Hwang Eui Jin, Goo Jin Mo, Kim Jihye, Park Sang Joon, Ahn Soyeon, Park Chang Min, Shin Yeong-Gil
Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
Deparment of Radiology, Armed Forces Seoul Hospital, Seoul, Korea.
Eur Radiol. 2017 Aug;27(8):3257-3265. doi: 10.1007/s00330-016-4713-8. Epub 2017 Jan 3.
To develop a prediction model for the variability range of lung nodule volumetry and validate the model in detecting nodule growth.
For model development, 50 patients with metastatic nodules were prospectively included. Two consecutive CT scans were performed to assess volumetry for 1,586 nodules. Nodule volume, surface voxel proportion (SVP), attachment proportion (AP) and absolute percentage error (APE) were calculated for each nodule and quantile regression analyses were performed to model the 95% percentile of APE. For validation, 41 patients who underwent metastasectomy were included. After volumetry of resected nodules, sensitivity and specificity for diagnosis of metastatic nodules were compared between two different thresholds of nodule growth determination: uniform 25% volume change threshold and individualized threshold calculated from the model (estimated 95% percentile APE).
SVP and AP were included in the final model: Estimated 95% percentile APE = 37.82 · SVP + 48.60 · AP-10.87. In the validation session, the individualized threshold showed significantly higher sensitivity for diagnosis of metastatic nodules than the uniform 25% threshold (75.0% vs. 66.0%, P = 0.004) CONCLUSION: Estimated 95% percentile APE as an individualized threshold of nodule growth showed greater sensitivity in diagnosing metastatic nodules than a global 25% threshold.
• The 95 % percentile APE of a particular nodule can be predicted. • Estimated 95 % percentile APE can be utilized as an individualized threshold. • More sensitive diagnosis of metastasis can be made with an individualized threshold. • Tailored nodule management can be provided during nodule growth follow-up.
建立肺结节体积测量变异性范围的预测模型，并在检测结节生长中验证该模型。
为建立模型，前瞻性纳入50例有转移结节的患者。进行连续两次CT扫描以评估1586个结节的体积。计算每个结节的体积、表面体素比例（SVP）、附着比例（AP）和绝对百分比误差（APE），并进行分位数回归分析以建立APE的第95百分位数模型。为进行验证，纳入41例行转移瘤切除术的患者。在对切除结节进行体积测量后，比较在两种不同的结节生长判定阈值下诊断转移结节的敏感性和特异性：统一的25%体积变化阈值和根据模型计算的个体化阈值（估计的APE第95百分位数）。
SVP和AP纳入最终模型：估计的APE第95百分位数 = 37.82·SVP + 48.60·AP - 10.87。在验证阶段，个体化阈值对转移结节诊断的敏感性显著高于统一的25%阈值（75.0%对66.0%，P = 0.004）。结论：估计的APE第95百分位数作为结节生长的个体化阈值在诊断转移结节方面比全局的25%阈值具有更高的敏感性。
• 可以预测特定结节的APE第95百分位数。• 估计的APE第95百分位数可作为个体化阈值。• 使用个体化阈值可更敏感地诊断转移。• 在结节生长随访期间可提供定制的结节管理。
