Prognostic Performance of Kidney Volume Measurement for Polycystic Kidney Disease: A Comparative Study of Ellipsoid vs. Manual Segmentation
Prognostic Performance of Kidney Volume Measurement for Polycystic Kidney Disease: A Comparative Study of Ellipsoid vs. Manual Segmentation
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DOI：
10.1038/s41598-019-47206-4
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发表时间：
2019-07-29
影响因子：
4.6
通讯作者：
Pei, York
中科院分区：
文献类型：
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作者：
Shi, Beili;Akbari, Pedram;Pei, York
肾脏总体积（TKV）是常染色体显性遗传性多囊肾病（ADPKD）风险评估的有效预后生物标志物。通过手动分割（MS）进行TKV是“黄金标准”，但耗时且需要专业知识。本研究的目的是在一个大型患者队列中比较椭圆体（EL）与MS基于TKV的预后性能。对在三级转诊中心就诊的308例患者进行的横断面研究;所有患者均接受了标准化MRI检查，具有ADPKD的典型成像。由一名经验丰富的放射科医生对患者临床结果设盲，通过EL和MS进行所有TKV测量。我们通过组内相关性（ICC）和Bland-Altman图评估了TKV测量的一致性，以及两种方法的不一致如何影响马约临床成像分类（MCIC）的预后性能。我们发现EL与MS之间TKV测量值的ICC较高（0.991，p < 0.001）;然而，5.5%的病例显示TKV测量值不一致> 20%。我们还发现单个MCIC风险类别（即1A至1 E）的高度一致性，Cohen加权Kappa值为0.89;但42例（13.6%）被EL错误分类，没有错误分类跨越一个以上的风险类别。EL在区分低危（1A-B）和高危（1C-E）MCIC预后分组方面的敏感性和特异性分别为96.6%和96.1%。总体而言，我们发现EL和MS之间基于TKV的风险评估非常一致。但是，对于MCIC 1B和1C患者需要谨慎，因为错误分类可能会导致治疗后果。
Total kidney volume (TKV) is a validated prognostic biomarker for risk assessment in autosomal dominant polycystic kidney disease (ADPKD). TKV by manual segmentation (MS) is the "gold standard" but is time-consuming and requires expertise. The purpose of this study was to compare TKV-based prognostic performance by ellipsoid (EL) vs. MS in a large cohort of patients. Cross-sectional study of 308 patients seen at a tertiary referral center; all had a standardized MRI with typical imaging of ADPKD. An experienced radiologist blinded to patient clinical results performed all TKV measurements by EL and MS. We assessed the agreement of TKV measurements by intraclass correlation(ICC) and Bland-Altman plot and also how the disagreement of the two methods impact the prognostic performance of the Mayo Clinic Imaging Classification (MCIC). We found a high ICC of TKV measurements (0.991, p < 0.001) between EL vs. MS; however, 5.5% of the cases displayed disagreement of TKV measurements >20%. We also found a high degree of agreement of the individual MCIC risk classes (i.e. 1A to 1E) with a Cohen's weighted-kappa of 0.89; but 42 cases (13.6%) were misclassified by EL with no misclassification spanning more than one risk class. The sensitivity and specificity of EL in distinguishing low-risk (1A-B) from high-risk (1C-E) MCIC prognostic grouping were 96.6% and 96.1%, respectively. Overall, we found an excellent agreement of TKV-based risk assessment between EL and MS. However, caution is warranted for patients with MCIC 1B and 1C, as misclassification can have therapeutic consequence.