Evidence map›Paper›PMID 40973695›Full record

ArticleMedical physics2025

Modular breast and tumor perfusion phantoms for 4D dynamic contrast-enhanced dedicated breast CT.

Liselot C Goris, Sanne Gouma, Juan J Pautasso, Koen Michielsen, Ioannis Sechopoulos

Abstract read
In one paragraph

Article in Medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Liselot C GorisTechnical Medical Centre, University of Twente, Enschede, The Netherlands.
Sanne GoumaTechnical Medical Centre, University of Twente, Enschede, The Netherlands.
Juan J PautassoDepartment of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
Koen MichielsenDepartment of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
Ioannis SechopoulosTechnical Medical Centre, University of Twente, Enschede, The Netherlands.

Funding

European Research Council 864929
6 · The paper itself

Abstract

backgroundTumor heterogeneity presents significant challenges in breast cancer diagnosis and treatment. Four-dimensional dynamic contrast-enhanced dedicated breast CT (4D DCE-bCT) is a novel imaging technique designed to capture contrast agent kinetics with high spatial and temporal resolution, enabling detailed assessment of tumor perfusion and heterogeneity. PURPOSE: To develop modular breast tumor phantoms capable of simulating a range of physiologically relevant perfusion patterns and structural heterogeneities for validation of 4D DCE-bCT.

methodsTumor phantoms (1.5 cm diameter) were 3D-printed using clear resin in several designs: small-channel phantoms (0.8 and 1.0 mm diameter), a leaking vessel model with permeable outer walls, gyroid structures (1.3 and 1.5 mm pores) mimicking microvascularization, and a dual-input/output model to replicate heterogeneous perfusion. The phantoms were integrated into a programmable flow system, enabling iodinated contrast (up to 5 mg I/mL) delivery with custom profiles: full wash-in/wash-out, persistent, plateau, and partial wash-out. 4D DCE-bCT acquisitions with a 65 kV + 0.25 mm Cu filter involved 1 pre-contrast scan (360 pulses over a 10-second revolution at 80 mA) followed by three post-contrast phases (400 pulses over 10 revolutions at 32 mA). Images were reconstructed using 40 projections at 5-second intervals using prior image constrained compressed sensing (PICCS). Time-intensity curves (TICs) were analyzed in volumes of interest in various sections of the tumor phantoms. A gamma variate function was fitted to each TIC, and the corresponding fit parameters and coefficients of determination (R

resultsDynamic imaging demonstrated successful capture of expected contrast kinetics. Larger channels (1.0 mm) produced 2.5 times greater enhancement compared to smaller ones (0.8 mm). The R

conclusionThe developed 3D-printed tumor phantoms effectively simulate key perfusion features and point towards the feasibility of using 4D DCE-bCT to image detailed perfusion patterns.

Indexed as

BreastBreast NeoplasmsContrast MediaFour-Dimensional Computed TomographyPhantoms, ImagingFemaleHumansPerfusionPrinting, Three-DimensionalContrast Media3D printing4D DCE‐bCTbreast cancerphysical phantomstumor model

Identifiers

PMID40973695
PMCPMC12449291

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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.