• Diagnostic Imaging
• Prognosis
• Respiratory infections
• Tuberculosis
• Ultrasound

• Humans
• Male
• Prospective Studies
• Female
• Middle Aged
• Ultrasonography
• Pneumonia/diagnostic imaging
• Pneumonia/mortality
• Tuberculosis, Pulmonary/epidemiology
• Tuberculosis, Pulmonary/diagnostic imaging
• Aged
• Lung/diagnostic imaging
• Vietnam/epidemiology
• Community-Acquired Infections/diagnostic imaging
• Sensitivity and Specificity
• Tomography, X-Ray Computed
• Hospital Mortality
• Adult
• Endemic Diseases
• Prognosis

• Antibiotic
• Antibiotique
• Biologie
• Biology
• Corticoid
• Corticoïde
• Imagerie
• Imaging
• Pneumonia
• Pneumonie

• Antibiotic
• Biology
• Corticosteroids
• Imagery
• Pneumonia

• Antibiotic
• Biology
• Corticosteroids
• Imagery
• Pneumonia

• acute chest trauma
• hrct thorax
• lung ultrasonography (lus)
• pneumothorax
• real-time imaging

• bedside lung ultrasound
• pneumonia
• point-of-care investigation
• sensitivity

• Humans
• Anti-Bacterial Agents/therapeutic use
• Community-Acquired Infections/diagnosis
• Community-Acquired Infections/drug therapy
• Community-Acquired Infections/epidemiology
• Community-Acquired Infections/microbiology
• Hospitalization/statistics & numerical data
• Pneumonia/diagnosis
• Pneumonia/drug therapy
• Pneumonia/epidemiology
• Pneumonia/microbiology
• Risk Factors
• Antiviral Agents/therapeutic use
• Severity of Illness Index
• SARS-CoV-2/isolation & purification
• Alphainfluenzavirus/isolation & purification
• Lung/diagnostic imaging
• Glucocorticoids/therapeutic use

• K08 HS026530 AHRQ HHS
• R01 HL144599 NHLBI NIH HHS
• K24 HL159247 NHLBI NIH HHS
• U01 HL168308 NHLBI NIH HHS

• diagnostic accuracy
• emergency department
• handheld ultrasound
• lung ultrasound
• novice
• pneumonia

• N/A University of Southern Denmark
• N/A Region of Southern Denmark
• N/A A.P. Møller og Hustru Chastine Mc-Kinney Møllers Fond

• bronchiolitis
• chest x rays
• lung ultrasound
• pneumonia
• walri

• Chest
• Children
• Lungs
• Pneumonia
• Radiography
• Ultrasound

• Male
• Child
• Humans
• Child, Preschool
• Infant
• Female
• Cohort Studies
• South Africa
• Radiography, Thoracic/methods
• Prospective Studies
• Lung/diagnostic imaging
• Pneumonia/diagnostic imaging
• Radiography
• Lung Diseases
• Ultrasonography/methods

• 1U01AI110466–01A1 NIAID NIH HHS

• chest X-ray
• computed tomography
• infection
• lung ultrasound
• tuberculosis

• ICU
• accuracy
• emergency
• knowledge
• pneumonia
• senstivity
• specificity
• training
• wards
• “lung ultrasound versus chest x-ray

• Algorithm
• Antibiotic prescription
• Clinical trial
• Community-acquired pneumonia
• Diagnostic tool
• Emergency department
• Lower respiratory tract infection
• Lung ultrasound
• Procalcitonin
• Protocol

• Adult
• Humans
• Procalcitonin
• Quality of Life
• Switzerland
• Respiratory Tract Infections/diagnostic imaging
• Respiratory Tract Infections/drug therapy
• Pneumonia/diagnostic imaging
• Pneumonia/drug therapy
• Lung/diagnostic imaging
• Anti-Bacterial Agents/adverse effects
• Ultrasonography
• Emergency Service, Hospital
• Randomized Controlled Trials as Topic

• 33IC30_201300 / 1 Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
• University of Lausanne

• chest radiography
• chest ultrasound
• critical care
• point-of-care lung ultrasound
• thoracic ultrasound

• diagnosis stewardship
• epidemiology
• etiology
• healthcare-associated pneumonia
• hospital at home
• management
• nosocomial pneumonia
• prevention
• radiologic findings
• readmission
• rescue
• therapeutic failure
• vaccination

• Humans
• Lung Diseases/diagnostic imaging
• Ultrasonography/methods
• Lung/diagnostic imaging
• Connective Tissue
• Thorax

• R21 EB033150 NIBIB NIH HHS

• Humans
• COVID-19 Testing
• Robotics/methods
• Triage
• COVID-19/diagnostic imaging
• Ultrasonography/methods
• Lung/diagnostic imaging

• acute chest syndrome
• diagnosis
• point-of-care testing
• radiograph
• sickle cell anemia
• sickle cell disease
• ultrasound

• Adult
• Humans
• Child
• Acute Chest Syndrome/diagnostic imaging
• Acute Chest Syndrome/etiology
• Sensitivity and Specificity
• Lung/diagnostic imaging
• Anemia, Sickle Cell/complications
• Anemia, Sickle Cell/diagnostic imaging
• Diagnostic Tests, Routine

• UL1 TR001857 NCATS NIH HHS

• Chest X-Ray
• Emergency Department (ED)
• Hypoxia
• Uganda
• Ultrasound

Congestive nephropathy is kidney dysfunction caused by the impact of elevated venous pressures on renal hemodynamics. As a part of cardiorenal syndrome, the diagnosis is usually made based on history and physical examination, with findings such as jugular venous distension, a third heart sound, and vital signs as supporting findings. More recently, however, these once though objective measures have come under scrutiny for their accuracy. At the same time, bedside ultrasound has increased in popularity and is routinely being used by clinicians to take some of the guess work out of making the diagnosis of volume overload and venous congestion. In this mini-review, we will discuss some of the traditional methods used to measure venous congestion, describe the role of point-of-care ultrasound and how it can ameliorate a clinician’s evaluation, and offer a description of venous excess ultrasound score, a relatively novel scoring technique used to objectively quantify congestion. While there is a paucity of published large scale clinical trials evaluating the potential benefit of ultrasonography in venous congestion compared to gold standard invasive measurements, more study is underway to solidify the role of this objective measure in daily clinical practice.

• Ultrasound
• Point-of-care ultrasonography
• Doppler
• Venous excess ultrasound score
• Congestion
• Hemodynamics
• Heart failure
• Nephrology

• anaesthesia
• decision-making
• diagnostic imaging
• lung disease
• lung ultrasound
• pneumonia

• Malawi
• POCUS
• international health
• point-of-care
• ultrasound
• ultrasound global health

• Chest radiograph
• Computed tomography
• Lung ultrasound
• Tuberculosis

• Humans
• Lung/diagnostic imaging
• Prospective Studies
• Tomography, X-Ray Computed
• Tuberculosis, Pulmonary/diagnostic imaging
• Ultrasonography/methods
• X-Rays

• accuracy
• chest x-ray
• emergency department
• low-dose ct
• ultra-low dose ct

• Humans
• Pleural Effusion/diagnostic imaging
• Pneumonia
• Pneumothorax/diagnostic imaging
• Prospective Studies
• Radiation Dosage
• Tomography, X-Ray Computed/methods

• Coronavirus, consolidation, microthrombi, computed tomography, bedside ultrasound, critical care, microbubble

• BLUE protocol
• Lung ultrasound
• Lung ultrasound score
• Pneumonia

Coronavirus disease 2019 (COVID-19) is caused by the novel viral pathogen, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 primarily involves the lungs. Nucleic acid testing based on reverse-transcription polymerase chain reaction of respiratory samples is the current gold standard for the diagnosis of SARS-CoV-2 infection. Imaging modalities have an established role in triaging, diagnosis, evaluation of disease severity, monitoring disease progression, extra-pulmonary involvement, and complications. As our understanding of the disease improves, there has been substantial evidence to highlight its potential for multi-systemic involvement and development of long-term sequelae. Molecular imaging techniques are highly sensitive, allowing non-invasive visualization of physiological or pathological processes at a cellular or molecular level with potential for detection of functional changes earlier than conventional radiological imaging. The purpose of this review article is to highlight the evolving role of molecular imaging in evaluation of COVID-19 sequelae. Though not ideal for diagnosis, the various modalities of molecular imaging play an important role in assessing pulmonary and extra-pulmonary sequelae of COVID-19. Perfusion imaging using single photon emission computed tomography fused with computed tomography (CT) can be utilized as a first-line imaging modality for COVID-19 related pulmonary embolism. ¹⁸F-fluorodeoxyglucose positron emission tomography (PET)/CT is a sensitive tool to detect multi-systemic inflammation, including myocardial and vascular inflammation. PET in conjunction with magnetic resonance imaging helps in better characterization of neurological sequelae of COVID-19. Despite the fact that the majority of published literature is retrospective in nature with limited sample sizes, it is clear that molecular imaging provides additional valuable information (complimentary to anatomical imaging) with semi-quantitative or quantitative parameters to define inflammatory burden and can be used to guide therapeutic strategies and assess response. However, widespread clinical applicability remains a challenge owing to longer image acquisition times and the need for adoption of infection control protocols.

• Molecular imaging
• Nuclear medicine
• Functional imaging
• COVID-19
• SARS-CoV-2
• Sequelae

• GERIATRIC MEDICINE
• Respiratory infections
• Thoracic medicine

• Aged
• Anti-Bacterial Agents/therapeutic use
• Humans
• Lung/diagnostic imaging
• Multicenter Studies as Topic
• Pneumonia/diagnostic imaging
• Pneumonia/drug therapy
• Randomized Controlled Trials as Topic
• Standard of Care
• Tomography, X-Ray Computed
• Ultrasonography/methods

The pandemic outbreak of the novel coronavirus disease (COVID-19) has highlighted the need to combine rapid, non-invasive and widely accessible techniques with the least risk of patient’s cross-infection to achieve a successful early detection and surveillance of the disease. In this regard, the lung ultrasound (LUS) technique has been proved invaluable in both the differential diagnosis and the follow-up of COVID-19 patients, and its potential may be destined to evolve. Recently, indeed, LUS has been empowered through the development of automated image processing techniques.

To provide a systematic review of the application of artificial intelligence (AI) technology in medical LUS analysis of COVID-19 patients using the preferred reporting items of systematic reviews and meta-analysis (PRISMA) guidelines.

A literature search was performed for relevant studies published from March 2020 - outbreak of the pandemic - to 30 September 2021. Seventeen articles were included in the result synthesis of this paper.

As part of the review, we presented the main characteristics related to AI techniques, in particular deep learning (DL), adopted in the selected articles. A survey was carried out on the type of architectures used, availability of the source code, network weights and open access datasets, use of data augmentation, use of the transfer learning strategy, type of input data and training/test datasets, and explainability.

Finally, this review highlighted the existing challenges, including the lack of large datasets of reliable COVID-19-based LUS images to test the effectiveness of DL methods and the ethical/regulatory issues associated with the adoption of automated systems in real clinical scenarios.

• Lung ultrasound
• Deep learning
• Neural network
• COVID-19 pneumonia
• Medical imaging

• airway
• lung ultrasound
• point of care ultrasound
• respiration
• ultrasound

• Artificial intelligence
• COVID-19 pandemic
• Electronic health record
• Machine learning

• RF1 AG072449 NIA NIH HHS

Improved emergency care of children with acute illness or injuries is needed for countries in Africa to continue to reduce childhood mortality rates. Quality improvement efforts will depend on robust baseline data, but little has been published on the breadth and severity of paediatric illness seen in Mozambique.

This was a retrospective review of routinely collected provider shift summary data from the Paediatric Emergency Department (PED) at Hospital Central de Maputo (HCM), the principal academic and referral hospital in the country. All children 0–14 years of age seen in the 12-month period from August 2018–July 2019 were included. Descriptive statistical analyses were performed.

Data from 346 days and 64,966 patient encounters were analyzed. The large majority of patients (96.4%) presented directly to the PED without referral from a lower level facility. An average of 188 patients was seen per day, with significant seasonal variation peaking in March (292 patients/day). The most common diagnoses were upper respiratory infections (URI), gastroenteritis, asthma, and dermatologic problems. The highest acuity diagnoses were neurologic problems (59%), asthma (57%), and neonatal diagnoses (50%). Diagnoses with the largest proportion of admissions included neurologic problems, malaria, and neonatal diagnoses. Rapid malaria antigen tests were the most commonly ordered laboratory test across all diagnostic categories; full blood count (FBC) and chemistries were also commonly ordered. Urinalysis and HIV testing were rarely done in the PED.

This epidemiologic profile of illness seen in the HCM PED will allow for improved resource utilisation. We identified opportunities for evidence-based care algorithms for common diagnoses such as respiratory illness to improve patient care and flow. The PED may also be able to optimize laboratory and radiology evaluation for patients and develop standardized admission criteria by diagnosis.

• Emergency care
• Paediatric
• Sub-Saharan Africa
• Triage

• COVID-19
• Disease classification
• Image processing
• Lung ultrasound
• Spectral mask

Respiratory illness is a leading cause of morbidity in adults and the number one cause of mortality in children, yet billions of people lack access to medical imaging to assist in its diagnosis. Although ultrasound is highly sensitive and specific for respiratory illness such as pneumonia, its deployment is limited by a lack of sonographers. As a solution, we tested a standardised lung ultrasound volume sweep imaging (VSI) protocol based solely on external body landmarks performed by individuals without prior ultrasound experience after brief training. Each step in the VSI protocol is saved as a video clip for later interpretation by a specialist.

Dyspneic hospitalised patients were scanned by ultrasound naive operators after 2 hours of training using the lung ultrasound VSI protocol. Separate blinded readers interpreted both lung ultrasound VSI examinations and standard of care chest radiographs to ascertain the diagnostic value of lung VSI considering chest X-ray as the reference standard. Comparison to clinical diagnosis as documented in the medical record and CT (when available) were also performed. Readers offered a final interpretation of normal, abnormal, or indeterminate/borderline for each VSI examination, chest X-ray, and CT.

Operators scanned 102 subjects (0–89 years old) for analysis. Lung VSI showed a sensitivity of 93% and a specificity of 91% for an abnormal chest X-ray and a sensitivity of 100% and a specificity of 93% for a clinical diagnosis of pneumonia. When any cases with an indeterminate rating on chest X-ray or ultrasound were excluded (n=38), VSI lung ultrasound showed 92% agreement with chest X-ray (Cohen’s κ 0.83 (0.68 to 0.97, p<0.0001)). Among cases with CT (n=21), when any ultrasound with an indeterminate rating was excluded (n=3), there was 100% agreement with VSI.

Lung VSI performed by previously inexperienced ultrasound operators after brief training showed excellent agreement with chest X-ray and high sensitivity and specificity for a clinical diagnosis of pneumonia. Blinded readers were able to identify other respiratory diseases including pulmonary oedema and pleural effusion. Deployment of lung VSI could benefit the health of the global community.

• pleural effusion
• pneumonia
• pulmonary edema
• teleultrasound
• ultrasound

• Artifacts
• Computer Simulation
• Human Body
• Humans
• Lung/diagnostic imaging
• Ultrasonography

• COVID-19
• Coronavirus
• Doppler imaging
• Lung Ultrasound
• Pandemic
• Pneumothorax

• CNN
• COVID-19
• Deep Learning
• LSTM
• hyperparameter optimization
• lung ultrasound
• neural networks

• COVID-19
• Diagnosis, Computer-Assisted
• Humans
• Lung/diagnostic imaging
• Neural Networks, Computer
• SARS-CoV-2

• COVID-19
• Emergency
• Lung ultrasound
• Outbreak
• Pneumonia
• Screening

• Adult
• Aged
• Aged, 80 and over
• COVID-19/complications
• COVID-19/diagnostic imaging
• Emergency Service, Hospital/organization & administration
• Emergency Service, Hospital/statistics & numerical data
• Female
• Humans
• Lung/diagnostic imaging
• Lung/physiopathology
• Male
• Mass Screening/methods
• Mass Screening/statistics & numerical data
• Middle Aged
• Pneumonia/diagnosis
• Pneumonia/diagnostic imaging
• Pneumonia/etiology
• Real-Time Polymerase Chain Reaction/methods
• Real-Time Polymerase Chain Reaction/statistics & numerical data
• Retrospective Studies
• Ultrasonography/methods
• Ultrasonography/trends

• Lung ultrasound
• robotic ultrasound
• teleoperation

• DP5 OD028162 NIH HHS
• Korea National Institute of Health