Apr 10, 2024

Public workspaceQuality assessment for images obtained using 3D printed stereotaxic frame

DOI
dx.doi.org/10.17504/protocols.io.4r3l2qmn3l1y/v1
  • Lucy Liang1,
  • David J Schaeffer1,
  • Tales Santini1,
  • Isabela Zimmermann Rollin1,
  • Elvira Pirondini1
  • 1University of Pittsburgh
Lucy Liang
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DOI: https://dx.doi.org/10.17504/protocols.io.4r3l2qmn3l1y/v1
Protocol Citation: Lucy Liang, David J Schaeffer, Tales Santini, Isabela Zimmermann Rollin, Elvira Pirondini 2024. Quality assessment for images obtained using 3D printed stereotaxic frame. protocols.io https://dx.doi.org/10.17504/protocols.io.4r3l2qmn3l1y/v1
Manuscript citation:
Liang, L., Zimmermann Rollin, I., Alikaya, A., Ho, J.C., Santini, T., Bostan, A.C., Schwerdt, H.N., Stauffer, W.R., Ibrahim, T.S., Pirondini, E., Schaeffer, D.J., 2024. An open-source MRI compatible frame for multimodal presurgical mapping in macaque and capuchin monkeys. BioRxiv https://doi.org/10.1101/2024.02.17.580767
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License,  which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: March 20, 2024
Last Modified: May 31, 2024
Protocol Integer ID: 97019
Keywords: ASAPCRN, image distortion, geometric phantom, 3D printed stereotaxic frame, non-human primate, printed stereotaxic frame, stereotaxic frame, plastic stereotaxic frame, quality assessment for image, source mri compatible frame for multimodal presurgical mapping, stereotaxic frame this protocol, source mri, mri, multimodal presurgical mapping, using 3d, macaque, 3d, quality assessment, mr signal noise, engineering drawings for the frame, distortion, quality, capuchin monkey
Funders Acknowledgements:
Aligning Science Across Parkinson's
Grant ID: ASAP-020519
Abstract
This protocol describes the steps taken to assess whether MR signal noise and distortion is introduced by utilization of a 3D printed plastic stereotaxic frame.

The computer-aided design files and engineering drawings for the frame used in this protocol are publicly available, with the modular design allowing for low cost and manageable manufacturing.
You can find it here: https://github.com/SchaefferLab/Macaque-Stereotax
This protocol is supplementary to the manuscript:
Liang, L., Zimmermann Rollin, I., Alikaya, A., Ho, J.C., Santini, T., Bostan, A.C., Schwerdt, H.N., Stauffer, W.R., Ibrahim, T.S., Pirondini, E., Schaeffer, D.J., 2024. An open-source MRI compatible frame for multimodal presurgical mapping in macaque and capuchin monkeys. BioRxiv https://doi.org/10.1101/2024.02.17.580767
Guidelines
The geometric phantom used in this assessment was chosen to match the size of a macaque monkey head, with internal geometric structure the size of a typical monkey brain, our target imaging structure. This protocol can be used also for other imaging targets, but the phantom should be adjusted to obtain accurate assessment results.
Materials
Imaging Equipment
  • Siemens 7T whole body MRI scanner (Magnetom, Siemens Healthcare, Erlangen, Germany)
  • 2nd generation Tic-Tac-Toe radiofrequency (RF) system (Sajewskiet al., 2023; Santini et al., 2021)
  • small animal CT scanner (Si78; Bruker BioSpin GmbH, Ettlingen, Germany), with software package ParaVision-360 (version 3.2; Bruker BioSpin Corp, Billerica, MA)

Materials
Geometric phantom (radius = 35 mm and height = 190 mm)

Image Processing Software
  • FSL: fsleyes, flirt, fslmaths (Smith et al. 2004)
  • MATLAB 2022b

S.M. Smith, M. Jenkinson, M.W. Woolrich, C.F. Beckmann, T.E.J. Behrens, H. Johansen-Berg, P.R. Bannister, M. De Luca, I. Drobnjak, D.E. Flitney, R.K. Niazy, J. Saunders, J. Vickers, Y. Zhang, N. De Stefano, J.M. Brady, P.M. Matthews, Advances in functional and structural MR image analysis and implementation as FSL Neuroimage, 23 (2004), pp. S208-S219
https://doi-org.pitt.idm.oclc.org/10.1016/j.neuroimage.2004.07.051
Troubleshooting
Image Acquisitions
Acquire MRI using gradient-echo sequences in the 7T MRI scanner (Magnetom, Siemens Healthcare, Erlangen, Germany) with the following parameters:
  • TE/TR=8.16/40 ms
  • resolution 400 μm isotropic (same as what you will acquire for your target structure)
  • matrix size=176×384×384
  • flip angle=15°
  • acceleration factor (GRAPPA)=2
Without stereotaxic frame: place the geometric phantom in the center of the coil, acquire images as described
With stereotaxic frame: center the geometric phantom in the stereotaxic frame in the same orientation as without the frame, place the stereotaxic frame in the center of the coil, acquire images with same parameters as before
Next, acquire CT images of the same phantom in a small animal CT scanner (Si78; Bruker BioSpin GmbH, Ettlingen, Germany) with the following parameters:
  • resolution 200 μm isotropic, FOV: 79.6×199 mm
  • Low Dose 1 mm aluminum filter, “step and shoot” method (0.6-degree gantry step)
  • reconstruct using filtered back projection algorithm equipped with the software package ParaVision-360
Signal to Noise Ratio (SNR) Assessment
In MATLAB, calculate the SNR maps for MRI of the phantom (with and without frame) by dividing the signal in the image by the standard deviation of the background noise.
Compare the average SNR value of the entire image stack, calculated for each of the two MRIs. They should be very similar. This allows us to assess the overall signal quality.
In FSL, visualize (fsleyes) and coregister the SNR maps of the MRIs with and without stereotaxic frame using rigid transformation (flirt).
Overlay the SNR maps (with and without frame). The hyper/hypo-intensities should match well if there are no spatial distortions introduced by the frame.
Geometric Distortion Assessment
In FSL, visualize (fsleyes) and coregister the MRIs with the CT image using rigid transformation (flirt).
Binarize the phantom (include only internal geometric structure) CT image using thresholding with fslmaths or any equivalent software/function.
Overlay the binarized image with the MR SNR maps. Check conformity of the rectilinear geometric structure between the two.
Protocol references
3D printable stereotaxic frame: https://github.com/SchaefferLab/Macaque-Stereotax
Liang, L., Zimmermann Rollin, I., Alikaya, A., Ho, J.C., Santini, T., Bostan, A.C., Schwerdt, H.N., Stauffer, W.R., Ibrahim, T.S., Pirondini, E., Schaeffer, D.J., 2024. An open-source MRI compatible frame for multimodal presurgical mapping in macaque and capuchin monkeys. BioRxiv https://doi.org/10.1101/2024.02.17.580767

Sajewski, A., Santini, T., Tiago, M., Berardinelli, J., Ibrahim, T.S., 2023. Comparison of the Optimization of a 60-channel Transmit Coil in pTx and sTx mode at 7T. Presented at the ISMRM.
Santini, T., Wood, S., Krishnamurthy, N., Martins, T., Aizenstein, H.J., Ibrahim, T.S., 2021. Improved 7 Tesla transmit field homogeneity with reduced electromagnetic power deposition using coupled Tic Tac Toe antennas. Sci Rep 11, 3370. https://doi.org/10.1038/s41598-020-79807-9

S.M. Smith, M. Jenkinson, M.W. Woolrich, C.F. Beckmann, T.E.J. Behrens, H. Johansen-Berg, P.R. Bannister, M. De Luca, I. Drobnjak, D.E. Flitney, R.K. Niazy, J. Saunders, J. Vickers, Y. Zhang, N. De Stefano, J.M. Brady, P.M. Matthews, Advances in functional and structural MR image analysis and implementation as FSL Neuroimage, 23 (2004), pp. S208-S219
https://doi-org.pitt.idm.oclc.org/10.1016/j.neuroimage.2004.07.051