Diagnostic accuracy of ultra-low-dose chest computed tomography in an emergency department

Can clinicians identify community-acquired pneumonia on ultralow-dose CT? A diagnostic accuracy study

BACKGROUND

Without increasing radiation exposure, ultralow-dose computed tomography (CT) of the chest provides improved diagnostic accuracy of radiological pneumonia diagnosis compared to a chest radiograph. Yet, radiologist resources to rapidly report the chest CTs are limited. This study aimed to assess the diagnostic accuracy of emergency clinicians' assessments of chest ultralow-dose CTs for community-acquired pneumonia using a radiologist's assessments as reference standard.

METHODS

This was a cross-sectional diagnostic accuracy study. Ten emergency department clinicians (five junior clinicians, five consultants) assessed chest ultralow-dose CTs from acutely hospitalised patients suspected of having community-acquired pneumonia. Before assessments, the clinicians attended a focused training course on assessing ultralow-dose CTs for pneumonia. The reference standard was the assessment by an experienced emergency department radiologist. Primary outcome was the presence or absence of pulmonary opacities consistent with community-acquired pneumonia. Sensitivity, specificity, and predictive values were calculated using generalised estimating equations.

RESULTS

All clinicians assessed 128 ultralow-dose CTs. The prevalence of findings consistent with community-acquired pneumonia was 56%. Seventy-eight percent of the clinicians' CT assessments matched the reference assessment. Diagnostic accuracy estimates were: sensitivity = 83% (95%CI: 77-88), specificity = 70% (95%CI: 59-81), positive predictive value = 80% (95%CI: 74-84), negative predictive value = 78% (95%CI: 73-82).

CONCLUSION

This study found that clinicians could assess chest ultralow-dose CTs for community-acquired pneumonia with high diagnostic accuracy. A higher level of clinical experience was not associated with better diagnostic accuracy.

XRAInet: AI-based decision support for pneumothorax and pleural effusion management

PURPOSE

This study aimed to develop and assess the performance of an artificial intelligence (AI)-driven decision support system, XRAInet, in accurately identifying pediatric patients with pleural effusion or pneumothorax and determining whether tube thoracostomy intervention is warranted.

METHODS

In this diagnostic accuracy study, we retrospectively analyzed a data set containing 510 X-ray images from 170 pediatric patients admitted between 2005 and 2022. Patients were categorized into two groups: Tube (requiring tube thoracostomy) and Conservative (managed conservatively). XRAInet, a deep learning-based algorithm, was trained using this data set. We evaluated its performance using various metrics, including mean Average Precision (mAP), recall, precision, and F1 score.

RESULTS

XRAInet, achieved a mAP score of 0.918. This result underscores its ability to accurately identify and localize regions necessitating tube thoracostomy for pediatric patients with pneumothorax and pleural effusion. In an independent testing data set, the model exhibited a sensitivity of 64.00% and specificity of 96.15%.

CONCLUSION

In conclusion, XRAInet presents a promising solution for improving the detection and decision-making process for cases of pneumothorax and pleural effusion in pediatric patients using X-ray images. These findings contribute to the expanding field of AI-driven medical imaging, with potential applications for enhancing patient outcomes. Future research endeavors should explore hybrid models, enhance interpretability, address data quality issues, and align with regulatory requirements to ensure the safe and effective deployment of XRAInet in healthcare settings.

Imaging in pulmonary infections of immunocompetent adult patients

Pneumonia is a clinical syndrome characterised by fever, cough and alveolar infiltration of purulent fluid, caused by infection with a microbial pathogen. It can be caused by infections with bacteria, viruses or fungi, but a causative organism is identified in less than half of cases. The most common type of pneumonia is community-acquired pneumonia, which is caused by infections acquired outside the hospital. Current guidelines for pneumonia diagnosis require imaging to confirm the clinical suspicion of pneumonia. Thus, imaging plays an important role in both the diagnosis and management of pneumonia, with each modality having specific advantages and limitations. Chest radiographs are commonly used but have limitations in terms of sensitivity and specificity. Lung ultrasound shows high sensitivity and specificity. Computed tomography scans offer higher diagnostic accuracy but involve higher radiation doses. Radiological patterns, including lobar, lobular and interstitial pneumonia, provide valuable insights into causative pathogens and treatment decisions. Understanding these radiological patterns is crucial for accurate diagnosis. In this review, we will summarise the most important aspects pertaining to the role of imaging in pneumonia and will highlight the imaging characteristics of the most common causative organisms.

The yield of chest X-ray or ultra-low-dose chest-CT in emergency department patients suspected of pulmonary infection without respiratory symptoms or signs

OBJECTIVE

The yield of pulmonary imaging in patients with suspected infection but no respiratory symptoms or signs is probably limited, ultra-low-dose CT (ULDCT) is known to have a higher sensitivity than Chest X-ray (CXR). Our objective was to describe the yield of ULDCT and CXR in patients clinically suspected of infection, but without respiratory symptoms or signs, and to compare the diagnostic accuracy of ULDCT and CXR.

METHODS

In the OPTIMACT trial, patients suspected of non-traumatic pulmonary disease at the emergency department (ED) were randomly allocated to undergo CXR (1210 patients) or ULDCT (1208 patients). We identified 227 patients in the study group with fever, hypothermia, and/or elevated C-reactive protein (CRP) but no respiratory symptoms or signs, and estimated ULDCT and CXR sensitivity and specificity in detecting pneumonia. The final day-28 diagnosis served as the clinical reference standard.

RESULTS

In the ULDCT group, 14/116 (12%) received a final diagnosis of pneumonia, versus 8/111 (7%) in the CXR group. ULDCT sensitivity was significantly higher than that of CXR: 13/14 (93%) versus 4/8 (50%), a difference of 43% (95% CI: 6 to 80%). ULDCT specificity was 91/102 (89%) versus 97/103 (94%) for CXR, a difference of - 5% (95% CI: - 12 to 3%). PPV was 54% (13/24) for ULDCT versus 40% (4/10) for CXR, NPV 99% (91/92) versus 96% (97/101).

CONCLUSION

Pneumonia can be present in ED patients without respiratory symptoms or signs who have a fever, hypothermia, and/or elevated CRP. ULDCT's sensitivity is a significant advantage over CXR when pneumonia has to be excluded.

CLINICAL RELEVANCE STATEMENT

Pulmonary imaging in patients with suspected infection but no respiratory symptoms or signs can result in the detection of clinically significant pneumonia. The increased sensitivity of ultra-low-dose chest CT compared to CXR is of added value in vulnerable and immunocompromised patients.

KEY POINTS

• Clinical significant pneumonia does occur in patients who have a fever, low core body temperature, or elevated CRP without respiratory symptoms or signs. • Pulmonary imaging should be considered in patients with unexplained symptoms or signs of infections. • To exclude pneumonia in this patient group, ULDCT's improved sensitivity is a significant advantage over CXR.

Empirical antibiotic treatment for community-acquired pneumonia and accuracy for Legionella pneumophila, Mycoplasma pneumoniae, and Clamydophila pneumoniae: a descriptive cross-sectional study of adult patients in the emergency department

BACKGROUND

Many factors determine empirical antibiotic treatment of community-acquired pneumonia (CAP). We aimed to describe the empirical antibiotic treatment CAP patients with an acute hospital visit and to determine if the current treatment algorithm provided specific and sufficient coverage against Legionella pneumophila, Mycoplasma pneumoniae, and Clamydophila pneumoniae (LMC).

METHODS

A descriptive cross-sectional, multicenter study of all adults with an acute hospital visit in the Region of Southern Denmark between January 2016 and March 2018 was performed. Using medical records, we retrospectively identified the empirical antibiotic treatment and the microbiological etiology for CAP patients. CAP patients who were prescribed antibiotics within 24 h of admission and with an identified bacterial pathogen were included. The prescribed empirical antibiotic treatment and its ability to provide specific and sufficient coverage against LMC pneumonia were determined.

RESULTS

Of the 19,133 patients diagnosed with CAP, 1590 (8.3%) patients were included in this study. Piperacillin-tazobactam and Beta-lactamase sensitive penicillins were the most commonly prescribed empirical treatments, 515 (32%) and 388 (24%), respectively. Our analysis showed that 42 (37%, 95% CI: 28-47%) of 113 patients with LMC pneumonia were prescribed antibiotics with LMC coverage, and 42 (12%, 95% CI: 8-15%) of 364 patients prescribed antibiotics with LMC coverage had LMC pneumonia.

CONCLUSION

Piperacillin-tazobactam, a broad-spectrum antibiotic recommended for uncertain infectious focus, was the most frequent CAP treatment and prescribed to every third patient. In addition, the current empirical antibiotic treatment accuracy was low for LMC pneumonia. Therefore, future research should focus on faster diagnostic tools for identifying the infection focus and precise microbiological testing.

Evaluating cardiac function with chest computed tomography in acute ischemic stroke: feasibility and correlation with short-term outcome

Background

The outcomes of patients with acute ischemic stroke (AIS) are related to cardiac function. Cardiac insufficiency can manifest as hydrostatic changes in the lungs. Computed tomography (CT) of the chest is commonly used for screening pulmonary abnormalities and provides an opportunity to assess cardiac function.

Purpose

To evaluate the correlation between hydrostatic lung manifestations on chest CT and cardiac function with its potential to predict the short-term outcome of AIS patients.

Methods

We retrospectively analyzed AIS patients who had undergone chest CT at admission and echocardiogram within 48 h. Morphological and quantitative hydrostatic changes and left ventricular dimensions were assessed using chest CT. Improvement in the National Institutes of Health Stroke Scale (NIHSS) score on the seventh day determined short-term outcomes. Multivariate analysis examined the correspondence between hydrostatic lung manifestations, left ventricular dimension, and left ventricle ejection fraction (LVEF) on echocardiography, and the correlation between hydrostatic changes and short-term outcomes.

Results

We included 204 patients from January to December 2021. With the progression of hydrostatic changes on chest CT, the LVEF on echocardiography gradually decreased (p < 0.05). Of the 204, 53 patients (26%) with varying degrees of hypostatic lung manifestations had less improvement in the NIHSS score (p < 0.05). The density ratio of the anterior/posterior lung on CT showed a significant negative correlation with improvement in the NIHSS score (r = -5.518, p < 0.05). Additionally, patients with a baseline NIHSS ≥4 with left ventricular enlargement had significantly lower LVEF than that of patients with normal NIHSS scores.

Conclusion

Hydrostatic lung changes on chest CT can be used as an indicator of cardiac function and as a preliminary reference for short-term outcome in AIS patients.

Ultra-low dose computed tomography of the chest in an emergency setting: A prospective agreement study

Ultra-low dose computed tomography (ULD-CT) assessed by non-radiologists in a medical Emergency Department (ED) has not been examined in previous studies. To (i) investigate intragroup agreement among attending physicians caring for ED patients (i.e., radiologists, senior- and junior clinicians) and medical students for the detection of acute lung conditions on ULD-CT and supine chest X-ray (sCXR), and (ii) evaluate the accuracy of interpretation compared to the reference standard. In this prospective study, non-traumatic patients presenting to the ED, who received an sCXR were included. Between February and July 2019, 91 patients who underwent 93 consecutive examinations were enrolled. Subsequently, a ULD-CT and non-contrast CT were performed. The ULD-CT and sCXR were assessed by 3 radiologists, 3 senior clinicians, 3 junior clinicians, and 3 medical students for pneumonia, pneumothorax, pleural effusion, and pulmonary edema. The non-contrast CT, assessed by a chest radiologist, was used as the reference standard. The results of the assessments were compared within each group (intragroup agreement) and with the reference standard (accuracy) using kappa statistics. Accuracy and intragroup agreement improved for pneumothorax on ULD-CT compared with the sCXR for all groups. Accuracy and intragroup agreement improved for pneumonia on ULD-CT when assessed by radiologists and for pleural effusion when assessed by medical students. In patients with acute lung conditions ULD-CT offers improvement in the detection of pneumonia by radiologists and the detection of pneumothorax by radiologists as well as non-radiologists compared to sCXR. Therefore, ULD-CT may be considered as an alternative first-line imaging modality to sCXR for non-traumatic patients who present to EDs.