Development and validation of an ultrasound-based prediction model for differentiating between malignant and benign solid pancreatic lesions

被引:7
|
作者
Huang, Jiayan [1 ]
Yang, Jie [1 ]
Ding, Jianming [2 ]
Zhou, Jing [3 ]
Yang, Rui [1 ]
Li, Jiawu [1 ]
Luo, Yan [1 ]
Lu, Qiang [4 ]
机构
[1] Sichuan Univ, Dept Ultrasound, West China Hosp, Chengdu 610041, Peoples R China
[2] Tianjin Third Cent Hosp, Dept Ultrasound, Tianjin 300170, Peoples R China
[3] Affiliated Hosp Southwest Med Univ, Dept Ultrasound, Luzhou 646000, Sichuan, Peoples R China
[4] Sichuan Univ, West China Hosp, Lab Ultrasound Med, Dept Ultrasound, Chengdu 610041, Peoples R China
基金
中国国家自然科学基金;
关键词
Pancreatic neoplasms; Ultrasonography; Contrast media; Nomograms; CONTRAST-ENHANCED ULTRASOUND; DIAGNOSTIC PERFORMANCE; CANCER; TUMORS; MASS; ULTRASONOGRAPHY; MULTICENTER; SONOGRAPHY; PATTERNS; DUCT;
D O I
10.1007/s00330-022-08930-0
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Objective To identify the diagnostic ability of precontrast and contrast-enhanced ultrasound (CEUS) in differentiating between malignant and benign solid pancreatic lesions (MSPLs and BSPLs) and to develop an easy-to-use diagnostic nomogram. Materials and methods This study was approved by the institutional review board. Patients with pathologically confirmed solid pancreatic lesions were enrolled from one tertiary medical centre from March 2011 to June 2021 and in two tertiary institutions between January 2015 and June 2021. A prediction nomogram model was established in the training set by using precontrast US and CEUS imaging features that were independently associated with MSPLs. The performance of the prediction model was further externally validated. Results A total of 155 patients (mean age, 55 +/- 14.6 years, M/F = 84/71) and 78 patients (mean age, 59 +/- 13.4 years, M/F = 36/42) were included in the training and validation cohorts, respectively. In the training set, an ill-defined border and dilated main pancreatic duct on precontrast ultrasound, CEUS patterns of hypoenhancement in both the arterial and venous phases of CEUS, and hyperenhancement/isoenhancement followed by washout were independently associated with MSPLs. The prediction nomogram model developed with the aforementioned variables showed good performance in differentiating MSPLs from BSPLs with an area under the curve (AUC) of 0.938 in the training set and 0.906 in the validation set. Conclusion Hypoenhancement in all phases, hyperenhancement/isoenhancement followed by washout on CEUS, an ill-defined border, and a dilated main pancreatic duct were independent risk factors for MSPLs. The nomogram constructed based on these predictors can be used to diagnose MSPLs.
引用
收藏
页码:8296 / 8305
页数:10
相关论文
共 50 条
  • [21] Ultrasound-based radiomics analysis for differentiating benign and malignant breast lesions: from static images to CEUS video analysis (vol 12, 951973, 2022)
    Zhu, Jun-Yan
    He, Han-Lu
    Lin, Zi-Mei
    Zhao, Jian-Qiang
    Jiang, Xiao-Chun
    Liang, Zhe-Hao
    Huang, Xiao-Ping
    Bao, Hai-Wei
    Huang, Pin-Tong
    Chen, Fen
    FRONTIERS IN ONCOLOGY, 2024, 14
  • [22] SEMI-QUANTITATIVE AND QUALITATIVE ASSESSMENT OF BREAST ULTRASOUND ELASTOGRAPHY IN DIFFERENTIATING BETWEEN MALIGNANT AND BENIGN LESIONS
    Alhabshi, Sharifah Majedah Idrus
    Rahmat, Kartini
    Halim, Nurazidawati Abdul
    Aziz, Suraya
    Radhika, Sridharan
    Gan, Gek Choo
    Vijayananthan, Anushya
    Westerhout, Caroline Judy
    Mohd-Shah, Mohammad Nazri
    Jaszle, Saladina
    Latar, Nani Harlina Mohd
    Muhammad, Rohaizak
    ULTRASOUND IN MEDICINE AND BIOLOGY, 2013, 39 (04): : 568 - 578
  • [23] Contrast-enhanced ultrasound for differentiating benign from malignant focal solid renal lesions in pediatric patients
    Fu, Yusi
    Zhong, Jia
    Tan, Yan
    Zheng, Taiqing
    Liu, Minghui
    Wang, Guotao
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [24] Scoring model of convex probe endobronchial ultrasound multimodal imaging in differentiating benign and malignant lung lesions
    Zhi, Xinxin
    Wang, Lei
    Chen, Junxiang
    Zheng, Xiaoxuan
    Li, Ying
    Sun, Jiayuan
    JOURNAL OF THORACIC DISEASE, 2020, 12 (12) : 7645 - 7655
  • [25] Development and validation of an ultrasound-based nomogram to improve the diagnostic accuracy for malignant thyroid nodules
    Bao-liang Guo
    Fu-sheng Ouyang
    Li-zhu Ouyang
    Zi-wei Liu
    Shao-jia Lin
    Wei Meng
    Xi-yi Huang
    Hai-xiong Chen
    Shao-ming Yang
    Qiu-gen Hu
    European Radiology, 2019, 29 : 1518 - 1526
  • [26] Ultrasound-based deep learning radiomics model for differentiating benign, borderline, and malignant ovarian tumours: a multi-class classification exploratory study
    Du, Yangchun
    Guo, Wenwen
    Xiao, Yanju
    Chen, Haining
    Yao, Jinxiu
    Wu, Ji
    BMC MEDICAL IMAGING, 2024, 24 (01)
  • [27] Development and validation of an ultrasound-based nomogram to improve the diagnostic accuracy for malignant thyroid nodules
    Guo, Bao-liang
    Ouyang, Fu-sheng
    Ouyang, Li-zhu
    Liu, Zi-wei
    Lin, Shao-jia
    Meng, Wei
    Huang, Xi-yi
    Chen, Hai-xiong
    Yang, Shao-ming
    Hu, Qiu-gen
    EUROPEAN RADIOLOGY, 2019, 29 (03) : 1518 - 1526
  • [28] The Diagnostic Accuracy of Endoscopic Ultrasound (EUS) Elastography in Differentiating Benign From Malignant Pancreatic Lesions, a Meta-Analysis
    Ortiz, Arleen M.
    Elhanafi, Sherif
    Mccallum, Richard
    Zuckerman, Marc J.
    Othman, Mohamed O.
    GASTROINTESTINAL ENDOSCOPY, 2012, 75 (04) : 181 - 182
  • [29] Role of Ultrasound and Ultrasound-Based Prediction Model in Differentiating Follicular Thyroid Carcinoma From Follicular Thyroid Adenoma
    Zhang, Fan
    Mei, Fang
    Chen, Wen
    Zhang, Yongyue
    JOURNAL OF ULTRASOUND IN MEDICINE, 2024, 43 (08) : 1389 - 1399
  • [30] Role of Ultrasound and Ultrasound-Based Prediction Model in Differentiating Follicular Thyroid Carcinoma From Follicular Thyroid Adenoma
    Hu, Zhe
    Tian, Zhikang
    Chen, Yueqin
    Chen, Yuge
    JOURNAL OF ULTRASOUND IN MEDICINE, 2024, 43 (11) : 2217 - 2217