Bringing prevost's sign into the third dimension: Artificial intelligence estimation of conjugate gaze adjusted length (CGAL) and correlation with acute ischemic stroke.


Journal

Medicine
ISSN: 1536-5964
Titre abrégé: Medicine (Baltimore)
Pays: United States
ID NLM: 2985248R

Informations de publication

Date de publication:
04 Dec 2020
Historique:
entrez: 8 12 2020
pubmed: 9 12 2020
medline: 29 12 2020
Statut: ppublish

Résumé

Conjugate gaze deviation is associated with acute ischemic stroke (AIS), although previously only measured on a 2D plane. The current study evaluates 3D imaging efficacy to assess conjugate gaze deviation and correlate direction and strength of deviation to neuro-clinical findings.A retrospective analysis of 519 patients who had CT scans for suspected AIS at our institution. Direction and angle of eye deviation were calculated based on 2D axial images. Volumetric reconstruction of CT scans allowed for calculation of 3D conjugate gaze adjusted length (CGAL). Angle, direction, and vector strength of both 2D and 3D scans were calculated by an artificial intelligence algorithm and tested for agreement with hemispheric ischemia location. CGAL measurements were correlated to NIHSS scores. Follow up MRI data was used to evaluate the sensitivity and specificity of CGAL in the identification of AIS.The final analysis included 122 patients. A strong agreement was found between 3D gaze direction and hemispheric ischemia location. CGAL measurements were highly correlated with NIHSS score (r = .72, P = .01). A CGAL >0.25, >0.28, and >0.35 exhibited a sensitivity of 91%, 86%, and 82% and specificity of 66%, 89%, and 89%, respectively, in AIS identification. A CGAL >0.28 has the best sensitivity-specificity balance in the identification of AIS. A CGAL >0.25 has the highest sensitivity.Given CED's correlation with NIHSS score a 1/4 deviation in the ipsilateral direction is a sensitive ancillary radiographic sign to assist radiologists in making a correct diagnosis even when not presented with full clinical data.

Identifiants

pubmed: 33285711
doi: 10.1097/MD.0000000000023330
pii: 00005792-202012040-00048
pmc: PMC7717852
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e23330

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Auteurs

Hillel S Maresky (HS)

Department of Radiology, Shamir Medical Center, Zerifin.
Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel.
Department of Radiology, Lewis Katz School of Medicine, Temple University, Philadelphia, Pennyslvania.

Joseph M Rootman (JM)

Department of Psychology, University of British Columbia, Kelowna, BC, Canada.

Miriam M Klar (MM)

Department of Medicine, SUNY Downstate Health Sciences University, Brooklyn, New York.

Max Levitt (M)

Division of Urology, Department of Surgery, University of Ottawa, Ottawa, Ontario, Canada.

Alexander P Kossar (AP)

Department of Surgery, NewYork-Presbyterian Hospital/Columbia University Irving Medical Center, New York, New York.

David Zucker (D)

Department of Radiology, Shamir Medical Center, Zerifin.
Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel.

Michael Glazier (M)

Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel.

Shani Kalmanovich-Avnery (S)

Department of Interventional Neuroradiology, Shamir Medical Center, Zerifin, Israel.

Richard Aviv (R)

Department of Radiology, The Ottawa Hospital and University of Ottawa, Ottawa.

Birgit Ertl-Wagner (B)

Division of Neuroradiology, The Hospital for Sick Children, Toronto, Ontario, Canada.

Sigal Tal (S)

Department of Radiology, Shamir Medical Center, Zerifin.
Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel.

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Classifications MeSH