title: Can non-contrast-enhanced CT (NECT) triage patients suspected of having non-traumatic acute aortic syndromes (AAS)?
abstract: This work was conducted to determine whether non-contrast-enhanced CT (NECT) of patients with suspected acute aortic syndrome (AAS) can identify patients with a very low likelihood of a positive diagnosis. In the derivation phase, patients who received both NECT and contrast-enhanced CT angiography (CTA) for suspected AAS were identified. Two readers blinded to CTA results analyzed NECTs from AAS positive and negative cases, recording maximal aortic diameters and qualitative findings of aortic disease. Logistic regression analysis was performed to identify independent positive predictors for AAS; those predictors were then used to create a decision rule. For the validation phase, NECTs from patients evaluated for AAS at a second institution were reviewed by two independent readers who recorded the presence of decision rule predictors while blinded to CTA results. In the derivation phase, 34 CTA positive and 83 CTA negative cases were reviewed. Measurements of aortic diameter alone achieved mean sensitivity and specificity of 82 % and of 83 %, respectively. Logistic regression identified aortic diameter, displaced calcifications, high attenuation aortic wall and abnormal aortic contour as independent predictors of AAS. The decision rule incorporating these findings achieved higher mean sensitivity (93 %), negative predictive value (96 %), and moderate reader agreement (kappa = 0.59). For the validation phase, application of the decision rule to 35 AAS positive and 45 AAS negative cases at the second institution yielded sensitivity of 100 % and specificity of 74 % for both readers. NECT can identify patients with a very low likelihood of AAS and potentially mitigate the urgency of performing CTA.
authors.affiliation: Department of Radiology, University of New Mexico Health Science Center, MSC10 5530, 1 University of New Mexico, Albuquerque, NM, 87131-0001, USA.
authors.forename: Paul R
authors.initials: PR
authors.lastname: Vantine
authors.forename: Jessica K
authors.initials: JK
authors.lastname: Rosenblum
authors.forename: William G
authors.initials: WG
authors.lastname: Schaeffer
authors.forename: Kevin T
authors.initials: KT
authors.lastname: Williams
authors.forename: David W
authors.initials: DW
authors.lastname: Dockray
authors.forename: Jeffrey M
authors.initials: JM
authors.lastname: Levsky
authors.forename: Linda B
authors.initials: LB
authors.lastname: Haramati
authors.forename: Loren H
authors.initials: LH
authors.lastname: Ketai
mesh_terms: D000208:Acute Disease; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001018:Aortic Diseases / Q000000981:diagnostic imaging*; D003287:Contrast Media; D003661:Decision Support Techniques; D003937:Diagnosis, Differential; D006801:Humans; D007472:Iohexol / Q000031:analogs & derivatives; D007479:Iopamidol; D008875:Middle Aged; D011857:Radiographic Image Interpretation, Computer-Assisted; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D013577:Syndrome; D014057:Tomography, X-Ray Computed / Q000295:instrumentation / Q000379:methods*; D014218:Triage
chemical_list: D003287:Contrast Media; D007472:Iohexol; C038192:iopromide; D007479:Iopamidol