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For: Abramson RG, Arlinghaus LR, Dula AN, Quarles CC, Stokes AM, Weis JA, Whisenant JG, Chekmenev EY, Zhukov I, Williams JM, Yankeelov TE. MR Imaging Biomarkers in Oncology Clinical Trials. Magn Reson Imaging Clin N Am 2016;24:11-29. [PMID: 26613873 DOI: 10.1016/j.mric.2015.08.002] [Cited by in Crossref: 19] [Cited by in F6Publishing: 15] [Article Influence: 3.2] [Reference Citation Analysis]
Number Citing Articles
1 Giganti F, Tang L, Baba H. Gastric cancer and imaging biomarkers: Part 1 - a critical review of DW-MRI and CE-MDCT findings. Eur Radiol 2019;29:1743-53. [PMID: 30280246 DOI: 10.1007/s00330-018-5732-4] [Cited by in Crossref: 20] [Cited by in F6Publishing: 20] [Article Influence: 5.0] [Reference Citation Analysis]
2 Goldenberg JM, Cárdenas-Rodríguez J, Pagel MD. Machine learning improves classification of preclinical models of pancreatic cancer with chemical exchange saturation transfer MRI. Magn Reson Med 2019;81:594-601. [PMID: 30277270 DOI: 10.1002/mrm.27439] [Cited by in Crossref: 1] [Article Influence: 0.3] [Reference Citation Analysis]
3 Curcean S, Cheng L, Picchia S, Tunariu N, Collins D, Blackledge M, Popat S, O'Brien M, Minchom A, Leach MO, Koh DM. Early Response to Chemotherapy in Malignant Pleural Mesothelioma Evaluated Using Diffusion-Weighted Magnetic Resonance Imaging: Initial Observations. JTO Clin Res Rep 2021;2:100253. [PMID: 34870249 DOI: 10.1016/j.jtocrr.2021.100253] [Reference Citation Analysis]
4 Woodall RT, Barnes SL, Hormuth DA 2nd, Sorace AG, Quarles CC, Yankeelov TE. The effects of intravoxel contrast agent diffusion on the analysis of DCE-MRI data in realistic tissue domains. Magn Reson Med 2018;80:330-40. [PMID: 29115690 DOI: 10.1002/mrm.26995] [Cited by in Crossref: 5] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
5 Hectors SJ, Wagner M, Bane O, Besa C, Lewis S, Remark R, Chen N, Fiel MI, Zhu H, Gnjatic S, Merad M, Hoshida Y, Taouli B. Quantification of hepatocellular carcinoma heterogeneity with multiparametric magnetic resonance imaging. Sci Rep. 2017;7:2452. [PMID: 28550313 DOI: 10.1038/s41598-017-02706-z] [Cited by in Crossref: 45] [Cited by in F6Publishing: 46] [Article Influence: 9.0] [Reference Citation Analysis]
6 Rastegar S, Beigi J, Saeedi E, Shiri I, Qasempour Y, Rezaei M, Abdollahi H. Radiographic Image Radiomics Feature Reproducibility: A Preliminary Study on the Impact of Field Size. J Med Imaging Radiat Sci 2020;51:128-36. [PMID: 32089514 DOI: 10.1016/j.jmir.2019.11.006] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
7 Sorace AG, Wu C, Barnes SL, Jarrett AM, Avery S, Patt D, Goodgame B, Luci JJ, Kang H, Abramson RG, Yankeelov TE, Virostko J. Repeatability, reproducibility, and accuracy of quantitative mri of the breast in the community radiology setting. J Magn Reson Imaging 2018. [PMID: 29570895 DOI: 10.1002/jmri.26011] [Cited by in Crossref: 16] [Cited by in F6Publishing: 20] [Article Influence: 4.0] [Reference Citation Analysis]
8 Deng J, Wang Y. Quantitative magnetic resonance imaging biomarkers in oncological clinical trials: Current techniques and standardization challenges. Chronic Dis Transl Med 2017;3:8-20. [PMID: 29063052 DOI: 10.1016/j.cdtm.2017.02.002] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 1.6] [Reference Citation Analysis]
9 Kurz C, Buizza G, Landry G, Kamp F, Rabe M, Paganelli C, Baroni G, Reiner M, Keall PJ, van den Berg CAT, Riboldi M. Medical physics challenges in clinical MR-guided radiotherapy. Radiat Oncol 2020;15:93. [PMID: 32370788 DOI: 10.1186/s13014-020-01524-4] [Cited by in Crossref: 30] [Cited by in F6Publishing: 29] [Article Influence: 15.0] [Reference Citation Analysis]
10 Aryal MP, Lee C, Hawkins PG, Chapman C, Eisbruch A, Mierzwa M, Cao Y. Real-Time Quantitative Assessment of Accuracy and Precision of Blood Volume Derived from DCE-MRI in Individual Patients During a Clinical Trial. Tomography 2019;5:61-7. [PMID: 30854443 DOI: 10.18383/j.tom.2018.00029] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 1.5] [Reference Citation Analysis]
11 Saida Y, Brender JR, Yamamoto K, Mitchell JB, Krishna MC, Kishimoto S. Multimodal Molecular Imaging Detects Early Responses to Immune Checkpoint Blockade. Cancer Res 2021;81:3693-705. [PMID: 33837042 DOI: 10.1158/0008-5472.CAN-20-3182] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
12 Antolak AG, Jackson EF. Development and evaluation of an arterial spin-labeling digital reference object for quality control and comparison of data analysis applications. Phys Med Biol 2019;64:02NT01. [PMID: 30540982 DOI: 10.1088/1361-6560/aaf83b] [Reference Citation Analysis]
13 Lin G, Keshari KR, Park JM. Cancer Metabolism and Tumor Heterogeneity: Imaging Perspectives Using MR Imaging and Spectroscopy. Contrast Media Mol Imaging 2017;2017:6053879. [PMID: 29114178 DOI: 10.1155/2017/6053879] [Cited by in Crossref: 21] [Cited by in F6Publishing: 16] [Article Influence: 4.2] [Reference Citation Analysis]
14 Hernando D, Zhang Y, Pirasteh A. Quantitative diffusion MRI of the abdomen and pelvis. Med Phys 2021. [PMID: 34554579 DOI: 10.1002/mp.15246] [Reference Citation Analysis]
15 Baldi D, Aiello M, Duggento A, Salvatore M, Cavaliere C. MR Imaging-Histology Correlation by Tailored 3D-Printed Slicer in Oncological Assessment. Contrast Media Mol Imaging 2019;2019:1071453. [PMID: 31275082 DOI: 10.1155/2019/1071453] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 2.3] [Reference Citation Analysis]
16 Weingärtner S, Desmond KL, Obuchowski NA, Baessler B, Zhang Y, Biondetti E, Ma D, Golay X, Boss MA, Gunter JL, Keenan KE, Hernando D; ISMRM Quantitative MR Study Group. Development, validation, qualification, and dissemination of quantitative MR methods: Overview and recommendations by the ISMRM quantitative MR study group. Magn Reson Med 2021. [PMID: 34825741 DOI: 10.1002/mrm.29084] [Reference Citation Analysis]
17 Khan AQ, Siveen KS, Prabhu KS, Kuttikrishnan S, Akhtar S, Shanmugakonar M, Al-naemi HA, Haris M, Uddin S. Role of animal research in human malignancies. Animal Models in Cancer Drug Discovery. Elsevier; 2019. pp. 1-29. [DOI: 10.1016/b978-0-12-814704-7.00003-9] [Cited by in Crossref: 2] [Article Influence: 0.7] [Reference Citation Analysis]
18 Bianchini L, Santinha J, Loução N, Figueiredo M, Botta F, Origgi D, Cremonesi M, Cassano E, Papanikolaou N, Lascialfari A. A multicenter study on radiomic features from T2 -weighted images of a customized MR pelvic phantom setting the basis for robust radiomic models in clinics. Magn Reson Med 2021;85:1713-26. [PMID: 32970859 DOI: 10.1002/mrm.28521] [Cited by in Crossref: 5] [Cited by in F6Publishing: 6] [Article Influence: 2.5] [Reference Citation Analysis]
19 Virostko J, Sorace AG, Slavkova KP, Kazerouni AS, Jarrett AM, DiCarlo JC, Woodard S, Avery S, Goodgame B, Patt D, Yankeelov TE. Quantitative multiparametric MRI predicts response to neoadjuvant therapy in the community setting. Breast Cancer Res 2021;23:110. [PMID: 34838096 DOI: 10.1186/s13058-021-01489-6] [Reference Citation Analysis]