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Automatic assessment of the quality of patient positioning and field of view of head CT scans
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Paper Abstract

The purpose of this paper is the investigation of automatic evaluation of the quality of patient positioning and Field of View (FoV) in head CT scans. Studies have shown elevated risk of radiation-induced cataract in patients undergoing head CT examinations. The American Association of Physicists in Medicine (AAPM) published a protocol for head CT scans including requirements linking the optimal scan angle to anatomic landmarks in the skull. To help sensitizing staff for the need of correct patient positioning, a software-based tool detecting nonoptimal patient positioning was developed. Our experiments were conducted on 209 head CT exams acquired at the University Medical Center Hamburg Eppendorf (UKE). All of these examinations were done on the same Philips iCT scanner. Each exam contains a 3D volume with an in-plane voxel spacing of 0.44mm x 0.44mm and a slice distance of 1mm. As ground truth anatomic landmarks on the skull were annotated independently by three different readers. We applied an atlas registration technique to map CT scans to a probabilistic anatomical atlas. For a new CT scan, previously defined model landmarks were mapped back to the CT volume when registering it to the atlas thus labelling new head CT scans. From the location of the detected landmarks we derive the deviation of the actual head angulation and scan length from the optimal values. Furthermore, the presence of the eye-lenses in the FoV is predicted. The median error of the estimated landmark positions measured as distance to the plane generated from the ground truth landmark positions is below 1mm and comparable to the interobserver variability. A classifier for the prediction of the presence of the eye-lenses in the FoV from the estimated landmark locations achieves a κ value of 0.74. Furthermore there is moderate agreement of the estimated deviations of optimal head tilt and scan length with an expert’s rating.

Paper Details

Date Published: 15 March 2019
PDF: 13 pages
Proc. SPIE 10954, Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications, 109540N (15 March 2019); doi: 10.1117/12.2509823
Show Author Affiliations
Thomas Buelow, Philips Research (Germany)
Stewart Young, Philips Research (Germany)
Tim Harder, Philips Research (Germany)
Isabelle Frischmuth, Universitätsklinikum Hamburg-Eppendorf (Germany)
Jan-Hendrik Buhk, Universitätsklinikum Hamburg-Eppendorf (Germany)

Published in SPIE Proceedings Vol. 10954:
Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications
Po-Hao Chen; Peter R. Bak, Editor(s)

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