Interobserver Variability in Target Definition for Stereotactic Arrhythmia Radioablation

BackgroundStereotactic arrhythmia radioablation (STAR) is emerging as a potential new therapy for patients with refractory ventricular tachycardia (VT). The arrhythmogenic substrate (target) is synthesized from clinical and electro-anatomical information. This study was designed to evaluate the baseline interobserver variability in target delineation for STAR. MethodsDelineation software designed for research purposes was used. The study was split into three phases. Firstly, electrophysiologists (observers) delineated a well-defined structure in three patients (spinal canal). Secondly, observers delineated the arrhythmogenic cardiac VT target in three patients previously treated with STAR based on case descriptions. To evaluate baseline performance, a basic workflow approach was used, no advanced techniques were allowed (e.g. image integration). Thirdly, observers delineated three predefined segments from the cardiac 17-segment model. Interobserver variability was evaluated by assessing volumes, variation in distance to the median volume as expressed by the root-mean-square of the observer standard deviation (RMS SD) over the target volume, and the Dice coefficient. ResultsTen electrophysiologists completed the study. For the first phase (spinal canal delineation), interobserver variability was low as indicated by low variation in distance to the median volume (RMS SD range: 0.02-0.02cm) and high Dice coefficients (mean: 0.97{+/-}0.01). In the second phase (VT-target delineation), distance to the median volume was large (RMS SD range: 0.52-1.02cm) and the Dice coefficients low (mean: 0.40{+/-}0.15). In the third phase (segment delineation), similar results were observed (RMS SD range: 0.51-1.55cm, Dice coefficient mean: 0.31{+/-}0.21) ConclusionsInterobserver variability is high for manual delineation of the VT-target and ventricular segments. Difficulties in cardiac anatomical orientation on traditional radiation oncology CT scans appear to be an important driver of variability. This evaluation of the baseline observer variation shows that there is a need for methods and tools to improve variability and allows for future comparison of interventions aiming to reduce observer variation.