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For: Wei J, Jiang H, Gu D, Niu M, Fu F, Han Y, Song B, Tian J. Radiomics in liver diseases: Current progress and future opportunities. Liver Int 2020;40:2050-63. [PMID: 32515148 DOI: 10.1111/liv.14555] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
Number Citing Articles
1 Lafata KJ, Wang Y, Konkel B, Yin FF, Bashir MR. Radiomics: a primer on high-throughput image phenotyping. Abdom Radiol (NY) 2021. [PMID: 34435228 DOI: 10.1007/s00261-021-03254-x] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
2 Granata V, Fusco R, De Muzio F, Cutolo C, Setola SV, Dell'Aversana F, Grassi F, Belli A, Silvestro L, Ottaiano A, Nasti G, Avallone A, Flammia F, Miele V, Tatangelo F, Izzo F, Petrillo A. Radiomics and machine learning analysis based on magnetic resonance imaging in the assessment of liver mucinous colorectal metastases. Radiol Med 2022. [PMID: 35653011 DOI: 10.1007/s11547-022-01501-9] [Reference Citation Analysis]
3 Anteby R, Klang E, Horesh N, Nachmany I, Shimon O, Barash Y, Kopylov U, Soffer S. Deep learning for noninvasive liver fibrosis classification: A systematic review. Liver Int 2021. [PMID: 34008300 DOI: 10.1111/liv.14966] [Reference Citation Analysis]
4 Granata V, Fusco R, Belli A, Borzillo V, Palumbo P, Bruno F, Grassi R, Ottaiano A, Nasti G, Pilone V, Petrillo A, Izzo F. Conventional, functional and radiomics assessment for intrahepatic cholangiocarcinoma. Infect Agents Cancer 2022;17. [DOI: 10.1186/s13027-022-00429-z] [Reference Citation Analysis]
5 Li Y, Xie Y, Xu Y, Zhang N, Li G, Ju S. A new scheme of global feature management improved the performance and stability of radiomics model: a study based on CT images of acute brainstem infarction. Eur Radiol 2022. [PMID: 35267092 DOI: 10.1007/s00330-022-08659-w] [Reference Citation Analysis]
6 Granata V, Fusco R, De Muzio F, Cutolo C, Setola SV, Dell' Aversana F, Ottaiano A, Avallone A, Nasti G, Grassi F, Pilone V, Miele V, Brunese L, Izzo F, Petrillo A. Contrast MR-Based Radiomics and Machine Learning Analysis to Assess Clinical Outcomes following Liver Resection in Colorectal Liver Metastases: A Preliminary Study. Cancers (Basel) 2022;14:1110. [PMID: 35267418 DOI: 10.3390/cancers14051110] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
7 Zhou Y, Zhou G, Zhang J, Xu C, Zhu F, Xu P. DCE-MRI based radiomics nomogram for preoperatively differentiating combined hepatocellular-cholangiocarcinoma from mass-forming intrahepatic cholangiocarcinoma. Eur Radiol 2022. [PMID: 35128572 DOI: 10.1007/s00330-022-08548-2] [Reference Citation Analysis]
8 Granata V, Fusco R, Setola SV, Simonetti I, Cozzi D, Grazzini G, Grassi F, Belli A, Miele V, Izzo F, Petrillo A. An update on radiomics techniques in primary liver cancers. Infect Agent Cancer 2022;17:6. [PMID: 35246207 DOI: 10.1186/s13027-022-00422-6] [Reference Citation Analysis]
9 Wei J, Jiang H, Gu D, Niu M, Fu F, Han Y, Song B, Tian J. Radiomics in liver diseases: Current progress and future opportunities. Liver Int 2020;40:2050-63. [PMID: 32515148 DOI: 10.1111/liv.14555] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
10 Vitellius C, Paisant A, Lannes A, Chaigneau J, Oberti F, Lebigot J, Fouchard I, Boursier J, David P, Aubé C, Calès P; CDMIR group. Liver fibrosis staging by computed tomography: Prospective randomized multicentric evaluation of image analyses. Clin Res Hepatol Gastroenterol 2021;46:101797. [PMID: 34500117 DOI: 10.1016/j.clinre.2021.101797] [Reference Citation Analysis]
11 Chong H, Gong Y, Pan X, Liu A, Chen L, Yang C, Zeng M. Peritumoral Dilation Radiomics of Gadoxetate Disodium-Enhanced MRI Excellently Predicts Early Recurrence of Hepatocellular Carcinoma without Macrovascular Invasion After Hepatectomy. J Hepatocell Carcinoma 2021;8:545-63. [PMID: 34136422 DOI: 10.2147/JHC.S309570] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
12 Granata V, Fusco R, De Muzio F, Cutolo C, Setola SV, Dell'Aversana F, Ottaiano A, Nasti G, Grassi R, Pilone V, Miele V, Brunese MC, Tatangelo F, Izzo F, Petrillo A. EOB-MR Based Radiomics Analysis to Assess Clinical Outcomes following Liver Resection in Colorectal Liver Metastases. Cancers (Basel) 2022;14:1239. [PMID: 35267544 DOI: 10.3390/cancers14051239] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
13 Granata V, Fusco R, Setola SV, De Muzio F, Dell' Aversana F, Cutolo C, Faggioni L, Miele V, Izzo F, Petrillo A. CT-Based Radiomics Analysis to Predict Histopathological Outcomes Following Liver Resection in Colorectal Liver Metastases. Cancers (Basel) 2022;14:1648. [PMID: 35406419 DOI: 10.3390/cancers14071648] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
14 Ren S, Li Q, Liu S, Qi Q, Duan S, Mao B, Li X, Wu Y, Zhang L. Clinical Value of Machine Learning-Based Ultrasomics in Preoperative Differentiation Between Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma: A Multicenter Study. Front Oncol 2021;11:749137. [PMID: 34804935 DOI: 10.3389/fonc.2021.749137] [Reference Citation Analysis]
15 Jensen LJ, Kim D, Elgeti T, Steffen IG, Hamm B, Nagel SN. Stability of Liver Radiomics across Different 3D ROI Sizes-An MRI In Vivo Study. Tomography 2021;7:866-76. [PMID: 34941645 DOI: 10.3390/tomography7040073] [Reference Citation Analysis]
16 Reginelli A, Nardone V, Giacobbe G, Belfiore MP, Grassi R, Schettino F, Del Canto M, Grassi R, Cappabianca S. Radiomics as a New Frontier of Imaging for Cancer Prognosis: A Narrative Review. Diagnostics (Basel) 2021;11:1796. [PMID: 34679494 DOI: 10.3390/diagnostics11101796] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
17 Duan J, Qiu Q, Zhu J, Shang D, Dou X, Sun T, Yin Y, Meng X. Reproducibility for Hepatocellular Carcinoma CT Radiomic Features: Influence of Delineation Variability Based on 3D-CT, 4D-CT and Multiple-Parameter MR Images. Front Oncol 2022;12:881931. [DOI: 10.3389/fonc.2022.881931] [Reference Citation Analysis]
18 Fusco R, Granata V, Grazzini G, Pradella S, Borgheresi A, Bruno A, Palumbo P, Bruno F, Grassi R, Giovagnoni A, Grassi R, Miele V, Barile A. Radiomics in medical imaging: pitfalls and challenges in clinical management. Jpn J Radiol 2022. [PMID: 35344132 DOI: 10.1007/s11604-022-01271-4] [Reference Citation Analysis]
19 Xiang F, Liang X, Yang L, Liu X, Yan S. CT radiomics nomogram for the preoperative prediction of severe post-hepatectomy liver failure in patients with huge (≥ 10 cm) hepatocellular carcinoma. World J Surg Oncol 2021;19:344. [PMID: 34895260 DOI: 10.1186/s12957-021-02459-0] [Reference Citation Analysis]
20 Chen ZW, Tang K, Zhao YF, Chen YZ, Tang LJ, Li G, Huang OY, Wang XD, Targher G, Byrne CD, Zheng XW, Zheng MH. Radiomics based on fluoro-deoxyglucose positron emission tomography predicts liver fibrosis in biopsy-proven MAFLD: a pilot study. Int J Med Sci 2021;18:3624-30. [PMID: 34790034 DOI: 10.7150/ijms.64458] [Reference Citation Analysis]
21 Granata V, Fusco R, De Muzio F, Cutolo C, Mattace Raso M, Gabelloni M, Avallone A, Ottaiano A, Tatangelo F, Brunese MC, Miele V, Izzo F, Petrillo A. Radiomics and Machine Learning Analysis Based on Magnetic Resonance Imaging in the Assessment of Colorectal Liver Metastases Growth Pattern. Diagnostics 2022;12:1115. [DOI: 10.3390/diagnostics12051115] [Reference Citation Analysis]
22 Peng Z, Wang Y, Wang Y, Jiang S, Fan R, Zhang H, Jiang W. Application of radiomics and machine learning in head and neck cancers. Int J Biol Sci 2021;17:475-86. [PMID: 33613106 DOI: 10.7150/ijbs.55716] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
23 Gong XQ, Tao YY, Wu YK, Liu N, Yu X, Wang R, Zheng J, Liu N, Huang XH, Li JD, Yang G, Wei XQ, Yang L, Zhang XM. Progress of MRI Radiomics in Hepatocellular Carcinoma. Front Oncol 2021;11:698373. [PMID: 34616673 DOI: 10.3389/fonc.2021.698373] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
24 Chong H, Gong Y, Zhang Y, Dai Y, Sheng R, Zeng M. Radiomics on Gadoxetate Disodium-enhanced MRI: Non-invasively Identifying Glypican 3-Positive Hepatocellular Carcinoma and Postoperative Recurrence. Acad Radiol 2022:S1076-6332(22)00254-9. [PMID: 35562264 DOI: 10.1016/j.acra.2022.04.006] [Reference Citation Analysis]