Data-Driven Respiration-Gated SPECT for Liver Radioembolization

Antoine Robert (1) , Simon Rit (1) , Thomas Baudier (1) , Julien Jomier (1) , David Sarrut (1)

1 Imagerie Tomographique et Radiothérapie

Respiratory motion leads to blur and artifacts in single photon emission computed tomography (SPECT) images. This may be an issue in some treatments such as liver radioembolization. The purpose of this work was to reconstruct four-dimensional (4D) respiration-gated SPECT images using a data-driven approach. A respiratory signal was extracted from SPECT list-mode data using Laplacian Eigenmaps and used for retrospective phase gating. The method was evaluated on various SPECT datasets: Monte Carlo simulation of a patient acquisition, several acquisitions of a dynamic phantom and 20 acquisitions of patients treated with liver radioembolization. We observed an increase of the mean activity inside the tumor (A) and of the tumor-to-normal liver ratio (T/N) in respiration-gated SPECT image compared to the 3D image without motion correction. For the patient acquisitions, an average 3.3% (up to 11.9%) and 3.2% (up to 9.7%) increase was observed for A and T/N, respectively. For the simulation, the activity was within 2.6% of the reference without movement and around 3% for the three patterns of tumor motion simulated with the mechanical phantom. Overall, the proposed respiration-gated SPECT reconstruction improves the estimation of the activity in the tumor without the need for extra hardware.

Mots clés: SPECT; breathing motion; radioembolization; tomographic reconstruction

Domaines: Imagerie médicale

Antoine Robert, Simon Rit, Thomas Baudier, Julien Jomier, David Sarrut. Data-Driven Respiration-Gated SPECT for Liver Radioembolization. IEEE Transactions on Radiation and Plasma Medical Sciences, 2022, 6 (7), pp.778-787. ⟨10.1109/TRPMS.2021.3137990⟩. ⟨hal-03515752⟩