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

Sponsor

Asan Medical Center (Other)

Overall Status

Unknown status

CT.gov ID

NCT04268251

Collaborator

(none)

Enrollment

Location

Arm

13.6

Anticipated Duration (Months)

5.6

Patients Per Site Per Month

Study Details

Study Description

Brief 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.

Condition or Disease	Intervention/Treatment	Phase
Cavernous Sinus Invasion by Pituitary Adenoma	Diagnostic Test: MRI with deep learning based denoising	N/A

Study Design

Study Type:

Interventional

Anticipated Enrollment :

76 participants

Allocation:

N/A

Intervention Model:

Single Group Assignment

Masking:

None (Open Label)

Primary Purpose:

Diagnostic

Official Title:

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

Actual Study Start Date :

Jan 12, 2020

Anticipated Primary Completion Date :

Feb 28, 2021

Anticipated Study Completion Date :

Feb 28, 2021

Arms and Interventions

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

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

Outcome Measures

Primary Outcome Measures

Cavernous sinus invasion [Within 1 week]
Presence or absence of cavernous sinus invasion determined surgically

Secondary Outcome Measures

Size of pituitary adenoma (in mm), laterality of pituitary adenoma (unilateral or bilateral) on the MRI [Within 1 week]
Size of the tumor (in mm), laterality of the tumor (unilateral or bilateral) on the MRI
Margin of pituitary adenoma (well-delineated, poorly delineated) on the MRI [Within 1 week]
Margin of pituitary adenoma (well-delineated, poorly delineated) on the MRI

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years and Older

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

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

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Asan Medical Center	Seoul		Korea, Republic of

Sponsors and Collaborators

Asan Medical Center

Investigators

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

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

Responsible Party:

Ho Sung Kim, Professor, Asan Medical Center

ClinicalTrials.gov Identifier:

NCT04268251

Other Study ID Numbers:

AsanMCHSKim_06

First Posted:

Feb 13, 2020

Last Update Posted:

Feb 20, 2020

Last Verified:

Feb 1, 2020

Individual Participant Data (IPD) Sharing Statement:

Plan to Share IPD:

Studies a U.S. FDA-regulated Drug Product:

Studies a U.S. FDA-regulated Device Product:

Additional relevant MeSH terms:

Adenoma

Pituitary Neoplasms

Pituitary Diseases

Study Results

No Results Posted as of Feb 20, 2020