Skip to main content
SpringerLink
Log in

Apparent diffusion coefficient and pituitary macroadenomas: pre-operative assessment of tumor atypia

  • Published:
Pituitary Aims and scope Submit manuscript

Abstract

Rationale and objectives

Pituitary macroadenomas are predominantly benign intracranial neoplasms that can be locally aggressive with invasion of adjacent structures. Biomarkers of aggressive behavior have been identified in the pathology literature, including the proliferative marker MIB-1. In the radiology literature, diffusion weighted imaging and low ADC values provide similar markers of aggressive behavior in brain tumors. The purpose of this study was to determine if there is a correlation between ADC and MIB-1 in pituitary macroadenomas.

Materials and methods

A retrospective review of diffusion imaging and immunohistochemical characteristics of pituitary macroadenomas was performed. The ADC ratio and specimen Ki-67 (MIB-1) indices were measured. Linear regression analysis of normalized ADC values and MIB-1 indices was used to compare these parameters.

Results

There were 17 patients with available ADC maps and MIB-1 indices. Local invasion was confirmed by imaging and intraoperative visualization in 11 patients. The mean ADC ratio for the invasive group was 0.68, with a mean MIB-1 index of 2.21 %. In the noninvasive group, the mean ADC ratio was 1.05, with a mean MIB-1 index of 0.9 %. Linear regression analysis of normalized ADC values versus MIB-1 demonstrates a negative correlation, with a linear slope significantly different from zero (p = 0.003, correlation coefficient of 0.77, and r squared = 0.59).

Conclusion

We determine a strong correlation of low ADC values and MIB-1, demonstrating the potential of diffusion imaging as a possible biomarker for atypical, proliferative adenomas, which may ultimately affect the surgical approach and postoperative management.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Asa SL, Ezzat S (1998) The cytogenesis and pathogenesis of pituitary adenomas. Endocr Rev 19:798–827

    CAS  PubMed  Google Scholar 

  2. Ezzat S, Asa SL, Couldwell WT et al (2004) The prevalence of pituitary adenomas: a systemic review. Cancer 101:613–619

    Article  PubMed  Google Scholar 

  3. Magagna-Poveda A, Leske H, Schmid C et al (2013) Expression of somatostatin receptors, angiogenesis and proliferation markers in pituitary adenomas: an immunohistochemical study with diagnostic and therapeutic implications. Swiss Med Wkly 143:1–11

    Google Scholar 

  4. Ironside JW (2003) Pituitary gland pathology. J Clin Pathol 56:561–568

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Asa SL (2008) Practical pituitary pathology: what does the pathologist need to know. Arch Pathol Lab Med 132:1231–1240

    PubMed  Google Scholar 

  6. Zada G, Woodmanse WW, Ramkissoon S et al (2011) Atypical pituitary adenomas: incidence, clinical characteristics, and implications. J Neurosurg 114:336–344

    Article  PubMed  Google Scholar 

  7. Osamura RY, Kajiya H, Takei M et al (2008) Pathology of the human pituitary adenomas. Histochem Cell Biol 130:495–507

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Saeger W, Ludecke DK, Buchfelder M et al (2007) Pathohistological classification of pituitary tumors: 10 years of experience with the German Pituitary Tumor Registry. Eur J Endocrinol 156:203–216

    Article  CAS  PubMed  Google Scholar 

  9. Mete O, Ezzat S, Asa SL (2012) Biomarkers of aggressive pituitary adenomas. J Mol Endocrinol 49:69–78

    Article  Google Scholar 

  10. Paek KI, Kim SH, Song SH, Choi SW et al (2005) Clinical significance of Ki-67 labeling index in pituitary macroadenoma. J Korean Med Sci 20:489–494

    Article  PubMed  PubMed Central  Google Scholar 

  11. Ginat DT, Mangla R, Yeaney G et al (2010) Correlation of diffusion and perfusion MRI with Ki-67 in high grade meningiomas. AJR 195:1391–1395

    Article  PubMed  Google Scholar 

  12. Calvar JA, Meli FJ, Romero C, Calcagno ML et al (2005) Characterization of brain tumors by MRS, DWI and Ki-67 labeling index. J Neurooncol 72:273–280

    Article  CAS  PubMed  Google Scholar 

  13. Matsuyama J (2012) Ki-67 expression for predicting progression of postoperative residual pituitary adenomas: correlations with clinical variables. Neurol Med Chir 52:563–569

    Article  Google Scholar 

  14. Mohamed FF, Abouhashem S (2013) Diagnostic value of apparent diffusion coefficient (ADC) in assessment of pituitary macroadenoma consistency. Egypt J Radiol Nucl Med 44:617–624

    Article  Google Scholar 

  15. Mahmoud OM, Tominaga A, Amatya VJ, Ohtaki M et al (2011) Role of PROPELLER diffusion weighted imaging and apparent diffusion coefficient in the evaluation of pituitary adenomas. Eur J Radiol 80:412–417

    Article  PubMed  Google Scholar 

  16. Sizuki C, Maeda M, Hori K et al (2007) Apparent diffusion coefficient of pituitary macroadenoma evaluated with line scan diffusion weighted imaging. J Neuroradiol 34:228–235

    Article  Google Scholar 

  17. Boxerman JL, Rogg JM, Donahue JE, Machan JT et al (2010) Preoperative MRI evaluation of pituitary macroadenoma: imaging features predictive of successful trans-sphenoidal surgery. AJR 195:720–728

    Article  PubMed  Google Scholar 

  18. Pierallini A, Caramia F, Falcone C et al (2006) Pituitary macroadenomas: preoperative evaluation of consistency with diffusion weighted MR imaging- initial experience. Radiology 239:223–231

    Article  PubMed  Google Scholar 

  19. Micko ASG, Wohrer A, Wolfsberger S, Knosp E (2015) Invasion of the cavernous sinus space in pituitary adenomas: endoscopic verification and its correlation with MRI-based classification. JNS 122:803–811

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Radiology, University of California San Francisco, 505 Parnassus Avenue, M-391, San Francisco, CA, 94143-0628, USA

    Benita Tamrazi, Mariam Aboian & Christine M. Glastonbury

  2. Department of Pathology, University of California San Francisco, 505 Parnassus Avenue, M-391, San Francisco, CA, 94143-0628, USA

    Melike Pekmezci & Tarik Tihan

  3. Department of Radiology #81, Children’s Hospital Los Angeles, Los Angeles, CA, 90027, USA

    Benita Tamrazi

Authors
  1. Benita Tamrazi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Melike Pekmezci
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mariam Aboian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tarik Tihan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Christine M. Glastonbury
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Benita Tamrazi.

Ethics declarations

Conflict of interest

The authors of this manuscript have no conflicts of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tamrazi, B., Pekmezci, M., Aboian, M. et al. Apparent diffusion coefficient and pituitary macroadenomas: pre-operative assessment of tumor atypia. Pituitary 20, 195–200 (2017). https://doi.org/10.1007/s11102-016-0759-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11102-016-0759-5

Keywords

Search

Navigation