Sangita Kapur
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Research Interests
Sangita Kapur has a total of 37 co-authors. Here are the top co-authors by number of shared publications:
- Abdelkader Mahammedi
Division of Neuroimaging and Neurointervention, Department of Radiology, Stanford Center for Academic Medicine, Stanford University School of Medicine, Palo Alto, USA
1 shared publication Achala Vagal
Professor, Executive Vice Chair of Radiology, and Vice Chair of Research, Department of Radiology, University of Cincinnati, Cincinnati, Ohio
1 shared publication- Achala Vagal
University of Cincinnati
1 shared publication - Amaya Hilario
Department of Radiology, Hospital Universitario “12 de Octubre”, Madrid, Spain
1 shared publication - Ana Ramos
Neuroradiology Section, Department of Radiology, Hospital Universitario 12 de Octubre, Avenida de Córdoba s/n, 28045 Madrid, Spain
1 shared publication - Ann L. Brown
Department of Radiology, University of Cincinnati, Cincinnati, Ohio
1 shared publication
Latest Publications
- 6 January 2024
- Published by Elsevier in Journal of the American College of Radiology
- Vol. 21 (7) , 1145-1148
Humanized Health Care: Human-Centered Design in Screening Mammography
- 6 January 2024
- Published by Elsevier in Journal of the American College of Radiology
- Vol. 21 (7) , 1145-1148
Humanized Health Care: Human-Centered Design in Screening Mammography
- 11 March 2021
- Published by American Society of Neuroradiology (ASNR) in American Journal of Neuroradiology
- Vol. 42 (6) , 1008-1016
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
PURPOSE: Our aim was to study the association between abnormal findings on chest and brain imaging in patients with coronavirus disease 2019 (COVID-19) and neurologic symptoms. MATERIALS AND METHODS: In this retrospective, international multicenter study, we reviewed the electronic medical records and imaging of hospitalized patients with COVID-19 from March 3, 2020, to June 25, 2020. Our inclusion criteria were patients diagnosed with Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) infection with acute neurologic manifestations and available chest CT and brain imaging. The 5 lobes of the lungs were individually scored on a scale of 0–5 (0 corresponded to no involvement and 5 corresponded to >75% involvement). A CT lung severity score was determined as the sum of lung involvement, ranging from 0 (no involvement) to 25 (maximum involvement). RESULTS: A total of 135 patients met the inclusion criteria with 132 brain CT, 36 brain MR imaging, 7 MRA of the head and neck, and 135 chest CT studies. Compared with 86 (64%) patients without acute abnormal findings on neuroimaging, 49 (36%) patients with these findings had a significantly higher mean CT lung severity score (9.9 versus 5.8, P < .001). These patients were more likely to present with ischemic stroke (40 [82%] versus 11 [13%], P < .0001) and were more likely to have either ground-glass opacities or consolidation (46 [94%] versus 73 [84%], P = .01) in the lungs. A threshold of the CT lung severity score of >8 was found to be 74% sensitive and 65% specific for acute abnormal findings on neuroimaging. The neuroimaging hallmarks of these patients were acute ischemic infarct (28%), intracranial hemorrhage (10%) including microhemorrhages (19%), and leukoencephalopathy with and/or without restricted diffusion (11%). The predominant CT chest findings were peripheral ground-glass opacities with or without consolidation. CONCLUSIONS: The CT lung disease severity score may be predictive of acute abnormalities on neuroimaging in patients with COVID-19 with neurologic manifestations. This can be used as a predictive tool in patient management to improve clinical outcome.
- 11 March 2021
- Published by American Society of Neuroradiology (ASNR) in American Journal of Neuroradiology
- Vol. 42 (6) , 1008-1016
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
PURPOSE: Our aim was to study the association between abnormal findings on chest and brain imaging in patients with coronavirus disease 2019 (COVID-19) and neurologic symptoms. MATERIALS AND METHODS: In this retrospective, international multicenter study, we reviewed the electronic medical records and imaging of hospitalized patients with COVID-19 from March 3, 2020, to June 25, 2020. Our inclusion criteria were patients diagnosed with Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) infection with acute neurologic manifestations and available chest CT and brain imaging. The 5 lobes of the lungs were individually scored on a scale of 0–5 (0 corresponded to no involvement and 5 corresponded to >75% involvement). A CT lung severity score was determined as the sum of lung involvement, ranging from 0 (no involvement) to 25 (maximum involvement). RESULTS: A total of 135 patients met the inclusion criteria with 132 brain CT, 36 brain MR imaging, 7 MRA of the head and neck, and 135 chest CT studies. Compared with 86 (64%) patients without acute abnormal findings on neuroimaging, 49 (36%) patients with these findings had a significantly higher mean CT lung severity score (9.9 versus 5.8, P < .001). These patients were more likely to present with ischemic stroke (40 [82%] versus 11 [13%], P < .0001) and were more likely to have either ground-glass opacities or consolidation (46 [94%] versus 73 [84%], P = .01) in the lungs. A threshold of the CT lung severity score of >8 was found to be 74% sensitive and 65% specific for acute abnormal findings on neuroimaging. The neuroimaging hallmarks of these patients were acute ischemic infarct (28%), intracranial hemorrhage (10%) including microhemorrhages (19%), and leukoencephalopathy with and/or without restricted diffusion (11%). The predominant CT chest findings were peripheral ground-glass opacities with or without consolidation. CONCLUSIONS: The CT lung disease severity score may be predictive of acute abnormalities on neuroimaging in patients with COVID-19 with neurologic manifestations. This can be used as a predictive tool in patient management to improve clinical outcome.