# Morphological MRI knee phantoms: Design, preliminary results, and perspectives for applied research

Habeeb Yusuff, Thibault Willaume, Elodie Breton, Guillaume Bierry, Jean-Philippe Dillenseger

► To cite this version:

Habeeb Yusuff, Thibault Willaume, Elodie Breton, Guillaume Bierry, Jean-Philippe Dillenseger. Morphological MRI knee phantoms: Design, preliminary results, and perspectives for applied research. Radiography, 2025, 31 (6), pp.103195. 10.1016/j.radi.2025.103195. hal-05334222

HAL Id: hal-05334222

https://univoak.hal.science/hal-05334222v1

Submitted on 28 Oct 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_2.png" /></figure>

# Morphological MRI knee phantoms: Design, preliminary results, and perspectives for applied research

H. Yusuff<sup>a</sup>, T. Willaume<sup>b,d</sup>, E. Breton<sup>a</sup>, G. Bierry<sup>a,b,c,d</sup>, J.-P. Dillenseger<sup>a,b,c,d,*</sup>

<figure><img src="image_3.png" /></figure>

## ARTICLE INFO

**Article history:**
Received 15 May 2025
Received in revised form
21 September 2025
Accepted 24 September 2025
Available online xxx

**Keywords:**
MSK magnetic resonance imaging
Phantom
Knee MRI
3D printing
Educational MRI phantoms
Applied research

## ABSTRACT

**Introduction:** There is currently no MRI phantom capable of generating high-precision anatomical images in musculoskeletal (MSK) imaging. Yet, such phantoms, also referred to as "super-phantoms", could offer substantial value for MRI sequence testing, optimization, and applied research.

**Methods:** In this study, we focused on the knee region, creating phantoms based on reference MRI slices. Using computer-aided design (CAD) software, detailed anatomical structures were modeled, 3D printed, and filled with tissue-mimicking gels. MRI acquisitions were then performed to evaluate the potential of these tools.

**Results:** The resulting images demonstrated high anatomical fidelity and clinically realistic MRI-weighted contrasts. These phantoms show promise for a range of applications, including training, sequence optimization, hardware evaluation, and ethical aspects.

**Conclusion:** Although technical refinements are needed to improve long-term stability and achieve more accurate relaxometry, the phantoms hold strong potential for supporting applied MRI research.

**Implication for practice:** This new type of phantom can be considered an original and versatile tool for sequence development and hardware comparison. Moreover, it represents a valuable means to promote evidence-based practices and encourage MRI professionals (e.g. radiographers) to engage in applied research initiatives.

© 2025 The Author(s). Published by Elsevier Ltd on behalf of The College of Radiographers. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

## Introduction

The concept of "Super-Phantom" was recently defined by Manohar et al.<sup>1</sup> as "a computer model, an inanimate physical object, or an ex vivo organ that replicates the most relevant anatomic and functional imaging biomarkers of the structure of interest under carefully controlled laboratory settings." According to Manohar et al., the need for such innovative phantoms is particularly evident in two primary clinical scenarios. The first occurs when an existing imaging system demonstrates inadequate performance in a specific clinical application, prompting improvements in existing imaging hardware, protocols, or sequences. The second scenario reflects a broader clinical limitation, in which clinical needs may necessitate disruptive new technologies. In both contexts, early-stage validation using research prototypes

such as super-phantoms is essential for evaluating the prototypes and for accelerating translation into clinical practice.

The development of anatomical sectional phantoms has recently been described in the literature, but the published results are limited to the brain.<sup>2-7</sup> Although knee MRI accounts for a significant portion of clinical imaging activity, morphological phantoms of the knee are rare, costly, and generally limited in terms of MRI contrasts and anatomical realism. While Sultan et al.<sup>8</sup> attempted to develop an anthropomorphic phantom of the knee, their focus was limited to the dielectric properties of the joint. This gap is particularly relevant for knee imaging, as the knee is among the most commonly examined joints in MRI<sup>8</sup> and serves as a standard case for radiographer students beginning clinical training. Aligning with the concept of super-phantoms, innovative MSK phantoms for MRI hold significant potential for MR users both for educational and technical applications.

This work presents preliminary results of a low-cost, 3D-printed knee phantom suitable for MRI in terms of morphological realism and contrast. It also discusses the potential applications of these phantoms, supporting emerging avenues in applied MRI research.

<footnote><sup>a</sup>Université de Strasbourg, CNRS, Inserm, ICube UMR 7357, Strasbourg, France</footnote>

<footnote><sup>b</sup>Pôle d'imagerie médicale, Service d'imagerie 2, Hôpitaux Universitaires de Strasbourg, Strasbourg, France</footnote>

<footnote><sup>c</sup>Faculté de Médecine, Maïeutique et Sciences de la Santé, Université de Strasbourg, Strasbourg, France</footnote>

<footnote><sup>d</sup>Fédération de Médecine Translationnelle de Strasbourg (FMTS), FRU6702, Strasbourg, France</footnote>

<footnote>* Corresponding author. Faculté de Médecine, Maïeutique et Sciences de la Santé, 4, rue Kirschleger, 67000 Strasbourg - France.
E-mail address: jp.dillenseger@unistra.fr (J.-P. Dillenseger).</footnote>
# Methods

## Morphological phantoms design

In this study, we focused on the knee anatomical region, a joint frequently examined in MRI.

To achieve a high level of anatomical realism, the primary anatomical structures of interest were manually delineated from two reference knee MRI slices (Fig. 1a):

* A sagittal MRI slice through the posterior cruciate ligament

* A transversal MRI slice through the intercondylar fossa.

These slices were selected to capture critical morphological features relevant for musculoskeletal imaging.

The contours of anatomical structures were manually delineated using Keynote software (Keynote v12.2.1, Apple Inc, Cuperstino, USA) to generate anatomical illustrations (Fig. 1b) which were exported in PNG format. These images served as the basis for subsequent 3D CAD modeling⁹ using PTC Creo software (v10.0, Parametric Technology Corporation, Boston, USA). For each illustration, the anatomical boundaries were manually retraced to convert raster image data into vector representations interpretable by the CAD system for surface and volume generation. The 2D contours were extruded by 20 mm to generate hollow structures designed to be filled with gels (Fig. 1c).

In the sagittal phantom, a vertical cylindrical insert (6 mm diameter) was integrated into the tibial region to simulate the position of an orthopedic screw, thereby enabling the reproduction of metal-induced artefacts. This feature is particularly relevant for evaluating MRI sequences and guiding the selection of optimal imaging parameters in the presence of metallic implants.

In the coronal phantom, a 28 mm cylindrical housing was embedded within the gastrocnemius muscle to accommodate a 25 mm diameter spatial-resolution insert containing 0.6 mm alternating lines, equivalent to 8.33-line pairs per centimeter. Designed using the same 3D CAD software, this insert serves as a quick visual metric to assess whether the imaging sequence achieves a spatial resolution of 0.6 mm in either the readout or phase-encoding direction.

The integration of both a metal artefact-mimicking feature and a spatial resolution insert expands the phantom's utility beyond

anatomical fidelity and weighted contrast simulation, towards MRI system performance evaluation.

Each reference slice was integrated into a circular module with an external diameter of 140 mm, an internal diameter of 130 mm, and a height of 20 mm (Fig. 1c). All CAD files were exported in stereolithography (STL) format and subsequently 3D printed (Fig. 1d; see Section 2.2). The printed modules were filled with tissue-mimicking materials (TMM) as described in Section 2.3. The different steps of this phantom building process are shown in Fig. 1.

## Printing methods

STL models were printed using a fused deposition modeling (FDM) printer (X1-Carbon, Bambu Lab, Shenzhen, China) with 1.75 mm polyethylene-terephthalate-glycol (PETG) filament (Prusa Polymers, Prague, Czech Republic). G-code files for FDM printing were generated using BambuStudio slicer (v1.9.1.67, Bambu Lab, Shenzhen, China).

The spatial resolution inserts were printed using a stereolithography (SLA) printer (Halot-One, Creality 3D technology Co., Shenzhen, China) with a UV curable resin (Creality Standard Regid resin Plus, Creality 3D technology Co., Shenzhen, China). SLA printing was chosen for its high-resolution capabilities (<0.1 mm), which are not achievable with our FDM technology. The print files prepared in the proprietary cx3d format were generated using Halot-Box slicer (v3.5.5, Creality 3D Technology Co., Shenzhen, China).

Specific printing parameters are detailed in Table 1.

The printed modules underwent post-processing to remove residual support structures generated during the printing process. To address the presence of micro-gaps inherent in FDM printing, the internal walls of both modules were coated with a sealing spray (Vernis Universal, Akzo Nobel Decorative Paints, France) prior to gel filling. The printing material cost per phantom was less than 10€. All STL files are available in Supplementary Material 1.

## Tissue-mimicking materials and phantom filling

Tissue-Mimicking Materials (TMM) compositions were formulated based on a review of published literature,¹⁰⁻²⁰ with the aim of achieving relative contrasts representative of common MRI weightings ($T1_w$, $T2_w$ and proton density ($PD_w$) images).

<figure><img src="image_4.png" /><figcaption>**Figure 1.** $T1_w$ human knee MRI (a), anatomical drawing (b), phantoms CAD (c), 3D printed phantoms without (d) and with gels (e).</figcaption></figure>
<table><caption>**Table 1**
FDM and SLA 3D printing parameters.</caption><thead><tr><th></th><th></th></tr></thead><tbody><tr><td>FDM Printer model</td><td>X1-Carbon (Bambu Lab)</td></tr><tr><td>Nozzle</td><td>0.4 mm</td></tr><tr><td>Material/nozzle temperature/bed temperature</td><td>PETG/250 °C/60 °C</td></tr><tr><td>Infill/infill pattern</td><td>50 %/Grid</td></tr><tr><td>Layer height</td><td>0.2 mm</td></tr><tr><td>Print; Travel speed</td><td>50-300 mm/s; 500 mm/s</td></tr><tr><td>Average printing duration</td><td>4h</td></tr><tr><td>SLA printer model</td><td>Halot-One (Creality)</td></tr><tr><td>Layer thickness/Total floors</td><td>0.050mm/520</td></tr><tr><td>Initial exposure/Exposure time</td><td>40s/3s</td></tr><tr><td>Resin volume</td><td>49 mL</td></tr><tr><td>Printing duration</td><td>2h23min</td></tr></tbody></table>

- Synovial fluid was mimicked using commercial ultrasound gel chosen for its high water content and high signal intensity in T2<sub>w</sub> and PD<sub>w</sub> images. The relaxation times described in the literature<sup>18</sup> range from 1470 to 4273 ms for T1, and from 535 to 1577 ms for T2.

- Fat-containing structures (e.g., subcutaneous fat, bone marrow) were mimicked using 70 % polyvinyl chloride plastisol (PVC-P) to create a solid TMM with low water content and its inherent chemical shift properties, relevant for fat-saturation sequences.<sup>16</sup>

- Cartilage and muscle were mimicked using a composition of 1 % w/w carrageenan, 1 % w/w agarose, and 0.130 mmol/kg of gadolinium-based contrast agent<sup>17</sup> (gadoteric acid, 0.5 mmol/mL, Dotarem, Guerbet, Villepinte, France). Measurements performed in our laboratory yielded the following relaxation times: 1029 ms for T1, and 151 ms for T2, which are close to the values reported in the literature.<sup>19,20</sup>

- To simulate the presence of a metallic implant, high relaxivity (7.9 mmol<sup>-1</sup>s<sup>-1</sup>) gadolinium-based contrast agent (gadobenic acid, 0.5 mmol/mL, Multihance, Bracco Diagnostics Inc., Milan, Italy) was mixed with 2 % w/w carrageenan as a gelling agent.

Each TMM was poured into its corresponding compartment within the 3D-printed hollow modules prior to gelling, using a beaker for larger cavities and a syringe for smaller or more intricate ones. All phantoms were covered with protective plastic film and refrigerated at 4 °C until image acquisition, four days after gel filling.

## MRI acquisitions and image processing

Experiments were conducted using a 0.55T clinical MRI system (MAGNETOM Free.Max, Siemens Shenzhen Magnetic Resonance

Ltd., Shenzhen, PRC) with a 12-channel Head and Neck coil. Phantoms were positioned in the center of the coil and imaged through standard protocols used in diagnostic knee imaging, namely T1-weighted (T1<sub>w</sub>) turbo-spin-echo (TR 450 ms/TE 13 ms), and proton density-weighted with spectral fat suppression (PD<sub>w</sub>-FS) spin-echo (TR 3630 ms/TE 34 ms). For each contrast (T1<sub>w</sub> and PD<sub>w</sub>-FS) four acquisitions were performed with a slice thickness of 3 mm and four native pixel sizes (1.1 × 1.1 mm<sup>2</sup>; 1.1 × 0.55 mm<sup>2</sup>; 0.55 × 1.1<sup>2</sup> mm; and 0.55 × 0.55 mm<sup>2</sup>) to observe the effects on spatial resolution, chemical shift and metal artefacts (Table 2).

Images were reconstructed, both with and without a deep learning reconstruction (DLR) algorithm (Deep Resolve Boost, Siemens Healthineers, Germany). Quantitative measurements were extracted using Horos software (www.horosproject.org), employing region-of-interest (ROI) analysis, distance measurements, and intensity profile evaluations.

## Results

Figs. 2 and 3 illustrate the T1<sub>w</sub> and PD<sub>w</sub>-FS MRI images acquired using three different in-plane resolutions. The contrasts observed between the TMM in T1<sub>w</sub> and PD<sub>w</sub>-FS images are consistent with clinically known contrasts between muscle, synovial fluid and fat.

The spatial-resolution insert, composed of alternating 0.6 mm structures arranged in four circular quadrants, enabled assessment of whether the acquisition effectively resolves 0.6 mm details in both the phase and frequency encoding directions (Fig. 2). As expected, the spatial-resolution insert demonstrates that spatial resolution primarily depends on the size of the acquired pixels, and that it varies along the readout and phase-encoding direction when the acquired pixel is anisotropic (Fig. 2b, e, 2h). This interpretation is further supported by intensity profiles (Fig. 2a-c). The results demonstrate that reconstructed pixel sizes does not accurately reflect the actual spatial resolution in MRI.

Signal-to-noise ratio measurements were performed to assess the effects of pixel size and deep learning reconstruction (DLR) on image quality (Fig. 2d-i). Results showed that SNR increased with larger pixels sizes, regardless of DLR application. We also observed that DLR significantly increases the SNR (by a factor of 1.6-1.9) (Fig. 2d-f vs. 2g-i). Intensity profile analysis of the resolution insert further suggests that DLR enhances spatial resolution (Fig. 2f vs. 2i).

In the sagittal sectional phantom, a cavity filled with a high concentration of gadolinium contrast agent was used to simulate the signal void associated with metallic implants (Fig. 3). The orientation of the metallic artefact follows the readout gradient direction (Fig. 3c and d). Additionally, an increase in the readout bandwidth led to a reduction in deformations (Fig. 3c and d). This phantom also allows for observation of the chemical shift artefact at water-fat TMM interfaces along the readout axis (Fig. 3a and b).

<table><caption>**Table 2**
MRI sequence parameters.</caption><thead><tr><th>MRI system</th><th colspan="2">0.55T, MAGNETOM Free.Max, Siemens Healthineers</th></tr></thead><tbody><tr><td>Contrast</td><td>T1<sub>w</sub></td><td>PD<sub>w</sub> + Fat saturation</td></tr><tr><td>Sequence</td><td>Turbo Spin echo 2D</td><td>Turbo Spin echo 2D + fat saturation</td></tr><tr><td>Echo train length</td><td>3</td><td>7</td></tr><tr><td>TR/TE</td><td>450 ms/13 ms</td><td>3630 ms/34 ms</td></tr><tr><td>Flip angle</td><td>90°</td><td>90°</td></tr><tr><td>Number of average</td><td>3</td><td></td></tr><tr><td>FOV</td><td>140 mm × 140 mm</td><td></td></tr><tr><td>Slice thickness</td><td>3 mm</td><td></td></tr><tr><td>Native matrix (phase x freq.)</td><td>128 × 128</td><td>256 × 256</td></tr><tr><td>Native pixel size (phase x freq.)</td><td>1.1 mm × 1.1 mm</td><td>0.55 × 0.55 mm</td></tr><tr><td>Reconstructed matrix</td><td>256 × 256</td><td>512 × 512</td></tr><tr><td>Reconstructed pixel size</td><td>0.55 × 0.55 mm</td><td>0.27 × 0.27 mm</td></tr></tbody></table>
<figure><img src="image_5.png" /><figcaption>**Figure 2.** T1w and PD<sub>w</sub>-FS images of the transverse knee phantom acquired with three different pixel sizes. Effective spatial resolution is assessed by observing the pattern within the spatial-resolution insert, depending on the native pixel dimensions and the phase-encoding direction (white arrow). T1<sub>w</sub> images are shown without (d–f) and with (g–i) deep learning reconstruction (DLR). Intensity profiles from images a–c reveal the 0.6 mm alternating line patterns in both the phase (orange box) and frequency (blue box) encoding directions. Profiles from images f and i quantify the contribution of DLR to spatial resolution: the amplitude of alternating lines is greater with DLR (1051) than without (414). Regions of interest (ROIs) positioned on the lateral femoral condyle in images d–i demonstrate that SNR increases with both larger pixel sizes and DLR application. These findings are consistent with known MRI principles and will require further validation through extended theoretical and experimental studies. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)</figcaption></figure>

Fig. 4 highlights the anatomical realism of the phantom design. Across both sagittal and coronal planes, approximately 20 distinct anatomical structures were visually identifiable.

All results presented correspond to preliminary data and will be further investigated in dedicated follow-up studies beyond the scope of this paper.

Discussion

Anatomical realism and spatial resolution evaluation

The developed phantoms demonstrated a high degree of anatomical realism, with numerous visually identifiable structures
<figure><img src="image_6.png" /><figcaption>**Figure 3.** T1w (a, b) and PDw-FS (c, d) images of the sagittal knee phantom. The orientation of the metallic artefact follows the readout gradient direction and decreases with smaller native pixel sizes (a, b) and increased readout bandwidth (BW) (c, d). The magnified areas framed in blue (c, d) illustrate artefact reduction when BW is increased from 150 Hz/pixel to 500 Hz/pixel (corresponding to a decrease in distortion from 13.3 mm to 10.3 mm). This phantom also reveals the presence of the chemical shift artefact at water-fat interfaces along both the frequency encoding axis (a, b) and the readout axis (a vs. b). The magnified areas framed in orange (a, b) highlight this artefact using intensity profiles: the walls at the water-fat interfaces are clearly visible in image b but are no longer distinguishable in image a due to chemical shift displacement along the readout axis. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>**Figure 4.** Anatomical labelling of the knee sectional MRI phantoms in T1w at 0.55T.</figcaption></figure>
corresponding to key anatomical landmarks routinely assessed in clinical knee MRI (Fig. 4). Although 0.4 mm separation walls are present between different anatomical structures and tissues, they do not hinder anatomical analysis. To our knowledge, this work presents the first MRI-dedicated knee phantoms with such anatomical fidelity reported in the literature to date. The design and resolution achieved through our 3D printing workflow proved sufficient to reproduce detailed and anatomically distinguishable features (Fig. 4), supporting the suitability of the approach for musculoskeletal imaging research and education.

A spatial resolution insert was used to objectively assess the spatial resolution of our acquisitions in both the phase and frequency encoding directions (Fig. 2). However, in this study we were limited to a test pattern with 0.6 mm alternations, whereas most knee MRI sequences use smaller pixel sizes, limiting this test pattern. In future work, it would be worthwhile to consider using higher-resolution test patterns such as 0.4 mm or 0.3 mm, or patterns with two alternating values (e.g., 0.4 mm and 0.6 mm per quadrant pair), to enable a more detailed spatial resolution analysis.

## Contrast fidelity

The TMM used in this study provided MRI signal weighting consistent with clinical expectations, producing relative contrasts that aligned well with standard T1<sub>w</sub> and PD<sub>w</sub> sequences (Figs. 2–4). While relative contrasts appeared visually realistic (water < muscle < fat in T1<sub>w</sub>; water > muscle > fat in PD<sub>w</sub>-FS), the relaxation properties of the gels were not specifically designed to match those of biological tissues (see Methods - Tissue-Mimicking Materials). Future efforts will aim to identify and characterize TMM formulations that yield relaxation times closer to in vivo values¹⁸ and demonstrate long-term temporal stability (see phantom stability below). Additionally, tissues with very short T2 values, such as tendons, ligaments, and cortical bone, were represented using unmodified PETG, which yields no signal under standard MRI sequences. While this approach produced the desired hyposignal appearance and supported relative contrast simulation, it is not sufficient for replicating true tissue-like properties. Finally, using ultrasound gel to simulate synovial fluid proved challenging due to its high viscosity, which made it difficult to fill small cavities without air bubbles. A potential solution is to gently heat the gel prior to filling, thereby reducing its viscosity and improving flow into narrow anatomical structures.

Although the current phantom demonstrates promising contrast fidelity for soft tissues, the development of TMM with both realistic relative contrast and quantitatively accurate relaxation times remains a key area for future improvement.

## Phantom stability

Phantom modules were stored under refrigeration at 4 °C, and MRI acquisitions were conducted four days after gel preparation and filling. While the materials remained stable in the short term, visual signs of dehydration, including partial detachment of the hydrogels from the surrounding walls, became evident after approximately two weeks in our first trials. This preliminary observation highlights the importance of designing hermetically sealed phantom structures to prevent gel exposure to air and minimize degradation over time.

One potential solution to the degradation problem is to seal the phantom with a thin-layer of epoxy resin to maintain humidity and structural integrity. This approach was tested by sealing the transverse phantom with a 5 mm-thick epoxy resin layer. Six months later, the sealed phantom showed no visible signs of

degradation, as documented in Supplementary Material 2. This analysis is ongoing and will be part of a broader study exploring additional solutions, such as the use of preservatives²⁰ or vacuum packaging.

## Potential uses of these phantoms

Although further improvements are required, particularly in enhancing gel stability and improving tissue-specific relaxometry, our initial results demonstrate the potential of these phantoms across several domains:

### - Educational use

These phantoms offer significant value as hands-on teaching tools in radiography and MRI education. They can be used for anatomical training in musculoskeletal imaging (Fig. 5); contrast recognition across T1<sub>w</sub>, T2<sub>w</sub>, PD<sub>w</sub>, and fat-suppressed sequences (Figs. 1–5); assessment of sequence parameters and their effects on spatial resolution (Fig. 2); and image quality analysis, including, artefacts evaluation (Figs. 2 and 3) at different magnetic field strengths (Fig. 5). Formal educational assessments using student cohorts have not yet been conducted; future studies will be needed to assess the educational utility of the phantom.

### - Sequences optimization and hardware comparisons.

These phantoms enable various comparisons to be made, including:

* Comparisons of field strength (Fig. 5a) and hardware design, such as between different coil types (e.g., birdcage vs multi-channel phased array coils);

* Optimization of MRI sequence parameters under controlled conditions, such as comparing fat suppression methods (Fig. 5c) or evaluating metal artefact reduction techniques (Fig. 5b);

* Evaluation of reconstruction algorithms, including comparisons between conventional and deep learning-based techniques (Fig. 2d–f vs 2g-i);

### - Ethics.

Using phantoms as a first-line testing platform provides both ethical and methodological advantages. From an ethical standpoint, it provides an alternative to primarily testing unvalidated sequences on animals, healthy volunteers, or patients. From a methodological standpoint, this approach ensures that all comparisons are performed on the same anatomical and physical model, thereby improving reproducibility and reducing confounding factors. This approach enhances the safety, efficiency, and robustness of both educational and research-oriented MRI workflows.

## Limits and perspectives

Although our results approximate realistic morphology and MRI contrast, they do not yet meet the comprehensive criteria of a "super-phantom" as conceptualized by Manohar et al.,¹ which includes functional imaging properties and dynamic biomarker simulation. This work presents preliminary results that open promising avenues but also involves several limitations.

First, acquisitions were performed on a single 0.55 T MRI system, which does not correspond to the standard clinical field strengths of 1.5 T and 3 T. The 0.55 T system was used for practical reasons; it is available for research purposes and provides privileged access without the organizational constraints associated
<figure><img src="image_8.png" /><figcaption>**Figure 5.** Panels a–c illustrate preliminary results highlighting potential research applications of the phantom. Fig. 5a presents images acquired at different magnetic field strengths (0.31 T, 0.55 T, 1.5 T, and 3 T) using various MRI systems. Fig. 5b compares two metal artefact reduction techniques—VAT and SEMAC—at 1.5 T. Fig. 5c compares two fat-suppression methods, SPAIR and STIR, also at 1.5 T. All images correspond to early-stage results from specific research projects that extend beyond the scope of this article.</figcaption></figure>

with patient flow. Subsequent investigations will extend evaluations to other MRI systems, particularly those operating at the more common magnetic fields of 1.5 and 3T. Preliminary results are shown in Fig. 5a. Such evaluations will support cross-platform comparisons and magnetic field-dependent performance assessments.

Future studies would also benefit from comparison with established phantoms, such as the ACR¹⁴ phantom, in order to rigorously evaluate the added value of our morphologically realistic approach.

Additionally, this first iteration was limited to phantoms representing normal anatomical structures of the knee. We focused on the knee joint because it is typically the first region studied by radiography students during MRI training. Another reason for this choice is the lower manufacturing complexity of this anatomical region, both in terms of morphology and TMM, compared to more complex areas such as the brain. Furthermore, the MRI sequences used in MSK imaging are less varied than those used in MR-neuroimaging (e.g. FLAIR, DIR, SWI, DWI, etc.) which simplified the technical specifications. Once TMM design is further optimized, there is considerable potential to simulate pathological conditions, ranging from simple lesions (e.g., meniscal tears) to more complex signal abnormalities (e.g., bone marrow edema). Future efforts will aim to evaluate this and identify gel compositions that yield relaxation times close to in vivo values,¹⁸ enabling the testing of quantitative MRI sequences (e.g., T1 and T2 mapping).

Importantly, the growing accessibility and affordability of 3D printing technologies further supports extending this design approach to other anatomical regions (e.g. hip, spine), thereby broadening the range of phantom applications. These preliminary results suggest that this type of phantom could be integrated into clinical practice to evaluate sequence programming and evaluate new technical options or equipment prior to clinical implementation. This would represent a valuable asset for strengthening evidence-based practice²¹ and encouraging MRI users to initiate

research projects. However, further investigations targeting specific use cases, including comparative studies across anatomical regions or imaging systems, protocol optimization, and pedagogical applications are necessary to rigorously validate the added value of this phantom framework.

## Conclusion

To our knowledge, this study presents the first MRI phantoms dedicated to the musculoskeletal system, with a focus on the knee joint, combining anatomically realistic morphology with clinically relevant contrast properties. However, achieving the full vision of an MRI super-phantom remains a complex challenge that has not yet been attained in this study. Key areas for further development include the refinement of tissue-mimicking material formulations,¹⁸ improved phantom stability, and scalable 3D modelling approaches. This work provides a foundational framework in that direction and lays the groundwork for future advancements in reproducible, ethical, and high-impact phantom-based MRI research. The preliminary results presented here highlight the promise of such phantoms in education, clinical evaluation, and research innovation, and lay the foundation for future multidisciplinary investigations.

## Ethics approval

Not applicable: Phantom study.

## Availability of data

Data required for this study may be made available by the corresponding author upon reasonable request.

## Author contributions

H. Yusuff: HY.
T. Willaume: **TW**.

E. Breton: **EB**.

G. Bierry: **GB**.

J.-P. Dillenseger: **JPD**.

(1) conception and design, or acquisition of data, or analysis and interpretation of data, **HY, TW, EB, JPD**

(2) drafting the article or revising it critically for important intellectual content, **HY, GB, TW, EB, JPD**

(3) final approval of the version to be published, **JPD**

(4) agree to be accountable for all aspects of the work if questions arise related to its accuracy or integrity. **JPD**

**Declaration of generative AI and AI-assisted technologies in the writing process**

The authors used ChatGPT-4 (OpenAI) to improve the clarity and fluency of the English language during the writing of this manuscript. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.

**Funding**

IHU Strasbourg - Institute of Image Guided Surgery, ANR-10-IAHU-0002.

IdEx Unistra, ANR-10-IDEX-0002.

SFRI - STRAT'US, ANR-20-SFRI-0012.

**Declaration of interests**

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

**Acknowledgements**

This work of the Interdisciplinary Thematic Institute Health-Tech, as part of the ITI 2021-2028 program of the University of Strasbourg, CNRS and Inserm, was supported by IdEx Unistra (ANR-10-IDEX-0002) and SFRI (STRAT'US project, ANR-20-SFRI-0012) under the framework of the French Investments for the Future Program. This work has benefitted from funding of the IHU Strasbourg (Institute of Image Guided Surgery, ANR-10-IAHU-0002).

**Appendix A. Supplementary data**

Supplementary data to this article can be found online at https://doi.org/10.1016/j.radi.2025.103195.

**References**

1. Manohar S, Sechopoulos I, Anastasio MA, Maier-Hein L, Gupta R. Super phantoms: advanced models for testing medical imaging technologies. *Commun Eng.* 2024;3(1):73. https://doi.org/10.1038/s44172-024-00218-z.

2. Kilian D, Kilian W, Troia A, Itterlann B, Zilberti L, Gelinsky M. 3D extrusion printing of biphasic anthropomorphic brain phantoms mimicking MR relaxation times based on alginate-agarose-carrageenan blends. *ACS Appl Mater Interfaces*. 2022. https://doi.org/10.1021/acsmami.2c12872.

3. Kraft M, Ryger S, Berman BP, Downs ME, Jordanova KV, Poorman ME, et al. Towards a barrier-free anthropomorphic brain phantom for quantitative magnetic resonance imaging: Design, first construction attempt, and challenges. *PLoS One*. 2023. https://doi.org/10.1371/journal.pone.0285432.

4. Gopalan K, Tamir JI, Arias AC, Lustig M. Quantitative anatomy mimicking slice phantoms. *Magn Reson Med*. 2021. https://doi.org/10.1002/mrm.28740.

5. Crasto N, Kirubarajan A, Sussman D. Anthropomorphic brain phantoms for use in MRI systems: a systematic review. *Magn Reson Mater Phy*. 2022. https://doi.org/10.1007/s10334-021-00953-w.

6. Meerbothe TG, Florczak S, Van den Berg CAT, Levato R, Mandija S. A reusable 3D printed brain-like phantom for benchmarking electrical properties tomography reconstructions. *Magn Reson Med*. 2024. https://doi.org/10.1002/mrm.30189.

7. Habeeb Y, Zorn PE, Blindauer F, Kharouf N, Sémeril D, Bierry G, et al. High-fidelity anatomical phantoms for MRI practical training. *Phys Med*. 2024;127:104832. https://doi.org/10.1016/j.ejmp.2024.104832.

8. Sultan KS, Mohammed B, Mills PC, Abbosh A. Anthropomorphic durable realistic knee phantom for testing electromagnetic imaging systems. *IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology*. 2020;5(2):132–138.

9. Yusuff H, Zorn PE, Giraudeau C, Wach B, Choquet P, Chatelin S, et al. Development of a cost-effective 3D-printed MRI phantom for enhanced teaching of system performance and image quality concepts. *Magn Reson Mater Phy*. 2024;1–14. https://doi.org/10.1007/s10334-024-01217-z.

10. McGarry CK, Grattan LJ, Ivory AM, Leek F, Liney GP, Liu Y, et al. Tissue mimicking materials for imaging and therapy phantoms: a review. *Phys Med Biol*. 2020. https://doi.org/10.1088/1361-6560/abb1d7.

11. Antoniou A, Damianou C. MR relaxation properties of tissue-mimicking phantoms. *Ultrasonics*. 2022. https://doi.org/10.1016/j.ultras.2021.106600.

12. Antoniou A, Georgiou L, Christodoulou T, Panayiotou N, Ioannides C, Zamboglou N, et al. MR relaxation times of agar-based tissue-mimicking phantoms. *J Appl Clin Med Phys*. 2022. https://doi.org/10.1002/acm2.13533.

13. Woletz M, Roat S, Hummer A, Tik M, Windischberger C. Human tissue-equivalent MRI phantom preparation for 3 and 7 Tesla. *Med Phys*. 2021. https://doi.org/10.1002/mp.14986.

14. Kato H, Kuroda M, Yoshimura K, Yoshida A, Hanamoto K, Kawasaki S, et al. Composition of MRI phantom equivalent to human tissues. *Med Phys*. 2005. https://doi.org/10.1118/1.4790023.

15. Chen CC, Wan YL, Wai YY, Liu HL. Quality assurance of clinical MRI scanners using ACR MRI phantom: preliminary results. *J Digit Imag*. 2004. https://doi.org/10.1007/s10278-004-1023-5.

16. Chatelin S, Breton E, Arulrajah A, Giraudeau C, Wach B, Meylheuc L, et al. Investigation of polyvinyl chloride plastisol tissue-mimicking phantoms for MR and ultrasound-elastography. *Front Physiol*. 2020;8:577358.

17. Kim MJ, Lee SR, Song KH, Baek HM, Choe BY, Suh TS. Development of a hybrid magnetic resonance/computed tomography-compatible phantom for magnetic resonance guided radiotherapy. *J Radiat Res*. 2020 Mar;61(2):314–324.

18. Drake-Pérez M, Delattre BMA, Boto J, Fitsiori A, Lovblad KO, Boudabbous S, et al. Normal values of magnetic relaxation parameters of spine components with the synthetic MRI sequence. *Am J Neuroradiol*. 2018. https://doi.org/10.3174/ajnr.A5566.

19. Hattori K, Ikemoto Y, Takao W, Ohno S, Harimoto T, Kanazawa S, et al. Development of MRI phantom equivalent to human tissues for 3.0-T MRI. *Med phys*. 2013. https://doi.org/10.1118/1.2047807.

20. Yusuff H, Chatelin C, Dillenseger JP. Narrative review of tissue-mimicking materials for MRI phantoms: composition, fabrication, and relaxation properties. *Radiography*. 2024. https://doi.org/10.1016/j.radi.2024.09.063.

21. Al Balushi H, Watts H, Akudjedu TN. Research and evidence-based practice in clinical radiography: a systematic review of barriers and recommendations for a new direction. *Radiography*. 2024. https://doi.org/10.1016/j.radi.2024.01.012.