PMID- 35762028 OWN - NLM STAT- MEDLINE DCOM- 20220914 LR - 20220914 IS - 2473-4209 (Electronic) IS - 0094-2405 (Linking) VI - 49 IP - 9 DP - 2022 Sep TI - Deformable 3D-2D image registration and analysis of global spinal alignment in long-length intraoperative spine imaging. PG - 5715-5727 LID - 10.1002/mp.15819 [doi] AB - BACKGROUND: Spinal deformation during surgical intervention (caused by patient positioning and/or the correction of malalignment) confounds conventional navigation due to the assumptions of rigid transformation. Moreover, the ability to accurately quantify spinal alignment in the operating room would provide an assessment of the surgical product via metrics that correlate with clinical outcomes. PURPOSE: A method for deformable 3D-2D registration of preoperative CT to intraoperative long-length tomosynthesis images is reported for an accurate 3D evaluation of device placement in the presence of spinal deformation and automated evaluation of global spinal alignment (GSA). METHODS: Long-length tomosynthesis ("Long Film," LF) images were acquired using an O-arm imaging system (Medtronic, Minneapolis USA). A deformable 3D-2D patient registration was developed using multi-scale masking (proceeding from the full-length image to local subvolumes about each vertebra) to transform vertebral labels and planning information from preoperative CT to the LF images. Automatic measurement of GSA (main thoracic kyphosis [MThK] and lumbar lordosis [LL]) was obtained using a spline fit to registered labels. The "Known-Component Registration" method for device registration was adapted to the multi-scale process for 3D device localization from orthogonal LF images. The multi-scale framework was evaluated using a deformable spine phantom in which pedicle screws were inserted, and deformations were induced over a range in LL approximately 25 degrees -80 degrees . Further validation was carried out in a cadaver study with implanted pedicle screws and a similar range of spinal deformation. The accuracy of patient and device registration was evaluated in terms of 3D translational error and target registration error, respectively, and the accuracies of automatic GSA measurements were compared to manual annotation. RESULTS: Phantom studies demonstrated accurate registration via the multi-scale framework for all vertebral levels in both the neutral and deformed spine: median (interquartile range, IQR) patient registration error was 1.1 mm (0.7-1.9 mm IQR). Automatic measures of MThK and LL agreed with manual delineation within -1.1 degrees +/- 2.2 degrees and 0.7 degrees +/- 2.0 degrees (mean and standard deviation), respectively. Device registration error was 0.7 mm (0.4-1.0 mm IQR) at the screw tip and 0.9 degrees (1.0 degrees -1.5 degrees ) about the screw trajectory. Deformable 3D-2D registration significantly outperformed conventional rigid registration (p < 0.05), which exhibited device registration errors of 2.1 mm (0.8-4.1 mm) and 4.1 degrees (1.2 degrees -9.5 degrees ). Cadaver studies verified performance under realistic conditions, demonstrating patient registration error of 1.6 mm (0.9-2.1 mm); MThK within -4.2 degrees +/- 6.8 degrees and LL within 1.7 degrees +/- 3.5 degrees ; and device registration error of 0.8 mm (0.5-1.9 mm) and 0.7 degrees (0.4 degrees -1.2 degrees ) for the multi-scale deformable method, compared to 2.5 mm (1.0-7.9 mm) and 2.3 degrees (1.6 degrees -8.1 degrees ) for rigid registration (p < 0.05). CONCLUSION: The deformable 3D-2D registration framework leverages long-length intraoperative imaging to achieve accurate patient and device registration over the extended lengths of the spine (up to 64 cm) even with strong anatomical deformation. The method offers a new means for the quantitative validation of spinal correction (intraoperative GSA measurement) and the 3D verification of device placement in comparison to preoperative images and planning data. CI - (c) 2022 American Association of Physicists in Medicine. FAU - Zhang, Xiaoxuan AU - Zhang X AD - Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA. FAU - Uneri, Ali AU - Uneri A AD - Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA. FAU - Huang, Yixuan AU - Huang Y AD - Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA. FAU - Jones, Craig K AU - Jones CK AD - The Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, Maryland, USA. FAU - Witham, Timothy F AU - Witham TF AD - Department of Neurosurgery, Johns Hopkins University, Baltimore, Maryland, USA. FAU - Helm, Patrick A AU - Helm PA AD - Medtronic Inc., Littleton, Massachusetts, USA. FAU - Siewerdsen, Jeffrey H AU - Siewerdsen JH AD - Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA. AD - The Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, Maryland, USA. AD - Department of Neurosurgery, Johns Hopkins University, Baltimore, Maryland, USA. LA - eng GR - Biomedical Research Partnership with Medtronic Inc./ PT - Journal Article DEP - 20220725 PL - United States TA - Med Phys JT - Medical physics JID - 0425746 SB - IM MH - Algorithms MH - Cadaver MH - Humans MH - Imaging, Three-Dimensional/methods MH - *Pedicle Screws MH - Spine/diagnostic imaging/surgery MH - *Surgery, Computer-Assisted/methods MH - Tomography, X-Ray Computed/methods OTO - NOTNLM OT - 3D-2D registration OT - deformable registration OT - image-guided surgery OT - intraoperative imaging OT - spine surgery EDAT- 2022/06/29 06:00 MHDA- 2022/09/15 06:00 CRDT- 2022/06/28 02:12 PHST- 2022/06/03 00:00 [revised] PHST- 2022/02/15 00:00 [received] PHST- 2022/06/13 00:00 [accepted] PHST- 2022/06/29 06:00 [pubmed] PHST- 2022/09/15 06:00 [medline] PHST- 2022/06/28 02:12 [entrez] AID - 10.1002/mp.15819 [doi] PST - ppublish SO - Med Phys. 2022 Sep;49(9):5715-5727. doi: 10.1002/mp.15819. Epub 2022 Jul 25.