Characterization of Cardiac Electrogram Signals During Atrial Fibrillation

Atrial fibrillation (AF) is the most common cardiac arrhythmia in United States. The most popular treatment for AF is a percutaneous procedure called catheter ablation. Current AF ablation procedures unfortunately have a poor success rate, primarily because the mechanisms involved in AF are incompletely understood even today. Intra-atrial electrograms have previously been shown to provide information on the mechanisms of AF. This thesis focuses on two such mechanisms – AF-sustaining sites known as sustained rotational activities (RotAs), and atrial tissue with unique electrical properties known as myocardial scars. Catheter ablation procedures today construct the 3D electroanatomic map of the left atrium (LA) by maneuvering a conventional Multipolar Diagnostic Catheter (MPDC) along the LA endocardial surface. These procedures are limited to pulmonary vein isolation and other linear ablation performed on various regions of the left atrium (such as roof and mitral isthmus) where the regions are decided based on the atrial anatomy. However, it remains unclear how to utilize the information provided by the MPDC to analyze and characterize the RotAs and scars. Previous electrogram characterization studies mainly use a single bipole rather than MPDCs to characterize the electrograms based on features such as cycle length or dominant frequency from the time or frequency domain. In this thesis we developed novel techniques for investigating the above mentioned mechanisms using signal analysis, mathematical modeling, numerical simulation and clinical experiments, all utilizing MPDC recordings. First, the variations in the total conduction delay (TCD) from MPDC electrograms as the MPDC moves towards a RotA source was investigated. Second, the maximum peak-to-peak amplitudes of MPDC electrograms recorded during AF and NSR were analyzed. This thesis provides insights into methods of characterization of cardiac electrograms and the findings of this thesis could address the current challenges in AF ablation

Computer-Aided Clinical Decision Support Systems for Atrial Fibrillation

Clinical decision support systems (clinical DSSs) are widely used today for various clinical applications such as diagnosis, treatment, and recovery. Clinical DSS aims to enhance the end‐to‐end therapy management for the doctors, and also helps to provide improved experience for patients during each phase of the therapy. The goal of this chapter is to provide an insight into the clinical DSS associated with the highly prevalent heart rhythm disorder, atrial fibrillation (AF). The use of clinical DSS in AF management is ubiquitous, starting from detection of AF through sophisticated electrophysiology treatment procedures, all the way to monitoring the patient\u27s health during follow‐ups. Most of the software associated with AF DSS are developed based on signal processing, image processing, and artificial intelligence techniques. The chapter begins with a brief description of DSS in general and then introduces DSS that are used for various clinical applications. The chapter continues with a background on AF and some relevant mechanisms. Finally, a couple of clinical DSS used today in regard with AF are discussed, along with some proposed methods for potential implementation of clinical DSS for detection of AF, prediction of an AF treatment outcome, and localization of AF targets during a treatment procedure

Mediastinal masses - the bad, the ugly and the unusual!

Background: Differential diagnosis of mediastinal masses is wide and management of individual cases can be challenging. In addition to common malignancies e.g. lymphomas and thymomas. Many other benign and malignant conditions can present with mediastinal masses. Patients and Methods: We describe five patients with a diagnosis of mediastinal mass. We wish to showcase the range of diagnosis possible in these situations. This is followed by a brief discussion on the general approach to such cases. Conclusion: A good history, detailed careful clinical examination, judicious use of imaging and investigations e.g. blood counts and tumour makers can give a vital clue to the diagnosis of mediastinal mass

Predicting acute termination and non-termination during ablation of human atrial fibrillation using quantitative indices

Background: Termination of atrial fibrillation (AF), the most common arrhythmia in the United States, during catheter ablation is an attractive procedural endpoint, which has been associated with improved long-term outcome in some studies. It is not clear, however, whether it is possible to predict termination using clinical data. We developed and applied three quantitative indices in global multielectrode recordings of AF prior to ablation: average dominant frequency (ADF), spectral power index (SPI), and electrogram quality index (EQI). Methods: In N = 42 persistent AF patients (65 ± 9 years, 14% female) we collected unipolar electrograms from 64-pole baskets (Abbott, CA). We studied N = 17 patients in whom AF terminated during ablation ('Term') and N = 25 in whom it did not ('Non-term'). For each index, we determined its ability to predict ablation by computing receiver operating characteristic (ROC) and calculated the area under the curve (AUC). Results: The ADF did not differ for Term and Non-term patients at 5.28 ± 0.82 Hz and 5.51 ± 0.81 Hz, respectively (p = 0.34). Conversely, the SPI for these two groups was. 0.85 (0.80-0.92) and 0.97 (0.93-0.98) and the EQI was 0.61 (0.58-0.64) and 0.56 (0.55-0.59) (p < 0.0001). The AUC for predicting AF termination for the SPI was 0.85 ([0.68, 0.95] 95% CI), and for the EQI, 0.86 ([0.72, 0.95] 95% CI). Conclusion: Both the EQI and the SPI may provide a useful clinical tool to predict procedural ablation outcome in persistent AF patients. Future studies are required to identify which physiological features of AF are revealed by these indices and hence linked to AF termination or non-termination

Atrial fibrillation signatures on intracardiac electrograms identified by deep learning

Automatic detection of atrial fibrillation (AF) by cardiac devices is increasingly common yet suboptimally groups AF, flutter or tachycardia (AT) together as 'high rate events'. This may delay or misdirect therapy. Objective: We hypothesized that deep learning (DL) can accurately classify AF from AT by revealing electrogram (EGM) signatures. Methods: We studied 86 patients in whom the diagnosis of AF or AT was established at electrophysiological study (25 female, 65 ± 11 years). Custom DL architectures were trained to identify AF using N = 29,340 unipolar and N = 23,760 bipolar EGM segments. We compared DL to traditional classifiers based on rate or regularity. We explained DL using computer models to assess the impact of controlled variations in shape, rate and timing on AF/AT classification in 246,067 EGMs reconstructed from clinical data. Results: DL identified AF with AUC of 0.97 ± 0.04 (unipolar) and 0.92 ± 0.09 (bipolar). Rule-based classifiers misclassified ∼10-12% of cases. DL classification was explained by regularity in EGM shape (13%) or timing (26%), and rate (60%; p 15% timing variation, <0.48 correlation in beat-to-beat EGM shapes and CL < 190 ms (p < 0.001). Conclusions: Deep learning of intracardiac EGMs can identify AF or AT via signatures of rate, regularity in timing or shape, and specific EGM shapes. Future work should examine if these signatures differ between different clinical subpopulations with AF

Microbial Production of Amylase from Cassava Waste

Bacterium mura was isolated from cassava waste, (Tamil Nadu, India) for the production of extracellular amylase. On screening for amylase producing bacteria, 5 isolates showed positive results, of which Bacterium mura showed best amylase activity. The optimal conditions for the amylase activity were found at pH 6.0 (39 U/ml) and at temperature 37°C. Amylase activity was found to be higher when lactose (31 U/ml), casein, barley (42 U/ml) and SDS (32 U/ml) were used as the carbon source, nitrogen source, agro waste source and as additives respectively. The enzyme was partially purified by dialysis and the molecular mass was found to be 65kDa by SDS-PAGE. The partially purified and crude amylase was confirmed by zymogram. The partially purified amylase was used in bread making, which improved the softening of the bread and was used as a de-sizing agent

Three dimensional reconstruction to visualize atrial fibrillation activation patterns on curved atrial geometry

Background: The rotational activation created by spiral waves may be a mechanism for atrial fibrillation (AF), yet it is unclear how activation patterns obtained from endocardial baskets are influenced by the 3D geometric curvature of the atrium or 'unfolding' into 2D maps. We develop algorithms that can visualize spiral waves and their tip locations on curved atrial geometries. We use these algorithms to quantify differences in AF maps and spiral tip locations between 3D basket reconstructions, projection onto 3D anatomical shells and unfolded 2D surfaces. Methods: We tested our algorithms in N = 20 patients in whom AF was recorded from 64-pole baskets (Abbott, CA). Phase maps were generated by non-proprietary software to identify the tips of spiral waves, indicated by phase singularities. The number and density of spiral tips were compared in patient-specific 3D shells constructed from the basket, as well as 3D maps from clinical electroanatomic mapping systems and 2D maps. Results: Patients (59.4±12.7 yrs, 60% M) showed 1.7±0.8 phase singularities/patient, in whom ablation terminated AF in 11/20 patients (55%). There was no difference in the location of phase singularities, between 3D curved surfaces and 2D unfolded surfaces, with a median correlation coefficient between phase singularity density maps of 0.985 (0.978-0.990). No significant impact was noted by phase singularities location in more curved regions or relative to the basket location (p>0.1). Conclusions: AF maps and phase singularities mapped by endocardial baskets are qualitatively and quantitatively similar whether calculated by 3D phase maps on patient-specific curved atrial geometries or in 2D. Phase maps on patient-specific geometries may be easier to interpret relative to critical structures for ablation planning

Management of B-cell lineage acute lymphoblastic leukemia: expert opinion from an Indian panel via Delphi consensus method

IntroductionCurrently, there are no guidelines for the management of B-cell lineage acute lymphoblastic leukemia (B-ALL) from an Indian perspective. The diagnostic workup, monitoring, and treatment of B-ALL vary among different physicians and institutes.ObjectiveTo develop evidence-based practical consensus recommendations for the management of B-ALL in Indian settings.MethodsModified Delphi consensus methodology was considered to arrive at a consensus. An expert scientific committee of 15 experts from India constituted the panel. Clinically relevant questions belonging to three major domains were drafted for presentation and discussion: (i) diagnosis and risk assignment; (ii) frontline treatment; and (iii) choice of therapy (optimal vs. real-world practice) in relapsed/refractory (R/R) settings. The questionnaire was shared with the panel members through an online survey platform. The level of consensus was categorized into high (≥ 80%), moderate (60%–79%), and no consensus (&lt; 60%). The process involved 2 rounds of discussion and 3 rounds of Delphi survey. The questions that received near or no consensus were discussed during virtual meetings (Delphi rounds 1 and 2). The final draft of the consensus was emailed to the panel for final review.ResultsExperts recommended morphologic assessment of peripheral blood or bone marrow, flow cytometric immunophenotyping, and conventional cytogenetic analysis in the initial diagnostic workup. Berlin–Frankfurt–Münster (BFM)–based protocol is the preferred frontline therapy in pediatric and adolescent and young adult patients with B-ALL. BFM/German Multicenter Study Group for Adult Acute Lymphoblastic Leukemia–based regimen is suggested in adult patients with B-ALL. Immunotherapy (blinatumomab or inotuzumab ozogamicin) followed by allogeneic hematopoietic cell transplantation (allo-HCT) is the optimal choice of therapy that would yield the best outcomes if offered in the first salvage in patients with R/R B-ALL. In patients with financial constraints or prior allo-HCT (real-world practice) at first relapse, standard-intensive chemotherapy followed by allo-HCT may be considered. For subsequent relapses, chimeric antigen receptor T-cell therapy or palliative care was suggested as the optimal choice of therapy.ConclusionThis expert consensus will offer guidance to oncologists/clinicians on the management of B-ALL in Indian settings