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10.1016/j.ejrad.2020.109049

http://scihub22266oqcxt.onion/10.1016/j.ejrad.2020.109049
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32464580!ä!32464580

suck abstract from ncbi


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pmid32464580      Eur+J+Radiol 2020 ; 129 (ä): 109049
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  • Evaluating feasibility of high resolution T1-perfusion MRI with whole brain coverage using compressed SENSE: Application to glioma grading #MMPMID32464580
  • Sasi S D; Ramaniharan AK; Bhattacharjee R; Gupta RK; Saha I; Van Cauteren M; Shah T; Gopalakrishnan K; Gupta A; Singh A
  • Eur J Radiol 2020[Aug]; 129 (ä): 109049 PMID32464580show ga
  • PURPOSE: To evaluate the efficacy of optimized T1-Perfusion MRI protocol (protocol-2) with whole brain coverage and improved spatial resolution using Compressed-SENSE (CSENSE) to differentiate high-grade-glioma (HGG) and low-grade-glioma (LGG) and to compare it with the conventional protocol (protocol-1) with partial brain coverage used in our center. METHODS: This study included MRI data from 5 healthy volunteers, a phantom and 126 brain tumor patients. Current study had two parts: To analyze the effect of CSENSE on 3D-T1-weighted (W) fast-field-echo (FFE) images, T1-W, dual-PDT2-W turbo-spin-echo images and T1 maps, and to evaluate the performance of high resolution T1-Perfusion MRI protocol with whole brain coverage optimized using CSENSE. Coefficient-of-Variation (COV), Relative-Percentage-Error (RPE), Normalized-Mean-Squared-Error (NMSE) and qualitative scoring were used for the former study. Tracer-kinetic (K(trans),v(e),v(p)) and hemodynamic (rCBV,rCBF) parameters computed from both protocols were used to differentiate LGG and HGG. RESULTS: The image quality of all structural images was found to be of diagnostic quality till R?=?4. NMSE in healthy T1-W-FFE images and COV in phantom images increased with-respect-to R and images provided optimum quality till R?=?4. Structural images and maps exhibited artefacts from R?=?6. All parameters in tumor tissue and hemodynamic parameters in healthy gray matter tissue computed from both protocols were not significantly different. Parameters computed from protocol-2 performed better in terms of glioma grading. For both protocols, rCBF performed least (AUC?=?0.759 and 0.851) and combination of all parameters performed best (AUC?=?0.890 and 0.964). CONCLUSION: CSENSE (R?=?4) can be used to improve the resolution and brain coverage for T1-Perfusion analysis used to differentiate gliomas.
  • |Adolescent[MESH]
  • |Adult[MESH]
  • |Aged[MESH]
  • |Aged, 80 and over[MESH]
  • |Brain Mapping/*methods[MESH]
  • |Brain Neoplasms/*diagnostic imaging/*pathology[MESH]
  • |Brain/diagnostic imaging/pathology[MESH]
  • |Child[MESH]
  • |Feasibility Studies[MESH]
  • |Female[MESH]
  • |Glioma/*diagnostic imaging/*pathology[MESH]
  • |Humans[MESH]
  • |Magnetic Resonance Imaging/*methods[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Neoplasm Grading[MESH]
  • |Phantoms, Imaging[MESH]
  • |Prospective Studies[MESH]
  • |Retrospective Studies[MESH]


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