"PICS": a novel patient-specific landmark for thalamic surgical interventions
Poster No:
7
Submission Type:
Abstract Submission
Authors:
Remi Patriat1, Jayashree Chandrasekaran1, Karianne Sretavan1, Henry Braun1, Samuel Brenny1, Yasamin Seddighi1, Joshua Aman1, Meghan Hill1, Jerrold Vitek1, Noam Harel1, Leonardo Brito de Almeida1
Institutions:
1University of Minnesota, Minneapolis, MN
First Author:
Co-Author(s):
Introduction:
Visualizing the individual thalamic nuclei using conventional MRI techniques is challenging. It has posed obstacles in targeting specific subnuclei for clinical interventions, such as deep brain stimulation (DBS) and MR-guided focused ultrasound, leading to variable patient outcomes(Agrawal et al., 2021; Flora et al., 2010) and repeat surgeries. Imaging methods have been developed for directly visualizing thalamic targets with limited clinical applicability. Using the DiMANI contrast(Patriat et al., 2024), we present a new MRI landmark in the posterior limb of the internal capsule (pLIC), referred to as PICS, that indicates the location of the Vim nucleus of the thalamus, enabling direct targeting approaches for surgical interventions.
Methods:
One healthy control and fifteen essential tremor (ET) patients were scanned at 7Tesla including: diffusion, MPRAGE, FGATIR, SWI, and T2 for all plus QSM, T2*, Neuromelanin, and MP2RAGE for the control. Manual segmentation of the pLIC was performed on DiMANI images (see (Patriat et al., 2024)). Each participant's T1 was non-linearly registered to MNI space and within subject images were linearly co-registered to their T1. To characterize the PICS fibers, three pLIC tractography schemes were conducted with cortical ROIs as seeds and the pLIC as a waypoint. The gross motor cortical ROIs were extracted from the HMAT template(Mayka et al., 2006) (experiment1), M1 and S1 homunculus were extracted from the Brainnetome data(Fan et al., 2016) (experiments2 and 3). To visualize tractography results in a common space, DTI-TK was used to create a study-specific template(Bach et al., 2014; Zhang et al., 2007). Results are shown as 80% thresholded maps and as center-of-mass skeletons for clarity. Finally, intra- and post-operative clinical data were merged for one ET DBS patient to show correspondence between the parcellation results and clinical observations.
Results:
The PICS in the pLIC region was distinctly visible using DiMANI in 15 out of 15 patients. PICS was observed in the pLIC region across multiple MR-contrasts however, it was much more prominent on DiMANI images(Fig.1). Fig.2 shows the pLIC tractography results. The HMAT average tractography results demonstrate an anterior-posterior organization in the pLIC with S1 posteriormost followed anteriorly by M1, PMv, PMd, SMA and preSMA corresponding to the cortical organization. The regions of SMA and PMd of the pLIC overlapped the most and maintained similar anterior-posterior distribution across subjects (Fig.2A-C). For the M1 homunculus, two somatotopic clusters were observed: one including mostly trunk, lower and upper limbs; and another with head/face clustering with tongue/larynx. Within the trunk and limbs cluster, lower limb was found more medial to the trunk region, while upper limb was distributed more anterolateral to trunk (Fig.2D-F). The S1 homunculus regions of pLIC were located posterior and lateral to M1 homunculus (not shown here due to figure limitations). Stimulation using the sheath of the microelectrode intra-operatively at two different depths resulted in pLIC-specific side effect in the tongue/face. Measurements showed closer proximity of the DBS electrode at those depths to M1 cluster of head/face and tongue/larynx, validating the clinical findings obtained intraoperatively.
Conclusions:
We present PICS, an imaging landmark that could facilitate patient-specific direct targeting for Vim-based surgical procedures. PICS is clearly visible on DiMANI but can also be seen with other MR contrasts to a lesser degree. We showed that PICS is mostly comprised of cortico-spinal tracts, but not corticobulbar tracts fibers, and it is consistently located lateral to the Vim, making it a potential landmark for thalamic procedures. The parcellations of the pLIC using M1 and S1 homunculus could potentially inform lead or ablation location based on side effect profiles (e.g. head/face/tongue vs. trunk/limbs).
Brain Stimulation:
Deep Brain Stimulation 1
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s)
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis 2
Keywords:
HIGH FIELD MR
Movement Disorder
MRI
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
Other - Deep Brain Stimulation
1|2Indicates the priority used for review
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Bach, M., Laun, F. B., Leemans, A., Tax, C. M., Biessels, G. J., Stieltjes, B., & Maier-Hein, K. H. (2014). Methodological considerations on tract-based spatial statistics (TBSS). Neuroimage, 100, 358-369. https://doi.org/10.1016/j.neuroimage.2014.06.021
Behrens, T. E., Berg, H. J., Jbabdi, S., Rushworth, M. F., & Woolrich, M. W. (2007). Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? Neuroimage, 34(1), 144-155. https://doi.org/10.1016/j.neuroimage.2006.09.018
Fan, L., Li, H., Zhuo, J., Zhang, Y., Wang, J., Chen, L.,…Jiang, T. (2016). The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture. Cereb Cortex, 26(8), 3508-3526. https://doi.org/10.1093/cercor/bhw157
Flora, E. D., Perera, C. L., Cameron, A. L., & Maddern, G. J. (2010). Deep brain stimulation for essential tremor: a systematic review. Mov Disord, 25(11), 1550-1559. https://doi.org/10.1002/mds.23195
Mayka, M. A., Corcos, D. M., Leurgans, S. E., & Vaillancourt, D. E. (2006). Three-dimensional locations and boundaries of motor and premotor cortices as defined by functional brain imaging: a meta-analysis. Neuroimage, 31(4), 1453-1474. https://doi.org/10.1016/j.neuroimage.2006.02.004
Patriat, R., Palnitkar, T., Chandrasekaran, J., Sretavan, K., Braun, H., Yacoub, E.,…Harel, N. (2024). DiMANI: diffusion MRI for anatomical nuclei imaging-Application for the direct visualization of thalamic subnuclei. Front Hum Neurosci, 18, 1324710. https://doi.org/10.3389/fnhum.2024.1324710
Zhang, H., Avants, B. B., Yushkevich, P. A., Woo, J. H., Wang, S., McCluskey, L. F.,…Gee, J. C. (2007). High-dimensional spatial normalization of diffusion tensor images improves the detection of white matter differences: an example study using amyotrophic lateral sclerosis. IEEE Trans Med Imaging, 26(11), 1585-1597. https://doi.org/10.1109/TMI.2007.906784