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基于 UTE-MRI 的放射组学模型预测肺腺癌组织病理亚型的可行性:与 CT 基于放射组学模型的比较。

Feasibility of UTE-MRI-based radiomics model for prediction of histopathologic subtype of lung adenocarcinoma: in comparison with CT-based radiomics model.

机构信息

Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, 50-1 Yonsei-Ro Seodaemun-Gu, Seoul, 03722, South Korea.

Department of Thoracic and Cardiovascular Surgery, Severance Hospital, Yonsei University College of Medicine, Seoul, 03722, South Korea.

出版信息

Eur Radiol. 2024 May;34(5):3422-3430. doi: 10.1007/s00330-023-10302-1. Epub 2023 Oct 16.

Abstract

OBJECTIVES

To assess the feasibility of the UTE-MRI radiomic model in predicting the micropapillary and/or solid (MP/S) patterns of surgically resected lung adenocarcinoma.

MATERIALS AND METHODS

We prospectively enrolled 74 lesions from 71 patients who underwent UTE-MRI and CT before curative surgery for early lung adenocarcinoma. For conventional radiologic analysis, we analyzed the longest lesion diameter and lesion characteristics at both UTE-MRI and CT. Radiomic features were extracted from the volume of interest of the lesions and Rad-scores were generated using the least absolute shrinkage and selection operator with fivefold cross-validation. Six models were constructed by combining the conventional radiologic model, UTE-MRI Rad-score, and CT Rad-score. The areas under the curves (AUCs) of each model were compared using the DeLong method. Early recurrence after curative surgery was analyzed, and Kaplan-Meier survival analysis was performed.

RESULTS

Twenty-four lesions were MP/S-positive, and 50 were MP/S-negative. The longitudinal size showed a small systematic difference between UTE-MRI and CT, with fair intermodality agreement of lesion characteristic (kappa = 0.535). The Rad-scores of the UTE-MRI and CT demonstrated AUCs of 0.84 and 0.841, respectively (p = 0.98). Among the six models, mixed conventional, UTE-MRI, and CT Rad-score model showed the highest diagnostic performance (AUC = 0.879). In the survival analysis, the high- and low-risk groups were successfully divided by the Rad-score in UTE-MRI (p = 0.01) and CT (p < 0.01).

CONCLUSION

UTE-MRI radiomic model predicting MP/S positivity is feasible compared with the CT radiomic model. Also, it was associated with early recurrence in the survival analysis.

CLINICAL RELEVANCE STATEMENT

A radiomic model utilizing UTE-MRI, which does not present a radiation hazard, was able to successfully predict the histopathologic subtype of lung adenocarcinoma, and it was associated with the patient's recurrence-free survival.

KEY POINTS

• No studies have reported the ultrashort echo time (UTE)-MRI-based radiomic model for lung adenocarcinoma. • The UTE-MRI Rad-score showed comparable diagnostic performance with CT Rad-score for predicting micropapillary and/or solid histopathologic pattern. • UTE-MRI is feasible not only for conventional radiologic analysis, but also for radiomics analysis.

摘要

目的

评估超短回波时间(UTE)-MRI 放射组学模型预测手术切除肺腺癌微乳头和/或实性(MP/S)模式的可行性。

材料与方法

我们前瞻性纳入了 71 例接受 UTE-MRI 和 CT 检查的早期肺腺癌患者的 74 个病灶。进行常规放射学分析时,我们分析了 UTE-MRI 和 CT 上最长病灶直径和病灶特征。从病灶感兴趣区提取放射组学特征,并使用 5 重交叉验证的最小绝对值收缩和选择算子生成 Rad 评分。通过结合常规放射学模型、UTE-MRI Rad 评分和 CT Rad 评分,构建了 6 个模型。使用 DeLong 方法比较了每个模型的曲线下面积(AUC)。分析了根治性手术后的早期复发情况,并进行 Kaplan-Meier 生存分析。

结果

24 个病灶为 MP/S 阳性,50 个病灶为 MP/S 阴性。UTE-MRI 和 CT 之间的纵向大小存在较小的系统差异,病灶特征的模态间一致性较好(kappa=0.535)。UTE-MRI 和 CT 的 Rad 评分的 AUC 分别为 0.84 和 0.841(p=0.98)。在 6 个模型中,混合常规、UTE-MRI 和 CT Rad 评分模型显示出最高的诊断性能(AUC=0.879)。在生存分析中,Rad 评分可成功区分 UTE-MRI(p=0.01)和 CT(p<0.01)高风险和低风险组。

结论

与 CT 放射组学模型相比,预测 MP/S 阳性的 UTE-MRI 放射组学模型是可行的。此外,在生存分析中,它与早期复发相关。

临床相关性声明

利用 UTE-MRI 构建的放射组学模型,不会产生辐射危害,能够成功预测肺腺癌的组织病理学亚型,并与患者的无复发生存相关。

要点

  1. 尚无研究报道基于超短回波时间(UTE)-MRI 的放射组学模型用于肺腺癌。

  2. UTE-MRI Rad 评分与 CT Rad 评分在预测微乳头和/或实性组织病理学模式方面具有相当的诊断性能。

  3. UTE-MRI 不仅可用于常规放射学分析,还可用于放射组学分析。

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