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PET/SPECT/Spectral-CT/CBCT imaging in a small-animal radiation therapy platform: A Monte Carlo study-Part II: Biologically guided radiotherapy.
Li, Xiadong; Wang, Hui; Xu, Lixia; Kuang, Yu.
Afiliación
  • Li X; Medical Imaging and Translational Medicine laboratory, Department of Radiotherapy, Affiliated Hangzhou Cancer Hospital, Westlake University School of Medicine, Hangzhou, Zhejiang, China.
  • Wang H; Medical Imaging and Translational Medicine laboratory, Department of Radiotherapy, Affiliated Hangzhou Cancer Hospital, Westlake University School of Medicine, Hangzhou, Zhejiang, China.
  • Xu L; Medical Physics Program, University of Nevada, Las Vegas, Nevada, USA.
  • Kuang Y; Medical Imaging and Translational Medicine laboratory, Department of Radiotherapy, Affiliated Hangzhou Cancer Hospital, Westlake University School of Medicine, Hangzhou, Zhejiang, China.
Med Phys ; 51(5): 3619-3634, 2024 May.
Article en En | MEDLINE | ID: mdl-38517359
ABSTRACT

BACKGROUND:

This study addresses the technical gap between clinical radiation therapy (RT) and preclinical small-animal RT, hindering the comprehensive validation of innovative clinical RT approaches in small-animal models of cancer and the translation of preclinical RT studies into clinical practices.

PURPOSE:

The main aim was to explore the feasibility of biologically guided RT implemented within a small-animal radiation therapy (SART) platform, with integrated quad-modal on-board positron emission tomography (PET), single-photon emission computed tomography, photon-counting spectral CT, and cone-beam CT (CBCT) imaging, in a Monte Carlo model as a proof-of-concept.

METHODS:

We developed a SART workflow employing quad-modal imaging guidance, integrating multimodal image-guided RT and emission-guided RT (EGRT). The EGRT algorithm was outlined using positron signals from a PET radiotracer, enabling near real-time adjustments to radiation treatment beams for precise targeting in the presence of a 2-mm setup error. Molecular image-guided RT, incorporating a dose escalation/de-escalation scheme, was demonstrated using a simulated phantom with a dose painting plan. The plan involved delivering a low dose to the CBCT-delineated planning target volume (PTV) and a high dose boosted to the highly active biological target volume (hBTV) identified by the 18F-PET image. Additionally, the Bayesian eigentissue decomposition method illustrated the quantitative decomposition of radiotherapy-related parameters, specifically iodine uptake fraction and virtual noncontrast (VNC) electron density, using a simulated phantom with Kidney1 and Liver2 inserts mixed with an iodine contrast agent at electron fractions of 0.01-0.02.

RESULTS:

EGRT simulations generated over 4,000 beamlet responses in dose slice deliveries and illustrated superior dose coverage and distribution with significantly lower doses delivered to normal tissues, even with a 2-mm setup error introduced, demonstrating the robustness of the novel EGRT scheme compared to conventional image-guided RT. In the dose-painting plan, doubling the dose to the hBTV while maintaining a low dose for the PTV resulted in an organ-at-risk (OAR) dose comparable to the low-dose treatment for the PTV alone. Furthermore, the decomposition of radiotherapy-related parameters in Kidney1 and Liver2 inserts, including iodine uptake fractions and VNC electron densities, exhibited average relative errors of less than 1.0% and 2.5%, respectively.

CONCLUSIONS:

The results demonstrated the successful implementation of biologically guided RT within the proposed quad-model image-guided SART platform, with potential applications in preclinical RT and adaptive RT studies.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Método de Montecarlo / Tomografía Computarizada de Haz Cónico / Radioterapia Guiada por Imagen Idioma: En Revista: Med Phys Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Método de Montecarlo / Tomografía Computarizada de Haz Cónico / Radioterapia Guiada por Imagen Idioma: En Revista: Med Phys Año: 2024 Tipo del documento: Article País de afiliación: China