NCT04268251

Evaluation of Cavernous Sinus Invasion by Pituitary Adenoma Using Deep Learning Based Denoising MR

Prospective MRI Evaluation of Cavernous Sinus Invasion by Pituitary Adenoma Using Deep Learning Based Denoising

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 67 (actual)
• Sponsor: Asan Medical Center · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

Preoperative evaluation of cavernous sinus invasion by pituitary adenoma is critical for performing safe operation and deciding on surgical extent as well as for treatment success. Because of the small size of the pituitary gland and sellar fossa, determining the exact relationship between the pituitary adenoma and cavernous sinus can be challenging. Performing thin slice thickness MRI may be beneficial but is inevitably associated with increased noise level. By applying deep learning based denoising algorithm, diagnosis of cavernous sinus invasion by pituitary adenoma may be improved.

Conditions

• Cavernous Sinus Invasion by Pituitary Adenoma

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	MRI with deep learning based denoising	1-mm coronal contrast-enhanced T1 weighted image with deep learning based denoising

Timeline

• Start date: 2020-01-12
• Primary completion: 2020-08-30
• Completion: 2022-02-28
• First posted: 2020-02-13
• Last updated: 2024-05-14

Locations

1 site across 1 country: South Korea