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Virtual precision surgery for mri implant safety

Oriano Bottauscio¹, Alessandro Arduino¹, Fabio Baruffaldi², Mario Chiampi¹, Jessica Martinez¹, Umberto Zanovello¹, and Luca Zilberti¹
¹Advanced Materials Metrology and Life Science, Istituto Nazionale di Ricerca Metrologica, Torino, Italy, ²IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy

Synopsis

In silico evaluation of heating during an MRI exam for patients with passive implants patients need detailed anatomical models to reproduce in vivo scenarios. A quantification of the influence of the model approximation is fundamental to define the main requirements of the digital model.Here, we analyze the impact of different model approximation in simulating RF and gradient-induced heating caused by orthopedic implants. It was found that, whereas the heating due to switched gradient fields does not strictly require the adoption of advanced virtual surgery, the heating caused by RF is strongly affected by the precision of the digital model.

INTRODUCTION

Safety concerns of patients with passive implants undergoing MRI exams have increased in relevance, also at standardization level^1-3. To this purpose, reliable and validated tools, capable of reproducing in vivo scenarios, are essential. Whereas several studies have focused on active implantable medical devices^4-11, greater attention has been recently given to passive implants, due to evident heating effects produced by radiofrequency (RF) and switched gradient coil (GC) fields^12-15.
In this work, the impact of increasingly detailed virtual surgery on predicting RF and GC heating is analyzed. Modified versions of two anatomical models belonging to the Virtual Population (ViP)¹⁶ are analyzed using four levels of details: from a single compartment model to a model obtained by applying a thorough virtual surgery procedure. In all cases, commercial hip, knee and shoulder implants are adopted.

METHODS

Heating analysis for RF and GC were evaluated for four levels of details of the modified anatomical models: a homogeneous anatomical model (Surgery 0), with physical properties of the ASTM F2182 gel¹⁷; a heterogeneous anatomical model with implants overlapped to the native tissues (Surgery 1); two anatomical models with realistic modification of the tissues surrounding the implant according to the virtual surgery procedure (Surgery 2). Two filler tissues are considered in the latter: connective tissue (2A) or synovial fluid (2B), with properties of the cerebrospinal fluid assigned due to tissue similarities^18,19.
The adult female Yoon-Sun and the adult male Glenn, from ViP Version 3, were selected. A total hip (model Apta-Fix) and total knee (model Genus MB) prostheses (Adler Ortho® SpA, Italy), were considered and their sizes selected according to the anatomy. Regarding the shoulder implant, two products were selected: an anatomichemi-prosthesis (model SMR Anatomic) for Yoon-Sun and a reverse prosthesis (model SMR Reverse) for GlennLimaCorporate SpA, Italy).
Virtual implants were implanted on one side using Sim4Life V5.220, modifying the original posture of the human models when required. For virtual Surgery 2, implant position was double-checked by orthopedic surgeons at IOR making special care to shape the periprosthetic bones of the human model to optimally fit the relevant implants (Figure 1).
RF simulations were performed with Sim4Life, positioning the virtual model within birdcage coils, tuned at 1.5 and 3 T, so that the implant is placed at the coil extremities from the isocenter (Figure 2) to maximize the power deposition^12,15. The coil input power was adjusted to generate an average B1+ of 2 μT on a 2D transverse slice at the coil isocenter.
For the GC simulations, a tubular gradient coil set was used, considering sequences producing worst-case exposure¹⁵: EPI and TrueFISP. A homemade software was used^21-23, analyzing nine body positions within the bore.

RESULTS

For the GC heating with EPI sequence (frequency encoding along the z-axis) the maximum temperature increases after 900 s are collected in Figure 3. Due to the smaller size, the temperature increases for hip and knee in Yoon-Sun are lower with respect to Glenn. For the shoulder implant, values found for Glenn are significantly lower, due to the non-metallic glenosphere.
For the hip implant, values range from 0.88 °C for Yoon-Sun (resp. 1.77 °C for Glenn), with Surgery 1 to 0.72 °C (resp. 1.6 °C), with Surgery 0. For the knee implant, values range from 0.81 °C (resp. 2.1 °C), with Surgery 1 to 0.64 °C (resp. 1.9 °C), with Surgery 0. For the shoulder implant values range from 1.1 °C (resp. 0.41 °C), with Surgery 1 to 0.82 °C (resp. 0.36 °C), with Surgery 0. Surgery 1 always gives rise to the highest values, whereas results obtained with Surgery 2A and 2B are almost coincident.
Figures 4 and 5 summarize temperature, 2-g and 10-g SAR results of Yoon-Sun for the knee implant (lowest temperature increase) and the shoulder implant (greatest temperature increase).
At 1.5 T, the maximum temperature increase was observed for Surgeries 2A and 2B (hip: 0.87 °C; Knee: 0.36 °C; Shoulder: 1.2 °C), followed by Surgery 1 and Surgery 0. At 3 T, the maximum temperature was observed for Surgeries 2A and 2B for the knee and shoulder implants (Knee: 1.6 °C; Shoulder: 7.4 °C), followed by Surgery 0 and Surgery 1. Maximum temperature for the hip implant was observed for Surgery 1 (3.6 °C), followed by Surgeries 2A/2B and Surgery 0.

DISCUSSION AND CONCLUSIONS

GC-induced heating does not strictly need the adoption of advanced virtual surgery. A simple overlapping of the implant CAD with the body anatomy successfully provides an acceptable estimation of heating. Surgery 2 results are weakly affected by the selected filling material. This overall behavior was found to be almost independent of the anatomical model and considered sequence.
For the RF-induced heating, an accurate virtual surgery is found to be essential. The different surgeries give rise to a variation up to ~55 % both for the 2-g averaged SAR and the maximum temperature increase. The differences are mainly due to the electromagnetic problem in the tissues, which dominates the RF-induced heating. The properties of the filling material negligibly affect the computed SAR distribution in Surgery 2.

Acknowledgements

The results presented here have been developed in the framework of the 17IND01 MIMAS Project. This project has received funding from the EMPIR Programme, co-financed by the Participating States and from the European Union’s Horizon 2020 Research and Innovation Programme.

Authors thank Zurich Med Tech, Zurich, Switzerland for making the modified versions of the ViP models, equipped with the considered orthopedic implants, available in the voxelized structure for subsequent in silico analysis.

CAD models of hip and knee implants were kindly provided by the manufacturer of prosthetic devices Adler Ortho® SpA, Italy (www.adlerortho.com).

Authors wish to thanks the orthopaedic surgeons F. Giardina, E. Tassinari (Orthopaedic-Traumatology and Prosthetic surgery and revisions of hip and knee implants, Istituto Ortopedico Rizzoli, Italy) and E. Guerra (Shoulder and Elbow Surgery, Istituto Ortopedico Rizzoli, Italy) for supervising virtual surgery activities.

References

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Figures

FIG.1-Glenn and Yoon-Sun models with the considered prostheses. On the right, for the Yoon-Sun models, the details of the three considered surgeries for each implant. The red material represents the implant, while the yellow one in Surgery 2 is the filler material, where parts of the bones have been removed after the insertion of the implant.

FIG.2-On the left the Yoon-Sun model in the nine considered positions for GC simulations. The wireframe of the GC coils is shown in blue. For each body position, the z-coordinate of the feet is reported. On the right the placement of Yoon-Sun within the birdcage coil. The implants were placed at the coil extremities at a given distance from the isocenter (highlighted in white): +93.1 mm for the shoulder implant ball, +35.3 mm for the hip implant head, and -89.5 mm for the knee implant femoral part.

FIG.3-GC heating: maximum temperature increases after 900 s for each considered position of the body within the MRI bore. Simulations with Glenn model (left plots) and Yoon-Sun model (right plots) from Pos1 (head imaging) to Pos9 (Femur/Knee imaging). Results refer to the EPI-Z sequence with frequency encoding along the z-axis.

FIG.4-Knee implant under RF field: temperature increase, 2-g SAR, and 10-g SAR maps across the four levels of approximation for the knee implant at 1.5 T and 3 T. Maximum values were observed at the right side of the femoral component. Note: Both temperature and SAR maps have different limits between the field strengths.

FIG.5-Shoulder implant under RF field: temperature increase, 2-g SAR, and 10-g SAR maps across the four levels of approximation for the shoulder implant at 1.5 T and 3 T. Maximum values were observed at the right side of the humeral stem. Note: Both temperature and SAR maps have different limits between the field strengths.

Proc. Intl. Soc. Mag. Reson. Med. 30 (2022)

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DOI: https://doi.org/10.58530/2022/2634