评分系统结合放射组学和影像学特征,预测偶发的不确定小(<20 毫米)实性肺结节的恶性可能性。

IF 2.9 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING BMC Medical Imaging Pub Date : 2024-09-06 DOI:10.1186/s12880-024-01413-2
Bai-Qiang Qu, Yun Wang, Yue-Peng Pan, Pei-Wei Cao, Xue-Ying Deng
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引用次数: 0

摘要

目的:根据放射组学和影像学特征开发一套实用的评分系统,用于预测小于20毫米的偶发不确定肺小实体结节(IISSPN)的恶性可能性:基于放射组学和影像学特征,开发一套实用的评分系统,用于预测小于20毫米的偶发不确定肺实性小结节(IISSPN)的恶性可能性:回顾性分析了360例经手术确诊的恶性IISSPN(213例)和良性IISSPN(147例)患者。整个组群按 7:3 的比例随机分为训练组和验证组。采用最小绝对收缩和选择算子(LASSO)算法对放射组学特征进行降维处理。通过多变量逻辑分析建立模型。记录了每个模型的接受者操作特征曲线(ROC)、曲线下面积(AUC)、95% 置信区间(CI)、灵敏度和特异性。根据几率比建立了评分系统:结果:选择了三个放射组学特征进一步建立模型。经过多变量逻辑分析,在训练组中,包括平均值、年龄、肺气肿、分叶和大小的组合模型的AUC最高,为0.877(95%CI:0.830-0.915),准确率为83.3%,灵敏度为85.3%,特异性为80.2%,其次是放射组学模型(AUC:0.804)和成像模型(AUC:0.773)。制定了一个分界值大于 4 分的评分系统。如果评分大于 8 分,诊断恶性 IISSPN 的可能性至少可达 92.7%:综合模型在预测 IISSPN 的恶性可能性方面表现出良好的诊断性能。结论:该综合模型在预测 IISSPN 的恶性可能性方面表现出了良好的诊断性能,在用户友好型评分系统中,只要得分超过 12 分,准确率就能达到 100%。
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The scoring system combined with radiomics and imaging features in predicting the malignant potential of incidental indeterminate small (<20 mm) solid pulmonary nodules.

Objective: Develop a practical scoring system based on radiomics and imaging features, for predicting the malignant potential of incidental indeterminate small solid pulmonary nodules (IISSPNs) smaller than 20 mm.

Methods: A total of 360 patients with malignant IISSPNs (n = 213) and benign IISSPNs (n = 147) confirmed after surgery were retrospectively analyzed. The whole cohort was randomly divided into training and validation groups at a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) algorithm was used to debase the dimensions of radiomics features. Multivariate logistic analysis was performed to establish models. The receiver operating characteristic (ROC) curve, area under the curve (AUC), 95% confidence interval (CI), sensitivity and specificity of each model were recorded. Scoring system based on odds ratio was developed.

Results: Three radiomics features were selected for further model establishment. After multivariate logistic analysis, the combined model including Mean, age, emphysema, lobulated and size, reached highest AUC of 0.877 (95%CI: 0.830-0.915), accuracy rate of 83.3%, sensitivity of 85.3% and specificity of 80.2% in the training group, followed by radiomics model (AUC: 0.804) and imaging model (AUC: 0.773). A scoring system with a cutoff value greater than 4 points was developed. If the score was larger than 8 points, the possibility of diagnosing malignant IISSPNs could reach at least 92.7%.

Conclusion: The combined model demonstrated good diagnostic performance in predicting the malignant potential of IISSPNs. A perfect accuracy rate of 100% can be achieved with a score exceeding 12 points in the user-friendly scoring system.

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来源期刊
BMC Medical Imaging
BMC Medical Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
4.60
自引率
3.70%
发文量
198
审稿时长
27 weeks
期刊介绍: BMC Medical Imaging is an open access journal publishing original peer-reviewed research articles in the development, evaluation, and use of imaging techniques and image processing tools to diagnose and manage disease.
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