Prospective Registry Study on Thermal Liver Ablation of Primary and Secondary Liver Tumours Named the A-IMAGIO Study

  • A. L. van der Velden*
  • , C. A.M. Verhagen
  • , F. Gholamiankhah
  • , H. Rahmani
  • , R. M. van Dam
  • , J. J. van Duijn-de Vreugd
  • , S. R. Simon
  • , P. Hendriks
  • , G. C.M. van Erp
  • , R. R.M.M. Knapen
  • , L. Volmer
  • , K. Overduin
  • , J. P.B.M. Braak
  • , R. Bale
  • , G. Laimer
  • , R. Lanocita
  • , M. R. Meijerink
  • , Y. Kampfer
  • , A. Denys
  • , P. Littler
  • B. Sternberg, H. Kobeiter, M. L.J. Smits, M. J.L. van Strijen, K. J. Pieterman, A. Broersen, J. Dijkstra, R. Brecheisen, M. C. Burgmans, C. van der Leij
*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Purpose: The long-term objective of the Ablation-IMaging and Advanced Guidance for workflow optimization in Interventional Oncology (A-IMAGIO) project is to develop a standardized, accessible, low-complex, high-precision, end-to-end solution for treatment planning, needle guidance, and treatment evaluation for thermal liver ablation. Materials and Methods: This is a prospective, international, multicentre, observational registry study. Patients will be included with age ≥ 18 years, diagnosed with primary or secondary liver tumours, and undergoing thermal liver ablation. A detailed dataset of medical history, baseline clinical and imaging parameters, tumour characteristics, ablation technique/parameters, treatment outcomes, periprocedural images, and adverse events, will be collected for all participants. This data will be used to develop AI algorithms for prognostic modelling and quantitative imaging analysis. Additionally, costs associated with thermal liver ablation clinical pathway will be evaluated. Expected Gain of Knowledge: The results of this registry study are expected to provide profound insight in current variability among centres in performing thermal liver ablation, and identify best practices in order to eventually facilitate standardization and universally excellent clinical outcomes. Trial Registration: National Institute of Health Clinical trial database (NCT06179602) https://clinicaltrials.gov/study/NCT06179602.

Original languageEnglish
Pages (from-to)1193-1199
Number of pages7
JournalCardiovascular and Interventional Radiology
Volume48
Issue number8
Early online date23 Jun 2025
DOIs
Publication statusPublished - Aug 2025

Keywords

  • Artificial intelligence
  • Colorectal liver metastases
  • Deep learning
  • Hepatocellular carcinoma
  • Microwave ablation
  • Radiofrequency ablation
  • Thermal ablation

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