| 1 |
Dong Y, Cekuolis A, Schreiber-Dietrich D, et al. Review on pediatric malignant focal liver lesions with imaging evaluation: Part II[J]. Diagnostics (Basel), 2023, 13(24): 3659.
|
| 2 |
Kelgeri C, Renz D, McGuirk S, et al. Liver tumours in children: The hepatologist's view[J]. J Pediatr Gastroenterol Nutr, 2021,72(4): 487-493.
|
| 3 |
耿耿, 崔楷悦, 朱呈瞻, 等. 计算机辅助手术系统对各年龄段小儿肝脏体积的大数据分析及临床意义[J]. 临床小儿外科杂志, 2017, 16(4): 335-340.
|
| 4 |
梁萍, 于杰. 肝病超声诊断指南[J]. 临床肝胆病杂志, 2021, 37(8): 1770-1785,1993-1994.
|
| 5 |
张亚茹, 杨艺华, 刘培, 等. 儿童肿瘤患者诊疗镇静现状研究进展[J]. 中华肿瘤防治杂志, 2021, 28(15): 1192-1196.
|
| 6 |
Cui XW, Li KN, Yi AJ, et al. Ultrasound elastography[J]. Endosc Ultrasound, 2022, 11(4): 252-274.
|
| 7 |
Abdulla M, Abdulla M, Al-Hashimi H, et al. Two-dimensional shear wave ultrasound elastography for monitoring pediatric liver transplantation: a review of recent advances[J]. Pediatr Transplant, 2025, 29(1): e70010.
|
| 8 |
Ferraioli G, Barr RG, Berzigotti A, et al. WFUMB guideline/guidance on liver multiparametric ultrasound: Part 1. Update to 2018 guidelines on liver ultrasound elastography[J]. Ultrasound Med Biol, 2024, 50(8): 1071-1087.
|
| 9 |
Obrist A, Ruby L, Martin A, et al. Influence of measurement depth and acquisition parameters on shear wave speed and shear wave dispersion in certified phantoms using a canon aplio clinical ultrasound scanner[J]. Ultrasound Med Biol, 2023, 49(8): 1742-1759.
|
| 10 |
Imtiaz M, Khaqan MU, Mazhar M, et al. Correlation of shear wave elastography with liver biopsy in children with chronic liver disease[J]. Pak J Med Sci, 2025, 41(2): 585-589.
|
| 11 |
中华医学会病理学分会儿科病理学组, 福棠儿童医学发展研究中心病理专业委员会. 肝母细胞瘤病理诊断专家共识[J]. 中华病理学杂志, 2019, 48(3): 176-181.
|
| 12 |
袁理, 王凤华, 李丽萍, 等. 儿童肝脏血管源性肿瘤22例患者临床病理分析[J]. 中华病理学杂志, 2021, 50(9): 5.
|
| 13 |
Wang Y, Jia L, Wang X, et al. Diagnostic performance of 2-D shear wave elastography for differentiation of hepatoblastoma and hepatic hemangioma in children under 3 years of age[J]. Ultrasound Med Biol, 2019, 45(6): 1397-1406.
|
| 14 |
Özmen E, Adaletli I, Kayadibi Y, et al. The impact of share wave elastography in differentiation of hepatic hemangioma from malignant liver tumors in pediatric population[J]. Eur J Radiol, 2014, 83(9): 1691-1697.
|
| 15 |
Krolak C, Wei A, Shumaker M, et al. A Comprehensive and repeatable contrast-enhanced ultrasound quantification approach for clinical evaluations of tumor blood flow[J]. Invest Radiol, 2025, 60(4): 281-290.
|
| 16 |
Badiu SM, Gheorghe EC, Nicolau C, et al. Quantitative time intensity curve analysis of contrast-enhanced ultrasound (CEUS) examinations for the assessment of focal liver lesions[J]. Med Ultrason, 2024, 26(1): 63-71.
|
| 17 |
Schooler GR, Squires JH, Alazraki A, et al. Pediatric hepatoblastoma, hepatocellular carcinoma, and other hepatic neoplasms: Consensus Imaging Recommendations from American College of Radiology Pediatric Liver Reporting and Data System (LI-RADS) Working Group[J]. Radiology, 2020, 296(3): 493-497.
|
| 18 |
Darge K, Back SJ, Barth RA, et al. Starting a pediatric contrast ultrasound service: made simple![J]. Pediatr Radiol, 2021, 51(12): 2139-2146.
|
| 19 |
Squires JH, Mccarville MB. Contrast-enhanced ultrasound in children: Implementation and key diagnostic applications[J]. AJR Am J Roentgenol, 2021, 217(5): 1217-1231.
|
| 20 |
Chen M, Qiu M, Liu Y, et al. Utility of the pediatric liver contrast-enhanced ultrasound criteria in differentiating malignant and benign multifocal lesions[J]. Pediatr Radiol, 2023, 53(10): 2004-2012.
|
| 21 |
Wang G, Xie X, Chen H, et al. Development of a pediatric liver CEUS criterion to classify benign and malignant liver lesions in pediatric patients: a pilot study[J]. Eur Radiol, 2021, 31(9): 6747-6757.
|
| 22 |
Fang C, Anupindi SA, Back SJ, et al. Contrast-enhanced ultrasound of benign and malignant liver lesions in children[J]. Pediatr Radiol, 2021, 51(12): 2181-2197.
|
| 23 |
Han D, Wang T, Wang R, et al. Application of quantitative parameters of contrast-enhanced ultrasound in common benign and malignant lesions in pediatric livers: a preliminary study[J]. Diagnostics (Basel), 2023, 13(22): 3443.
|
| 24 |
Mostafa AG, Abramson Z, Ghbrial M, et al. Correction: contrast enhanced ultrasound of liver lesions in patients treated for childhood malignancies[J]. Cancer Imaging, 2024, 24(1): 138.
|
| 25 |
Jiang ZP, Zeng KY, Huang JY, et al. Differentiating malignant and benign focal liver lesions in children using CEUS LI-RADS combined with serum alpha-fetoprotein[J]. World J Gastroenterol, 2022, 28(21): 2350-2360.
|
| 26 |
Cannella R, Pilato G, Mazzola M, et al. New microvascular ultrasound techniques: abdominal applications[J]. Radiol Med, 2023, 128(9): 1023-1034.
|
| 27 |
Zhang X, Cheng F, Song X, et al. Superb microvascular imaging for evaluation of microvascularity in breast nodules compared with conventional Doppler imaging[J]. Quant Imaging Med Surg, 2023, 13(10): 7029-7040.
|
| 28 |
Gu LH, Fang H, Liu XS, et al. Additional value of superb microvascular imaging for assessing hepatic arterial blood flow after pediatric liver transplantation[J]. Pediatr Transplant, 2020, 24(7): e13785.
|
| 29 |
Hwang SM, Yoo SY, Jeong WK, et al. Superb microvascular imaging in pediatric focal nodular hyperplasia[J]. J Pediatr Hematol Oncol, 2024, 46(3): e233-e240.
|
| 30 |
Chen X, Zhou L, Xia Y, et al. Superb microvascular imaging for evaluating the activity of juvenile localised scleroderma: a preliminary study[J]. Eur Radiol, 2024, 34(10): 6376-6383.
|
| 31 |
Yaxier N, Zhang Y, Song J, et al. Clinical evaluation of new bone formation during limb lengthening in children using ultrasound combined with superb microvascular imaging[J]. Bone Joint J, 2024, 106-B(7): 751-758.
|
| 32 |
Ohno Y, Fujimoto T, Shibata Y. A new era in diagnostic ultrasound, superb microvascular imaging: preliminary results in pediatric hepato-gastrointestinal disorders[J]. Eur J Pediatr Surg, 2017, 27(1): 20-25.
|
| 33 |
Zhang H, Meng Z, Ru J, et al. Application and prospects of AI-based radiomics in ultrasound diagnosis[J]. Vis Comput Ind Biomed Art, 2023, 6(1): 20.
|
| 34 |
Tiyarattanachai T, Apiparakoon T, Marukatat S, et al. The feasibility to use artificial intelligence to aid detecting focal liver lesions in real-time ultrasound: a preliminary study based on videos[J]. Sci Rep, 2022, 12(1): 7749.
|
| 35 |
Nishida N, Yamakawa M, Shiina T, et al. Artificial intelligence (AI) models for the ultrasonographic diagnosis of liver tumors and comparison of diagnostic accuracies between AI and human experts[J]. J Gastroenterol, 2022, 57(4): 309-321.
|
| 36 |
Zhao T, Zeng Z, Li T, et al. USC-ENet: a high-efficiency model for the diagnosis of liver tumors combining B-mode ultrasound and clinical data[J]. Health Inf Sci Syst, 2023, 11(1): 15.
|
| 37 |
Ding W, Meng Y, Ma J, et al. Contrast-enhanced ultrasound-based AI model for multi-classification of focal liver lesions[J]. J Hepatol, 2025: S0168-8278(25)00018-2.
|
| 38 |
袁瑶, 唐缨, 牛宁宁, 等. 基于超声影像组学鉴别小儿肝移植后淋巴组织增生性疾病与淋巴结反应性增生[J]. 中国超声医学杂志, 2023, 39(5): 540-544.
|
| 39 |
Lin W, Ruan J, Liu Z, et al. Exploring the diagnostic value of ultrasound radiomics for neonatal respiratory distress syndrome[J]. BMC Pediatr, 2024, 24(1): 215.
|
| 40 |
Chen J, Wen ZY, Yang XQ, et al. Ultrasound-based radiomics for the classification of Henoch-Schönlein purpura nephritis in children[J]. Ultrason Imaging, 2024, 46(2): 110-120.
|