title: Multidetector-row computed tomography diagnosis of small bowel obstruction: can coronal reformations replace axial images?
abstract: Feasibility of diagnosing small bowel obstruction on multidetector-row computed tomography (MDCT) using coronal reformations alone is evaluated. Three radiologists with subspecialty training in abdominal imaging reviewed abdominopelvic CT of 67 patients in consensus. Thirty-four patients had surgically proven small bowel obstruction. The remaining 33 patients had CT for other reasons and had no intestinal obstruction. The images were displayed in either axial or coronal planes and were reviewed on separate days . Each CT was evaluated for the presence of small bowel obstruction and its etiology when applicable. Thirty-three (100%) of 33 patients were correctly diagnosed not to have intestinal obstruction on coronal images. Thirty-four (100%) of 34 patients were correctly diagnosed to have small bowel obstruction on both forms of image display. There were five patients where the final surgical diagnosis for the etiology of small bowel obstruction did not agree with the interpretation of either the coronal or axial images; however, in all five patients, the interpretations of axial and coronal images were similar. In only one patient, the etiology of small bowel obstruction based on the coronal images did not agree with that of axial images and the surgical result; however, the site of small bowel obstruction was correctly diagnosed. There were approximately 20% fewer images in the coronal reformation data set, and the radiologists found review of these images to be easier for localizing the zone of transition in small bowel obstruction. Very high diagnostic accuracy can be achieved based on coronal reformations alone, and this form of image display may potentially be substituted for the conventional axial images. Since there are fewer images to review when the studies are displayed in coronal plane, this may positively impact radiologist workflow.
authors.affiliation: Department of Radiology, Northwestern University, Suite 800, 676 N. St. Clair St., Chicago, IL 60611, USA. v-yaghmai@northwestern.edu
authors.forename: Vahid
authors.initials: V
authors.lastname: Yaghmai
authors.forename: Paul
authors.initials: P
authors.lastname: Nikolaidis
authors.forename: Nancy A
authors.initials: NA
authors.lastname: Hammond
authors.forename: Bojan
authors.initials: B
authors.lastname: Petrovic
authors.forename: Richard M
authors.initials: RM
authors.lastname: Gore
authors.forename: Frank H
authors.initials: FH
authors.lastname: Miller
mesh_terms: D001185:Artificial Intelligence; D016022:Case-Control Studies; D002641:Chicago; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007415:Intestinal Obstruction / Q000000981:diagnostic imaging* / Q000209:etiology / Q000473:pathology / Q000601:surgery; D007421:Intestine, Small / Q000000981:diagnostic imaging* / Q000473:pathology*; D007813:Laparotomy; D008875:Middle Aged; D015588:Observer Variation; D011857:Radiographic Image Interpretation, Computer-Assisted; D011873:Radiology Information Systems; D012107:Research Design; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*