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For: Khalifa F, Soliman A, El-Baz A, Abou El-Ghar M, El-Diasty T, Gimel’farb G, Ouseph R, Dwyer AC. Models and methods for analyzing DCE-MRI: a review. Med Phys. 2014;41:124301. [PMID: 25471985 DOI: 10.1118/1.4898202] [Cited by in Crossref: 128] [Cited by in F6Publishing: 118] [Article Influence: 18.3] [Reference Citation Analysis]
Number Citing Articles
1 Debus C, Floca R, Ingrisch M, Kompan I, Maier-Hein K, Abdollahi A, Nolden M. MITK-ModelFit: A generic open-source framework for model fits and their exploration in medical imaging - design, implementation and application on the example of DCE-MRI. BMC Bioinformatics 2019;20:31. [PMID: 30651067 DOI: 10.1186/s12859-018-2588-1] [Cited by in Crossref: 12] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
2 Jansen MJA, Kuijf HJ, Veldhuis WB, Wessels FJ, Viergever MA, Pluim JPW. Automatic classification of focal liver lesions based on MRI and risk factors. PLoS One. 2019;14:e0217053. [PMID: 31095624 DOI: 10.1371/journal.pone.0217053] [Cited by in Crossref: 11] [Cited by in F6Publishing: 9] [Article Influence: 3.7] [Reference Citation Analysis]
3 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]
4 Petralia G, Summers PE, Agostini A, Ambrosini R, Cianci R, Cristel G, Calistri L, Colagrande S. Dynamic contrast-enhanced MRI in oncology: how we do it. Radiol med 2020;125:1288-300. [DOI: 10.1007/s11547-020-01220-z] [Cited by in Crossref: 6] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
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6 Xie T, Chen X, Fang J, Kang H, Xue W, Tong H, Cao P, Wang S, Yang Y, Zhang W. Textural features of dynamic contrast-enhanced MRI derived model-free and model-based parameter maps in glioma grading. J Magn Reson Imaging 2018;47:1099-111. [PMID: 28845594 DOI: 10.1002/jmri.25835] [Cited by in Crossref: 29] [Cited by in F6Publishing: 22] [Article Influence: 5.8] [Reference Citation Analysis]
7 Gimnich OA, Holbrook J, Belousova T, Short CM, Taylor AA, Nambi V, Morrisett JD, Ballantyne CM, Bismuth J, Shah DJ, Brunner G. Relation of Magnetic Resonance Imaging Based Arterial Signal Enhancement to Markers of Peripheral Artery Disease. Am J Cardiol 2021;140:140-7. [PMID: 33144163 DOI: 10.1016/j.amjcard.2020.10.049] [Reference Citation Analysis]
8 Crich SG, Terreno E, Aime S. Nano-sized and other improved reporters for magnetic resonance imaging of angiogenesis. Adv Drug Deliv Rev 2017;119:61-72. [PMID: 28802567 DOI: 10.1016/j.addr.2017.08.004] [Cited by in Crossref: 14] [Cited by in F6Publishing: 11] [Article Influence: 2.8] [Reference Citation Analysis]
9 Zou J, Balter JM, Cao Y. Estimation of pharmacokinetic parameters from DCE-MRI by extracting long and short time-dependent features using an LSTM network. Med Phys 2020;47:3447-57. [PMID: 32379942 DOI: 10.1002/mp.14222] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]
10 van Hoof RH, Hermeling E, Truijman MT, van Oostenbrugge RJ, Daemen JW, van der Geest RJ, van Orshoven NP, Schreuder AH, Backes WH, Daemen MJ, Wildberger JE, Kooi ME. Phase-based vascular input function: Improved quantitative DCE-MRI of atherosclerotic plaques. Med Phys 2015;42:4619-28. [PMID: 26233189 DOI: 10.1118/1.4924949] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 1.0] [Reference Citation Analysis]
11 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]
12 Huang W, Beckett BR, Tudorica A, Meyer JM, Afzal A, Chen Y, Mansoor A, Hayden JB, Doung YC, Hung AY, Holtorf ML, Aston TJ, Ryan CW. Evaluation of Soft Tissue Sarcoma Response to Preoperative Chemoradiotherapy Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging. Tomography 2016;2:308-16. [PMID: 28066805 DOI: 10.18383/j.tom.2016.00202] [Cited by in Crossref: 13] [Cited by in F6Publishing: 16] [Article Influence: 2.2] [Reference Citation Analysis]
13 Ahmed Z, Levesque IR. Pharmacokinetic modeling of dynamic contrast-enhanced MRI using a reference region and input function tail. Magn Reson Med 2020;83:286-98. [PMID: 31393033 DOI: 10.1002/mrm.27913] [Cited by in Crossref: 1] [Article Influence: 0.3] [Reference Citation Analysis]
14 Huang HM, Lin C. A kernel-based image denoising method for improving parametric image generation. Med Image Anal 2019;55:41-8. [PMID: 31022639 DOI: 10.1016/j.media.2019.04.003] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 1.3] [Reference Citation Analysis]
15 Wu PH, Gibbons M, Foreman SC, Carballido-Gamio J, Han M, Krug R, Liu J, Link TM, Kazakia GJ. Cortical bone vessel identification and quantification on contrast-enhanced MR images. Quant Imaging Med Surg 2019;9:928-41. [PMID: 31367547 DOI: 10.21037/qims.2019.05.23] [Cited by in Crossref: 6] [Article Influence: 2.0] [Reference Citation Analysis]
16 Nguyen TB, Cron GO, Bezzina K, Perdrizet K, Torres CH, Chakraborty S, Woulfe J, Jansen GH, Thornhill RE, Zanette B, Cameron IG. Correlation of Tumor Immunohistochemistry with Dynamic Contrast-Enhanced and DSC-MRI Parameters in Patients with Gliomas. AJNR Am J Neuroradiol 2016;37:2217-23. [PMID: 27585700 DOI: 10.3174/ajnr.A4908] [Cited by in Crossref: 16] [Cited by in F6Publishing: 6] [Article Influence: 2.7] [Reference Citation Analysis]
17 Pathak V, Nolte T, Rama E, Rix A, Dadfar SM, Paefgen V, Banala S, Buhl EM, Weiler M, Schulz V, Lammers T, Kiessling F. Molecular magnetic resonance imaging of Alpha-v-Beta-3 integrin expression in tumors with ultrasound microbubbles. Biomaterials 2021;275:120896. [PMID: 34090049 DOI: 10.1016/j.biomaterials.2021.120896] [Reference Citation Analysis]
18 Louis JS, Odille F, Mandry D, De Chillou C, Huttin O, Felblinger J, Venner C, Beaumont M. Design and evaluation of an abbreviated pixelwise dynamic contrast enhancement analysis protocol for early extracellular volume fraction estimation. Magn Reson Imaging 2021;76:61-8. [PMID: 33227403 DOI: 10.1016/j.mri.2020.11.007] [Reference Citation Analysis]
19 Chen BB, Hsu CY, Yu CW, Liang PC, Hsu C, Hsu CH, Cheng AL, Shih TT. Dynamic Contrast-enhanced MR Imaging of Advanced Hepatocellular Carcinoma: Comparison with the Liver Parenchyma and Correlation with the Survival of Patients Receiving Systemic Therapy. Radiology. 2016;281:454-464. [PMID: 27171020 DOI: 10.1148/radiol.2016152659] [Cited by in Crossref: 17] [Cited by in F6Publishing: 15] [Article Influence: 2.8] [Reference Citation Analysis]
20 Gerwing M, Krähling T, Schliemann C, Harrach S, Schwöppe C, Berdel AF, Klein S, Hartmann W, Wardelmann E, Heindel WL, Lenz G, Berdel WE, Wildgruber M. Multiparametric Magnetic Resonance Imaging for Immediate Target Hit Assessment of CD13-Targeted Tissue Factor tTF-NGR in Advanced Malignant Disease. Cancers (Basel) 2021;13:5880. [PMID: 34884988 DOI: 10.3390/cancers13235880] [Reference Citation Analysis]
21 Li M, Xu X, Xia K, Jiang H, Jiang J, Sun J, Lu Z. Comparison of Diagnostic Performance between Perfusion-Related Intravoxel Incoherent Motion DWI and Dynamic Contrast-Enhanced MRI in Rectal Cancer. Comput Math Methods Med 2021;2021:5095940. [PMID: 34367318 DOI: 10.1155/2021/5095940] [Reference Citation Analysis]
22 Brix G, Salehi Ravesh M, Griebel J. Two-compartment modeling of tissue microcirculation revisited. Med Phys 2017;44:1809-22. [DOI: 10.1002/mp.12196] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 1.0] [Reference Citation Analysis]
23 Yin Z, Li X, Zhang Y, Tao J, Yang Y, Fang S, Zhang Z, Yuan Y, Liu Y, Wang S. Correlations between DWI, IVIM, and HIF-1α expression based on MRI and pathology in a murine model of rhabdomyosarcoma. Magn Reson Med 2022. [PMID: 35377480 DOI: 10.1002/mrm.29250] [Reference Citation Analysis]
24 Budzik J, Lefebvre G, Behal H, Verclytte S, Hardouin P, Teixeira P, Cotten A. Bone marrow perfusion measured with dynamic contrast enhanced magnetic resonance imaging is correlated to body mass index in adults. Bone 2017;99:47-52. [DOI: 10.1016/j.bone.2017.03.048] [Cited by in Crossref: 10] [Cited by in F6Publishing: 8] [Article Influence: 2.0] [Reference Citation Analysis]
25 Li B, Oka R, Xuan P, Yoshimura Y, Nakaguchi T. Robust multi-modal prostate cancer classification via feature autoencoder and dual attention. Informatics in Medicine Unlocked 2022;30:100923. [DOI: 10.1016/j.imu.2022.100923] [Reference Citation Analysis]
26 Ryu JK, Rhee SJ, Song JY, Cho SH, Jahng GH. Characteristics of quantitative perfusion parameters on dynamic contrast-enhanced MRI in mammographically occult breast cancer. J Appl Clin Med Phys 2016;17:377-90. [PMID: 27685105 DOI: 10.1120/jacmp.v17i5.6091] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 0.8] [Reference Citation Analysis]
27 Fan G, Ya Y, Ni X, Hou J, Yu R. Application Value of Magnetic Resonance Perfusion Imaging in the Early Diagnosis of Rat Hepatic Fibrosis. Biomed Res Int 2019;2019:5095934. [PMID: 31950040 DOI: 10.1155/2019/5095934] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
28 Spanakis M, Kontopodis E, Van Cauter S, Sakkalis V, Marias K. Assessment of DCE-MRI parameters for brain tumors through implementation of physiologically-based pharmacokinetic model approaches for Gd-DOTA. J Pharmacokinet Pharmacodyn 2016;43:529-47. [PMID: 27647272 DOI: 10.1007/s10928-016-9493-x] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 0.8] [Reference Citation Analysis]
29 Meyer H, Hamerla G, Höhn AK, Surov A. Whole Lesion Histogram Analysis Derived From Morphological MRI Sequences Might be Able to Predict EGFR- and Her2-Expression in Cervical Cancer. Academic Radiology 2019;26:e208-15. [DOI: 10.1016/j.acra.2018.09.008] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 1.7] [Reference Citation Analysis]
30 Park JS, Lim E, Choi SH, Sohn CH, Lee J, Park J. Model-Based High-Definition Dynamic Contrast Enhanced MRI for Concurrent Estimation of Perfusion and Microvascular Permeability. Med Image Anal 2020;59:101566. [PMID: 31639623 DOI: 10.1016/j.media.2019.101566] [Reference Citation Analysis]
31 Sun Y, Reynolds HM, Wraith D, Williams S, Finnegan ME, Mitchell C, Murphy D, Haworth A. Automatic stratification of prostate tumour aggressiveness using multiparametric MRI: a horizontal comparison of texture features. Acta Oncol 2019;58:1118-26. [PMID: 30994052 DOI: 10.1080/0284186X.2019.1598576] [Cited by in Crossref: 9] [Cited by in F6Publishing: 5] [Article Influence: 3.0] [Reference Citation Analysis]
32 Lefrançois P, Zummo-Soucy M, Olivié D, Billiard JS, Gilbert G, Garel J, Visée E, Manchec P, Tang A. Diagnostic performance of intravoxel incoherent motion diffusion-weighted imaging and dynamic contrast-enhanced MRI for assessment of anal fistula activity.PLoS One. 2018;13:e0191822. [PMID: 29370278 DOI: 10.1371/journal.pone.0191822] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 0.8] [Reference Citation Analysis]
33 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]
34 Zhang J, Liu H, Tong H, Wang S, Yang Y, Liu G, Zhang W. Clinical Applications of Contrast-Enhanced Perfusion MRI Techniques in Gliomas: Recent Advances and Current Challenges. Contrast Media Mol Imaging 2017;2017:7064120. [PMID: 29097933 DOI: 10.1155/2017/7064120] [Cited by in Crossref: 32] [Cited by in F6Publishing: 33] [Article Influence: 6.4] [Reference Citation Analysis]
35 Kim JK. Magnetic Resonance Imaging for Drug Development. Adv Exp Med Biol 2021;1310:187-209. [PMID: 33834438 DOI: 10.1007/978-981-33-6064-8_9] [Reference Citation Analysis]
36 Fang K, Wang Z, Li Z, Wang B, Han G, Cheng Z, Chen Z, Lan C, Zhang Y, Zhao P, Jin X, Liu Y, Bai R. Convolutional neural network for accelerating the computation of the extended Tofts model in dynamic contrast-enhanced magnetic resonance imaging. J Magn Reson Imaging 2021;53:1898-910. [PMID: 33382513 DOI: 10.1002/jmri.27495] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
37 Xia Z, Gu H, Yuan Y, Xiang S, Zhang Z, Tao X. Value of Dynamic Contrast-Enhanced (DCE) MRI in Predicting Response to Foam Sclerotherapy of Venous Malformations. J Magn Reson Imaging 2021. [PMID: 33991357 DOI: 10.1002/jmri.27657] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
38 Li X, Wang Q, Dou Y, Zhang Y, Tao J, Yang L, Wang S. Soft tissue sarcoma: can dynamic contrast-enhanced (DCE) MRI be used to predict the histological grade? Skeletal Radiol 2020;49:1829-38. [PMID: 32519183 DOI: 10.1007/s00256-020-03491-z] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
39 Lang N, Yuan H, Yu HJ, Su MY. Diagnosis of Spinal Lesions Using Heuristic and Pharmacokinetic Parameters Measured by Dynamic Contrast-Enhanced MRI. Acad Radiol 2017;24:867-75. [PMID: 28162875 DOI: 10.1016/j.acra.2016.12.014] [Cited by in Crossref: 5] [Cited by in F6Publishing: 6] [Article Influence: 1.0] [Reference Citation Analysis]
40 Petitclerc L, Sebastiani G, Gilbert G, Cloutier G, Tang A. Liver fibrosis: Review of current imaging and MRI quantification techniques. J Magn Reson Imaging. 2017;45:1276-1295. [PMID: 27981751 DOI: 10.1002/jmri.25550] [Cited by in Crossref: 89] [Cited by in F6Publishing: 78] [Article Influence: 14.8] [Reference Citation Analysis]
41 Lu Y, Peng W, Song J, Chen T, Wang X, Hou Z, Yan Z, Koh TS. On the potential use of dynamic contrast-enhanced (DCE) MRI parameters as radiomic features of cervical cancer. Med Phys 2019;46:5098-109. [PMID: 31523829 DOI: 10.1002/mp.13821] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
42 Wu M, Lu L, Zhang Q, Guo Q, Zhao F, Li T, Zhang X. Relating Doses of Contrast Agent Administered to TIC and Semi-Quantitative Parameters on DCE-MRI: Based on a Murine Breast Tumor Model. PLoS One 2016;11:e0149279. [PMID: 26901876 DOI: 10.1371/journal.pone.0149279] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.3] [Reference Citation Analysis]
43 Wang X, Lin W, Mao Y, Peng W, Song J, Lu Y, Zhao Y, Koh TS, Hou Z, Yan Z. A Comparative Study of Two-Compartment Exchange Models for Dynamic Contrast-Enhanced MRI in Characterizing Uterine Cervical Carcinoma. Contrast Media Mol Imaging 2019;2019:3168416. [PMID: 31897081 DOI: 10.1155/2019/3168416] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
44 Callewaert B, Jones EAV, Himmelreich U, Gsell W. Non-Invasive Evaluation of Cerebral Microvasculature Using Pre-Clinical MRI: Principles, Advantages and Limitations. Diagnostics (Basel) 2021;11:926. [PMID: 34064194 DOI: 10.3390/diagnostics11060926] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
45 Giannini V, Mazzetti S, Vignati A, Russo F, Bollito E, Porpiglia F, Stasi M, Regge D. A fully automatic computer aided diagnosis system for peripheral zone prostate cancer detection using multi-parametric magnetic resonance imaging. Comput Med Imaging Graph 2015;46 Pt 2:219-26. [PMID: 26391055 DOI: 10.1016/j.compmedimag.2015.09.001] [Cited by in Crossref: 35] [Cited by in F6Publishing: 26] [Article Influence: 5.0] [Reference Citation Analysis]
46 Thibodeau-Antonacci A, Petitclerc L, Gilbert G, Bilodeau L, Olivié D, Cerny M, Castel H, Turcotte S, Huet C, Perreault P, Soulez G, Chagnon M, Kadoury S, Tang A. Dynamic contrast-enhanced MRI to assess hepatocellular carcinoma response to Transarterial chemoembolization using LI-RADS criteria: A pilot study. Magn Reson Imaging 2019;62:78-86. [PMID: 31247250 DOI: 10.1016/j.mri.2019.06.017] [Cited by in Crossref: 11] [Cited by in F6Publishing: 10] [Article Influence: 3.7] [Reference Citation Analysis]
47 King AD, Chow SK, Yu KH, Mo FK, Yeung DK, Yuan J, Law BK, Bhatia KS, Vlantis AC, Ahuja AT. DCE-MRI for Pre-Treatment Prediction and Post-Treatment Assessment of Treatment Response in Sites of Squamous Cell Carcinoma in the Head and Neck. PLoS One 2015;10:e0144770. [PMID: 26657972 DOI: 10.1371/journal.pone.0144770] [Cited by in Crossref: 15] [Cited by in F6Publishing: 13] [Article Influence: 2.1] [Reference Citation Analysis]
48 Han X, Hong G, Guo Y, Wu H, Sun P, Wei Q, Chen Z, He W, Liu Z, Liang C. Novel MRI technique for the quantification of biochemical deterioration in steroid-induced osteonecrosis of femoral head: a prospective diagnostic trial. J Hip Preserv Surg 2021;8:40-50. [PMID: 34567599 DOI: 10.1093/jhps/hnab032] [Reference Citation Analysis]
49 Paprad T, Lertbutsayanukul C, Jittapiromsak N. Value of Diffusion-Weighted Imaging and Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Prediction of Treatment Outcomes in Nasopharyngeal Carcinoma. J Comput Assist Tomogr 2022. [PMID: 35483078 DOI: 10.1097/RCT.0000000000001304] [Reference Citation Analysis]
50 Menon RG, Zibetti MVW, Pendola M, Regatte RR. Measurement of Three-Dimensional Internal Dynamic Strains in the Intervertebral Disc of the Lumbar Spine With Mechanical Loading and Golden-Angle Radial Sparse Parallel-Magnetic Resonance Imaging. J Magn Reson Imaging 2021;54:486-96. [PMID: 33713520 DOI: 10.1002/jmri.27591] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
51 Hu R, Yang H, Chen Y, Zhou T, Zhang J, Chen TW, Zhang XM. Dynamic Contrast-Enhanced MRI for Measuring Pancreatic Perfusion in Acute Pancreatitis: A Preliminary Study. Acad Radiol 2019;26:1641-9. [PMID: 30885415 DOI: 10.1016/j.acra.2019.02.007] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
52 Fiordelisi MF, Cavaliere C, Auletta L, Basso L, Salvatore M. Magnetic Resonance Imaging for Translational Research in Oncology. J Clin Med 2019;8:E1883. [PMID: 31698697 DOI: 10.3390/jcm8111883] [Cited by in Crossref: 5] [Cited by in F6Publishing: 2] [Article Influence: 1.7] [Reference Citation Analysis]
53 Wang HY, Su ZH, Xu X, Sun ZP, Duan FX, Song YY, Li L, Wang YW, Ma X, Guo AT, Ma L, Ye HY. Dynamic Contrast-enhanced MR Imaging in Renal Cell Carcinoma: Reproducibility of Histogram Analysis on Pharmacokinetic Parameters. Sci Rep 2016;6:29146. [PMID: 27380733 DOI: 10.1038/srep29146] [Cited by in Crossref: 14] [Cited by in F6Publishing: 15] [Article Influence: 2.3] [Reference Citation Analysis]
54 van Dijken BRJ, van Laar PJ, Smits M, Dankbaar JW, Enting RH, van der Hoorn A. Perfusion MRI in treatment evaluation of glioblastomas: Clinical relevance of current and future techniques. J Magn Reson Imaging 2019;49:11-22. [PMID: 30561164 DOI: 10.1002/jmri.26306] [Cited by in Crossref: 28] [Cited by in F6Publishing: 24] [Article Influence: 14.0] [Reference Citation Analysis]
55 Byk K, Jasinski K, Bartel Z, Jasztal A, Sitek B, Tomanek B, Chlopicki S, Skorka T. MRI-based assessment of liver perfusion and hepatocyte injury in the murine model of acute hepatitis. MAGMA 2016;29:789-98. [PMID: 27160299 DOI: 10.1007/s10334-016-0563-2] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
56 Lin CN, Liao YS, Chen WC, Wang YS, Lee LW. Use of Myometrium as an Internal Reference for Endometrial and Cervical Cancer on Multiphase Contrast-Enhanced MRI. PLoS One 2016;11:e0157820. [PMID: 27326456 DOI: 10.1371/journal.pone.0157820] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 0.8] [Reference Citation Analysis]
57 Boutry S, Laurent S, Burtea C. Editorial for "New Cluster Analysis Method for Quantitative DCE-MRI Assessing Tumor Heterogeneity Induced by E7130 Treatment to a Breast Cancer Mouse Model". J Magn Reson Imaging 2022. [PMID: 35506540 DOI: 10.1002/jmri.28225] [Reference Citation Analysis]
58 Bernal J, Valdés-Hernández MDC, Escudero J, Viksne L, Heye AK, Armitage PA, Makin S, Touyz RM, Wardlaw JM. Analysis of dynamic texture and spatial spectral descriptors of dynamic contrast-enhanced brain magnetic resonance images for studying small vessel disease. Magn Reson Imaging 2020;66:240-7. [PMID: 31730881 DOI: 10.1016/j.mri.2019.11.001] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Article Influence: 1.3] [Reference Citation Analysis]
59 Baboli M, Zhang J, Kim SG. Advances in Diffusion and Perfusion MRI for Quantitative Cancer Imaging. Curr Pathobiol Rep 2019;7:129-41. [PMID: 33344067 DOI: 10.1007/s40139-019-00204-7] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
60 Liao Y, Lee L, Yang P, Kuo L, Kuan L, Tseng W, Hwang D. Assessment of liver cirrhosis for patients with Child's A classification before hepatectomy using dynamic contrast-enhanced MRI. Clinical Radiology 2019;74:407.e11-7. [DOI: 10.1016/j.crad.2019.01.017] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.7] [Reference Citation Analysis]
61 Zhang Y, Yue B, Zhao X, Chen H, Sun L, Zhang X, Hao D. Benign or Malignant Characterization of Soft-Tissue Tumors by Using Semiquantitative and Quantitative Parameters of Dynamic Contrast-Enhanced Magnetic Resonance Imaging. Can Assoc Radiol J 2020;71:92-9. [PMID: 32062994 DOI: 10.1177/0846537119888409] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
62 Yan Y, Sun X, Shen B. Contrast agents in dynamic contrast-enhanced magnetic resonance imaging. Oncotarget 2017;8:43491-505. [PMID: 28415647 DOI: 10.18632/oncotarget.16482] [Cited by in Crossref: 17] [Cited by in F6Publishing: 12] [Article Influence: 4.3] [Reference Citation Analysis]
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