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

May 12, 2024 updated by: Ho Sung Kim, Asan Medical Center

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

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.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Actual)

67

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

14 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • Patients undergoing preoperative brain MR for pituitary adenoma

Exclusion Criteria:

  • Patients who have any type of bioimplant activated by mechanical, electronic, or magnetic means (e.g., cochlear implants, pacemakers, neurostimulators, biostimulates, electronic infusion pumps, etc), because such devices may be displaced or malfunction
  • Patients who are pregnant or breast feeding; urine pregnancy test will be performed on women of child bearing potential
  • Poor MRI image quality due to artifacts

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Deep learning based denoising MR
1 mm slice thickness coronal contrast-enhanced T1 weighted imaging with deep learning based denoising vs. 3 mm slice thickness coronal contrast-enhanced T1 weighted imaging
Diagnostic test: MRI with deep learning based denoising
1-mm coronal contrast-enhanced T1 weighted image with deep learning based denoising

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Cavernous sinus invasion
Time Frame: Within 1 week
Presence or absence of cavernous sinus invasion determined surgically
Within 1 week

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Size of pituitary adenoma (in mm), laterality of pituitary adenoma (unilateral or bilateral) on the MRI
Time Frame: Within 1 week
Size of the tumor (in mm), laterality of the tumor (unilateral or bilateral) on the MRI
Within 1 week
Margin of pituitary adenoma (well-delineated, poorly delineated) on the MRI
Time Frame: Within 1 week
Margin of pituitary adenoma (well-delineated, poorly delineated) on the MRI
Within 1 week

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Asan Medical Center

Investigators

  • Principal Investigator: Ho Sung Kim, MD PhD, Asan Medical Center

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 12, 2020

Primary Completion (Actual)

August 30, 2020

Study Completion (Actual)

February 28, 2022

Study Registration Dates

First Submitted

January 13, 2020

First Submitted That Met QC Criteria

February 11, 2020

First Posted (Actual)

February 13, 2020

Study Record Updates

Last Update Posted (Actual)

May 14, 2024

Last Update Submitted That Met QC Criteria

May 12, 2024

Last Verified

May 1, 2024

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • AsanMCHSKim_06

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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