Model-based versus specific dosimetry in diagnostic context: Comparison of three dosimetric approaches

Authors


Abstract

Purpose:

The dosimetric assessment of novel radiotracers represents a legal requirement in most countries. While the techniques for the computation of internal absorbed dose in a therapeutic context have made huge progresses in recent years, in a diagnostic scenario the absorbed dose is usually extracted from model-based lookup tables, most often derived from International Commission on Radiological Protection (ICRP) or Medical Internal Radiation Dose (MIRD) Committee models. The level of approximation introduced by these models may impact the resulting dosimetry. The aim of this work is to establish whether a more refined approach to dosimetry can be implemented in nuclear medicine diagnostics, by analyzing a specific case.

Methods:

The authors calculated absorbed doses to various organs in six healthy volunteers administered with flutemetamol (18F) injection. Each patient underwent from 8 to 10 whole body 3D PET/CT scans. This dataset was analyzed using a Monte Carlo (MC) application developed in-house using the toolkit gate that is capable to take into account patient-specific anatomy and radiotracer distribution at the voxel level. They compared the absorbed doses obtained with gate to those calculated with two commercially available software: olinda/exm and stratos implementing a dose voxel kernel convolution approach.

Results:

Absorbed doses calculated with gate were higher than those calculated with olinda. The average ratio between gate absorbed doses and olinda’s was 1.38 ± 0.34 σ (from 0.93 to 2.23). The discrepancy was particularly high for the thyroid, with an average gate/olinda ratio of 1.97 ± 0.83 σ for the six patients. Differences between stratos and gate were found to be higher. The average ratio between gate and stratos absorbed doses was 2.51 ± 1.21 σ (from 1.09 to 6.06).

Conclusions:

This study demonstrates how the choice of the absorbed dose calculation algorithm may introduce a bias when gamma radiations are of importance, as is the case in nuclear medicine diagnostics.

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