scholarly journals Magnetoencephalography STOUT Method Adapted to Radiofrequency Thermocoagulation for MR-Negative Insular Epilepsy: A Case Report

2021 ◽  
Vol 12 ◽  
Author(s):  
Kaiqiang Ma ◽  
Guoming Luan ◽  
Xiongfei Wang ◽  
Shen Luo ◽  
Lang Qin ◽  
...  

Epilepsy is one of the most challenging neurologic diseases confronted by human society. Approximately 30–40% of the worldwide epilepsy patients are diagnosed with drug-resistant epilepsy and require pre-surgery evaluation. Magnetoencephalography (MEG) is a unique technology that provides optimal spatial-temporal resolution and has become a powerful non-invasive imaging modality that can localize the interictal spikes and guide the implantation of intracranial electrodes. Currently, the most widely used MEG source estimation method for clinical applications is equivalent current dipoles (ECD). However, ECD has difficulties in precisely locating deep sources such as insular lobe. In contrast to ECD, another MEG source estimation method named spatio-temporal unifying tomography (STOUT) with spatial sparsity has particular advantages in locating deep sources. In this case study, we recruited a 5 year-old female patient with insular lobe epilepsy and her seizure recurred in 1 year after receiving the radiofrequency thermocoagulation (RF-TC) therapy. The STOUT method was adopted to locate deep sources for identifying the epileptic foci in epilepsy evaluation. MEG STOUT method strongly supported a stereo-electroencephalographic (SEEG)-guided RF-TC operation, and the patient reported a satisfactory therapeutic effect. This case raises the possibility that STOUT method can be used particularly for the localization of deep sources, and successfully conducted RF-TC under the guidance of MEG STOUT results.

Pain Medicine ◽  
2018 ◽  
Vol 20 (8) ◽  
pp. 1551-1558 ◽  
Author(s):  
Zhigang Guo ◽  
Zhijia Wang ◽  
Kai Li ◽  
Chao Du ◽  
Xingli Zhao ◽  
...  

Abstract Objectives Patients with trigeminal neuralgia who are refractory to medical therapy may choose to undergo Gasserian ganglion percutaneous radiofrequency thermocoagulation. However, in cases where the foramen ovale is difficult to access due to various anatomical anomalies, the typical estimation of the facial entry point is suboptimal. Methods Three-dimensional computed tomography reconstruction imaging performed before surgery revealed anatomical variations in each of the four adult patient cases that made it more difficult to successfully access the foramen ovale (FO) for percutaneous radiofrequency thermocoagulation. Using measurements collected from preoperative imaging that showed each specific anatomical variation in the FO, researchers marked alternate facial entry points that would allow successful probe placement into the FO and recorded the arc angle data in the stereotactic instrument. Results Patients were evaluated during follow-up visits ranging from seven to 26 months after surgery and asked to rate postoperative pain using a visual analog scale. These scores decreased from 10 to 3 in all four patients by the third day after the procedure. There were no permanent complications or morbidities from the surgery. One patient experienced mild facial numbness; however, this side effect subsided within three months after surgery. During the follow-up period, no patient reported pain recurrence. Conclusions The expectation for clinicians approaching trigeminal nerve block using a peri-oral approach should be to expect a great degree of potential variability in terms of both distances from the corner of the mouth and needle angle taken to successfully navigate the anatomy and access the foramen ovale.


2020 ◽  
Vol 12 (4) ◽  
pp. 1-19
Author(s):  
Prathap Rudra Boppuru ◽  
Ramesha K.

In developing countries like India, crime plays a detrimental role in economic growth and prosperity. With the increase in delinquencies, law enforcement needs to deploy limited resources optimally to protect citizens. Data mining and predictive analytics provide the best options for the same. This paper examines the news feed data collected from various sources regarding crime in India and Bangalore city. The crimes are then classified on the geographic density and the crime patterns such as time of day to identify and visualize the distribution of national and regional crime such as theft, murder, alcoholism, assault, etc. In total, 68 types of crime-related dictionary keywords are classified into six classes based on the news feed data collected for one year. Kernel density estimation method is used to identify the hotspots of crime. With the help of the ARIMA model, time series prediction is performed on the data. The diversity of crime patterns is visualized in a customizable way with the help of a data mining platform.


Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1953 ◽  
Author(s):  
Seo ◽  
Lee

Drought is a complex phenomenon caused by lack of precipitation that affects water resources and human society. Groundwater drought is difficult to assess due to its complexity and the lack of spatio-temporal groundwater observations. In this study, we present an approach to evaluate groundwater drought based on relatively high spatial resolution groundwater storage change data. We developed an artificial neural network (ANN) that employed satellite data (Gravity Recovery and Climate Experiment (GRACE) and Tropical Rainfall Measuring Mission (TRMM)) as well as Global Land Data Assimilation System (GLDAS) models. The Standardized Groundwater Level Index (SGI) was calculated by normalizing ANN-predicted groundwater storage changes from 2003 to 2015 across South Korea. The ANN-predicted 25 km groundwater storage changes correlated well with both the in situ and the water balance equation (WBE)-estimated groundwater storage changes, with mean correlation coefficients of 0.87 and 0.64, respectively. The Standardized Precipitation–Evapotranspiration Index (SPEI), having an accumulation time of 1–6 months, and the Palmer Drought Severity Index (PDSI) were used to validate the SGI. The results showed that the SGI had a pattern similar to that of SPEI-1 and SPEI-2 (1- and 2-month accumulation periods, respectively), and PDSI. However, the SGI performance fluctuated slightly due to its relatively short study period (13 years) as compared to SPEI and PDSI (more than 30 years). The SGI, which was developed using a new approach in this study, captured the characteristics of groundwater drought, thus presenting a framework for the assessment of these characteristics.


2016 ◽  
Vol 16 (1) ◽  
pp. 51-61 ◽  
Author(s):  
Youngkyu Kim ◽  
Yeonsu Kim ◽  
Wansik Yu ◽  
Sungryul Oh ◽  
Kwansue Jung

Author(s):  
L. Sacconi ◽  
L. Silvestri ◽  
E.C. Rodríguez ◽  
G.A.B. Armstrong ◽  
F.S. Pavone ◽  
...  

AbstractFast volumetric imaging is essential for understanding the function of excitable tissues such as those found in the brain and heart. Measuring cardiac voltage transients in tissue volumes with spatial and temporal resolutions needed to give insight to cardiac function has so far been impossible. We introduce a new imaging modality based on simultaneous illumination of multiple planes in the tissue and parallel detection with multiple cameras, avoiding compromises inherent in any scanning approach. The system enables imaging of voltage transients in-situ, allowing us, for the first time, to map voltage activity in the whole heart volume at KHz rates. The unprecedented spatio-temporal resolution of our method enabled the observation of novel dynamics of electrical propagation through the zebrafish atrioventricular canal.


2022 ◽  
Vol 10 (1) ◽  
pp. 44
Author(s):  
Hongliang Liu ◽  
Nianxue Luo ◽  
Qiansheng Zhao

China is one of the countries most affected by typhoon disasters. It is of great significance to study the mechanism of typhoon disasters and construct a typhoon disaster chain for emergency management and disaster reduction. The evolution process of typhoon disaster based on expert knowledge and historical disaster data has been summarized in previous studies, which relied too much on artificial experience while less in-depth consideration was given to the disaster exposure, the social environment, as well as the spatio-temporal factors. Hence, problems, such as incomplete content and inconsistent expression of typhoon disaster knowledge, have arisen. With the development of computer technology, massive Web corpus with numerous Web news and various improvised content on the social media platform, and ontology that enables consistent expression new light has been shed on the knowledge discovery of typhoon disaster. With the Chinese Web corpus as its source, this research proposes a method to construct a typhoon disaster chain so as to obtain disaster information more efficiently, explore the spatio-temporal trends of disasters and their impact on human society, and then comprehensively comprehend the process of typhoon disaster. First, a quintuple structure (Concept, Property, Relationship, Rule and Instance) is used to design the Typhoon Disaster Chain Ontology Model (TDCOM) which contains the elements involved in a typhoon disaster. Then, the information extraction process, regarded as a sequence labeling task in the present study, is combined with the BERT model so as to extract typhoon event-elements from the customized corpus. Finally, taking Typhoon Mangkhut as an example, the typical typhoon disaster chain is constructed by data fusion and structured expression. The results show that the methods presented in this research can provide scientific support for analyzing the evolution process of typhoon disasters and their impact on human society.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 190263-190276
Author(s):  
Canyang Guo ◽  
Genggeng Liu ◽  
Lingjuan Lyu ◽  
Chi-Hua Chen

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