Fading of Deep Brain Stimulation Efficacy Versus Disease Progression: Untangling a Gordian Knot

Loss of Efficacy in Ventral Intermediate Nucleus Stimulation for Essential Tremor

OBJECTIVE

The primary aim of this study is to report long-term outcomes associated with deep brain stimulation (DBS) of the ventral intermediate nucleus (VIM) performed at our institution. We further aimed to elicit the factors associated with loss of efficacy and to discuss the need for exploring and establishing reliable rescue targets.

METHODS

To study long-term outcomes, we performed a retrospective chart review and extracted tremor scores of 43 patients who underwent VIM DBS lead implantation for essential tremor at our center. We further evaluated factors that could influence outcomes over time, including demographics, body mass index, duration of follow-up, degree of parenchymal atrophy indexed by the global cortical atrophy scale, and third ventricular width.

RESULTS

In this cohort, tremor scores on the latest follow-up (median 52.7 months) were noted to be worse than initial postoperative scores in 56% of DBS leads. Furthermore, 14% of leads were associated with clinically significant loss of benefit. Factors including the length of time since the lead implantation, age at the time of surgery, sex, body mass index, preoperative atrophy, and third ventricular width were not predictive of long-term outcomes.

CONCLUSIONS

Our study identified a substantial subgroup of VIM-DBS patient who experienced a gradual decline in treatment efficacy over time. We propose that this phenomenon can be attributed primarily to habituation and disease progression. Furthermore, we discuss the need to establish reliable and effective rescue targets for this subpopulation of patients, with ventral-oralis complex and dentate nucleus emerging as potential candidates.

Predicting Motor Outcome of Subthalamic Nucleus Deep Brain Stimulation for Parkinson's Disease Using Quantitative Susceptibility Mapping and Radiomics: A Pilot Study

Background

Emerging evidence indicates that iron distribution is heterogeneous within the substantia nigra (SN) and it may reflect patient-specific trait of Parkinson’s Disease (PD). We assume it could account for variability in motor outcome of subthalamic nucleus deep brain stimulation (STN-DBS) in PD.

Objective

To investigate whether SN susceptibility features derived from radiomics with machine learning (RA-ML) can predict motor outcome of STN-DBS in PD.

Methods

Thirty-three PD patients underwent bilateral STN-DBS were recruited. The bilateral SN were segmented based on preoperative quantitative susceptibility mapping to extract susceptibility features using RA-ML. MDS-UPDRS III scores were recorded 1–3 days before and 6 months after STN-DBS surgery. Finally, we constructed three predictive models using logistic regression analyses: (1) the RA-ML model based on radiomics features, (2) the RA-ML+LCT (levodopa challenge test) response model which combined radiomics features with preoperative LCT response, (3) the LCT response model alone.

Results

For the predictive performances of global motor outcome, the RA-ML model had 82% accuracy (AUC = 0.85), while the RA-ML+LCT response model had 74% accuracy (AUC = 0.83), and the LCT response model alone had 58% accuracy (AUC = 0.55). For the predictive performance of rigidity outcome, the accuracy of the RA-ML model was 80% (AUC = 0.85), superior to those of the RA-ML+LCT response model (76% accuracy, AUC = 0.82), and the LCT response model alone (58% accuracy, AUC = 0.42).

Conclusion

Our findings demonstrated that SN susceptibility features from radiomics could predict global motor and rigidity outcomes of STN-DBS in PD. This RA-ML predictive model might provide a novel approach to counsel candidates for STN-DBS.

Deep Brain Stimulation Selection Criteria for Parkinson's Disease: Time to Go beyond CAPSIT-PD

Despite being introduced in clinical practice more than 20 years ago, selection criteria for deep brain stimulation (DBS) in Parkinson's disease (PD) rely on a document published in 1999 called 'Core Assessment Program for Surgical Interventional Therapies in Parkinson's Disease'. These criteria are useful in supporting the selection of candidates. However, they are both restrictive and out-of-date, because the knowledge on PD progression and phenotyping has massively evolved. Advances in understanding the heterogeneity of PD presentation, courses, phenotypes, and genotypes, render a better identification of good DBS outcome predictors a research priority. Additionally, DBS invasiveness, cost, and the possibility of serious adverse events make it mandatory to predict as accurately as possible the clinical outcome when informing the patients about their suitability for surgery. In this viewpoint, we analyzed the pre-surgical assessment according to the following topics: early versus delayed DBS; the evolution of the levodopa challenge test; and the relevance of axial symptoms; patient-centered outcome measures; non-motor symptoms; and genetics. Based on the literature, we encourage rethinking of the selection process for DBS in PD, which should move toward a broad clinical and instrumental assessment of non-motor symptoms, quantitative measurement of gait, posture, and balance, and in-depth genotypic and phenotypic characterization.