Endoscopic Ultrasound-guided Transesophageal Fine-Needle Biopsy of Lung Masses: Diagnostic Performance and Safety.

BACKGROUND AND AIMS: Pulmonary masses are a diagnostic challenge in the field of endoscopic ultrasound(EUS) tissue acquisition, especially through transesophageal EUS-FNB(fine needle biopsy). Our study evaluated the feasibility, diagnostic performance, and safety of EUS-FNB of pulmonary lesions. METHODS: Fifty-three patients were enrolled in a prospective registry. All of the EUS procedures were performed by experienced endosonographers. Outcomes were specimen adequacy, diagnostic accuracy, diagnostic sensibility, diagnostic specificity, and safety. RESULTS: The mean age was 70±10.4, and 71.7% were male. The mean lesion size was 52.4±23.3 mm, and patients had mostly a single lesion(86.8%). Most of the patients had advanced stage at diagnosis(stage IV, 41.82%), and the most common lung cancer was non-small cell lung carcinoma(69.4%). Diagnostic adequacy rate was 92.86%, and diagnostic accuracy was 87.5%. Adverse events were reported in 3 procedures. CONCLUSIONS: Transesophageal EUS-FNB is a feasible and safe diagnostic method of tissue sampling for lung masses reachable by EUS.

Robust localization of poorly visible tumor in fiducial free stereotactic body radiation therapy.

BACKGROUND AND PURPOSE: Effective respiratory motion management reduces healthy tissue toxicity and ensures sufficient dose delivery to lung cancer cells in pulmonary stereotactic body radiation therapy (SBRT) with high fractional doses. An articulated robotic arm paired with an X-ray imaging system is designed for real-time motion-tracking (RTMT) dose delivery. However, small tumors (<15 mm) or tumors at challenging locations may not be visible in the X-ray images, disqualifying patients with such tumors from RTMT dose delivery unless fiducials are implanted via an invasive procedure. To track these practically invisible lung tumors in SBRT, we hereby develop a deep learning-enabled template-free tracking framework, SAFE Track. METHODS: SAFE Track is a fully supervised framework that trains a generalizable prior for template-free target localization. Two sub-stages are incorporated in SAFE Track, including the initial pretraining on two large-scale medical image datasets (DeepLesion and Node21) followed by fine-tuning on our in-house dataset. A two-stage detector, Faster R-CNN, with a backbone of ResNet50, was selected as our detection network. 94 patients (415 fractions; 40,348 total frames) with low tumor visibility who thus had implanted fiducials were included. The cohort is categorized by the longest dimension of the tumor (<10 mm, 10-15 mm and > 15 mm). The patients were split into training (n = 66) and testing (n = 28) sets. We simulated fiducial-free tumors by removing the fiducials from the X-ray images. We classified the patients into two groups - fiducial implanted inside tumors and implanted outside tumors. To ensure the rigor of our experiment design, we only conducted fiducial removal simulation in training patients and utilized patients with fiducial implanted outside of the tumors for testing. Commercial Xsight Lung Tracking (XLT) and a Deep Match were included for comparison. RESULTS: SAFE Track achieves promising outcomes to as accurate as 1.23±1.32 mm 3D distance in testing patients with tumor size > 15 mm where Deep Match is at 4.75±1.67 mm and XLT is at 12.23±4.58 mm 3D distance. Even for the most challenging tumor size (<10 mm), SAFE Track maintains its robustness at 1.82 plus or minus 1.67 mm 3D distance, where Deep Match is at 5.32 plus or minus 2.32 mm, and XLT is at 24.83±12.95 mm 3D distance. Moreover, SAFE Track can detect some considerably challenging cases where the tumor is almost invisible or overlapped with dense anatomies. CONCLUSION: SAFE Track is a robust, clinically compatible, fiducial-free, and template-free tracking framework that is applicable to patients with small tumors or tumors obscured by overlapped anatomies in SBRT.

Diagnosis of SPECT/CT bone imaging combined with two serum examinations in patients with bone metastases from pulmonary cancer

Purpose To study the clinical diagnostic value of SPECT/CT bone imaging combined with two serum examinations in patients with bone metastases from pulmonary cancer. Methods The clinical data of 120 patients consistent with pulmonary cancer admitted to the First Affiliated Hospital of Hebei North University from March 2019 to December 2019 were selected for retrospective analysis, and they were divided into the bone metastasis group (n = 58) and non-bone metastasis group (n = 62) according to comprehensive evaluation result of X-ray, CT, MRI and clinical follow-up. The CT values of patients were obtained by SPECT/CT bone imaging to compare serum levels of ALP (alkaline phosphatase belongs to phosphoric monoester hydrolases, as a specific phosphatase, mainly in body tissues and body fluid) and BAP (bone alkaline phosphatase is formed by different modification and processing of alkaline phosphatase, and is mainly released by osteoblasts) and CT values of patients in both groups, using receiver operating characteristic (ROC) curve to evaluate the diagnostic efficacy of single detection and combined detection. Results SPECT/CT bone imaging in patients with bone metastasis from pulmonary cancer showed abnormal radioactive accumulation in spine, pelvis and bilateral ribs. Serum ALP, BAP and CT values in bone metastasis group were overtly higher than the non-bone metastasis group (P < 0.001). Logistic regression analysis showed that serum ALP, BAP and CT value were independent risk factors for bone metastasis from pulmonary cancer. The AUC value and Youden index of combined diagnosis were higher than those of single diagnosis. Conclusion SPECT/CT bone imaging combined with serum detection of ALP and BAP in patients with pulmonary cancer is helpful for early diagnosis of bone metastasis, which provides more basis for the formulation and selection of clinical treatment options (AU)

Diagnosis of SPECT/CT bone imaging combined with two serum examinations in patients with bone metastases from pulmonary cancer.

PURPOSE: To study the clinical diagnostic value of SPECT/CT bone imaging combined with two serum examinations in patients with bone metastases from pulmonary cancer. METHODS: The clinical data of 120 patients consistent with pulmonary cancer admitted to the First Affiliated Hospital of Hebei North University from March 2019 to December 2019 were selected for retrospective analysis, and they were divided into the bone metastasis group (n = 58) and non-bone metastasis group (n = 62) according to comprehensive evaluation result of X-ray, CT, MRI and clinical follow-up. The CT values of patients were obtained by SPECT/CT bone imaging to compare serum levels of ALP (alkaline phosphatase belongs to phosphoric monoester hydrolases, as a specific phosphatase, mainly in body tissues and body fluid) and BAP (bone alkaline phosphatase is formed by different modification and processing of alkaline phosphatase, and is mainly released by osteoblasts) and CT values of patients in both groups, using receiver operating characteristic (ROC) curve to evaluate the diagnostic efficacy of single detection and combined detection. RESULTS: SPECT/CT bone imaging in patients with bone metastasis from pulmonary cancer showed abnormal radioactive accumulation in spine, pelvis and bilateral ribs. Serum ALP, BAP and CT values in bone metastasis group were overtly higher than the non-bone metastasis group (P < 0.001). Logistic regression analysis showed that serum ALP, BAP and CT value were independent risk factors for bone metastasis from pulmonary cancer. The AUC value and Youden index of combined diagnosis were higher than those of single diagnosis. CONCLUSION: SPECT/CT bone imaging combined with serum detection of ALP and BAP in patients with pulmonary cancer is helpful for early diagnosis of bone metastasis, which provides more basis for the formulation and selection of clinical treatment options.

MicroRNAs as Potential Biomarkers of Environmental Exposure to Polycyclic Aromatic Hydrocarbons and Their Link with Inflammation and Lung Cancer.

Exposure to atmospheric air pollution containing volatile organic compounds such as polycyclic aromatic hydrocarbons (PAHs) has been shown to be a risk factor in the induction of lung inflammation and the initiation and progression of lung cancer. MicroRNAs (miRNAs) are small single-stranded non-coding RNA molecules of ~20-22 nucleotides that regulate different physiological processes, and their altered expression is implicated in various pathophysiological conditions. Recent studies have shown that the regulation of gene expression of miRNAs can be affected in diseases associated with outdoor air pollution, meaning they could also be useful as biomarkers of exposure to environmental pollution. In this article, we review the published evidence on miRNAs in relation to exposure to PAH pollution and discuss the possible mechanisms that may link these compounds with the expression of miRNAs.

Machine Learning Model of ResNet50-Ensemble Voting for Malignant-Benign Small Pulmonary Nodule Classification on Computed Tomography Images.

BACKGROUND: The early detection of benign and malignant lung tumors enabled patients to diagnose lesions and implement appropriate health measures earlier, dramatically improving lung cancer patients' quality of living. Machine learning methods performed admirably when recognizing small benign and malignant lung nodules. However, exploration and investigation are required to fully leverage the potential of machine learning in distinguishing between benign and malignant small lung nodules. OBJECTIVE: The aim of this study was to develop and evaluate the ResNet50-Ensemble Voting model for detecting the benign and malignant nature of small pulmonary nodules (<20 mm) based on CT images. METHODS: In this study, 834 CT imaging data from 396 patients with small pulmonary nodules were gathered and randomly assigned to the training and validation sets in an 8:2 ratio. ResNet50 and VGG16 algorithms were utilized to extract CT image features, followed by XGBoost, SVM, and Ensemble Voting techniques for classification, for a total of ten different classes of machine learning combinatorial classifiers. Indicators such as accuracy, sensitivity, and specificity were used to assess the models. The collected features are also shown to investigate the contrasts between them. RESULTS: The algorithm we presented, ResNet50-Ensemble Voting, performed best in the test set, with an accuracy of 0.943 (0.938, 0.948) and sensitivity and specificity of 0.964 and 0.911, respectively. VGG16-Ensemble Voting had an accuracy of 0.887 (0.880, 0.894), with a sensitivity and specificity of 0.952 and 0.784, respectively. CONCLUSION: Machine learning models that were implemented and integrated ResNet50-Ensemble Voting performed exceptionally well in identifying benign and malignant small pulmonary nodules (<20 mm) from various sites, which might help doctors in accurately diagnosing the nature of early-stage lung nodules in clinical practice.

Malignant lung PEComa (clear cell tumor): rare case report and literature review.

Clear cell tumors of the lung (CCTL), or "sugar tumors" of lung, are very uncommon lesions and are mostly benign perivascular epithelioid cell (PEC) tumors with no specific morphologic features. Fewer than 100 cases have been reported; the aggressive nature demonstrated in sporadic reports has rarely been described in the literature. Although the course is generally described as benign, eight reported cases showed malignant behavior. We report a case of a PEC with a malignant presentation in a young man, correlating the main characteristics of the tumor with other cases reported in the literature to better elucidate this rare presentation. We also performed a literature review of reports on benign and malignant CCTL cases, with a focus on clinical, imaging, and immunohistochemical differentiation. CCTLs are rare tumors that require histopathological and immunohistochemical confirmation; to date, criteria that can predict malignant evolution are lacking.

Comparison of different dose accumulation strategies to estimate organ doses after stereotactic magnetic resonance-guided adaptive radiotherapy.

INTRODUCTION: Re-irradiation is frequently performed in the era of precision oncology, but previous doses to organs-at-risk (OAR) must be assessed to avoid cumulative overdoses. Stereotactic magnetic resonance-guided online adaptive radiotherapy (SMART) enables highly precise ablation of tumors close to OAR. However, OAR doses may change considerably during adaptive treatment, which complicates potential re-irradiation. We aimed to compare the baseline plan with different dose accumulation techniques to inform re-irradiation. PATIENTS & METHODS: We analyzed 18 patients who received SMART to lung or liver tumors inside prospective databases. Cumulative doses were calculated inside the planning target volumes (PTV) and OAR for the adapted plans and theoretical non-adapted plans via (1) cumulative dose volume histograms (DVH sum plan) and (2) deformable image registration (DIR)-based dose accumulation to planning images (DIR sum plan). We compared cumulative dose parameters between the baseline plan, DVH sum plan and DIR sum plan using equivalent doses in 2 Gy fractions (EQD2). RESULTS: Individual patients presented relevant increases of near-maximum doses inside the proximal bronchial tree, spinal cord, heart and gastrointestinal OAR when comparing adaptive treatment to the baseline plans. The spinal cord near-maximum doses were significantly increased in the liver patients (D2% median: baseline 6.1 Gy, DIR sum 8.1 Gy, DVH sum 8.4 Gy, p = 0.04; D0.1 cm³ median: baseline 6.1 Gy, DIR sum 8.1 Gy, DVH sum 8.5 Gy, p = 0.04). Three OAR overdoses occurred during adaptive treatment (DIR sum: 1, DVH sum: 2), and four more intense OAR overdoses would have occurred during non-adaptive treatment (DIR sum: 4, DVH sum: 3). Adaptive treatment maintained similar PTV coverages to the baseline plans, while non-adaptive treatment yielded significantly worse PTV coverages in the lung (D95% median: baseline 86.4 Gy, DIR sum 82.4 Gy, DVH sum 82.2 Gy, p = 0.006) and liver patients (D95% median: baseline 87.4 Gy, DIR sum 82.1 Gy, DVH sum 81.1 Gy, p = 0.04). CONCLUSION: OAR doses can increase during SMART, so that re-irradiation should be planned based on dose accumulations of the adapted plans instead of the baseline plan. Cumulative dose volume histograms represent a simple and conservative dose accumulation strategy.

Impact of Cancerous Pulmonary Involvement on Outcomes in COVID-19 Patients.

BACKGROUND: SARS-CoV2 is a highly contagious virus causing COVID-19 (Corona virus disease 2019), which has resulted in more than 6 million deaths worldwide as of June 2022. Mortality in COVID-19 has mainly been attributed to respiratory failure. Previous studies showed that the presence of cancer did not adversely affect the outcome of COVID-19. However, in our clinical practice, it was noted that in cancer patients with pulmonary involvement, COVID-19-related morbidity, and morbidity were high. Therefore, this study was designed to assess the impact of cancerous pulmonary involvement on COVID-19 outcomes and to compare clinical outcomes of COVID-19 in cancer and non-cancer population, with further discretion between cancers with and without pulmonary involvement. METHODS: We performed a retrospective study from April 2020 until June 2020 with a sample size of 117 patients with a confirmed diagnosis of SARS-CoV2 on nasal swab PCR. Data was extracted from HIS (Hospital Information System). Hospitalization, supplemental oxygen, ventilatory support, and death were compared between non-cancer and cancer patients with a particular focus on pulmonary involvement. RESULTS: Admissions, supplemental oxygen requirement, and mortality were significantly higher in cancer patients with pulmonary involvement (63.3%, 36.4%, and 45%, respectively) compared to cancer patients without pulmonary involvement (22.1%, 14.7%, and 8.8% respectively) (p-values: 0.00003, 0.003, and 0.00003 respectively). In the non-cancer group, there was no mortality, only 2% required admission, and none needed supplemental oxygen. CONCLUSION: We conclude that the cancer patient with pulmonary involvement was significantly at higher risk of complications and death from COVID when compared with the non-pulmonary cancer group and the general population.

To fly or not to fly: Stereotactic MR-guided adaptive radiotherapy effectively treats ultracentral lung tumors with favorable long-term outcomes.

BACKGROUND: Stereotactic radiotherapy of ultracentral lung tumors (ULT) is challenging as it may cause overdoses to sensitive mediastinal organs with severe complications. We aimed to describe long-term outcomes after stereotactic magnetic resonance (MR)-guided online adaptive radiotherapy (SMART) as an innovative treatment of ULT. PATIENTS & METHODS: We analyzed 36 patients that received SMART to 40 tumors between 02/2020 - 08/2021 inside prospective databases. ULT were defined by planning target volume (PTV) overlap with the proximal bronchial tree or esophagus. We calculated Kaplan Meier estimates for overall survival (OS) and progression-free survival (PFS), and competing risk estimates for the incidence of tumor progression and treatment-related toxicities. ULT patients (N = 16) were compared to non-ULT patients (N = 20). RESULTS: Baseline characteristics were similar between ULT and non-ULT, but ULT were larger (median PTV: ULT 54.7 cm3, non-ULT 19.2 cm3). Median follow-up was 23.6 months. ULT and non-ULT showed a similar OS (2-years: ULT 67%, non-ULT 60%, p = 0.7) and PFS (2-years: ULT 37%, non-ULT 34%, p = 0.73). Progressions occurred mainly at distant sites (2-year incidence of distant progression: ULT 63%, non-ULT 61%, p = 0.77), while local tumor control was favorable (2-year incidence of local progression: ULT 7%, non-ULT 0%, p = 0.22). Treatment of ULT led to significantly more toxicities ≥ grade (G) 2 (ULT: 9 (56%), non-ULT: 1 (5%), p = 0.002). Most toxicities were moderate (G2). Two ULT patients developed high-grade toxicities: 1) esophagitis G3 and bronchial bleeding G4 after VEGF treatment, 2) bronchial bleeding G3. Estimated incidence of high-grade toxicities was 19% (3-48%) in ULT, and no treatment-related death occurred. CONCLUSION: Our small series supports SMART as potentially effective treatment of ULT. SMART with careful fractionation could reduce severe complications, but treatment of ULT remains a high-risk procedure and needs careful benefit-risk-assessment.

Recurrence-Free Survival in Early and Locally Advanced Large Cell Neuroendocrine Carcinoma of the Lung after Complete Tumor Resection.

BACKGROUND: Large Cell Neuroendocrine Carcinoma (LCNEC) is a rare subtype of lung cancer with poor clinical outcomes. Data on recurrence-free survival (RFS) in early and locally advanced pure LCNEC after complete resection (R0) are lacking. This study aims to evaluate clinical outcomes in this subgroup of patients and to identify potential prognostic markers. METHODS: Retrospective multicenter study including patients with pure LCNEC stage I-III and R0 resection. Clinicopathological characteristics, RFS, and disease-specific survival (DSS) were evaluated. Univariate and multivariate analyses were performed. RESULTS: 39 patients (M:F = 26:13), with a median age of 64 years (44-83), were included. Lobectomy (69.2%), bilobectomy (5.1%), pneumonectomy (18%), and wedge resection (7.7%) were performed mostly associated with lymphadenectomy. Adjuvant therapy included platinum-based chemotherapy and/or radiotherapy in 58.9% of cases. After a median follow-up of 44 (4-169) months, the median RFS was 39 months with 1-, 2- and 5-year RFS rates of 60.0%, 54.6%, and 44.9%, respectively. Median DSS was 72 months with a 1-, 2- and 5-year rate of 86.8, 75.9, and 57.4%, respectively. At multivariate analysis, age (cut-off 65 years old) and pN status were independent prognostic factors for both RFS (HR = 4.19, 95%CI = 1.46-12.07, p = 0.008 and HR = 13.56, 95%CI 2.45-74.89, p = 0.003, respectively) and DSS (HR = 9.30, 95%CI 2.23-38.83, p = 0.002 and HR = 11.88, 95%CI 2.28-61.84, p = 0.003, respectively). CONCLUSION: After R0 resection of LCNEC, half of the patients recurred mostly within the first two years of follow-up. Age and lymph node metastasis could help to stratify patients for adjuvant therapy.

Malignant Pleural Mesothelioma: Preliminary Toxicity Results of Adjuvant Radiotherapy Hypofractionation in a Prospective Trial (MESO-RT).

Malignant Pleural Mesothelioma (MPM) is a rare malignancy with an overall poor prognosis. The standard therapeutic strategy in early-stage disease is trimodality therapy. In this publication, we report the preliminary toxicity results of the first 20 patients treated with accelerated hypofractionated radiotherapy. Between July 2017 to June 2019, 20 MPM patients were enrolled and treated with accelerated hypofractionated radiotherapy using helical tomotherapy and intensity-modulated arc therapy. The prescription dose was 30 Gy in five daily fractions, while an inhomogeneous dose escalation to 40 Gy was prescribed based solely upon the presence of gross residual tumor. Only one case of G3 toxicity was reported, which was a bilateral pneumonitis that occurred two years after treatment probably due to superinfection. Median Time to Progression reached 18.2 months while one- and three-year Overall Survival rates were 85% (95% CI:60.4-94.9) and 49.5% (95% CI:26.5-68.9), respectively. Treatment of the intact lung with pleural intensity-modulated arc irradiation is a novel treatment strategy that appears to be safe, feasible, and without a high grade of lung toxicity. Survival rates and Time to Progression are encouraging.

Occupational exposure to nickel and hexavalent chromium and the risk of lung cancer in a pooled analysis of case-control studies (SYNERGY).

There is limited evidence regarding the exposure-effect relationship between lung-cancer risk and hexavalent chromium (Cr(VI)) or nickel. We estimated lung-cancer risks in relation to quantitative indices of occupational exposure to Cr(VI) and nickel and their interaction with smoking habits. We pooled 14 case-control studies from Europe and Canada, including 16 901 lung-cancer cases and 20 965 control subjects. A measurement-based job-exposure-matrix estimated job-year-region specific exposure levels to Cr(VI) and nickel, which were linked to the subjects' occupational histories. Odds ratios (OR) and associated 95% confidence intervals (CI) were calculated by unconditional logistic regression, adjusting for study, age group, smoking habits and exposure to other occupational lung carcinogens. Due to their high correlation, we refrained from mutually adjusting for Cr(VI) and nickel independently. In men, ORs for the highest quartile of cumulative exposure to CR(VI) were 1.32 (95% CI 1.19-1.47) and 1.29 (95% CI 1.15-1.45) in relation to nickel. Analogous results among women were: 1.04 (95% CI 0.48-2.24) and 1.29 (95% CI 0.60-2.86), respectively. In men, excess lung-cancer risks due to occupational Cr(VI) and nickel exposure were also observed in each stratum of never, former and current smokers. Joint effects of Cr(VI) and nickel with smoking were in general greater than additive, but not different from multiplicative. In summary, relatively low cumulative levels of occupational exposure to Cr(VI) and nickel were associated with increased ORs for lung cancer, particularly in men. However, we cannot rule out a combined classical measurement and Berkson-type of error structure, which may cause differential bias of risk estimates.

3D-PulCNN: Pulmonary cancer classification from hyperspectral images using convolution combination unit based CNN.

Pulmonary cancer is one of the most common malignancies worldwide. Accurate classification of its subtypes is required in differential diagnosis. However, existing algorithms are mostly based on color images, and the improvement of accuracy is quite challenging. In this study, we propose a convolution combination unit (CCU)-based three-dimensional convolutional neural network (3D-PulCNN) for classifying pulmonary cancer presented in microscopic hyperspectral image with both spatial and spectral information. CCU is designed to fuse the features acquired by different convolution scales. Compared with VGGNet, only two fully connected layers are used in this model, reducing the network parameters and model complexity. Experimental results show that 3D-PulCNN achieves overall average (OA) of 0.962 and Precision, Recall, and Kappa of more than 0.920, superior to 2D-VGGNet. Then, 3D-UNet is leveraged to segment cancer cells, and their morphological characteristics are calculated to supply quantitative virtual analysis data for classification results explanation and prognosis assessment.

Molecular pathogenesis of hereditary lung cancer: a literature review.

Among all cancer types, pulmonary cancer has the highest mortality rate. Tobacco consumption remains the major risk factor for the development of lung cancer. However, many studies revealed a correlation between inherited genetic variants and predisposition to lung cancer, especially in nonsmokers. To date, genetic testing for the detection of germline mutations is not yet recommended in patients with lung cancer and testing is focused on somatic alterations given their implication in the treatment choice. Understanding the impact of genetic predisposition on the occurrence of lung cancer is essential to enable the introduction of accurate guidelines and recommendations that might reduce mortality. In this review paper, we describe familial lung cancer, and expose germline mutations that are linked to this type of cancer. We also report pathogenic genetic variants linked to syndromes associated with lung cancer.

Artificial intelligence-based vessel suppression for detection of sub-solid nodules in lung cancer screening computed tomography.

BACKGROUND: Lung cancer screening (LCS) with low-dose computed tomography (LDCT) helps early lung cancer detection, commonly presenting as small pulmonary nodules. Artificial intelligence (AI)-based vessel suppression (AI-VS) and automatic detection (AI-AD) algorithm can improve detection of subsolid nodules (SSNs) on LDCT. We assessed the impact of AI-VS and AI-AD in detection and classification of SSNs [ground-glass nodules (GGNs) and part-solid nodules (PSNs)], on LDCT performed for LCS. METHODS: Following regulatory approval, 123 LDCT examinations with sub-solid pulmonary nodules (average diameter ≥6 mm) were processed to generate three image series for each examination-unprocessed, AI-VS, and AI-AD series with annotated lung nodules. Two thoracic radiologists in consensus formed the standard of reference (SOR) for this study. Two other thoracic radiologists (R1 and R2; 5 and 10 years of experience in thoracic CT image interpretation) independently assessed the unprocessed images alone, then together with AI-VS series, and finally with AI-AD for detecting all ≥6 mm GGN and PSN. We performed receiver operator characteristics (ROC) and Cohen's Kappa analyses for statistical analyses. RESULTS: On unprocessed images, R1 and R2 detected 232/310 nodules (R1: 114 GGN, 118 PSN) and 255/310 nodules (R2: 122 GGN, 133 PSN), respectively (P>0.05). On AI-VS images, they detected 249/310 nodules (119 GGN, 130 PSN) and 277/310 nodules (128 GGN, 149 PSN), respectively (P≥0.12). When compared to the SOR, accuracy (AUC) for detection of PSN on the AI-VS images (AUC 0.80-0.81) was greater than on the unprocessed images (AUC 0.70-0.76). AI-VS images enabled detection of solid components in five nodules deemed as GGN on the unprocessed images. Accuracy of AI-AD was lower than both the radiologists (AUC 0.60-0.72). CONCLUSIONS: AI-VS improved the detection and classification of SSN into GGN and PSN on LDCT of the chest for the two radiologist (R1 and R2) readers.

Hepatic steatosis and respiratory diseases: a new panorama.

Non-alcoholic fatty liver disease is defined as hepatic fat accumulation in more than 5% of hepatocytes, without other liver steatosis causes. It comprises a broad spectrum that can range from benign steatosis and progress to non-alcoholic steatohepatitis, fibrosis, and ultimately hepatocellular carcinoma. Non-alcoholic fatty liver is considered a multisystemic disease since it is related to multiple disorders, such as type 2 diabetes mellitus, polycystic ovary syndrome, chronic kidney disease, psoriasis, osteoporosis, hypothyroidism, cardiovascular diseases, and obstructive sleep apnea syndrome; it is becoming increasingly clear that it is also a risk factor for developing certain respiratory diseases. This article aims to understand the liver and chronic obstructive pulmonary disease mechanisms, obstructive sleep apnea syndrome, asthma, and lung cancer. Given that non-alcoholic fatty liver disease has a considerable impact on the patient's well-being and life quality, as well as on the costs they generate for the country's health services, it is essential to continue research, especially in areas such as the respiratory tract, as there is much misinformation about it.

Adaptive MR-Guided Stereotactic Radiotherapy is Beneficial for Ablative Treatment of Lung Tumors in High-Risk Locations.

PURPOSE: To explore the benefit of adaptive magnetic resonance-guided stereotactic body radiotherapy (MRgSBRT) for treatment of lung tumors in different locations with a focus on ultracentral lung tumors (ULT). PATIENTS & METHODS: A prospective cohort of 21 patients with 23 primary and secondary lung tumors was analyzed. Tumors were located peripherally (N = 10), centrally (N = 2) and ultracentrally (N = 11, planning target volume (PTV) overlap with proximal bronchi, esophagus and/or pulmonary artery). All patients received MRgSBRT with gated dose delivery and risk-adapted fractionation. Before each fraction, the baseline plan was recalculated on the anatomy of the day (predicted plan). Plan adaptation was performed in 154/165 fractions (93.3%). Comparison of dose characteristics between predicted and adapted plans employed descriptive statistics and Bayesian linear multilevel models. The posterior distributions resulting from the Bayesian models are presented by the mean together with the corresponding 95% compatibility interval (CI). RESULTS: Plan adaptation decreased the proportion of fractions with violated planning objectives from 94% (predicted plans) to 17% (adapted plans). In most cases, inadequate PTV coverage was remedied (predicted: 86%, adapted: 13%), corresponding to a moderate increase of PTV coverage (mean +6.3%, 95% CI: [5.3-7.4%]) and biologically effective PTV doses (BED10) (BEDmin: +9.0 Gy [6.7-11.3 Gy], BEDmean: +1.4 Gy [0.8-2.1 Gy]). This benefit was smaller in larger tumors (-0.1%/10 cm³ PTV [-0.2 to -0.02%/10 cm³ PTV]) and ULT (-2.0% [-3.1 to -0.9%]). Occurrence of exceeded maximum doses inside the PTV (predicted: 21%, adapted: 4%) and violations of OAR constraints (predicted: 12%, adapted: 1%, OR: 0.14 [0.04-0.44]) was effectively reduced. OAR constraint violations almost exclusively occurred if the PTV had touched the corresponding OAR in the baseline plan (18/19, 95%). CONCLUSION: Adaptive MRgSBRT is highly recommendable for ablative treatment of lung tumors whose PTV initially contacts a sensitive OAR, such as ULT. Here, plan adaptation protects the OAR while maintaining best-possible PTV coverage.

Diagnostic value of artificial intelligence-assisted diagnostic system for pulmonary cancer based on CT images: A systematic review and meta-analysis of 4 771 patients / 中国胸心血管外科临床杂志

@#Objective    To evaluate the diagnostic value of artificial intelligence (AI)-assisted diagnostic system for pulmonary cancer based on CT images. Methods    Databases including PubMed, The Cochrane Library, EMbase, CNKI, WanFang Data and Chinese BioMedical Literature Database (CBM) were electronically searched to collect relevant studies on AI-assisted diagnostic system in the diagnosis of pulmonary cancer from 2010 to 2019. The eligible studies were selected according to inclusion and exclusion criteria, and the quality of included studies was assessed and the special information was identified. Then, meta-analysis was performed using RevMan 5.3, Stata 12.0 and SAS 9.4 softwares. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio were pooled and the summary receiver operating characteristic (SROC) curve was drawn. Meta-regression analysis was used to explore the sources of heterogeneity. Results    Totally 18 studies were included with 4 771 patients. Random effect model was used for the analysis due to the heterogeneity among studies. The results of meta-analysis showed that the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnosis odds ratio and area under the SROC curve were   0.87 [95%CI (0.84, 0.90)], 0.89 [95%CI (0.84, 0.92)], 7.70 [95%CI (5.32, 11.15)], 0.14 [95%CI (0.11, 0.19)], 53.54 [95%CI (30.68, 93.42)] and 0.94 [95%CI (0.91, 0.95)], respectively. Conclusion    AI-assisted diagnostic system based on CT images has high diagnostic value for pulmonary cancer, and thus it is worthy of clinical application. However, due to the limited quality and quantity of included studies, above results should be validated by more studies.

Research Progress on the Anti-Cancer Molecular Mechanisms of Huaier.

Huaier (Trametes robiniophila Murr), a Chinese traditional herb of medicine, has demonstrated promising curative effects in clinical treatment for various tumors. There are documented experiments showing the biological functions of Huaier with its antineoplastic molecular mechanisms: restraining proliferation and metastasis, arresting cell cycle, inducing apoptosis, pyrosis, and autophagy, anti-intratumoral angiogenesis, attenuating characteristics of tumor stem-like cells, interfering with the function of the tumor-related immune system, reversing drug resistance, and enhancing the sensitivity to chemotherapeutic drugs, etc. In addition, studies suggest that non-coding RNA (ncRNA) acts a pivotal part in cancer occurrence and development, and demonstrates that Huaier adjusts the performance of certain lncRNA (long non-coding RNA) and proceeds to affect the microRNA and its target genes, rendering an anti-tumor effect. Huaier also modulates the expression of lncRNA to attenuate the activity of ncRNA-sponged microRNA and then inhibits the expression of downstream target genes. We summarize and illustrate the experimentally confirmed anti-cancer molecular mechanisms of Huaier, to inspire new ideas for researchers in relevant fields.