{"title":"Ultrasomics differentiation of malignant and benign focal liver lesions based on contrast-enhanced ultrasound","authors":"Hang-Tong Hu, Ming-De Li, Jian-Chao Zhang, Si-Min Ruan, Shan-Shan Wu, Xin-Xin Lin, Hai-Yu Kang, Xiao-Yan Xie, Ming-De Lu, Ming Kuang, Er-Jiao Xu, Wei Wang","doi":"10.1186/s12880-024-01426-x","DOIUrl":null,"url":null,"abstract":"To establish a nomogram for differentiating malignant and benign focal liver lesions (FLLs) using ultrasomics features derived from contrast-enhanced ultrasound (CEUS). 527 patients were retrospectively enrolled. On the training cohort, ultrasomics features were extracted from CEUS and b-mode ultrasound (BUS). Automatic feature selection and model development were performed using the Ultrasomics-Platform software, outputting the corresponding ultrasomics scores. A nomogram based on the ultrasomics scores from artery phase (AP), portal venous phase (PVP) and delayed phase (DP) of CEUS, and clinical factors were established. On the validation cohort, the diagnostic performance of the nomogram was assessed and compared with seniorexpert and resident radiologists. In the training cohort, the AP, PVP and DP scores exhibited better differential performance than BUS score, with area under the curve (AUC) of 84.1-85.1% compared with the BUS (74.6%, P < 0.05). In the validation cohort, the AUC of combined nomogram and expert was significantly higher than that of the resident (91.4% vs. 89.5% vs. 79.3%, P < 0.05). The combined nomogram had a comparable sensitivity with the expert and resident (95.2% vs. 98.4% vs. 97.6%), while the expert had a higher specificity than the nomogram and the resident (80.6% vs. 72.2% vs. 61.1%, P = 0.205). A CEUS ultrasomics based nomogram had an expert level performance in FLL characterization.","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":"19 1","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Medical Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12880-024-01426-x","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
To establish a nomogram for differentiating malignant and benign focal liver lesions (FLLs) using ultrasomics features derived from contrast-enhanced ultrasound (CEUS). 527 patients were retrospectively enrolled. On the training cohort, ultrasomics features were extracted from CEUS and b-mode ultrasound (BUS). Automatic feature selection and model development were performed using the Ultrasomics-Platform software, outputting the corresponding ultrasomics scores. A nomogram based on the ultrasomics scores from artery phase (AP), portal venous phase (PVP) and delayed phase (DP) of CEUS, and clinical factors were established. On the validation cohort, the diagnostic performance of the nomogram was assessed and compared with seniorexpert and resident radiologists. In the training cohort, the AP, PVP and DP scores exhibited better differential performance than BUS score, with area under the curve (AUC) of 84.1-85.1% compared with the BUS (74.6%, P < 0.05). In the validation cohort, the AUC of combined nomogram and expert was significantly higher than that of the resident (91.4% vs. 89.5% vs. 79.3%, P < 0.05). The combined nomogram had a comparable sensitivity with the expert and resident (95.2% vs. 98.4% vs. 97.6%), while the expert had a higher specificity than the nomogram and the resident (80.6% vs. 72.2% vs. 61.1%, P = 0.205). A CEUS ultrasomics based nomogram had an expert level performance in FLL characterization.
利用对比增强超声(CEUS)得出的超声组学特征,建立区分肝脏恶性和良性病灶(FLLs)的提名图。研究人员回顾性招募了 527 名患者。在训练队列中,从CEUS和双模式超声(BUS)中提取了超声组学特征。使用超声组学平台软件进行自动特征选择和模型开发,并输出相应的超声组学评分。根据CEUS动脉期(AP)、门静脉期(PVP)和延迟期(DP)的超声组学评分和临床因素建立了提名图。在验证队列中,评估了提名图的诊断性能,并与老年专家和常驻放射科医生进行了比较。在训练队列中,AP、PVP 和 DP 评分的差异化表现优于 BUS 评分,曲线下面积(AUC)为 84.1-85.1%,而 BUS 为 74.6%,P < 0.05。在验证队列中,联合提名图和专家的 AUC 明显高于住院医师(91.4% vs. 89.5% vs. 79.3%,P < 0.05)。联合提名图的灵敏度与专家和住院医师相当(95.2% vs. 98.4% vs. 97.6%),而专家的特异性高于提名图和住院医师(80.6% vs. 72.2% vs. 61.1%,P = 0.205)。基于CEUS超声组学的提名图在FLL定性方面的表现达到了专家水平。
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.