EuroSafe Imaging 2020
Action 9 - Facilitation of research in advanced topics of radiation protection, Interventional non-vascular, Interventional vascular, Radioprotection / Radiation dose, Fluoroscopy, Dosimetry, Radiation effects, Radiation safety, Dosimetric comparison, Quality assurance, Retrospective, Not applicable, Performed at one institution
M. Hellström, C. Granberg, J. Lundman, K. Ahlström Riklund, J. S. Andersson
During interventional radiology (IR) procedures, X-ray induced skin injuries may occur due to high absorbed patient skin doses. In some complicated interventions, the skin doses to patients approach the levels of some radiotherapy treatments, which can result in acute skin injuries such as erythema, permanent epilation and delayed skin necrosis .
The cumulated absorbed dose to skin varies spatially over the skin surface of the patient due to procedure-specifics such as beam-angulation and table position. The peak value of the procedure cumulative absorbed dose to the skin, commonly denoted peak skin dose (PSD), is the metric of interest for patient-specific follow-up and monitoring of X-ray induced skin injuries. Therefore, an easy-to-use and clinically applicable tool for PSD estimation is of interest for post-procedure evaluation. The intervention staff can use PSD as a decision basis for whether the patient should be booked for a follow-up appointment with a dermatologist.
Action levels for skin injury follow-up are commonly based solely on the interventional reference point (IRP) cumulative air Kerma. This metric lack influence of irradiation geometry, conversion of air Kerma to absorbed skin dose, scattered radiation, and pre-patient attenuation. However, methodologies for calculating PSD from IRP air Kerma is established , and several of the required irradiation event specifics are reported by modern radiological equipment in the radiation dose structured report (RDSR).
The purpose of this work was to develop an improved skin dose metric for IR procedures, in the form of a PSD estimation framework based on RDSR data. Necessary features of this framework are automation, customizability, and cross-platform compliance between different vendors and models to simplify the end-usage in a clinical environment.