LinkedIn

 آمار

تعداد نشریات20
تعداد شماره‌ها1,149
تعداد مقالات10,518
تعداد مشاهده مقاله45,416,040
تعداد دریافت فایل اصل مقاله11,291,711
Farshidfar, Z, Faeghi, F, Haghighatkhah, H R, Abdolmohammadi, J. (1396). The Optimization of Magnetic Resonance Imaging Pulse Sequences in Order to Better Detection of Multiple Sclerosis Plaques. سامانه مدیریت نشریات علمی, 7(3), 265-270.
Z Farshidfar; F Faeghi; H R Haghighatkhah; J Abdolmohammadi. "The Optimization of Magnetic Resonance Imaging Pulse Sequences in Order to Better Detection of Multiple Sclerosis Plaques". سامانه مدیریت نشریات علمی, 7, 3, 1396, 265-270.
Farshidfar, Z, Faeghi, F, Haghighatkhah, H R, Abdolmohammadi, J. (1396). 'The Optimization of Magnetic Resonance Imaging Pulse Sequences in Order to Better Detection of Multiple Sclerosis Plaques', سامانه مدیریت نشریات علمی, 7(3), pp. 265-270.
Farshidfar, Z, Faeghi, F, Haghighatkhah, H R, Abdolmohammadi, J. The Optimization of Magnetic Resonance Imaging Pulse Sequences in Order to Better Detection of Multiple Sclerosis Plaques. سامانه مدیریت نشریات علمی, 1396; 7(3): 265-270.

The Optimization of Magnetic Resonance Imaging Pulse Sequences in Order to Better Detection of Multiple Sclerosis Plaques

Journal of Biomedical Physics and Engineering
مقاله 7، دوره 7، شماره 3، آذر 2017، صفحه 265-270    اصل مقاله (542.4 K)
نوع مقاله: Original Research
نویسندگان
Z Farshidfar1؛ F Faeghi2؛ H R Haghighatkhah3؛ J Abdolmohammadi* 4
1MSc of Medical Imaging Technology (MRI), Radiology Department of Paramedical School, Shiraz University of Medical Sciences, Shiraz, Iran
2Ph.D. in Medical Physics, Radiology Technology Department, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
3MD, Department of Radiology, Shohada Tajrish Hospital, Shahid Beheshti University of medical sciences, Tehran, Iran
4MSc. of Medical Imaging Technology (MRI), Department of Radiology, Faculty of Paramedical Sciences, Kurdistan University of Medical Sciences, Sanandaj, Iran
چکیده
Background and objective: Magnetic resonance imaging (MRI) is the most sensitive technique to detect multiple sclerosis (MS) plaques in central nervous system. In some cases, the patients who were suspected to MS, Whereas MRI images are normal, but whether patients don’t have MS plaques or MRI images are not enough optimized enough in order to show MS plaques? The aim of the current study is evaluating the efficiency of different MRI sequences in order to better detection of MS plaques.Materials and methods: In this cross-sectional study which was performed at Shohada-E Tajrish in Tehran - Iran hospital between October, 2011 to April, 2012, included 20 patients who suspected to MS disease were selected by the method of random sampling and underwent routine brain Pulse sequences (Axial T2w, Axial T1w, Coronal T2w, Sagittal T1w, Axial FLAIR) by Siemens, Avanto, 1.5 Tesla system. If any lesion which is suspected to the MS disease was observed, additional sequences such as: Sagittal FLAIR Fat Sat, Sagittal PDw-fat Sat, Sagittal PDw-water sat was also performed.Results: This study was performed in about 52 lesions and the results in more than 19 lesions showed that, for the Subcortical and Infratentorial areas, PDWw sequence with fat suppression is the best choice, And in nearly 33 plaques located in Periventricular area, FLAIR Fat Sat was the most effective sequence than both PDw fat and water suppression pulse sequences.Conclusion: Although large plaques may visible in all images, but important problem in patients with suspected MS is screening the tiny MS plaques. This study showed that for revealing the MS plaques located in the Subcortical and Infratentorial areas, PDw-fat sat is the most effective sequence, and for MS plaques in the periventricular area, FLAIR fat Sat is the best choice.
کلیدواژه‌ها
Multiple Sclerosis؛ MRI؛ PDW fat suppression؛ PDW water suppression؛ FLAIR
مراجع
  1. Lucchinetti CF, Popescu BF, Bunyan RF, Moll NM, Roemer SF, Lassmann H, et al. Inflammatory cortical demyelination in early multiple sclerosis. N Engl J Med. 2011;365:2188-97. doi.org/10.1056/NEJMoa1100648. PubMed PMID: 22150037. PubMed PMCID: 3282172.
  2. Filippi M, Rocca MA, Barkhof F, Bruck W, Chen JT, Comi G, et al. Association between pathological and MRI findings in multiple sclerosis. Lancet Neurol. 2012;11:349-60. doi.org/10.1016/S1474-4422(12)70003-0. PubMed PMID: 22441196.
  3. Antel J, Antel S, Caramanos Z, Arnold DL, Kuhlmann T. Primary progressive multiple sclerosis: part of the MS disease spectrum or separate disease entity? Acta Neuropathol. 2012;123:627-38. doi.org/10.1007/s00401-012-0953-0. PubMed PMID: 22327362.
  4. Vrethem M, Malmgren K, Lindh J. A patient with both narcolepsy and multiple sclerosis in association with Pandemrix vaccination. J Neurol Sci. 2012;321:89-91. doi.org/10.1016/j.jns.2012.07.025. PubMed PMID: 22841884.
  5. Skoog B, Runmarker B, Winblad S, Ekholm S, Andersen O. A representative cohort of patients with non-progressive multiple sclerosis at the age of normal life expectancy. Brain. 2012;135:900-11. doi.org/10.1093/brain/awr336. PubMed PMID: 22366800.
  6. Milo R, Kahana E. Multiple sclerosis: geoepidemiology, genetics and the environment. Autoimmunity reviews. 2010;9(5):A387-A94.
  7. Alport AR, Sander HW. Clinical approach to peripheral neuropathy: anatomic localization and diagnostic testing. Continuum (Minneap Minn). 2012;18:13-38. doi.org/10.1212/01.CON.0000411546.13207.b1. PubMed PMID: 22810068.
  8. Reimer P, Parizel PM, Meaney JF, Stichnoth FA. Clinical MR imaging: Springer; 2010.
  9. Minneboo A. Magnetic Resonance Imaging Predictors for Disability in Multiple Sclerosis: Amsterdam: Vrije Universiteit; 2008.
  10. Poser CM, Brinar VV. Diagnostic criteria for multiple sclerosis: an historical review. Clin Neurol Neurosurg. 2004;106:147-58. doi.org/10.1016/j.clineuro.2004.02.004. PubMed PMID: 15177763.
  11. McDonald WI, Compston A, Edan G, Goodkin D, Hartung HP, Lublin FD, et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann Neurol. 2001;50:121-7. doi.org/10.1002/ana.1032. PubMed PMID: 11456302.
  12. Polman CH, Reingold SC, Edan G, Filippi M, Hartung HP, Kappos L, et al. Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria”. Ann Neurol. 2005;58:840-6. doi.org/10.1002/ana.20703. PubMed PMID: 16283615.
  13. Loizou CP, Murray V, Pattichis MS, Seimenis I, Pantziaris M, Pattichis CS. Multiscale amplitude-modulation frequency-modulation (AM-FM) texture analysis of multiple sclerosis in brain MRI images. IEEE Trans Inf Technol Biomed. 2011;15:119-29. doi.org/10.1109/TITB.2010.2091279. PubMed PMID: 21062681.
  14. Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol. 2011;69:292-302. doi.org/10.1002/ana.22366. PubMed PMID: 21387374. PubMed PMCID: 3084507.
  15. Montalban X, Tintore M, Swanton J, Barkhof F, Fazekas F, Filippi M, et al. MRI criteria for MS in patients with clinically isolated syndromes. Neurology. 2010;74:427-34. doi.org/10.1212/WNL.0b013e3181cec45c. PubMed PMID: 20054006.
  16. Traboulsee A, Li DK, Zhao G, Paty DW. Conventional MRI techniques in multiple sclerosis. MR Imaging in White Matter Diseases of the Brain and Spinal Cord: Springer; 2005. p. 211-23.
  17. Miller DH, Albert PS, Barkhof F, Francis G, Frank JA, Hodgkinson S, et al. Guidelines for the use of magnetic resonance techniques in monitoring the treatment of multiple sclerosis. US National MS Society Task Force. Ann Neurol. 1996;39:6-16. doi.org/10.1002/ana.410390104. PubMed PMID: 8572668.
  18. Gawne-Cain ML, Silver NC, Moseley IF, Miller DH. Fast FLAIR of the brain: the range of appearances in normal subjects and its application to quantification of white-matter disease. Neuroradiology. 1997;39:243-9. doi.org/10.1007/s002340050402. PubMed PMID: 9144670.
  19. Kepes JJ. Large focal tumor-like demyelinating lesions of the brain: intermediate entity between multiple sclerosis and acute disseminated encephalomyelitis? A study of 31 patients. Ann Neurol. 1993;33:18-27. doi.org/10.1002/ana.410330105. PubMed PMID: 8494332.
  20. Brück W, Bitsch A, Kolenda H, Brück Y, Stiefel M, Lassmann H. Inflammatory central nervous system demyelination: correlation of magnetic resonance imaging findings with lesion pathology. Annals of Neurology. 1997;42(5):783-93.
  21. Nijeholt GJ, van Walderveen MA, Castelijns JA, van Waesberghe JH, Polman C, Scheltens P, et al. Brain and spinal cord abnormalities in multiple sclerosis. Correlation between MRI parameters, clinical subtypes and symptoms. Brain. 1998;121:687-97. doi.org/10.1093/brain/121.4.687. PubMed PMID: 9577394.
  22. Herskovits EH, Itoh R, Melhem ER. Accuracy for detection of simulated lesions: comparison of fluid-attenuated inversion-recovery, proton density--weighted, and T2-weighted synthetic brain MR imaging. AJR Am J Roentgenol. 2001;176:1313-8. doi.org/10.2214/ajr.176.5.1761313. PubMed PMID: 11312201.
  23. Kamson DO, Illes Z, Aradi M, Orsi G, Perlaki G, Leel-Ossy E, et al. Volumetric comparisons of supratentorial white matter hyperintensities on FLAIR MRI in patients with migraine and multiple sclerosis. J Clin Neurosci. 2012;19:696-701. doi.org/10.1016/j.jocn.2011.07.044. PubMed PMID: 22440862.
  24. Prosperini L, Kouleridou A, Petsas N, Leonardi L, Tona F, Pantano P, et al. The relationship between infratentorial lesions, balance deficit and accidental falls in multiple sclerosis. J Neurol Sci. 2011;304:55-60. doi.org/10.1016/j.jns.2011.02.014. PubMed PMID: 21402386.
  25. Lazeron RH, Langdon DW, Filippi M, van Waesberghe JH, Stevenson VL, Boringa JB, et al. Neuropsychological impairment in multiple sclerosis patients: the role of (juxta)cortical lesion on FLAIR. Mult Scler. 2000;6:280-5. doi.org/10.1177/135245850000600410. PubMed PMID: 10962549.
  26. Castillo MS, Davis FG, Surawicz T, Bruner JM, Bigner S, Coons S, et al. Consistency of primary brain tumor diagnoses and codes in cancer surveillance systems. Neuroepidemiology. 2004;23:85-93. doi.org/10.1159/000073980. PubMed PMID: 14739573.
  27. Gawne-Cain ML, O’Riordan JI, Thompson AJ, Moseley IF, Miller DH. Multiple sclerosis lesion detection in the brain: a comparison of fast fluid-attenuated inversion recovery and conventional T2-weighted dual spin echo. Neurology. 1997;49:364-70. doi.org/10.1212/WNL.49.2.364. PubMed PMID: 9270563.
  28. Bakshi R, Czarnecki D, Shaikh ZA, Priore RL, Janardhan V, Kaliszky Z, et al. Brain MRI lesions and atrophy are related to depression in multiple sclerosis. Neuroreport. 2000;11:1153-8. doi.org/10.1097/00001756-200004270-00003. PubMed PMID: 10817583.
  29. Seewann A, Kooi EJ, Roosendaal SD, Pouwels PJ, Wattjes MP, van der Valk P, et al. Postmortem verification of MS cortical lesion detection with 3D DIR. Neurology. 2012;78:302-8. doi.org/10.1212/WNL.0b013e31824528a0. PubMed PMID: 22218278.
  30. Roosendaal SD, Moraal B, Pouwels PJ, Vrenken H, Castelijns JA, Barkhof F, et al. Accumulation of cortical lesions in MS: relation with cognitive impairment. Mult Scler. 2009;15:708-14. doi.org/10.1177/1352458509102907. PubMed PMID: 19435749.
آمار
تعداد مشاهده مقاله: 740
تعداد دریافت فایل اصل مقاله: 139


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب