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

Last updated: May 12, 2024
Sponsor: Asan Medical Center
Overall Status: Completed

Phase

N/A

Condition

N/A

Treatment

MRI with deep learning based denoising

Clinical Study ID

NCT04268251
AsanMCHSKim_06
  • Ages > 18
  • All Genders

Study 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.

Eligibility Criteria

Inclusion

Inclusion Criteria:

  • Patients undergoing preoperative brain MR for pituitary adenoma

Exclusion

Exclusion Criteria:

  • Patients who have any type of bioimplant activated by mechanical, electronic, ormagnetic means (e.g., cochlear implants, pacemakers, neurostimulators,biostimulates, electronic infusion pumps, etc), because such devices may bedisplaced or malfunction

  • Patients who are pregnant or breast feeding; urine pregnancy test will be performedon women of child bearing potential

  • Poor MRI image quality due to artifacts

Study Design

Total Participants: 67
Treatment Group(s): 1
Primary Treatment: MRI with deep learning based denoising
Phase:
Study Start date:
January 12, 2020
Estimated Completion Date:
February 28, 2022

Connect with a study center

  • Asan Medical Center

    Seoul,
    Korea, Republic of

    Site Not Available

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