Predicting late radiation-induced xerostomia in nasopharyngeal carcinoma based on radiomics features extracted from T2WI images of parotids

Q1 Health Professions Radiation Medicine and Protection Pub Date : 2023-09-01 DOI:10.1016/j.radmp.2023.06.002
Yonghui Qin , Cheng Chang , Li Huang , Yong Yin , Ruozheng Wang
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Abstract

Objective

To explore the value of radiomics features extracted from the T2-weighted imaging (T2WI) images of parotids in predicting late radiation-induced xerostomia in nasopharyngeal carcinoma (NPC) patients after radiotherapy (RT).

Methods

A retrospective analysis was conducted for 123 NPC patients who received RT at the Affiliated Tumour Hospital of Xinjiang Medical University from January 2019 to March 2021. All the patients underwent MRI pre-RT and post-RT. They were randomly divided into a training set and a testing set at a ratio of 4:1 using a random number table, with the former and the latter comprising 98 and 25 cases, respectively. The ipsilateral parotid gland (iPG) and the contralateral parotid gland (cPG) were delineated on T2WI images pre-RT and post-RT as regions of interest (ROIs). A total of 851 radiomics features were extracted from each ROI. Spearman analysis was used to remove redundant features, and the recursive feature elimination (RFE) method was then used to determine useful features. Using radiomics features extracted from images pre-treatment, images post-treatment, and differences between images pre- and post-treatment, this study constructed three radiomic models, namely the pre-treatment radiomics model (preRT), the post-treatment radiomics model (postRT), and the delta-radiomics model (DeltaRT). Then, this study plotted the receiver operating characteristic (ROC) curves based on the late radiation-induced xerostomia grades of patients post-RT. Furthermore, the models’ effectiveness and performance in predicting late radiation-induced xerostomia and advanced radioactive xerostomia was evaluated. In addition, the area under the curve (AUC), sensitivity, specificity, accuracy, precision, and negative predictive value (NPV) were calculated.

Results

Among the features extracted from bilateral parotid glands (PGs), 20 were determined pre-RT (six from iPG and 14 from cPG), 19 were determined post-RT (six from iPG and 13 from cPG), and 20 were derived from the DeltaRT (20 from cPG). The PGs pre-RT and post-RT in the training set had AUCs of 0.902 (95% CI: 0.895–0.909) and 0.761 (95% CI: 0.744–0.778), respectively, while those in the testing set had AUCs of 0.740 (95% CI: 0.504–0.983) and 0.701 (95% CI: 0.478–0.924), respectively. In contrast, the AUC of the cPG derived from the DeltaRT was 0.867 (95% CI: 0.856–0.878) in the training set and 0.851 (95% CI: 0.697–0.999) in the testing set.

Conclusions

There are significant correlations between radiomics features extracted from MRI T2WI images of parotids and late radiation-induced xerostomia in NPC patients. Among the radiomics features, the changes in cPG features pre-RT and post-RT have higher accuracy in predicting late radiation-induced xerostomia.

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基于腮腺T2WI影像的放射组学特征预测鼻咽癌晚期放射性口干症
目的探讨腮腺T2WI影像提取的放射组学特征对鼻咽癌放疗后晚期放射性口干的预测价值。方法对2019年1月至2021年3月在新疆医科大学附属肿瘤医院接受放疗的123例鼻咽癌患者进行回顾性分析。所有患者在放疗前和放疗后均行MRI检查。采用随机数字表,以4:1的比例随机分为训练集和测试集,其中训练集和测试集分别为98例和25例。对侧腮腺(cPG)和同侧腮腺(iPG)分别在T2WI图像上作为感兴趣区域(roi)。从每个ROI中提取了851个放射组学特征。采用Spearman分析法剔除冗余特征,采用递归特征消除法确定有用特征。本研究利用从图像预处理、图像处理后以及图像处理前后的差异中提取的放射组学特征,构建了三个放射组学模型,即治疗前放射组学模型(preRT)、治疗后放射组学模型(postRT)和delta-radiomics模型(DeltaRT)。然后,本研究根据放疗后患者晚期放射性口干分级绘制了受试者工作特征(ROC)曲线。此外,还评估了模型在预测晚期辐射性口干和晚期放射性口干的有效性和性能。计算曲线下面积(AUC)、敏感性、特异性、准确度、精密度和阴性预测值(NPV)。结果从双侧腮腺(pg)提取的特征中,rt前提取20个(iPG提取6个,cPG提取14个),rt后提取19个(iPG提取6个,cPG提取13个),DeltaRT提取20个(cPG提取20个)。训练集的pg在rt前和rt后的auc分别为0.902 (95% CI: 0.895-0.909)和0.761 (95% CI: 0.744-0.778),而测试集的pg的auc分别为0.740 (95% CI: 0.504-0.983)和0.701 (95% CI: 0.478-0.924)。相比之下,由DeltaRT得出的cPG的AUC在训练集中为0.867 (95% CI: 0.856-0.878),在测试集中为0.851 (95% CI: 0.697-0.999)。结论腮腺MRI T2WI影像放射组学特征与鼻咽癌晚期放射性口干有显著相关性。放射组学特征中,放疗前和放疗后cPG特征的变化对预测晚期辐射性口干有较高的准确性。
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来源期刊
Radiation Medicine and Protection
Radiation Medicine and Protection Health Professions-Emergency Medical Services
CiteScore
2.10
自引率
0.00%
发文量
0
审稿时长
103 days
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