Establishing a priori and a posteriori predictive models to assess patients’ peak skin dose in interventional cardiology. Part 2: results of the VERIDIC project

Research output: Contribution to journalArticlepeer-review


  • Joëlle Feghali
  • Julie Delépierre
  • Olivera F. Ciraj-Bjelac
  • Marine Deleu
  • Francesca De Monte
  • Milan Dobric
  • Aoife Gallagher
  • Lama Hadid-Beurrier
  • Patrick Henry
  • Hrvoje Hrsak
  • Tom Kiernan
  • Rajesh Kumar
  • Zeljka Knezevic
  • Carlos Maccia
  • Marija Majer
  • Françoise L. Malchair
  • Stéphane Noble
  • Davor Obrad
  • Marta Sans-Mercé
  • Georgios Sideris
  • Georgios Simantirakis
  • Christian Spaulding
  • Giuseppe Tarantini
  • Claire Van Ngoc Ty

Institutes & Expert groups

  • University Hospital Centre Zagreb
  • Centre d’Assurance de qualité des Applications Technologiques dans le domaine de la Santé
  • APHP - Assistance Publique – Hôpitaux de Paris
  • University Paris-Sud
  • University of Belgrade - Vinča Institute of Nuclear Sciences
  • HUG - Hôpitaux universitaires de Genève - Geneva University Hospital
  • IOV IRCCS - Istituto Oncologico Veneto - Italy
  • St. James's Hospital
  • Lariboisière University Hospital
  • University Hospital Limerick
  • RBI - Ruđer Bošković Institute
  • IRA - Institute of Radiation Physics, University Hospital of Lausanne
  • EEAE – Greek Atomic Energy Commission
  • European Georges Pompidou University Hospital
  • University of Padua

Documents & links


BACKGROUND: Optimizing patient exposure in interventional cardiology is key to avoid skin injuries. PURPOSE: To establish predictive models of peak skin dose (PSD) during percutaneous coronary intervention (PCI), chronic total occlusion percutaneous coronary intervention (CTO), and transcatheter aortic valve implantation (TAVI) procedures. MATERIAL AND METHODS: A total of 534 PCI, 219 CTO, and 209 TAVI were collected from 12 hospitals in eight European countries. Independent associations between PSD and clinical and technical dose determinants were examined for those procedures using multivariate statistical analysis. A priori and a posteriori predictive models were built using stepwise multiple linear regressions. A fourfold cross-validation was performed, and models' performance was evaluated using the root mean square error (RMSE), mean absolute percentage error (MAPE), coefficient of determination (R(2)), and linear correlation coefficient (r). RESULTS: Multivariate analysis proved technical parameters to overweight clinical complexity indices with PSD mainly affected by fluoroscopy time, tube voltage, tube current, distance to detector, and tube angulation for PCI. For CTO, these were body mass index, tube voltage, and fluoroscopy contribution. For TAVI, these parameters were sex, fluoroscopy time, tube voltage, and cine acquisitions. When benchmarking the predictive models, the correlation coefficients were r = 0.45 for the a priori model and r = 0.89 for the a posteriori model for PCI. These were 0.44 and 0.67, respectively, for the CTO a priori and a posteriori models, and 0.58 and 0.74, respectively, for the TAVI a priori and a posteriori models. CONCLUSION: A priori predictive models can help operators estimate the PSD before performing the intervention while a posteriori models are more accurate estimates and can be useful in the absence of skin dose mapping solutions.


Original languageEnglish
Pages (from-to)1-14
Number of pages14
JournalActa Radiologica
Publication statusPublished - 22 Dec 2021


  • Interventional cardiology, Radiation protection, Peak skin dose, Predictive models, Optimization

ID: 7376337