Web-Interface-Driven Development for Neuro3D, a Clinical Data Capture and Decision Support System for Deep Brain Stimulation

Summary Objective: We have been developing a decision support system that uses electronic clinical data and provides alerts to clinicians. However, the inference rules for such a system are difficult to write in terms of representing domain concepts and temporal reasoning. To address this problem, we have developed an ontologybased mediator of clinical information for the decision support system. Methods: Our approach consists of three steps: 1) development of an ontology-based mediator that represents domain concepts and temporal information; 2) mapping of clinical data to corresponding concepts in the mediator; 3) temporal abstraction that creates high-level, interval-based concepts from time-stamped clinical data. As a result, we can write a concept-based rule expression that is available for use in domain concepts and interval-based temporal information. The proposed approach was applied to a prototype of clinical alert system, and the rules for adverse drug events were executed on data gathered over a 3-month period. Results: The system generated 615 alerts. 346 cases (56%) were considered appropriate and 269 cases (44%) were inappropriate. Of the false alerts, 192 cases were due to data inaccuracy and 77 cases were due to insufficiency of the temporal abstraction. Conclusion: Our approach enabled to represent a concept-based rule expression that was available for the prototype of a clinical alert system. We believe our approach will contribute to narrow the gaps of information model between domain concepts and clinical data repositories.

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Sweetspot mapping in deep brain stimulation: Strengths and limitations of current approaches

10.1101/2020.09.08.20190223 ◽

2020 ◽

Author(s):

Till A Dembek ◽

Carlos Baldermann ◽

Jan-Niklas Petry-Schmelzer ◽

Hannah Jergas ◽

Harald Treuer ◽

...

Keyword(s):

Deep Brain Stimulation ◽

Clinical Data ◽

Brain Stimulation ◽

In Silico ◽

Ground Truth ◽

Ground Truth Data ◽

Open Questions ◽

Out Of Sample ◽

Optimal Target ◽

Deep Brain

Objective: Open questions remain regarding the optimal target, or sweetspot, for deep brain stimulation (DBS) in e.g. Parkinson's Disease. Previous studies introduced different methods of mapping DBS effects to determine sweetspots. While having a direct impact on surgical targeting and postoperative programming in DBS, these methods so far have not been investigated in ground truth data. Materials & Methods: This study investigated five previously published DBS mapping methods regarding their potential to correctly identify a ground truth sweetspot. Methods were investigated in silico in eight different use case scenarios, which incorporated different types of clinical data, noise, and differences in underlying neuroanatomy. Dice coefficients were calculated to determine the overlap between identified sweetspots and the ground truth. Additionally, out of sample predictive capabilities were assessed using the amount of explained variance R-squared. Results: The five investigated methods resulted in highly variable sweetspots. Methods based on voxel-wise statistics against average outcomes showed the best performance overall. While predictive capabilities were high, even in the best of cases Dice coefficients remained limited to values around 0.5, highlighting the overall limitations of sweetspot identification. Conclusions: This study highlights the strengths and limitations of current approaches to DBS sweetspot mapping. Those limitations need to be taken into account when considering the clinical implications. All future approaches should be investigated in silico before being applied to clinical data.

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VISIR: Technological infrastructure of an operational service for safe and efficient navigation in the Mediterranean Sea

10.5194/nhess-2016-32 ◽

2016 ◽

Cited By ~ 2

Author(s):

G. Mannarini ◽

G. Turrisi ◽

A. D'Anca ◽

M. Scalas ◽

N. Pinardi ◽

...

Keyword(s):

Decision Support ◽

Decision Support System ◽

Support System ◽

Mobile Applications ◽

Route Optimization ◽

Web Interface ◽

Ship Routing ◽

Technological Infrastructure ◽

Main Components ◽

Operational Service

Abstract. VISIR (discoVerIng Safe and effIcient Routes) is an operational Decision Support System (DSS) for ship routing designed and implemented in the frame of the TESSA (TEchnology for Situational Sea Awareness) project. The system is aimed to increase safety and efficiency of navigation through the use of forecast environmental fields and route optimization. VISIR can be accessed through both a web interface (www.visir-nav.com) and mobile applications for both iOS and Android devices. This paper focuses on the technological infrastructure developed for operating VISIR as a DSS. Its main components are described, the major challenges faced by the operational system are highlighted, and its potential for interoperability is outlined.

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Anatomo-clinical atlases correlate clinical data and electrode contact coordinates: Application to subthalamic deep brain stimulation

Journal of Neuroscience Methods ◽

10.1016/j.jneumeth.2012.11.002 ◽

2013 ◽

Vol 212 (2) ◽

pp. 297-307 ◽

Cited By ~ 14

Author(s):

Florent Lalys ◽

Claire Haegelen ◽

Maroua Mehri ◽

Sophie Drapier ◽

Marc Vérin ◽

...

Keyword(s):

Deep Brain Stimulation ◽

Clinical Data ◽

Brain Stimulation ◽

Electrode Contact ◽

Deep Brain

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Selection of deep brain stimulation contacts using volume of tissue activated software following subthalamic nucleus stimulation

Journal of Neurosurgery ◽

10.3171/2020.6.jns192157 ◽

2020 ◽

pp. 1-8

Author(s):

Mathilde Devaluez ◽

Melissa Tir ◽

Pierre Krystkowiak ◽

Mickael Aubignat ◽

Michel Lefranc

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Deep Brain Stimulation ◽

Subthalamic Nucleus ◽

Clinical Data ◽

Brain Stimulation ◽

Therapeutic Window ◽

Patient Specific ◽

Subthalamic Nucleus Stimulation ◽

Deep Brain

OBJECTIVEHigh-frequency deep brain stimulation (DBS) of the subthalamic nucleus (STN) is effective in the treatment of motor symptoms of Parkinson’s disease. Using a patient-specific lead and volume of tissue activated (VTA) software, it is possible to visualize contact positions in the context of the patient’s own anatomy. In this study, the authors’ aim was to demonstrate that VTA software can be used in clinical practice to help determine the clinical effectiveness of stimulation in patients with Parkinson’s disease undergoing DBS of the STN.METHODSBrain images of 26 patients undergoing STN DBS were analyzed using VTA software. Preoperative clinical and neuropsychological data were collected. Contacts were chosen by two experts in DBS blinded to the clinical data. A therapeutic window of amplitude was determined. These results were compared with the parameter settings for each patient. Data were obtained at 3 months and 1 year postsurgery.RESULTSIn 90.4% (95% CI 82%–98%) of the patients, the contacts identified by the VTA software were concordant with the clinically effective contacts or with an effective contact in contact-by-contact testing. The therapeutic window of amplitude selected virtually included 81.3% of the clinical amplitudes.CONCLUSIONSVTA software appears to present significant concordance with clinical data for selecting contacts and stimulation parameters that could help in postoperative follow-up and programming.

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