Artificial intelligence to predict the need for mechanical ventilation in cases of severe COVID-19

Objective

To determinate the accuracy of computed tomography (CT) imaging assessed by deep neural networks for predicting the need for mechanical ventilation (MV) in patients hospitalized with severe acute respiratory syndrome due to coronavirus disease 2019 (COVID-19).

Materials and Methods

This was a retrospective cohort study carried out at two hospitals in Brazil. We included CT scans from patients who were hospitalized due to severe acute respiratory syndrome and had COVID-19 confirmed by reverse transcription-polymerase chain reaction (RT-PCR). The training set consisted of chest CT examinations from 823 patients with COVID-19, of whom 93 required MV during hospitalization. We developed an artificial intelligence (AI) model based on convolutional neural networks. The performance of the AI model was evaluated by calculating its accuracy, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve.

Results

For predicting the need for MV, the AI model had a sensitivity of 0.417 and a specificity of 0.860. The corresponding area under the ROC curve for the test set was 0.68.

Conclusion

The high specificity of our AI model makes it able to reliably predict which patients will and will not need invasive ventilation. That makes this approach ideal for identifying high-risk patients and predicting the minimum number of ventilators and critical care beds that will be required.

Artificial Intelligence for Cardiothoracic Imaging: Overview of Current and Emerging Applications

Artificial intelligence algorithms can learn by assimilating information from large datasets in order to decipher complex associations, identify previously undiscovered pathophysiological states, and construct prediction models. There has been tremendous interest and increased incorporation of artificial intelligence into various industries, including healthcare. As a result, there has been an exponential rise in the number of research articles and industry participants producing models intended for a variety of applications in medical imaging, which can be challenging to navigate for radiologists. In thoracic imaging, multiple applications are being evaluated for chest radiography and computed tomography and include applications for lung nodule evaluation and cancer imaging, quantifying diffuse lung disorders, and cardiac imaging, to name a few. This review aims to provide an overview of current clinical AI models, focusing on the most common clinical applications of AI in cardiothoracic imaging.

Fluoroscopia por tomografia computadorizada - biópsia percutânea guiada de nódulos pulmonares ≤ 10 mm: análise retrospectiva de procedimentos realizados no período de pandemia de COVID-19

Resumo Objetivo: Avaliar o desempenho diagnóstico da biópsia pulmonar percutânea transtorácica (BPPT) guiada por fluoroscopia associada a tomografia computadorizada (FTC) em nódulos pulmonares ≤ 10 mm no período de pandemia de COVID-19. Materiais e Métodos: No período de 1º de janeiro de 2020 a 30 de abril de 2022, 359 BPPTs guiadas por FTC foram realizadas em um centro terciário de radiologia intervencionista. As lesões pulmonares mediam entre 2 mm e 108 mm. Dessas 359 BPPTs, 27 (7,5%) foram realizadas com agulha 18G em nódulos de 2 mm a 10 mm. Resultados: Das 27 BPPTs realizadas nos nódulos ≤ 10 mm, quatro lesões tinham dimensões menores que 5 mm e 23 lesões mediam entre 5 e 10 mm. Sensibilidade e acurácia diagnóstica das BPPTs guiadas por FTC foram de 100% e 92,3%, respectivamente. A dose média de radiação ionizante para os pacientes durante o procedimento de BPPT guiada por FTC foi de 581,33 mGy*cm, variando de 303 a 1129 mGy*cm. A média de tempo dos procedimentos de biópsia foi de 6,6 minutos, variando de 2 a 12 minutos. Nas 27 BPPTs, nenhuma complicação maior foi descrita. Conclusão: A BBPT guiada por FTC resultou em alto rendimento diagnóstico e baixas taxas de complicações.

The clinical-radiological paradox in multiple sclerosis: myth or truth?

BACKGROUND

Multiple sclerosis (MS) is an inflammatory, degenerative, demyelinating disease that ranges from benign to rapidly progressive forms. A striking characteristic of the disease is the clinical-radiological paradox.

OBJECTIVES

The present study was conducted to determine whether, in our cohort, the clinical-radiological paradox exists and whether lesion location is related to clinical disability in patients with MS.

METHODS

Retrospective data from 95 patients with MS (60 women and 35 men) treated at a single center were examined. One head-and-spine magnetic resonance imaging (MRI) examination from each patient was selected randomly, and two independent observers calculated lesion loads (LLs) on T2/fluid attenuation inversion recovery sequences manually, considering the whole brain and four separate regions (periventricular, juxtacortical, posterior fossa, and spinal cord). The LLs were compared with the degree of disability, measured by the Kurtzke Expanded Disability Status Scale (EDSS), at the time of MRI examination in the whole cohort and in patients with relapsing-remitting (RR), primarily progressive, and secondarily progressive MS.

RESULTS

High LLs correlated with high EDSS scores in the whole cohort (r = 0.34; p < 0.01) and in the RRMS group (r = 0.27; p = 0.02). The EDSS score correlated with high regional LLs in the posterior fossa (r = 0.31; p = 0.002) and spinal cord (r = 0.35; p = 0.001).

CONCLUSIONS

Our results indicate that the clinical-radiological paradox is a myth and support the logical connection between lesion location and neurological repercussion.

Computed tomography fluoroscopy-guided percutaneous biopsy of pulmonary nodules ≤ 10 mm: retrospective analysis of procedures performed during the COVID-19 pandemic

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.

Narrowing the Differential Diagnosis of Cystic Lesions in Smokers with Expiratory CT Acquisition Using the Cyst-Airway Communication Hypothesis

The aim of this study was to assess percentage respiratory changes (δ) in the size of pulmonary cysts of different smoking-related etiologies. Retrospectively, we measured the cystic lesions due to histopathological-confirmed honeycombing from interstitial pulmonary fibrosis, pulmonary Langerhans cell histiocytosis (PLCH), and paraseptal emphysema, using paired inspiratory and expiratory CT scans. In a sample of 72 patients and 216 lesions, the mean diameter of PLCH and honeycombing decreased during expiration (PLCH, δ = 60.9%; p = 0.001; honeycombing, δ = 47.5%; p = 0.014). Conversely, paraseptal emphysema did not show any changes (δ = 5.2%; p = 0.34). In summary, our results demonstrated that cysts in smokers with PLCH and honeycombing fibrosis get smaller during expiratory CT scans, whereas the size of cystic-like lesions due to paraseptal emphysema and bullae tend to remain constant during respiratory cycles. These results support the hypothesis of cyst-airway communication in some cystic diseases, which could assist in the differential diagnosis in smoking-related lung diseases.

The diagnostic value of magnetic resonance imaging compared to computed tomography in the evaluation of fat-containing thoracic lesions

Intrathoracic fat-containing lesions may arise in the mediastinum, lungs, pleura, or chest wall. While CT can be helpful in the detection and diagnosis of these lesions, it can only do so if the lesions contain macroscopic fat. Furthermore, because CT cannot demonstrate microscopic or intravoxel fat, it can fail to identify and diagnose microscopic fat-containing lesions. MRI, employing spectral and chemical shift fat suppression techniques, can identify both macroscopic and microscopic fat, with resultant enhanced capability to diagnose these intrathoracic lesions non-invasively and without ionizing radiation. This paper aims to review the CT and MRI findings of fat-containing lesions of the chest and describes the fat-suppression techniques utilized in their assessment.

Chest Imaging in Systemic Endemic Mycoses

Endemic fungal infections are responsible for high rates of morbidity and mortality in certain regions of the world. The diagnosis and management remain a challenge, and the reason could be explained by the lack of disease awareness, variability of symptoms, and insidious and often overlooked clinical presentation. Imaging findings are nonspecific and frequently misinterpreted as other more common infectious or malignant diseases. Patient demographics and clinical and travel history are important clues that may lead to a proper diagnosis. The purpose of this paper is to review the presentation and differential diagnosis of endemic mycoses based on the most common chest imaging findings.

Variability of pulmonary nodule volumetry on coronary CT angiograms

This study aims to investigate the variability of pulmonary nodule (PN) volumetry on multiphase coronary CT angiograms (CCTA). Two radiologists reviewed 5973 CCTA scans in this cross-sectional study to detect incidental solid noncalcified PNs measuring between 5 and 8 mm. Each radiologist measured the nodules' diameters and volume, in systole and diastole, using 2 commercially available software packages to analyze PNs. Bland-Altman analysis was applied between different observers, software packages, and cardiac phases. Bland-Altman subanalysis for the systolic and diastolic datasets were also performed. A total of 195 PNs were detected within the inclusion criteria and measured in systole and diastole. Bland-Altman analysis was used to test the variability of volumetry between cardiac phases ([-47.0%; 52.3%]), software packages ([-50.2%; 68.2%]), and observers ([-14.5%; 27.8%]). The inter-observer variability of the systolic and diastolic subsets was [-13.6%; 31.4%] and [-13.9%; 19.7%], respectively. Using diastolic volume measurements, the variability of PN volumetry on CCTA scans is similar to the reported variability of volumetry on low-dose CT scans. Therefore, growth estimation of PNs on CCTA scans could be feasible.

Incidental chest findings on coronary CT angiography: a pictorial essay and management proposal

Many health systems have been using coronary CT angiography (CCTA) as a first-line examination for ischaemic heart disease patients in various countries. The rising number of CCTA examinations has led to a significant increase in the number of reported incidental extracardiac findings, mainly in the chest. Pulmonary nodules are the most common incidental findings on CCTA scans, as there is a substantial overlap of risk factors between the population seeking to exclude ischaemic heart disease and those at risk of developing lung cancer (i.e., advanced age and smoking habits). However, most incidental findings are clinically insignificant and actively pursuing them could be cost-prohibitive and submit the patient to unnecessary and potentially harmful examinations. Furthermore, there is little consensus regarding when to report or actively exclude these findings and how to manage them, that is, when to trigger an alert or to immediately refer the patient to a pulmonologist, a thoracic surgeon or a multidisciplinary team. This pictorial essay discusses the current literature on this topic and is illustrated with a review of CCTA scans. We also propose a checklist organised by organ and system, recommending actions to raise awareness of pulmonologists, thoracic surgeons, cardiologists and radiologists regarding the most significant and actionable incidental findings on CCTA scans.

Human Oncoviruses and Thoracic Tumors: Understanding the Imaging Findings

Approximately 1.4 million virus-induced cancers occur annually, representing roughly 10% of the cancer burden worldwide. Seven oncogenic DNA and RNA viruses (ie, oncoviruses) are implicated in approximately 12%-25% of all human cancers owing to a variety of mechanisms as uncommon consequences of the normal viral life cycle. These seven well-recognized human oncoviruses are Epstein-Barr virus (EBV), human T-lymphotropic virus 1, hepatitis B virus, hepatitis C virus, HIV, human papilloma virus (HPV), and human herpesvirus 8 (HHV-8). Several viruses-namely, EBV, HPV, and Kaposi sarcoma herpesvirus or HHV-8-are increasingly being recognized as being related to HIV and/or AIDS, the growing number of transplant cases, and the use of immunosuppressive therapies. Infectious and inflammatory processes, and the accompanying lymphadenopathy, are great mimickers of human oncovirus-related tumors. Although it is often difficult to differentiate these entities, the associated clinical setting and radiologic findings may provide clues for an accurate diagnosis and appropriate management. Malignant lymphoid lesions are best evaluated with multidetector chest CT. The radiologic findings of these lesions are often nonspecific and are best interpreted in correlation with clinical data and histopathologic findings. ^©RSNA, 2022.