Graph-based risk assessment and error detection in radiation therapy

Purpose : The objective of this study was to formalize and automate quality assurance (QA) in radiation oncology. QA in radiation oncology entails a multistep verification of complex, personalized radiation plans to treat cancer involving an interdisciplinary team and high technology, multivendor software and hardware. We addressed the pretreatment physics chart review (TPCR) using methods from graph theory and constraint programming to study the effect of dependencies between variables and automatically identify logical inconsistencies and how they propagate. Materials and Methods : We used a modular approach to decompose the TPCR process into tractable units comprising subprocesses, modules and variables. Modules represent the main software entities comprised in the radiation treatment planning workflow and subprocesses group the checks to be performed by functionality. Module‐associated variables serve as inputs to the subprocesses. Relationships between variables were modeled by means of a directed graph. The detection of errors, in the form of inconsistencies, was formalized as a constraint satisfaction problem whereby checks were encoded as logical formulae. The sequence in which subprocesses are visited was described in a activity diagram. Results : The comprehensive model for the TPCR process comprised 5 modules, 19 subprocesses and 346 variables, 225 of which were distinct. Modules included ”Treatment Planning System” and ”Record and Verify System”. Subprocesses included ”Dose Prescription”, ”Documents”, ”CT Integrity”, ”Anatomical Contours”, ”Beam Configuration”, ”Dose Calculation”, ”3D Dose Distribution Quality” and ”Treatment Approval”. Variable inconsistencies, their source and propagation are determined by checking for constraint violation and through graph traversal. Impact scores, obtained through graph traversal, combined with severity scores associated with an inconsistency, allow risk assessment. Conclusions : Directed graphs combined with constraint programming hold promise for formalizing complex QA processes in radiation oncology, performing risk assessment and automating the TPCR process. Though complex, the process is tractable.PostprintPeer reviewe

Controversies on the network theory of epilepsy : Debates held during the ICTALS 2019 conference

Acknowledgements We would like to acknowledge the contributions of the discussants to the exposition and discussion of the six debate topics. The discussants for debates 1-6 were Fabrice Wendling, Mark Cook, Mark Richardson, Thorsten Rings, Klaus Lehnertz and Piotr Suffczynski, respectively. Funding for ICTALS 2019 was received from the following foundations and industry partners: UCB S.A. (Belgium), American Epilepsy Society (AES), Epilepsy Innovation Institute (Ei2) and Epilepsy Foundation of America (EFA), NeuraLynx (Bozeman, MT, USA) and LivaNova (London, UK). The contribution of HZ was supported by award R01NS109062 from the National Institutes of Health, MG by the EPSRC via grants EP/P021417/1 and EP/N014391/1 and a Wellcome Trust Institutional Strategic Support Award (WT105618MA), and PJ by awards from the Ministry of Health of the Czech Republic AZV 17-28427A and the Czech Science Foundation 20-25298S. The opinions expressed in this article do not necessarily reflect the view of the National Institutes of Health, the Department of Health and Human Services, or the United States government.Peer reviewedPostprin

Controversies in epilepsy: Debates held during the Fourth International Workshop on Seizure Prediction

Debates on six controversial topics were held during the Fourth International Workshop on Seizure Prediction (IWSP4) convened in Kansas City, KS, USA, July 4–7, 2009. The topics were (1) Ictogenesis: Focus versus Network? (2) Spikes and Seizures: Step-relatives or Siblings? (3) Ictogenesis: A Result of Hyposynchrony? (4) Can Focal Seizures Be Caused by Excessive Inhibition? (5) Do High-Frequency Oscillations Provide Relevant Independent Information? (6) Phase Synchronization: Is It Worthwhile as Measured? This article, written by the IWSP4 organizing committee and the debaters, summarizes the arguments presented during the debates

Seizure prediction : ready for a new era

Acknowledgements: The authors acknowledge colleagues in the international seizure prediction group for valuable discussions. L.K. acknowledges funding support from the National Health and Medical Research Council (APP1130468) and the James S. McDonnell Foundation (220020419) and acknowledges the contribution of Dean R. Freestone at the University of Melbourne, Australia, to the creation of Fig. 3.Peer reviewedPostprin

Modelling of ECoG in Temporal Lobe Epilepsy

Subdural recordings of the electrical activity of the human brain give electrocorticograms (ECoG) almost free of artifacts and distortions by the skull and other intervening material. This paper discusses the modelling of the ECoG during the pre-ictal, ictal and post-ictal phases of an epileptic seizure. Optimum order linear autoregressive (AR) models are formed and the movement of the poles of the models are traced with time. Nonlinear extension to the AR models (NAR) is formulated based on the assumption of existenceof nonlinear oscillations in the data. The optimum order of this model is determined and its performance is compared with that of the linear AR models. The analysis of the data with NAR resulted in the satisfaction of sufficient conditions for limit cycles in the ictal phase. KEY WORDS: Electrocorticography; focal epilepsy; nonlinear modelling; limit cycles. I. INTRODUCTION In this paper we are concerned with the building of models for discrete time domain ECoG data. Ou..

Phase Space Topography and the Lyapunov Exponent of Electrocorticograms in Partial Seizures

over a period of time (10 minutes before to 10 minutes after the seizure outburst) revealed a remarkable coherence of theabrupt transient drops of L* for the electrodes that showed the initial ictal onset. The L* values for the electrodes away from the focus exhibited less abrupt transient drops. These results indicate that the largest average Lyapunov exponent L can be useful in seizure detection as well as a discriminatory factor for focus localization in multielectrocle analysis. Key words: phase space; chaos; Lyapunov exponents; ECoG; partial epileptic seizures; epileptogenic focus localization. Introduction Long-term recordings of brain electrical activity recorded from scalp and sphenoidal electrodes, depth electrodes or subdural electrodes are employed in our clinical laboratories to localize the origin of seizure discharges in patients with partial (focal) seizures who are candidates for surgical removal of the seizure focus. Currently, in clinical practice, t