Evidence map›Paper›PMID 37162901›Full record

ArticleResearch square2023

Design and fabrication of 3D-printed patient-specific soft tissue and bone phantoms for CT imaging.

Kai Mei, Pouyan Pasyar, Michael Geagan, Leening P Liu, Nadav Shapira, Grace J Gang, J Webster Stayman, Peter B Noël

Open access · greenAbstract readPreprint
In one paragraph

Article in Research square, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Kai MeiUniversity of Pennsylvania.
Pouyan PasyarUniversity of Pennsylvania.
Michael GeaganUniversity of Pennsylvania.
Leening P LiuUniversity of Pennsylvania.
Nadav ShapiraUniversity of Pennsylvania.
Grace J GangUniversity of Pennsylvania.
J Webster StaymanJohns Hopkins University.
Peter B NoëlUniversity of Pennsylvania.
California University of Pennsylvania · USJohns Hopkins University · US

Funding

Framework for radiomics standardization with application in pulmonary CT scansR01EB031592 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI GANG, JIANAN GRACE, STAYMAN, JOSEPH WEBSTER · 2022 to 2025
$2.6M
Patient-specific, high-sensitivity spectral CT for assessment of pancreatic cancerR01EB030494 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI GANG, JIANAN GRACE, NOËL, PETER B · 2021 to 2024
$2.4M
Nonlinear performance analysis and prediction for robust low dose lung CTR01CA249538 · NCI · UNIVERSITY OF PENNSYLVANIA · PI GANG, JIANAN GRACE · 2021 to 2024
$2.0M
NCI NIH HHS R01 CA249538NIBIB NIH HHS R01 EB030494NIBIB NIH HHS R01 EB031592
6 · The paper itself

Abstract

The objective of this study is to create patient-specific phantoms for computed tomography (CT) that have realistic image texture and densities, which are critical in evaluating CT performance in clinical settings. The study builds upon a previously presented 3D printing method (PixelPrint) by incorporating soft tissue and bone structures. We converted patient DICOM images directly into 3D printer instructions using PixelPrint and utilized stone-based filament to increase Hounsfield unit (HU) range. Density was modeled by controlling printing speed according to volumetric filament ratio to emulate attenuation profiles. We designed micro-CT phantoms to demonstrate the reproducibility and to determine mapping between filament ratios and HU values on clinical CT systems. Patient phantoms based on clinical cervical spine and knee examinations were manufactured and scanned with a clinical spectral CT scanner. The CT images of the patient-based phantom closely resembled original CT images in texture and contrast. Measured differences between patient and phantom were less than 15 HU for soft tissue and bone marrow. The stone-based filament accurately represented bony tissue structures across different X-ray energies, as measured by spectral CT. In conclusion, this study demonstrated the possibility of extending 3D-printed patient-based phantoms to soft tissue and bone structures while maintaining accurate organ geometry, image texture, and attenuation profiles.

Indexed as

3D printingbone imagingcomputed tomographyphantomsquality assurance

Identifiers

PMID37162901
PMCPMC10168445
OpenAlexW4367059395

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.