Department of Radiology, NYU Langone Health (L.A., W.H.M., J.B., J.P.K.).
Department of Radiology, NYU Langone Health (L.A., W.H.M., J.B., J.P.K.).
Acad Radiol. 2022 Feb;29 Suppl 2:S98-S107. doi: 10.1016/j.acra.2021.01.026. Epub 2021 Feb 18.
To evaluate the inter-observer consistency for subsolid pulmonary nodule radiomic features.
Subsolid nodules were selected by reviewing radiology reports of CT examinations performed December 1, 2015 to April 1, 2016. Patients with CTs at two time points were included in this study. There were 55 patients with subsolid nodules, of whom 14 had two nodules. Of 69 subsolid nodules, 66 were persistent at the second time point, yielding 135 lesions for segmentation. Two thoracic radiologists and an imaging fellow segmented the lesions using a semi-automated volumetry algorithm (Syngo.via Vb20, Siemens). Coefficient of variation (CV) was used to assess consistency of 91 quantitative measures extracted from the subsolid nodule segmentations, including first and higher order texture features. The accuracy of segmentation was visually graded by an experienced thoracic radiologist. Influencing factors on radiomic feature consistency and segmentation accuracy were assessed using generalized estimating equation analyses and the Exact Mann-Whitney test.
Mean patient age was 71 (38-93 years), with 39 women and 16 men. Mean nodule volume was 1.39mL, range .03-48.2mL, for 135 nodules. Several radiomic features showed high inter-reader consistency (CV<5%), including entropy, uniformity, sphericity, and spherical disproportion. Descriptors such as surface area and energy had low consistency across inter-reader segmentations (CV>10%). Nodule percent solid component and attenuation influenced inter-reader variability of some radiomic features. The presence of contrast did not significantly affect the consistency of subsolid nodule radiomic features. Near perfect segmentation, within 5% of actual nodule size, was achieved in 68% of segmentations, and very good segmentation, within 25% of actual nodule size, in 94%. Morphologic features including nodule margin and shape (each p <0.01), and presence of air bronchograms (p = 0.004), bubble lucencies (p = 0.02) and broad pleural contact (p < 0.01) significantly affected the probability of near perfect segmentation. Stroke angle (p = 0.001) and length (p < 0.001) also significantly influenced probability of near perfect segmentation.
The inter-observer consistency of radiomic features for subsolid pulmonary nodules varies, with high consistency for several features, including sphericity, spherical disproportion, and first and higher order entropy, and normalized non-uniformity. Nodule morphology influences the consistency of subsolid nodule radiomic features, and the accuracy of subsolid nodule segmentation.
评估亚实性肺结节放射组学特征的观察者间一致性。
通过回顾 2015 年 12 月 1 日至 2016 年 4 月 1 日进行的 CT 检查的放射学报告,选择亚实性结节。本研究纳入了在两个时间点进行 CT 检查的患者。共有 55 例亚实性结节患者,其中 14 例有 2 个结节。在 69 个亚实性结节中,66 个在第二次时间点仍然存在,产生了 135 个用于分割的病变。两名胸部放射科医生和一名影像研究员使用半自动体积测量算法(Syngo.via Vb20,西门子)对病变进行分割。变异系数(CV)用于评估从亚实性结节分割中提取的 91 个定量指标的一致性,包括一阶和高阶纹理特征。一位经验丰富的胸部放射科医生对分割的准确性进行了视觉分级。使用广义估计方程分析和精确曼-惠特尼检验评估了影响放射组学特征一致性和分割准确性的因素。
平均患者年龄为 71 岁(38-93 岁),其中 39 名女性和 16 名男性。135 个结节的平均结节体积为 1.39ml,范围为 0.03-48.2ml。一些放射组学特征的观察者间一致性较高(CV<5%),包括熵、均匀性、球形度和球形不均一性。表面积和能量等描述符在观察者间分割中的一致性较低(CV>10%)。结节的固体成分百分比和衰减影响了一些放射组学特征的观察者间变异性。对比剂的存在并未显著影响亚实性结节放射组学特征的一致性。68%的分割达到了 5%以内的实际结节大小的近乎完美分割,94%的分割达到了 25%以内的实际结节大小的非常好的分割。形态特征,包括结节边缘和形状(均 p<0.01)、空气支气管征(p=0.004)、泡状透亮影(p=0.02)和广泛胸膜接触(p<0.01),显著影响了近乎完美分割的概率。中风角度(p=0.001)和长度(p<0.001)也显著影响了近乎完美分割的概率。
亚实性肺结节放射组学特征的观察者间一致性存在差异,一些特征的一致性较高,包括球形度、球形不均一性、一阶和高阶熵以及归一化非均匀性。结节形态影响亚实性结节放射组学特征的一致性和亚实性结节的分割准确性。