基于双能 CT 的影像组学在肾透明细胞癌核分级和 T 分期中的研究。

Study of radiomics based on dual-energy CT for nuclear grading and T-staging in renal clear cell carcinoma.

机构信息

Department of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan 250013, Shandong Province, P. R. China.

Department of Radiology, Longkou Traditional Chinese Medicine Hospital, Yantai 265700, Shandong Province, P. R. China.

出版信息

Medicine (Baltimore). 2024 Mar 8;103(10):e37288. doi: 10.1097/MD.0000000000037288.

DOI:10.1097/MD.0000000000037288

PMID:38457546

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10919525/

Abstract

INTRODUCTION

Clear cell renal cell carcinoma (ccRCC) is the most lethal subtype of renal cell carcinoma with a high invasive potential. Radiomics has attracted much attention in predicting the preoperative T-staging and nuclear grade of ccRCC.

OBJECTIVE

The objective was to evaluate the efficacy of dual-energy computed tomography (DECT) radiomics in predicting ccRCC grade and T-stage while optimizing the models.

METHODS

200 ccRCC patients underwent preoperative DECT scanning and were randomized into training and validation cohorts. Radiomics models based on 70 KeV, 100 KeV, 150 KeV, iodine-based material decomposition images (IMDI), virtual noncontrasted images (VNC), mixed energy images (MEI) and MEI + IMDI were established for grading and T-staging. Receiver operating characteristic analysis and decision curve analysis (DCA) were performed. The area under the curve (AUC) values were compared using Delong test.

RESULTS

For grading, the AUC values of these models ranged from 0.64 to 0.97 during training and from 0.54 to 0.72 during validation. In the validation cohort, the performance of MEI + IMDI model was optimal, with an AUC of 0.72, sensitivity of 0.71, and specificity of 0.70. The AUC value for the 70 KeV model was higher than those for the 100 KeV, 150 KeV, and MEI models. For T-staging, these models achieved AUC values of 0.83 to 1.00 in training and 0.59 to 0.82 in validation. The validation cohort demonstrated AUCs of 0.82 and 0.70, sensitivities of 0.71 and 0.71, and specificities of 0.80 and 0.60 for the MEI + IMDI and IMDI models, respectively. In terms of grading and T-staging, the MEI + IMDI model had the highest AUC in validation, with IMDI coming in second. There were statistically significant differences between the MEI + IMDI model and the 70 KeV, 100 KeV, 150 KeV, MEI, and VNC models in terms of grading (P < .05) and staging (P ≤ .001). DCA showed that both MEI + IDMI and IDMI models outperformed other models in predicting grade and stage of ccRCC.

CONCLUSIONS

DECT radiomics models were helpful in grading and T-staging of ccRCC. The combined model of MEI + IMDI achieved favorable results.

摘要

介绍

透明细胞肾细胞癌（ccRCC）是肾细胞癌中最致命的亚型，具有较高的侵袭性。放射组学在预测 ccRCC 的术前 T 分期和核分级方面引起了广泛关注。

目的

旨在评估双能 CT（DECT）放射组学在优化模型的同时预测 ccRCC 分级和 T 分期的效果。

方法

200 例 ccRCC 患者接受术前 DECT 扫描，并随机分为训练和验证队列。基于 70keV、100keV、150keV、碘基物质分解图像（IMDI）、虚拟非对比图像（VNC）、混合能量图像（MEI）和 MEI+IMDI 建立了用于分级和 T 分期的放射组学模型。进行了受试者工作特征分析和决策曲线分析（DCA）。使用 Delong 检验比较曲线下面积（AUC）值。

结果

在训练中，这些模型的分级 AUC 值范围为 0.64 至 0.97，在验证中为 0.54 至 0.72。在验证队列中，MEI+IMDI 模型的表现最佳，AUC 为 0.72，灵敏度为 0.71，特异性为 0.70。70keV 模型的 AUC 值高于 100keV、150keV 和 MEI 模型。对于 T 分期，这些模型在训练中的 AUC 值为 0.83 至 1.00，在验证中的 AUC 值为 0.59 至 0.82。验证队列的 AUC 值分别为 0.82 和 0.70，灵敏度分别为 0.71 和 0.71，特异性分别为 0.80 和 0.60，用于 MEI+IMDI 和 IMDI 模型。在分级和 T 分期方面，MEI+IMDI 模型在验证中具有最高的 AUC，而 IMDI 模型位居第二。在分级（P<.05）和分期（P≤.001）方面，MEI+IMDI 模型与 70keV、100keV、150keV、MEI 和 VNC 模型之间存在统计学差异。DCA 显示，MEI+IDMI 和 IDMI 模型在预测 ccRCC 的分级和分期方面均优于其他模型。