The Utility of Using Preoperative MRI as a Predictor for Intraoperative Pituitary Adenoma Consistency and Surgical Resection Technique

Abstract

Objective Most pituitary adenomas are of soft consistency and can be resected during surgery with routine suction instruments. However, fibrous adenomas may require more aggressive techniques. The ability to predict consistency on magnetic resonance imaging (MRI) would improve preoperative preparation and may have implications on the extent of resection.

Design A retrospective review of MRI and tumor histology of 50 consecutive patients who underwent endoscopic endonasal resection for nonfunctional adenomas was performed.

Methods An intensity ratio was calculated based on quantitative MRI signal intensity of the adenoma and pons. Intraoperatively, a sequentially graded technique required for resection ranged from suction (R1) for softer tumors, curettes (R2) for tumors with intermediate consistency, and aspirators and/or other microinstruments (R3) for firmer tumors. Fibrotic content was determined from histologic collagen percentage, and rates of gross total resection (GTR) were calculated from postoperative imaging. Statistical analyses were performed to determine if resection classification could be predicted by intensity ratio or collagen percentage, calculate ratio of cut-off points for clinical use, and assess for correlation between intensity ratios and collagen percentage.

Results Tumors with ratios < 1.6 on the T2-weighted coronal image and collagen content > 5.3% were likely to have required a more aggressive resection technique. Statistically significant lower rates of GTR and higher rates of perioperative complications were seen with such tumors.

Conclusion Preoperative MRI analyses can be helpful but not definitive in predicting adenoma consistency. Fibrous adenomas, associated with higher collagen content, are more difficult to resect and have higher rates of subtotal resection.

Keywords

Endoscopic - pituitary adenoma - transsphenoidal - tumor consistency

• References

• 1 Wei L, Lin SA, Fan K, Xiao D, Hong J, Wang S. Relationship between pituitary adenoma texture and collagen content revealed by comparative study of MRI and pathology analysis. Int J Clin Exp Med 2015; 8 (08) 12898-12905
• 2 Ezzat S, Asa SL, Couldwell WT. et al. The prevalence of pituitary adenomas: a systematic review. Cancer 2004; 101 (03) 613-619
• 3 Smith KA, Leever JD, Chamoun RB. Prediction of consistency of pituitary adenomas by magnetic resonance imaging. J Neurol Surg B Skull Base 2015; 76 (05) 340-343
• 4 Iuchi T, Saeki N, Tanaka M, Sunami K, Yamaura A. MRI prediction of fibrous pituitary adenomas. Acta Neurochir (Wien) 1998; 140 (08) 779-786
• 5 Yamamoto J, Kakeda S, Shimajiri S. et al. Tumor consistency of pituitary macroadenomas: predictive analysis on the basis of imaging features with contrast-enhanced 3D FIESTA at 3T. AJNR Am J Neuroradiol 2014; 35 (02) 297-303
• 6 Snow RB, Johnson CE, Morgello S, Lavyne MH, Patterson Jr RH. Is magnetic resonance imaging useful in guiding the operative approach to large pituitary tumors?. Neurosurgery 1990; 26 (05) 801-803
• 7 Bahuleyan B, Raghuram L, Rajshekhar V, Chacko AG. To assess the ability of MRI to predict consistency of pituitary macroadenomas. Br J Neurosurg 2006; 20 (05) 324-326
• 8 Heringer LC, de Oliveira MF, Rotta JM, Botelho RV. Effect of repeated transsphenoidal surgery in recurrent or residual pituitary adenomas: a systematic review and meta-analysis. Surg Neurol Int 2016; 7: 14
• 9 Boxerman JL, Rogg JM, Donahue JE, Machan JT, Goldman MA, Doberstein CE. Preoperative MRI evaluation of pituitary macroadenoma: imaging features predictive of successful transsphenoidal surgery. AJR Am J Roentgenol 2010; 195 (03) 720-728
• 10 Liu JK, Das K, Weiss MH, Laws Jr ER, Couldwell WT. The history and evolution of transsphenoidal surgery. J Neurosurg 2001; 95 (06) 1083-1096
• 11 Pierallini A, Caramia F, Falcone C. et al. Pituitary macroadenomas: preoperative evaluation of consistency with diffusion-weighted MR imaging--initial experience. Radiology 2006; 239 (01) 223-231
• 12 Schindelin J, Arganda-Carreras I, Frise E. et al. Fiji: an open-source platform for biological-image analysis. Nat Methods 2012; 9 (07) 676-682
• 13 Theodros D, Patel M, Ruzevick J, Lim M, Bettegowda C. Pituitary adenomas: historical perspective, surgical management and future directions. CNS Oncol 2015; 4 (06) 411-429
• 14 Kane LA, Leinung MC, Scheithauer BW. et al. Pituitary adenomas in childhood and adolescence. J Clin Endocrinol Metab 1994; 79 (04) 1135-1140
• 15 De Coene B, Hajnal JV, Gatehouse P. et al. MR of the brain using fluid-attenuated inversion recovery (FLAIR) pulse sequences. AJNR Am J Neuroradiol 1992; 13 (06) 1555-1564
• 16 Dickerman RD, Oldfield EH. Basis of persistent and recurrent Cushing disease: an analysis of findings at repeated pituitary surgery. J Neurosurg 2002; 97 (06) 1343-1349
• 17 Hagiwara A, Inoue Y, Wakasa K, Haba T, Tashiro T, Miyamoto T. Comparison of growth hormone-producing and non-growth hormone-producing pituitary adenomas: imaging characteristics and pathologic correlation. Radiology 2003; 228 (02) 533-538
• 18 Suzuki C, Maeda M, Hori K. et al. Apparent diffusion coefficient of pituitary macroadenoma evaluated with line-scan diffusion-weighted imaging. J Neuroradiol 2007; 34 (04) 228-235
• 19 Naganuma H, Satoh E, Nukui H. Technical considerations of transsphenoidal removal of fibrous pituitary adenomas and evaluation of collagen content and subtype in the adenomas. Neurol Med Chir (Tokyo) 2002; 42 (05) 202-212 , discussion 213
• 20 Monsalves E, Larjani S, Loyola Godoy B. et al. Growth patterns of pituitary adenomas and histopathological correlates. J Clin Endocrinol Metab 2014; 99 (04) 1330-1338