Evidence map›Paper›PMID 35445429›Full record

ArticleMedical physics2022

Generating patient-matched 3D-printed pedicle screw and laminectomy drill guides from Cone Beam CT images: Studies in ovine and porcine cadavers.

Andrew Kanawati, Alex Constantinidis, Zoe Williams, Ricky O'Brien, Tess Reynolds

Open access · hybridAbstract read
In one paragraph

Article in Medical physics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Andrew KanawatiWestmead Hospital, Sydney, NSW, Australia.
Alex ConstantinidisWestmead Hospital, Sydney, NSW, Australia.
Zoe WilliamsFaculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.
Ricky O'BrienFaculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.
Tess ReynoldsFaculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.
The University of Sydney · AUWestmead Hospital · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe emergence of robotic Cone Beam Computed Tomography (CBCT) imaging systems in trauma departments has enabled 3D anatomical assessment of musculoskeletal injuries, supplementing conventional 2D fluoroscopic imaging for examination, diagnosis, and treatment planning. To date, the primary focus has been on trauma sites in the extremities. PURPOSE: To determine if CBCT images can be used during the treatment planning process in spinal instrumentation and laminectomy procedures, allowing accurate 3D-printed pedicle screw and laminectomy drill guides to be generated for the cervical and thoracic spine.

methodsThe accuracy of drill guides generated from CBCT images was assessed using animal cadavers (ovine and porcine). Preoperative scans were acquired using a robotic CBCT C-arm system, the Siemens ARTIS pheno (Siemens Healthcare, GmbH, Germany). The CBCT images were imported into 3D-Slicer version 4.10.2 (www.slicer.org) where vertebral models and specific guides were developed and subsequently 3D-printed. In the ovine cadaver, 11 pedicle screw guides from the T1-T5 and T7-T12 vertebra and six laminectomy guides from the C2-C7 vertebra were planned and printed. In the porcine cadaver, nine pedicle screw guides from the C3-T4 vertebra were planned and printed. For the pedicle screw guides, accuracy was assessed by three observers according to pedicle breach via the Gertzbein-Robbins grading system as well as measured mean axial and sagittal screw error via postoperative CBCT and CT scans. For the laminectomies, the guides were designed to leave 1 mm of lamina. The average thickness of the lamina at the mid-point was used to assess the accuracy of the guides, measured via postoperative CBCT and CT scans from three observers. For all measurements, the intraclass correlation coefficient (ICC) was calculated to determine observer reliability.

resultsCompared with the planned screw angles for both the ovine and porcine procedures (n = 32), the mean axial and sagittal screw error measured on the postoperative CBCT scans from three observers were 3.9 ± 1.9° and 1.8 ± 0.8°, respectively. The ICC among the observes was 0.855 and 0.849 for the axial and sagittal measurements, respectively, indicating good reliability. In the ovine cadaver, directly comparing the measured axial and sagittal screw angle of the visible screws (n = 14) in the postoperative CBCT and conventional CT scans from three observers revealed an average difference 1.9 ± 1.0° in axial angle and 1.8 ± 1.0° in the sagittal angle. The average thickness of the lamina at the middle of each vertebra, as measured on-screen in the postoperative CBCT scans by three observes was 1.6 ± 0.2 mm. The ICC among observers was 0.693, indicating moderate reliability. No lamina breaches were observed in the postoperative images.

conclusionHere, CBCT images have been used to generate accurate 3D-printed pedicle screw and laminectomy drill guides for use in the cervical and thoracic spine. The results demonstrate sufficient precision compared with those previously reported, generated from standard preoperative CT and MRI scans, potentially expanding the treatment planning capabilities of robotic CBCT imaging systems in trauma departments and operating rooms.

Indexed as

Pedicle ScrewsSpinal FusionSurgery, Computer-AssistedAnimalsCadaverCervical VertebraeCone-Beam Computed TomographyLaminectomyPrinting, Three-DimensionalReproducibility of ResultsSheepSwine3D-printingCone Beam CTspine

Identifiers

PMID35445429
PMCPMC9544846
OpenAlexW4224213958

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.