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DOI: 10.4103/ajns.AJNS_56_16
Initial experience with diffusion-weighted imaging to predict the tumor consistency and surgical success in solid growth hormone producing pituitary macroadenomas

Background: Tumor consistency is an important factor impeding transsphenoidal resection of some pituitary macroadenomas. Preoperative prediction of the tumor consistency may help neurosurgeons in preparing the patients for other therapeutic options after a subtotally resected growth hormone (GH)-producing macroadenoma. We present the preliminary results of our study about the application of the preoperative diffusion-weighted (DW) magnetic resonance imaging (MRI) to predict the consistency and resection rate of GH-producing pituitary macroadenomas. Materials and Methods: Sixteen primary patients with solid GH-producing pituitary macroadenomas were enrolled. Hormonal assays as well as standard and DW-MRI were obtained before surgery. All the patients were operated via an endoscopic transsphenoidal approach. The intraoperative tumor consistencies (suctionable versus nonsuctionable) were documented. The samples were stained for measurement of the collagen content (low, moderate, and high). Postoperative hormonal study and MRI were performed after 8 weeks to evaluate the resection ratio and the hormonal remission. Results: On DW images, the tumor diffusion was enhanced (free) in four, moderate in ten, and restricted in two patients. The tumor was suctionable in 14 cases; gross total resection and hormonal remission were achieved in 12/14 of these. All the 14 suctionable tumors had moderate to enhanced diffusion on DW imaging (DWI). The two patients with a nonsuctionable fibrous tumor had a restricted diffusion in DWI. These were the only ones to have high collagen content in the histopathologic study. Conclusion: DWI could help identify the fibrous nonsuctionable GH-producing adenomas from the others.
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Publication History
Article published online:
09 September 2022
© 2019. Asian Congress of Neurological Surgeons. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)
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