Predicting visual recovery in pituitary adenoma patients post-endoscopic endonasal transsphenoidal surgery: Harnessing delta-radiomics of the optic chiasm from MRI

Abstract

Objectives To investigate whether morphological changes after surgery and delta-radiomics of the optic chiasm obtained from routine MRI could help predict postoperative visual recovery of pituitary adenoma patients. Methods A total of 130 pituitary adenoma patients were retrospectively enrolled and divided into the recovery group (n = 87) and non-recovery group (n = 43) according to visual outcome 1 year after endoscopic endonasal transsphenoidal surgery. Morphological parameters of the optic chiasm were measured preoperatively and postoperatively, including chiasmal thickness, deformed angle, and suprasellar extension. Delta-radiomics of the optic chiasm were calculated based on features extracted from preoperative and postoperative coronal T2-weighted images, followed by machine learning modeling using least absolute shrinkage and selection operator wrapped with support vector machine through fivefold cross-validation in the development set. The delta-radiomic model was independently evaluated in the test set, and compared with the combined model that incorporated delta-radiomics, significant clinical and morphological parameters. Results Postoperative morphological changes of the optic chiasm could not significantly be used as predictors for the visual outcome. In contrast, the delta-radiomics model represented good performances in predicting visual recovery, with an AUC of 0.821 in the development set and 0.811 in the independent test set. Moreover, the combined model that incorporated age and delta-radiomics features of the optic chiasm achieved the highest AUC of 0.841 and 0.840 in the development set and independent test set, respectively. Conclusions Our proposed machine learning models based on delta-radiomics of the optic chiasm can be used to predict postoperative visual recovery of pituitary adenoma patients. Clinical relevance statement Our delta-radiomics-based models from MRI enable accurate visual recovery predictions in pituitary adenoma patients who underwent endoscopic endonasal transsphenoidal surgery, facilitating better clinical decision-making and ultimately improving patient outcomes. Key Points • Prediction of the postoperative visual outcome for pituitary adenoma patients is important but challenging. • Delta-radiomics of the optic chiasm after surgical decompression represented better prognostic performances compared with its morphological changes. • The proposed machine learning models can serve as novel approaches to predict visual recovery for pituitary adenoma patients in clinical practice.

Optico-chiasmatic distortions in pituitary adenomas: correlation between postoperative morphological reversal and follow-up functional visual recovery

“…More recently Zhang et al reported no correlation between postoperative chiasm morphology and improvement in VF de cits. [24] However, in this study postoperative imaging was performed <72 hours after surgery which is probably an inadequate time-frame for any meaningful change in chiasm dimensions, especially in patients with chronic visual compression from a suprasellar mass. It may appear counter-intuitive that postoperative optic nerve deviations correlated with VF scores and not VA scores in our study.…”

Compressive optic neuropathy in the setting of tumors of the chiasmal and sellar region: a review

“…It is the endoscopic skull-base surgery that has been reported to be the best option for visual recovery [44]. Predicting visual acuity and visual field outcomes after removal of chiasmal-sellar tumors is still an important task [107,108,109,110].…”