Pineal parenchymal tumor of intermediate differentiation with cytologic pleomorphism

Atsushi Sasaki1, Keishi Horiguchi, Yoichi Nakazato

  • 1Department of Human Pathology, Gunma University Graduate School of Medicine, Maebashi, Gunma 371-8511, Japan. achie@med.gunma-u.ac.jp

Insights

This case study highlights a pineal parenchymal tumor diagnosed via endoscopic biopsy. The findings demonstrate that significant cell variation can occur in these intermediate-grade tumors.

Area of Science:

  • Neuropathology
  • Oncology
  • Neuroimaging

Background:

  • Pineal parenchymal tumors (PPTs) are rare neoplasms arising from the pineal gland.
  • Accurate diagnosis and classification are crucial for patient management and prognosis.
  • Intermediate-grade PPTs can exhibit diverse histological features, posing diagnostic challenges.

Purpose of the Study:

  • To report a case of pineal parenchymal tumor with unusual cytologic pleomorphism.
  • To characterize the histological, immunohistochemical, and ultrastructural features of this tumor.
  • To emphasize the potential for significant cellular atypia in intermediate PPTs.

Main Methods:

  • Magnetic Resonance Imaging (MRI) for initial detection and characterization.
  • Endoscopic biopsy for tissue acquisition.
  • Routine histology, immunohistochemistry (IHC), and electron microscopy (EM) for detailed tumor analysis.

Main Results:

  • MRI revealed a small, unhomogeneously enhancing lesion in the pineal region.
  • Histology showed a highly cellular tumor with small cells, nuclear atypia, and pleomorphism including giant cells.
  • Immunohistochemistry confirmed neural and pinealocyte markers, with a high MIB-1 labeling index (6.3%).
  • Electron microscopy demonstrated features of pinealocytic differentiation.

Conclusions:

  • The tumor was confirmed as a pineal parenchymal tumor of intermediate differentiation.
  • This case illustrates that marked cytologic pleomorphism can be a feature of intermediate-grade PPTs.
  • Comprehensive diagnostic methods are essential for accurate PPT classification.