Prefrontal-subthalamic theta signaling mediates delayed responses during conflict processing

While medial frontal cortex (MFC) and subthalamic nucleus (STN) have been implicated in conflict monitoring and action inhibition, respectively, an integrated understanding of the spatiotemporal and spectral interaction of these nodes and how they interact with motor cortex (M1) to definitively modify motor behavior during conflict is lacking. We recorded neural signals intracranially across presupplementary motor area (preSMA), M1, STN, and globus pallidus internus (GPi), during a flanker task in 20 patients undergoing deep brain stimulation implantation surgery for Parkinson disease or dystonia. Conflict is associated with sequential and causal increases in local theta power from preSMA to STN to M1 with movement delays directly correlated with increased STN theta power, indicating preSMA is the MFC locus that monitors conflict and signals STN to implement a 'break.' Transmission of theta from STN-to-M1 subsequently results in a transient increase in M1-to-GPi beta flow immediately prior to movement, modulating the motor network to actuate the conflict-related action inhibition (i.e., delayed response). Action regulation during conflict relies on two distinct circuits, the conflict-related theta and movement-related beta networks, that are separated spatially, spectrally, and temporally, but which interact dynamically to mediate motor performance, highlighting complex parallel yet interacting networks regulating movement.

Irregularity of instantaneous gamma frequency in the motor control network characterize visuomotor and proprioceptive information processing

Objective.The study aims to characterize movements with different sensory goals, by contrasting the neural activity involved in processing proprioceptive and visuo-motor information. To accomplish this, we have developed a new methodology that utilizes the irregularity of the instantaneous gamma frequency parameter for characterization.Approach.In this study, eight essential tremor patients undergoing an awake deep brain stimulation implantation surgery repetitively touched the clinician's finger (forward visually-guided/FV movement) and then one's own chin (backward proprioceptively-guided/BP movement). Neural electrocorticographic recordings from the motor (M1), somatosensory (S1), and posterior parietal cortex (PPC) were obtained and band-pass filtered in the gamma range (30-80 Hz). The irregularity of the inter-event intervals (IEI; inverse of instantaneous gamma frequency) were examined as: (1) auto-information of the IEI time series and (2) correlation between the amplitude and its proceeding IEI. We further explored the network connectivity after segmenting the FV and BP movements by periods of accelerating and decelerating forces, and applying the IEI parameter to transfer entropy methods.Main results.Conceptualizing that the irregularity in IEI reflects active new information processing, we found the highest irregularity in M1 during BP movement, highest in PPC during FV movement, and the lowest during rest at all sites. Also, connectivity was the strongest from S1 to M1 and from S1 to PPC during FV movement with accelerating force and weakest during rest.Significance. We introduce a novel methodology that utilize the instantaneous gamma frequency (i.e. IEI) parameter in characterizing goal-oriented movements with different sensory goals, and demonstrate its use to inform the directional connectivity within the motor cortical network. This method successfully characterizes different movement types, while providing interpretations to the sensory-motor integration processes.

Know DBS: patient perceptions and knowledge of deep brain stimulation in Parkinson's disease

Introduction

Deep brain stimulation (DBS) is an established therapy for Parkinson's disease (PD) that can significantly improve motor symptoms and quality of life. Despite its effectiveness, little is known about patient perceptions of DBS.

Objectives

To evaluate patient perceptions of DBS for PD, focusing on understanding, satisfaction, and factors influencing their outlook. This study aims to enhance patient education and counseling by identifying key determinants of patient perceptions.

Design

A patient survey.

Methods

We surveyed 77 PD patients who had undergone DBS at multiple centers using a comprehensive questionnaire. The questionnaire included questions on demographic information, disease history, and detailed understanding about the indications for DBS, side effects, outlook, and other common misconceptions. We summarize data using measures of central tendency and dispersion appropriate to the data type (categorical, continuous, proportional) and model relationships among variables using fractional and linear regression methods.

Results

Participants had a median age of 66 years, were predominantly male (66%), Caucasian (90%), well-educated (79% with at least college degrees), and had a disease duration of greater than 5 years (97%). They conveyed good understanding of the signs and symptoms addressed by DBS across the motor and non-motor domains and associated side effects. Regression analysis identified age, disease duration, and education level as key determinants of patient understanding and outlook of DBS.

Conclusion

Our study provides a detailed understanding of patient perceptions of DBS for PD, including the benefits, challenges, and misconceptions. Our findings underscore the importance of identifying the causes of disparities in patient knowledge and perceptions regarding DBS to tailor patient counseling and ensure optimal treatment outcomes.

Connectivity-based segmentation of the thalamic motor region for deep brain stimulation in essential tremor: A comparison of deterministic and probabilistic tractography

OBJECTIVE

Deep brain stimulation (DBS) studies have shown that stimulation of the motor segment of the thalamus based on probabilistic tractography is predictive of improvement in essential tremor (ET). However, probabilistic methods are computationally demanding, requiring the need for alternative tractography methods for use in the clinical setting. The purpose of this study was to compare probabilistic vs deterministic tractography methods for connectivity-based targeting in patients with ET.

METHODS

Probabilistic and deterministic tractography methods were retrospectively applied to diffusion-weighted data sets in 36 patients with refractory ET. The thalamus and precentral gyrus were selected as regions of interest and fiber tracking was performed between these regions to produce connectivity-based thalamic segmentations, per prior methods. The resultant deterministic target maps were compared with those of thresholded probabilistic maps. The center of gravity (CG) of each connectivity map was determined and the differences in spatial distribution between the tractography methods were characterized. Furthermore, the intersection between the connectivity maps and CGs with the therapeutic volume of tissue activated (VTA) was calculated. A mixed linear model was then used to assess clinical improvement in tremor with volume of overlap.

RESULTS

Both tractography methods delineated the region of the thalamus with connectivity to the precentral gyrus to be within the posterolateral aspect of the thalamus. The average CG of deterministic maps was more medial-posterior in both the left (3.7 ± 1.3 mm3) and the right (3.5 ± 2.2 mm3) hemispheres when compared to 30 %-thresholded probabilistic maps. Mixed linear model showed that the volume of overlap between CGs of deterministic and probabilistic targeting maps and therapeutic VTAs were significant predictors of clinical improvement.

CONCLUSIONS

Deterministic tractography can reconstruct DBS thalamic target maps in approximately 5 min comparable to those produced by probabilistic methods that require > 12 h to generate. Despite differences in CG between the methods, both deterministic-based and probabilistic targeting were predictive of clinical improvement in ET.

Proceedings of the 11th Annual Deep Brain Stimulation Think Tank: pushing the forefront of neuromodulation with functional network mapping, biomarkers for adaptive DBS, bioethical dilemmas, AI-guided neuromodulation, and translational advancements

The Deep Brain Stimulation (DBS) Think Tank XI was held on August 9-11, 2023 in Gainesville, Florida with the theme of "Pushing the Forefront of Neuromodulation". The keynote speaker was Dr. Nico Dosenbach from Washington University in St. Louis, Missouri. He presented his research recently published in Nature inn a collaboration with Dr. Evan Gordon to identify and characterize the somato-cognitive action network (SCAN), which has redefined the motor homunculus and has led to new hypotheses about the integrative networks underpinning therapeutic DBS. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers, and researchers (from industry and academia) can freely discuss current and emerging DBS technologies, as well as logistical and ethical issues facing the field. The group estimated that globally more than 263,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: cutting-edge translational neuromodulation, cutting-edge physiology, advances in neuromodulation from Europe and Asia, neuroethical dilemmas, artificial intelligence and computational modeling, time scales in DBS for mood disorders, and advances in future neuromodulation devices.

Longitudinal prognosis of Parkinson's outcomes using causal connectivity

Despite the prevalence of Parkinson's disease (PD), there are no clinically-accepted neuroimaging biomarkers to predict the trajectory of motor or cognitive decline or differentiate Parkinson's disease from atypical progressive parkinsonian diseases. Since abnormal connectivity in the motor circuit and basal ganglia have been previously shown as early markers of neurodegeneration, we hypothesize that patterns of interregional connectivity could be useful to form patient-specific predictive models of disease state and of PD progression. We use fMRI data from subjects with Multiple System Atrophy (MSA), Progressive Supranuclear Palsy (PSP), idiopathic PD, and healthy controls to construct predictive models for motor and cognitive decline and differentiate between the four subgroups. Further, we identify the specific connections most informative for progression and diagnosis. When predicting the one-year progression in the MDS-UPDRS-III1* and Montreal Cognitive assessment (MoCA), we achieve new state-of-the-art mean absolute error performance. Additionally, the balanced accuracy we achieve in the diagnosis of PD, MSA, PSP, versus healthy controls surpasses that attained in most clinics, underscoring the relevance of the brain connectivity features. Our models reveal the connectivity between deep nuclei, motor regions, and the thalamus as the most important for prediction. Collectively these results demonstrate the potential of fMRI connectivity as a prognostic biomarker for PD and increase our understanding of this disease.

Small pretreatment lesion size and high sphericity as favorable prognostic factors after laser interstitial thermal therapy in brain metastases

OBJECTIVE

The objective of this study was to identify baseline clinical and radiological characteristics of brain metastases (BMs) associated with a higher probability of lesion-specific progression-free survival (PFS-L) after laser interstitial thermal therapy (LITT).

METHODS

A total of 47 lesions in 42 patients with BMs treated with LITT were retrospectively examined, including newly diagnosed BM, suspected recurrent BM, and suspected radiation necrosis. The association of baseline clinical and radiological features with PFS-L was assessed using survival analyses. Radiological features included lesion size measurements, diffusion and perfusion metrics, and sphericity, which is a radiomic feature ranging from 1 (perfect sphere) to 0.

RESULTS

The probability of PFS-L for the entire cohort was 88.0% at 3 months, 70.6% at 6 months, 67.4% at 1 and 2 years, and 62.2% at 3 years. For lesions progressing after LITT (n = 13), the median time to progression was 3.9 months, and most lesions (n = 11) progressed within 6 months after LITT. In lesions showing response to LITT (n = 17), the median time to response was 12.1 months. All 3 newly diagnosed BMs showed a long-term response. The mean (± SD) follow-up duration for all censored lesions (n = 34) was 20.7 ± 19.4 months (range 12 days to 6.1 years). The mean pretreatment enhancing volume was 2.68 cm3 and the mean sphericity was 0.70. Pretreatment small enhancing volume (p = 0.003) and high sphericity (p = 0.024) computed from lesion segmentation predicted a longer PFS-L after LITT. Lesions meeting optimal cutoffs of either enhancing volume < 2.5 cm3 (adjusted p = 0.004) or sphericity ≥ 0.705 (adjusted p = 0.019) had longer PFS-L, and their probability of PFS-L was 86.8% at 3 years. Lesions meeting both cutoffs showed a cumulative benefit (p < 0.0001), with a 100% probability of PFS-L at 3 years, which was unchanged at the end of follow-up (4.1 years). Manually computed estimates of lesion size (maximal axial diameter, p = 0.011) and sphericity (p = 0.043) were also predictors of PFS-L. Optimal cutoffs of diameter < 2 cm (adjusted p = 0.035) or manual sphericity ≥ 0.91 (adjusted p = 0.092) identified lesions with longer PFS-L, and lesions meeting both cutoffs showed a cumulative benefit (p = 0.0023). Baseline diffusion imaging did not predict PFS-L. A subset of lesions (n = 7) with highly perfused hotspots had worse PFS-L (adjusted p = 0.010), but perfusion signal contamination from vessels and cortex and underlying size differences were possible confounders.

CONCLUSIONS

Small size and high sphericity are ideal baseline features for lesions considered for LITT treatment, with a cumulative PFS-L benefit when both features are present, that could aid patient selection.

Prefrontal network engagement by deep brain stimulation in limbic hubs

Prefrontal circuits in the human brain play an important role in cognitive and affective processing. Neuromodulation therapies delivered to certain key hubs within these circuits are being used with increasing frequency to treat a host of neuropsychiatric disorders. However, the detailed neurophysiological effects of stimulation to these hubs are largely unknown. Here, we performed intracranial recordings across prefrontal networks while delivering electrical stimulation to two well-established white matter hubs involved in cognitive regulation and depression: the subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VC/VS). We demonstrate a shared frontotemporal circuit consisting of the ventromedial prefrontal cortex, amygdala, and lateral orbitofrontal cortex where gamma oscillations are differentially modulated by stimulation target. Additionally, we found participant-specific responses to stimulation in the dorsal anterior cingulate cortex and demonstrate the capacity for further tuning of neural activity using current-steered stimulation. Our findings indicate a potential neurophysiological mechanism for the dissociable therapeutic effects seen across the SCC and VC/VS targets for psychiatric neuromodulation and our results lay the groundwork for personalized, network-guided neurostimulation therapy.

Evaluating Deep Learning Performance for P300 Neural Signal Classification

P300 event-related potential (ERP) signals are useful neurological biomarkers, and their accurate classification is important when studying the cognitive functions in patients with neurological disorders. While many studies have proposed models for classifying these signals, results have been inconsistent. As a result, a consensus has not yet been reached on the optimal model for this classification. In this study, we evaluated the performance of classic machine learning and novel deep learning methods for P300 signal classification in both within and across subject training scenarios across a dataset of 75 subjects. Although the deep learning models attained high attended event classification F1 scores, they did not outperform Stepwise Linear Discriminant Analysis (SWLDA) in the within-subject paradigm. In the across-subject paradigm, however, EEG-Inception was able to significantly outperform SWLDA. These results suggest that deep learning models may provide a general model that do not require subject-specific training and calibration in clinical settings.

Criticality supports cross-frequency cortical-thalamic information transfer during conscious states

Consciousness is thought to be regulated by bidirectional information transfer between the cortex and thalamus, but the nature of this bidirectional communication - and its possible disruption in unconsciousness - remains poorly understood. Here, we present two main findings elucidating mechanisms of corticothalamic information transfer during conscious states. First, we identify a highly preserved spectral channel of cortical-thalamic communication that is present during conscious states, but which is diminished during the loss of consciousness and enhanced during psychedelic states. Specifically, we show that in humans, mice, and rats, information sent from either the cortex or thalamus via δ/θ/α waves (∼1-13 Hz) is consistently encoded by the other brain region by high γ waves (52-104 Hz); moreover, unconsciousness induced by propofol anesthesia or generalized spike-and-wave seizures diminishes this cross-frequency communication, whereas the psychedelic 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) enhances this low-to-high frequency interregional communication. Second, we leverage numerical simulations and neural electrophysiology recordings from the thalamus and cortex of human patients, rats, and mice to show that these changes in cross-frequency cortical-thalamic information transfer may be mediated by excursions of low-frequency thalamocortical electrodynamics toward/away from edge-of-chaos criticality, or the phase transition from stability to chaos. Overall, our findings link thalamic-cortical communication to consciousness, and further offer a novel, mathematically well-defined framework to explain the disruption to thalamic-cortical information transfer during unconscious states.

Benefits of sharing neurophysiology data from the BRAIN Initiative Research Opportunities in Humans Consortium

Sharing human brain data can yield scientific benefits, but because of various disincentives, only a fraction of these data is currently shared. We profile three successful data-sharing experiences from the NIH BRAIN Initiative Research Opportunities in Humans (ROH) Consortium and demonstrate benefits to data producers and to users.

Stereotactic radiosurgery in the management of non-small cell lung cancer brain metastases: a prospective study using the NeuroPoint Alliance Stereotactic Radiosurgery Registry

OBJECTIVE

The literature on non-small cell lung cancer (NSCLC) brain metastases (BMs) managed using stereotactic radiosurgery (SRS) relies mainly on single-institution studies or randomized controlled trials (RCTs). There is a literature gap on clinical and radiological outcomes of SRS for NSCLC metastases in real-world practice. The objective of this study was to benchmark mortality and progression outcomes in patients undergoing SRS for NSCLC BMs and identify risk factors for these outcomes using a national quality registry.

METHODS

The SRS Registry of the NeuroPoint Alliance was used for this study. This registry included patients from 16 enrolling sites who underwent SRS from 2017 to 2022. Data are prospectively collected without a prespecified research purpose. The main outcomes of this analysis were overall survival (OS), out-of-field recurrence, local progression, and intracranial progression. All time-to-event investigations included Kaplan-Meier analyses and multivariable Cox regressions.

RESULTS

Two hundred sixty-four patients were identified, with a mean age of 66.7 years and a female proportion of 48.5%. Most patients (84.5%) had a Karnofsky Performance Status (KPS) score of 80-100, and the mean baseline EQ-5D score was 0.539 quality-adjusted life years. A single lesion was present in 53.4% of the patients, and 29.1% of patients had 3 or more lesions. The median OS was 28.1 months, and independent predictors of mortality included no control of primary tumor (hazard ratio [HR] 2.1), KPS of 80 (HR 2.4) or lower (HR 2.4), coronary artery disease (HR 2.8), and 5 or more lesions present at the time of SRS treatment (HR 2.3). The median out-of-field progression-free survival (PFS) was 24.8 months, and the median local PFS was unreached. Intralesional hemorrhage was an independent risk factor of local progression, with an HR of 6.0. The median intracranial PFS was 14.0 months and was predicted by the number of lesions at the time of SRS (3-4 lesions, HR 2.2; 5-14 lesions, HR 2.5).

CONCLUSIONS

In this real-world prospective study, the authors used a national quality registry and found favorable OS in patients with NSCLC BMs undergoing SRS compared with results from previously published RCTs. The intracranial PFS was mainly driven by the emergence of new lesions rather than local progression. A greater number of lesions at baseline was associated with out-of-field progression, while intralesional hemorrhage at baseline was associated with local progression.

Aperiodic neural activity is a biomarker for depression severity

A reliable physiological biomarker for Major Depressive Disorder (MDD) is necessary to improve treatment success rates by shoring up variability in outcome measures. In this study, we establish a passive biomarker that tracks with changes in mood on the order of minutes to hours. We record from intracranial electrodes implanted deep in the brain - a surgical setting providing exquisite temporal and spatial sensitivity to detect this relationship in a difficult-to-measure brain area, the ventromedial prefrontal cortex (VMPFC). The aperiodic slope of the power spectral density captures the balance of activity across all frequency bands and is construed as a putative proxy for excitatory/inhibitory balance in the brain. This study demonstrates how shifts in aperiodic slope correlate with depression severity in a clinical trial of deep brain stimulation for treatment-resistant depression (TRD). The correlation between depression severity scores and aperiodic slope is significant in N=5 subjects, indicating that flatter (less negative) slopes correspond to reduced depression severity, especially in the ventromedial prefrontal cortex. This biomarker offers a new way to track patient response to MDD treatment, facilitating individualized therapies in both intracranial and non-invasive monitoring scenarios.

Computational mechanism underlying switching of motor actions

Surviving in a constantly changing environment requires not only the ability to select actions, but also the flexibility to stop and switch actions when necessary. Extensive research has been devoted to understanding how the brain switches actions, yet the computations underlying switching and how it relates to selecting and stopping processes remain elusive. A central question is whether switching is an extension of the stopping process or involves different mechanisms. To address this question, we modeled action regulation tasks with a neurocomputational theory and evaluated its predictions on individuals performing reaches in a dynamic environment. Our findings suggest that, unlike stopping, switching does not necessitate a proactive pause mechanism to delay movement onset. However, switching engages a pause mechanism after movement onset, if the new target location is unknown prior to switch signal. These findings offer a new understanding of the action-switching computations, opening new avenues for future neurophysiological investigations.

Stereo-EEG-guided network modulation for psychiatric disorders: Surgical considerations

BACKGROUND

Deep brain stimulation (DBS) and other neuromodulatory techniques are being increasingly utilized to treat refractory neurologic and psychiatric disorders.

OBJECTIVE

/Hypothesis: To better understand the circuit-level pathophysiology of treatment-resistant depression (TRD) and treat the network-level dysfunction inherent to this challenging disorder, we adopted an approach of inpatient intracranial monitoring borrowed from the epilepsy surgery field.

METHODS

We implanted 3 patients with 4 DBS leads (bilateral pair in both the ventral capsule/ventral striatum and subcallosal cingulate) and 10 stereo-electroencephalography (sEEG) electrodes targeting depression-relevant network regions. For surgical planning, we used an interactive, holographic visualization platform to appreciate the 3D anatomy and connectivity. In the initial surgery, we placed the DBS leads and sEEG electrodes using robotic stereotaxy. Subjects were then admitted to an inpatient monitoring unit for depression-specific neurophysiological assessments. Following these investigations, subjects returned to the OR to remove the sEEG electrodes and internalize the DBS leads to implanted pulse generators.

RESULTS

Intraoperative testing revealed positive valence responses in all 3 subjects that helped verify targeting. Given the importance of the network-based hypotheses we were testing, we required accurate adherence to the surgical plan (to engage DBS and sEEG targets) and stability of DBS lead rotational position (to ensure that stimulation field estimates of the directional leads used during inpatient monitoring were relevant chronically), both of which we confirmed (mean radial error 1.2±0.9 mm; mean rotation 3.6±2.6°).

CONCLUSION

This novel hybrid sEEG-DBS approach allows detailed study of the neurophysiological substrates of complex neuropsychiatric disorders.

Stereo-EEG-guided network modulation for psychiatric disorders: Interactive holographic planning

BACKGROUND

Connectomic modeling studies are expanding understanding of the brain networks that are modulated by deep brain stimulation (DBS) therapies. However, explicit integration of these modeling results into prospective neurosurgical planning is only beginning to evolve. One challenge of employing connectomic models in patient-specific surgical planning is the inherent 3D nature of the results, which can make clinically useful data integration and visualization difficult.

METHODS

We developed a holographic stereotactic neurosurgery research tool (HoloSNS) that integrates patient-specific brain models into a group-based visualization environment for interactive surgical planning using connectomic hypotheses. HoloSNS currently runs on the HoloLens 2 platform and it enables remote networking between headsets. This allowed us to perform surgical planning group meetings with study co-investigators distributed across the country.

RESULTS

We used HoloSNS to plan stereo-EEG and DBS electrode placements for each patient participating in a clinical trial (NCT03437928) that is targeting both the subcallosal cingulate and ventral capsule for the treatment of depression. Each patient model consisted of multiple components of scientific data and anatomical reconstructions of the head and brain (both patient-specific and atlas-based), which far exceed the data integration capabilities of traditional neurosurgical planning workstations. This allowed us to prospectively discuss and evaluate the positioning of the electrodes based on novel connectomic hypotheses.

CONCLUSIONS

The 3D nature of the surgical procedure, brain imaging data, and connectomic modeling results all highlighted the utility of employing holographic visualization to support the design of unique clinical experiments to explore brain network modulation with DBS.

A comparison of neuroelectrophysiology databases

As data sharing has become more prevalent, three pillars - archives, standards, and analysis tools - have emerged as critical components in facilitating effective data sharing and collaboration. This paper compares four freely available intracranial neuroelectrophysiology data repositories: Data Archive for the BRAIN Initiative (DABI), Distributed Archives for Neurophysiology Data Integration (DANDI), OpenNeuro, and Brain-CODE. The aim of this review is to describe archives that provide researchers with tools to store, share, and reanalyze both human and non-human neurophysiology data based on criteria that are of interest to the neuroscientific community. The Brain Imaging Data Structure (BIDS) and Neurodata Without Borders (NWB) are utilized by these archives to make data more accessible to researchers by implementing a common standard. As the necessity for integrating large-scale analysis into data repository platforms continues to grow within the neuroscientific community, this article will highlight the various analytical and customizable tools developed within the chosen archives that may advance the field of neuroinformatics.

Disentangling Function from Benefit: Participant Perspectives from an Early Feasibility Trial for a Novel Visual Cortical Prosthesis

Visual cortical prostheses (VCPs) have the potential to provide artificial vision for visually impaired persons. However, the nature and utility of this form of vision is not yet fully understood. Participants in the early feasibility trial for the Orion VCP were interviewed to gain insight into their experiences using artificial vision, their motivations for participation, as well as their expectations and assessments of risks and benefits. Analyzed using principles of grounded theory and an interpretive description approach, these interviews yielded six themes, including: the irreducibility of benefit to device functionality, mixed expectations for short-term device functionality and long-term technological advancement of visual prostheses, and a broad range of risks, concerns, and fears related to trial participation. We argue that these narratives motivate a nuanced set of ethical considerations related to the complex relationship between functionality and benefit, the intersection of user experience with disability justice, and the import of expectations and indirect risks on consent.

Decoding Depression Severity From Intracranial Neural Activity

BACKGROUND

Disorders of mood and cognition are prevalent, disabling, and notoriously difficult to treat. Fueling this challenge in treatment is a significant gap in our understanding of their neurophysiological basis.

METHODS

We recorded high-density neural activity from intracranial electrodes implanted in depression-relevant prefrontal cortical regions in 3 human subjects with severe depression. Neural recordings were labeled with depression severity scores across a wide dynamic range using an adaptive assessment that allowed sampling with a temporal frequency greater than that possible with typical rating scales. We modeled these data using regularized regression techniques with region selection to decode depression severity from the prefrontal recordings.

RESULTS

Across prefrontal regions, we found that reduced depression severity is associated with decreased low-frequency neural activity and increased high-frequency activity. When constraining our model to decode using a single region, spectral changes in the anterior cingulate cortex best predicted depression severity in all 3 subjects. Relaxing this constraint revealed unique, individual-specific sets of spatiospectral features predictive of symptom severity, reflecting the heterogeneous nature of depression.

CONCLUSIONS

The ability to decode depression severity from neural activity increases our fundamental understanding of how depression manifests in the human brain and provides a target neural signature for personalized neuromodulation therapies.

A Comparison of Neuroelectrophysiology Databases

As data sharing has become more prevalent, three pillars - archives, standards, and analysis tools - have emerged as critical components in facilitating effective data sharing and collaboration. This paper compares four freely available intracranial neuroelectrophysiology data repositories: Data Archive for the BRAIN Initiative (DABI), Distributed Archives for Neurophysiology Data Integration (DANDI), OpenNeuro, and Brain-CODE. The aim of this review is to describe archives that provide researchers with tools to store, share, and reanalyze both human and non-human neurophysiology data based on criteria that are of interest to the neuroscientific community. The Brain Imaging Data Structure (BIDS) and Neurodata Without Borders (NWB) are utilized by these archives to make data more accessible to researchers by implementing a common standard. As the necessity for integrating large-scale analysis into data repository platforms continues to grow within the neuroscientific community, this article will highlight the various analytical and customizable tools developed within the chosen archives that may advance the field of neuroinformatics.

Brain mechanisms underlying the emotion processing bias in treatment-resistant depression

Depression is associated with a cognitive bias towards negative information and away from positive information. This biased emotion processing may underlie core depression symptoms, including persistent feelings of sadness or low mood and a reduced capacity to experience pleasure. The neural mechanisms responsible for this biased emotion processing remain unknown. Here, we had a unique opportunity to record stereotactic electroencephalography (sEEG) signals in the amygdala and prefrontal cortex (PFC) from 5 treatment-resistant depression (TRD) patients and 12 epilepsy patients (as control) while they participated in an affective bias task in which happy and sad faces were rated. First, compared with the control group, patients with TRD showed increased amygdala responses to sad faces in the early stage (around 300 ms) and decreased amygdala responses to happy faces in the late stage (around 600 ms) following the onset of faces. Further, during the late stage of happy face processing, alpha-band activity in PFC as well as alpha-phase locking between the amygdala and PFC were significantly greater in TRD patients compared to the controls. Second, after deep brain stimulation (DBS) delivered to bilateral subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VC/VS), atypical amygdala and PFC processing of happy faces in TRD patients remitted toward the normative pattern. The increased amygdala activation during the early stage of sad face processing suggests an overactive bottom-up processing system in TRD. Meanwhile, the reduced amygdala response during the late stage of happy face processing could be attributed to inhibition by PFC through alpha-band oscillation, which can be released by DBS in SCC and VC/VS.

Exaggerated High-Beta Oscillations are Associated with Cortical Thinning at the Motor Cortex in Parkinson's Disease

Elevated β oscillations (13-35 Hz) are characteristic pathophysiology in Parkinson's Disease (PD). Cortical thinning has also been reported in the disease, however the relationship between these biomarkers of PD has not been established. By comparing electrophysiological measurements with cortical thickness, this study aims to reveal the pathoetiology of disease and symptoms in PD. Preoperative magnetic resonance imaging (MRI) and intraoperative local field potentials (LFPs) were collected from 34 subjects diagnosed with PD. Cortical surfaces were reconstructed from the images, and cortical thickness was extracted from the subregions where the recording electrode was placed in M1. LFPs were preprocessed and cleaned using a semiautomatic artifact detection algorithm, then power spectral densities (PSD) were computed and periodic and aperiodic frequency components were calculated. Nonparametric Spearman rank correlations assessed the relationship between electrophysiological components (i.e. center frequency (CF), power, bandwidth, 1/f exponent, knee), with cortical thickness. According to the CF of each subject's PSD, the cohort was split into two sub-groups: low-β peak (13-20 Hz) and high-β peak (20-35 Hz) groups. There was a significant negative correlation between power and cortical thickness only in the high-β subgroup (r=-0.48, p(corrected)=0.049). This relationship remained significant when correcting for age (r=-0.52,p=0.015), indicating that the effect of age on cortical thinning was not the determining factor. We did not find significant differences between UPDRS-III motor symptom scores for the low-and high-β subgroups. Of note is the dominance of high-β oscillatory power and its relationship with cortical thickness. As suggested by the literature, increased high-β activity during movement may be exaggerated in PD. These findings suggest that the characteristic cortical thinning in PD causes variation in electrical activity, leading to elevated high-β activity.Clinical relevance- This multimodal study provides additional insights on the pathophysiology and its relevance with morphology of Parkinson's Disease.

Decoding and geometry of ten finger movements in human posterior parietal cortex and motor cortex

Objective. Enable neural control of individual prosthetic fingers for participants with upper-limb paralysis.Approach. Two tetraplegic participants were each implanted with a 96-channel array in the left posterior parietal cortex (PPC). One of the participants was additionally implanted with a 96-channel array near the hand knob of the left motor cortex (MC). Across tens of sessions, we recorded neural activity while the participants attempted to move individual fingers of the right hand. Offline, we classified attempted finger movements from neural firing rates using linear discriminant analysis with cross-validation. The participants then used the neural classifier online to control individual fingers of a brain-machine interface (BMI). Finally, we characterized the neural representational geometry during individual finger movements of both hands.Main Results. The two participants achieved 86% and 92% online accuracy during BMI control of the contralateral fingers (chance = 17%). Offline, a linear decoder achieved ten-finger decoding accuracies of 70% and 66% using respective PPC recordings and 75% using MC recordings (chance = 10%). In MC and in one PPC array, a factorized code linked corresponding finger movements of the contralateral and ipsilateral hands.Significance. This is the first study to decode both contralateral and ipsilateral finger movements from PPC. Online BMI control of contralateral fingers exceeded that of previous finger BMIs. PPC and MC signals can be used to control individual prosthetic fingers, which may contribute to a hand restoration strategy for people with tetraplegia.

Future directions in psychiatric neurosurgery: Proceedings of the 2022 American Society for Stereotactic and Functional Neurosurgery meeting on surgical neuromodulation for psychiatric disorders

OBJECTIVE

Despite advances in the treatment of psychiatric diseases, currently available therapies do not provide sufficient and durable relief for as many as 30-40% of patients. Neuromodulation, including deep brain stimulation (DBS), has emerged as a potential therapy for persistent disabling disease, however it has not yet gained widespread adoption. In 2016, the American Society for Stereotactic and Functional Neurosurgery (ASSFN) convened a meeting with leaders in the field to discuss a roadmap for the path forward. A follow-up meeting in 2022 aimed to review the current state of the field and to identify critical barriers and milestones for progress.

DESIGN

The ASSFN convened a meeting on June 3, 2022 in Atlanta, Georgia and included leaders from the fields of neurology, neurosurgery, and psychiatry along with colleagues from industry, government, ethics, and law. The goal was to review the current state of the field, assess for advances or setbacks in the interim six years, and suggest a future path forward. The participants focused on five areas of interest: interdisciplinary engagement, regulatory pathways and trial design, disease biomarkers, ethics of psychiatric surgery, and resource allocation/prioritization. The proceedings are summarized here.

CONCLUSION

The field of surgical psychiatry has made significant progress since our last expert meeting. Although weakness and threats to the development of novel surgical therapies exist, the identified strengths and opportunities promise to move the field through methodically rigorous and biologically-based approaches. The experts agree that ethics, law, patient engagement, and multidisciplinary teams will be critical to any potential growth in this area.

Two Practices to Improve Informed Consent for Intraoperative Brain Research

As the clinical applications of neurologically implanted devices increase, so do opportunities for intracranial investigations in human patients. In some of these studies, patients participate in research during their awake brain surgery, performing additional tasks without the prospect of personal therapeutic benefit. These intraoperative studies raise persistent ethical challenges because they are conducted during a clinical intervention, in a clinical space, and often by the treating clinician. Whether intraoperative research necessitates innovative informed consent methods has become a pressing conversation. Familiar worries about inadequate participant understanding and undue influence dominate these discussions, as do calls for increasing information retention (e.g., using methods such as "teach-back") and minimizing enrollment pressures (e.g., preventing surgeons from consenting their own patients). However, efforts have yet to inspire widespread consent practices that mirror the scope of ethical concern. Focusing on awake, intraoperative intracranial research, we identify 2 underappreciated problems in approaches to informed consent. The first is epistemic: Many practices do not fully consider when and under which conditions participants are adequately informed. The second is relational: Many practices do not fully consider the effects of trust between patient-participants and surgeon-researchers. In exploring these concerns, we also raise questions about whether additional steps beyond preoperative consent may improve the process because decisions at this time are decoupled from both the experiences and vulnerability of awake brain surgery. Motivated by these considerations, we propose 2 practices: first, requiring a third-party patient advocate in initial consent and second, requiring verbal intraoperative reconsent before initiating research.

"They were already inside my head to begin with": Trust, Translational Misconception, and Intraoperative Brain Research

Background: Patients undergoing invasive neurosurgical procedures offer researchers unique opportunities to study the brain. Deep brain stimulation patients, for example, may participate in research during the surgical implantation of the stimulator device. Although this research raises many ethical concerns, little attention has been paid to basic studies, which offer no therapeutic benefits, and the value of patient-participant perspectives.Methods: Semi-structured interviews were conducted with fourteen individuals across two studies who participated in basic intraoperative research during their deep brain stimulator surgery. Interviews explored interpretations of risks and benefits, enrollment motivations, and experiences of participating in awake brain research. Reflexive thematic analysis was conducted.Results: Seven themes were identified from participant narratives, including robust attitudes of trust, high valuations of basic science research, impacts of the surgical context, and mixed experiences of participation.Conclusion: We argue that these narratives raise the potential for a translational misconception and motivate intraoperative re-consent procedures.

Connectivity-based parcellation of the amygdala and identification of its main white matter connections

The amygdala plays a role in emotion, learning, and memory and has been implicated in behavioral disorders. Better understanding of the amygdala circuitry is crucial to develop new therapies for these disorders. We used data from 200 healthy-subjects from the human connectome project. Using probabilistic tractography, we created population statistical maps of amygdala connectivity to brain regions involved in limbic, associative, memory, and reward circuits. Based on the amygdala connectivity with these regions, we applied k-means clustering to parcellate the amygdala into three clusters. The resultant clusters were averaged across all subjects and the main white-matter pathways of the amygdala from each averaged cluster were generated. Amygdala parcellation into three clusters showed a medial-to-lateral pattern. The medial cluster corresponded with the centromedial and cortical nuclei, the basal cluster with the basal nuclei and the lateral cluster with the lateral nuclei. The connectivity analysis revealed different white-matter pathways consistent with the anatomy of the amygdala circuit. This in vivo connectivity-based parcellation of the amygdala delineates three clusters of the amygdala in a mediolateral pattern based on its connectivity with brain areas involved in cognition, memory, emotion, and reward. The human amygdala circuit presented in this work provides the first step for personalized amygdala circuit mapping for patients with behavioral disorders.

Focused ultrasound using a novel targeting method four-tract tractography for magnetic resonance-guided high-intensity focused ultrasound targeting

Magnetic resonance-guided high-intensity focused ultrasound thalamotomy is a Food and Drug Administration-approved treatment for essential tremor. The target, the ventral intermediate nucleus of the thalamus, is not visualized on standard, anatomic MRI sequences. Several recent reports have used diffusion tensor imaging to target the dentato-rubro-thalamic-tract. There is considerable variability in fibre tracking algorithms and what fibres are tracked. Targeting discrete white matter tracts with magnetic resonance-guided high-intensity focused ultrasound is an emerging precision medicine technique that has the promise to improve patient outcomes and reduce treatment times. We provide a technical overview and clinical benefits of our novel, easily implemented advanced tractography method: four-tract tractography. Our method is novel because it targets both the decussating and non-decussating dentato-rubro-thalamic-tracts while avoiding the medial lemniscus and corticospinal tracts. Our method utilizes Food and Drug Administration-approved software and is easily implementable into existing workflows. Initial experience using this approach suggests that it improves patient outcomes by reducing the incidence of adverse effects.

Stability of motor representations after paralysis

Neural plasticity allows us to learn skills and incorporate new experiences. What happens when our lived experiences fundamentally change, such as after a severe injury? To address this question, we analyzed intracortical population activity in the posterior parietal cortex (PPC) of a tetraplegic adult as she controlled a virtual hand through a brain–computer interface (BCI). By attempting to move her fingers, she could accurately drive the corresponding virtual fingers. Neural activity during finger movements exhibited robust representational structure similar to fMRI recordings of able-bodied individuals’ motor cortex, which is known to reflect able-bodied usage patterns. The finger representational structure was consistent throughout multiple sessions, even though the structure contributed to BCI decoding errors. Within individual BCI movements, the representational structure was dynamic, first resembling muscle activation patterns and then resembling the anticipated sensory consequences. Our results reveal that motor representations in PPC reflect able-bodied motor usage patterns even after paralysis, and BCIs can re-engage these stable representations to restore lost motor functions.

Deep Brain Stimulation for Depression Informed by Intracranial Recordings

The success of deep brain stimulation (DBS) for treating Parkinson's disease has led to its application to several other disorders, including treatment-resistant depression. Results with DBS for treatment-resistant depression have been heterogeneous, with inconsistencies largely driven by incomplete understanding of the brain networks regulating mood, especially on an individual basis. We report results from the first subject treated with DBS for treatment-resistant depression using an approach that incorporates intracranial recordings to personalize understanding of network behavior and its response to stimulation. These recordings enabled calculation of individually optimized DBS stimulation parameters using a novel inverse solution approach. In the ensuing double-blind, randomized phase incorporating these bespoke parameter sets, DBS led to remission of symptoms and dramatic improvement in quality of life. Results from this initial case demonstrate the feasibility of this personalized platform, which may be used to improve surgical neuromodulation for a vast array of neurologic and psychiatric disorders.

Automated optimization of deep brain stimulation parameters for modulating neuroimaging-based targets

Objective.Therapeutic efficacy of deep brain stimulation (DBS) in both established and emerging indications, is highly dependent on accurate lead placement and optimized clinical programming. The latter relies on clinicians' experience to search among available sets of stimulation parameters and can be limited by the time constraints of clinical practice. Recent innovations in device technology have expanded the number of possible electrode configurations and parameter sets available to clinicians, amplifying the challenge of time constraints. We hypothesize that patient specific neuroimaging data can effectively assist the clinical programming using automated algorithms.Approach.This paper introduces the DBS Illumina 3D algorithm as a tool which uses patient-specific imaging to find stimulation settings that optimizes activating a target area while minimizing the stimulation of areas outside the target that could result in unknown or undesired side effects. This approach utilizes preoperative neuroimaging data paired with the postoperative reconstruction of the lead trajectory to search the available stimulation space and identify optimized stimulation parameters. We describe the application of this algorithm in three patients with treatment-resistant depression who underwent bilateral implantation of DBS in subcallosal cingulate cortex and ventral capsule/ventral striatum using tractography optimized targeting with an imaging defined target previously described.Main results.Compared to the stimulation settings selected by the clinicians (informed by anatomy), stimulation settings produced by the algorithm that achieved similar or greater target coverage, produced a significantly smaller stimulation area that spilled outside the target (P= 0.002).Significance. The DBS Illumina 3D algorithm is seamlessly integrated with the clinician programmer software and effectively and rapidly assists clinicians with the analysis of image based anatomy, and provides a starting point to search the highly complex stimulation parameter space and arrive at the stimulation settings that optimize activating a target area.

Imaging versus electrographic connectivity in human mood-related fronto-temporal networks

BACKGROUND

The efficacy of psychiatric DBS is thought to be driven by the connectivity of stimulation targets with mood-relevant fronto-temporal networks, which is typically evaluated using diffusion-weighted tractography.

OBJECTIVE

Leverage intracranial electrophysiology recordings to better predict the circuit-wide effects of neuromodulation to white matter targets. We hypothesize strong convergence between tractography-predicted structural connectivity and stimulation-induced electrophysiological responses.

METHODS

Evoked potentials were elicited by single-pulse stimulation to two common DBS targets for treatment-resistant depression - the subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VCVS) - in two patients undergoing DBS with stereo-electroencephalographic (sEEG) monitoring. Evoked potentials were compared with predicted structural connectivity between DBS leads and sEEG contacts using probabilistic, patient-specific diffusion-weighted tractography.

RESULTS

Evoked potentials and tractography showed strong convergence in both patients in orbitofrontal, ventromedial prefrontal, and lateral prefrontal cortices for both SCC and VCVS stimulation targets. Low convergence was found in anterior cingulate (ACC), where tractography predicted structural connectivity from SCC targets but produced no evoked potentials during SCC stimulation. Further, tractography predicted no connectivity to ACC from VCVS targets, but VCVS stimulation produced robust evoked potentials.

CONCLUSION

The two connectivity methods showed significant convergence, but important differences emerged with respect to the ability of tractography to predict electrophysiological connectivity between SCC and VCVS to regions of the mood-related network. This multimodal approach raises intriguing implications for the use of tractography in surgical targeting and provides new data to enhance our understanding of the network-wide effects of neuromodulation.

Implicit mechanisms of intention

High-level cortical regions encode motor decisions before or even absent awareness, suggesting that neural processes predetermine behavior before conscious choice. Such early neural encoding challenges popular conceptions of human agency. It also raises fundamental questions for brain-machine interfaces (BMIs) that traditionally assume that neural activity reflects the user's conscious intentions. Here, we study the timing of human posterior parietal cortex single-neuron activity recorded from implanted microelectrode arrays relative to the explicit urge to initiate movement. Participants were free to choose when to move, whether to move, and what to move, and they retrospectively reported the time they felt the urge to move. We replicate prior studies by showing that posterior parietal cortex (PPC) neural activity sharply rises hundreds of milliseconds before the reported urge. However, we find that this "preconscious" activity is part of a dynamic neural population response that initiates much earlier, when the participant first chooses to perform the task. Together with details of neural timing, our results suggest that PPC encodes an internal model of the motor planning network that transforms high-level task objectives into appropriate motor behavior. These new data challenge traditional interpretations of early neural activity and offer a more holistic perspective on the interplay between choice, behavior, and their neural underpinnings. Our results have important implications for translating BMIs into more complex real-world environments. We find that early neural dynamics are sufficient to drive BMI movements before the participant intends to initiate movement. Appropriate algorithms ensure that BMI movements align with the subject's awareness of choice.

Ethical commitments, principles, and practices guiding intracranial neuroscientific research in humans

Leveraging firsthand experience, BRAIN-funded investigators conducting intracranial human neuroscience research propose two fundamental ethical commitments: (1) maintaining the integrity of clinical care and (2) ensuring voluntariness. Principles, practices, and uncertainties related to these commitments are offered for future investigation.

Mesolimbic Neurobehavioral Mechanisms of Reward Motivation in Anorexia Nervosa: A Multimodal Imaging Study

Diminished motivation to pursue and obtain primary and secondary rewards has been demonstrated in anorexia nervosa (AN). However, the neurobehavioral mechanisms underlying the behavioral activation component of aberrant reward motivation remains incompletely understood. This work aims to explore this underexplored facet of reward motivation in AN. We recruited female adolescents with AN, restricting type (n = 32) and a healthy control group (n = 28). All participants underwent functional magnetic resonance imaging (fMRI) while performing a monetary reward task. Diffusion MRI data was also collected to examine the reward motivation circuit's structural connectivity. Behavioral results demonstrated slower speed of reward-seeking behavior in those with AN compared with controls. Accompanying this was lower functional connectivity and reduced white matter structural integrity of the connection between the ventral tegmental area/substantia nigra pars compacta and the nucleus accumbens within the mesolimbic circuit. Further, there was evidence of neurobehavioral decoupling in AN between reward-seeking behavior and mesolimbic regional activation and functional connectivity. Aberrant activity of the bed nucleus of the stria terminalis (BNST) and its connectivity with the mesolimbic system was also evident in AN during the reward motivation period. Our findings suggest functional and structural dysconnectivity within a mesolimbic reward circuit, neurofunctional decoupling from reward-seeking behavior, and abnormal BNST function and circuit interaction with the mesolimbic system. These results show behavioral indicators of aberrant reward motivation in AN, particularly in its activational component. This is mediated neuronally by mesolimbic reward circuit functional and structural dysconnectivity as well as neurobehavioral decoupling. Based on these findings, we suggest a novel circuit-based mechanism of impaired reward processing in AN, with the potential for translation to developing more targeted and effective treatments in this difficult-to-treat psychiatric condition.

Extending Brain-Computer Interface Access with a Multilingual Language Model in the P300 Speller

Brain-computer interfaces (BCI) such as the P300 speller have the potential to restore communication to advanced-stage neuromuscular disease patients. Research has improved typing speed and accuracy through innovations including the use of language models. While significant advances have been made, implementations have largely been restricted to a single language, primarily English. It is unclear whether these improvements would extend to other languages that present potential technical hurdles due to different alphabets and grammatical structures. Here, we adapt a language model-based classifier designed for English to two other languages, Spanish and Greek, to demonstrate the generalizability of these methods. Online experimental trials with 30 healthy native English, Spanish, and Greek speakers showed no significant difference between performances using the different versions of the system (66.20 vs. 61.97 vs. 60.89 bits/minute). Extending these methods across languages allows for expanding access to BCI systems to other populations, particularly in the developing world.

Linear accelerator-based radiosurgery for trigeminal neuralgia: comparative outcomes of frame-based and mask-based techniques

OBJECTIVE

Precise and accurate targeting is critical to optimize outcomes after stereotactic radiosurgery (SRS) for trigeminal neuralgia (TN). The aim of this study was to compare the outcomes after SRS for TN in which two different techniques were used: mask-based 4-mm cone versus frame-based 5-mm cone.

METHODS

The authors performed a retrospective review of patients who underwent SRS for TN at their institution between 1996 and 2019. The Barrow Neurological Institute (BNI) pain score and facial hypesthesia scale were used to evaluate pain relief and facial numbness.

RESULTS

A total of 234 patients were included in this study; the mean age was 67 years. In 97 patients (41.5%) radiation was collimated by a mask-based 4-mm cone, whereas a frame-based 5-mm cone was used in the remaining 137 patients (58.5%). The initial adequate pain control rate (BNI I-III) was 93.4% in the frame-based 5-mm group, compared to 87.6% in the mask-based 4-mm group. This difference between groups lasted, with an adequate pain control rate at ≥ 24 months of 89.9% and 77.8%, respectively. Pain relief was significantly different between groups from initial response until the last follow-up (≥ 24 months, p = 0.02). A new, permanent facial hypesthesia occurred in 30.3% of patients (33.6% in the frame-based 5-mm group vs 25.8% in the mask-based 4-mm group). However, no significant association between the BNI facial hypesthesia score and groups was found. Pain recurrence occurred earlier (median time to recurrence 12 months vs 29 months, p = 0.016) and more frequently (38.1% vs 20.4%, p = 0.003) in the mask-based 4-mm than in the frame-based 5-mm group.

CONCLUSIONS

Frame-based 5-mm collimator SRS for TN resulted in a better long-term pain relief with similar toxicity profiles to that seen with mask-based 4-mm collimator SRS.

Simultaneous radiosurgery for multiple brain metastases: technical overview of the UCLA experience

PURPOSE/OBJECTIVE(S)

To communicate our institutional experience with single isocenter radiosurgery treatments for multiple brain metastases, including challenges with determining planning target volume (PTV) margins and resulting consequences, image-guidance translational and rotational tolerances, intra-fraction patient motion, and prescription considerations with larger PTV margins.

MATERIALS/METHODS

Eight patient treatments with 51 targets were planned with various margins using Elements Multiple Brain Mets SRS treatment planning software (Brainlab, Munich, Germany). Forty-eight plans with 0 mm, 1 mm and 2 mm margins were created, including plans with variable margins, where targets more than 6 cm away from the isocenter were planned with larger margins. The dosimetric impact of the margins were analyzed with V5Gy, V8Gy, V10Gy, V12Gy values. Additionally, 12 patient motion data were analyzed to determine both the impact of the repositioning threshold and the distributions of the patient translational and rotational movements.

RESULTS

The V5Gy, V8Gy, V10Gy, V12Gy volumes approximately doubled when margins change from 0 to 1 mm and tripled when change from 0 to 2 mm. With variable margins, the aggregated results are similar to results from plans using the lower of two margins, since only 12.2% of the targets were more than 6 cm away from the isocenter. With 0.5 mm re-positioning threshold, 57.4% of the time the patients are repositioned. Reducing the threshold to 0.25 mm results in 91.7% repositioning rate, due to limitations of the fusion algorithm and actual patient motion. The 90th percentile of translational movements in all directions is 0.7 mm, while the 90th percentile of rotational movements in all directions is 0.6 degrees. Median translations and rotations are 0.2 mm and 0.2 degrees, respectively.

CONCLUSIONS

Based on the data presented, we have switched our modus operandi from 2 to 1 mm PTV margins, with an eventual goal of using 0.5 and 1.0 mm variable margins when an automated margin assignment method becomes available. The 0.5 mm and 0.5 degrees repositioning thresholds are clinically appropriate with small residual patient movements.