Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Acute aortic syndromes and traumatic aortic injury are often diagnosed on CT angiography, possibly requiring emergent intervention. Advances in handheld computing have created the possibility of viewing full DICOM datasets from a remote location. We evaluated the ability to diagnose and characterize acute aortic pathologies on CT angiograms of the thorax using an iPhone-based DICOM viewer. This study was performed after Institutional Review Board approval. Fifteen CT angiograms of the thorax in suspected acute aortic syndromes were evaluated by three blinded radiologists on a handheld device using a DICOM viewer. Studies were evaluated for the ability to identify and classify aortic dissection, transection, or intramural hematoma, measure aortic dimensions, and identify mediastinal hematoma, arch variants, and pulmonary pathology. Studies were compared to blinded interpretations on a dedicated PACS workstation. The aortic pathology was correctly identified as aortic transection/pseudoaneurysm (n = 5), type A dissection (n = 2), and type A intramural hematoma (n = 1) by all reviewers, with no false-positive interpretations. This represents a sensitivity and specificity of 100 %. Mediastinal hematoma (n = 6), pneumothorax (five right, three left), and arch vessel involvement (n = 2) were identified in all cases. There was 88.5 % accuracy in identifying arch variants. Measurement of the size of the involved aortic segment was similar on handheld device and PACS workstation; however the adjacent normal aorta was 1.2 ± 1.0 mm larger on the handheld device (p = 0.03). Handheld DICOM viewers may be useful for emergent consultations and triage, and may expedite preprocedure planning to reduce the time interval between diagnostic scan and therapeutic intervention.
Acute aortic syndromes and traumatic aortic injury are often diagnosed on CT angiography, possibly requiring emergent intervention. Advances in handheld computing have created the possibility of viewing full DICOM datasets from a remote location. We evaluated the ability to diagnose and characterize acute aortic pathologies on CT angiograms of the thorax using an iPhone-based DICOM viewer. This study was performed after Institutional Review Board approval. Fifteen CT angiograms of the thorax in suspected acute aortic syndromes were evaluated by three blinded radiologists on a handheld device using a DICOM viewer. Studies were evaluated for the ability to identify and classify aortic dissection, transection, or intramural hematoma, measure aortic dimensions, and identify mediastinal hematoma, arch variants, and pulmonary pathology. Studies were compared to blinded interpretations on a dedicated PACS workstation. The aortic pathology was correctly identified as aortic transection/pseudoaneurysm (n = 5), type A dissection (n = 2), and type A intramural hematoma (n = 1) by all reviewers, with no false-positive interpretations. This represents a sensitivity and specificity of 100 %. Mediastinal hematoma (n = 6), pneumothorax (five right, three left), and arch vessel involvement (n = 2) were identified in all cases. There was 88.5 % accuracy in identifying arch variants. Measurement of the size of the involved aortic segment was similar on handheld device and PACS workstation; however the adjacent normal aorta was 1.2 ± 1.0 mm larger on the handheld device (p = 0.03). Handheld DICOM viewers may be useful for emergent consultations and triage, and may expedite preprocedure planning to reduce the time interval between diagnostic scan and therapeutic intervention.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.