通过基于三维图像的时空模型实现放射性药物在实体瘤中的传输

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Anahita Piranfar, Farshad Moradi Kashkooli, Wenbo Zhan, Ajay Bhandari, Babak Saboury, Arman Rahmim, M. Soltani
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引用次数: 0

摘要

镥-177前列腺特异性膜抗原(177Lu-PSMA)靶向放射性药物疗法是经临床批准用于治疗转移性去势抵抗性前列腺癌(mCRPC)患者的一种疗法。尽管通常的做法是勉强采用 "一刀切 "的方法,但医学界认为,深入了解放射性药物疗法并使其个性化还有很大的空间。为了实现这一目标,我们提出了一种基于临床成像数据的三维时空放射性药物给药模型,以模拟前列腺肿瘤内 177Lu-PSMA 的药代动力学。该模型包括间隙流动、放射性药物在组织中的运输、受体循环、与配体的结合/解离、PSMA 受体的合成、受体循环、放射性药物的内化以及受体和药物的降解。该模型针对一系列注射量(100-1000 nmol)、受体密度(10-500 nmol-l-1)和受体循环速率(10-4 至 10-1 min-1)值进行了研究。此外,还讨论了注入类型、不同的对流-扩散-反应机制、特征时间尺度和长度尺度。研究发现,增加受体密度、配体量和标记配体可提高肿瘤对放射性药物的吸收。高受体循环速率(0.1 min-1)可促进与肿瘤细胞受体的重复结合,从而增加放射性药物浓度。与栓剂给药相比,持续输注可使肿瘤内的放射性药物浓度更高。通过了解放射性药物在肿瘤内的分布机制,这些见解对于推进前列腺癌的靶向治疗至关重要。此外,还计算了特征长度和平流时间尺度。所提出的肿瘤时空传输模型可以分析影响 177Lu-PSMA 传输的不同生理参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Radiopharmaceutical transport in solid tumors via a 3-dimensional image-based spatiotemporal model

Radiopharmaceutical transport in solid tumors via a 3-dimensional image-based spatiotemporal model

Lutetium-177 prostate-specific membrane antigen (177Lu-PSMA)-targeted radiopharmaceutical therapy is a clinically approved treatment for patients with metastatic castration-resistant prostate cancer (mCRPC). Even though common practice reluctantly follows “one size fits all” approach, medical community believes there is significant room for deeper understanding and personalization of radiopharmaceutical therapies. To pursue this aim, we present a 3-dimensional spatiotemporal radiopharmaceutical delivery model based on clinical imaging data to simulate pharmacokinetic of 177Lu-PSMA within the prostate tumors. The model includes interstitial flow, radiopharmaceutical transport in tissues, receptor cycles, association/dissociation with ligands, synthesis of PSMA receptors, receptor recycling, internalization of radiopharmaceuticals, and degradation of receptors and drugs. The model was studied for a range of values for injection amount (100–1000 nmol), receptor density (10–500 nmol•l–1), and recycling rate of receptors (10–4 to 10–1 min–1). Furthermore, injection type, different convection-diffusion-reaction mechanisms, characteristic time scales, and length scales are discussed. The study found that increasing receptor density, ligand amount, and labeled ligands improved radiopharmaceutical uptake in the tumor. A high receptor recycling rate (0.1 min–1) increased radiopharmaceutical concentration by promoting repeated binding to tumor cell receptors. Continuous infusion results in higher radiopharmaceutical concentrations within tumors compared to bolus administration. These insights are crucial for advancing targeted therapy for prostate cancer by understanding the mechanism of radiopharmaceutical distribution in tumors. Furthermore, measures of characteristic length and advection time scale were computed. The presented spatiotemporal tumor transport model can analyze different physiological parameters affecting 177Lu-PSMA delivery.

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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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