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
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
-
-
Seoul, Korea, Republic of
- Asan Medical Center
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
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
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: N/A
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / 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
|
1-mm coronal contrast-enhanced T1 weighted image with deep learning based denoising
|
What is the study measuring?
Primary Outcome Measures
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
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
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Ho Sung Kim, MD PhD, Asan Medical Center
Publications and helpful links
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
- Brain Diseases
- Central Nervous System Diseases
- Nervous System Diseases
- Neoplasms by Histologic Type
- Neoplasms
- Neoplasms by Site
- Neoplasms, Glandular and Epithelial
- Endocrine System Diseases
- Endocrine Gland Neoplasms
- Hypothalamic Diseases
- Hypothalamic Neoplasms
- Supratentorial Neoplasms
- Brain Neoplasms
- Central Nervous System Neoplasms
- Nervous System Neoplasms
- Adenoma
- Pituitary Neoplasms
- Pituitary Diseases
Other Study ID Numbers
Other Study ID Numbers
- AsanMCHSKim_06
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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