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从磁共振引导激光诱导热疗的热图像监测中恢复体内纳米颗粒浓度的反问题方法。

An inverse problem approach to recovery of in vivo nanoparticle concentrations from thermal image monitoring of MR-guided laser induced thermal therapy.

机构信息

Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA.

出版信息

Ann Biomed Eng. 2013 Jan;41(1):100-11. doi: 10.1007/s10439-012-0638-9. Epub 2012 Aug 24.

Abstract

Quantification of local variations in the optical properties of tumor tissue introduced by the presence of gold-silica nanoparticles (NP) presents significant opportunities in monitoring and control of NP-mediated laser induced thermal therapy (LITT) procedures. Finite element methods of inverse parameter recovery constrained by a Pennes bioheat transfer model were applied to estimate the optical parameters. Magnetic resonance temperature imaging (MRTI) acquired during a NP-mediated LITT of a canine transmissible venereal tumor in brain was used in the presented statistical inverse problem formulation. The maximum likelihood (ML) value of the optical parameters illustrated a marked change in the periphery of the tumor corresponding with the expected location of NP and area of selective heating observed on MRTI. Parameter recovery information became increasingly difficult to infer in distal regions of tissue where photon fluence had been significantly attenuated. Finite element temperature predictions using the ML parameter values obtained from the solution of the inverse problem are able to reproduce the NP selective heating within 5 °C of measured MRTI estimations along selected temperature profiles. Results indicate the ML solution found is able to sufficiently reproduce the selectivity of the NP mediated laser induced heating and therefore the ML solution is likely to return useful optical parameters within the region of significant laser fluence.

摘要

定量研究金-硅纳米粒子(NP)存在时肿瘤组织的局部光学性质变化,为监测和控制 NP 介导的激光诱导热疗(LITT)过程提供了重要机会。采用基于 Pennes 生物传热模型的反演参数恢复有限元方法来估计光学参数。本研究采用了脑内犬传染性性病肿瘤 NP 介导的 LITT 过程中的磁共振温度成像(MRTI)来进行提出的统计反问题公式化。光学参数的最大似然(ML)值表明,肿瘤周边出现明显变化,与 NP 的预期位置以及 MRTI 上观察到的选择性加热区域相对应。在组织的远端区域,光子通量显著衰减,因此参数恢复信息变得越来越难以推断。使用从反问题求解中获得的 ML 参数值进行有限元温度预测,能够在选定的温度曲线内以测量的 MRTI 估计值的 5°C 内重现 NP 选择性加热。结果表明,ML 解能够充分重现 NP 介导的激光诱导加热的选择性,因此 ML 解很可能在显著激光通量区域内返回有用的光学参数。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b74a/3524364/810af8afe048/nihms406236f1.jpg

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