Automated radiomic analysis of CT images to predict likelihood of spontaneous passage of symptomatic renal stones.
Automated radiomic analysis of CT images to predict likelihood of spontaneous passage of symptomatic renal stones.
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DOI：
10.1007/s10140-021-01915-4
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发表时间：
2021-08
影响因子：
2.2
通讯作者：
Fletcher JG
中科院分区：
文献类型：
--
作者：
Mohammadinejad P;Ferrero A;Bartlett DJ;Khandelwal A;Marcus R;Lieske JC;Moen TR;Mara KC;Enders FT;McCollough CH;Fletcher JG
评价半自动放射组学分析软件与人工测量相比预测尿结石自发排出可能性的能力。有症状的患者就诊于急诊科，怀疑肾或输尿管结石，并接受CT扫描。对患者进行长达6个月的随访，以获得传代试验的结果。手动测量轴位和冠状位图像中的最大结石直径。结石的长度、宽度、高度、最大直径、体积、亨氏单位的平均值和标准差以及形态特征也使用自动放射分析软件进行测量。使用这些数据开发多变量模型来预测随后的自发结石通过，结果表示为受试者工作曲线下面积（AUC）。纳入了184例患者（69例女性），中位年龄为56岁。114例患者（62%）发生自发性结石通过。单变量分析表明，轴面和冠状面手动确定的最大结石直径的AUC分别为0.83和0.82。多变量模型显示，包括轴向和冠状面最大结石直径手动测量的模型的AUC为0.82。对于包括结石最大高度和直径的自动测量的模型，发现了相同的AUC。进一步添加自动测量的形态学参数不会使AUC增加超过0.83。半自动放射组学分析的尿结石显示类似的准确性相比，人工测量预测尿结石通过。需要进一步的研究来预测报告泌尿系结石通过的可能性和使用自动放射组学分析软件改善观察者间差异的临床影响。
To evaluate the ability of a semi-automated radiomic analysis software in predicting the likelihood of spontaneous passage of urinary stones compared with manual measurements. Symptomatic patients visiting the emergency department with suspected stones in either kidney or ureters who underwent a CT scan were included. Patients were followed for up to 6 months for the outcome of a trial of passage. Maximum stone diameters in axial and coronal images were measured manually. Stone length, width, height, max diameter, volume, the mean and standard deviation of the Hounsfield units, and morphologic features were also measured using automated radiomic analysis software. Multivariate models were developed using these data to predict subsequent spontaneous stone passage, with results expressed as the area under a receiver operating curve (AUC). One hundred eighty-four patients (69 females) with a median age of 56 years were included. Spontaneous stone passage occurred in 114 patients (62%). Univariate analysis demonstrated an AUC of 0.83 and 0.82 for the maximum stone diameter determined manually in the axial and coronal planes, respectively. Multivariate models demonstrated an AUC of 0.82 for a model including manual measurement of maximum stone diameter in axial and coronal planes. The same AUC was found for a model including automatic measurement of maximum height and diameter of the stone. Further addition of morphological parameters measured automatically did not increase AUC beyond 0.83. The semi-automated radiomic analysis of urinary stones shows similar accuracy compared with manual measurements for predicting urinary stone passage. Further studies are needed to predict clinical impacts of reporting the likelihood of urinary stone passage and improving inter-observer variation using automatic radiomic analysis software.
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影响因子：
5.9
作者：
Jendeberg J;Geijer H;Alshamari M;Cierzniak B;Lidén M
通讯作者：
Lidén M
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5
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Coll, DM;Varanelli, MJ;Smith, RC
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Smith, RC
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5.9
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Liden, Mats
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作者：
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作者：
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Silverman, Stuart G.