European Radiology:超低剂量CT深度学习重建对尿路结石的评价价值

2022-08-11 shaosai MedSci原创

随着近年来人工智能的快速发展,CT图像的深度学习重建(DLR)已经被开发出来并应用于多项研究。

尿石症是腹痛的一个常见原因,在世界范围内具有发病率。尿石症的诊断通常通过平扫计算机断层扫描(CT)来确认,评估尿石症的标准成像方式。

众所周知平扫CT的一个缺点是辐射暴露。考虑到尿石症的高复发率和重复成像的要求,辐射剂量已成为临床关注的一个主要问题。为了防止不必要的辐射相关影响,人们探索了各种方法来减少CT的辐射剂量,如降低管电压或使用锡过滤器。有研究表明超低剂量CT(ULDCT)也用于评估泌尿系结石,但辐射剂量的减少往往会带来较高的图像噪声和较差的图像质量,这对结石评估产生不利影响。因此,临床上引入了先进的混合迭代重建(HIR)算法在可保持图像质量的同时减少图像噪声。

随着近年来人工智能的快速发展,CT图像的深度学习重建(DLR)已经被开发出来并应用于多项研究。研究表明,DLR有助于在降低辐射剂量的情况下保持或提高胸部和腹部CT图像的质量,同时不改变噪声纹理。研究还表明,与迭代重建的LDCT相比,LDCT-DLR表现出良好的图像质量和尿路结石的可检测性。然而,DLR-ULDCT的临床应用价值或尿路结石检测不明确

近日,发表在European Radiology杂志的一项研究通过评估ULDCT-DLR与ULDCT-HIR相比的诊断准确性和图像质量,探讨了DLR对临床上疑似尿路结石患者的诊断及评估价值,为进一步减少患者辐射剂量、提高诊断准确性提供了技术支持。

本研究将怀疑有尿石症的患者前瞻性地纳入研究每位患者均接受了腹盆腔LDCT扫描,如果观察到尿路结的存在则进行ULDCT扫描。评估和比较了辐射暴露、结石特征、图像噪声、信噪比(SNR)和5分Likert评分法的主观图像质量。 

ULDCT的平均有效辐射剂量明显低于LDCT(1.28 ± 0.34 vs. 5.49 ± 1.00 mSv,P < 0.001)。根据参考标准(LDCT-HIR),在85.0%(51/60)的患者中观察到148个尿路结石。ULDCT-DLR检测到143个结石,比率为96.6%,而ULDCT-HIR检测到142个结石,比率为95.9%。用ULDCT-DLR或ULDCT-HIR没有观察到的尿路结石是小于3毫米的肾结石。ULDCT-DLR、ULDCT-HIR和LDCT-HIR对有临床意义的结石(≥3毫米)的检测和结石大小的估计没有明显差异。ULDCT-DLR的图像质量优于ULDCT-HIR和LDCT-HIR,图像噪声低、信噪比高平均主观评分均较高。 


 a LDCT-HIR图像显示肾盂系统中有一个2.2mm的结石(箭头);b ULDCT-HIR和c ULDCT-DLR未能显示结石。LDCT,低剂量计算机断层成像;HIR,混合迭代重建;ULDCT,超低剂量计算机断层成像;DLR,深度学习重建

本研究表明,与LDCT-HIR相比,ULDCT的DLR算法在提高了图像质量的同时,在尿路结石检测、尺寸估计和CT衰减方面也具有良好的性能,但对尺寸小于3mm的尿路结石的检测可能会略有影响。本研究提示,ULDCT-DLR在评估常规临床实践中的泌尿系结石方面具有很大的潜力。

原文出处:

Gumuyang Zhang,Xiaoxiao Zhang,Lili Xu,et al.Value of deep learning reconstruction at ultra-low-dose CT for evaluation of urolithiasis.DOI:10.1007/s00330-022-08739-x

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    2023-05-22 feather89
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    2022-08-18 12337380m37(暂无昵称)

    低剂量ct是肾结石首选方法,临床应用观点改变了。

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    2022-08-13 huagfeg
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