A multicenter retrospective study of patients treated in the thalamus with responsive neurostimulation

INTRODUCTION: For drug resistant epilepsy patients who are either not candidates for resective surgery or have already failed resective surgery, neuromodulation is a promising option. Neuromodulatory approaches include responsive neurostimulation (RNS), deep brain stimulation (DBS), and vagal nerve stimulation (VNS). Thalamocortical circuits are involved in both generalized and focal onset seizures. This paper explores the use of RNS in the centromedian nucleus of the thalamus (CMN) and in the anterior thalamic nucleus (ANT) of patients with drug resistant epilepsy. METHODS: This is a retrospective multicenter study from seven different epilepsy centers in the United States. Patients that had unilateral or bilateral thalamic RNS leads implanted in the CMN or ANT for at least 6 months were included. Primary objectives were to describe the implant location and determine changes in the frequency of disabling seizures at 6 months, 1 year, 2 years, and \u3e 2 years. Secondary objectives included documenting seizure free periods, anti-seizure medication regimen changes, stimulation side effects, and serious adverse events. In addition, the global clinical impression scale was completed. RESULTS: Twelve patients had at least one lead placed in the CMN, and 13 had at least one lead placed in the ANT. The median baseline seizure frequency was 15 per month. Overall, the median seizure reduction was 33% at 6 months, 55% at 1 year, 65% at 2 years, and 74% at \u3e2 years. Seizure free intervals of at least 3 months occurred in nine patients. Most patients (60%, 15/25) did not have a change in anti-seizure medications post RNS placement. Two serious adverse events were recorded, one related to RNS implantation. Lastly, overall functioning seemed to improve with 88% showing improvement on the global clinical impression scale. DISCUSSION: Meaningful seizure reduction was observed in patients who suffer from drug resistant epilepsy with unilateral or bilateral RNS in either the ANT or CMN of the thalamus. Most patients remained on their pre-operative anti-seizure medication regimen. The device was well tolerated with few side effects. There were rare serious adverse events. Most patients showed an improvement in global clinical impression scores

Responding to symptoms suggestive of lung cancer: a qualitative interview study.

BACKGROUND: Late diagnosis of lung cancer can impact on survival rates. Patients delay seeking help for a number of reasons. This study explored symptom appraisal and help-seeking decisions among patients referred to specialist respiratory services with symptoms suggestive of lung cancer. METHODS: In-depth qualitative interviews with patients as soon as possible after referral, ideally before diagnosis and mainly within 10 weeks, explored factors impacting on their pathways prior to referral. Framework analysis, underpinned by the Model of Pathways to Treatment, was used to explore the data with particular focus on patients' beliefs and experiences, disease factors and healthcare professional influences. RESULTS: 35 patients were interviewed (aged 41-88 years, 15 women, 17 with lung cancer). All described similar presenting symptoms and triggers to seek help. Appraisal of symptoms was influenced by whether they had a lung comorbidity; seriousness of symptoms was interpreted within the context of previous illness experiences. Help-seeking was triggered when: symptoms failed to respond as expected; there was an increased awareness of symptoms of lung cancer; the public nature of a cough meant others were able to endorse help-seeking. Almost half visited the general practitioner (GP) two or more times before referral; during this period they reinterpreted initial symptoms and appraised new symptoms. The meaning given to symptoms changed over time and many became increasingly concerned they may have lung cancer. The GP played a role in ensuring timely further help-seeking but often there was little guidance on how to monitor symptoms or when to reconsult. CONCLUSIONS: Patients diagnosed with and without lung cancer had similar symptom pathways. Findings provide guidance for lung cancer awareness campaigns on the importance of social networks in endorsing patient help-seeking. The importance of appropriate advice, monitoring and safety-netting procedures by GPs for people presenting with symptoms suggestive of lung cancer is also highlighted.This report presents independent research funded by the National Institute for Health Research Programme Grants for Applied Research programme (RP-PG-0608-10045).This is the final version. It was first published by BMJ Group at http://bmjopenrespres.bmj.com/content/1/1/e00006

The researchers’ role in knowledge translation: a realist evaluation of the development and implementation of diagnostic pathways for cancer in two UK localities

Abstract Background In examining an initiative to develop and implement new cancer diagnostic pathways in two English localities, this paper evaluates ‘what works’ and examines the role of researchers in facilitating knowledge translation amongst teams of local clinicians and policymakers. Methods Using realist evaluation with a mixed methods case study approach, we conducted documentary analysis of meeting minutes and pathway iterations to map pathway development. We interviewed 14 participants to identify the contexts, mechanisms and outcomes (CMOs) that led to successful pathway development and implementation. Interviews were analysed thematically and four CMO configurations were developed. Results One site produced three fully implemented pathways while the other produced two that were partly implemented. In explaining the differences, we found that a respected, independent, well-connected leader modelling partnership-working who facilitates a local, stable group that agree about the legitimacy of the data and project (context) can empower local teams to become sufficiently autonomous (mechanism) to develop and implement research-based pathways (outcome). Although both teams designed relevant, research-based cancer pathways, the research team assisted where the pathways were successfully implemented while in the other the research team drove the initiative. Discussion Based on our study findings, local stakeholders can apply local and research knowledge to develop and implement research-based pathways. However, success will depend on how academics empower local teams to create autonomy. After re-packaging and translating research for local circumstances, identifying fertile environments with the right elements for implementation and developing collaborative relationships with local leaders, crucially academics then have to step back. Keywords Knowledge translation; realist evaluation; qualitative research; diagnostic pathways for cance

Robot assisted MRI-guided LITT of the anterior, lateral, and medial temporal lobe for temporal lobe epilepsy

Robotic systems have fundamentally altered the landscape of functional neurosurgery. These allow automated stereotaxy with high accuracy and reliability, and are rapidly becoming a mainstay in stereotactic surgeries such as deep brain stimulation (DBS), stereoelectroencephalography (SEEG), and stereotactic laser ablation/MRI guided laser interstitial thermal therapy (MRgLITT). Robotic systems have been effectively applied to create a minimally invasive approach for diagnostics and therapeutics in the treatment of epilepsy, utilizing robots for expeditious and accurate stereotaxy for SEEG and MRgLITT. MRgLITT has been shown to approach open surgical techniques in efficacy of seizure control while minimizing collateral injury. We describe the use of robot assisted MRgLITT for a minimally invasive laser anterior temporal lobotomy, describing the approach and potential pitfalls. Goals of MRgLITT are complete ablation of the epileptogenic zone and avoiding injury to uninvolved structures. In the middle fossa these include structures such as cranial nerves in the skull base and cavernous sinus and the thalamus. These can be mitigated with careful trajectory planning and control of laser ablation intensity

BrainWAVE: A flexible method for noninvasive stimulation of brain rhythms across species

Rhythmic neural activity, which coordinates brain regions and neurons to achieve multiple brain functions, is impaired in many diseases. Despite the therapeutic potential of driving brain rhythms, methods to noninvasively target deep brain regions are limited. Accordingly, we recently introduced a noninvasive stimulation approach using flickering lights and sounds ( flicker ). Flicker drives rhythmic activity in deep and superficial brain regions. Gamma flicker spurs immune function, clears pathogens, and rescues memory performance in mice with amyloid pathology. Here, we present substantial improvements to this approach that is flexible, user-friendly, and generalizable across multiple experimental settings and species. We present novel open-source methods for flicker stimulation across rodents and humans. We demonstrate rapid, cross-species induction of rhythmic activity without behavioral confounds in multiple settings from electrophysiology to neuroimaging. This flicker approach provides an exceptional opportunity to discover the therapeutic effects of brain rhythms across scales and species

Artificial Intelligence Techniques That May Be Applied to Primary Care Data to Facilitate Earlier Diagnosis of Cancer : Systematic Review

Acknowledgments This research was funded by the National Institute for Health Research (NIHR) Policy Research Programme, conducted through the Policy Research Unit in Cancer Awareness, Screening, and Early Diagnosis, PR-PRU-1217-21601. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. This work was also supported by the CanTest Collaborative (funded by Cancer Research UK C8640/A23385), of which FW and WH are directors and JE, HS, and NdW are associate directors. HS is additionally supported by the Houston Veterans Administration Health Services Research and Development Center for Innovations in Quality, Effectiveness, and Safety (CIN13-413) and the Agency for Healthcare Research and Quality (R01HS27363). The funding sources had no role in the study design, data collection, data analysis, data interpretation, writing of the report, or the decision to submit for publication. The authors would like to thank Isla Kuhn, Reader Services Librarian, University of Cambridge Medical Library, for her help in developing the search strategy.Peer reviewedPublisher PD

Artificial Intelligence Techniques That May Be Applied to Primary Care Data to Facilitate Earlier Diagnosis of Cancer: Systematic Review.

BACKGROUND: More than 17 million people worldwide, including 360,000 people in the United Kingdom, were diagnosed with cancer in 2018. Cancer prognosis and disease burden are highly dependent on the disease stage at diagnosis. Most people diagnosed with cancer first present in primary care settings, where improved assessment of the (often vague) presenting symptoms of cancer could lead to earlier detection and improved outcomes for patients. There is accumulating evidence that artificial intelligence (AI) can assist clinicians in making better clinical decisions in some areas of health care. OBJECTIVE: This study aimed to systematically review AI techniques that may facilitate earlier diagnosis of cancer and could be applied to primary care electronic health record (EHR) data. The quality of the evidence, the phase of development the AI techniques have reached, the gaps that exist in the evidence, and the potential for use in primary care were evaluated. METHODS: We searched MEDLINE, Embase, SCOPUS, and Web of Science databases from January 01, 2000, to June 11, 2019, and included all studies providing evidence for the accuracy or effectiveness of applying AI techniques for the early detection of cancer, which may be applicable to primary care EHRs. We included all study designs in all settings and languages. These searches were extended through a scoping review of AI-based commercial technologies. The main outcomes assessed were measures of diagnostic accuracy for cancer. RESULTS: We identified 10,456 studies; 16 studies met the inclusion criteria, representing the data of 3,862,910 patients. A total of 13 studies described the initial development and testing of AI algorithms, and 3 studies described the validation of an AI algorithm in independent data sets. One study was based on prospectively collected data; only 3 studies were based on primary care data. We found no data on implementation barriers or cost-effectiveness. Risk of bias assessment highlighted a wide range of study quality. The additional scoping review of commercial AI technologies identified 21 technologies, only 1 meeting our inclusion criteria. Meta-analysis was not undertaken because of the heterogeneity of AI modalities, data set characteristics, and outcome measures. CONCLUSIONS: AI techniques have been applied to EHR-type data to facilitate early diagnosis of cancer, but their use in primary care settings is still at an early stage of maturity. Further evidence is needed on their performance using primary care data, implementation barriers, and cost-effectiveness before widespread adoption into routine primary care clinical practice can be recommended.CRU