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Introduction: Lung cancer is third most common cancer and highest cause of cancer death in the UK. COPD and smoking are known cancer risk factors so early intervention is essential. Incidence is higher in areas of deprivation where early presentation is less likely and outcomes poorer. Middlesbrough has some of the highest areas of deprivation. Aim(s): To evaluate diagnostic value of CT screening pilot in detecting lung cancer and follow-up outcomes for patients with incidental finding of pulmonary nodules. Method(s): Between March 2019 - December 2022 17 GP practices in Middlesbrough were invited to offer non-contrast CT thorax to asymptomatic COPD patients eligible for review, aged 50-75 with 20 pack year history and QCancer risk >5%. Pulmonary nodules followed up as per BTS guidelines. This pilot was conducted in partnership and with support from the Northern Cancer Alliance. Result(s): 407 patients referred for CT, 312 met the criteria and enrolled. 5 (1.6% conversion rate) lung cancers, also 1 renal cancer diagnosed. 51 (17%) had features of pulmonary nodules or groundglass opacities and selected for follow up. 2 died from COVID infection before follow-up CT. 32 (62.8%) discharged after followup CT revealed stable appearances or resolution, follow-up CT still outstanding for 2. 4 (7.8%) selected for further follow-up of sub-solid, new or increasing nodules. 2 (3.9%) received radiological diagnosis of lung cancer and referred for radiotherapy, 1 underwent surgical resection revealing lung tumourlets and 1 referred for surgical resection of enlarging nodule. Conclusion(s): Pulmonary nodules consisted significant part of the CT screening pilot findings in COPD patients with significant further conversion rate to lung cancer diagnosis after follow-up. Therefore, CT screening of high-risk population in deprived areas has a role in detecting lung cancer and identifying pulmonary nodules, with a proportion of those later diagnosed as early lung cancer. Disclosure: No significant relationships.Copyright © 2023 Elsevier B.V.
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BACKGROUND: Thoracic computed tomography (CT) scan plays a role in detecting and assessing the progression of COVID-19. It can evaluate the response to the therapy given. In diagnosis, the CT scan of the chest may complement the limitations of reverse transcription polymerase chain reaction (RT-PCR). Several recent studies have discussed the importance of CT scans in COVID-19 patients with false-negative RT-PCR results. The sensitivity of chest CT scan in the diagnosis of COVID-19 is reportedly around 98%. AIM: This study aimed to determine the compatibility of CT scan of the thorax with RT-PCR in suspected COVID-19 patients. MATERIALS AND METHODS: This research was conducted in the Radiology Department of the Wahidin Sudirohusodo Hospital Makassar from April to December 2020 with 350 patients. The method used was a 2 x 2 table diagnostic test. RESULT(S): The study included 188 male patients (53.7%) and 162 female patients (46.2%). The most common age group was 46-65 years (35.4%). The most common types of lesions were ground-glass opacity (163 cases), consolidation (128 cases), and fibrosis (124 cases), mostly found in the inferior lobe with a predominantly peripheral or subpleural distribution. The sensitivity of the CT scan to the PCR examination was 86%, and the specificity was 91%. CONCLUSION(S): Thoracic CT scan was a good modality in establishing the diagnosis of COVID-19. CT scan of the chest with abnormalities could confirm the diagnosis in 88% of cases based on RT-PCR examination. It excluded the diagnosis in 91% based on the RT-PCR examination. The accuracy of the thoracic CT scan was 88% with RT-PCR as the reference value.Copyright © 2023 Sri Asriyani, Albert Alexander Alfonso, Mirna Muis, Andi Alfian Zainuddin, Irawaty Djaharuddin, Muhammad Ilyas.
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Pulmonary sclerosing pneumocytomas are benign tumors. These tumors are often found incidentally and can be challenging to distinguish from lung malignancies. Here, we describe the case of a 31-year-old woman who presented with an incidental finding of a lung nodule in the lingula. She was asymptomatic and had no history of cancer. Positron emission tomography showed [18F] fluorodeoxyglucose (FDG) uptake in the nodule but no FDG-avid mediastinal lymphadenopathy. In view of these findings, a bronchoscopy was performed, and biopsy samples were taken. The final pathological diagnosis revealed a sclerosing pneumocytoma.
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Context: During the COVID-19 pandemic, both people with underlying diseases and previously healthy people were infected with SARS-CoV-2. In our institute, most hospitalized patients underwent chest computed tomography (CT) to evaluate pulmonary involvement and complication of COVID-19. There are currently limited data regarding thyroid CT incidentalomas in healthy people. Objective: We aimed to investigate the prevalence and predictors of thyroid incidentalomas among hospitalized patients with COVID-19. Methods: A single-center retrospective study included hospitalized patients aged ≥15 years with COVID-19 who underwent chest CT during April 2020 and October 2021. Thyroid incidentalomas were reviewed and identified by an experienced radiologist. Logistic regression analysis was used to determine predictors for thyroid incidentalomas. Results: In the 1326 patients (mean age 49.4 years and 55.3% female) that were included, the prevalence of thyroid incidentalomas was 20.2%. Patients with thyroid incidentalomas were older (59.6 years vs 46.8 years, P < .001) and more often female than those without incidentalomas (63.4% vs 53.2%, P = .003). On multivariate analysis, only female sex (OR 1.56; 95% CI 1.17-2.07) and older age (OR 1.04; 95% CI 1.03-1.05) were significantly associated with thyroid incidentalomas. Conclusion: In COVID-19 patients, the prevalence of thyroid incidentalomas identified on chest CT was higher (20.2%) than in previous studies in the general population (<1% to 16.8%). Female sex and older age were independent factors associated with thyroid incidentalomas.
Subject(s)
Lung Neoplasms , Surgeons , Humans , Lung Neoplasms/diagnosis , Lung Neoplasms/surgery , Early Detection of Cancer , PulmonologistsABSTRACT
Introduction: With the increasing detection of incidental pulmonary nodules (IPNs), there is a clinical need for a dedicated IPN service to ensure that growing PNs are managed in a timely manner. Pre COVID-19, our centre ran a virtual nodule service, delivered on an ad-hoc basis by the lung cancer physicians. We hypothesised that efficiency of the service would improve with a dedicated nodule team. We were awarded a pump priming grant by the Thames Valley Cancer Alliance to implement a nodule navigator run service. We report the initial outcomes of this project here. Objective(s): To evaluate the PN navigator service. Method(s): Retrospective data pre-service development was collected from patients presenting to the PN service between April and June 2022. The service was established in October 2022 and data from October and November 2022 collected. Student t-test was used to compare means. [Table presented] Results: 107 patients were included pre-service and 92 patients in the post-service development cohorts. Data for time to CT report and patient contact are summarised in Table 1. There was no reduction in mean time from CT scan date to CT report (Table 1;31vs 27;p=0.143) but a reduction was seen between CT report and patient contact (Table 1, 45 vs 20;p<0.001). Conclusion(s): This small cohort study shows an improvement in the time between CT scan and patient contact following the introduction of a dedicated PN service. This may reduce delays in the diagnosis of early-stage lung cancer. Whilst there was no significant difference between the CT scan date and CT report, these data highlight an area in the pathway that can improve. Further aims of the project are to collect patient satisfaction and IPN discharge. Disclosure: No significant relationships.Copyright © 2023 Elsevier B.V.
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Objective: Describe incidental tomographic in the sample, correlating them with risk factors for chest diseases and sociodemographic data. Method(s): This is a retrospective and observational study covering 162 patients admitted to the COVID sector of the HU/UFJF, from April 1, 2020, to July 7, 2021, with a confirmed laboratory diagnosis of COVID-19. The variables were described in absolute and relative frequencies. The comparison of the correlation between the outcome variable (the tomographic findings) for independent samples was performed using Pearson's chi-square test (without correction) or Fisher's test when relevant. Result(s): Of the 162 patients, 15.4% had a solitary pulmonary nodule;14.8% had multiple pulmonary nodules;1.8%, lung mass;3.1%, mediastinal mass, and 9.3% had mediastinal adenomegaly. Findings such as excavations, pleural effusion, emphysema, PTE, pneumothorax, chronic interstitial disease, cavitation, aneurysms, and significant atheromatosis, classified in this study in the "Other" category showed impressive results, with an overall prevalence of 81.5%. This study demonstrated that 34% of patients had two or more types of incidental CT findings and that 88.3% of patients had at least some type of incidental CT finding. Conclusion(s): The pandemic of SARS-CoV-2 infections has brought a series of challenges and lessons learned to healthcare teams around the world. The massive implementation of highly sensitive diagnostic methods, such as chest tomography, ends up bringing an additional challenge, which is to deal with incidental findings, making good clinical reasoning necessary to avoid unnecessary investigations and not leave without diagnosis and treatment of diseases in early and asymptomatic stages.Copyright © 2023 Faculdade de Medicina de Ribeirao Preto - U.S.P.. All rights reserved.
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Chest radiography (X-ray) is the most common diagnostic method for pulmonary disorders. A trained radiologist is required for interpreting the radiographs. But sometimes, even experienced radiologists can misinterpret the findings. This leads to the need for computer-aided detection diagnosis. For decades, researchers were automatically detecting pulmonary disorders using the traditional computer vision (CV) methods. Now the availability of large annotated datasets and computing hardware has made it possible for deep learning to dominate the area. It is now the modus operandi for feature extraction, segmentation, detection, and classification tasks in medical imaging analysis. This paper focuses on the research conducted using chest X-rays for the lung segmentation and detection/classification of pulmonary disorders on publicly available datasets. The studies performed using the Generative Adversarial Network (GAN) models for segmentation and classification on chest X-rays are also included in this study. GAN has gained the interest of the CV community as it can help with medical data scarcity. In this study, we have also included the research conducted before the popularity of deep learning models to have a clear picture of the field. Many surveys have been published, but none of them is dedicated to chest X-rays. This study will help the readers to know about the existing techniques, approaches, and their significance.
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In recent years, the corona virus disease 2019 (COVID-19) pandemic has had a huge impact on the global medical, political and economic fields. Since the beginning of the COVID-19 epidemic, our understanding of the impact of COVID-19 has grown exponentially. Recently, the COVID-19 epidemic has changed rapidly in China, and there has been controversy over how to carry out surgical operations for patients with lung neoplastic lesions. Some studies have shown that lung cancer patients undergoing surgery are more likely to experience respiratory failure and perioperative death after contract-ing COVID-19 than the general population, however, delays in cancer treatment are also associated with increased mortality among these patients. In particular, the novel coronavirus Omikron variant has a higher transmissibility and may escape the immunity obtained through the previous novel coronavirus infection and vaccination. In order to minimize the risk of novel coronavirus infection in surgical patients, it is necessary to develop new treatment guidelines, expert consensus and preventive measures. However, the current rapid change of the epidemic situation has led to insufficient time and evidence to develop guidelines and consensus. Therefore, thoracic surgeons need to evaluate specific patient populations at higher risk of severe complications before surgery and weigh the benefit of surgical treatment against the risk of novel coronavirus infection. We try to give some recommendations on lung surgery during the current domestic epidemic situation based on the guidelines and consensus of oncology and thoracic surgery organizations in different regions on lung surgery.Copyright © 2023, Chinese Journal of Lung Cancer. All rights reserved.
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In recent years, the corona virus disease 2019 (COVID-19) pandemic has had a huge impact on the global medical, political and economic fields. Since the beginning of the COVID-19 epidemic, our understanding of the impact of COVID-19 has grown exponentially. Recently, the COVID-19 epidemic has changed rapidly in China, and there has been controversy over how to carry out surgical operations for patients with lung neoplastic lesions. Some studies have shown that lung cancer patients undergoing surgery are more likely to experience respiratory failure and perioperative death after contract-ing COVID-19 than the general population, however, delays in cancer treatment are also associated with increased mortality among these patients. In particular, the novel coronavirus Omikron variant has a higher transmissibility and may escape the immunity obtained through the previous novel coronavirus infection and vaccination. In order to minimize the risk of novel coronavirus infection in surgical patients, it is necessary to develop new treatment guidelines, expert consensus and preventive measures. However, the current rapid change of the epidemic situation has led to insufficient time and evidence to develop guidelines and consensus. Therefore, thoracic surgeons need to evaluate specific patient populations at higher risk of severe complications before surgery and weigh the benefit of surgical treatment against the risk of novel coronavirus infection. We try to give some recommendations on lung surgery during the current domestic epidemic situation based on the guidelines and consensus of oncology and thoracic surgery organizations in different regions on lung surgery.Copyright © 2023, Chinese Journal of Lung Cancer. All rights reserved.
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Background: There have been reports of demyelinating syndromes in association with COVID-19 and to a much lesser extent COVID 19 vaccines. The association between demyelination and vaccines, in general, remains controversial. We review a presentation of fulminant demyelination, and discuss antecedent COVID-19 vaccination, the formulation of a broader differential diagnosis and ultimately the pathologic diagnosis. Case presentation: An 80-year-old woman presented with seizure, encephalopathy, quadriparesis and ultimately expired. She received a SARS-CoV-2 vaccine one day prior. Imaging revealed contrast enhancing cerebral lesions, longitudinally extensive transverse myelitis. CSF was markedly inflammatory. Pathologic examination of the CNS lesions revealed demyelination and inflammation beyond white matter, not restricted to a perivenular distribution. Conclusion(s): This case depicts a seemingly fulminant course of a diffuse demyelinating syndrome characterized clinicopathologically as Marburg's variant of multiple sclerosis. There are several unique aspects of this case including the extremely rapid course, the unusual evolution of CSF abnormalities, with hypoglycorrhachia and markedly elevated protein. The proximity to vaccination is a pertinent association to document, though we cannot unequivocally prove causation.Copyright © 2022 The Authors
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Background: 49 patients underwent Lung Biopsy due to different indications and Post-COVID Pulmonary Fibrosis(PCPF) was suspected in 25 patients. Objective(s): To document the evidence of PCPF in patients with history of suspected COVID 19 infection (in past oneyear) through Transbronchial Lung Biopsy(TBLB)with flexible bronchoscopy. PFT and HRCT gave variedpresentation. Method(s): we have evaluated patients who underwent Lung Biopsy on flexible Bronchoscopy between 08/07/2021 till31/01/2022 at Metro Hospitals and Heath Institute, Meerut, UP, India. The history of exposure to COVID 19 infectionwas taken. Most of these patients underwent Echocardiography (ECHO) for Left Ventricular Ejection Fraction (LVEF)and Pulmonary Artery Pressure (PAH), Pulmonary Function Test (PFT) and High Resolution CT Scan Chest (HRCTChest). Result(s): 49 patients underwent Lung Biopsy. 25 patients gave the history of exposure to COVID 19 infection with complaint of breathlessness and chest discomfort in the last 1 year. HRCT chest was suggestive of Atelectasis in 3 patients, Interstitial Lung Disease (ILD) in 6, Fibrosis in 8, Pulmonary Nodules in 4 and HRCT was not done in 4 patients. PFT showed Mixed Ventilator Defect in 8, Obstructive in 3, Restrictive in 7, small airway disease in 1 and 6 patients couldn't perform PFT. PAH was normal for 6,mild for 16, moderate for 2 and 1 severe. 4 patients had Coronary Artery Disease. 2 patients had major complications like pneumothorax who underwent TBLB. Conclusion(s): PCPF was detected with the help of TBLB in the patients with history of exposure to COVID 19 infection. However, TBLB may cause major complication like pneumothorax seen in 8% cases.
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Aim: The pandemic period has led to social and individual behavioral changes all over the world. In this study, the differences in the admissions of non-coronavirus disease 2019 (non-COVID-19) community-acquired pneumonia cases during the pandemic lockdown period in Turkey were analyzed. Material(s) and Method(s): Patients with suspected COVID-19 and under the age of 18 were excluded, and non-COVID-19, hospitalized community-acquired pneumonia cases were included in this retrospective, cohort study. The analyzes were carried out by creating two groups as before the pandemic (March-May 2019) and the lockdown period of the pandemic (March-May 2020). The number of admissions and mortality rates were taken into consideration as primary outcomes. Result(s): There were 178 cases in the 2019 group and 63 cases in the 2020 group. Gender and age distribution were similar in these two groups. While the rate of intensive care hospitalization was high in the 2020 group, mortality was low (14.3% vs 19.1%);but these differences were not statistically significant. In addition, bilateral infiltration rates were significantly higher in the 2019 group (80.9% vs. 22.2%;p<0.001). Discussion(s): The low number of admissions during the lockdown period shows that there is awareness of the pandemic in society. Again, it can be said that this closure process plays a role in reducing the transmission of infectious diseases such as pneumonia.Copyright © 2022, Derman Medical Publishing. All rights reserved.
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Medicago truncatula in symbiosis with its rhizobial bacterium partner produces more than 700 nodule-specific cysteine-rich (NCR) peptides with diverse physicochemical properties. Most of the cationic NCR peptides have antimicrobial activity and the potential to tackle antimicrobial resistance with their novel modes of action. This work focuses on the antibacterial activity of the NCR169 peptide derivatives as we previously demonstrated that the C-terminal sequence of NCR169 (NCR169C17-38) has antifungal activity, affecting the viability, morphology, and biofilm formation of various Candida species. Here, we show that NCR169C17-38 and its various substituted derivatives are also able to kill ESKAPE pathogens such as Enterococcus faecalis, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Escherichia coli. The replacement of the two cysteines with serines enhanced the antimicrobial activity against most of the tested bacteria, indicating that the formation of a disulfide bridge is not required. As tryptophan can play role in the interaction with bacterial membranes and thus in antibacterial activity, we replaced the tryptophans in the NCR169C17-38C12,17/S sequence with various modified tryptophans, namely 5-methyl tryptophan, 5-fluoro tryptophan, 6-fluoro tryptophan, 7-aza tryptophan, and 5-methoxy tryptophan, in the synthesis of NCR169C17-38C12,17/S analogs. The results demonstrate that the presence of modified fluorotryptophans can significantly enhance the antimicrobial activity without notable hemolytic effect, and this finding could be beneficial for the further development of new AMPs from the members of the NCR peptide family.
Subject(s)
Anti-Bacterial Agents , Tryptophan , Tryptophan/pharmacology , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/chemistry , Peptides/pharmacology , Bacteria , Staphylococcus aureus , Microbial Sensitivity TestsABSTRACT
Over 2 million patients developed lung cancer in 2018, and lung malignancy is responsible for an estimated 1.8 million deaths worldwide. Lung cancer diagnosis usually occurs after suspicious symptoms or incidental radiologic findings on chest imaging when the cancer is probably in an advanced stage. Therefore, initial evaluation, diagnosis, staging, and prompt treatment of lung cancer are required to improve pulmonary malignancies' morbidity and mortality rate. Unfortunately, the size of the tumor, the time of imaging, the quality and quantity of pleural fluid, and pleural biopsy all contribute to diagnostic difficulties in evaluating a lung lesion, leaving even the most astute clinician occasionally perplexed. We discuss a case of a female with lung cancer whose diagnosis was challenging because of a negative pleural biopsy, despite initial radiographic imaging suggesting a lung lesion.
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Objective: To evaluate the diagnostic performance of computed tomography (CT) fluoroscopy-guided percutaneous transthoracic needle biopsy (PTNB) in pulmonary nodules ≤ 10 mm during the coronavirus disease 2019 pandemic. Materials and Methods: Between January 1, 2020 and April 30, 2022, a total of 359 CT fluoroscopy-guided PTNBs were performed at an interventional radiology center. Lung lesions measured between 2 mm and 108 mm. Of the 359 PTNBs, 27 (7.5%) were performed with an 18G core needle on nodules ≤ 10 mm in diameter. Results: Among the 27 biopsies performed on nodules ≤ 10 mm, the lesions measured < 5 mm in four and 5-10 mm in 23. The sensitivity and overall diagnostic accuracy of PTNB were 100% and 92.3%, respectively. The mean dose of ionizing radiation during PTNB was 581.33 mGy*cm (range, 303-1,129 mGy*cm), and the mean biopsy procedure time was 6.6 min (range, 2-12 min). There were no major postprocedural complications. Conclusion: CT fluoroscopy-guided PTNB appears to provide a high diagnostic yield with low complication rates.
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Although multimodal ultrasound approaches have been suggested to potentially improve the diagnosis of thyroid cancer; the diagnostic utility of the combination of SWE and malignancy-risk stratification systems remains vague due to the lack of standardized criteria. The purpose of the study was to assess the diagnostic value of the combination of grey scale ultrasound assessment using EU TIRADS and shear wave elastography. 121 patients (126 nodules-81 benign; 45 malignant) underwent grey scale ultrasound and SWE imaging of nodules between 0.5 cm and 5 cm prior to biopsy and/or surgery. Nodules were analyzed based on size stratifications: <1 cm (n = 43); 1-2 cm (n = 52) and >2 cm (n = 31) and equivocal cytology status (n = 52), and diagnostic performance assessments were conducted. The combination of EU TIRADS with SWE using the SD parameter; maintained a high sensitivity and significantly improved the specificity of sole EU TIRADS for nodules 1-2 cm (SEN: 72.2% vs. 88.9%, p > 0.05; SPEC: 76.5% vs. 55.9%, p < 0.01) and >2 cm (SEN: 71.4% vs. 85.7%, p > 0.05; SPEC: 95.8% vs. 62.5%, p < 0.01). For cytologically-equivocal nodules; the combination with the SWE minimum parameter resulted in a significant reduction in sensitivity with increased specificity (SEN: 60% vs. 80%; SPEC: 83.4% vs. 37.8%; all p < 0.05). SWE in combination with EU TIRADS is diagnostically efficient in discriminating nodules > 1 cm but is not ideal for discriminating cytologically-equivocal nodules.
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Recent advances in deep learning have given rise to high performance in image analysis operations in healthcare. Lung diseases are of particular interest, as most can be identified using non-invasive image modalities. Deep learning techniques such as convolutional neural networks, convolution autoencoders, and graph convolutional networks have been implemented in several pulmonary disease identification applications, e.g., lung nodule classification, Covid-19, and pneumonia detection. Various sources of medical images such as X-rays, computed tomography scans, magnetic resonance imaging, and positron emission tomography scans make deep learning techniques favorable to identify lung diseases with great accuracy. This paper discusses state-of-the-art methods that use deep learning on various medical imaging modalities to detect and classify diseases in the lungs. A description of a few publicly available databases is included in this study, along with some distinct deep learning techniques developed in recent times. Furthermore, several challenges and open research areas for pulmonary disease diagnosis using deep learning are discussed. The objective of this work is to direct researchers in the field of diagnosis of lung diseases.
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Lung cancer is the uncontrolled growth of abnormal cells in one or both lungs. This is one of the dangerous diseases. A lot of feature extraction with classification methods were discussed previously regarding this disease, but none of the methods give sufficient results, not only that, those methods have high over fitting problem, as a result, the detection accuracy was minimizing. Therefore, to overcome these issues, a Lung Disease Detection using Self-Attention Generative Adversarial Capsule Network optimized with Sun flower Optimization Algorithm (SA-Caps GAN-SFOA-LDC) is proposed in this manuscript. Initially, NIH chest X-ray image dataset is gathered through Kaggle repository to diagnose the lung disease. Then, the chests X-ray images are pre-processed by using the contrast limited adaptive histogram equalization (CLAHE) filtering method to eliminate the noise and to enhance the image quality. These pre-processed outputs are fed to feature extraction process. In the feature extraction process, the empirical wavelet transform method is used. These extracted features are given into Self-Attention based Generative Adversarial Capsule classifier for detecting the lung disease. The hyper parameters of SA-Caps GAN classifier is optimized using Sun flower Optimization Algorithm. The simulation is implemented in MATLAB. The proposed SA-Caps GAN-SFOA-LDC method attains higher accuracy 21.05%, 33.28%, 30.27%, 29.68%, 32.57% and 44.28%, Higher Precision 30.24%, 35.68%, 32.08%, 41.27%, 28.57% and 34.20%, Higher F-Score 32.05%, 31.05%, 36.24%, 30.27%, 37.59% and 22.05% analyzed with the existing methods, SVM-SMO-LDC, CNN-MOSHO-LDC, XGboost-PSO-LDC respectively. © 2022 Elsevier Ltd