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

NCT04268251 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 67

Last updated 2024-05-14

No results posted yet for this 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.

Conditions

  • Cavernous Sinus Invasion by Pituitary Adenoma

Interventions

DIAGNOSTIC_TEST

MRI with deep learning based denoising

1-mm coronal contrast-enhanced T1 weighted image with deep learning based denoising

Sponsors & Collaborators

  • Asan Medical Center

    lead OTHER

Principal Investigators

  • Ho Sung Kim, MD PhD · Asan Medical Center

Study Design

Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-01-12
Primary Completion
2020-08-30
Completion
2022-02-28

Countries

  • South Korea

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04268251 on ClinicalTrials.gov