Brain and Lung Imaging Correlation in Patients with COVID-19: Could the Severity of Lung Disease Reflect the Prevalence of Acute Abnormalities on Neuroimaging? A Global Multicenter Observational Study

Mahammedi, Abdelkader; Ramos, Ana; Bargalló, Núria; Gaskill, Mary; Kapur, Sandip; Saba, Luca; Carrete, Henrique; Sengupta, Soma; Salvador, E.; Hilario, Amaya; Revilla, Yolanda; Sánchez, María Verónica Calyeca; Perez-Nuñez, M.; Bachir, Suha; Zhang, B.; Oleaga, Laura; J, Sergio; Koren, Lindsay; Martín-Medina, P.; Wang, L.; Benegas, Mariana; Ostos, Fernando; González-Ortega, Guillermo; Calleja, Patricia; Udstuen, Gavin; Williamson, Brady J.; Khandwala, Vivek; Chadalavada, Sucharitha; Woo, Doni; Vagal, Achala

doi:10.3174/ajnr.a7072

Cited by 26 publications

(33 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although COVID-19 is seen as a disease that primarily affects the lungs, it may also damage other organs, including heart 93 , 99 and brain, 93 , 99 – 102 and many long-term COVID-19 effects are still unknown. The COVID-19 patients have to be closely monitored even after their recovery, when imaging and AI may play a pivotal role.…”

Section: Ai Using Clinical Histopathology and Genomics With Imaging Datamentioning

confidence: 99%

“…96 The imaging characteristics can be used for prognosis assessment 97 and evaluation of the extent of disease, 11 and it has potential to predict the length of hospital stay. 98 Although COVID-19 is seen as a disease that primarily affects the lungs, it may also damage other organs, including heart 93,99 and brain, 93,[99][100][101][102] and many long-term COVID-19 effects are still unknown. The COVID-19 patients have to be closely monitored even after their recovery, when imaging and AI may play a pivotal role.…”

Section: Covid-19 Severity Assessment/prognosismentioning

confidence: 99%

See 1 more Smart Citation

Lessons learned in transitioning to AI in the medical imaging of COVID-19

Naqa

Fuhrman

et al. 2021

J. Med. Imag.

View full text Add to dashboard Cite

. The coronavirus disease 2019 (COVID-19) pandemic has wreaked havoc across the world. It also created a need for the urgent development of efficacious predictive diagnostics, specifically, artificial intelligence (AI) methods applied to medical imaging. This has led to the convergence of experts from multiple disciplines to solve this global pandemic including clinicians, medical physicists, imaging scientists, computer scientists, and informatics experts to bring to bear the best of these fields for solving the challenges of the COVID-19 pandemic. However, such a convergence over a very brief period of time has had unintended consequences and created its own challenges. As part of Medical Imaging Data and Resource Center initiative, we discuss the lessons learned from career transitions across the three involved disciplines (radiology, medical imaging physics, and computer science) and draw recommendations based on these experiences by analyzing the challenges associated with each of the three associated transition types: (1) AI of non-imaging data to AI of medical imaging data, (2) medical imaging clinician to AI of medical imaging, and (3) AI of medical imaging to AI of COVID-19 imaging. The lessons learned from these career transitions and the diffusion of knowledge among them could be accomplished more effectively by recognizing their associated intricacies. These lessons learned in the transitioning to AI in the medical imaging of COVID-19 can inform and enhance future AI applications, making the whole of the transitions more than the sum of each discipline, for confronting an emergency like the COVID-19 pandemic or solving emerging problems in biomedicine.

show abstract

Section: Ai Using Clinical Histopathology and Genomics With Imaging Datamentioning

confidence: 99%

Section: Covid-19 Severity Assessment/prognosismentioning

confidence: 99%

Lessons learned in transitioning to AI in the medical imaging of COVID-19

Naqa

Fuhrman

et al. 2021

J. Med. Imag.

View full text Add to dashboard Cite

show abstract

“…Studies have shown that patients with COVID-19 with acute neuroimaging abnormalities are more likely to have an ischemic stroke. Neuroimaging features of these patients are not invariable but are predominated by acute ischemic infarction, intracranial hemorrhage, and leukoencephalopathy [ 81 ]. COVID-19 is an independent risk factor for acute ischemic stroke and a valid indicator of poor prognosis.…”

Section: Examination Methods Reflecting Nervous System Damage In Covid-19 Patientsmentioning

confidence: 99%

What can the neurological manifestations of COVID-19 tell us: a meta-analysis

Bai

Zhu

et al. 2021

J Transl Med

View full text Add to dashboard Cite

Background Covid-19 became a global pandemic in 2019. Studies have shown that coronavirus can cause neurological symptoms, but clinical studies on its neurological symptoms are limited. In this meta-analysis, we aimed to summarize the various neurological manifestations that occurred in COVID-19 patients and calculate the incidence of various neurological manifestations. At the same time, we further explored the mechanism of nervous system injury and prognosis in COVID-19 patients in combination with their nervous system manifestations. This study provides a reference for early clinical identification of COVID-19 nervous system injury in the future, so as to achieve early treatment and reduce neurological sequelae. Methods We systematically searched all published English literature related to the neurological manifestations of COVID-19 from January 1, 2020, to April 30, 2021, in Pubmed, Embase, and Cochrane Library. The keywords used were COVID-19 and terminology related to the nervous system performance. All included studies were selected by two independent reviewers using EndNote and NoteExpress software, any disagreement was resolved by consensus or by a third reviewer, and the selected data were then collected for meta-analysis using a random-effects model. Results A total of 168 articles (n = 292,693) were included in the study, and the meta-analysis showed that the most common neurological manifestations of COVID-19 were myalgia(33%; 95%CI 0.30–0.37; I2 = 99.17%), smell impairment(33%; 95%CI 0.28–0.38; I2 = 99.40%), taste dysfunction(33%; 95%CI 0.27–0.39; I2 = 99.09%), altered mental status(32%; 95%CI 0.22–0.43; I2 = 99.06%), headache(29%; 95%CI 0.25–0.33; I2 = 99.42%), encephalopathy(26%; 95%CI 0.16–0.38; I2 = 99.31%), alteration of consciousness(13%; 95%CI 0.08–0.19; I2 = 98.10%), stroke(12%; 95%CI 0.08–0.16; I2 = 98.95%), dizziness(10%; 95%CI 0.08–0.13; I2 = 96.45%), vision impairment(6%; 95%CI 0.03–0.09; I2 = 86.82%), intracerebral haemorrhage(5%; 95%CI 0.03–0.09; I2 = 95.60%), seizure(4%; 95%CI 0.02 -0.05; I2 = 98.15%), encephalitis(2%; 95%CI 0.01–0.03; I2 = 90.36%), Guillan-Barré Syndrome (GBS) (1%; 95%CI 0.00–0.03; I2 = 89.48%). Conclusions Neurological symptoms are common and varied in Covid-19 infections, and a growing number of reports suggest that the prevalence of neurological symptoms may be increasing. In the future, the role of COVID-19 neurological symptoms in the progression of COVID-19 should be further studied, and its pathogenesis and assessment methods should be explored, to detect and treat early neurological complications of COVID-19 and reduce mortality.

show abstract

“…Ultimately, this cascade could result in neuronal and astroglial injury/death that will present as cognitive decline [208]. As worsening pulmonary health is correlated with neurological symptoms in COVID-19 patients, the hypoxia cascade is a plausible component of detrimental neurological alterations [210]. Fibrosis is a possible long-term pulmonary consequence from COVID-19, especially after long-duration severe disease, which can reduce overall lung capacity and reduce the efficiency of gas exchange [211].…”

Section: Pulmonary Renal and Liver Interactions With Covid-19mentioning

confidence: 99%

The Impact of the COVID-19 Pandemic on Dementia Risk: Potential Pathways to Cognitive Decline

Pyne¹,

Brickman²

2021

Neurodegener Dis

View full text Add to dashboard Cite

Background: Coronavirus disease 2019 (COVID-19), the far-reaching pandemic, has infected approximately 185 million of the world’s population to date. After infection, certain groups, including older adults, men, and people of color, are more likely to have adverse medical outcomes. COVID-19 can affect multiple organ systems, even among asymptomatic/mild severity individuals, with progressively worse damage for those with higher severity infections. Summary: The COVID-19 virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), primarily attaches to cells through the angiotensin-converting enzyme 2 (ACE2) receptor, a universal receptor present in most major organ systems. As SARS-CoV-2 binds to the ACE2 receptor, its bioavailability becomes limited, thus disrupting homeostatic organ function and inducing an injury cascade. Organ damage can then arise from multiple sources including direct cellular infection, overactive detrimental systemic immune response, and ischemia/hypoxia through thromboembolisms or disruption of perfusion. In the brain, SARS-CoV-2 has neuroinvasive and neurotropic characteristics with acute and chronic neurovirulent potential. In the cardiovascular system, COVID-19 can induce myocardial and systemic vascular damage along with thrombosis. Other organ systems such as the lungs, kidney, and liver are all at risk for infection damage. Key Messages: Our hypothesis is that each injury consequence has the independent potential to contribute to long-term cognitive deficits with the possibility of progressing to or worsening pre-existing dementia. Already, reports from recovered COVID-19 patients indicate that cognitive alterations and long-term symptoms are prevalent. This critical review highlights the injury pathways possible through SARS-CoV-2 infection that have the potential to increase and contribute to cognitive impairment and dementia.

show abstract

Brain and Lung Imaging Correlation in Patients with COVID-19: Could the Severity of Lung Disease Reflect the Prevalence of Acute Abnormalities on Neuroimaging? A Global Multicenter Observational Study

Cited by 26 publications

References 26 publications

Lessons learned in transitioning to AI in the medical imaging of COVID-19

Lessons learned in transitioning to AI in the medical imaging of COVID-19

What can the neurological manifestations of COVID-19 tell us: a meta-analysis

The Impact of the COVID-19 Pandemic on Dementia Risk: Potential Pathways to Cognitive Decline

Contact Info

Product

Resources

About