Why the study?
Target definition and transfer from electro-anatomic maps to radiotherapy treatment planning systems for stereotactic arrhythmia radioablation is challenging and operator-dependent.
Do 3D-3D and 2D-3D registration software solutions yield similar Clinical Target Volumes when transferring targets from electro-anatomic maps to radiotherapy treatment planning systems in patients with ventricular tachycardia?
Do 3D-3D and 2D-3D registration software solutions yield similar Clinical Target Volumes when transferring targets from electro-anatomic maps to radiotherapy treatment planning systems in patients with ventricular tachycardia?
Two conceptually different software solutions for transferring stereotactic arrhythmia radioablation targets from electro-anatomic maps to treatment planning systems resulted in nearly identical 3D structures, supporting their use for standardized workflows.
Software registration may aid EAM-to-TPS transfer in STAR; leaves open need for prospective validation before routine adoption.
BACKGROUND: Stereotactic arrhythmia radioablation (STAR) is a therapeutic option for ventricular tachycardia (VT) where catheter-based ablation is not feasible or has previously failed. Target definition and its transfer from electro-anatomic maps (EAM) to radiotherapy treatment planning systems (TPS) is challenging and operator-dependent. Software solutions have been developed to register EAM with cardiac CT and semi-automatically transfer 2D target surface data into 3D CT volume coordinates. Results of a cross-validation study of two conceptually different software solutions using data from the RAVENTA trial (NCT03867747) are reported. METHODS: Clinical Target Volumes (CTVs) were created from target regions delineated on EAM using two conceptually different approaches by separate investigators on data of 10 patients, blinded to each other's results. Targets were transferred using 3D-3D registration and 2D-3D registration, respectively. The resulting CTVs were compared in a core-lab using two complementary analysis software packages for structure similarity and geometric characteristics. RESULTS: . The Dice-coefficient was 0.84 ± 0.04; median surface-distance and Hausdorff-distance were 0.53 ± 0.37 mm and 6.91 ± 2.26 mm, respectively. The 3D-center-of-mass difference was 3.62 ± 0.99 mm. Geometrical volume similarity was 0.94 ± 0.05 %. CONCLUSION: The STAR targets transferred from EAM to TPS using both software solutions resulted in nearly identical 3D structures. Both solutions can be used for QA (quality assurance) and EAM-to-TPS transfer of STAR-targets. Semi-automated methods could potentially help to avoid mistargeting in STAR and offer standardized workflows for methodically harmonized treatments.
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Hohmann et al. (2024) studied this question.
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