公开(公告)号：US10850122B2

公开(公告)日：2020-12-01

申请号：US15843706

申请日：2017-12-15

Applicant: STC.UNM

Inventor： Shuang Luan ,  Daniel Andres Riofrio Almeida

IPC: A61N5/10 ,  G06N3/00 ,  G06F19/00 ,  G16H20/40

Abstract: An optimization technique for use with radiation therapy planning that combines stochastic optimization techniques such as Particle Swarm Optimization (PSO) with deterministic techniques to solve for optimal and reliable locations for delivery of radiation doses to a targeted tumor while minimizing the radiation dose experienced by the surrounding critical structures such as normal tissues and organs.

公开(公告)号：US20170036037A1

公开(公告)日：2017-02-09

申请号：US15304306

申请日：2015-04-30

Applicant: STC.UNM

Inventor： Shuang Luan ,  Daniel Andres Riofrio Almeida

IPC: A61N5/10 ,  G06F19/00

CPC classification number: A61N5/1031 ,  A61N5/10 ,  A61N5/1001 ,  A61N5/1007 ,  A61N5/103 ,  A61N5/1084 ,  A61N2005/101 ,  A61N2005/1024 ,  A61N2005/1034 ,  G06F19/00 ,  G06F19/325 ,  G06N3/006 ,  G16H20/40

Abstract: An optimization technique for use with radiation therapy planning that combines stochastic optimization techniques such as Particle Swarm Optimization (PSO) with deterministic techniques to solve for optimal and reliable locations for delivery of radiation doses to a targeted tumor while minimizing the radiation dose experienced by the surrounding critical structures such as normal tissues and organs.

Abstract translation: 一种用于放射治疗计划的优化技术，其将随机优化技术（例如粒子群优化（PSO））与确定性技术相结合，以解决将靶向肿瘤辐射剂量递送到最佳和可靠的位置，同时最小化周围的辐射剂量 关键结构如正常组织和器官。

公开(公告)号：US09561389B2

公开(公告)日：2017-02-07

申请号：US15179289

申请日：2016-06-10

Applicant: STC.UNM

Inventor： Shuang Luan ,  Lijun Ma ,  Zhe Chen

IPC: A61N5/00 ,  A61N5/10

CPC classification number: A61N5/1084 ,  A61B6/4085 ,  A61N5/10 ,  A61N5/1031 ,  A61N5/1065 ,  A61N5/1067 ,  A61N5/1071 ,  A61N5/1081 ,  A61N2005/1074

Abstract: Photon-based radiosurgery is widely used for treating local and regional tumors. The key to improving the quality of radiosurgery is to increase the dose falloff rate from high dose regions inside the tumor to low dose regions of nearby healthy tissues and structures. Dynamic photon painting (DPP) further increases dose falloff rate by treating a target by moving a beam source along a dynamic trajectory, where the speed, direction and even dose rate of the beam source change constantly during irradiation. DPP creates dose gradient that rivals proton Bragg Peak and outperforms Gamma Knife® radiosurgery.

Abstract translation: 基于光子的放射外科手术广泛用于治疗局部和局部肿瘤。 提高放射外科手术质量的关键是提高肿瘤内部高剂量区域到附近健康组织和结构的低剂量区域的剂量衰减率。 动态光子绘画（DPP）通过沿着动态轨迹移动光束源来处理目标物体进一步增加剂量衰减速率，其中光束源的速度，方向和均匀剂量率在照射期间不断变化。 DPP产生与质子Bragg峰值相当的剂量梯度，并优于GammaKnife®放射外科手术。