Webinar Q&A Report - InsideScientific

Webinar Q&A Report: Don’t Miss a Beat: Arrhythmia Detection for Preclinical ECG Research

Q: How did you detect the arrhythmia? If you went through the software, how much time did you save in manual vs. software usage? If you use the software, how long did it take you to learn the software proficiently? DSI: Data Insights uses Search Definitions to interrogate the Derived Parameter data calculated from the signal by Ponemah’s library of automated analysis modules. Searchers are composed of one of more Search Clauses, which are Boolean expressions composed of inputs and functions. The inputs include amplitude and timing data calculated by Ponemah (RR interval, Heart Rate, LVEDP etc.), pattern matching results, and time of day information. The functions determine how inputs are used when evaluating the Boolean expression that forms a Search Clause (Increase, Decrease, % Increase, % Decrease, etc.). Data Insights includes a number of predefined species-specific searches. Users are free to edit existing searches or create their own based. H. Holzgrefe: Regarding time savings, Data Insights offers the ability to interrogate the full data set (typically greater than 100 K beats) in a matter of minutes. Full manual scans of such large data sets are simply not feasible and are typically relegated to snapshot analyses which are comprised of 10 to 30 beats extracted at selected time points and forward it to a cardiologist for analysis. Given the differences in methodology, a direct time comparison is simply not feasible. With respect to the learning curve, users that are familiar with the standard Ponemah interface will find the software controls to be familiar and intuitive. The ability to use and /or construct arrhythmia searches and discriminate actual arrhythmic events from telemetric noise still requires an interactive approach where the learning curve will depend on the user's expertise and comfort with ECG waveform analysis. B.A. Mohamed: It is my belief that the most important advantage upon using Ponemah software is the Time saving benefit. Manual analysis of 24h measurements of one mouse takes one day’s work (around 8h), in contrast, using Ponemah it takes us 10-15 min. Learning how to use the software is not a big issue, because of great support the person will have from the DSI Personnel (in my case was Dr. Gaburro, who showed me how to successfully use the software, it took around 2 online sessions each was 2h).

Q: For Hank, what do you believe the effect of exercise would be on ouabain? Can exercise possibly mimic the effects of ouabain? H. Holzgrefe: As the ventricular proarrhythmic mechanism of ouabain is largely driven by altered calcium homeostasis with ventricular arrhythmias generally arising subsequent to delayed after depolarizations, it is difficult to envision how this effect could be initiated or substantially modified by exercise. If the ventricular arrhythmias were of sufficient duration to affect myocardial and systemic perfusion, then ischemia would certainly be an added and confounding factor. This was not addressed in the current study. Q: What sample rate was used to collect ECG data on mice and how long of a segment was recorded? DSI: Typically 1000 Hz is used for mouse ECG recordings. Q: Have validation studies been completed in conscious animals? In particular has validation been completed in NHP and swine models? DSI: Yes the validation data was from conscious animals. Data Insights is preloaded with species-specific default arrhythmia search definitions. These speciesspecific default arrhythmia search definitions were qualified for dog, non-human primate, and minipig by comparing arrhythmias identified using Data Insights against hand-scored reference data-segments. Hand-scoring was performed by a board-certified veterinary cardiologist on 41 data-segments. Each data-segment was 15 minutes in duration, for a cumulative total of 10.25 hours of data. The datasegments were analyzed independently by the cardiologist and a Data Insights operator. Analysts were blinded to the results until each dataset was fully analyzed by the respective method. In seven out of eight cases, arrhythmia incidences identified by Data Insights were congruent to those identified by hand-scoring. Premature Atrial Contractions (PAC) accounted for the only discrepancy. Detecting PACs can be complicated by naturally varying P-P intervals which confounds the definition of prematurity. In some cases a designation relies largely on judgment, not simply measurements. The three instances noted by Dr. Olivier that were not identified by Data Insights were labelled by him as "possible PACs". All overt PACs identified by Dr. Olivier were also identified by Data Insights. Q: Is this current version GLP compliant? DSI: Data Insights is compatible with Ponemah v5.20. When combined with the Ponemah Data Security Option, the software is capable of operating in accordance with FDA 21 Part 11 regulations for GLP compliance. For information on how DSI can help with GLP validation, please contact DSI Scientific Service [email protected]. Q: For Dr. Mohamed, Do you have any positive control compound data to reduce arrhythmia in your mode? Such as beta blocker? B.A. Mohamed: We have used propranolol in our study. Propranolol-treated mice showed massive reduction of arrhythmias score in contrast to Vehicle-treated animals

Q: Is the software flexible enough to export data for presentation in any format? DSI: Data Insights exports reports into Microsoft Excel. All information contained in the Data Insights dialog is available to output in the Excel out. All numeric data used to generate Data Insights graphs are also available should the user want to customize graphing within Excel or export to another visualization software. Data may also be reported without formatting to permit the user to create pivot table of results. To obtain samples of the waveform match results or the Data Insights dialog, screenshot may be taken. Q: Can the speakers recommend handbooks dealing with ECG analysis and arrhythmia in rodents? H. Holzgrefe: The speaker is not aware of any ECG textbooks that deal specifically with rodents. There are however many academic papers that provide examples of rodent ECG interpretation. Three of the most widely used preclinical and clinical ECG textbooks are listed below for additional background. 

Electrocardiography of Laboratory Animals 1st Edition by Jeffrey W. Richig and Meg M. Sleeper VMD DACVIM



Manual of Canine and Feline Cardiology, July 20, 2015 by Francis W. K. Smith Jr. DVM DACVIM and Larry P. Tilley DVM DACVIM



Rapid Interpretation of EKG's, Sixth Edition 6th Edition by Dale Dubin

B.A. Mohamed: I recommend the following… Thireau, J., Zhang, B. L., Poisson, D. and Babuty, D. (2008), Heart rate variability in mice: a theoretical and practical guide. Experimental Physiology, 93: 83–94. doi:10.1113/expphysiol.2007.040733 Q: Does DSI provide implantable transmitters/hardware for conscious recordings in rabbits? DSI: Yes. DSI PhysioTel® Implantable Telemetry is designed for monitoring and collecting data from conscious, freely moving laboratory animals. Implants are available in a variety of sizes to accommodate species and cage size requirements. Researchers and scientists can measure arterial pressure, venous pressure, left ventricular pressure, intra-ocular pressure, bladder pressure, kidney pressure, ECG, EMG, EEG, EOG, temperature, activity, as well as other parameters. Implants are available in Extra Small (for animals weighing 17 g or more), Small (for animals weighing 175 g or more, and Large (for animals weighing 2.5 kg or more). Species commonly monitored with extra-small implants include mice, hamsters, gerbils, and juvenile rats. Species commonly monitored with small implants include rats, guinea pigs, rabbits, ferrets, and marmosets. Species commonly monitored with large implants include, but are not limited to, non-human primates, dogs, rabbits, and swine. Q: For Hank, during dosing of Ouabain what is relation of diastolic pressure to detected arrhythmia? H. Holzgrefe: In the current study, the onset of increases in systemic blood pressure (systolic and diastolic) preceded the onset of ventricular arrhythmias. As such, no clear relation between diastolic pressure and proarrhythmia was observed in the current study design.

Q: For Belal: Did you quantify the blood pressure in this model? More specifically, blood pressure during arrhythmia quantification? What was the cytosolic calcium concentration in sham vs. CH or HF? B.A. Mohamed: We did not measure the BP. We did not measure the cytosolic Calcium but the Ca leak and SR Ca content. Q: For Belal: How did you specifically score the events over 24 hours? B.A. Mohamed: Arrhythmia severity was scored on the basis of the most severe arrhythmia observed in each heart over 24 hours continuous ECG recording (0= no PVCs, 1= single PVCs, 2= bigeminy or salvos, 3= non-sustained ventricular tachycardia and 4= sustained ventricular tachycardia) (1). 1. Curtis MJ, Walker MJ. Quantification of arrhythmias using scoring systems: an examination of seven scores in an in vivo model of regional myocardial ischaemia. Cardiovasc Res 1988;22:656-65. Q: Have you ever run any test for accuracy of ARR? How does this compare to manual ECG review? DSI: Yes. Please see the question regarding validation results above. Q: How are the searches applied in the data insights program? Does the user setup data parameters for what defines these beats? Or are the searches standard within the program? DSI: Data Insights includes a number of predefined species-specific searches. However, users are free to edit these searches or create their own search. Once a search is created, the user simply needs to dragand-drop the search onto the channel(s) desired to be interrogated. Data Insights will then display the match results for that search within the Results section of the dialog. Q: How Data Insight could distinguish arrhythmia to noise or artifact, more specifically when the mice or rats are moving DSI: Signals acquired from freely moving test subjects often include noise artifacts, which may result in invalid marking of some cycles, and ultimately inaccurate derived output calculations. Data Insights permits interrogation of beat by beat or averaged derived data. Incorrectly marked cycles or interesting data can often be isolated by searching on derived output parameters for extremes, or for large changes in consecutive values as shown below. Data Insights includes default searches to expose these sections of data and are indicated with a “dv_” prefix, to indicate that it is a data validation search. The ability to rapidly process and evaluate these search results is important to ensure study throughput. A result may be excluded from the current set of results or may be marked as invalid data, removing it from all further processing. In either case, sorting and bulk selection permits results to be evaluated rapidly. Further, a search definition may include a search clause using Noise as a search input, allowing the user to exclude from the Match Results any cycle that has a Noise level greater than a user defined threshold.

Q: How variable are the telemetry recordings between animals? DSI Surgical Services Team: Telemetry signals can be affected (i.e. variability) increased based on surgical placement. Some key factors to remember are the tip of the catheter must remain in freely flowing blood to consistently measure blood pressure, and the ECG leads should form a vector across the heart. The specific positioning of the ECG leads will affect the appearance of the signal. Therefore, it is advisable to determine an optimized placement for the device body, catheter(s) and biopotential (ECG) leads, etc. for your specific animal population and use fixed anatomical landmarks to ensure as much consistency as possible between individuals. New positioning may be required if you change your animal model. For example, we always recommend you obtain new measurements for the depth of catheter insertion into a mouse carotid artery if you change animal strain, size, or sex. Q: How is Data Insights different from ECG PRO? DSI: ECG Pattern Recognition Option (PRO) is an ECG signal morphology-based analysis type. It permits users to select a representative ECG cycle(s) as a template cycle(s) against which all other ECG cycles in the dataset are precisely compared. Once a template cycle is selected, the researcher may improve the placement of the fiduciary marks on the template cycle, if necessary, and then execute the analysis. Ponemah will then compare the morphology of the cycle segment(s) selected (e.g. T wave) and augment the corresponding mark placement of all cycles that match the morphology of the template cycle segment. Since the Derived Parameters (Heart Rate, RR-interval, PR-interval, etc.) are calculated based on the mark placement, this approach may lead to improved accuracy of Derived Parameter results. Data Insights, on the other hand, interrogates the Derived Parameter values based on user-defined searches to locate, classify, and report on data patterns and anomalies; e.g. cardiac arrhythmias. Using Data Insights, researchers may assess the quality of their data analysis and target problem areas for additional cleaning and analysis without having to manually over read the dataset. Data Insights’ ability to work with Derived Parameters from all channels associated with a subject (ECG, blood pressure, respiration, temperature, etc.) permits a wide variety of searches. In addition to using Derived Parameters, Data Insights can also use match information from ECG PRO in its search definitions. Q: We noticed that the T wave in mice is not well recorded. Is there a specific way to improve the recording of T wave in mice? DSI Data Services Team: The T wave in mice is different than what is seen in humans. This is evident when looking at the action potential of mouse. The Action potential in a human has a rapid late repolarization (represented by the T wave) whereas the mouse does not have this late repolarization. The “T wave” is immediately following the S wave and is seen as the second positive deflection after the R wave. Refer to the article and images in the publication referenced below for more information.

Liu, G., Iden, J. B., Kovithavongs, K., Gulamhusein, R., Duff, H. J., & Kavanagh, K. M. (2004). In vivo temporal and spatial distribution of depolarization and repolarization and the illusive murine T wave. The Journal of Physiology, 555(Pt 1), 267–79.

DSI Surgical Services Team: There have also been some publications detailing alternative surgical placements that may help improve signal quality and decrease noise. Sgoifo, A., Stilli, D., et al., Electrode Positioning for Reliable Telemetry ECG Recordings During Social Stress in Unrestrained Rats. Physiology and Behavior. 60(6). Pp. 1397-1401. 1996. Q: What acquisition program was used to acquire the data that was analyzed with Data Insights and is this only compatible with continuous data acquisition or can data insights be used with scheduled sampling? DSI: DSI’s Ponemah v5.20 software platform was used to acquire and analyze the data with Data Insights. Ponemah v5.20 is backwards compatible with previous versions of Ponemah. Data collected with Dataquest A.R.T. using continuous and/or scheduled sampling may also be converted for analysis within Ponemah, including with Data Insights. Q: What is the best method or appropriate process to calculate QTc in mice? B.A. Mohamed: We did not measure it. Q: Which fluorescein that was used to detect the SR Ca leak by the confocal microscope. B.A. Mohamed: fluo-4/AM (10 μmol/L; Molecular Probes, Life Technologies, Carlsbad, CA, USA) Q: Will using the Data Insights program eliminate the need for analysis of ECG by a cardiologist ? DSI: Data Insights offers a reliable, automated method to accurately locate and present potential arrhythmias for further adjudication by a veterinary cardiologist. Q: Do you feel there is consensus in Arrythmia definition in animal models or are there discrepancies in literature e.g. for Atrial Fibrillation where p might be present in rodents or not visible? H. Holzgrefe: For most large animals I feel that there is a general consensus where the patterns of the various arrhythmias are fairly well conserved in the four chambered mammalian heart. This statement, however, cannot be extended to rodents where there are fundamental differences in the cardiac ion channels. B.A. Mohamed: In mice the arrhythmias detection was based on the same Criteria published by previous studies. I would say there is no discrepancy between the literature at least in the parameters I used in my study (PVCs, VTs).

Q: For Belal: Was the data in mice obtained under anesthesia? B.A. Mohamed: No, the data was detected by ambulatory Telemetry (DSI) in conscious unstrained mice. Q: Can you create your own arrhythmia algorithm (pattern recognition)? DSI: Data Insights search definitions can include Template clauses which permit accessing pattern recognition output. Using this feature in conjunction with a template or a group of template that identify the morphology of an arrhythmic beat, an arrhythmia search can leverage ECG PRO. Q: Is the DATA insight software applicable for rodents? DSI: Yes. Data Insights may be used with data collect from any preclinical animal species. Q: For Belal: Is it possible to use intervention to inhibit SR-ca ion? B.A. Mohamed: Yes it is possible and now there are a lot of studies testing the protective role of drugs against arrhythmias via inhibition of SR Ca leak. Q: What is the sensitivity of the software? Also, how can one check the accuracy of their results? DSI: Data Insights is designed to promote high sensitivity. The sorting, visualization and bulk result handing capability that Data Insights provides, permits a user to err on the side of sensitivity and easily deal with false positives. Verifying accuracy is best accomplished by a manual over-read of the data Q: Would you find of a value to share through the community species specific searches that might work for some customer in order to have consistency in arrhythmia definitions in animals? DSI: Yes – as Data Insights is used in different research settings, we anticipate the library of searches will grow. These new searches will be added to our default search definitions and can also be shared via an Export/Import capability built into Data Insights Q: How do you extract PR interval if there is a lot of baseline noise in mouse ECG? DSI: A small P wave coupled with noise may render PR information unavailable. When such a situation arises, the focus shifts to ensuring that we do not use information from mismarked P waves. This can be accomplished during mark placement and supplemented by including a Noise clause in Data Insights to exclude cycles that have Noise above a user specified level, ensuring that the Data Insights report does not include information from poorly marked P waves.

Q: to Dr. Holzgrefe: can he comment on learning curve of Data Insights if someone know very well Ponemah vs. less known or new? H. Holzgrefe: As Data Insights is tightly integrated into the Ponemah user interface, the learning curve for an experienced Ponemah user can be quite rapid. In our laboratory this could generally be accomplished in a matter of days, assuming that the user was generally familiar with normal and abnormal ECG waveforms. For a new user, unaccustomed to the Ponemah interface, the learning curve will certainly be longer and is not something that can be predicted with any accuracy as it will be a very user and institution-dependent experience.

Q: to Dr. Holzgrefe: how was he analyzing Arrhythmia prior to Data Insights? How much time did he save with Data Insights? H. Holzgrefe: We did not perform comprehensive beat-to-beat arrhythmia analysis prior to the installation of Data Insights. In the absence of a semi-automated system that could scan all recorded beats, we employed traditional 10 to 30 beat periodic snapshot analyses (over read by a cardiologist) that has constituted an industry standard for many years. With Data Insights we are now able to complete full beat-to-beat arrhythmia analysis on 24-hour data sets within a few hours following the completion of data acquisition. As the two methods of arrhythmia analysis represent entirely unique and different approaches, it is not possible to accurately scale the potential time savings.

If you have additional questions for Data Sciences International (DSI) regarding content from their webinar or wish to receive additional information about Data Insights Software, telemetry products and laboratory services please contact them by phone or email:

North America

Asia Pacific

Data Sciences International (DSI) Headquarters and North America Sales 119 14th St NW Suite 100 St. Paul, MN 55112 U.S.A. Tel: 1-800-262-9687 (U.S.) Tel: +1-651-481-7400 (International) Fax: +1-651-481-7404 Email: [email protected]

Data Sciences International, Shanghai Office 780 Cailun Road, Room 618 Zhangjiang Hi-Tech Park Pudong New Area Shanghai, China 201203 Tel: +86-21-50793177 Fax: +86-21-50793033 Email: [email protected]

Europe Data Sciences International De Tweeling 20-22 5215 MC s'Hertogenbosch The Netherlands Tel: +31 13 5479356 Fax: +31 13 2202 000 Email: [email protected]

Click Here For a List of Authorized Global Distributors

Copyright 2016 Data Sciences International (DSI) & InsideScientific Corporation. All rights Reserved.