Advancing Hyperspectral Targeted Alpha Therapy with Adversarial Machine Learning

Fuente: arXiv
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Hauptverfasser: Zhao, Jim, Leadman, Greg
Format: Preprint
Veröffentlicht: 2024
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author Zhao, Jim
Leadman, Greg
author_facet Zhao, Jim
Leadman, Greg
contents Targeted Alpha Therapy (TAT) has emerged as a promising modality for the treatment of various malignancies, leveraging the high linear energy transfer (LET) and short range of alpha particles to selectively irradiate cancer cells while sparing healthy tissue. Monitoring and optimizing TAT delivery is crucial for its clinical success. Hyper-spectral Single Photon Imaging (HSPI) presents a novel and versatile approach for the real-time assessment of TAT in vivo. This study introduces a comprehensive framework for HSPI in TAT, encompassing spectral unmixing, quantitative dosimetry, and spatiotemporal visualization. We report the development of a dedicated HSPI system tailored to alpha-emitting radionuclides, enabling the simultaneous acquisition of high-resolution spectral data and single-photon localization. Utilizing advanced spectral unmixing algorithms, we demonstrate the discrimination of alpha-induced scintillation from background fluorescence, facilitating precise alpha particle tracking with adversarial machine learning.
format Preprint
id arxiv_https___arxiv_org_abs_2403_07149
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Advancing Hyperspectral Targeted Alpha Therapy with Adversarial Machine Learning
Zhao, Jim
Leadman, Greg
Medical Physics
Targeted Alpha Therapy (TAT) has emerged as a promising modality for the treatment of various malignancies, leveraging the high linear energy transfer (LET) and short range of alpha particles to selectively irradiate cancer cells while sparing healthy tissue. Monitoring and optimizing TAT delivery is crucial for its clinical success. Hyper-spectral Single Photon Imaging (HSPI) presents a novel and versatile approach for the real-time assessment of TAT in vivo. This study introduces a comprehensive framework for HSPI in TAT, encompassing spectral unmixing, quantitative dosimetry, and spatiotemporal visualization. We report the development of a dedicated HSPI system tailored to alpha-emitting radionuclides, enabling the simultaneous acquisition of high-resolution spectral data and single-photon localization. Utilizing advanced spectral unmixing algorithms, we demonstrate the discrimination of alpha-induced scintillation from background fluorescence, facilitating precise alpha particle tracking with adversarial machine learning.
title Advancing Hyperspectral Targeted Alpha Therapy with Adversarial Machine Learning
topic Medical Physics
url https://arxiv.org/abs/2403.07149