Gamma knife capsulotomy for intractable OCD: Neuroimage analysis of lesion size, location, and clinical response

Obsessive-compulsive disorder (OCD) affects 2-3% of the population. One-third of patients are poorly responsive to conventional therapies, and for a subgroup, gamma knife capsulotomy (GKC) is an option. We examined lesion characteristics in patients previously treated with GKC through well-established programs in Providence, RI (Butler Hospital/Rhode Island Hospital/Alpert Medical School of Brown University) and São Paulo, Brazil (University of São Paolo). Lesions were traced on T1 images from 26 patients who had received GKC targeting the ventral half of the anterior limb of the internal capsule (ALIC), and the masks were transformed into MNI space. Voxel-wise lesion-symptom mapping was performed to assess the influence of lesion location on Y-BOCS ratings. General linear models were built to compare the relationship between lesion size/location along different axes of the ALIC and above or below-average change in Y-BOCS ratings. Sixty-nine percent of this sample were full responders (≥35% improvement in OCD). Lesion occurrence anywhere within the targeted region was associated with clinical improvement, but modeling results demonstrated that lesions occurring posteriorly (closer to the anterior commissure) and dorsally (closer to the mid-ALIC) were associated with the greatest Y-BOCS reduction. No association was found between Y-BOCS reduction and overall lesion volume. GKC remains an effective treatment for refractory OCD. Our data suggest that continuing to target the bottom half of the ALIC in the coronal plane is likely to provide the dorsal-ventral height required to achieve optimal outcomes, as it will cover the white matter pathways relevant to change. Further analysis of individual variability will be essential for improving targeting and clinical outcomes, and potentially further reducing the lesion size necessary for beneficial outcomes.

Deep Transfer Learning Based Classification Model for COVID-19 Disease

The COVID-19 infection is increasing at a rapid rate, with the availability of limited number of testing kits. Therefore, the development of COVID-19 testing kits is still an open area of research. Recently, many studies have shown that chest Computed Tomography (CT) images can be used for COVID-19 testing, as chest CT images show a bilateral change in COVID-19 infected patients. However, the classification of COVID-19 patients from chest CT images is not an easy task as predicting the bilateral change is defined as an ill-posed problem. Therefore, in this paper, a deep transfer learning technique is used to classify COVID-19 infected patients. Additionally, a top-2 smooth loss function with cost-sensitive attributes is also utilized to handle noisy and imbalanced COVID-19 dataset kind of problems. Experimental results reveal that the proposed deep transfer learning-based COVID-19 classification model provides efficient results as compared to the other supervised learning models.

Longitudinal Changes in Depressive Circuitry in Response to Neuromodulation Therapy

Background: Major depressive disorder (MDD) is a public health problem worldwide. There is increasing interest in using non-invasive therapies such as repetitive transcranial magnetic stimulation (rTMS) to treat MDD. However, the changes induced by rTMS on neural circuits remain poorly characterized. The present study aims to test whether the brain regions previously targeted by deep brain stimulation (DBS) in the treatment of MDD respond to rTMS, and whether functional connectivity (FC) measures can predict clinical response.

Methods: rTMS (20 sessions) was administered to five MDD patients at the left-dorsolateral prefrontal cortex (L-DLPFC) over 4 weeks. Magnetoencephalography (MEG) recordings and Montgomery-Asberg depression rating scale (MADRS) assessments were acquired before, during and after treatment. Our primary measures, obtained with MEG source imaging, were changes in power spectral density (PSD) and changes in FC as measured using coherence.

Results: Of the five patients, four met the clinical response criterion (40% or greater decrease in MADRS) after 4 weeks of treatment. An increase in gamma power at the L-DLPFC was correlated with improvement in symptoms. We also found that increases in delta band connectivity between L-DLPFC/amygdala and L-DLPFC/pregenual anterior cingulate cortex (pACC), and decreases in gamma band connectivity between L-DLPFC/subgenual anterior cingulate cortex (sACC), were correlated with improvements in depressive symptoms.

Conclusions: Our results suggest that non-invasive intervention techniques, such as rTMS, modulate the ongoing activity of depressive circuits targeted for DBS, and that MEG can capture these changes. Gamma oscillations may originate from GABA-mediated inhibition, which increases synchronization of large neuronal populations, possibly leading to increased long-range FC. We postulate that responses to rTMS could provide valuable insights into early evaluation of patient candidates for DBS surgery.

Proceedings of the Third Annual Deep Brain Stimulation Think Tank: A Review of Emerging Issues and Technologies

The proceedings of the 3rd Annual Deep Brain Stimulation Think Tank summarize the most contemporary clinical, electrophysiological, imaging, and computational work on DBS for the treatment of neurological and neuropsychiatric disease. Significant innovations of the past year are emphasized. The Think Tank's contributors represent a unique multidisciplinary ensemble of expert neurologists, neurosurgeons, neuropsychologists, psychiatrists, scientists, engineers, and members of industry. Presentations and discussions covered a broad range of topics, including policy and advocacy considerations for the future of DBS, connectomic approaches to DBS targeting, developments in electrophysiology and related strides toward responsive DBS systems, and recent developments in sensor and device technologies.

The role of electrode location and stimulation polarity in patient response to cortical stimulation for major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a neuropsychiatric condition that affects about one-sixth of the US population. Chronic epidural stimulation (EpCS) of the left dorsolateral prefrontal cortex (DLPFC) was recently evaluated as a treatment option for refractory MDD and was found to be effective during the open-label phase. However, two potential sources of variability in the study were differences in electrode position and the range of stimulation modes that were used in each patient. The objective of this study was to examine these factors in an effort to characterize successful EpCS therapy.

METHODS

Data were analyzed from eleven patients who received EpCS via a chronically implanted system. Estimates were generated of response probability as a function of duration of stimulation. The relative effectiveness of different stimulation modes was also evaluated. Lastly, a computational analysis of the pre- and post-operative imaging was performed to assess the effects of electrode location. The primary outcome measure was the change in Hamilton Depression Rating Scale (HDRS-28).

RESULTS

Significant improvement was observed in mixed mode stimulation (alternating cathodic and anodic) and continuous anodic stimulation (full power). The changes observed in HDRS-28 over time suggest that 20 weeks of stimulation are necessary to approach a 50% response probability. Lastly, stimulation in the lateral and anterior regions of DLPFC was correlated with greatest degree of improvement.

CONCLUSIONS

A persistent problem in neuromodulation studies has been the selection of stimulation parameters and electrode location to provide optimal therapeutic response. The approach used in this paper suggests that insights can be gained by performing a detailed analysis of response while controlling for important details such as electrode location and stimulation settings.

An upper limb robot model of children limb for cerebral palsy neurorehabilitation

Robot therapy has emerged in the last few decades as a tool to help patients with neurological injuries relearn motor tasks and improve their quality of life. The main goal of this study was to develop a simple model of the human arm for children affected with cerebral palsy (CP). The Simulink based model presented here shows a comparison for children with and without disabilities (ages 6-15) with normal and reduced range of motion in the upper limb. The model incorporates kinematic and dynamic considerations required for activities of daily living. The simulation was conducted using Matlab/Simulink and will eventually be integrated with a robotic counterpart to develop a physical robot that will provide assistance in activities of daily life (ADLs) to children with CP while also aiming to improve motor recovery.

Covered conduction of individual C(60) nanowhiskers

We investigate the electronic properties of individual C(60) nanowhiskers by exploiting conductive atomic force microscopy at room temperature in ambient atmosphere. The pristine individual C(60) nanowhiskers exhibit conducting behavior. The outer C(60) oxide covering, confirmed by Auger electron spectroscopy, shelters the conductive properties of the C(60) nanowhiskers. It is proposed that the insulating outer C(60) oxide covering might be used as the dielectric layer in potential single C(60) nanowhisker-based field-effect transistors for nanoelectronics.

Investigation of soft-tissue stiffness alteration in denervated human tissue using an ultrasound indentation system

BACKGROUND/OBJECTIVE

Differences in soft-tissue stiffness may provide for a quantitative assessment and detection technique for pressure ulcers or deep-tissue injury. An ultrasound indentation system may provide a relatively convenient, simple, and noninvasive method for quantitative measurement of changes in soft-tissue stiffness in vivo.

METHODS

The Tissue Ultrasound Palpation System (TUPS) was used to quantitatively measure changes in soft-tissue stiffness at different anatomical locations within and between able-bodied persons and individuals with chronic spinal cord injury (SCI). The stiffness of soft tissue was measured at the ischial tuberosity, greater trochanter, posterior midthigh, and biceps brachii. Additionally, soft-tissue thickness and soft-tissue deformation were also measured.

RESULTS

Significant differences in soft-tissue stiffness were observed within the various anatomical locations tested, in both the able-bodied and SCI groups. Differences in soft-tissue stiffness were also observed between the 2 groups. Participants with SCI had significantly softer tissue in their buttock-thigh area.

CONCLUSIONS

TUPS is a clinically feasible technology that can reliably and effectively detect changes in soft-tissue stiffness. The study has provided a better understanding of the tissue mechanical response to external loading, specifically in the SCI population, suggesting the use of tissue stiffness as a parameter to detect and assess pressure-related soft-tissue injury.