Biomaterial Database

Detection of COVID-19 in Point of Care Lung Ultrasound. 2022

Joana Maximino, and Miguel Coimbra, and Joao Pedrosa

The coronavirus disease 2019 (COVID-19) evolved into a global pandemic, responsible for a significant number of infections and deaths. In this scenario, point-of-care ultrasound (POCUS) has emerged as a viable and safe imaging modality. Computer vision (CV) solutions have been proposed to aid clinicians in POCUS image interpretation, namely detection/segmentation of structures and image/patient classification but relevant challenges still remain. As such, the aim of this study is to develop CV algorithms, using Deep Learning techniques, to create tools that can aid doctors in the diagnosis of viral and bacterial pneumonia (VP and BP) through POCUS exams. To do so, convolutional neural networks were designed to perform in classification tasks. The architectures chosen to build these models were the VGG16, ResNet50, DenseNet169 e MobileNetV2. Patients images were divided in three classes: healthy (HE), BP and VP (which includes COVID-19). Through a comparative study, which was based on several performance metrics, the model based on the DenseNet169 architecture was designated as the best performing model, achieving 78% average accuracy value of the five iterations of 5- Fold Cross-Validation. Given that the currently available POCUS datasets for COVID-19 are still limited, the training of the models was negatively affected by such and the models were not tested in an independent dataset. Furthermore, it was also not possible to perform lesion detection tasks. Nonetheless, in order to provide explainability and understanding of the models, Gradient-weighted Class Activation Mapping (GradCAM) were used as a tool to highlight the most relevant classification regions. Clinical relevance - Reveals the potential of POCUS to support COVID-19 screening. The results are very promising although the dataset is limite.

UI	MeSH Term	Description	Entries
D008168	Lung	Either of the pair of organs occupying the cavity of the thorax that effect the aeration of the blood.	Lungs
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000086382	COVID-19	A viral disorder generally characterized by high FEVER; COUGH; DYSPNEA; CHILLS; PERSISTENT TREMOR; MUSCLE PAIN; HEADACHE; SORE THROAT; a new loss of taste and/or smell (see AGEUSIA and ANOSMIA) and other symptoms of a VIRAL PNEUMONIA. In severe cases, a myriad of coagulopathy associated symptoms often correlating with COVID-19 severity is seen (e.g., BLOOD COAGULATION; THROMBOSIS; ACUTE RESPIRATORY DISTRESS SYNDROME; SEIZURES; HEART ATTACK; STROKE; multiple CEREBRAL INFARCTIONS; KIDNEY FAILURE; catastrophic ANTIPHOSPHOLIPID ANTIBODY SYNDROME and/or DISSEMINATED INTRAVASCULAR COAGULATION). In younger patients, rare inflammatory syndromes are sometimes associated with COVID-19 (e.g., atypical KAWASAKI SYNDROME; TOXIC SHOCK SYNDROME; pediatric multisystem inflammatory disease; and CYTOKINE STORM SYNDROME). A coronavirus, SARS-CoV-2, in the genus BETACORONAVIRUS is the causative agent.	2019 Novel Coronavirus Disease,2019 Novel Coronavirus Infection,2019-nCoV Disease,2019-nCoV Infection,COVID-19 Pandemic,COVID-19 Pandemics,COVID-19 Virus Disease,COVID-19 Virus Infection,Coronavirus Disease 2019,Coronavirus Disease-19,SARS Coronavirus 2 Infection,SARS-CoV-2 Infection,Severe Acute Respiratory Syndrome Coronavirus 2 Infection,COVID19,2019 nCoV Disease,2019 nCoV Infection,2019-nCoV Diseases,2019-nCoV Infections,COVID 19,COVID 19 Pandemic,COVID 19 Virus Disease,COVID 19 Virus Infection,COVID-19 Virus Diseases,COVID-19 Virus Infections,Coronavirus Disease 19,Disease 2019, Coronavirus,Disease, 2019-nCoV,Disease, COVID-19 Virus,Infection, 2019-nCoV,Infection, COVID-19 Virus,Infection, SARS-CoV-2,Pandemic, COVID-19,SARS CoV 2 Infection,SARS-CoV-2 Infections,Virus Disease, COVID-19,Virus Infection, COVID-19
D014463	Ultrasonography	The visualization of deep structures of the body by recording the reflections or echoes of ultrasonic pulses directed into the tissues. Use of ultrasound for imaging or diagnostic purposes employs frequencies ranging from 1.6 to 10 megahertz.	Echography,Echotomography,Echotomography, Computer,Sonography, Medical,Tomography, Ultrasonic,Ultrasonic Diagnosis,Ultrasonic Imaging,Ultrasonographic Imaging,Computer Echotomography,Diagnosis, Ultrasonic,Diagnostic Ultrasound,Ultrasonic Tomography,Ultrasound Imaging,Diagnoses, Ultrasonic,Diagnostic Ultrasounds,Imaging, Ultrasonic,Imaging, Ultrasonographic,Imaging, Ultrasound,Imagings, Ultrasonographic,Imagings, Ultrasound,Medical Sonography,Ultrasonic Diagnoses,Ultrasonographic Imagings,Ultrasound, Diagnostic,Ultrasounds, Diagnostic
D016571	Neural Networks, Computer	A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming.	Computational Neural Networks,Connectionist Models,Models, Neural Network,Neural Network Models,Neural Networks (Computer),Perceptrons,Computational Neural Network,Computer Neural Network,Computer Neural Networks,Connectionist Model,Model, Connectionist,Model, Neural Network,Models, Connectionist,Network Model, Neural,Network Models, Neural,Network, Computational Neural,Network, Computer Neural,Network, Neural (Computer),Networks, Computational Neural,Networks, Computer Neural,Networks, Neural (Computer),Neural Network (Computer),Neural Network Model,Neural Network, Computational,Neural Network, Computer,Neural Networks, Computational,Perceptron
D019095	Point-of-Care Systems	Laboratory and other services provided to patients at the bedside. These include diagnostic and laboratory testing using automated information entry.	Bedside Computing,Point of Care Technology,Bedside Technology,Point-of-Care,Bedside Technologies,Computing, Bedside,Point of Care,Point of Care Systems,Point-of-Care System,Systems, Point-of-Care,Technologies, Bedside,Technology, Bedside