Design and development of a virtual anatomic atlas of the human skull for automatic segmentation in computer-assisted surgery, preoperative planning, and navigation

TY - JOUR

T1 - Design and development of a virtual anatomic atlas of the human skull for automatic segmentation in computer-assisted surgery, preoperative planning, and navigation

AU - Metzger, M C

AU - Bittermann, G

AU - Dannenberg, L

AU - Schmelzeisen, R

AU - Gellrich, N-C

AU - Hohlweg-Majert, B

AU - Scheifele, C

PY - 2013/9/8

Y1 - 2013/9/8

N2 - PURPOSE: Manual segmentation of CT datasets for preoperative planning and intraoperative navigation is a time-consuming procedure. The purpose of this study was to develop an automated segmentation procedure for the facial skeleton based on a virtual anatomic atlas of the skull, to test its practicability, and to evaluate the accuracy of the segmented objects.MATERIALS AND METHODS: The atlas skull was created by manually segmenting an unaffected skull CT dataset. For automated segmentation of cases via IPlan cranial (BrainLAB, Germany), the atlas skull underwent projection, controlled deformation, and a facultative threshold segmentation within the individual datasets, of which 16 routine CT (13 pathologies, 3 without) were processed. The variations of the no-threshold versus threshold segmentation results compared to the original were determined. The clinical usability of the results was assessed in a multicentre evaluation.RESULTS: Compared to the original dataset, the mean accuracy was [Formula: see text] mm for the threshold segmentation and 0.6-1.4 mm for the no-threshold segmentation. Comparing both methods together, the deviation was [Formula: see text] mm. An isolated no-threshold segmentation of the orbital cavity alone resulted in a mean accuracy of [Formula: see text] mm. With regard to clinical usability, the no-threshold method was clearly preferred, reaching modal scores of "good" to "moderate" in most areas. Limitations were seen in segmenting the TMJ, mandibular fractures, and thin bone in general.CONCLUSION: The feasibility of automated skull segmentation was demonstrated. The virtual anatomic atlas can improve the preprocessing of skull CT scans for computer assisted craniomaxillofacial surgery planning.

AB - PURPOSE: Manual segmentation of CT datasets for preoperative planning and intraoperative navigation is a time-consuming procedure. The purpose of this study was to develop an automated segmentation procedure for the facial skeleton based on a virtual anatomic atlas of the skull, to test its practicability, and to evaluate the accuracy of the segmented objects.MATERIALS AND METHODS: The atlas skull was created by manually segmenting an unaffected skull CT dataset. For automated segmentation of cases via IPlan cranial (BrainLAB, Germany), the atlas skull underwent projection, controlled deformation, and a facultative threshold segmentation within the individual datasets, of which 16 routine CT (13 pathologies, 3 without) were processed. The variations of the no-threshold versus threshold segmentation results compared to the original were determined. The clinical usability of the results was assessed in a multicentre evaluation.RESULTS: Compared to the original dataset, the mean accuracy was [Formula: see text] mm for the threshold segmentation and 0.6-1.4 mm for the no-threshold segmentation. Comparing both methods together, the deviation was [Formula: see text] mm. An isolated no-threshold segmentation of the orbital cavity alone resulted in a mean accuracy of [Formula: see text] mm. With regard to clinical usability, the no-threshold method was clearly preferred, reaching modal scores of "good" to "moderate" in most areas. Limitations were seen in segmenting the TMJ, mandibular fractures, and thin bone in general.CONCLUSION: The feasibility of automated skull segmentation was demonstrated. The virtual anatomic atlas can improve the preprocessing of skull CT scans for computer assisted craniomaxillofacial surgery planning.

KW - Adult

KW - Anatomy, Artistic/instrumentation

KW - Equipment Design

KW - Female

KW - Humans

KW - Imaging, Three-Dimensional

KW - Preoperative Care/methods

KW - Reproducibility of Results

KW - Skull/diagnostic imaging

KW - Software Design

KW - Surgery, Computer-Assisted/methods

KW - Tomography, X-Ray Computed/methods

U2 - 10.1007/s11548-013-0818-6

DO - 10.1007/s11548-013-0818-6

M3 - SCORING: Journal article

C2 - 23417709

VL - 8

SP - 691

EP - 702

JO - INT J COMPUT ASS RAD

JF - INT J COMPUT ASS RAD

SN - 1861-6410

IS - 5

ER -