Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Prediction of recurrence in meningiomas after surgical treatment

A quantitative approach

  • 23 Accesses

  • 94 Citations


The prognostic significance of nuclear count, nuclear area fraction, and mean nuclear area estimated by automatic image analysis was evaluated in benign meningiomas. One hundred thirty-two meningiomas without recurrences, 39 meningiomas that recurred, and 40 first recurrences were examined. The tumors were classified according to age and eex of patients, localization, and histology; and the correlation between these parameters and the recurrence rate was assessed.

The nuclear counts were identical in paraffin sections from meningiomas without recurrences (6.1 nuclei per 1,000 μm2) and in meningiomas that recurred (6.4 nuclei per 1,000 μm2). The cell count in the recurrences (7.4 nuclei per 1,000 μm2) was higher than in the primary tumors. The same relationship was found for the nuclear area fractions, which were identical in primary meningiomas without recurrences and in meningiomas that recurred. The nuclear area fraction was increased in recurrences. The mean nuclear areas were identical in all groups. The histological type was of little significance in prediction of recurrence rate, although bone invasion and necrosis were of some significance. We found a higher recurrence rate in parasagittal meningiomas. Meningiomas that recurred appeared in a younger age group than other meningiomas, and the recurrence rate was higher for males than for females.

This is a preview of subscription content, log in to check access.

We’re sorry, something doesn't seem to be working properly.

Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.


  1. Adegbite AB, Khan MI, Paine KWE, Tan LK (1983) The recurrence of intracranial meningiomas after surgical treatment. J Neurosurg 58:51–56

  2. Crompton MR, Gautier-Smith PC (1970) The prediction of recurrence in meningiomas. J Neurol Neurosurg Psychiatry 33:80–87

  3. Henschen F (1955) Tumoren des Zentralnervensystems und seiner Hüllen. In: Lubarsch O, Henke F, Rössle R (Hrsg) Handbuch der speziellen pathologischen Anatomie und Histologie. Springer, Berlin Göttingen Heidelberg, pp 441–496

  4. Jellinger K, Slowik F (1975) Histological subtypes and prognostic problems in meningiomas. J Neurol 208:279–298

  5. Jänisch W, Güthert H, Schreiber D (1976) Pathologie der Tumoren des Zentralnervensystems. Fischer Jena

  6. Laursen H, Diemer NH (1980) Capillary size, density and ultrastructure in brain of rats with urease-induced hyperammoniaemia. Acta Neurol Scand 62:103–115

  7. MacCarty CS, Taylor WF (1979) Intracranial meningiomas: Experiences at the Mayo Clinic. Neurol Med Chir (Tokyo) 19:569–574

  8. Melamed S, Sahar A, Beller AJ (1979) The recurrence of intracranial meningiomas. Neurochirurgia 22:47–51

  9. Rocher A (1979) Beitrag zur Kenntnis der Meningioma-Rezidive. Thesis, Pathologisches Institut der Universität Köln

  10. Rubinstein LJ (1972) Tumors of the central nervous system. Armed Forces Institute of Pathology, Stanford, California

  11. Simpson D (1957) The recurrence of intracranial meningiomas after surgical treatment. J Neurol Neurosurg Psychiatry 20:22–39

  12. Skullerud K, Löken AC (1974) The prognosis in meningiomas. Acta Neuropathol (Berl) 29:337–344

  13. Tamura M, Kawafuchi J, Inoue H, Takada F (1979) Prognosis in meningioma after surgical treatment. Neurol Med Chir (Tokyo) 19:411–419

Download references

Author information

Additional information

Supported by grant no. 512-10141 from the Danish Medical Research Council

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Christensen, D., Laursen, H. & Klinken, L. Prediction of recurrence in meningiomas after surgical treatment. Acta Neuropathol 61, 130–134 (1983). https://doi.org/10.1007/BF00697392

Download citation

Key words

  • Meningiomas
  • Recurrence rate
  • Automatic image analysis
  • Histology