Asleep subthalamic deep brain stimulation for Parkinson’s disease

Asleep subthalamic deep brain stimulation for Parkinson’s disease

Recent advances in methods used for deep brain stimulation (DBS) include subthalamic nucleus electrode implantation in the “asleep” patient without the traditional use of microelectrode recordings or intraoperative test stimulation.

Meta-Analysis

2019

Liu et al. systematically reviewed the literature to compare the efficacy and safety of awake and asleep deep brain stimulation surgery. They identified cohort studies from the Cochrane libraryMEDLINE, and EMBASE (January 1970 to August 2019) by using Review Manager 5.3 software to conduct a meta-analysis following the PRISMA guidelines. Fourteen cohort studies involving 1,523 patients were included. The meta-analysis results showed that there were no significant differences between the GA and LA groups in UPDRSIII score improvement (standard mean difference [SMD] 0.06; 95% CI -0.16 to 0.28; p = 0.60), postoperative LEDD requirement (SMD -0.17; 95% CI -0.44 to 0.12; p = 0.23), or operation time (SMD 0.18; 95% CI -0.31 to 0.67; p = 0.47). Additionally, there was no significant difference in the incidence of adverse events (OR 0.98; 95% CI 0.53-1.80; p = 0.94), including postoperative speech disturbance and intracranial hemorrhage. However, the volume of intracranial air was significantly lower in the GA group than that in the LA group. In a subgroup analysis, there was no significant difference in clinical efficacy between the microelectrode recording (MER) and non-MER groups. We demonstrated equivalent clinical outcomes of DBS surgery between GA and LA in terms of improvement of symptoms and the incidence of adverse events. Key Messages: MER might not be necessary for DBS implantation. For patients who cannot tolerate DBS surgery while being awake, GA should be an appropriate alternative 1).

Case series

A retrospective review of clinical outcomes of 152 consecutive patients. Their outcomes at 1 yr postimplantation are reported; these include Unified Parkinson’s Disease Rating Scale (UPDRS) assessment, Mobility Tinetti TestPDQ-39 quality of life assessment, Mattis Dementia Rating ScaleBeck Depression Inventory, and Beck Anxiety Inventory. They also report on a new parietal trajectory for electrode implantation.

UPDRS III improved from 39 to 20.5 (47%, P < .001). The total UPDRS score improved from 67.6 to 36.4 (46%, P < .001). UPDRS II scores improved from 18.9 to 10.5 (44%, P < .001) and UPDRS IV scores improved from 7.1 to 3.6 (49%, P < .001). There was a significant reduction in levodopa equivalent daily dose after surgery (mean: 35%, P < .001). PDQ-39 summary index improved by a mean of 7.1 points. There was no significant difference found in clinical outcomes between the frontal and parietal approaches.

“Asleep” robot-assisted DBS of the subthalamic nucleus demonstrates comparable outcomes with traditional techniques in the treatment of Parkinson’s disease. 2).


The objective of a study of Senemmar et al. was to investigate whether asleep deep brain stimulation surgery of the subthalamic nucleus (STN) improves therapeutic window (TW) for both directional (dDBS) and omnidirectional (oDBS) stimulation in a large single-center population.

A total of 104 consecutive patients with Parkinson’s disease (PD) undergoing STN-DBS surgery (80 asleep and 24 awake) were compared regarding TW, therapeutic thresholdside effect threshold, improvement of Unified PD Rating Scale motor score (UPDRS-III) and degree of levodopa equivalent daily dose (LEDD) reduction.

Asleep DBS surgery led to significantly wider TW compared to awake surgery for both dDBS and oDBS. However, dDBS further increased TW compared to oDBS in the asleep group only and not in the awake group. Clinical efficacy in terms of UPDRS-III improvement and LEDD reduction did not differ between groups.

The study provides first evidence for improvement of therapeutic window by asleep surgery compared to awake surgery, which can be strengthened further by dDBS. These results support the notion of preferring asleep over awake surgery but needs to be confirmed by prospective trial3).


Clinical outcome studies have shown that “asleep” DBS lead placement, performed using intraoperative imaging with stereotactic accuracy as the surgical endpoint, has motor outcomes comparable to traditional “awake” DBS using microelectrode recording (MER), but with shorter case times and improved speech fluency 4).


Ninety-six patients were retrospectively matched pairwise (48 asleep and 48 awake) and compared regarding improvement of Unified PD Rating Scale Motor Score (UPDRS-III), cognitive function, Levodopa-equivalent-daily-dose (LEDD), stimulation amplitudes, side effects, surgery duration, and complication rates. Routine testing took place at three months and one year postoperatively.

Results: Chronic DBS effects (UPDRS-III without medication and with stimulation on [OFF/ON]) significantly improved UPDRS-III only after awake surgery at three months and in both groups one year postoperatively. Acute effects (percentage UPDRS-III reduction after activation of stimulation) were also significantly better after awake surgery at three months but not at one year compared to asleep surgery. UPDRS-III subitems “freezing” and “speech” were significantly worse after asleep surgery at three months and one year, respectively. LEDD was significantly lower after awake surgery only one week postoperatively. The other measures did not differ between groups.

Overall motor function improved faster in the awake surgery group, but the difference ceased after one year. However, axial subitems were worse in the asleep surgery group suggesting that worsening of axial symptoms was risked improving overall motor function. Awake surgery still seems advantageous for STN-DBS in PD, although asleep surgery may be considered with lower threshold in patients not suitable for awake surgery 5).

References

1)

Liu Z, He S, Li L. General Anesthesia versus Local Anesthesia for Deep Brain Stimulation in Parkinson’s Disease: A Meta-Analysis. Stereotact Funct Neurosurg. 2019;97(5-6):381-390. doi:10.1159/000505079
2)

Moran CH, Pietrzyk M, Sarangmat N, Gerard CS, Barua N, Ashida R, Whone A, Szewczyk-Krolikowski K, Mooney L, Gill SS. Clinical Outcome of “Asleep” Deep Brain Stimulation for Parkinson Disease Using Robot-Assisted Delivery and Anatomic Targeting of the Subthalamic Nucleus: A Series of 152 Patients. Neurosurgery. 2020 Sep 28:nyaa367. doi: 10.1093/neuros/nyaa367. Epub ahead of print. PMID: 32985669.
3)

Senemmar F, Hartmann CJ, Slotty PJ, Vesper J, Schnitzler A, Groiss SJ. Asleep Surgery May Improve the Therapeutic Window for Deep Brain Stimulation of the Subthalamic Nucleus [published online ahead of print, 2020 Jul 13]. Neuromodulation. 2020;10.1111/ner.13237. doi:10.1111/ner.13237
4)

Mirzadeh Z, Chen T, Chapple KM, Lambert M, Karis JP, Dhall R, Ponce FA. Procedural Variables Influencing Stereotactic Accuracy and Efficiency in Deep Brain Stimulation Surgery. Oper Neurosurg (Hagerstown). 2018 Oct 18. doi: 10.1093/ons/opy291. [Epub ahead of print] PubMed PMID: 30339204.
5)

Blasberg F, Wojtecki L, Elben S, Slotty PJ, Vesper J, Schnitzler A, Groiss SJ. Comparison of Awake vs. Asleep Surgery for Subthalamic Deep Brain Stimulation in Parkinson’s Disease. Neuromodulation. 2018 Aug;21(6):541-547. doi: 10.1111/ner.12766. Epub 2018 Mar 13. PubMed PMID: 29532

Diffusion tensor imaging for trigeminal neuralgia

Diffusion tensor imaging for trigeminal neuralgia

A total of 22 patients with classic trigeminal neuralgia and 22 healthy controls (HC) with matching age, gender, and education were selected. All subjects underwent 3.0 T magnetic resonance diffusion tensor imaging and high resolution T1-weighted imaging. The corpus callosum (CC) was reconstructed by DTI technology, which was divided into three substructure regions: genu, body, and splenium. Group differences in multiple diffusion metrics, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD), were compared between CTN patients and HC, and correlations between the white matter change and disease duration and VAS in CTN patients were assessed.

Compared with HC group, CTN patients had extensive damage to the CC white matter. The FA of the genu (P = 0.04) and body (P = 001) parts decreased, while RD (P = 0.003; P = 0.02) and MD (P = 0.002; P = 0.04) increased. In addition, the authors observed that the disease duration and VAS of CTN patients were negatively correlated with FA.

The corpus callosum substructure region has extensive damage in chronic pain, and the selective microstructural integrity damage was particularly manifested by changes in axons and myelin sheath in the genu and body of corpus callosum 1).


Diffusion tensor imaging (DTI) has revealed microstructural changes in the symptomatic trigeminal root and root entry zone of patients with unilateral TN.

Noninvasive DTI analysis of patients with TN may lead to improved trigeminal neuralgia diagnosis of TN subtypes (e.g., TN1 and TN2) and improve patient selection for surgical intervention. DTI measurements may also provide insights into prognosis after intervention, as TN1 patients are known to have better surgical outcomes than TN2 patients 2).


As diffusion tensor imaging (DTI) is able to assess tissue integrity, Leal et al., used diffusion to detect abnormalities in trigeminal nerves (TGN) in patients with trigeminal neuralgia (TN) caused by neurovascular compression (NVC) who had undergone microvascular decompression (MVD).

Using DTI sequencing on a 3-T MRI scanner, we measured the fraction of anisotropy (FA) and apparent diffusion coefficient (ADC) of the TGN in 10 patients who had undergone MVD for TN and in 6 normal subjects. We compared data between affected and unaffected nerves in patients and both nerves in normal subjects (controls). We then correlated these data with CSA and V. Data from the affected side and the unaffected side before and 4 years after MVD were compared.

RESULTS: Before MVD, the FA of the affected side (0.37 ± 0.03) was significantly lower (p < 0.05) compared to the unaffected side in patients (0.48 ± 0.03) and controls (0.52 ± 0.02), and the ADC in the affected side (5.6 ± 0.34 mm2/s) was significantly higher (p < 0.05) compared to the unaffected side in patients (4.26 ± 0.25 mm2/s) and controls (3.84 ± 0.18 mm2/s). Affected nerves had smaller V and CSA compared to unaffected nerves and controls (p < 0.05). After MVD, the FA in the affected side (0.41 ± 0.02) remained significantly lower (p < 0.05) compared to the unaffected side (0.51 ± 0.02), but the ADC in the affected side (4.24 ± 0.34 mm2/s) had become similar (p > 0.05) to the unaffected side (4.01 ± 0.33 mm2/s).

CONCLUSIONS: DTI revealed a loss of anisotropy and an increase in diffusivity in affected nerves before surgery. Diffusion alterations correlated with atrophic changes in patients with TN caused by NVC. After removal of the compression, the loss of FA remained, but ADC normalized in the affected nerves, suggesting improvement in the diffusion of the trigeminal root 3).


Herveh et al. studied the trigeminal nerve in seven healthy volunteers and six patients with trigeminal neuralgia using the diffusion tensor imaging derived parameter fractional anisotropy (FA). While controls did not show a difference between both sides, there was a reduction of FA in the affected nerve in three of six patients with accompanying nerve-vessel conflict and atrophy. Reversibility of abnormally low FA values was demonstrated in one patient successfully treated with microvascular decompression 4).


3T MR diffusion weighted, T1, T2 and FLAIR sequences were acquired for Multiple sclerosis related trigeminal neuralgia MS-TN, TN, and controls. Multi-tensor tractography was used to delineate CN V across cisternal, root entry zone (REZ), pontine and peri-lesional segments. Diffusion metrics including fractional anisotropy (FA), and radial (RD), axial (AD), and mean diffusivities (MD) were measured from each segment.

CN V segments showed distinctive diffusivity patterns. The TN group showed higher FA in the cisternal segment ipsilateral to the side of pain, and lower FA in the ipsilateral REZ segment. The MS-TN group showed lower FA in the ipsilateral peri-lesional segments, suggesting differential microstructural changes along CN V in these conditions.

The study demonstrates objective differences in CN V microstrucuture in TN and MS-TN using non-invasive neuroimaging. This represents a significant improvement in the methods currently available to study pain in MS 5).


The aim of a study was to evaluate the microstructural tissue abnormalities in the trigeminal nerve in symptomatic trigeminal neuralgia not related to neurovascular compression using diffusion tensor imaging. Mean values of the quantitative diffusion parameters of trigeminal nerve, fractional anisotropy and apparent diffusion coefficient, were measured in a group of four symptomatic trigeminal neuralgia patients without neurovascular compression who showed focal non-enhancing T2-hyperintense lesions in the pontine trigeminal pathway. These diffusion parameters were compared between the affected and unaffected sides in the same patient and with four age-matched healthy controls. Cranial magnetic resonance imaging revealed hyperintense lesions in the dorsolateral part of the pons along the central trigeminal pathway on T2-fluid-attenuated inversion recovery sequences. The mean fractional anisotropy value on the affected side was significantly decreased (P = 0.001) compared to the unaffected side and healthy controls. Similarly, the mean apparent diffusion coefficient value was significantly higher (P = 0.001) on the affected side compared to the unaffected side and healthy controls. The cause of trigeminal neuralgia in our patients was abnormal pontine lesions affecting the central trigeminal pathway. The diffusion tensor imaging results suggest that microstructural tissue abnormalities of the trigeminal nerve also exist even in non-neurovascular compression-related trigeminal neuralgia 6).


DTI analysis allows the quantification of structural alterations, even in those patients without any discernible neurovascular contact on MRI. Moreover, our findings support the hypothesis that both the arteries and veins can cause structural alterations that lead to TN. These aspects can be useful for making treatment decisions 7).


The mean diameter of compression arteries (DCA) in NVC patients with TN (1.58 ± 0.34 mm) was larger than that without TN (0.89 ± 0.29 mm). Compared with NVC without TN and HC, the mean values of RD at the site of NVC with TN were significantly increased; however, no significant changes of AD were found between the groups. Correlation analysis showed that DCA positively correlated with radial diffusivity (RD) in NVC patients with and without TN (r = 0.830, p = 0.000). No significant correlation was found between DCA and axial diffusivity (AD) (r = 0.178, p = 0.077).

Larger-diameter compression arteries may increase the chances of TN, and may be a possible facilitating factor for TN 8).


Fractional anisotropy (FA) value quantitatively showed the alteration of trigeminal nerve (TGN) caused by Neurovascular compression (NVC). It provided direct evidence about the effect of NVC which facilitated the diagnosis and surgical decision of Type 2 trigeminal neuralgia (TN) . Besides, significant reduction of FA value may predict an optimistic outcome of microvascular decompression (MVD) 9).


Sophisticated structural MRI techniques including diffusion tensor imaging provide new opportunities to assess the trigeminal nerves and CNS to provide insight into TN etiology and pathogenesis. Specifically, studies have used high-resolution structural MRI methods to visualize patterns of trigeminal nerve-vessel relationships and to detect subtle pathological features at the trigeminal REZ. Structural MRI has also identified CNS abnormalities in cortical and subcortical gray matter and white matter and demonstrated that effective neurosurgical treatment for TN is associated with a reversal of specific nerve and brain abnormalities 10).


Forty-three patients with trigeminal neuralgia were recruited, and diffusion tensor imaging was performed before radiofrequency rhizotomy. By selecting the cisternal segment of the trigeminal nerve manually, they measured the volume of trigeminal nerve, fractional anisotropy, apparent diffusion coefficient, axial diffusivity, and radial diffusivity. The apparent diffusion coefficient and mean value of fractional anisotropy, axial diffusivity, and radial diffusivity were compared between the affected and normal side in the same patient, and were correlated with pre-rhizotomy and post-rhizotomy visual analogue scale pain scores. The results showed the affected side had significantly decreased fractional anisotropy, increased apparent diffusion coefficient and radial diffusivity, and no significant change of axial diffusivity. The volume of the trigeminal nerve on affected side was also significantly smaller. There was a trend of fractional anisotropy reduction and visual analogue scale pain score reduction (P = 0.072). The results suggest that demyelination without axonal injury, and decreased size of the trigeminal nerve, are the microstructural abnormalities of the trigeminal nerve in patients with trigeminal neuralgia caused by neurovascular compression. The application of diffusion tensor imaging in understanding the pathophysiology of trigeminal neuralgia, and predicting the treatment effect has potential and warrants further study 11).

References

1)

Li R, Chang N, Liu Y, Zhang Y, Luo Y, Zhang T, Zhao Q, Qi X. The Integrity of the Substructure of the Corpus Callosum in Patients with Right Classic Trigeminal Neuralgia-A Diffusion Tensor Imaging Study. J Craniofac Surg. 2020 Sep 22. doi: 10.1097/SCS.0000000000007082. Epub ahead of print. PMID: 32969923.
2)

Willsey MS, Collins KL, Conrad EC, Chubb HA, Patil PG. Diffusion tensor imaging reveals microstructural differences between subtypes of trigeminal neuralgia. J Neurosurg. 2019 Jul 19:1-7. doi: 10.3171/2019.4.JNS19299. [Epub ahead of print] PubMed PMID: 31323635.
3)

Leal PRL, Roch J, Hermier M, Berthezene Y, Sindou M. Diffusion tensor imaging abnormalities of the trigeminal nerve root in patients with classical trigeminal neuralgia: a pre- and postoperative comparative study 4 years after microvascular decompression. Acta Neurochir (Wien). 2019 May 2. doi: 10.1007/s00701-019-03913-5. [Epub ahead of print] PubMed PMID: 31049710.
4)

Herweh C, Kress B, Rasche D, Tronnier V, Tröger J, Sartor K, Stippich C. Loss of anisotropy in trigeminal neuralgia revealed by diffusion tensor imaging. Neurology. 2007 Mar 6;68(10):776-8. PubMed PMID: 17339587.
5)

Chen DQ, DeSouza DD, Hayes DJ, Davis KD, O’Connor P, Hodaie M. Diffusivity signatures characterize trigeminal neuralgia associated with multiple sclerosis. Mult Scler. 2016 Jan;22(1):51-63. doi: 10.1177/1352458515579440. PubMed PMID: 25921052.
6)

Neetu S, Sunil K, Ashish A, Jayantee K, Usha Kant M. Microstructural abnormalities of the trigeminal nerve by diffusion-tensor imaging in trigeminal neuralgia without neurovascular compression. Neuroradiol J. 2016 Feb;29(1):13-8. doi: 10.1177/1971400915620439. PubMed PMID: 26678753; PubMed Central PMCID: PMC4978338.
7)

Lutz J, Thon N, Stahl R, Lummel N, Tonn JC, Linn J, Mehrkens JH. Microstructural alterations in trigeminal neuralgia determined by diffusion tensor imaging are independent of symptom duration, severity, and type of neurovascular conflict. J Neurosurg. 2016 Mar;124(3):823-30. doi: 10.3171/2015.2.JNS142587. PubMed PMID: 26406792.
8)

Lin W, Zhu WP, Chen YL, Han GC, Rong Y, Zhou YR, Zhang QW. Large-diameter compression arteries as a possible facilitating factor for trigeminal neuralgia: analysis of axial and radial diffusivity. Acta Neurochir (Wien). 2016 Mar;158(3):521-6. doi: 10.1007/s00701-015-2673-4. PubMed PMID: 26733127; PubMed Central PMCID: PMC4752583.
9)

Chen F, Chen L, Li W, Li L, Xu X, Li W, Le W, Xie W, He H, Li P. Pre-operative declining proportion of fractional anisotropy of trigeminal nerve is correlated with the outcome of micro-vascular decompression surgery. BMC Neurol. 2016 Jul 16;16:106. doi: 10.1186/s12883-016-0620-5. PubMed PMID: 27422267; PubMed Central PMCID: PMC4947245.
10)

DeSouza DD, Hodaie M, Davis KD. Structural Magnetic Resonance Imaging Can Identify Trigeminal System Abnormalities in Classical Trigeminal Neuralgia. Front Neuroanat. 2016 Oct 19;10:95. Review. PubMed PMID: 27807409; PubMed Central PMCID: PMC5070392.
11)

Chen ST, Yang JT, Yeh MY, Weng HH, Chen CF, Tsai YH. Using Diffusion Tensor Imaging to Evaluate Microstructural Changes and Outcomes after Radiofrequency Rhizotomy of Trigeminal Nerves in Patients with Trigeminal Neuralgia. PLoS One. 2016 Dec 20;11(12):e0167584. doi: 10.1371/journal.pone.0167584. PubMed PMID: 27997548.

Sweet spot

Sweet spot

The sweet spot is a place where a combination of factors results in a maximum response for a given amount of effort.

The results of a study of Zolal et al. suggested the possibility that atlas-based clustering, as well as diffusion tractography-based parcellation, can be useful in estimating the stimulation target (“sweet spot”) for Subthalamic deep brain stimulation for Parkinson’s disease. Atlas-based as well as diffusion-based clustering might become a useful tool in DBS trajectory planning 1).


Stimulation effects of 449 DBS settings in 21 PD patients were clinically and quantitatively assessed through standardized monopolar reviews and mapped into standard space. A sweet spot for best motor outcome was determined using voxelwise and nonparametric permutation statistics. Two independent cohorts were used to investigate whether stimulation overlap with the sweet spot could predict acute motor outcome (10 patients, 163 settings) and long-term overall Unified Parkinson’s Disease Rating Scale Part III (UPDRS-III) improvement (63 patients).

Results: Significant clusters for suppression of rigidity and akinesia, as well as for overall motor improvement, resided around the dorsolateral border of the STN. Overlap of the volume of tissue activated with the sweet spot for overall motor improvement explained R2 = 37% of the variance in acute motor improvement, more than triple what was explained by overlap with the STN (R2 = 9%) and its sensorimotor subpart (R2 = 10%). In the second independent cohort, sweet spot overlap explained R2 = 20% of the variance in long-term UPDRS-III improvement, which was equivalent to the variance explained by overlap with the STN (R2 = 21%) and sensorimotor STN (R2 = 19%).

Interpretation: This study is the first to predict clinical improvement of parkinsonian motor symptoms across cohorts based on local DBS effects only. The new approach revealed a distinct sweet spot for STN DBS in PD. Stimulation overlap with the sweet spot can predict short- and long-term motor outcome and may be used to guide DBS programming 2).


Based on local field potential data acquired from 54 patients undergoing STN-DBS, power values within alpha, beta, low beta, and high beta bands were calculated. Values were projected into common stereotactic space after DBS lead localization. Recorded beta power values were significantly higher at posterior and dorsal lead positions, as well as in active compared with inactive pairs. The peak of activity in the beta band was situated within the sensorimotor functional zone of the nucleus. In contrast, higher alpha activity was found in a more ventromedial region, potentially corresponding to associative or premotor functional zones of the STN. Beta- and alpha-power peaks were then used as seeds in a fiber tracking experiment. Here, the beta-site received more input from primary motor cortex whereas the alpha-site was more strongly connected to premotor and prefrontal areas. The results summarize predominant spatial locations of frequency signatures recorded in STN-DBS patients in a probabilistic fashion. The site of predominant beta-activity may serve as an electrophysiologically determined target for optimal outcome in STN-DBS for PD in the future 3).

References

1)

Zolal A, Polanski WH, Klingelhoefer L, Kitzler HH, Linn J, Podlesek D, Sitoci-Ficici KH, Reichmann H, Leonhardt GK, Schackert G, Sobottka SB. Parcellation of the Subthalamic Nucleus in Parkinson’s Disease: A Retrospective Analysis of Atlas- and Diffusion-Based Methods. Stereotact Funct Neurosurg. 2020 Sep 23:1-8. doi: 10.1159/000509780. Epub ahead of print. PMID: 32966999.
2)

Dembek TA, Roediger J, Horn A, Reker P, Oehrn C, Dafsari HS, Li N, Kühn AA, Fink GR, Visser-Vandewalle V, Barbe MT, Timmermann L. Probabilistic sweet spots predict motor outcome for deep brain stimulation in Parkinson disease. Ann Neurol. 2019 Oct;86(4):527-538. doi: 10.1002/ana.25567. PMID: 31376171.
3)

Horn A, Neumann WJ, Degen K, Schneider GH, Kühn AA. Toward an electrophysiological “sweet spot” for deep brain stimulation in the subthalamic nucleus. Hum Brain Mapp. 2017 Jul;38(7):3377-3390. doi: 10.1002/hbm.23594. Epub 2017 Apr 8. PMID: 28390148; PMCID: PMC6867148.
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