Deep transformer-based personalized dosimetry from SPECT/CT images: a hybrid approach for [¹⁷⁷Lu]Lu-DOTATATE radiopharmaceutical therapy.

ABSTRACT:

Purpose

Accurate dosimetry is critical for ensuring the safety and efficacy of radiopharmaceutical therapies. In current clinical dosimetry practice, MIRD formalisms are widely employed. However, with the rapid advancement of deep learning (DL) algorithms, there has been an increasing interest in leveraging the calculation speed and automation capabilities for different tasks. We aimed to develop a hybrid transformer-based deep learning (DL) model that incorporates a multiple voxel S-value (MSV) approach for voxel-level dosimetry in [¹⁷⁷Lu]Lu-DOTATATE therapy. The goal was to enhance the performance of the model to achieve accuracy levels closely aligned with Monte Carlo (MC) simulations, considered as the standard of reference. We extended our analysis to include MIRD f

SUBMITTER: Mansouri Z 

PROVIDER: S-EPMC11043201 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature