...
首页> 外文期刊>Medical Physics >Voxel‐based multimodel fitting method for modeling time activity curves in SPECT images
【24h】

Voxel‐based multimodel fitting method for modeling time activity curves in SPECT images

机译:基于体素的多语素拟合方法,用于在SPECT图像中建模时间活动曲线

获取原文
获取原文并翻译 | 示例

摘要

Purpose Estimating the biodistribution and the pharmacokinetics from time‐sequence SPECT images on a per‐voxel basis is useful for studying activity nonuniformity or computing absorbed dose distributions by convolution of voxel kernels or Monte‐Carlo radiation transport. Current approaches are either region‐based, thus assuming uniform activity within the region, or voxel‐based but using the same fitting model for all voxels. Methods We propose a voxel‐based multimodel fitting method (VoMM) that estimates a fitting function for each voxel by automatically selecting the most appropriate model among a predetermined set with Akaike criteria. This approach can be used to compute the time integrated activity (TIA) for all voxels in the image. To control fitting optimization that may fail due to excessive image noise, an approximated version based on trapezoid integration, named restricted method, is also studied. From this comparison, the number of failed fittings within images was estimated and analyzed. Numerical experiments were used to quantify uncertainties and feasibility was demonstrated with real patient data. Results Regarding numerical experiments, root mean square errors of TIA obtained with VoMM were similar to those obtained with bi‐exponential fitting functions, and were lower (?5% vs. ??10%) than with single model approaches that consider the same fitting function for all voxels. Failure rates were lower with VoMM and restricted approaches than with single‐model methods. On real clinical data, VoMM was able to fit 90% of the voxels and led to less failed fits than single‐model approaches. On regions of interest (ROI) analysis, the difference between ROI‐based and voxel‐based TIA estimations was low, less than 4%. However, the computation of the mean residence time exhibited larger differences, up to 25%. Conclusions The proposed voxel‐based multimodel fitting method, VoMM, is feasible on patient data. VoMM leads organ‐based TIA estimations similar to conventional ROI‐based method. However, for pharmacokinetics analysis, studies of spatial heterogeneity or voxel‐based absorbed dose assessment, VoMM could be used preferentially as it prevents model overfitting.
机译:目的估算生物分布和从时间序列SPECT图像的药代动力学上的每个体素的基础是通过体素的内核或蒙特卡罗辐射传输的卷积学习活动的不均匀性或计算吸收剂量分布是有用的。目前的方法是任一区域为基础的,因此假设均匀的活动区域内,或体素的基础,但使用用于所有体素相同的拟合模型。方法我们提出了一种基于体素的多模型拟合方法(VOMM),其估计拟合函数用于通过自动选择预定的一组与赤池标准中最适当的模型中的每个体素。这种方法可以用于计算图像中的所有体素的时间积分活性(TIA)。为了控制拟合优度,可能会由于过度的图像噪声的基础上,结合梯形名为限制方法近似的版本,同时还研究了从这个比较中,估计图像中失败配件的数量和分析。数值实验被用来量化的不确定性和可行性与实际患者数据证实。结果关于数值实验中,VOMM获得TIA的根均方误差均类似于用双指数拟合函数获得的那些,和较低(小于?5%对&有10%)比用单模型接近于考虑所有体素相同的拟合函数。故障率较低与VOMM,并且比单一模式的方法限制的方法。在实际的临床数据,VOMM能够满足90%的体素,并导致更少的失败配合比单模型方法。上的感兴趣区域(ROI)分析,基于ROI和基于体素TIA估计之间的差低,低于4%。然而,平均停留时间的计算表现出较大的差异,高达25%。结论所提出的基于体素的多模式拟合方法,VOMM,是对患者数据是可行的。 VOMM导致器官基于类似于传统的基于ROI的方法TIA估计。然而,药代动力学分析,空间异质性或研究基于体素的吸收剂量评估,VOMM可优先使用,因为它可以防止模型过拟合。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号