation, characteristic EMG spontaneous potentials and after-discharge potentials in PNHS patients are most commonly seen in the lower limbs. Attention should be paid to concomitant sensory and autonomic nerve hyperexcitation. PNHS patients with positive serum anti-CASPR2 antibodies may require immunotherapy with multiple drugs.

Single cell RNA sequencing to reveal immune microenvironment in primary and brain metastatic lesion of non-small cell lung cancer.

e21009 Background: Despite immune checkpoint inhibitors (ICIs) have been proven effective in patients with advanced NSCLC, suboptimal therapeutic responses are seen in brain metastatic lesions. The heterogeneous cellular components in the tumor immune microenvironment (TIME) pose a challenge in understanding the low immune response. A comprehensive understanding of the heterogeneous TIME in primary and brain metastatic NSCLC is currently lacking, but crucial for improving ICI therapeutic responses in NSCLC patients with brain metastasis. Therefore, we use single cell RNA sequencing (scRNA-seq) to reveal distinct immune microenvironment in primary and brain metastatic lesion of NSCLC. Methods: Eight primary and nine brain metastatic NSCLC tumor samples were obtained through surgical resection. Immune cells (CD45+) were enriched through fluorescence-activated cell sorting (FACS) and subjected to scRNA-seq using the 10X Genomics platform. Sequencing reads were normalized and analyzed using R/Seurat package. Cellular components of each sample were determined based on known marker genes. Results: In our study, we observed a significant difference in the immune cell composition between primary and brain metastatic tumor samples. We found brain metastatic tumors are marked by an enrichment of TIMP1+ monocytes and PLTP+ tumor-associated macrophages (TAMs), both of which display heightened anti-inflammatory properties. In contrast, primary tumors exhibit an enrichment of FCN1+ monocytes and MARCO+ TAMs. Further analysis has revealed that the enrichment of TIMP1+ monocytes and PLTP+ TAMs is associated with a worse prognosis in patients receiving immunotherapy. Additionally, our examination of the transcriptome profile of CD8+ T cells showed an upregulation of inhibitory and exhausted signatures in brain metastatic tumor samples. Conclusions: Our study provided a comprehensive understanding of the TIME of primary and brain metastatic NSCLC and to gain deeper insights into the immunological mechanisms involved in the response to ICIs. The results of our study could prove valuable for the development of future immunotherapy strategies for NSCLC patients with brain metastasis.

Clinical and molecular characteristics of multiple primaries identified by whole-exome sequencing-based genetic divergence in non-small-cell lung cancer.

e20558 Background: With the recommendation of high-resolution chest computed tomography scan in lung cancer screening, multiple primary lung cancers (MPLC) is gaining more attention. Identifying MPLC from intrapulmonary metastases (IPM) is crucial to the clinical management. The current guidelines for the identification are always based on expert consensus rather than clinical evidence. We aim to develop a reliable identification method and further figure out the clinical and genetic features of MPLC. Methods: We retrospectively screened 305 lung lesions from 131 patients who underwent radical resection for multiple lung carcinomas. To minimize the effect of therapeutic intervention on prognostic outcomes, patients with each single tumor size smaller than 4cm, free of nodal or systemic metastases, and had high-quality whole-exon sequencing (WES) data were included. We selected 11 patients with confirmed intrapulmonary metastases for training. All patients’ follow-up information was collected until disease recurrence or metastases. A WES genetic divergence method for identifying MPLC from IPM was developed. The disease-free survival (DFS) was used as a validation tool for identification reliability. Results: A total of 61 eligible multi-lesion patients with 128 resected non-small cell lung cancer (NSCLC) lesions were finally analyzed. Based on WES genetic divergence identification, 51 MPLC patients were identified, whose DFS was significantly prolonged (HR, 0.27; 95% CI, 0.08 to 0.91; P = 0.02), while other recommended methods for identifying MPLC patients failed to show a DFS advantage. Among MPLC patients, 43.1% (22/51) had a first-degree relatives cancer family history, of whom 54.5% (12/22) had a lung cancer family history. EGFR was still the most common mutation gene (72.5%, 37/51); however, TP53 mutations was less frequent in MPLC (21% vs. 48%, P &lt; 0.05), and tumor mutation burden (TMB) was lower (median, 0.73 muts/Mb vs. 1.15 muts/Mb, P &lt; 0.01). Notably, despite the lack of shared alterations, unique germline variants in cancer-predisposing genes, particularly nonsynonymous SNV in solute carrier gene (SLC) family, were observed in most MPLC patients, rarely overlapping with IPM patients. Conclusions: WES-based genetic divergence clearly distinguishes independent primary tumors from IPM in NSCLC patients. MPLC patients represent a unique population which deserves further study.