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. 2022 Nov 4;26(2):401–408. doi: 10.1007/s40477-022-00740-w

Simple, inexpensive, and ergonomic phantom for quality assurance control of MRI guided Focused Ultrasound systems

Anastasia Antoniou 1, Christakis Damianou 1,✉
PMCID: PMC10247591  PMID: 36329304

Abstract

Purpose

The popularity of Magnetic Resonance guided Focused Ultrasound (MRgFUS) as a beneficial therapeutic solution for many diseases is increasing rapidly, thus raising the need for reliable quality assurance (QA) phantoms for routine testing of MRgFUS systems. In this study, we propose a thin acrylic film as the cheapest and most easily accessible phantom for assessing the functionality of MRgFUS hardware and software.

Methods

Through the paper, specific QA tests are detailed in the framework of evaluating an MRgFUS preclinical robotic device comprising a single element spherically focused transducer with a nominal frequency of 2.75 MHz. These tests take advantage of the reflection of ultrasonic waves at a plastic–air interface, which results in almost immediate lesion formation on the film at a threshold of applied acoustic energy.

Results

The phantom offered qualitative information on the power field distribution of the FUS transducer and the ability to visualize different FUS protocols. It also enabled quick and reliable assessment of various navigation algorithms as they are used in real treatments, and also allowed for the assessment of the accuracy of robotic motion.

Conclusion

Therefore, it could serve as a useful tool for detecting defects in system’s performance over its lifetime after establishing a baseline while concurrently contributing to establish QA and calibration guidelines for clinical routine controls.

Keywords: Quality assurance, Phantom, MRI, Acrylic film, Cheap, Ultrasound

Introduction

The therapeutic benefits of focused ultrasound (FUS) have been widely exploited in the area of oncology [1]. Malignant cells can be necrotized by concentrating the ultrasonic energy within the target region, thus increasing the temperature to lethal levels non-invasively [1]. The popularity of this technology is increasing substantially while quality assurance (QA) tools for FUS devices and protocols remain to be standardized, thus raising the need for dedicated high-quality QA phantoms.

So far, gel-based tissue mimicking materials (TMMs) have been the main tool for testing FUS hardware in the research and development (R&D) stage, including assessment of the thermal heating abilities of ultrasonic transducers [2–4] and the Magnetic Resonance Imaging (MRI) compatibility of devices intended for MRI-guided FUS (MRgFUS) applications [2–6]. To begin with, gel phantoms are considered suitable for thermal studies in that they enable insertion of thermocouples for benchtop temperature measurements [7]. In addition, their tissue-like MRI signal [8] is beneficial in monitoring thermal exposures in the MRI setting through the use of MR thermometry. Accordingly, they serve as a valuable tool for evaluating and optimizing therapeutic protocols before in-vivo applications, for example, by examining the impact of various scanning pathways on the off-target heating [9] and the formation of asymmetric lesions [10] owning to thermal diffusion phenomena.

Polyacrylamide (PAA) gels containing thermosensitive ingredients, such as thermochromic ink that progressively changes colour under heating [11], BSA protein [11], and egg-white [12], were proposed for FUS studies, having the advantage of visualizing the formed lesions due to protein denaturation. Agar gels were also proven effective for FUS studies having the benefit of easy and cost-effective preparation, as well as the ability to simulate the critical thermal, acoustical, and MRI properties of several soft tissues depending on the type and concentration of added complementary ingredients [13]. On the contrary, gelatin-based phantom are only suitable for hyperthermia applications because they cannot withstand ablative temperatures [14]. Notably, the use of 3D printed materials and plastics to mimic bony tissues is becoming popular in multi-modality phantoms intended for MRI and/or US imaging [15–17].

In terms of evaluating the motion accuracy of robotic mechanisms designed to navigate the ultrasonic transducer relative to the subject, the so far proposed R&D techniques include digital calliper-based methods [3], MRI imaging of the ultrasonic transducer or other dedicated MRI visible objects during step motion [18], and visual assessment of lesion formation in transparent thermosensitive phantoms [2, 19].

Regarding clinical use of test phantoms, the basic functionalities of a clinical MRgFUS device can also be tested by mapping the temperature rise during heating in a dedicated phantom. Several studies report on the use of MR thermometry during sonication in US/MRI phantoms as a simple QA method for clinical routine testing [20, 21]. In fact, this method has been the mainstay for clinical QA allowing for testing the acoustic power output, the targeting accuracy, the noise level introduced into the picture, and well as the size and shape of the focal spot. An indicative example is a 4-years retrospective study [21], which was performed to assess the basic functionalities of the first clinical MRgFUS system; ExAblate 2000 (InSightec Inc., Haifa, Israel) before each of 148 uterine fibroid treatment sessions.

The aforementioned QA measures are also employed before clinical deployment since they are extremely essential in the process of a system’s technical acceptance [22]. In this regard, the MRgFUS system ExAblate 2000 has been tested by employing MR thermometry in TMMs designed to match the ultrasonic properties of tissue [22]. The focus positioning accuracy was examined by performing grid sonications in coronal and axial planes and comparing the commanded position with the actual position of the focus as defined by the peak temperature location through the controlling software.

Similarly, Vicari et al. [23] proposed a series of radiation force measurements, 3D modelling and geometrical tests for daily in-vitro QA of the InSightec ExAblate 2100 equipment, with emphasis on the delivered power and position of the focus. The authors followed an interesting technique to assess the focus positioning accuracy and software reliability by sonicating a 96 well plate filled with a thermosensitive BSA-doped PAA gel [23].

While the need for phantoms dedicated to QA of FUS equipment has long been recognized [24], their development was delayed until recently, when two relevant studies were published [25, 26]. The proposed QA phantoms are both based on the concept of placing ultrasonic calibration equipment in a plastic container that is filled with a TMM. To be more specific, Acri et al. [25] developed an ergonomic phantom for clinical routine QA of MRgFUS devices consisting of a hollow polymethyl methacrylate (PMMA) cylinder that can host various movable inserts. These could be PMMA holders specially designed to support instruments, such as a precision balance or a thermometer, or small teflon pieces simulating microcalcifications. According to the authors, it is filled with different fluids depending on the tested parameters, which may be the precision and dimension of the FUS spot, the target temperature, and the linearity of output power.

Ambrogio et al. [26] developed a QA phantom of similar design to evaluate the performance of the Sonalleve commercial MRgFUS system (Philips, Canada) over a 12-month period. The developed phantom is a PMMA cubic structure that embeds a 3D-printed bone-mimic disk made of VeroWhite Plus material and 4 T-type thermocouples within an agar-based soft TMM in clinically relevant places for the specific intended therapeutic modalities of this system.

It becomes clear that gel phantom-based techniques have been essential in both R&D and clinical testing of MRgFUS devices. Although widely accepted, these techniques suffer from many potential sources of error related to human or instrument failures, which may cause the results of assessment to be interpreted incorrectly. For instance, gel phantoms are prone to air or other inhomogeneities that may be introduced during the preparation process, as well as to gradual water loss, which are very possible to influence the formation of uniform lesions and thus the reliability of measurements. Furthermore, since phantoms have limited lifetime, different phantoms will be used at different days, which is not ideal when examining the functionality and loss of precision on a routine basis.

Following the aforementioned unmet needs, in this study, we propose the use of an acrylic thin film as the most cost-effective and ergonomic way of evaluating the functionality and stability of MRgFUS equipment over time. A robotic device dedicated to MRgFUS preclinical applications, and the relevant treatment planning/monitoring software were employed in the study. The QA methodology is detailed through a series of experiments designed to assess the performance of this system in terms of targeting accuracy, heating effects of the ultrasonic transducer, software functionality, and proper communication between hardware and software.

Materials and methods

Quality assurance acrylic film

The QA phantom proposed in this study is a clear film made of acrylic plastic with a thickness of 0.9 mm (FDM400mc print plate, Stratasys, Minnesota, USA). The ultrasonic attenuation of the film was estimated at 8.5 dB/cm‐MHz (at 2 MHz) according to the transmission through technique [27]. The following QA tests take advantage of the almost complete reflection of ultrasonic waves at the plastic–air interface, which results in almost immediate lesion formation on the upper side of the film at a threshold of applied acoustic energy. Accordingly, in all experiments, the upper side of the film involved air while degassed water was used as the coupling media between the transducer and the bottom surface of the film, as shown in Fig. 1, so lesion formation was mainly based on reflection.

Fig. 1.

Fig. 1

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Concept of lesion formation on the plastic film

MRgFUS robotic device for preclinical use

A preclinical MRgFUS robotic device previously described in detail by Drakos et al. [3] was employed in the study. In brief, the system comprises a mechanism enclosure where all the mechanical and electronic components are hosted and another separate water enclosure where the transducer is actuated. The water enclosure includes an acoustic opening at the top for placing the target.

For the purpose of the current study, the transducer comprised a single element spherically focused ultrasonic piezoelectric (Piezohannas, Wuhan, China) with a nominal frequency of 2.75 MHz (Radius of curvature: 65 mm, Diameter: 50 mm, efficiency: 30%). The transducer was powered by an RF amplifier (AG1016, AG Series Amplifier, T & C Power Conversion, Inc., Rochester, US).

The system was integrated with and controlled by a custom made treatment planning-monitoring software which provided the ability to plan sonications in rectangular grids or complex patterns for full coverage of any segmented area on MRI images, as well as to define the sonication (acoustic power and sonication time) and grid parameters (spatial and temporal step).

Power field assessment

The power field of the 2.75 MHz ultrasonic transducer was evaluated by sonicating the plastic film at varying distance from its surface. The transducer was securely mounted on the bottom part of a plastic holder facing upwards to the plastic film. Careful design of the holder was followed to ensure horizontal placement of the film, thus minimizing sound refraction phenomena. The holder also included a height adjustment mechanism for changing the transducer-film distance with a 10-mm step. The setup was hosted in a tank, which was filled with degassed, deionized water up to the upper surface of the plastic film to achieve the aforementioned “water-plastic-air” configuration. Electrical power of 150 W (acoustic power of 45 W) was applied for 30 s in continuous mode for different transducer-film distances of 40–90 mm. The diameter of the formed lesion at each tested distance was measured using a digital caliper.

Assessment of change in lesion size by varying sonication parameters

In this experimental part, the QA film was securely mounted on the acoustic opening of the device using a dedicated holder, as shown in Fig. 2. The distance from the transducer was adjusted to equal the radius of curvature. Degassed water was used as described above to ensure ultrasonic coupling with the bottom surface of the film. The effect of the power (10–70 W electric power) and duration of sonication (1–11 s) on lesion formation was examined independently by performing sonications spaced by 1 cm.

Fig. 2.

Fig. 2

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Photo of the experimental setup with the phantom fixed to the acoustic opening of the MRgFUS device above the FUS transducer

Accuracy and repeatability of motion assessment

This experimental part was carried out to assess the accuracy and repeatability of motion, as well as whether the software commands are properly executed using a similar setup as detailed above. The film was sonicated by robotically moving the transducer along predefined pathways; square or irregular grids using the commands of the relevant software. The planned sonication spots were visited in a Zig-Zag pathway using varying motion step. An acoustical power of 6 W was applied for 5 s to each spot while a waiting time of 60 s was left between successive sonications to ensure adequate heat dissipation in the phantom.

Results

Lesions of different dimensions were formed by sonicating the acrylic film at varying distance from the transducer surface and served as indicators of the power film distribution. The sonicated films are shown in Fig. 3 with the measured lesion diameter indicated. Among the tested distances, the largest lesion is observed at 40 mm and gradually decreases in size until the distance of 60 mm, whereas at 80 mm it increases again, thus demonstrating heating in the far-field region. This change in lesion size with varying distance gives a good approximation of the power field distribution in that lesion dimensions can be defined as the half width and length of a Gaussian power distribution at each distance.

Fig. 3.

Fig. 3

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Photo of acrylic films sonicated at increasing distance from the transducer using acoustical power of 45 W for 30 s and the 2.75 MHz transducer (radius of curvature of 65 mm and diameter of 50 mm), indicating the diameter of the formed lesions

The lesion size at a specific distance from the transducer surface can be controlled by varying the sonication parameters. Figure 4 shows the change in lesion size by varying the electric power from 10 to 70 W while keeping constant the sonication duration at 6 s at the focal plane. The distance between successive sonications was set at 1 cm.

Fig. 4.

Fig. 4

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Photo of lesions formed using varying electric power of 10 to 70 W for a constant sonication duration of 6 s

Figures 5, 6 and 7 show indicative results of multiple lesions formed on the phantom following pathway planning on the dedicated software. Figure 5 shows discrete lesions formed in a 5 × 5 square grid using a spatial step of 10 mm (each spot exposed to 20 W electric power/ 6 W acoustical power for 5 s). The overlapping lesions shown in Fig. 6 were created after sonication in a 20 × 20 grid using identical ultrasonic parameters but a smaller spatial step of 1 mm. An indicative result of sonication in irregular pattern with similar sonication protocol and a 3-mm step is shown in Fig. 7. Note that the ablated area matches well the segmented area in the software. The selection of grid step defined the formation of discrete or overlapping lesions. Overall, the lesion patterns demonstrate good motion and alignment accuracy.

Fig. 5.

Fig. 5

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a Software screenshot showing the sonication spots (5 × 5 grid) and Zig-Zag pathway as planned on an MRI image of an agar phantom. b The corresponding lesions formed on the plastic film using acoustic power of 6 W for 5 s at each spot, with a spatial step of 10 mm, using the 2.75 MHz transducer (radius of curvature of 65 mm and diameter of 50 mm)

Fig. 6.

Fig. 6

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a Software screenshot showing the sonication area (20 × 20 grid) as planned on an MRI image of an agar phantom. b The corresponding overlapping lesions formed on the plastic film using acoustic power of 6 W for 5 s at each spot, with a spatial step of 1 mm, using the 2.75 MHz transducer (radius of curvature of 65 mm and diameter of 50 mm)

Fig. 7.

Fig. 7

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a Software screenshot showing the segmented irregular area on an MRI image of an agar phantom. b The corresponding almost overlapping lesions formed on the plastic film using acoustic power of 6 W for 5 s at each spot, with a spatial step of 3 mm, using the 2.75 MHz transducer (radius of curvature of 65 mm and diameter of 50 mm)

Discussion

Through a literature search, it can be easily concluded that while there are well established methods for calibrating FUS equipment, the methods and tools for QA of MRgFUS robotic devices are still far from being standardized. Herein, a thin acrylic film was proposed as the cheapest and most easily accessible quality assurance phantom for assessing the performance of MRgFUS hardware and software. Although, in this study, we used a 0.9 mm-thick print plate obtained from a Stratasys printer, one can simply buy a similar product from a bookstore at a very low price.

Specific methods involving the use of the proposed film were utilized for assessing the functionality of an MRgFUS preclinical robotic device. The setup is extremely simple and is based on the concept of “water-plastic-air” described previously, where lesion formation is mainly the result of sound reflection at the plastic/air boundary.

Regarding quality assurance of the FUS transducer, the phantom provides indication of the beam’s cross section. By collecting several slices in cross section, it is possible to get qualitative information for the power field distribution of the FUS transducer in axial direction. In addition, by adjusting the power and time it is possible to control the size of the individual lesions, thus simulating different focused ultrasound protocols. Following experiments with varying power and time, an acoustic energy of 18 W was proven sufficient to produce a lesion of easily measurable dimensions (≈ 2 mm in diameter) on the proposed phantom. A limitation of this approach is that evaluation is not possible in the axial direction.

Furthermore, the phantom was proven an efficient tool for assessing the accuracy and repeatability of robotic motion by navigating the robotic system in grid patterns and producing discrete lesions. Note that this was also demonstrated in a previous study [18], but it was further assessed with extensive experimentation of various motion algorithms. It is interesting to note that the formed lesion patterns did not show evidence of thermal diffusion.

By using small spacing during navigation, it is also possible to assess several navigation algorithms as they are used in actual treatments. In this study, complex shapes were sonicated successfully as evidenced by the lesions created on the plastic film, following planning of the sonication sequence on the software. This method helps to assess not only the software performance, but also its communication with the integrated robotic system and whether motion commands are properly executed.

The main limitation of the proposed QA methodology is that it cannot be used as a stand-alone tool to optimize clinical therapeutic protocols since it has different acoustic properties and response to heat than soft tissues. The mechanism of thermal diffusion that affects the formation of uniform lesions and treatment outcome in tissue [10, 28] is less effective in plastic due to the difference in thermal conductivity. Besides, the mechanism of lesion formation is completely different. This limitation is also considered a benefit in that it allows for reliable assessment of the planning algorithms and robotic motion without phantom-dependent parameters affecting the lesion’s size and shape significantly.

So far, tissue-mimicking gel phantoms have been the major tool for characterizing the performance of preclinical and clinical MRgFUS systems. However, they have a limited lifetime and are prone to air or other inhomogeneities, which are very likely to shift or distort the formed lesions. In this regard, they are not ideal for assessing the system’s functionality and stability over time or the motion accuracy of robotically positioned MRgFUS devices. Furthermore, in case a thermosensitive TMM is utilized that forms permanent lesions, it should be replaced after each QA test. Notably, two recently published articles report the development of more complex phantoms containing TMMs and FUS measurement tools for QA of clinical MRgFUS devices [25, 26]. In this study, the proposed QA phantom and relevant methodology are simpler and more ergonomic, highly cost-effective, universal, and do not depend on human or instrument-related factors. Although it is not reusable since the formed lesions are permanent, this is not a problem due to its very low cost.

Conclusions

Overall, the obtained results qualify the proposed acrylic phantom as a reliable QA tool for routine testing of MRgFUS robotic devices through a series of simple and quick tests. Accordingly, it could be used for the detection of defects in system’s performance and ease maintenance over its lifetime, while concurrently contributing towards developing quality control and calibration guidelines for clinical practices. It is though underlined that state-of-the-art gel-based methods should also be employed when testing therapeutic protocols to optimize the efficiency and safety before in-vivo use.

Acknowledgements

The study was co-funded by the European Structural & Investment Funds (ESIF) and the Republic of Cyprus through the Research and Innovation Foundation (RIF) under the project SOUNDPET (INTEGRATED/0918/0008).

Author contributions

AA contributed to the drafting of manuscript and scientific methods. CD had the overall supervision of the study.

Funding

This research was supported by Research and Innovation Foundation of Cyprus, SOUNDPET (INTEGRATED/0918/0008).

Declarations

Conflict of interests

The authors declare that they have no conflicts of interest.

Ethical approval

The study does not involve animals or human participants.

Consent to participate/consent to publish

Not applicable.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  • 1.Abe K, Taira T. Focused ultrasound treatment, present and future. Neurol Med Chir (Tokyo) 2017;57:386–391. doi: 10.2176/nmc.ra.2017-0024. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Damianou C, Giannakou M, Menikou G, Ioannou L. Magnetic resonance imaging-guided focused ultrasound robotic system with the subject placed in the prone position. Digit Med. 2020;6:24–31. doi: 10.4103/digm.digm_2_20. [DOI] [Google Scholar]
  • 3.Drakos T, Giannakou M, Menikou G, Filippou A, Evripidou N, Spanoudes K, et al. MRI-guided focused ultrasound robotic system for preclinical use. J Vet Med Anim Sci. 2021;4:1–11. [Google Scholar]
  • 4.Antoniou A, Giannakou M, Evripidou N, Stratis S, Pichardo S, Damianou C. Robotic system for top to bottom MRgFUS therapy of multiple cancer types. Int J Med Robot Comput Assist Surg. 2022;18(2):e2364. doi: 10.1002/rcs.2364. [DOI] [PubMed] [Google Scholar]
  • 5.Antoniou A, Giannakou M, Evripidou N, Evripidou G, Spanoudes K, Menikou G, et al. Robotic system for magnetic resonance guided focused ultrasound ablation of abdominal cancer. Int J Med Robot Comput Assist Surg. 2021 doi: 10.1002/rcs.2299. [DOI] [PubMed] [Google Scholar]
  • 6.Giannakou M, Drakos T, Menikou G, Evripidou N, Filippou A, Spanoudes K, et al. MRI-guided focused ultrasound robotic system for transrectal prostate cancer therapy. Int J Med Robot Comput Assist Surg. 2021;17(3):e2237. doi: 10.1002/rcs.2237. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Dabbagh A, Abdullah BJJ, Ramasindarum C, Abu Kasim NH. Tissue-mimicking gel phantoms for thermal therapy studies. Ultrason Imaging. 2014;36:291–316. doi: 10.1177/0161734614526372. [DOI] [PubMed] [Google Scholar]
  • 8.Antoniou A, Damianou C. MR relaxation properties of tissue-mimicking phantoms. Ultrasonics. 2022 doi: 10.1016/j.ultras.2021.106600. [DOI] [PubMed] [Google Scholar]
  • 9.Filippou A, Drakos T, Giannakou M, Evripidou N, Damianou C. Experimental evaluation of the near-field and far-field heating of focused ultrasound using the thermal dose concept. Ultrasonics. 2021;116:106513. doi: 10.1016/j.ultras.2021.106513. [DOI] [PubMed] [Google Scholar]
  • 10.Zhou Y, Kargl SG, Hwang JH. The effect of the scanning pathway in high-intensity focused ultrasound therapy on lesion production. Ultrasound Med Biol. 2011;37:1457–1468. doi: 10.1016/j.ultrasmedbio.2011.05.848. [DOI] [PubMed] [Google Scholar]
  • 11.Eranki A, Mikhail AS, Negussie AH, Katti PS, Wood BJ, Partanen A. Tissue-mimicking thermochromic phantom for characterization of HIFU devices and applications. Int J Hyperth. 2019;36:518–529. doi: 10.1080/02656736.2019.1605458. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Takegami K, Kaneko Y, Watanabe T, Maruyama T, Matsumoto Y, Nagawa H. Polyacrylamide gel containing egg white as new model for irradiation experiments using focused ultrasound. Ultrasound Med Biol. 2004;30:1419–1422. doi: 10.1016/j.ultrasmedbio.2004.07.016. [DOI] [PubMed] [Google Scholar]
  • 13.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 doi: 10.1002/acm2.13533. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Madsen EL, Hobson MA, Shi H, Varghese T, Frank GR. Tissue-mimicking agar/gelatin materials for use in heterogeneous elastography phantoms. Phys Med Biol. 2005;50:5597–5618. doi: 10.1088/0031-9155/50/23/013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Menikou G, Dadakova T, Pavlina M, Bock M, Damianou C. MRI compatible head phantom for ultrasound surgery. Ultrasonics. 2015;57:144–152. doi: 10.1016/j.ultras.2014.11.004. [DOI] [PubMed] [Google Scholar]
  • 16.Menikou G, Yiannakou M, Yiallouras C, Ioannides C, Damianou C. MRI-compatible breast/rib phantom for evaluating ultrasonic thermal exposures. Int J Med Robot Comput Assist Surg. 2018;14:1–12. doi: 10.1002/rcs.1849. [DOI] [PubMed] [Google Scholar]
  • 17.Menikou G, Yiannakou M, Yiallouras C, Ioannides C, Damianou C. MRI-compatible bone phantom for evaluating ultrasonic thermal exposures. Ultrasonics. 2016;71:12–19. doi: 10.1016/j.ultras.2016.05.020. [DOI] [PubMed] [Google Scholar]
  • 18.Antoniou A, Drakos T, Giannakou M, Evripidou N, Georgiou L, Christodoulou T, et al. Simple methods to test the accuracy of MRgFUS robotic systems. Int J Med Robot Comput Assist Surg. 2021 doi: 10.1002/rcs.2287. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Yiallouras C, Mylonas N, Damianou C. MRI-compatible positioning device for guiding a focused ultrasound system for transrectal treatment of prostate cancer. Int J Comput Assist Radiol Surg. 2014;9:745–753. doi: 10.1007/s11548-013-0964-x. [DOI] [PubMed] [Google Scholar]
  • 20.Chen L, Ma C, Meyer J. Quality assurance for MR guided focused ultrasound treatment of bone metastasis: a clinical experience. Int J Radiat Oncol. 2014;90:S703. doi: 10.1016/j.ijrobp.2014.05.2059. [DOI] [Google Scholar]
  • 21.Mcdannold N, Hynynen K. Quality assurance and system stability of a clinical MRI-guided focused ultrasound system: four-year experience. Med Phys. 2006;33:4307–4313. doi: 10.1118/1.2352853. [DOI] [PubMed] [Google Scholar]
  • 22.Gorny KR, Hangiandreou NJ, Hesley GK, Gostout BS, McGee KP, Felmlee JP. MR guided focused ultrasound: technical acceptance measures for a clinical system. Phys Med Biol. 2006;51:3155–3173. doi: 10.1088/0031-9155/51/12/011. [DOI] [PubMed] [Google Scholar]
  • 23.Vicari F, Russo G, Cammarata FP, Cirincione R, Forte GI, Borasi G, et al. A daily quality assurance routine for ultrasounds in vitro experiments. Transl Cancer Res. 2014;3:421–429. doi: 10.3978/j.issn.2218-676X.2014.09.02. [DOI] [Google Scholar]
  • 24.Schätzle U, Reuner T, Jenne J, Heilingbrunner A. Quality assurance tools for therapeutic ultrasound. Ultrasonics. 1998;36:679–682. doi: 10.1016/S0041-624X(97)00138-8. [DOI] [PubMed] [Google Scholar]
  • 25.Acri G, Caridi F, Testagrossa B, Gurgone S, Anfuso C, Paladini G, et al. (2022) A “user-friendly” phantom to conduct Quality Controls on MRgFUS device. J Phys Conf Ser, vol. 2162, IOP Publishing; p. 012004. 10.1088/1742-6596/2162/1/012004
  • 26.Ambrogio S, Baêsso RM, Bosio F, Fedele F, Ramnarine KV, Zeqiri B, et al. A standard test phantom for the performance assessment of magnetic resonance guided high intensity focused ultrasound (MRgHIFU) thermal therapy devices. Int J Hyperth. 2022;39:57–68. doi: 10.1080/02656736.2021.2017023. [DOI] [PubMed] [Google Scholar]
  • 27.Antoniou A, Evripidou N, Giannakou M, Constantinides G, Damianou C. Acoustical properties of 3D printed thermoplastics. J Acoust Soc Am. 2021;149:2854–2864. doi: 10.1121/10.0004772. [DOI] [PubMed] [Google Scholar]
  • 28.Curiel L, Chavrier F, Gignoux B, Pichardo S, Chesnais S, Chapelon JY. Experimental evaluation of lesion prediction modelling in the presence of cavitation bubbles: Intended for high-intensity focused ultrasound prostate treatment. Med Biol Eng Comput. 2004;42:44–54. doi: 10.1007/BF02351010. [DOI] [PubMed] [Google Scholar]

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