Evidence map›Paper›PMID 38922481›Full record

Article3D printing in medicine2024

Exploring CT pixel and voxel size effect on anatomic modeling in mandibular reconstruction.

Maariyah Ahmed, Myra Garzanich, Luigi E Melaragno, Sarah Nyirjesy, Natalia Von Windheim, Matthew Marquardt, Michael Luttrull, Nathan Quails, Kyle K VanKoevering

Abstract read
In one paragraph

Article in 3D printing in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

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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

6 citing papers in PubMed.

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4 · The record

Corrections and comments

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

9 authors.

Maariyah Ahmed *Center for Design and Manufacturing Excellence, The Ohio State University, Columbus, OH, USA.
Myra Garzanich *Center for Design and Manufacturing Excellence, The Ohio State University, Columbus, OH, USA.
Luigi E Melaragno *Center for Design and Manufacturing Excellence, The Ohio State University, Columbus, OH, USA.
Sarah NyirjesyDepartment of Otolaryngology-Head and Neck Surgery, The Ohio State University, 460 W 10th Ave 5th Floor Clinic, Columbus, OH, 43220, USA.
Natalia Von WindheimCenter for Design and Manufacturing Excellence, The Ohio State University, Columbus, OH, USA.
Matthew MarquardtDepartment of Otolaryngology-Head and Neck Surgery, The Ohio State University, 460 W 10th Ave 5th Floor Clinic, Columbus, OH, 43220, USA.
Michael LuttrullDepartment of Radiology, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
Nathan QuailsDepartment of Radiology, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
Kyle K VanKoeveringDepartment of Otolaryngology-Head and Neck Surgery, The Ohio State University, 460 W 10th Ave 5th Floor Clinic, Columbus, OH, 43220, USA. Kyle.vankoevering@osumc.edu.

Funding

The OSUCCC James Center for Cancer Engineering Accelerator Award n/a
6 · The paper itself

Abstract

backgroundComputer-aided modeling and design (CAM/CAD) of patient anatomy from computed tomography (CT) imaging and 3D printing technology enable the creation of tangible, patient-specific anatomic models that can be used for surgical guidance. These models have been associated with better patient outcomes; however, a lack of CT imaging guidelines risks the capture of unsuitable imaging for patient-specific modeling. This study aims to investigate how CT image pixel size (X-Y) and slice thickness (Z) impact the accuracy of mandibular models.

methodsSix cadaver heads were CT scanned at varying slice thicknesses and pixel sizes and turned into CAD models of the mandible for each scan. The cadaveric mandibles were then dissected and surface scanned, producing a CAD model of the true anatomy to be used as the gold standard for digital comparison. The root mean square (RMS) value of these comparisons, and the percentage of points that deviated from the true cadaveric anatomy by over 2.00 mm were used to evaluate accuracy. Two-way ANOVA and Tukey-Kramer post-hoc tests were used to determine significant differences in accuracy.

resultsTwo-way ANOVA demonstrated significant difference in RMS for slice thickness but not pixel size while post-hoc testing showed a significant difference in pixel size only between pixels of 0.32 mm and 1.32 mm. For slice thickness, post-hoc testing revealed significantly smaller RMS values for scans with slice thicknesses of 0.67 mm, 1.25 mm, and 3.00 mm compared to those with a slice thickness of 5.00 mm. No significant differences were found between 0.67 mm, 1.25 mm, and 3.00 mm slice thicknesses. Results for the percentage of points deviating from cadaveric anatomy greater than 2.00 mm agreed with those for RMS except when comparing pixel sizes of 0.75 mm and 0.818 mm against 1.32 mm in post-hoc testing, which showed a significant difference as well.

conclusionThis study suggests that slice thickness has a more significant impact on 3D model accuracy than pixel size, providing objective validation for guidelines favoring rigorous standards for slice thickness while recommending isotropic voxels. Additionally, our results indicate that CT scans up to 3.00 mm in slice thickness may provide an adequate 3D model for facial bony anatomy, such as the mandible, depending on the clinical indication.

Indexed as

Anatomic modelingCT scan resolutionHead and neck surgeryMandibular reconstructionPatient-specific modelingPixel sizeSlice thickness

Identifiers

PMID38922481
PMCPMC11202317

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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.