Advertisement

Child's Nervous System

, Volume 34, Issue 5, pp 901–910 | Cite as

Resting state signal latency predicts laterality in pediatric medically refractory temporal lobe epilepsy

  • Manish N. Shah
  • Anish Mitra
  • Manu S. Goyal
  • Abraham Z. Snyder
  • Jing Zhang
  • Joshua S. Shimony
  • David D. Limbrick
  • Marcus E. Raichle
  • Matthew D. Smyth
Original Paper

Abstract

Purpose

Temporal lobe epilepsy (TLE) affects resting state brain networks in adults. This study aims to correlate resting state functional MRI (rsMRI) signal latency in pediatric TLE patients with their laterality.

Methods

From 2006 to 2016, 26 surgical TLE patients (12 left, 14 right) with a mean age of 10.7 years (range 0.9–18) were prospectively studied. Preoperative rsMRI was obtained in patients with concordant lateralizing structural MRI, EEG, and PET studies. Standard preprocessing techniques and seed-based rsMRI analyses were performed. Additionally, the latency in rsMRI signal between each 6 mm voxel sampled was examined, compared to the global mean signal, and projected onto standard atlas space for individuals and the cohort.

Results

All but one of the 26 patients improved seizure frequency postoperatively with a mean follow-up of 2.9 years (range 0–7.7), with 21 patients seizure-free. When grouped for epileptogenic laterality, the latency map qualitatively demonstrated that the right TLE patients had a relatively early signal pattern, whereas the left TLE patients had a relatively late signal pattern compared to the global mean signal in the right temporal lobe. Quantitatively, the two groups had significantly different signal latency clusters in the bilateral temporal lobes (p < 0.001).

Conclusion

There are functional MR signal latency changes in medical refractory pediatric TLE patients. Qualitatively, signal latency in the right temporal lobe precedes the mean signal in right TLE patients and is delayed in left TLE patients. With larger confirmatory studies, preoperative rsMRI latency analysis may offer an inexpensive, noninvasive adjunct modality to lateralize pediatric TLE.

Keywords

Default mode network Functional magnetic resonance imaging Pediatric epilepsy Resting state Temporal lobe epilepsy 

Notes

Funding information

Research reported in this publication was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health under Award Number L30 HD089125 (MNS) as well as U54 HD087011 to the Intellectual and Developmental Disabilities Research Center at Washington University (JSS).

Compliance with ethical standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments.

Informed consent

Informed consent was obtained from all study participants.

Supplementary material

381_2018_3770_Fig5_ESM.gif (80 kb)
Supplementary Figure 1

Autocorrelation plot for preprocessed rsMRI data in the temporal lobes. The calculated mean autocorrelation coefficients of 3 time lags (1 TR, 2 TR, 3 TR) for averaged time series (preprocessed rsMRI data) extracted from symmetric regions of interest in the left and right temporal lobes (LTL and RTL) in both patient groups (LTLE and RTLE) show the trend that as lag increases, the autocorrelation coefficient reduces quickly to insignificant. This indicates that the effect of autocorrelation is negligible in the rsMRI temporal latency analysis. (GIF 80 kb)

381_2018_3770_MOESM2_ESM.tif (16.4 mb)
High resolution image (TIFF 16815 kb)
381_2018_3770_Fig6_ESM.gif (201 kb)
Supplementary Figure 2

Standard deviation maps. A. Mean standard deviation map for each patient with LTLE; B. Mean standard deviation map for each patient with RTLE. The standard deviation maps show that the voxel-wise mean standard deviation does not correlate with the temporal latency maps in these patients. (GIF 200 kb)

381_2018_3770_MOESM3_ESM.tif (7.2 mb)
High resolution image (TIFF 7347 kb)
381_2018_3770_MOESM1_ESM.docx (29 kb)
Supplementary Table 1 (DOCX 29 kb)

References

  1. 1.
    Gleissner U, Sassen R, Schramm J, Elger CE, Helmstaedter C (2005) Greater functional recovery after temporal lobe epilepsy surgery in children. BrainJ Neurol 128:2822–2829CrossRefGoogle Scholar
  2. 2.
    Mohamed A, Wyllie E, Ruggieri P, Kotagal P, Babb T, Hilbig A, Wylie C, Ying Z, Staugaitis S, Najm I, Bulacio J, Foldvary N, Luders H, Bingaman W (2001) Temporal lobe epilepsy due to hippocampal sclerosis in pediatric candidates for epilepsy surgery. Neurology 56:1643–1649CrossRefPubMedGoogle Scholar
  3. 3.
    Smyth MD, Limbrick DD Jr, Ojemann JG, Zempel J, Robinson S, O'Brien DF, Saneto RP, Goyal M, Appleton RE, Mangano FT, Park TS (2007) Outcome following surgery for temporal lobe epilepsy with hippocampal involvement in preadolescent children: emphasis on mesial temporal sclerosis. J Neurosurg 106:205–210PubMedGoogle Scholar
  4. 4.
    Camfield CS, Camfield PR, Gordon K, Wirrell E, Dooley JM (1996) Incidence of epilepsy in childhood and adolescence: a population-based study in Nova Scotia from 1977 to 1985. Epilepsia 37:19–23CrossRefPubMedGoogle Scholar
  5. 5.
    Cross JH, Jayakar P, Nordli D, Delalande O, Duchowny M, Wieser HG, Guerrini R, Mathern GW, International League against Epilepsy SfPES, Commissions of N, Paediatrics (2006) Proposed criteria for referral and evaluation of children for epilepsy surgery: recommendations of the Subcommission for Pediatric Epilepsy Surgery. Epilepsia 47:952–959CrossRefPubMedGoogle Scholar
  6. 6.
    Boshuisen K, van Schooneveld MM, Uiterwaal CS, Cross JH, Harrison S, Polster T, Daehn M, Djimjadi S, Yalnizoglu D, Turanli G, Sassen R, Hoppe C, Kuczaty S, Barba C, Kahane P, Schubert-Bast S, Reuner G, Bast T, Strobl K, Mayer H, de Saint-Martin A, Seegmuller C, Laurent A, Arzimanoglou A, Braun KP, TimeToStop cognitive outcome study group (2015) Intelligence quotient improves after antiepileptic drug withdrawal following pediatric epilepsy surgery. Ann Neurol 78:104–114CrossRefPubMedGoogle Scholar
  7. 7.
    Sugano H, Arai H (2015) Epilepsy surgery for pediatric epilepsy: optimal timing of surgical intervention. Neurol Med Chir (Tokyo) 55:399–406CrossRefGoogle Scholar
  8. 8.
    Cataldi M, Avoli M, de Villers-Sidani E (2013) Resting state networks in temporal lobe epilepsy. Epilepsia 54:2048–2059CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Constable RT, Scheinost D, Finn ES, Shen X, Hampson M, Winstanley FS, Spencer DD, Papademetris X (2013) Potential use and challenges of functional connectivity mapping in intractable epilepsy. Front Neurol 4:39CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Fox MD, Greicius M (2010) Clinical applications of resting state functional connectivity. Front Syst Neurosci 4:19PubMedPubMedCentralGoogle Scholar
  11. 11.
    Kokkonen SM, Nikkinen J, Remes J, Kantola J, Starck T, Haapea M, Tuominen J, Tervonen O, Kiviniemi V (2009) Preoperative localization of the sensorimotor area using independent component analysis of resting-state fMRI. Magn Reson Imaging 27:733–740CrossRefPubMedGoogle Scholar
  12. 12.
    Liu H, Buckner RL, Talukdar T, Tanaka N, Madsen JR, Stufflebeam SM (2009) Task-free presurgical mapping using functional magnetic resonance imaging intrinsic activity. J Neurosurg 111:746–754CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Hacker CD, Laumann TO, Szrama NP, Baldassarre A, Snyder AZ, Leuthardt EC, Corbetta M (2013) Resting state network estimation in individual subjects. NeuroImage 82:616–633CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Shannon BJ, Raichle ME, Snyder AZ, Fair DA, Mills KL, Zhang D, Bache K, Calhoun VD, Nigg JT, Nagel BJ, Stevens AA, Kiehl KA (2011) Premotor functional connectivity predicts impulsivity in juvenile offenders. Proc Natl Acad Sci U S A 108:11241–11245CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Lustig C, Snyder AZ, Bhakta M, O'Brien KC, McAvoy M, Raichle ME, Morris JC, Buckner RL (2003) Functional deactivations: change with age and dementia of the Alzheimer type. Proc Natl Acad Sci U S A 100:14504–14509CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Sheline YI, Barch DM, Price JL, Rundle MM, Vaishnavi SN, Snyder AZ, Mintun MA, Wang S, Coalson RS, Raichle ME (2009) The default mode network and self-referential processes in depression. Proc Natl Acad Sci U S A 106:1942–1947CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL (2001) A default mode of brain function. Proc Natl Acad Sci U S A 98:676–682CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Snyder AZ, Raichle ME (2012) A brief history of the resting state: the Washington University perspective. NeuroImage 62:902–910CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Broicher SD, Frings L, Huppertz HJ, Grunwald T, Kurthen M, Kramer G, Jokeit H (2012) Alterations in functional connectivity of the amygdala in unilateral mesial temporal lobe epilepsy. J Neurol 259:2546–2554CrossRefPubMedGoogle Scholar
  20. 20.
    Haneef Z, Lenartowicz A, Yeh HJ, Engel J Jr, Stern JM (2012) Effect of lateralized temporal lobe epilepsy on the default mode network. Epilepsy Behav 25:350–357CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Liao W, Zhang Z, Pan Z, Mantini D, Ding J, Duan X, Luo C, Wang Z, Tan Q, Lu G, Chen H (2011) Default mode network abnormalities in mesial temporal lobe epilepsy: a study combining fMRI and DTI. Hum Brain Mapp 32:883–895CrossRefPubMedGoogle Scholar
  22. 22.
    Luo C, Qiu C, Guo Z, Fang J, Li Q, Lei X, Xia Y, Lai Y, Gong Q, Zhou D, Yao D (2011) Disrupted functional brain connectivity in partial epilepsy: a resting-state fMRI study. PLoS One 7:e28196CrossRefPubMedGoogle Scholar
  23. 23.
    Stufflebeam SM, Liu H, Sepulcre J, Tanaka N, Buckner RL, Madsen JR (2011) Localization of focal epileptic discharges using functional connectivity magnetic resonance imaging. J Neurosurg 114:1693–1697CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Waites AB, Briellmann RS, Saling MM, Abbott DF, Jackson GD (2006) Functional connectivity networks are disrupted in left temporal lobe epilepsy. Ann Neurol 59:335–343CrossRefPubMedGoogle Scholar
  25. 25.
    Luo C, Li Q, Lai Y, Xia Y, Qin Y, Liao W, Li S, Zhou D, Yao D, Gong Q (2011) Altered functional connectivity in default mode network in absence epilepsy: a resting-state fMRI study. Hum Brain Mapp 32:438–449CrossRefPubMedGoogle Scholar
  26. 26.
    Pizoli CE, Shah MN, Snyder AZ, Shimony JS, Limbrick DD, Raichle ME, Schlaggar BL, Smyth MD (2011) Resting-state activity in development and maintenance of normal brain function. Proc Natl Acad Sci U S A 108:11638–11643CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Bettus G, Bartolomei F, Confort-Gouny S, Guedj E, Chauvel P, Cozzone PJ, Ranjeva JP, Guye M (2010) Role of resting state functional connectivity MRI in presurgical investigation of mesial temporal lobe epilepsy. J Neurol Neurosurg Psychiatry 81:1147–1154CrossRefPubMedGoogle Scholar
  28. 28.
    Bettus G, Guedj E, Joyeux F, Confort-Gouny S, Soulier E, Laguitton V, Cozzone PJ, Chauvel P, Ranjeva JP, Bartolomei F, Guye M (2009) Decreased basal fMRI functional connectivity in epileptogenic networks and contralateral compensatory mechanisms. Hum Brain Mapp 30:1580–1591CrossRefPubMedGoogle Scholar
  29. 29.
    James GA, Tripathi SP, Ojemann JG, Gross RE, Drane DL (2013) Diminished default mode network recruitment of the hippocampus and parahippocampus in temporal lobe epilepsy. J Neurosurg 119:288–300CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Wu DH, Lewin JS, Duerk JL (1997) Inadequacy of motion correction algorithms in functional MRI: role of susceptibility-induced artifacts. J Magn Reson Imaging 7:365–370CrossRefPubMedGoogle Scholar
  31. 31.
    Mitra A, Snyder AZ, Hacker CD, Raichle ME (2014) Lag structure in resting state fMRI. J Neurophysiol 111:2374–2391CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Mitra A, Snyder AZ, Constantino JN, Raichle ME (2015) The lag structure of intrinsic activity is focally altered in high functioning adults with autism. Cereb CortexGoogle Scholar
  33. 33.
    Amemiya S, Kunimatsu A, Saito N, Ohtomo K (2014) Cerebral hemodynamic impairment: assessment with resting-state functional MR imaging. Radiology 270:548–555CrossRefPubMedGoogle Scholar
  34. 34.
    Lv Y, Margulies DS, Cameron Craddock R, Long X, Winter B, Gierhake D, Endres M, Villringer K, Fiebach J, Villringer A (2013) Identifying the perfusion deficit in acute stroke with resting-state functional magnetic resonance imaging. Ann Neurol 73:136–140CrossRefPubMedGoogle Scholar
  35. 35.
    Xu Q, Zhang Z, Liao W, Xiang L, Yang F, Wang Z, Chen G, Tan Q, Jiao Q, Lu G (2014) Time-shift homotopic connectivity in mesial temporal lobe epilepsy. AJNR Am J Neuroradiol 35:1746–1752CrossRefPubMedGoogle Scholar
  36. 36.
    Fox MD, Zhang D, Snyder AZ, Raichle ME (2009) The global signal and observed anticorrelated resting state brain networks. J Neurophysiol 101:3270–3283CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Buckner RL, Head D, Parker J, Fotenos AF, Marcus D, Morris JC, Snyder AZ (2004) A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume. NeuroImage 23:724–738CrossRefPubMedGoogle Scholar
  38. 38.
    Fonov V, Evans AC, Botteron K, Almli CR, McKinstry RC, Collins DL, Brain Development Cooperative G (2011) Unbiased average age-appropriate atlases for pediatric studies. NeuroImage 54:313–327CrossRefPubMedGoogle Scholar
  39. 39.
    Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC, Raichle ME (2005) The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A 102:9673–9678CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Shannon BJ, Dosenbach RA, Su Y, Vlassenko AG, Larson-Prior LJ, Nolan TS, Snyder AZ, Raichle ME (2013) Morning-evening variation in human brain metabolism and memory circuits. J Neurophysiol 109:1444–1456CrossRefPubMedGoogle Scholar
  41. 41.
    Freitag H, Tuxhorn I (2005) Cognitive function in preschool children after epilepsy surgery: rationale for early intervention. Epilepsia 46:561–567CrossRefPubMedGoogle Scholar
  42. 42.
    Laufs H, Hamandi K, Salek-Haddadi A, Kleinschmidt AK, Duncan JS, Lemieux L (2007) Temporal lobe interictal epileptic discharges affect cerebral activity in “default mode” brain regions. Hum Brain Mapp 28:1023–1032CrossRefPubMedPubMedCentralGoogle Scholar
  43. 43.
    Zhang Z, Lu G, Zhong Y, Tan Q, Chen H, Liao W, Tian L, Li Z, Shi J, Liu Y (2010) fMRI study of mesial temporal lobe epilepsy using amplitude of low-frequency fluctuation analysis. Hum Brain Mapp 31:1851–1861CrossRefPubMedGoogle Scholar
  44. 44.
    Zhang Z, Liao W, Wang Z, Xu Q, Yang F, Mantini D, Jiao Q, Tian L, Liu Y, Lu G (2014) Epileptic discharges specifically affect intrinsic connectivity networks during absence seizures. J Neurol Sci 336:138–145CrossRefPubMedGoogle Scholar
  45. 45.
    Arya R, Tenney JR, Horn PS, Greiner HM, Holland KD, Leach JL, Gelfand MJ, Rozhkov L, Fujiwara H, Rose DF, Franz DN, Mangano FT (2015) Long-term outcomes of resective epilepsy surgery after invasive presurgical evaluation in children with tuberous sclerosis complex and bilateral multiple lesions. J Neurosurg Pediatr 15:26–33CrossRefPubMedGoogle Scholar
  46. 46.
    Broyd SJ, Demanuele C, Debener S, Helps SK, James CJ, Sonuga-Barke EJ (2009) Default-mode brain dysfunction in mental disorders: a systematic review. Neurosci Biobehav Rev 33:279–296CrossRefPubMedGoogle Scholar
  47. 47.
    Buckner RL, Vincent JL (2007) Unrest at rest: default activity and spontaneous network correlations. NeuroImage 37:1091–1096 discussion 1097-1099CrossRefPubMedGoogle Scholar
  48. 48.
    Raichle ME, Snyder AZ (2007) A default mode of brain function: a brief history of an evolving idea. NeuroImage 37:1083–1090 discussion 1097-1089CrossRefPubMedGoogle Scholar
  49. 49.
    Radhakrishnan K, So EL, Silbert PL, Jack CR Jr, Cascino GD, Sharbrough FW, O'Brien PC (1998) Predictors of outcome of anterior temporal lobectomy for intractable epilepsy: a multivariate study. Neurology 51:465–471CrossRefPubMedGoogle Scholar
  50. 50.
    Baumgartner C, Pataraia E, Lindinger G, Deecke L (2000) Neuromagnetic recordings in temporal lobe epilepsy. J Clin Neurophysiol 17:177–189CrossRefPubMedGoogle Scholar
  51. 51.
    Ho SS, Berkovic SF, Berlangieri SU, Newton MR, Egan GF, Tochon-Danguy HJ, McKay WJ (1995) Comparison of ictal SPECT and interictal PET in the presurgical evaluation of temporal lobe epilepsy. Ann Neurol 37:738–745CrossRefPubMedGoogle Scholar
  52. 52.
    Salanova V, Markand O, Worth R, Smith R, Wellman H, Hutchins G, Park H, Ghetti B, Azzarelli B (1998) FDG-PET and MRI in temporal lobe epilepsy: relationship to febrile seizures, hippocampal sclerosis and outcome. Acta Neurol Scand 97:146–153CrossRefPubMedGoogle Scholar
  53. 53.
    Ioannidis JP, Trikalinos TA (2005) Early extreme contradictory estimates may appear in published research: the Proteus phenomenon in molecular genetics research and randomized trials. J Clin Epidemiol 58:543–549CrossRefPubMedGoogle Scholar
  54. 54.
    Worsley KJ, Chen JI, Lerch J, Evans AC (2005) Comparing functional connectivity via thresholding correlations and singular value decomposition. Philos Trans R Soc Lond Ser B Biol Sci 360:913–920CrossRefGoogle Scholar
  55. 55.
    Osipowicz K, Sperling MR, Sharan AD, Tracy JI (2015) Functional MRI, resting state fMRI, and DTI for predicting verbal fluency outcome following resective surgery for temporal lobe epilepsy. J Neurosurg 1–9Google Scholar
  56. 56.
    Spader HS, Ellermeier A, O'Muircheartaigh J, Dean DC 3rd, Dirks H, Boxerman JL, Cosgrove GR, Deoni SC (2013) Advances in myelin imaging with potential clinical application to pediatric imaging. Neurosurg Focus 34:E9CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Manish N. Shah
    • 1
  • Anish Mitra
    • 3
  • Manu S. Goyal
    • 3
  • Abraham Z. Snyder
    • 3
    • 4
  • Jing Zhang
    • 1
  • Joshua S. Shimony
    • 3
  • David D. Limbrick
    • 2
  • Marcus E. Raichle
    • 3
    • 4
    • 5
    • 6
  • Matthew D. Smyth
    • 2
  1. 1.Departments of Pediatric Surgery and NeurosurgeryMcGovern Medical School at UTHealthHoustonUSA
  2. 2.Department of Neurological Surgery, St. Louis Children’s HospitalWashington University School of MedicineSt. LouisUSA
  3. 3.Mallinckrodt Institute of RadiologyWashington University School of MedicineSt. LouisUSA
  4. 4.Department of NeurologyWashington University School of MedicineSt. LouisUSA
  5. 5.Department of Biomedical EngineeringWashington University School of MedicineSt. LouisUSA
  6. 6.Department of Anatomy and NeurobiologyWashington University School of MedicineSt. LouisUSA

Personalised recommendations