Application of Multi-Slice Spiral CT in the Evaluation of Diffuse Lung Diseases

This article analyzes the manifestations, characteristics, and significance of multi-slice spiral CT for diffuse lung disease, and evaluates the diagnostic value of multi-slice CT multi-directional reconstruction for diffuse lung disease. After performing multi-slice spiral CT examination on the patient and collecting relevant data, the characteristic multi-slice CT imaging findings of diffuse lung disease were determined by statistical analysis. Diffuse lung disease is representative in multi-slice spiral CT image imaging manifestations of the disease include multiple disseminated small nodules, multiple voids, ground glass shadows, and lung consolidation. And analyze the correlation of image performance, and then use statistical methods to analyze and evaluate the value of multi-slice spiral CT characteristic images in the diagnosis of diffuse lung disease, and analyze the characteristics of these characteristic multi-slice CT image appearances. The use of high-resolution CT to screen the characteristic CT imaging findings of the same research object, and then to perform a statistical analysis of the diagnostic differences with multi-slice spiral CT, further confirmed the importance of multi-slice CT for diffuse lung disease Diagnostic value. Studies have shown that multi-slice CT imaging technology is of great significance in the evaluation of diffuse lung diseases.

Spectrum of childhood interstitial and diffuse lung diseases at a tertiary hospital in Egypt

BackgroundChildhood interstitial and diffuse lung diseases (chILD) encompass a broad spectrum of rare pulmonary disorders. In most developing middle eastern countries, chILD is still underdiagnosed. Objective: To describe and investigate patients diagnosed with chILD in a tertiary university hospital in Egypt.MethodsWe analyzed data of consecutive subjects (<18 years) referred for further evaluation at the Children's Hospital, Ain Shams University. Diagnosis of chILD was made in accordance with the chILD-EU criteria. The following information was obtained: demographic data, clinical characteristics, chest CT findings, laboratory studies, spirometry, BAL and histopathology findings.Results22 subjects were enrolled over 24 months. Median age at diagnosis was 7 years (range 3.5–14 years). The most common manifestations were dyspnea (100%), cough (90.9%), clubbing (95.5%) and tachypnea (90.9%). Systematic evaluation led to the following diagnoses: hypersensitivity pneumonitis (n=3), idiopathic interstitial pneumonias (n=4), chILD related to chronic granulomatous disease (n=3), chILD related to small airway disease (n=3), postinfectious chILD (n=2), Langerhans cell histiocytosis (n=2), Idiopathic pulmonary hemosiderosis (n=2), granulomatous lymphocytic interstitial lung disease (n=1), systemic sclerosis (n=1), familial interstitial lung disease (n=1). Among the subjects who completed the diagnostic evaluation (n=19), treatment was changed in 13 (68.4%) subjects.ConclusionSystematic evaluation and multidisciplinary peer review of chILD patients at our tertiary hospital led to changes in management in 68% of the patients. This study also highlights the need for an Egyptian chILD network with genetic testing, as well as the value of collaborating with international groups in improving health care for children with chILD.

Development and evaluation of a computer-based decision support system for diffuse lung diseases at high-resolution computed tomography

Background High-resolution computed tomography (HRCT) is essential in narrowing the possible differential diagnoses of diffuse and interstitial lung diseases. Purpose To investigate the value of a novel computer-based decision support system (CDSS) for facilitating diagnosis of diffuse lung diseases at HRCT. Material and Methods A CDSS was developed that includes about 100 different illustrations of the most common HRCT signs and patterns and describes the corresponding pathologies in detail. The logical set-up of the software facilitates a structured evaluation. By selecting one or more CT patterns, the program generates a ranked list of the most likely differential diagnoses. Three independent and blinded radiology residents initially evaluated 40 cases with different lung diseases alone; after at least 12 weeks, observers re-evaluated all cases using the CDSS. Results In 40 patients, a total of 113 HRCT patterns were evaluated. The percentage of correctly classified patterns was higher with CDSS (96.8%) compared to assessment without CDSS (90.3%; P < 0.01). Moreover, the percentage of correct diagnosis (81.7% vs. 64.2%) and differential diagnoses (89.2% vs. 38.3%) were superior with CDSS compared to evaluation without CDSS (both P < 0.01). Conclusion Addition of a CDSS using a structured approach providing explanations of typical HRCT patterns and graphical illustrations significantly improved the performance of trainees in characterizing and correctly identifying diffuse lung diseases.

SPECTRUM OF HRCT CHEST FINDINGS IN COVID-19

INTRODUCTION: Coronavirus (COVID-19) pandemic is current ongoing pandemic in world since its outbreak in Wuhan China in December 2019. It has affected 78.8 million people with 1.7 million deaths worldwide till date (23rd December 2020). To evaluate spectrum of HRCT AIMS: Chest ndings in patients infected with SARS-CoV-2 i.e. COVID-19. HRCT were done in MATERIAL AND METHODS: 242 patients with SARS-CoV-2 RT-PCR positive status admitted in our COVID CARE CENTRE. HRCT is useful in assessment of severity of COVID-19 infection and subsequent plan for the treatment. HRCT of the chest obtains thin-slice chest images and process in a high-spatial-frequency reconstruction algorithm. This technique obtains images with exquisite lung detail, which are ideal for the assessment of diffuse lung diseases. RESULTS: Ground glass opacication is predominant nding present in majority of cases of COVID-19. Other common ndings include crazy paving pattern, consolidation, vascular dilation and subpleural linear opacities. These ndings can aid in early diagnosis of COVID-19. ABBREVIATIONS: HRCT (High-resolution computed tomography), COVID-19(Coronavirus disease-19), SARS-CoV-2(severe acute respiratory syndrome coronavirus 2), GGO (ground glass opacication), ARDS (acute respiratory distress syndrome), RT-PCR (reverse transcriptase-polymerase chain reaction), DIC (disseminated intravascular coagulation), DVT (deep vein thrombosis).

The Value of Transbronchial Lung Biopsy in the Diagnosis of Lymphangioleiomyomatosis

BACKGROUND: Transbronchial lung biopsy (TBLB) in the diagnosis of lymphangioleiomyomatosis (LAM) is not a common approach, although TBLB is often performed in diffuse lung diseases. We aimed to examine the diagnostic value and safety of TBLB in LAM patients based on the data collected in our center.METHODS: We reviewed LAM patients registered with the LAM Clinic in our hospital from December 8, 2006, to December 30, 2019. All patients with definite or probable diagnosis of LAM who had been examined using TBLB were included. All available pathology slides were reviewed by an experienced LAM pathologist. All complications were reviewed by the medical record and confirmed using telephone interviews.RESULTS: The pathology results of 86 patients (including 74 definite LAM and 12 probable LAM) were available. The positive rate of TBLB in LAM patients was 49/86 (57.0%). The positive rates of SMA, HMB-45, ER, and PR in LAM patients were 97.6%, 93%, 84.6%, and 78.4%, respectively. The positive rate of TBLB was 40%, 60% and 60.8% in mild, moderate, or severe LAM patients, respectively, and the difference was not significant. Patients who had 3-4 or 5-6 biopsied specimens had a higher rate of diagnosis than those with 1-2 biopsied specimens. Four patients (5.6%) reported pneumothorax. No major hemoptysis was reported.CONCLUSIONS: TBLB is a feasible and safe procedure for obtaining a pathological diagnosis of LAM. Taking more than 2 samples during the biopsy procedure increased the rate of diagnosis.

ILDGDB: a manually curated database of genomics, transcriptomics, proteomics and drug information for interstitial lung diseases

Background Interstitial lung diseases (ILDs), a diverse group of diffuse lung diseases, mainly affect the lung parenchyma. The low-throughput ‘omics’ technologies (genomics, transcriptomics, proteomics) and relative drug information have begun to reshaped our understanding of ILDs, whereas, these data are scattered among massive references and are difficult to be fully exploited. Therefore, we manually mined and summarized these data at a database (ILDGDB, http://ildgdb.org/) and will continue to update it in the future. Main body The current version of ILDGDB incorporates 2018 entries representing 20 ILDs and over 600 genes obtained from over 3000 articles in four species. Each entry contains detailed information, including species, disease type, detailed description of gene (e.g. official symbol of gene), and the original reference etc. ILDGDB is free, and provides a user-friendly web page. Users can easily search for genes of interest, view their expression pattern and detailed information, manage genes sets and submit novel ILDs-gene association. Conclusion The main principle behind ILDGDB’s design is to provide an exploratory platform, with minimum filtering and interpretation, while making the presentation of the data very accessible, which will provide great help for researchers to decipher gene mechanisms and improve the prevention, diagnosis and therapy of ILDs.