The Diagnostic Performance of Chest Ultrasonography in the Up-to-date Workup in Patients with Chest Diseases

Background: Application of chest radiography for all patients with chest diseases is associated with a significant increase in total costs, exposure to radiation, and overcrowding of the emergency department in case of emergency. Ultrasound has been introduced as an alternative diagnostic tool in this regard. The aim of the work is to determine sensitivity, specificity and diagnostic accuracy of chest ultrasonography as an easy and fast form of imagery for different thoracic conditions. Results: This prospective study was carried out on sixty patients. The majority of patients presented with lung masses (20%) and pleural effusion (16.7%). Chest US findings showed great concordance or agreement with the chest CT findings. The only lower concordance is noted in the diagnosis of pulmonary nodules or mass, where chest US reported pulmonary nodules or mass in 33.3% of patients compared to 46.7%% by chest CT. US showed a highly comparable diagnostic performance in chest-related pathological entities, compared to chest CT. Chest US had 100% sensitivity in detecting all pathological chest entities except for lung collapse (83.3%) and pulmonary nodules (71.4%). However, chest US was more specific than sensitive. It had 100% specificity in all pathological entities except for lung collapse consolidation. Chest US had 100% diagnostic accuracy in all chest-related pathological entities except for lung collapse consolidation and pulmonary nodules or masses. However, when presenting these findings among male and female patients, Chest US had better overall diagnostic accuracy among female patients than male patients. Conclusion: US examination of the chest is a noninvasive and promising bedside tool for the examination of respiratory problems patients. Consequently, chest ultrasonography can be adjoined in the up-to-date work-up of the outpatients as an ancillary tool aiding in disease diagnosis.

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Diagnostic performance of chest CT in differentiating COVID-19 from other causes of ground-glass opacities

Egyptian Journal of Radiology and Nuclear Medicine ◽

10.1186/s43055-020-00398-6 ◽

2021 ◽

Vol 52 (1) ◽

Author(s):

Ali H. Elmokadem ◽

Dalia Bayoumi ◽

Sherif A. Abo-Hedibah ◽

Ahmed El-Morsy

Keyword(s):

Diagnostic Performance ◽

Pulmonary Nodules ◽

Ground Glass Opacity ◽

Chest Ct ◽

Ground Glass ◽

Rt Pcr ◽

Laboratory Findings ◽

Halo Sign ◽

Traction Bronchiectasis ◽

Chest Ct Scan

Abstract Background To evaluate the diagnostic performance of chest CT in differentiating coronavirus disease 2019 (COVID-19) and non-COVID-19 causes of ground-glass opacities (GGO). Results A total of 80 patients (49 males and 31 females, 46.48 ± 16.09 years) confirmed with COVID-19 by RT-PCR and who underwent chest CT scan within 2 weeks of symptoms, and 100 patients (55 males and 45 females, 48.94 ± 18.97 years) presented with GGO on chest CT were enrolled in the study. Three radiologists reviewed all CT chest exams after removal of all identifying data from the images. They expressed the result as positive or negative for COVID-19 and recorded the other pulmonary CT features with mention of laterality, lobar affection, and distribution pattern. The clinical data and laboratory findings were recorded. Chest CT offered diagnostic accuracy ranging from 59 to 77.2% in differentiating COVID-19- from non-COVID-19-associated GGO with sensitivity from 76.25 to 90% and specificity from 45 to 67%. The specificity was lower when differentiating COVID-19 from non-COVID-19 viral pneumonias (30.5–61.1%) and higher (53.1–70.3%) after exclusion of viral pneumonia from the non-COVID-19 group. Patients with COVID-19 were more likely to have lesions in lower lobes (p = 0.005), peripheral distribution (p < 0.001), isolated ground-glass opacity (p = 0.043), subpleural bands (p = 0.048), reverse halo sign (p = 0.005), and vascular thickening (p = 0.013) but less likely to have pulmonary nodules (p < 0.001), traction bronchiectasis (p = 0.005), pleural effusion (p < 0.001), and lymphadenopathy (p < 0.001). Conclusions Chest CT offered reasonable sensitivity when differentiating COVID-19- from non-COVID-19-associated GGO with low specificity when differentiating COVID-19 from other viral pneumonias and moderate specificity when differentiating COVID-19 from other causes of GGO.

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Is diagnostic accuracy for detecting pulmonary nodules in chest CT reduced after a long day of reading?

10.1117/12.910748 ◽

2012 ◽

Cited By ~ 1

Author(s):

Elizabeth A. Krupinski ◽

Kevin S. Berbaum ◽

Robert Caldwell ◽

Kevin M. Schartz

Keyword(s):

Diagnostic Accuracy ◽

Pulmonary Nodules ◽

Chest Ct ◽

Long Day

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Diagnostic Accuracy of Machine Learning-Based Radiomics in Grading Gliomas: Systematic Review and Meta-Analysis

Contrast Media & Molecular Imaging ◽

10.1155/2020/2127062 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Curtis K. Sohn ◽

Sotirios Bisdas

Keyword(s):

Machine Learning ◽

Diagnostic Accuracy ◽

Diagnostic Performance ◽

Meta Analysis ◽

Total Sample ◽

Low Grade ◽

Sample Sizes ◽

Summary Receiver Operating Characteristic ◽

Pubmed Database ◽

Sensitivity Specificity

Purpose. This study aimed to estimate the diagnostic accuracy of machine learning- (ML-) based radiomics in differentiating high-grade gliomas (HGG) from low-grade gliomas (LGG) and to identify potential covariates that could affect the diagnostic accuracy of ML-based radiomic analysis in classifying gliomas. Method. A primary literature search of the PubMed database was conducted to find all related literatures in English between January 1, 2009, and May 1, 2020, with combining synonyms for “machine learning,” “glioma,” and “radiomics.” Five retrospective designed original articles including LGG and HGG subjects were chosen. Pooled sensitivity, specificity, their 95% confidence interval, area under curve (AUC), and hierarchical summary receiver-operating characteristic (HSROC) models were obtained. Result. The pooled sensitivity when diagnosing HGG was higher (96% (95% CI: 0.93, 0.98)) than the specificity when diagnosing LGG (90% (95% CI 0.85, 0.93)). Heterogeneity was observed in both sensitivity and specificity. Metaregression confirmed the heterogeneity in sample sizes ( p = 0.05 ), imaging sequence types ( p = 0.02 ), and data sources ( p = 0.01 ), but not for the inclusion of the testing set ( p = 0.19 ), feature extraction number ( p = 0.36 ), and selection of feature number ( p = 0.18 ). The results of subgroup analysis indicate that sample sizes of more than 100 and feature selection numbers less than the total sample size positively affected the diagnostic performance in differentiating HGG from LGG. Conclusion. This study demonstrates the excellent diagnostic performance of ML-based radiomics in differentiating HGG from LGG.

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Comparative accuracy and cost-effectiveness of dynamic contrast-enhanced CT and positron emission tomography in the characterisation of solitary pulmonary nodules

Thorax ◽

10.1136/thoraxjnl-2021-216948 ◽

2021 ◽

pp. thoraxjnl-2021-216948

Author(s):

Fiona J Gilbert ◽

Scott Harris ◽

Kenneth A Miles ◽

Jonathan R Weir-McCall ◽

Nagmi R Qureshi ◽

...

Keyword(s):

Cost Effectiveness ◽

Diagnostic Accuracy ◽

Pulmonary Nodules ◽

Solitary Pulmonary Nodules ◽

Contrast Enhanced Ct ◽

Positron Emission ◽

Contrast Enhanced ◽

Pet Ct ◽

Enhanced Ct ◽

Sensitivity Specificity

IntroductionDynamic contrast-enhanced CT (DCE-CT) and positron emission tomography/CT (PET/CT) have a high reported accuracy for the diagnosis of malignancy in solitary pulmonary nodules (SPNs). The aim of this study was to compare the accuracy and cost-effectiveness of these.MethodsIn this prospective multicentre trial, 380 participants with an SPN (8–30 mm) and no recent history of malignancy underwent DCE-CT and PET/CT. All patients underwent either biopsy with histological diagnosis or completed CT follow-up. Primary outcome measures were sensitivity, specificity and overall diagnostic accuracy for PET/CT and DCE-CT. Costs and cost-effectiveness were estimated from a healthcare provider perspective using a decision-model.Results312 participants (47% female, 68.1±9.0 years) completed the study, with 61% rate of malignancy at 2 years. The sensitivity, specificity, positive predictive value and negative predictive values for DCE-CT were 95.3% (95% CI 91.3 to 97.5), 29.8% (95% CI 22.3 to 38.4), 68.2% (95% CI 62.4% to 73.5%) and 80.0% (95% CI 66.2 to 89.1), respectively, and for PET/CT were 79.1% (95% CI 72.7 to 84.2), 81.8% (95% CI 74.0 to 87.7), 87.3% (95% CI 81.5 to 91.5) and 71.2% (95% CI 63.2 to 78.1). The area under the receiver operator characteristic curve (AUROC) for DCE-CT and PET/CT was 0.62 (95% CI 0.58 to 0.67) and 0.80 (95% CI 0.76 to 0.85), respectively (p<0.001). Combined results significantly increased diagnostic accuracy over PET/CT alone (AUROC=0.90 (95% CI 0.86 to 0.93), p<0.001). DCE-CT was preferred when the willingness to pay per incremental cost per correctly treated malignancy was below £9000. Above £15 500 a combined approach was preferred.ConclusionsPET/CT has a superior diagnostic accuracy to DCE-CT for the diagnosis of SPNs. Combining both techniques improves the diagnostic accuracy over either test alone and could be cost-effective.Trial registration numberNCT02013063

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Diagnostic Performance of Two-Dimensional Speckle Tracking Echocardiography for Detection of Obstructive Coronary Artery Disease: A Meta-Analysis.

10.22541/au.160952100.08353836/v1 ◽

2021 ◽

Author(s):

Arun Kannan ◽

Jaspreet Singh ◽

Vincent Sorrell ◽

Aiden Abidov

Keyword(s):

Confidence Interval ◽

Diagnostic Accuracy ◽

Odds Ratio ◽

Diagnostic Performance ◽

Stress Echocardiography ◽

Longitudinal Strain ◽

Speckle Tracking Echocardiography ◽

Meta Analysis ◽

Artery Disease ◽

Sensitivity Specificity

Background: Two-dimensional speckle tracking echocardiography (STE) is a quantitative myocardial strain imaging technique in evaluating global and segmental myocardial deformation. The aim of the meta-analysis was to determine the diagnostic accuracy of STE in the detection of significant coronary artery disease (CAD) in patients undergoing resting or stress echocardiography. Methods: We performed a literature search in PubMed and Medline until March 2020 for studies evaluating the role of STE in diagnosing CAD. We assessed the diagnostic performance of STE in detecting CAD by using the pooled estimate of sensitivity, specificity, likelihood ratio, diagnostic odds ratio and diagnostic accuracy. We analyzed longitudinal strain data that were reported in resting and stress echocardiography. Results: A total of 17 studies (n=1762) were included for the analysis. 12 studies (n=1239) reported global longitudinal strain (GLS) in resting echocardiography and 5 studies (n=523) reported GLS in stress echocardiography. Overall, in resting echocardiography studies, pooled GLS sensitivity and specificity for predicting obstructive CAD data were calculated to be 79% (95% confidence interval 74-83%) and 77% (95% confidence interval 72-82%), respectively. The pooled odds ratio was 13.6 (95% confidence interval 8.7-21.5). When we considered the dobutamine stress echocardiograms alone, the sensitivity and specificity in predicting obstructive CAD was 77% (95% confidence interval 59-89%) and 78% (95% confidence interval 53-92%), respectively. The odds ratio was 12.6 (95% confidence interval 2.7-58.5). Conclusions: In this meta-analysis of patients with suspected CAD, we found that STE could effectively detect obstructive CAD with a high diagnostic sensitivity, specificity and diagnostic accuracy

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The value of S-Detect in improving the diagnostic performance of radiologists for the differential diagnosis of thyroid nodules

Medical Ultrasonography ◽

10.11152/mu-2501 ◽

2020 ◽

Vol 22 (4) ◽

pp. 415

Author(s):

Qi Wei ◽

Shu-E Zeng ◽

Li-Ping Wang ◽

Yu-Jing Yan ◽

Ting Wang ◽

...

Keyword(s):

Diagnostic Accuracy ◽

Predictive Value ◽

Diagnostic Performance ◽

Thyroid Nodules ◽

Characteristic Curve ◽

Diagnostic Value ◽

Ultrasound Images ◽

Experienced Radiologist ◽

Before And After ◽

Sensitivity Specificity

Aims: To compare the diagnostic value of S-Detect (a computer aided diagnosis system using deep learning) in differentiating thyroid nodules in radiologists with different experience and to assess if S-Detect can improve the diagnostic performance of radiologists.Materials and methods: Between February 2018 and October 2019, 204 thyroid nodules in 181 patients were included. An experienced radiologist performed ultrasound for thyroid nodules and obtained the result of S-Detect. Four radiologists with different experience on thyroid ultrasound (Radiologist 1, 2, 3, 4 with 1, 4, 9, 20 years, respectively) analyzed the conventional ultrasound images of each thyroid nodule and made a diagnosis of “benign” or “malignant” based on the TI-RADS category. After referring to S-Detect results, they re-evaluated the diagnoses. The diagnostic performance of radiologists was analyzed before and after referring to the results of S-Detect.Results: The accuracy, sensitivity, specificity, positive predictive value and negative predictive value of S-Detect were 77.0, 91.3, 65.2, 68.3 and 90.1%, respectively. In comparison with the less experienced radiologists (radiologist 1 and 2), S-Detect had a higher area under receiver operating characteristic curve (AUC), accuracy and specificity (p <0.05). In comparison with the most experienced radiologist, the diagnostic accuracy and AUC were lower (p<0.05). In the less experienced radiologists, the diagnostic accuracy, specificity and AUC were significantly improved when combined with S-Detect (p<0.05), but not for experienced radiologists (radiologist 3 and 4) (p>0.05).Conclusions: S-Detect may become an additional diagnostic method for the diagnosis of thyroid nodules and improve the diagnostic performance of less experienced radiologists.

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Diagnostic performance of chest computed tomography during the epidemic wave of COVID-19 varied as a function of time since the beginning of the confinement in France

PLoS ONE ◽

10.1371/journal.pone.0242840 ◽

2020 ◽

Vol 15 (11) ◽

pp. e0242840

Author(s):

Samia Boussouar ◽

Mathilde Wagner ◽

Victoria Donciu ◽

Nicoletta Pasi ◽

Joe Elie Salem ◽

...

Keyword(s):

Respiratory Symptoms ◽

Diagnostic Performance ◽

High Sensitivity ◽

Chest Ct ◽

Rt Pcr ◽

First Line ◽

Chest Computed Tomography ◽

Sensitivity Specificity ◽

Epidemic Wave

Objective To evaluate the diagnostic performance of the initial chest CT to diagnose COVID-19 related pneumonia in a French population of patients with respiratory symptoms according to the time from the onset of country-wide confinement to better understand what could be the role of the chest CT in the different phases of the epidemic. Material and method Initial chest CT of 1064 patients with respiratory symptoms suspect of COVID-19 referred between March 18th, and May 12th 2020, were read according to a standardized procedure. The results of chest CTs were compared to the results of the RT-PCR. Results 546 (51%) patients were found to be positive for SARS-CoV2 at RT-PCR. The highest rate of positive RT-PCR was during the second week of confinement reaching 71.9%. After six weeks of confinement, the positive RT-PCR rate dropped significantly to 10.5% (p<0.001) and even 2.2% during the two last weeks. Overall, CT revealed patterns suggestive of COVID-19 in 603 patients (57%), whereas an alternative diagnosis was found in 246 patients (23%). CT was considered normal in 215 patients (20%) and inconclusive in 1 patient. The overall sensitivity of CT was 88%, specificity 76%, PPV 79%, and NPV 85%. At week-2, the same figures were 89%, 69%, 88% and 71% respectively and 60%, 84%, 30% and 95% respectively at week-6. At the end of confinement when the rate of positive PCR became extremely low the sensitivity, specificity, PPV and NPV of CT were 50%, 82%, 6% and 99% respectively. Conclusion At the peak of the epidemic, chest CT had sufficiently high sensitivity and PPV to serve as a first-line positive diagnostic tool but at the end of the epidemic wave CT is more useful to exclude COVID-19 pneumonia.

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Transthoracic lung biopsy for pulmonary nodules ≤20mm in the routine clinical care

ERJ Open Research ◽

10.1183/23120541.00562-2021 ◽

2021 ◽

pp. 00562-2021

Author(s):

Emilie Lissavalid ◽

Antoine Khalil ◽

Ghassen Soussi ◽

Marie-Pierre Debray ◽

Alice Guyard ◽

...

Keyword(s):

Diagnostic Performance ◽

Cancer Survival ◽

Clinical Care ◽

Research Question ◽

Pulmonary Nodules ◽

Lesion Group ◽

Ct Guided ◽

Lung Biopsies ◽

Sensitivity Specificity ◽

Prolonged Hospital

BACKGROUNDComputed tomography (CT) screening has improved lung cancer survival, yet increasingly detected small lung lesions. The number of transthoracic lung biopsies (TTLB) for small nodules is thus expected to rise significantly.RESEARCH QUESTIONTo evaluate the diagnostic accuracy and safety of CT-guided TTLB for nodules ≤20 mm versus nodules >20mm.STUDY DESIGN AND METHODSData for CT-guided TTLBs from 474 consecutive patients were prospectively collected over a 3-year period (198 lesions ≤20 mm and 276 lesions >20 mm) in a teaching hospital and analysed in terms of diagnostic performance and complications.RESULTSThere were more conclusive biopsies in the >20 mm lesion group (n=236; 85.5%) than in ≤20 mm lesion group (n=140; 70.7%; p<0.001). The overall accuracy, sensitivity, specificity, and negative predictive value for diagnosing malignant lesions after first TTLB were 88.4%, 84%, 100%, and 70.1% for ≤20 mm lesions and 94.2%, 93%, 100%, and 74.6% for >20 mm lesions, respectively. Pneumothorax requiring drainage was significantly more common for ≤20 mm lesions, compared to TTLB of larger lesions (9.6% versus 4.3%; p=0.02). Prolonged hospital stay due to pneumothorax occurred in 27 (17.4%) TTLBs of ≤20 mm lesions and 15 (7%) TTLBs of >20mm lesions (p=0.002). There were no deaths. The only variable significantly associated with diagnostic failure in the ≤20mm lesion group was the radiologist's experience.INTERPRETATIONTTLBs for lesions ≤20 mm were associated with slightly lower diagnostic performance, whereas the higher rate of major complications was still inferior to that extrapolated from United States insurance databases.

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Diagnostic accuracy of Computed Tomography for Identifying Hospitalization in Patients with Suspected COVID-19

Digital Diagnostics ◽

10.17816/dd46818 ◽

2021 ◽

Author(s):

S. P. Morozov ◽

Roman V. Reshetnikov ◽

Victor A. Gombolevskiy ◽

N. V. Ledikhova ◽

I. A. Blokhin ◽

...

Keyword(s):

Computed Tomography ◽

Diagnostic Accuracy ◽

Scoring System ◽

Scoring Systems ◽

Chest Ct ◽

Ct Scans ◽

Quantitative Ct ◽

System Sensitivity ◽

Thoracic Computed Tomography ◽

Sensitivity Specificity

Background and Objectives The use of computed tomography (CT) in COVID-19 screening is controversial. The controversy is associated with ambiguous characteristics of chest CT as a diagnostic test. The reported values of CT sensitivity and especially specificity calculated using reverse transcription polymerase chain reaction as a reference standard vary widely, raising reasonable doubts about the applicability of the method. The objective of this study was to reevaluate the diagnostic and prognostic value of CT using an alternative approach. Methods This study included 973 symptomatic COVID-19 patients aged 42 17 years, 56% females. For all of them, we reviewed the disease dynamics between the initial and follow-up CT studies using a "CT0-4" visual semi-quantitative grading system to assess the severity of the disease. Sensitivity and specificity were calculated as conditional probabilities that a patient's condition would improve or deteriorate, depending on the results of the initial CT examination. For the calculation of negative (NPV) and positive (PPV) predictive values, we estimated the COVID-19 prevalence in Moscow. The data on total cases of COVID-19 from March 6, 2020, to August 24, 2020, were taken from the Rospotrebnadzor website. We used several ARIMA and EST models with different parameters to fit the data and forecast the incidence. Results The "CT0-4" grading scale demonstrated low sensitivity (28%), but high specificity (95%). The best statistical model for describing the epidemiological situation in Moscow was ARIMA(0,2,1). According to our calculations, with the predicted point prevalence of 3.9%, the values of NPV and PPV would be 97% and 18%, correspondingly. Discussion We associate the low sensitivity and PPV values of the "CT0-4" grading scale with the small sample size of the patients with severe symptoms and non-optimal methodological setup for measuring these specific characteristics. We found that the grading scale was highly specific and predictive for identifying admissions to hospitals of COVID-19 patients. Only 5% of patients assigned to home treatment were eventually hospitalized. Despite the ambiguous accuracy, chest CT proved to be an effective practical tool for patient management during the pandemic, provided that the necessary infrastructure and human resources are available.

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Chest Computerized Tomography Images under Iterative Model Reconstruction Algorithm in Patients with Lung Cancer

Scientific Programming ◽

10.1155/2021/7897784 ◽

2021 ◽

Vol 2021 ◽

pp. 1-8

Author(s):

Jie Li ◽

Wei Wang ◽

Shizhi Long ◽

Xin Liu ◽

Long Huang ◽

...

Keyword(s):

Lung Cancer ◽

Pulmonary Nodule ◽

Area Under The Curve ◽

Pulmonary Nodules ◽

Reconstruction Algorithm ◽

Chest Ct ◽

Iterative Model ◽

Iterative Model Reconstruction ◽

Sensitivity Specificity ◽

Density Resolution

To explore the effect of the full iterative model reconstruction algorithm (IMR) on chest CT image processing and its adoption value in the clinical diagnosis of lung cancer patients, multislice spiral CT (MSCT) scans were performed on 96 patients with pulmonary nodules. Reconstruction was performed by hybrid iterative reconstruction (iDose4) and IMR2 algorithms. Then, the image contrast, spatial resolution, density resolution, image uniformity, and noise of the CT reconstructed image were recorded. The benign and malignant pulmonary nodules of patients were collected and classified into malignant pulmonary nodule group and benign pulmonary nodule group, and the differences in chest CT imaging characteristics between the two groups were compared. The subject’s receiver operating characteristic (ROC) curve was used to analyze the diagnostic sensitivity, specificity, and area under the curve (AUC) of CT for benign and malignant pulmonary nodules. It was found that the spatial resolution, density resolution, image uniformity, and contrast of the CT image reconstructed by the IMR2 algorithm were remarkably greater than those of the iDose4 algorithm, and the noise was considerably less than that of the iDose4 algorithm ( P < 0.05 ). Among 96 patients with pulmonary nodules, 65 were malignant nodules, including 15 squamous cell carcinoma, 31 adenocarcinoma, and 19 small cell carcinomas. There were 31 cases of benign nodules, including 14 cases of hamartoma, 10 cases of tuberculous granuloma, 2 cases of sclerosing hemangioma, and 5 cases of diffuse lymphocyte proliferation. The pulmonary nodule malignant group and the pulmonary nodule benign group had statistical differences in pulmonary nodule size, nodule morphology, burr sign, lobular sign, vascular sign, bronchial sign, and pleural depression sign ( P < 0.05 ). The sensitivity, specificity, and area under the curve (AUC) of IMR2 algorithm processing chest CT images for liver cancer diagnosis were 85.7%, 82.3%, and 0.815, respectively, which were significantly higher than the original CT images ( P < 0.05 ). In short, chest MSCT based on the IMR2 algorithm can greatly improve the diagnosis efficiency of lung cancer and had practical significance for the timely detection of early lung cancer.

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