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Methods Inf Med 2016; 55(03): 215-222
DOI: 10.3414/ME15-01-0148
Original Articles
Schattauer GmbH

Evaluation of Spontaneous Spinal Cerebrospinal Fluid Leaks Disease by Computerized Image Processing

Mustafa S. Yıldırım
1   Fatih University, Institute of Biomedical Engineering, Istanbul, Turkey
,
Sadık Kara
1   Fatih University, Institute of Biomedical Engineering, Istanbul, Turkey
,
Mehmet S. Albayram
2   Istanbul University, Faculty of Medicine, Istanbul, Turkey
,
Şükrü Okkesim
1   Fatih University, Institute of Biomedical Engineering, Istanbul, Turkey
› Institutsangaben
Weitere Informationen

Publikationsverlauf

received: 09. November 2015

accepted in revised form: 21. März 2016

Publikationsdatum:
08. Januar 2018 (online)

    Lizenzen und Reprints

Summary

Background: Spontaneous Spinal Cerebro -spinal Fluid Leaks (SSCFL) is a disease based on tears on the dura mater. Due to widespread symptoms and low frequency of the disease, diagnosis is problematic. Diagnostic lumbar puncture is commonly used for diagnosing SSCFL, though it is invasive and may cause pain, inflammation or new leakages. T2-weighted MR imaging is also used for diagnosis; however, the literature on T2-weighted MRI states that findings for diagnosis of SSCFL could be erroneous when differentiating the diseased and control. One another technique for diagnosis is CT-myelography, but this has been suggested to be less successful than T2-weighted MRI and it needs an initial lumbar puncture.

Objectives: This study aimed to develop an objective, computerized numerical analysis method using noninvasive routine Magnetic Resonance Images that can be used in the evaluation and diagnosis of SSCFL disease.

Methods: Brain boundaries were automatically detected using methods of mathematical morphology, and a distance transform was employed. According to normalized distances, average densities of certain sites were proportioned and a numerical criterion related to cerebrospinal fluid distribution was calculated.

Results: The developed method was able to differentiate between 14 patients and 14 control subjects significantly with p = 0.0088 and d = 0.958. Also, the pre and post-treatment MRI of four patients was obtained and analyzed. The results were differentiated statistically (p = 0.0320, d = 0.853).

Conclusions: An original, noninvasive and objective diagnostic test based on computerized image processing has been developed for evaluation of SSCFL. To our knowledge, this is the first computerized image processing method for evaluation of the disease. Discrimination between patients and controls shows the validity of the method. Also, post-treatment changes observed in four patients support this verdict.

Keywords

Spontaneous Spinal Cerebrospinal Fluid Leaks - spontaneous intracranial hypotension - computer-aided diagnosis - mathematical morphology - biomedical image processing
 

  • References

  • 1 Eklund A, Smielewski P, Chambers I, Alperin N, Malm J, Czosnyka M. et al. Assessment of cerebrospinal fluid outflow resistance. Med Biol Eng Comput 2007; 45 (Suppl. 08) 719-35. PubMed PMID: ISI:000248613400002.
    CrossrefPubMedSuche in Google Scholar
  • 2 Graff-Radford SB, Schievink WI. High-Pressure Headaches, Low-Pressure Syndromes, and CSF Leaks: Diagnosis and Management. Headache: The Journal of Head and Face Pain 2014; 54 (Suppl. 02) 394-401.
    CrossrefPubMedSuche in Google Scholar
  • 3 Schievink WI. Misdiagnosis of spontaneous intracranial hypotension. Arch Neurol 2003; 60 (Suppl. 12) 1713-8. PubMed PMID: ISI:000187178700006.
    CrossrefPubMedSuche in Google Scholar
  • 4 Schievink WI. Spontaneous spinal cerebrospinal fluid leaks and intracranial hypotension. JAMA 2006; 295 (Suppl. 19) 2286-96. PubMed PMID: 16705110. Epub 2006/05/18.
    CrossrefPubMedSuche in Google Scholar
  • 5 Rahman M, Bidari SS, Quisling RG, Friedman WA. Spontaneous intracranial hypotension: Dilemmas in diagnosis. Neurosurgery 2011; 69 (Suppl. 01) 4-14.
    CrossrefPubMedSuche in Google Scholar
  • 6 Schievink WI. Novel neuroimaging modalities in the evaluation of spontaneous cerebrospinal fluid leaks. Curr Neurol Neurosci Rep 2013; 13 (Suppl. 07) 358. PubMed PMID: 23703239. Epub 2013/05/25.
    CrossrefPubMedSuche in Google Scholar
  • 7 Hoxworth JM, Trentman TL, Kotsenas AL, Thielen KR, Nelson KD, Dodick DW. The role of digital subtraction myelography in the diagnosis and localization of spontaneous spinal CSF leaks. AJR Am J Roentgenol 2012; 199 (Suppl. 03) 649-53. PubMed PMID: 22915407. Epub 2012/08/24.
    CrossrefPubMedSuche in Google Scholar
  • 8 Ferrante E, Regna-Gladin C, Arpino I, Rubino F, Porrinis L, Ferrante MM. et al. Pseudo-subarachnoid hemorrhage: a potential imaging pitfall associated with spontaneous intracranial hypotension. Clin Neurol Neurosurg 2013; 115 (Suppl. 11) 2324-8. PubMed PMID: 24075686. Epub 2013/10/01.
    CrossrefPubMedSuche in Google Scholar
  • 9 Franzini A, Messina G, Chiapparini L, Bussone G. Treatment of spontaneous intracranial hypotension: evolution of the therapeutic and diagnostic modalities. Neurol Sci 2013; 34 (Suppl. 01) S151-S5. PubMed PMID: ISI:000332448100034.
    CrossrefPubMedSuche in Google Scholar
  • 10 Hunderfund ANL, Mokri B. Orthostatic headache without CSF leak. Neurology 2008; 71 (Suppl. 23) 1902-6.
    CrossrefPubMedSuche in Google Scholar
  • 11 Uysal S, Albayram S, Ercan TE. Spontaneous intracranial hypotension: a case report. J Child Neurol 2008; 23 (Suppl. 11) 1312-5. PubMed PMID: 18984842. Epub 2008/11/06.
    CrossrefPubMedSuche in Google Scholar
  • 12 Evan RW, Mokri B. Spontaneous intracranial hypotension resulting in coma. Headache 2002; 42 (Suppl. 02) 159-60. PubMed PMID: 12005297. Epub 2002/05/15.
    CrossrefPubMedSuche in Google Scholar
  • 13 Hong M, Shah GV, Adams KM, Turner RS, Foster NL. Spontaneous intracranial hypotension causing reversible frontotemporal dementia. Neurology 58 (Suppl. 08) 1285-7. PubMed PMID: 11971102. Epub 2002/04/24.
    PubMed
  • 14 Sharma P, Sharma A, Chacko AG. Syringomyelia in spontaneous intracranial hypotension. Case report. J Neurosurg 2001; 95 (Suppl. 05) 905-8. PubMed PMID: 11702886. Epub 2001/11/13.
    CrossrefPubMedSuche in Google Scholar
  • 15 Schievink WI, Morreale VM, Atkinson JL, Meyer FB, Piepgras DG, Ebersold MJ. Surgical treatment of spontaneous spinal cerebrospinal fluid leaks. J Neurosurg 1998; 88 (Suppl. 02) 243-6. PubMed PMID: 9452231. Epub 1998/02/06.
    CrossrefPubMedSuche in Google Scholar
  • 16 Schievink WI, Maya MM, Moser F, Tourje J, Torbati S. Frequency of spontaneous intracranial hypotension in the emergency department. J Headache Pain 2007; 8 (Suppl. 06) 325-8. PubMed PMID: 18071632. PMCID: 3476164. Epub 2007/12/12.
    CrossrefPubMedSuche in Google Scholar
  • 17 Yuh EL, Dillon WP. Intracranial hypotension and intracranial hypertension. Neuroimaging Clin N Am 2010; 20 (Suppl. 04) 597-617. PubMed PMID: 20974378. Epub 2010/10/27.
    CrossrefPubMedSuche in Google Scholar
  • 18 Bell WE, Joynt RJ, Sahs AL. Low spinal fluid pressure syndromes. Neurology 1960; 10: 512-21. PubMed PMID: 13798523. Epub 1960/05/01.
    CrossrefPubMedSuche in Google Scholar
  • 19 Farber M, Hummel F, Gerloff C, Handels H. Virtual reality simulator for the training of lumbar punctures. Methods Inf Med 2009; 48 (Suppl. 05) 493-501. PubMed PMID: 19448881. Epub 2009/05/19.
    Thieme ConnectPubMedSuche in Google Scholar
  • 20 Paldino M, Mogilner AY, Tenner MS. Intracranial hypotension syndrome: a comprehensive review. Neurosurg Focus 2003; 15 (Suppl. 06) ECP2. PubMed PMID: 15305844. Epub 2004/08/13.
    PubMedSuche in Google Scholar
  • 21 Schievink WI. Spontaneous spinal cerebrospinal fluid leaks. Cephalalgia. 2008 28. 12 PubMed PMID: ISI:000261138600015.
    PubMedSuche in Google Scholar
  • 22 Schievink WI. Spontaneous spinal cerebrospinal fluid leaks: a review. Neurosurg Focus 2000; 9 (Suppl. 01) e8. PubMed PMID: 16859269. Epub 2006/07/25.
    PubMedSuche in Google Scholar
  • 23 Wang YF, Lirng JF, Fuh JL, Hseu SS, Wang SJ. Heavily T2-weighted MR myelography vs CT myelography in spontaneous intracranial hypotension. Neurology 2009; 73 (Suppl. 22) 1892-8. PubMed PMID: 19949036. Epub 2009/12/02.
    CrossrefPubMedSuche in Google Scholar
  • 24 Yildirim MS, Kara S, Albayram MS. Algorithm for Computer Aided Diagnosis in Spontaneous Intracranial Hypotension. ICECCO 2013; 36-9. PubMed PMID: ISI:000336616500010.
    PubMedSuche in Google Scholar
  • 25 Song T, Gasparovic C, Andreasen N, Bockholt J, Jamshidi M, Lee RR. et al. A hybrid tissue segmentation approach for brain MR images. Med Biol Eng Comput 2006; 44 (Suppl. 03) 242-9. PubMed PMID: ISI:000240031900009.
    CrossrefPubMedSuche in Google Scholar
  • 26 Liew AWC, Yan H. Current methods in the automatic tissue segmentation of 3D magnetic resonance brain images. Curr Med Imaging Rev 2006; 2 (Suppl. 01) 91-103. PubMed PMID: ISI:000235845300008.
    CrossrefPubMedSuche in Google Scholar
  • 27 Suzuki H, Toriwaki J. Automatic Segmentation of Head Mri Images by Knowledge Guided Thresholding. Comput Med Imaging Graph 1991; 15 (Suppl. 04) 233-40. PubMed PMID: ISI:A1991GC89000005.
    CrossrefPubMedSuche in Google Scholar
  • 28 Kovacevic N, Lobaugh NJ, Bronskill MJ, Levine B, Feinstein A, Black SE. A robust method for extraction and automatic segmentation of brain images. Neuroimage 2002; 17 (Suppl. 03) 1087-100. PubMed PMID: ISI:000179012800001.
    CrossrefPubMedSuche in Google Scholar
  • 29 Matsumae M, Kikinis R, Morocz IA, Lorenzo AV, Sandor T, Albert MS. et al. Age-related changes in intracranial compartment volumes in normal adults assessed by magnetic resonance imaging. J Neurosurg 1996; 84 (Suppl. 06) 982-91. PubMed PMID: ISI:A1996UM58700011.
    CrossrefPubMedSuche in Google Scholar
  • 30 Brinkley JF, Rosse C. Imaging and the Human Brain Project: a review. Methods Inf Med 2002; 41 (Suppl. 04) 245-60. PubMed PMID: 12425235. Epub 2002/11/12.
    Thieme ConnectPubMedSuche in Google Scholar
  • 31 Prastawa M, Bullitt E, Moon N, Van Leemput K, Gerig G. Automatic brain tumor segmentation by subject specific modification of atlas priors. Acad Radiol 2003; 10 (Suppl. 12) 1341-8. PubMed PMID: ISI:000187063600003.
    CrossrefPubMedSuche in Google Scholar
  • 32 Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C. et al. Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain. Neuron 2002; 33 (Suppl. 03) 341-55. PubMed PMID: ISI:000173643200006.
    CrossrefPubMedSuche in Google Scholar