Postoperative diffusion-weighted imaging and neurological outcome after convexity meningioma resection

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  • 1 Departments of Neurological Surgery and
  • | 2 Radiology and Biomedical Imaging, University of California, San Francisco, California
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OBJECTIVE

Convexity meningiomas are commonly managed with resection. Motor outcomes and predictors of new deficits after surgery are poorly studied. The objective of this study was to determine whether postoperative diffusion-weighted imaging (DWI) was associated with neurological deficits after convexity meningioma resection and to identify the risk factors for postoperative DWI restriction.

METHODS

A retrospective review of patients who had undergone convexity meningioma resection from 2014 to 2018 was performed. Univariate and multivariate logistic regressions were performed to identify variables associated with postoperative neurological deficits and a DWI signal. The amount of postoperative DWI signal was measured and was correlated with low apparent diffusion coefficient maps to confirm ischemic injury.

RESULTS

The authors identified 122 patients who had undergone a total of 125 operations for convexity meningiomas. The median age at surgery was 57 years, and 70% of the patients were female. The median follow-up was 26 months. The WHO grade was I in 62% of cases, II in 36%, and III in 2%. The most common preoperative deficits were seizures (24%), extremity weakness/paralysis (16%), cognitive/language/memory impairment (16%), and focal neurological deficit (16%). Following resection, 89% of cases had no residual deficit. Postoperative DWI showed punctate or no diffusion restriction in 78% of cases and restriction > 1 cm in 22% of cases. An immediate postoperative neurological deficit was present in 14 patients (11%), but only 8 patients (7%) had a deficit at 3 months postoperatively. Univariate analysis identified DWI signal > 1 cm (p < 0.0001), tumor diameter (p < 0.0001), preoperative motor deficit (p = 0.0043), older age (p = 0.0113), and preoperative embolization (p = 0.0171) as risk factors for an immediate postoperative deficit, whereas DWI signal > 1 cm (p < 0.0001), tumor size (p < 0.0001), and older age (p = 0.0181) were risk factors for deficits lasting more than 3 months postoperatively. Multivariate analysis revealed a DWI signal > 1 cm to be the only significant risk factor for deficits at 3 months postoperatively (OR 32.42, 95% CI 3.3–320.1, p = 0.0002). Further, estimated blood loss (OR 1.4 per 100 ml increase, 95% CI 1.1–1.7, p < 0.0001), older age (OR 1.1 per year older, 95% CI 1.0–1.1, p = 0.0009), middle third location in the sagittal plane (OR 16.9, 95% CI 1.3–216.9, p = 0.0026), and preoperative peritumoral edema (OR 4.6, 95% CI 1.2–17.7, p = 0.0249) were significantly associated with a postoperative DWI signal > 1 cm.

CONCLUSIONS

A DWI signal > 1 cm is significantly associated with postoperative neurological deficits, both immediate and long-lasting. Greater estimated blood loss, older age, tumor location over the motor strip, and preoperative peritumoral edema increase the risk of having a postoperative DWI signal > 1 cm, reflective of perilesional ischemia. Most immediate postoperative deficits will improve over time. These data are valuable when preoperatively communicating with patients about the risks of surgery and when postoperatively discussing prognosis after a deficit occurs.

ABBREVIATIONS

ADC = apparent diffusion coefficient; DWI = diffusion-weighted imaging; EBL = estimated blood loss.

Illustration from Kim et al. (pp 1164–1172). Copyright Eui Hyun Kim. Published with permission.

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  • 1

    Ostrom QT, Cioffi G, Gittleman H, et al. CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2012-2016. Neuro Oncol. 2019;21(suppl 5):v1v100.

    • Search Google Scholar
    • Export Citation
  • 2

    Wiemels J, Wrensch M, Claus EB. Epidemiology and etiology of meningioma. J Neurooncol. 2010;99(3):307314.

  • 3

    Zada G, Başkaya MK, Shah MV. Introduction: Surgical management of skull base meningiomas. Neurosurg Focus. 2017;43(VideoSuppl2):Intro.

  • 4

    Newman SA. Meningiomas: a quest for the optimum therapy. J Neurosurg. 1994;80(2):191194.

  • 5

    Sanai N, Sughrue ME, Shangari G, et al. Risk profile associated with convexity meningioma resection in the modern neurosurgical era. J Neurosurg. 2010;112(5):913919.

    • Search Google Scholar
    • Export Citation
  • 6

    Liu Y, Chotai S, Chen M, et al. Preoperative radiologic classification of convexity meningioma to predict the survival and aggressive meningioma behavior. PLoS One. 2015;10(3):e0118908.

    • Search Google Scholar
    • Export Citation
  • 7

    Morokoff AP, Zauberman J, Black PM. Surgery for convexity meningiomas. Neurosurgery. 2008;63(3):427434.

  • 8

    Magill ST, Dalle Ore CL, Diaz MA, et al. Surgical outcomes after reoperation for recurrent non–skull base meningiomas. J Neurosurg. 2019;131:11791187.

    • Search Google Scholar
    • Export Citation
  • 9

    Li TQ, Chen ZG, Hindmarsh T. Diffusion-weighted MR imaging of acute cerebral ischemia. Acta Radiol. 1998;39(5):460473.

  • 10

    Burke JF, Han SJ, Han JH, McDermott MW. Two-part parasagittal craniotomy: technical note. Cureus. 2014;6(8):e193.

  • 11

    von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Int J Surg. 2014;12(12):14951499.

    • Search Google Scholar
    • Export Citation
  • 12

    Morin O, Chen WC, Nassiri F, et al. Integrated models incorporating radiologic and radiomic features predict meningioma grade, local failure, and overall survival. Neurooncol Adv. 2019;1(1):vdz011.

    • Search Google Scholar
    • Export Citation
  • 13

    Le Bihan D, Breton E, Lallemand D, et al. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology. 1986;161(2):401407.

    • Search Google Scholar
    • Export Citation
  • 14

    Le Bihan D, Breton E, Lallemand D, et al. Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology. 1988;168(2):497505.

    • Search Google Scholar
    • Export Citation
  • 15

    Marks MP, de Crespigny A, Lentz D, et al. Acute and chronic stroke: navigated spin-echo diffusion-weighted MR imaging. Radiology. 1996;199(2):403408.

    • Search Google Scholar
    • Export Citation
  • 16

    Sorensen AG, Buonanno FS, Gonzalez RG, et al. Hyperacute stroke: evaluation with combined multisection diffusion-weighted and hemodynamically weighted echo-planar MR imaging. Radiology. 1996;199(2):391401.

    • Search Google Scholar
    • Export Citation
  • 17

    Warach S, Gaa J, Siewert B, et al. Acute human stroke studied by whole brain echo planar diffusion-weighted magnetic resonance imaging. Ann Neurol. 1995;37(2):231241.

    • Search Google Scholar
    • Export Citation
  • 18

    Ko C-C, Lim S-W, Chen T-Y, et al. Prediction of progression in skull base meningiomas: additional benefits of apparent diffusion coefficient value. J Neurooncol. 2018;138(1):6371.

    • Search Google Scholar
    • Export Citation
  • 19

    Ko C-C, Chen T-Y, Lim S-W, et al. Prediction of recurrence in parasagittal and parafalcine meningiomas: added value of diffusion-weighted magnetic resonance imaging. World Neurosurg. 2019;124:e470e479.

    • Search Google Scholar
    • Export Citation
  • 20

    Hwang WL, Marciscano AE, Niemierko A, et al. Imaging and extent of surgical resection predict risk of meningioma recurrence better than WHO histopathological grade. Neuro Oncol. 2016;18(6):863872.

    • Search Google Scholar
    • Export Citation
  • 21

    Nakamizo A, Inamura T, Yamaguchi S, et al. Diffusion-weighted imaging predicts postoperative persistence in meningioma patients with peritumoural abnormalities on magnetic resonance imaging. J Clin Neurosci. 2003;10(5):589593.

    • Search Google Scholar
    • Export Citation
  • 22

    Filippi CG, Edgar MA, Uluğ AM, et al. Appearance of meningiomas on diffusion-weighted images: correlating diffusion constants with histopathologic findings. AJNR Am J Neuroradiol. 2001;22(1):6572.

    • Search Google Scholar
    • Export Citation
  • 23

    Toh C-H, Castillo M, Wong AM-C, et al. Differentiation between classic and atypical meningiomas with use of diffusion tensor imaging. AJNR Am J Neuroradiol. 2008;29(9):16301635.

    • Search Google Scholar
    • Export Citation
  • 24

    Watanabe Y, Yamasaki F, Kajiwara Y, et al. Preoperative histological grading of meningiomas using apparent diffusion coefficient at 3T MRI. Eur J Radiol. 2013;82(4):658663.

    • Search Google Scholar
    • Export Citation
  • 25

    Elzarief AA, Ibrahim MF. Long-term follow-up of motor function deterioration following microsurgical resection of middle third parasagittal and falx meningioma. Egypt J Neurol Psychiat Neurosurg. 2018;54(1):9.

    • Search Google Scholar
    • Export Citation
  • 26

    Ottenhausen M, Rumalla K, Younus I, et al. Predictors of postoperative motor function in rolandic meningiomas. J Neurosurg. 2019;130:12831288.

    • Search Google Scholar
    • Export Citation
  • 27

    Zoia C, Bongetta D, Guerrini F, et al. Outcome of elderly patients undergoing intracranial meningioma resection: a single center experience. J Neurosurg Sci. Published online May 28, 2018. doi:10.23736/S0390-5616.18.04333-3

    • Search Google Scholar
    • Export Citation
  • 28

    Dobran M, Marini A, Nasi D, et al. Surgical treatment and outcome in patients over 80 years old with intracranial meningioma. Clin Neurol Neurosurg. 2018;167:173176.

    • Search Google Scholar
    • Export Citation
  • 29

    Loewenstern J, Aggarwal A, Pain M, et al. Peritumoral edema relative to meningioma size predicts functional outcomes after resection in older patients. Oper Neurosurg (Hagerstown). 2019;16(3):281291.

    • Search Google Scholar
    • Export Citation
  • 30

    Liouta E, Koutsarnakis C, Liakos F, Stranjalis G. Effects of intracranial meningioma location, size, and surgery on neurocognitive functions: a 3-year prospective study. J Neurosurg. 2016;124(6):15781584.

    • Search Google Scholar
    • Export Citation

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