公开(公告)号：US20160175052A1

公开(公告)日：2016-06-23

申请号：US14908264

申请日：2014-07-16

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Prashant KUMAR ,  Yogisha MALLYA

IPC: A61B34/10 ,  A61N7/00

Abstract: A method and system for determining a utility of performing a re-planning on a patient during a radiation therapy planning are provided. They automatically estimate quality improvements which may be possible by re-planning the patient, independent of clinician bias, so that the clinician can make an informed decision regarding whether to re-plan the patient in a fast and efficient manner. More uniformity and predictability in the adaptive re-planning is thus provided.

Abstract translation: 提供了一种用于在辐射治疗计划期间确定对患者进行重新规划的效用的方法和系统。 他们自动估计质量改善，这可能是通过重新规划患者，而不考虑临床医生的偏见，以便临床医生能够以快速高效的方式对患者进行重新规划作出明智的决定。 因此提供了适应性重新规划中的更均匀性和可预测性。

公开(公告)号：US20160166855A1

公开(公告)日：2016-06-16

申请号：US14908226

申请日：2014-07-11

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Prashant KUMAR ,  Karl Antonin BZDUSEK

IPC: A61N5/10

CPC classification number: A61N5/1039 ,  A61N5/1038

Abstract: An automated treatment planning system having a planning image memory (14) which stores a volume diagnostic image; a user interface device (32) configured for a user to input data defining a plurality of regions of interest within the volume diagnostic image; and one or more processors. The processors are configured to receive the volume diagnostic image and plurality of user-defined regions of interest indicated within the volume diagnostic image; map the plurality of regions of interest to the body atlas (35) to determine anatomical locations within the plurality of regions of interest; map each region of interest of the plurality of regions of interest to the body atlas to select correct corresponding anatomical structures; receive a treatment plan template based upon the anatomical structures from a knowledge base (36). A planning module (38) is configured to generate a treatment plan using the treatment plan template.

Abstract translation: 一种具有计划图像存储器（14）的自动治疗计划系统，其存储体积诊断图像; 用户界面设备（32），其被配置用于用户输入定义所述体积诊断图像内的多个感兴趣区域的数据; 和一个或多个处理器。 处理器被配置为接收体积诊断图像和在体积诊断图像内指示的多个用户定义的感兴趣区域; 将感兴趣的多个区域映射到身体图集（35）以确定所述多个感兴趣区域内的解剖位置; 将感兴趣的多个感兴趣区域的每个感兴趣区域映射到身体图集以选择正确的对应解剖结构; 基于知识库的解剖结构（36）接收治疗计划模板。 计划模块（38）被配置为使用治疗计划模板生成治疗计划。

公开(公告)号：US20160089549A1

公开(公告)日：2016-03-31

申请号：US14785751

申请日：2014-04-17

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Vaitheeswaran RANGANATHAN ,  Gipson JOE ANTO ,  Prashant KUMAR ,  Sivaramakrishnan KRISHNAIYER RAMAN ,  Deepak Uddhavrao MAHAJAN

IPC: A61N5/10

CPC classification number: A61N5/1031 ,  A61N5/1036 ,  A61N5/1045 ,  A61N5/1077 ,  A61N2005/1074 ,  G06F19/00

Abstract: A method for dose-gradient based optimization of an intensity modulated radiation therapy plan. First, an optimizer (6) performs a first optimization (40) of the plan to generate dose distributions corresponding to the plan. Next, the optimizer (6) generates a beam specific dose gradient map (42) for each beam of the plan. Then, new dose gradients are specified (44) for the plan. Last, the optimizer (6) performs a final optimization (46) using the new dose gradients. The final optimization is given the new dose gradients as soft constraints into an objective function. The optimizer (3) applies a limiting factor to the objective function such that a first dose gradient is limited by the optimizer only if the first dose gradient exceeds the new dose gradient for a specific beamlet.

Abstract translation: 一种强度调制放射治疗计划的剂量梯度优化方法。 首先，优化器（6）执行计划的第一优化（40）以产生对应于该计划的剂量分布。 接下来，优化器（6）针对该计划的每个波束产生波束特定剂量梯度图（42）。 然后，规定新剂量梯度（44）。 最后，优化器（6）使用新的剂量梯度进行最终优化（46）。 最终优化给出了新的剂量梯度作为目标函数的软约束。 优化器（3）对目标函数应用限制因子，使得仅当第一剂量梯度超过特定子束的新剂量梯度时，优化器才限制第一剂量梯度。

公开(公告)号：US20150141733A1

公开(公告)日：2015-05-21

申请号：US14600474

申请日：2015-01-20

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Prashant KUMAR ,  Karl Antonin BZDUSEK ,  Vaitheeswaran RANGANATHAN ,  Matthew PALMER ,  Michael KANTOR

IPC: A61N5/10

CPC classification number: A61N5/1039 ,  A61N5/1031 ,  A61N5/1038 ,  A61N5/1042 ,  A61N5/1045 ,  A61N5/1047 ,  G06F19/3481 ,  G16H20/40

Abstract: A therapy planning system and method generate an optimal treatment plan accounting for changes in anatomy. Therapy is delivered to the subject according to a first auto-planned optimal treatment plan based on a first image of a subject. A second image of the subject is received after a period of time. The second image is registered with the first image to generate a deformation map accounting for physiological changes. The second image is segmented into regions of interest using the deformation map. A mapped delivered dose is computed for each region of interest using the dose delivery goals and the deformation map. The first treatment plan is merged with the segmented regions of the second image and the mapped delivered dose during optimization.

Abstract translation: 治疗计划系统和方法产生解释解剖变化的最佳治疗方案。 根据受试者的第一个图像，根据第一个自动计划的最佳治疗计划，将治疗传递给该受试者。 在一段时间后收到主题的第二张图像。 将第二图像与第一图像一起登记，以生成考虑生理变化的变形图。 使用变形图将第二图像分割成感兴趣区域。 使用剂量递送目标和变形图计算每个感兴趣区域的映射递送剂量。 在优化过程中，第一个处理计划与第二个图像的分割区域和映射的递送剂量合并。

公开(公告)号：US20190388708A1

公开(公告)日：2019-12-26

申请号：US16481101

申请日：2018-01-30

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Prashant KUMAR ,  Vaitheeswaran RANGANATHAN

IPC: A61N5/10

Abstract: In order to assess the achievability of treatment goals for a radiation therapy treatment, an estimation unit generates a treatment plan for the radiation therapy treatment only on the basis of treatment goals relating to a target structure to obtain a first dose distribution, (i) segments the body region into a plurality of concentric shells (301a, 301b) surrounding the target structure (302) and determines a mean radiation dose assigned to each shell (301a, 301b) in accordance with the first dose distribution, and (iii) checks whether a further dose distribution can be determined which fulfills the treatment goals relating to at least one structure at risk and which is configured such that the mean radiation dose assigned to each shell (301a, 301b) in accordance with the further dose distribution corresponds to the mean radiation dose assigned to the same shell (301a, 301b) in accordance with the first dose distribution.

公开(公告)号：US20190038916A1

公开(公告)日：2019-02-07

申请号：US16076721

申请日：2017-03-01

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Vaitheeswaran RANGANATHAN ,  Prashant KUMAR ,  Karl Antonin BZDUSEK

IPC: A61N5/10 ,  A61B6/00

Abstract: An achievability estimate is computed for an intensity modulated radiation therapy (IMRT) geometry (32) including a target volume, an organ at risk (OAR), and at least one radiation beam. Namely, a geometric complexity (GC) metric is computed for the IMRT geometry that compares a number NT of beamlets of the at least one radiation beam available in the IMRT geometry for irradiating the target volume and a number n of these beamlets that also pass through the OAR. A GC metric ratio is computed of the GC metric for the IMRT geometry and the GC metric for a reference IMRT geometry for which an IMRT plan is achievable. If the clinician is satisfied with this estimate then optimization (38) of an IMRT plan for the IMRT geometry (32) is performed. Alternatively, a reference IMRT geometry is selected by comparing the GC metric with GC metrics of past IMRT plans.

公开(公告)号：US20170361127A1

公开(公告)日：2017-12-21

申请号：US15534697

申请日：2015-12-04

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Vaitheeswaran RANGANATHAN ,  Gipson JOE ANTO ,  Prashant KUMAR

IPC: A61N5/10

CPC classification number: A61N5/1031 ,  A61N5/1081 ,  A61N2005/1074 ,  A61N2005/1089

Abstract: A method and related system to adjust an existing treatment plan. A second optimization is run based on a dual objective function system that includes a first objective function used for the optimization in respect of the existing plan and a second, extended objective function that includes the said first objective function as a functional component.

公开(公告)号：US20200261744A1

公开(公告)日：2020-08-20

申请号：US16067861

申请日：2017-01-06

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Prashant KUMAR ,  Matthieu Frédéric BAL

IPC: A61N5/10

Abstract: The invention relates to a system and method for generating a radiotherapy treatment plan on the basis of treatment goals comprising optimization objectives and/or constraints. A planning unit (7) generates a first treatment plan including treatment parameters for fulfilling first treatment goals in a first optimization cycle, and a decision unit (8) receives second treatment goals and compares the first and second treatment goals to 5 determine a modification of the treatment goals, assigns to the modification a category from a plurality of predetermined categories, wherein to each category a strategy from a plurality of predetermined strategies for treatment plan generation is allocated, and instructs the planning unit (7) to generate the second treatment plan in accordance with a strategy allocated to the determined category of modifications in a second optimization cycle.

公开(公告)号：US20180154177A1

公开(公告)日：2018-06-07

申请号：US15572628

申请日：2016-05-23

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Karl Antonin BZDUSEK ,  Prashant KUMAR

IPC: A61N5/10

CPC classification number: A61N5/1031 ,  A61N5/1039 ,  A61N5/1047 ,  A61N5/1077

Abstract: A radiation therapy planning system (100) includes a radiation therapy optimization unit (124), which receives at least one target structure and at least one organ-at-risk (OAR) structure segmented from a volumetric image, and generates an optimized plan (126) based on at least one modified objective function. The optimized plan (126) includes a planned radiation dose for each voxel.

公开(公告)号：US20180111005A1

公开(公告)日：2018-04-26

申请号：US15571294

申请日：2016-05-11

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Vaitheeswaran RANGANATHAN ,  Prashant KUMAR ,  Gipson JOE ANTO

IPC: A61N5/10

CPC classification number: A61N5/1031 ,  A61N5/1045 ,  A61N5/1048 ,  A61N2005/1092

Abstract: The invention relates to a method of selecting a set of beam geometries for use in radiation therapy. The method (10) comprises providing (12) a plurality of candidate beam geometries; optimizing (1) a radiation treatment plan with all candidate beam geometries; and computing (14) a cost function value based on all candidate beam geometries. A first beam geometry from the plurality of candidate beam geometries is removed (15) and a first modified cost function value based on the candidate beam geometries without the removed first beam geometry computed (16). The first beam geometry is restored (17). The steps of removing a beam geometry, computing of a modified cost function value and restoring of the removed beam geometry are repeated (R) for all other candidate beam geometries. One or more beam geometries from the plurality of candidate beam geometries based on the modified cost function values are chosen (19).