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Image quality evaluation in a modern PET system: impact of new reconstructions methods and a radiomics approach

机译:现代PET系统中的图像质量评估:新的重建方法和放射线学方法的影响

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摘要

The present work investigates the influence of different biological and physical parameters on image quality (IQ) perception of the abdominal area in a modern PET scanner, using new reconstruction algorithms and testing the utility of a radiomics approach. Scans of 112 patients were retrospectively included. Images were reconstructed using both OSEM + PSF and BSRM methods, and IQ of the abdominal region was subjectively evaluated. First, 22 IQ related parameters were obtained (including count rate and biological or mixed parameters) and compared to the subjective IQ scores by means of correlations and logistic regression. Second, an additional set of radiomics features was extracted, and a model was constructed by means of an elastic-net regression. For the OSEM + PSF and especially for the BSRM reconstructions, IQ parameters presented only at best moderated correlations with the subjective IQ. None of the studied parameters presented a good predictive power for IQ, while a simple radiomics model increased the performance of the IQ prediction. These results suggest the necessity of changing the standard parameters to evaluate IQ, particularly when a BSRM algorithm is involved. Furthermore, it seems that a simple radiomics model can outperform the use of any single parameter to assess IQ.
机译:本工作使用新的重建算法并测试了放射线学方法的实用性,研究了现代PET扫描仪中不同生物学和物理参数对腹部区域的图像质量(IQ)感知的影响。回顾性分析112例患者。使用OSEM + PSF和BSRM方法重建图像,并主观评估腹部区域的智商。首先,获得22个与IQ相关的参数(包括计数率和生物学或混合参数),并通过相关性和逻辑回归将其与主观IQ得分进行比较。其次,提取了另一套放射学特征,并通过弹性网回归构建了模型。对于OSEM + PSF,特别是对于BSRM重建,IQ参数仅以与主观IQ最佳的适度相关性呈现。所研究的参数均未显示出对IQ的良好预测能力,而简单的放射性组模型可提高IQ预测的性能。这些结果表明有必要更改标准参数以评估IQ,尤其是在涉及BSRM算法时。此外,似乎简单的放射学模型可以胜过使用任何单个参数来评估智商。

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