Evidence map›Paper›PMID 38386922›Full record

ArticleJournal of applied clinical medical physics2024

Technical and clinical considerations of a physical liver phantom for CT radiomics analysis.

Bino Abel Varghese, Steven Yong Cen, Kristin Jensen, Joshua Levy, Hilde Kjernlie Andersen, Anselm Schulz, Xiaomeng Lei, Vinay Anant Duddalwar, David John Goodenough

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of applied clinical medical physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Radiomics and Back Pain.Global spine journal · 2026
    Review
  5. Article
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.

Bino Abel VargheseDepartment of Radiology, Keck Medical Center, University of Southern California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0002-0508-2899
Steven Yong CenDepartment of Radiology, Keck Medical Center, University of Southern California, Los Angeles, California, USA.
Kristin JensenDepartment of Physics and Computational Radiology, Oslo University Hospital, Oslo, Norway.
Joshua LevyThe Phantom Laboratory, Greenwich, New York, USA.
Hilde Kjernlie AndersenDepartment of Physics and Computational Radiology, Oslo University Hospital, Oslo, Norway.
Anselm SchulzDepartment of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
Xiaomeng LeiDepartment of Radiology, Keck Medical Center, University of Southern California, Los Angeles, California, USA.
Vinay Anant DuddalwarDepartment of Radiology, Keck Medical Center, University of Southern California, Los Angeles, California, USA.
David John GoodenoughDepartment of Radiology, George Washington University, Washington, D.C., USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study identifies key characteristics to help build a physical liver computed tomography (CT) phantom for radiomics harmonization; particularly, the higher-order texture metrics. MATERIALS AND

methodsCT scans of a radiomics phantom comprising of 18 novel 3D printed inserts with varying size, shape, and material combinations were acquired on a 64-slice CT scanner (Brilliance 64, Philips Healthcare). The images were acquired at 120 kV, 250 mAs, CTDIvol of 16.36 mGy, 2 mm slice thickness, and iterative noise-reduction reconstruction (iDose, Philips Healthcare, Andover, MA). Radiomics analysis was performed using the Cancer Imaging Phenomics Toolkit (CaPTk), following automated segmentation of 3D regions of interest (ROI) of the 18 inserts. The findings were compared to three additional ROI obtained of an anthropomorphic liver phantom, a patient liver CT scan, and a water phantom, at comparable imaging settings. Percentage difference in radiomic metrics values between phantom and tissue was used to assess the biological equivalency and <10% was used to claim equivalent.

resultsThe HU for all 18 ROI from the phantom ranged from -30 to 120 which is within clinically observed HU range of the liver, showing that our phantom material (T3-6B) is representative of biological CT tissue densities (liver) with >50% radiomic features having <10% difference from liver tissue. Based on the assessment of the Neighborhood Gray Tone Difference Matrix (NGTDM) metrics it is evident that the water phantom ROI show extreme values compared to the ROIs from the phantom. This result may further reinforce the difference between a structureless quantity such as water HU values and tissue HU values found in liver.

conclusionThe 3-D printed patterns of the constructed radiomics phantom cover a wide span of liver tissue textures seen in CT images. Using our results, texture metrics can be selectively harmonized to establish clinically relevant and reliable radiomics panels.

Indexed as

RadiomicsTomography, X-Ray ComputedHumansImage Processing, Computer-AssistedLiverPhantoms, ImagingTomography Scanners, X-Ray ComputedWaterWatercomputed tomographyimagingphantom studyradiomicsradiomics phantom

Identifiers

PMID38386922
PMCPMC11005983

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.