scholarly journals Clinical characteristics and chest computed tomography findings related to the infectivity of pulmonary tuberculosis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yuanyuan Wang ◽  
Xiaoqian Shang ◽  
Liang Wang ◽  
Jiahui Fan ◽  
Fengming Tian ◽  
...  

Abstract Aim This study mainly evaluates the clinical characteristics and chest chest computed tomography (CT) findings of AFB-positive and AFB-negative pulmonary tuberculosis (PTB) patients to explore the relationship between AFB-positive and clinico-radiological findings. Methods A retrospective analysis of 224 hospitalized tuberculosis patients from 2018 to 2020 was undertaken. According to the AFB smear results, they were divided into AFB-positive pulmonary tuberculosis (positive by Ziehl–Neelsen staining) and AFB-negative pulmonary tuberculosis and patients’ CT results and laboratory test results were analyzed. Results A total of 224 PTB patients were enrolled. AFB-positive (n = 94, 42%) and AFB-negative (n = 130, 58%). AFB-positive patients had more consolidation (77.7% vs. 53.8%, p < 0.01), cavity (55.3% vs. 34.6%, p < 0.01), calcification (38.3% vs. 20%, p < 0.01), bronchiectasis (7.5% vs. 1.5%, p < 0.05), bronchiarctia (6.4% vs. 0.8%, p < 0.05), and right upper lobe involvement (57.5% vs. 33.1%, p < 0.01), left upper lobe involvement (46.8% vs. 33.1%, p < 0.05) and lymphadenopathy (58.5% vs. 37.7%, p < 0.01). Conclusion The study found that when pulmonary tuberculosis patients have consolidation, cavity, upper lobe involvement and lymphadenopathy on chest CT images, they may have a higher risk of AFB-positive tuberculosis.

2021 ◽  
Vol 37 (6-WIT) ◽  
Author(s):  
Feng Zhu ◽  
Bo Zhang

Objective: We used U-shaped convolutional neural network (U_Net) multi-constraint image segmentation method to compare the diagnosis and imaging characteristics of tuberculosis and tuberculosis with lung cancer patients with Computed Tomography (CT). Methods: We selected 160 patients with tuberculosis from the severity scoring (SVR) task is provided by Image CLEF Tuberculosis 2019. According to the type of diagnosed disease, they were divided into tuberculosis combined with lung cancer group and others group, all patients were given chest CT scan, and the clinical manifestations, CT characteristics, and initial suspected diagnosis and missed diagnosis of different tumor diameters were observed and compared between the two groups. Results: There were more patients with hemoptysis and hoarseness in pulmonary tuberculosis combined with lung cancer group than in the pulmonary others group (P<0.05), and the other symptoms were not significantly different (P>0.05). Tuberculosis combined with lung cancer group had fewer signs of calcification, streak shadow, speckle shadow, and cavitation than others group; however, tuberculosis combined with lung cancer group had more patients with mass shadow, lobular sign, spines sign, burr sign and vacuole sign than others group. Conclusion: The symptoms of hemoptysis and hoarseness in pulmonary tuberculosis patients need to consider whether the disease has progressed and the possibility of lung cancer lesions. CT imaging of pulmonary tuberculosis patients with lung cancer usually shows mass shadows, lobular signs, spines signs, burr signs, and vacuoles signs. It can be used as the basis for its diagnosis. Simultaneously, the U-Net-based segmentation method can effectively segment the lung parenchymal region, and the algorithm is better than traditional algorithms. doi: https://doi.org/10.12669/pjms.37.6-WIT.4795 How to cite this:Zhu F, Zhang B. Analysis of the Clinical Characteristics of Tuberculosis Patients based on Multi-Constrained Computed Tomography (CT) Image Segmentation Algorithm. Pak J Med Sci. 2021;37(6):1705-1709. doi: https://doi.org/10.12669/pjms.37.6-WIT.4795 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


2018 ◽  
Vol 6 (2) ◽  
pp. 30-35
Author(s):  
Ade Ella Nur Rizky Oktaviyanti

One of the factors that influence compliance is individual motivation. There are still many pulmonary tuberculosis patients who do not wear masks, this can have an impact on disease transmission. Poor individual motivation can affect someone's compliance. The purpose of this research is to determine the relationship of patient motivation regarding prevention of transmission with adherence to the use of masks in patients with pulmonary tuberculosis in Rambipuji Health Center, Jember Regency. This research uses descriptive correlative type of research. In this study using a cross-sectional approach. The sample of this study was taken using simple random sampling, namely pulmonary tuberculosis patients at the Rambipuji Health Center in Jember Regency, totaling 105 patients but only 50 patients were used as samples. This research was conducted by giving a questionnaire to pulmonary tuberculosis patients to find out the patient's motivation about preventing transmission by adhering to the use of masks. The results of the study were analyzed using the Lambda Correlation Test, the results of the analysis found that the motivation of patients was good motivation (22%), patient motivation was sufficient (56%), and patient motivation was less motivation (22%). Whereas adherence to the use of masks in pulmonary tuberculosis patients is compliant (36%), and non-compliant (64%). The Lambda Correlation Test results obtained from the variable compliance with ρ = 0.389 positive direction with a value of ρ count of 0.027 <0.05 which means there is a relationship between patient motivation about prevention of transmission with compliance with the use of masks in patients with pulmonary tuberculosis in Rambipuji Health Center, Jember District. It is recommended that further studies be able to conduct more in-depth research related to the relationship of patient motivation regarding the prevention of transmission with adherence to the use of masks in pulmonary tuberculosis patients


Author(s):  
Shimaa Farghaly ◽  
Marwa Makboul

Abstract Background Coronavirus disease 2019 (COVID-19) is the most recent global health emergency; early diagnosis of COVID-19 is very important for rapid clinical interventions and patient isolation; chest computed tomography (CT) plays an important role in screening, diagnosis, and evaluating the progress of the disease. According to the results of different studies, due to high severity of the disease, clinicians should be aware of the different potential risk factors associated with the fatal outcome, so chest CT severity scoring system was designed for semi-quantitative assessment of the severity of lung disease in COVID-19 patients, ranking the pulmonary involvement on 25 points severity scale according to extent of lung abnormalities; this study aims to evaluate retrospectively the relationship between age and severity of COVID-19 in both sexes based on chest CT severity scoring system. Results Age group C (40–49 year) was the commonest age group that was affected by COVID-19 by 21.3%, while the least affected group was group F (≥ 70 years) by only 6.4%. As regards COVID-RADS classification, COVID-RADS-3 was the most commonly presented at both sexes in all different age groups. Total CT severity lung score had a positive strong significant correlation with the age of the patient (r = 0.64, P < 0.001). Also, a positive strong significant correlation was observed between CT severity lung score and age in both males and females (r = 0.59, P < 0.001) and (r = 0.69, P < 0.001) respectively. Conclusion We concluded that age can be considered as a significant risk factor for the severity of COVID-19 in both sexes. Also, CT can be used as a significant diagnostic tool for the diagnosis of COVID-19 and evaluation of the progression and severity of the disease.


2014 ◽  
Vol 4 ◽  
pp. 38 ◽  
Author(s):  
Lukas Ebner ◽  
Felix Knobloch ◽  
Adrian Huber ◽  
Julia Landau ◽  
Daniel Ott ◽  
...  

Objective: The aim of the present study was to evaluate a dose reduction in contrast-enhanced chest computed tomography (CT) by comparing the three latest generations of Siemens CT scanners used in clinical practice. We analyzed the amount of radiation used with filtered back projection (FBP) and an iterative reconstruction (IR) algorithm to yield the same image quality. Furthermore, the influence on the radiation dose of the most recent integrated circuit detector (ICD; Stellar detector, Siemens Healthcare, Erlangen, Germany) was investigated. Materials and Methods: 136 Patients were included. Scan parameters were set to a thorax routine: SOMATOM Sensation 64 (FBP), SOMATOM Definition Flash (IR), and SOMATOM Definition Edge (ICD and IR). Tube current was set constantly to the reference level of 100 mA automated tube current modulation using reference milliamperes. Care kV was used on the Flash and Edge scanner, while tube potential was individually selected between 100 and 140 kVp by the medical technologists at the SOMATOM Sensation. Quality assessment was performed on soft-tissue kernel reconstruction. Dose was represented by the dose length product. Results: Dose-length product (DLP) with FBP for the average chest CT was 308 mGy*cm ± 99.6. In contrast, the DLP for the chest CT with IR algorithm was 196.8 mGy*cm ± 68.8 (P = 0.0001). Further decline in dose can be noted with IR and the ICD: DLP: 166.4 mGy*cm ± 54.5 (P = 0.033). The dose reduction compared to FBP was 36.1% with IR and 45.6% with IR/ICD. Signal-to-noise ratio (SNR) was favorable in the aorta, bone, and soft tissue for IR/ICD in combination compared to FBP (the P values ranged from 0.003 to 0.048). Overall contrast-to-noise ratio (CNR) improved with declining DLP. Conclusion: The most recent technical developments, namely IR in combination with integrated circuit detectors, can significantly lower radiation dose in chest CT examinations.


2020 ◽  
pp. 084653712091883 ◽  
Author(s):  
Bingkun Jie ◽  
Xiaojin Liu ◽  
Huaqian Suo ◽  
Guoqing Qiao ◽  
Qingshui Zheng ◽  
...  

Purpose: To explore the clinical and dynamic computed tomography features of coronavirus disease 2019. Methods: We enrolled 24 patients with coronavirus disease 2019 treated at a regional center in Dezhou, China, from January 22 to February 5, 2020, and analyzed data retrospectively. Results: Nineteen cases had close contact with people with coronavirus disease 2019, and five patients denied a travel history in Wuhan City or contact with patients having coronavirus disease 2019. Symptoms were fever, cough, chest tightness, dyspnea, fatigue, and muscle pain. Chest computed tomography showed multiple ground-glass opacities distributed along peribronchial bundles and subpleural areas, often accompanied by bronchiectasis, vascular thickening, and interlobular septal thickening after coronavirus disease 2019 progression. Conclusions: Coronavirus disease 2019 has certain clinical characteristics and typical computed tomography features.


2020 ◽  
Vol 245 (13) ◽  
pp. 1096-1103 ◽  
Author(s):  
Molly D Wong ◽  
Theresa Thai ◽  
Yuhua Li ◽  
Hong Liu

The rapid and dramatic increase in confirmed cases of COVID-19 has led to a global pandemic. Early detection and containment are currently the most effective methods for controlling the outbreak. A positive diagnosis is determined by laboratory real-time reverse transcriptase polymerase chain reaction (rRT-PCR) testing, but the use of chest computed tomography (CT) has also been indicated as an important tool for detection and management of the disease. Numerous studies reviewed in this paper largely concur in their findings that the early hallmarks of COVID-19 infection are ground-glass opacities (GGOs), often with a bilateral and peripheral lung distribution. In addition, most studies demonstrated similar CT findings related to the progression of the disease, starting with GGOs in early disease, followed by the development of crazy paving in middle stages and finally increasing consolidation in the later stages of the disease. Studies have reported a low rate of misdiagnosis by chest CT, as well as a high rate of misdiagnosis by the rRT-PCR tests. Specifically, chest CT provides more accurate results in the early stages of COVID-19, when it is critical to begin treatment as well as isolate the patient to avoid the spread of the virus. While rRT-PCR will probably remain the definitive final test for COVID-19, until it is more readily available and can consistently provide higher sensitivity, the use of chest CT for early stage detection has proven valuable in avoiding misdiagnosis as well as monitoring the progression of the disease. With the understanding of the role of chest CT, researchers are beginning to apply deep learning and other algorithms to differentiate between COVID-19 and non-COVID-19 CT scans, determine the severity of the disease to guide the course of treatment, and investigate numerous additional COVID-19 applications. Impact statement The impact of the COVID-19 pandemic has been worldwide, and clinicians and researchers around the world have been working to develop effective and efficient methods for early detection as well as monitoring of the disease progression. This minireview compiles the various agency and expert recommendations, along with results from studies published in numerous countries, in an effort to facilitate the research in imaging technology development to benefit the detection and monitoring of COVID-19. To the best of our knowledge, this is the first review paper on the topic, and it provides a brief, yet comprehensive analysis.


2019 ◽  
Vol 56 (2) ◽  
pp. 285-293 ◽  
Author(s):  
Darin B White ◽  
Megan J Hora ◽  
Sarah M Jenkins ◽  
Randolph S Marks ◽  
Yolanda I Garces ◽  
...  

Abstract OBJECTIVES The aim of this study is to evaluate the efficacy of chest computed tomography (CT) to predict the pathological stage of thymic epithelial tumours (TET) using the recently introduced tumour, node and metastasis (TNM) staging with comparison to the modified Masaoka staging. METHODS Preoperative chest CT examinations in cases of resected TET with sampled lymph nodes (2006–2016) were retrospectively reviewed by 2 thoracic radiologists and radiologically (r) staged using both staging systems. A thoracic pathologist reviewed all cases for the pathological (p) stage. Concordance between r-staging and p-staging was assessed by % agreement and unweighted kappa statistics. Associations between r-stage and p-stage with outcomes were assessed using the Cox proportional hazards regression. RESULTS Sixty patients with TET were included (47 thymomas, 12 thymic carcinomas and 1 atypical carcinoid tumour). Sixteen patients (26.7%) had received neoadjuvant therapy. Fifty-four patients (90.0%) had complete resection. The overall agreement between the r-stage and p-stage was 66.7% (κ = 0.46) for TNM staging and 46.7% (κ = 0.30) for modified Masaoka staging. Agreement between r-assessment and p-assessment of the T, N and M components of the TNM stage was 61.7% (κ = 0.28), 86.7% (κ = 0.48) and 98.3% (κ = 0.88), respectively. CT overstaged 12 patients (20.0%) for TNM staging and 12 patients (20.0%) for modified Masaoka staging and understaged 8 (13.3%) and 20 (33.3%) patients for TNM staging modified Masaoka staging, respectively. The r-TNM staging accuracy was lower for patients with neoadjuvant therapy (50.0% with vs 72.7% without). During a median follow-up of 2.6 years (range 0.1–10.5 years), 12 patients had metastases and/or recurrence; 11 patients died (4 of disease). The r-TNM stage and modified Masaoka stage were associated with overall survival and progression-free survival (P < 0.001). CONCLUSIONS Preoperative chest CT is able to accurately predict p-TNM stage in two-thirds of surgically resected TET, with an agreement between radiological staging and pathological staging superior to the modified Masaoka staging.


Sign in / Sign up

Export Citation Format

Share Document