Fine structural human phantom in dentistry and instance tooth segmentation.

In this study, we present the development of a fine structural human phantom designed specifically for applications in dentistry. This research focused on assessing the viability of applying medical computer vision techniques to the task of segmenting individual teeth within a phantom. Using a virtual cone-beam computed tomography (CBCT) system, we generated over 170,000 training datasets. These datasets were produced by varying the elemental densities and tooth sizes within the human phantom, as well as varying the X-ray spectrum, noise intensity, and projection cutoff intensity in the virtual CBCT system. The deep-learning (DL) based tooth segmentation model was trained using the generated datasets. The results demonstrate an agreement with manual contouring when applied to clinical CBCT data. Specifically, the Dice similarity coefficient exceeded 0.87, indicating the robust performance of the developed segmentation model even when virtual imaging was used. The present results show the practical utility of virtual imaging techniques in dentistry and highlight the potential of medical computer vision for enhancing precision and efficiency in dental imaging processes.

Augmented-reality-based surgical navigation for endoscope retrograde cholangiopancreatography: A phantom study.

BACKGROUND: Endoscope retrograde cholangiopancreatography is a standard surgical treatment for gallbladder and pancreatic diseases. However, surgeons is at high risk and require sufficient surgical experience and skills. METHODS: (1) The simultaneous localisation and mapping technique to reconstruct the surgical environment. (2) The preoperative 3D model is transformed into the intraoperative video environment to implement the multi-modal fusion. (3) A framework for virtual-to-real projection based on hand-eye alignment. For the purpose of projecting the 3D model onto the imaging plane of the camera, it uses position data from electromagnetic sensors. RESULTS: Our AR-assisted navigation system can accurately guide physicians, which means a distance of registration error to be restricted to under 5 mm and a projection error of 5.76 ± 2.13, and the intubation procedure is done at 30 frames per second. CONCLUSIONS: Coupled with clinical validation and user studies, both the quantitative and qualitative results indicate that our navigation system has the potential to be highly useful in clinical practice.

Comprehensive framework of GPU-accelerated image reconstruction for photoacoustic computed tomography.

Significance: Photoacoustic computed tomography (PACT) is a promising non-invasive imaging technique for both life science and clinical implementations. To achieve fast imaging speed, modern PACT systems have equipped arrays that have hundreds to thousands of ultrasound transducer (UST) elements, and the element number continues to increase. However, large number of UST elements with parallel data acquisition could generate a massive data size, making it very challenging to realize fast image reconstruction. Although several research groups have developed GPU-accelerated method for PACT, there lacks an explicit and feasible step-by-step description of GPU-based algorithms for various hardware platforms. Aim: In this study, we propose a comprehensive framework for developing GPU-accelerated PACT image reconstruction (GPU-accelerated photoacoustic computed tomography), to help the research community to grasp this advanced image reconstruction method. Approach: We leverage widely accessible open-source parallel computing tools, including Python multiprocessing-based parallelism, Taichi Lang for Python, CUDA, and possible other backends. We demonstrate that our framework promotes significant performance of PACT reconstruction, enabling faster analysis and real-time applications. Besides, we also described how to realize parallel computing on various hardware configurations, including multicore CPU, single GPU, and multiple GPUs platform. Results: Notably, our framework can achieve an effective rate of ∼ 871 times when reconstructing extremely large-scale three-dimensional PACT images on a dual-GPU platform compared to a 24-core workstation CPU. In this paper, we share example codes via GitHub. Conclusions: Our approach allows for easy adoption and adaptation by the research community, fostering implementations of PACT for both life science and medicine.

The impact of the combat method on radiomics feature compensation and analysis of scanners from different manufacturers.

BACKGROUND: This study investigated whether the Combat compensation method can remove the variability of radiomic features extracted from different scanners, while also examining its impact on the subsequent predictive performance of machine learning models. MATERIALS AND METHODS: 135 CT images of Credence Cartridge Radiomic phantoms were collected and screened from three scanners manufactured by Siemens, Philips, and GE. 100 radiomic features were extracted and 20 radiomic features were screened according to the Lasso regression method. The radiomic features extracted from the rubber and resin-filled regions in the cartridges were labeled into different categories for evaluating the performance of the machine learning model. Radiomics features were divided into three groups based on the different scanner manufacturers. The radiomic features were randomly divided into training and test sets with a ratio of 8:2. Five machine learning models (lasso, logistic regression, random forest, support vector machine, neural network) were employed to evaluate the impact of Combat on radiomic features. The variability among radiomic features were assessed using analysis of variance (ANOVA) and principal component analysis (PCA). Accuracy, precision, recall, and area under the receiver curve (AUC) were used as evaluation metrics for model classification. RESULTS: The principal component and ANOVA analysis results show that the variability of different scanner manufacturers in radiomic features was removed (P˃0.05). After harmonization with the Combat algorithm, the distributions of radiomic features were aligned in terms of location and scale. The performance of machine learning models for classification improved, with the Random Forest model showing the most significant enhancement. The AUC value increased from 0.88 to 0.92. CONCLUSIONS: The Combat algorithm has reduced variability in radiomic features from different scanners. In the phantom CT dataset, it appears that the machine learning model's classification performance may have improved after Combat harmonization. However, further investigation and validation are required to fully comprehend Combat's impact on radiomic features in medical imaging.

Flexural pulse wave velocity in blood vessels.

Arteriosclerosis is a major risk factor for cardiovascular disease and results in arterial vessel stiffening. Velocity estimation of the pulse wave sent by the heart and propagating into the arteries is a widely accepted biomarker. This symmetrical pulse wave propagates at a speed which is related to the Young's modulus through the Moens Korteweg (MK) equation. Recently, an antisymmetric flexural wave has been observed in vivo. Unlike the symmetrical wave, it is highly dispersive. This property offers promising applications for monitoring arterial stiffness and early detection of atheromatous plaque. However, as far as it is known, no equivalent of the MK equation exists for flexural pulse waves. To bridge this gap, a beam based theory was developed, and approximate analytical solutions were reached. An experiment in soft polymer artery phantoms was built to observe the dispersion of flexural waves. A good agreement was found between the analytical expression derived from beam theory and experiments. Moreover, numerical simulations validated wave speed dependence on the elastic and geometric parameters at low frequencies. Clinical applications, such as arterial age estimation and arterial pressure measurement, are foreseen.

Imperfect refractive index matching in scanning laser optical tomography and a method for digital correction.

Significance: Scanning laser optical tomography (SLOT) is a volumetric multi-modal imaging technique that is comparable to optical projection tomography and computer tomography. Image quality is crucially dependent on matching the refractive indexes (RIs) of the sample and surrounding medium, but RI matching often requires some effort and is never perfect. Aim: Reducing the burden of RI matching between the immersion medium and sample in biomedical imaging is a challenging and interesting task. We aim at implementing a post processing strategy for correcting SLOT measurements that have errors caused by RI mismatch. Approach: To better understand the problems with poorly matched Ris, simulated SLOT measurements with imperfect RI matching of the sample and medium are performed and presented here. A method to correct distorted measurements was developed and is presented and evaluated. This method is then applied to a sample containing fluorescent polystyrene beads and a sample made of olydimethylsiloxane with embedded fluorescent nanoparticles. Results: From the simulations, it is evident that measurements with an RI mismatch larger than 0.02 and no correction yield considerably worse results compared to perfectly matched measurements. RI mismatches larger than 0.05 make it almost impossible to resolve finer details and structures. By contrast, the simulations imply that a measurement with an RI mismatch of up to 0.1 can still yield reasonable results if the presented correction method is applied. The experiments validate the simulated results for an RI mismatch of about 0.09. Conclusions: The method significantly improves the SLOT image quality for samples with imperfectly matched Ris. Although the absolutely best imaging quality will be achieved with perfect RI matching, these results pave the way for imaging in SLOT with RI mismatches while maintaining high image quality.

Impact of deep learning image reconstruction on volumetric accuracy and image quality of pulmonary nodules with different morphologies in low-dose CT.

BACKGROUND: This study systematically compares the impact of innovative deep learning image reconstruction (DLIR, TrueFidelity) to conventionally used iterative reconstruction (IR) on nodule volumetry and subjective image quality (IQ) at highly reduced radiation doses. This is essential in the context of low-dose CT lung cancer screening where accurate volumetry and characterization of pulmonary nodules in repeated CT scanning are indispensable. MATERIALS AND METHODS: A standardized CT dataset was established using an anthropomorphic chest phantom (Lungman, Kyoto Kaguku Inc., Kyoto, Japan) containing a set of 3D-printed lung nodules including six diameters (4 to 9 mm) and three morphology classes (lobular, spiculated, smooth), with an established ground truth. Images were acquired at varying radiation doses (6.04, 3.03, 1.54, 0.77, 0.41 and 0.20 mGy) and reconstructed with combinations of reconstruction kernels (soft and hard kernel) and reconstruction algorithms (ASIR-V and DLIR at low, medium and high strength). Semi-automatic volumetry measurements and subjective image quality scores recorded by five radiologists were analyzed with multiple linear regression and mixed-effect ordinal logistic regression models. RESULTS: Volumetric errors of nodules imaged with DLIR are up to 50% lower compared to ASIR-V, especially at radiation doses below 1 mGy and when reconstructed with a hard kernel. Also, across all nodule diameters and morphologies, volumetric errors are commonly lower with DLIR. Furthermore, DLIR renders higher subjective IQ, especially at the sub-mGy doses. Radiologists were up to nine times more likely to score the highest IQ-score to these images compared to those reconstructed with ASIR-V. Lung nodules with irregular margins and small diameters also had an increased likelihood (up to five times more likely) to be ascribed the best IQ scores when reconstructed with DLIR. CONCLUSION: We observed that DLIR performs as good as or even outperforms conventionally used reconstruction algorithms in terms of volumetric accuracy and subjective IQ of nodules in an anthropomorphic chest phantom. As such, DLIR potentially allows to lower the radiation dose to participants of lung cancer screening without compromising accurate measurement and characterization of lung nodules.

Imaging performance of portable and conventional ultrasound imaging technologies for ophthalmic applications.

PURPOSE: The aim of this study was to evaluate the imaging capabilities of Butterfly iQ with conventional ophthalmic (piezoelectric) ultrasound (COU) for ophthalmic imaging. METHODS: Custom phantom molds were designed and imaged with Butterfly iQ and COU to compare spatial resolution capabilities. To evaluate the clinical imaging performance of Butterfly iQ and COU, a survey containing pathological conditions from human subjects, imaged with both Butterfly iQ and COU probes, was given to three retina specialists and graded on image detail, resolution, quality, and diagnostic confidence on a ten-point Likert scale. Kruskal-Wallis analysis was performed for survey responses. RESULTS: Butterfly iQ and COU had comparable capabilities for imaging small axial and lateral phantom features (down to 0.1 mm) of high and low acoustic reflectivity. One of three retina specialists demonstrated a statistically significant preference for COU related to resolution, detail, and diagnostic confidence, but the remaining graders showed no significant preference for Butterfly iQ or COU across all sample images presented. CONCLUSION: The emergence of portable ultrasound probes offers an affordable alternative to COU technologies with comparable qualitative imaging resolution down to 0.1 mm. These findings suggest the value to further study the use of portable ultrasound systems and their utility in routine eye care.

Non-telecentric photoacoustic microscopy for multi-scale imaging.

Optical-resolution photoacoustic microscopy (OR-PAM) excels in precisely imaging a biological tissue based on absorption contrast. However, existing OR-PAMs are confined by fixed compromises between spatial resolution and field of view (FOV), preventing the integration of large FOV and local high-resolution within one system. Here, we present a non-telecentric OR-PAM (nTC-PAM) that empowers efficient adaptation of FOV and spatial resolution to match the multi-scale requirement of diverse biological imaging. Our method allows for a large-scale transformation in FOV and even surpassing the nominal FOV of the objective with minimal marginal degradation of the lateral resolution. We demonstrate the advantage of nTC-PAM through multi-scale imaging of the leaf phantom, mouse ear, and cortex. The results reveal that nTC-PAM can switch the FOV and spatial resolution to meet the requirements of different biological tissues, such as large-scale imaging of the whole cerebral cortex and high-resolution imaging of microvascular structures in local brain regions.

Optical coherence elastography under homolateral parallel acoustic radiation force excitation for ocular elasticity quantification.

Alteration in the elastic properties of biological tissues may indicate changes in the structure and components. Acoustic radiation force optical coherence elastography (ARF-OCE) can assess the elastic properties of the ocular tissues non-invasively. However, coupling the ultrasound beam and the optical beam remains challenging. In this Letter, we proposed an OCE method incorporating homolateral parallel ARF excitation for measuring the elasticity of the ocular tissues. An acoustic-optic coupling unit was established to reflect the ultrasound beam while transmitting the light beam. The ARF excited the ocular tissue in the direction parallel to the light beam from the same side of the light beam. We demonstrated the method on the agar phantoms, the porcine cornea, and the porcine retina. The results show that the ARF-OCE method can measure the elasticity of the cornea and the retina, resulting in higher detection sensitivity and a more extensive scanning range.

A modular motion compensation pipeline for prospective respiratory motion correction of multi-nuclear MR spectroscopy.

Magnetic resonance (MR) acquisitions of the torso are frequently affected by respiratory motion with detrimental effects on signal quality. The motion of organs inside the body is typically decoupled from surface motion and is best captured using rapid MR imaging (MRI). We propose a pipeline for prospective motion correction of the target organ using MR image navigators providing absolute motion estimates in millimeters. Our method is designed to feature multi-nuclear interleaving for non-proton MR acquisitions and to tolerate local transmit coils with inhomogeneous field and sensitivity distributions. OpenCV object tracking was introduced for rapid estimation of in-plane displacements in 2D MR images. A full three-dimensional translation vector was derived by combining displacements from slices of multiple and arbitrary orientations. The pipeline was implemented on 3 T and 7 T MR scanners and tested in phantoms and volunteers. Fast motion handling was achieved with low-resolution 2D MR image navigators and direct implementation of OpenCV into the MR scanner's reconstruction pipeline. Motion-phantom measurements demonstrate high tracking precision and accuracy with minor processing latency. The feasibility of the pipeline for reliable in-vivo motion extraction was shown on heart and kidney data. Organ motion was manually assessed by independent operators to quantify tracking performance. Object tracking performed convincingly on 7774 navigator images from phantom scans and different organs in volunteers. In particular the kernelized correlation filter (KCF) achieved similar accuracy (74%) as scored from inter-operator comparison (82%) while processing at a rate of over 100 frames per second. We conclude that fast 2D MR navigator images and computer vision object tracking can be used for accurate and rapid prospective motion correction. This and the modular structure of the pipeline allows for the proposed method to be used in imaging of moving organs and in challenging applications like cardiac magnetic resonance spectroscopy (MRS) or magnetic resonance imaging (MRI) guided radiotherapy.

Thermoluminescence dosimetry (TLD) in a 3 T magnetic resonance imaging (MRI) environment: implications for personnel exposure monitoring.

Thermoluminescent dosimeters (TLDs) serve as compact and user-friendly tools for various applications, including personal radiation dosimetry and radiation therapy. This study explores the potential of utilizing TLD-100 personal dosimetry, conventionally applied in PET/CT (positron emission tomography/computed tomography) settings, in the PET/MRI (magnetic resonance imaging) environment. The integration of MRI into conventional radiotherapy and PET systems necessitates ionizing radiation dosimetry in the presence of static magnetic fields. In this study, TLD-100 dosimeters were exposed on the surface of a water-filled cylindrical phantom containing PET-radioisotope and positioned on the patient table of a 3 T PET/MRI, where the magnetic field strength is around 0.2 T, aiming to replicate real-world scenarios experienced by personnel in PET/MRI environments. Results indicate that the modified MR-safe TLD-100 personal dosimeters exhibit no significant impact from the static magnetic field of the 3 T PET/MRI, supporting their suitability for personal dosimetry in PET/MRI settings. This study addresses a notable gap in existing literature on the effect of MRI static magnetic field on TLDs.

Novice providers' success in performing lumbar puncture: a randomized controlled phantom study between a conventional spinal needle and a novel bioimpedance needle.

BACKGROUND: Lumbar puncture (LP) is an important yet difficult skill in medical practice. In recent years, the number of LPs in clinical practice has steadily decreased, which reduces residents' clinical exposure and may compromise their skills and attitude towards LP. Our study aims to assess whether the novel bioimpedance needle is of assistance to a novice provider and thus compensates for this emerging knowledge gap. METHODS: This randomized controlled study, employing a partly blinded design, involved 60 s- and third-year medical students with no prior LP experience. The students were randomly assigned to two groups consisting of 30 students each. They performed LP on an anatomical lumbar model either with the conventional spinal needle or the bioimpedance needle. Success in LP was analysed using the independent samples proportion procedure. Additionally, the usability of the needles was evaluated with pertinent questions. RESULTS: With the conventional spinal needle, 40% succeeded in performing the LP procedure, whereas with the bioimpedance needle, 90% were successful (p < 0.001). The procedures were successful at the first attempt in 5 (16.7%) and 15 (50%) cases (p = 0.006), respectively. Providers found the bioimpedance needle more useful and felt more confident using it. CONCLUSIONS: The bioimpedance needle was beneficial in training medical students since it significantly facilitated the novice provider in performing LP on a lumbar phantom. Further research is needed to show whether the observed findings translate into clinical skills and benefits in hospital settings.

RFPID: development and 3D-printing of a female physical phantom for whole-body counter.

Whole-body counters (WBC) are used in internal dosimetry forin vivomonitoring in radiation protection. The calibration processes of a WBC set-up include the measurement of a physical phantom filled with a certificate radioactive source that usually is referred to a standard set of individuals determined by the International Commission on Radiological Protection (ICRP). The aim of this study was to develop an anthropomorphic and anthropometric female physical phantom for the calibration of the WBC systems. The reference female computational phantom of the ICRP, now called RFPID (Reference Female Phantom for Internal Dosimetry) was printed using PLA filament and with an empty interior. The goal is to use the RFPID to reduce the uncertainties associated within vivomonitoring system. The images which generated the phantom were manipulated using ImageJ®, Amide®, GIMP®and the 3D Slicer®software. RFPID was split into several parts and printed using a 3D printer in order to print the whole-body phantom. The newly printed physical phantom RFPID was successfully fabricated, and it is suitable to mimic human tissue, anatomically similar to a human body i.e., size, shape, material composition, and density.

Experimental validation of the accuracy of robotic-assisted radioactive seed implantation for tumor treatment.

An experimental validation of a robotic system for radioactive iodine-125 seed implantation (RISI) in tumor treatment was conducted using customized phantom models and animal models simulating liver and lung lesions. The robotic system, consisting of planning, navigation, and implantation modules, was employed to implant dummy radioactive seeds into the models. Fiducial markers were used for target localization. In phantom experiments across 40 cases, the mean errors between planned and actual seed positions were 0.98 ± 1.05 mm, 1.14 ± 0.62 mm, and 0.90 ± 1.05 mm in the x, y, and z directions, respectively. The x, y, and z directions correspond to the left-right, anterior-posterior, and superior-inferior anatomical planes. Silicone phantoms exhibiting significantly smaller x-axis errors compared to liver and lung phantoms (p < 0.05). Template assistance significantly reduced errors in all axes (p < 0.05). No significant dosimetric deviations were observed in parameters such as D90, V100, and V150 between plans and post-implant doses (p > 0.05). In animal experiments across 23 liver and lung cases, the mean implantation errors were 1.28 ± 0.77 mm, 1.66 ± 0.69 mm, and 1.86 ± 0.93 mm in the x, y, and z directions, slightly higher than in phantoms (p < 0.05), with no significant differences between liver and lung models. The dosimetric results closely matched planned values, confirming the accuracy of the robotic system for RISI, offering new possibilities in clinical tumor treatment.

Evaluating optimal quality assurance and quality control conditions of activation measurements at the accelerator-based boron neutron capture therapy system employing a lithium target.

Evaluating neutron output is important to ensure proper dose delivery for patients in boron neutron capture therapy (BNCT). It requires efficient quality assurance (QA) and quality control (QC) while maintaining measurement accuracy. This study investigated the optimal measurement conditions for QA/QC of activation measurements using a high-purity germanium (HP-Ge) detector in an accelerator-based boron neutron capture therapy (AB-BNCT) system employing a lithium target. The QA/QC uncertainty of the activation measurement was evaluated based on counts, reproducibility, and standard radiation source uncertainties. Measurements in a polymethyl methacrylate (PMMA) cylindrical phantom using aluminum-manganese (Al-Mn) foils and aluminum-gold (Al-Au) foils and measurements in a water phantom using gold wire with and without cadmium cover were performed to determine the optimal measurement conditions. The QA/QC uncertainties of the activation measurements were 4.5% for Au and 4.6% for Mn. The optimum irradiation proton charge and measurement time were determined to be 36 C and 900 s for measurements in a PMMA cylindrical phantom, 7.0 C and 900 s for gold wire measurements in a water phantom, and 54 C and 900 s at 0-2.2 cm depth and 3,600 s at deeper depths for gold wire measurements with cadmium cover. Our results serve as a reference for determining measurement conditions when performing QA/QC of activation measurements using HP-Ge detectors at an AB-BNCT employing a lithium target.

Surface dielectric resonator for in vivo EPR measurements.

This research report describes a novel surface dielectric resonator (SDR) with a flexible connector for in vivo electron paramagnetic resonance (EPR) spectroscopy. Contrary to the conventional cavity or surface loop-gap resonators, the newly developed SDR is constructed from a ceramic dielectric material, and it is tuned to operate at the L-band frequency band (1.15 GHz) in continuous-wave mode. The SDR is designed to be critically coupled and capable of working with both very lossy samples, such as biological tissues, and non-lossy materials. The SDR was characterized using electromagnetic field simulations, assessed for sensitivity with a B1 field-perturbation method, and validated with tissue phantoms using EPR measurements. The results showed remarkably higher sensitivity in lossy tissue phantoms than the previously reported multisegment surface-loop resonators. The new SDR can provide potential new insights for advancements in the application of in vivo EPR spectroscopy for biological measurements, including clinical oximetry.

Effects of phantom microstructure on their optical properties.

Significance: Developing stable, robust, and affordable tissue-mimicking phantoms is a prerequisite for any new clinical application within biomedical optics. To this end, a thorough understanding of the phantom structure and optical properties is paramount. Aim: We characterized the structural and optical properties of PlatSil SiliGlass phantoms using experimental and numerical approaches to examine the effects of phantom microstructure on their overall optical properties. Approach: We employed scanning electron microscope (SEM), hyperspectral imaging (HSI), and spectroscopy in combination with Mie theory modeling and inverse Monte Carlo to investigate the relationship between phantom constituent and overall phantom optical properties. Results: SEM revealed that microspheres had a broad range of sizes with average (13.47±5.98) µm and were also aggregated, which may affect overall optical properties and warrants careful preparation to minimize these effects. Spectroscopy was used to measure pigment and SiliGlass absorption coefficient in the VIS-NIR range. Size distribution was used to calculate scattering coefficients and observe the impact of phantom microstructure on scattering properties. The results were surmised in an inverse problem solution that enabled absolute determination of component volume fractions that agree with values obtained during preparation and explained experimentally observed spectral features. HSI microscopy revealed pronounced single-scattering effects that agree with single-scattering events. Conclusions: We show that knowledge of phantom microstructure enables absolute measurements of phantom constitution without prior calibration. Further, we show a connection across different length scales where knowledge of precise phantom component constitution can help understand macroscopically observable optical properties.

Improvement of Phased Antenna Array Applied in Focused Microwave Breast Hyperthermia.

Focused microwave breast hyperthermia (FMBH) employs a phased antenna array to perform beamforming that can focus microwave energy at targeted breast tumors. Selective heating of the tumor endows the hyperthermia treatment with high accuracy and low side effects. The effect of FMBH is highly dependent on the applied phased antenna array. This work investigates the effect of polarizations of antenna elements on the microwave-focusing results by simulations. We explore two kinds of antenna arrays with the same number of elements using different digital realistic human breast phantoms. The first array has all the elements' polarization in the vertical plane of the breast, while the second array has half of the elements' polarization in the vertical plane and the other half in the transverse plane, i.e., cross polarization. In total, 96 sets of different simulations are performed, and the results show that the second array leads to a better focusing effect in dense breasts than the first array. This work is very meaningful for the potential improvement of the antenna array for FMBH, which is of great significance for the future clinical applications of FMBH. The antenna array with cross polarization can also be applied in microwave imaging and sensing for biomedical applications.

Hardware and Software Setup for Quantitative 23Na Magnetic Resonance Imaging at 3T: A Phantom Study.

Magnetic resonance (MR) with sodium (23Na) is a noninvasive tool providing quantitative biochemical information regarding physiology, cellular metabolism, and viability, with the potential to extend MR beyond anatomical proton imaging. However, when using clinical scanners, the low detectable 23Na signal and the low 23Na gyromagnetic ratio require the design of dedicated radiofrequency (RF) coils tuned to the 23Na Larmor frequency and sequences, as well as the development of dedicated phantoms for testing the image quality, and an MR scanner with multinuclear spectroscopy (MNS) capabilities. In this work, we propose a hardware and software setup for evaluating the potential of 23Na magnetic resonance imaging (MRI) with a clinical scanner. In particular, the reliability of the proposed setup and the reproducibility of the measurements were verified by multiple acquisitions from a 3T MR scanner using a homebuilt RF volume coil and a dedicated sequence for the imaging of a phantom specifically designed for evaluating the accuracy of the technique. The final goal of this study is to propose a setup for standardizing clinical and research 23Na MRI protocols.