Synthetic CT for the planning of MR-HIFU treatment of bone metastases in pelvic and femoral bones: a feasibility study
Lena, Beatrice; Florkow, Mateusz C.; Ferrer, Cyril J.; van Stralen, Marijn; Seevinck, Peter R.; Vonken, Evert Jan P.A.; Boomsma, Martijn F.; Slotman, Derk J.; Viergever, Max A.; Moonen, Chrit T.W.; Bos, Clemens; Bartels, Lambertus W.
(2022) European Radiology, volume 32, issue 7, pp. 4537 - 4546
(Article)
Abstract
Objectives: Visualization of the bone distribution is an important prerequisite for MRI-guided high-intensity focused ultrasound (MRI-HIFU) treatment planning of bone metastases. In this context, we evaluated MRI-based synthetic CT (sCT) imaging for the visualization of cortical bone. Methods: MR and CT images of nine patients with pelvic and femoral metastases were
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retrospectively analyzed in this study. The metastatic lesions were osteolytic, osteoblastic or mixed. sCT were generated from pre-treatment or treatment MR images using a UNet-like neural network. sCT was qualitatively and quantitatively compared to CT in the bone (pelvis or femur) containing the metastasis and in a region of interest placed on the metastasis itself, through mean absolute difference (MAD), mean difference (MD), Dice similarity coefficient (DSC), and root mean square surface distance (RMSD). Results: The dataset consisted of 3 osteolytic, 4 osteoblastic and 2 mixed metastases. For most patients, the general morphology of the bone was well represented in the sCT images and osteolytic, osteoblastic and mixed lesions could be discriminated. Despite an average timespan between MR and CT acquisitions of 61 days, in bone, the average (± standard deviation) MAD was 116 ± 26 HU, MD − 14 ± 66 HU, DSC 0.85 ± 0.05, and RMSD 2.05 ± 0.48 mm and, in the lesion, MAD was 132 ± 62 HU, MD − 31 ± 106 HU, DSC 0.75 ± 0.2, and RMSD 2.73 ± 2.28 mm. Conclusions: Synthetic CT images adequately depicted the cancellous and cortical bone distribution in the different lesion types, which shows its potential for MRI-HIFU treatment planning. Key Points: • Synthetic computed tomography was able to depict bone distribution in metastatic lesions. • Synthetic computed tomography images intrinsically aligned with treatment MR images may have the potential to facilitate MR-HIFU treatment planning of bone metastases, by combining visualization of soft tissues and cancellous and cortical bone.
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Keywords: CT, High-intensity focused ultrasound ablation, MRI, Neoplasm metastasis, Synthetic CT, Radiology Nuclear Medicine and imaging, Journal Article
ISSN: 0938-7994
Publisher: Springer-Verlag
Note: Funding Information: This research is supported by the Applied and Engineering Sciences research program (project number 15179 and 15479), which is partly financed by the Netherlands Organization for Scientific Research, the Dutch Cancer Society, and PPP allowance of Top Sector Life Sciences & Health. Funding Information: The authors of this manuscript declare relationships with the following companies: PS and MvS are minority shareholders at MRIguidance BV. This research is supported by the Applied and Engineering Sciences research program (project number 15179 and 15479), which is partly financed by the Netherlands Organization for Scientific Research, the Dutch Cancer Society, and PPP allowance of Top Sector Life Sciences & Health. The authors wish to acknowledge the support of NVIDIA Corporation with the donation of a GPU for this research. Moreover, they would like to thank Ingrid Nijholt, Jacco van der Laan, Shanta Kalaykhan-Sewradj, and Pinar Kartal for their help in transferring the data between Isala Hospital and UMC Utrecht and Lambertus Bartels for being the scientific guarantor of this paper. Funding Information: The authors of this manuscript declare relationships with the following companies: PS and MvS are minority shareholders at MRIguidance BV. This research is supported by the Applied and Engineering Sciences research program (project number 15179 and 15479), which is partly financed by the Netherlands Organization for Scientific Research, the Dutch Cancer Society, and PPP allowance of Top Sector Life Sciences & Health. The authors wish to acknowledge the support of NVIDIA Corporation with the donation of a GPU for this research. Moreover, they would like to thank Ingrid Nijholt, Jacco van der Laan, Shanta Kalaykhan-Sewradj, and Pinar Kartal for their help in transferring the data between Isala Hospital and UMC Utrecht and Lambertus Bartels for being the scientific guarantor of this paper. Publisher Copyright: © 2022, The Author(s).
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