Predicting Mechanical Ventilation and Mortality in COVID-19 Using Radiomics and Deep Learning on Chest Radiographs: A Multi-Institutional Study.

In this study, we aimed to predict mechanical ventilation requirement and mortality using computational modeling of chest radiographs (CXRs) for coronavirus disease 2019 (COVID-19) patients. This two-center, retrospective study analyzed 530 deidentified CXRs from 515 COVID-19 patients treated at Stony Brook University Hospital and Newark Beth Israel Medical Center between March and August 2020. Linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and random forest (RF) machine learning classifiers to predict mechanical ventilation requirement and mortality were trained and evaluated using radiomic features extracted from patients' CXRs.

Early Diagnosis of COVID-19 on Non-Chest CT Studies in the Emergency Setting: A Case Series and Review of the Literature.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel strain of coronavirus that has spread throughout the globe causing coronavirus disease 2019 (COVID-19). As the number of cases rises in the United States (US), it has become more imperative to detect COVID-19 at its earliest radiologic stage to decrease community transmission. In this case series, we discuss five patients who presented with non-respiratory-related symptoms and underwent non-chest CT imaging, such as abdominal and neck CT, with a portion of the lungs visualized in each respective study.

Effects of Prone Ventilation on Oxygenation, Inflammation, and Lung Infiltrates in COVID-19 Related Acute Respiratory Distress Syndrome: A Retrospective Cohort Study.

Patients receiving mechanical ventilation for coronavirus disease 2019 (COVID-19) related, moderate-to-severe acute respiratory distress syndrome (CARDS) have mortality rates between 76-98%. The objective of this retrospective cohort study was to identify differences in prone ventilation effects on oxygenation, pulmonary infiltrates (as observed on chest X-ray (CXR)), and systemic inflammation in CARDS patients by survivorship and to identify baseline characteristics associated with survival after prone ventilation. The study cohort included 23 patients with moderate-to-severe CARDS who received prone ventilation for ≥16 h/day and was segmented by living status: living ( = 6) and deceased ( = 17).

Subdural hygroma after spontaneous rupture of an arachnoid cyst in a pediatric patient: A case report.

Arachnoid cysts are benign masses that represent a relatively small percentage of intracranial lesions. Spontaneous rupture of an arachnoid cyst resulting in a subdural hygroma is a very rare event. We report a case of a pediatric patient with a history of an arachnoid cyst and chronic headaches presenting with bilateral papilledema, worsening headaches, and no history of head trauma.

Juvenile idiopathic arthritis in the lumbosacral spine of a toddler: Periarticular osteopenia in a rare location.

Juvenile idiopathic arthritis (JIA) is a group of childhood inflammatory arthropathies that affects multiple joints including the spine, particularly the cervical region. There is paucity of literature regarding JIA in the lumbosacral spine; the few published studies which discuss imaging findings in the lumbosacral spine only include cohorts of older children and adolescents. We present a 22-month-old boy with refusal to walk, in which plain radiographs and contrast-enhanced magnetic resonance imaging of the lumbosacral spine suggested a diagnosis of JIA.

Predicting Clinical Outcomes in COVID-19 using Radiomics and Deep Learning on Chest Radiographs: A Multi-Institutional Study.

We predict mechanical ventilation requirement and mortality using computational modeling of chest radiographs (CXRs) for coronavirus disease 2019 (COVID-19) patients. This two-center, retrospective study analyzed 530 deidentified CXRs from 515 COVID-19 patients treated at Stony Brook University Hospital and Newark Beth Israel Medical Center between March and August 2020. DL and machine learning classifiers to predict mechanical ventilation requirement and mortality were trained and evaluated using patient CXRs.

Sister Mary Joseph nodule: an often overlooked or misdiagnosed entity on imaging.

Sister Mary Joseph nodule (SMJN) is an umbilical nodule representing a metastatic deposit from an intra-abdominal primary malignancy. Most radiologists are unaware of this phenomenon, and cases of SMJN have rarely been described in the radiology literature, to our knowledge. We present an example of a patient with known primary pancreatic adenocarcinoma found to have an umbilical nodule as the first manifestation of metastatic disease after an initial misdiagnosis on computed tomography.

Vaping-associated acute respiratory distress syndrome.

Vaping-associated lung injury via the use of electronic nicotine delivery systems (ENDS) is currently being evaluated as a potential source of pulmonary injury with uncertain etiology as the use of tetrahydrocannabinol (THC) is increasing throughout the USA. ENDS are marketed to be unlike traditional cigarette smoking in that they are purported to contain only propylene glycol, vegetable glycerine, nicotine, and flavorants compared with the > 60 carcinogenic ingredients in cigarettes. The New England Journal of Medicine (NEJM) currently reports four imaging patterns correlated with vaping-attributed pathology including acute eosinophilic pneumonia, diffuse alveolar damage, organizing pneumonia, and lipoid pneumonia.