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125 related items for PubMed ID: 32679410

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  • 2. Autoregressive moving average modeling for hepatic iron quantification in the presence of fat.
    Tipirneni-Sajja A, Krafft AJ, Loeffler RB, Song R, Bahrami A, Hankins JS, Hillenbrand CM.
    J Magn Reson Imaging; 2019 Nov; 50(5):1620-1632. PubMed ID: 30761652
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  • 5. Simulation of a virtual liver iron overload model and R2 * estimation using multispectral fat-water models for GRE and UTE acquisitions at 1.5 T and 3 T.
    Neupane P, Shrestha U, Brasher S, Abramson Z, Tipirneni-Sajja A.
    NMR Biomed; 2023 Dec; 36(12):e5018. PubMed ID: 37539770
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  • 8. Quantitative susceptibility mapping in combination with water-fat separation for simultaneous liver iron and fat fraction quantification.
    Lin H, Wei H, He N, Fu C, Cheng S, Shen J, Wang B, Yan X, Liu C, Yan F.
    Eur Radiol; 2018 Aug; 28(8):3494-3504. PubMed ID: 29470640
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  • 9. Detection of hepatic steatosis and iron content at 3 Tesla: comparison of two-point Dixon, quantitative multi-echo Dixon, and MR spectroscopy.
    Zhan C, Olsen S, Zhang HC, Kannengiesser S, Chandarana H, Shanbhogue KP.
    Abdom Radiol (NY); 2019 Sep; 44(9):3040-3048. PubMed ID: 31286208
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  • 12. Evaluation of liver iron overload with R2* relaxometry with versus without fat suppression: both are clinically accurate but there are differences.
    Plaikner M, Kremser C, Zoller H, Jaschke W, Steurer M, Viveiros A, Henninger B.
    Eur Radiol; 2020 Nov; 30(11):5826-5833. PubMed ID: 32535737
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  • 13. Evaluation of hepatic iron concentration heterogeneities using the MRI R2* mapping method.
    Mazé J, Vesselle G, Herpe G, Boucebci S, Silvain C, Ingrand P, Tasu JP.
    Eur J Radiol; 2019 Jul; 116():47-54. PubMed ID: 31153573
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  • 14. A hybrid (iron-fat-water) phantom for liver iron overload quantification in the presence of contaminating fat using magnetic resonance imaging.
    Mobini N, Malekzadeh M, Haghighatkhah H, Saligheh Rad H.
    MAGMA; 2020 Jun; 33(3):385-392. PubMed ID: 31732894
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  • 15. Quantification of pancreatic iron overload and fat infiltration and their correlation with glucose disturbance in pediatric thalassemia major patients.
    Huang J, Shen J, Yang Q, Cheng Z, Chen X, Yu T, Zhong J, Su Y, Guo H, Liang B.
    Quant Imaging Med Surg; 2021 Feb; 11(2):665-675. PubMed ID: 33532266
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  • 16. MRI-Based Quantitative R2* Mapping at 3 Tesla Reflects Hepatic Iron Overload and Pathogenesis in Nonalcoholic Fatty Liver Disease Patients.
    Imajo K, Kessoku T, Honda Y, Hasegawa S, Tomeno W, Ogawa Y, Motosugi U, Saigusa Y, Yoneda M, Kirikoshi H, Yamanaka S, Utsunomiya D, Saito S, Nakajima A.
    J Magn Reson Imaging; 2022 Jan; 55(1):111-125. PubMed ID: 34184822
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  • 17. Hepatic steatosis modeling and MRI signal simulations for comparison of single- and dual-R2* models and estimation of fat fraction at 1.5T and 3T.
    Shrestha U, Esparza JP, Satapathy SK, Vanatta JM, Abramson ZR, Tipirneni-Sajja A.
    Comput Biol Med; 2024 May; 174():108448. PubMed ID: 38626508
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  • 18. Quantitative ultrashort echo time imaging for assessment of massive iron overload at 1.5 and 3 Tesla.
    Krafft AJ, Loeffler RB, Song R, Tipirneni-Sajja A, McCarville MB, Robson MD, Hankins JS, Hillenbrand CM.
    Magn Reson Med; 2017 Nov; 78(5):1839-1851. PubMed ID: 28090666
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  • 19. Quantitative susceptibility mapping (QSM) minimizes interference from cellular pathology in R2* estimation of liver iron concentration.
    Li J, Lin H, Liu T, Zhang Z, Prince MR, Gillen K, Yan X, Song Q, Hua T, Zhao X, Zhang M, Zhao Y, Li G, Tang G, Yang G, Brittenham GM, Wang Y.
    J Magn Reson Imaging; 2018 Oct; 48(4):1069-1079. PubMed ID: 29566449
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  • 20. Automated vessel exclusion technique for quantitative assessment of hepatic iron overload by R2*-MRI.
    Tipirneni-Sajja A, Song R, McCarville MB, Loeffler RB, Hankins JS, Hillenbrand CM.
    J Magn Reson Imaging; 2018 Jun; 47(6):1542-1551. PubMed ID: 29083524
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