背景:术前软组织肉瘤(STS)切缘的确定对患者预后至关重要。
目的:使用T2加权Dixon序列评估影像组学模型对STS边缘浸润程度的诊断性能。
方法:回顾性。
方法:72名STS患者由训练组(n=58)和测试组(n=14)组成。
未经授权:A3.0T;T2加权Dixon图像。
结果:STS边缘浸润的病理结果(界限边缘;n=27,第1组,局灶性浸润边缘;n=31,第2-A组,弥漫性浸润边缘;n=14,第2-B组)为参考标准。从整个肿瘤体积和边缘提取影像体体积和形状(VS)和其他(T2)特征,分别。使用四种分类器算法组合生成了12个影像组学模型(R,SR,LR,LSR)和三个不同的输入(VS,T2,VS+T2[VST2]特征)来区分三组。三位放射科医生(读者1、2、3)用6量表置信度评分分析了边缘浸润。
方法:受试者工作特征曲线下面积(AUC)和一致率。
结果:R的平均AUC,SR,LR,LSR模型分别为0.438、0.466、0.438、0.466,使用VS特征,使用T2功能的0.596、0.584、0.814、0.815,和0.581、0.587、0.821、0.821使用VST2功能,分别。与放射科医师分析相比,使用T2或VST2特征构建的LR和LSR模型显示出更高的AUC和一致率(AUC;0.730、0.675、0.706,一致率;读数1、2、3中的0.46、0.43、0.47)。
结论:用T2加权Dixon序列上的肿瘤边缘特征构建的Radiomics模型是区分STS边缘浸润程度的一种有前途的方法。
方法:4技术效果:阶段2。
Determination of preoperative soft tissue sarcoma (STS) margin is crucial for patient prognosis.
To evaluate diagnostic performance of radiomics model using T2-weighted Dixon sequence for infiltration degree of STS margin.
Retrospective.
Seventy-two STS patients consisted of training (n = 58) and test (n = 14) sets.
A 3.0 T; T2-weighted Dixon images.
Pathologic result of marginal infiltration in STS (circumscribed margin; n = 27, group 1, focally infiltrative margin; n = 31, group 2-A, diffusely infiltrative margin; n = 14, group 2-B) was the reference standard. Radiomic volume and shape (VS) and other (T2) features were extracted from entire tumor volume and margin, respectively. Twelve radiomics models were generated using four combinations of classifier algorithms (R, SR, LR, LSR) and three different inputs (VS, T2, VS + T2 [VST2] features) to differentiate the three groups. Three radiologists (reader 1, 2, 3) analyzed the marginal infiltration with 6-scale confidence score.
Area under the receiver operating characteristic curve (AUC) and concordance rate.
Averaged AUCs of R, SR, LR, LSR models were 0.438, 0.466, 0.438, 0.466 using VS features, 0.596, 0.584, 0.814, 0.815 using T2 features, and 0.581, 0.587, 0.821, 0.821 using VST2 features, respectively. The LR and LSR models constructed with T2 or VST2 features showed higher AUC and concordance rate compared to radiologists\' analysis (AUC; 0.730, 0.675, 0.706, concordance rate; 0.46, 0.43, 0.47 in reader 1, 2, 3).
Radiomics model constructed with features from tumor margin on T2-weighted Dixon sequence is a promising method for differentiating infiltration degree of STS margin.
4 TECHNICAL EFFICACY: Stage 2.