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基于超声的甲状腺外侵犯评估中,放射组学优于超声评估:一项回顾性研究。

The superior value of radiomics to sonographic assessment for ultrasound-based evaluation of extrathyroidal extension in papillary thyroid carcinoma: a retrospective study.

机构信息

Department of Ultrasound, the Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.

Department of Statistical Science, University College London, London, United Kingdom.

出版信息

Radiol Oncol. 2024 Sep 15;58(3):386-396. doi: 10.2478/raon-2024-0040. eCollection 2024 Sep 1.

Abstract

BACKGROUND

Extrathyroidal extension was related with worse survival for patients with papillary thyroid carcinoma. For its preoperative evaluation, we measured and compared the predicting value of sonographic method and ultrasonic radiomics method in nodules of papillary thyroid carcinoma.

PATIENTS AND METHODS

Data from 337 nodules were included and divided into training group and validation group. For ultrasonic radiomics method, a best model was constructed based on clinical characteristics and ultrasonic radiomic features. The predicting value was calculated then. For sonographic method, the results were calculated using all samples.

RESULTS

For ultrasonic radiomics method, we constructed 9 models and selected the extreme gradient boosting model for its highest accuracy (0.77) and area under curve (0.813) in validation group. The accuracy and area under curve of sonographic method was 0.70 and 0.569. Meanwhile. We found that the top-6 important features of xgboost model included no clinical characteristics, all of whom were high-dimensional radiomic features.

CONCLUSIONS

The study showed the superior value of ultrasonic radiomics method to sonographic method for preoperative detection of extrathyroidal extension in papillary thyroid carcinoma. Furthermore, high-dimensional radiomic features were more important than clinical characteristics.

摘要

背景

甲状腺外延伸与甲状腺乳头状癌患者的生存预后较差有关。为了对其进行术前评估,我们测量并比较了超声方法和超声放射组学方法在甲状腺乳头状癌结节中的预测价值。

患者与方法

纳入 337 个结节的数据,并将其分为训练组和验证组。对于超声放射组学方法,基于临床特征和超声放射组学特征构建了最佳模型。然后计算了预测值。对于超声方法,使用所有样本计算结果。

结果

对于超声放射组学方法,我们构建了 9 个模型,并选择极端梯度增强模型,其在验证组中的准确率(0.77)和曲线下面积(0.813)最高。超声方法的准确率和曲线下面积分别为 0.70 和 0.569。同时,我们发现 xgboost 模型的前 6 个重要特征中没有临床特征,它们都是高维放射组学特征。

结论

该研究表明,超声放射组学方法在术前检测甲状腺乳头状癌甲状腺外延伸方面优于超声方法。此外,高维放射组学特征比临床特征更重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0a8/11432181/c8a63a3580fe/j_raon-2024-0040_fig_001.jpg

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