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

Cavernous Sinus Invasion by Pituitary Adenoma Clinical Trial

Official title:

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

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04268251
• Other study ID #: AsanMCHSKim_06
• Status: Completed
• Phase: N/A
• Start date: January 12, 2020
• Est. completion date: February 28, 2022

Study information

• Verified date: May 2024
• Source: Asan Medical Center
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 67
• Est. completion date: February 28, 2022
• Est. primary completion date: August 30, 2020
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

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

Related Conditions & MeSH terms

• Adenoma
• Cavernous Sinus Invasion by Pituitary Adenoma
• Pituitary Diseases
• Pituitary Neoplasms

Intervention

Diagnostic Test:
• MRI with deep learning based denoising
1-mm coronal contrast-enhanced T1 weighted image with deep learning based denoising

Locations

Country	Name	City	State
Korea, Republic of	Asan Medical Center	Seoul

Sponsors (1)

Lead Sponsor	Collaborator
Asan Medical Center

Country where clinical trial is conducted

Korea, Republic of, 

References & Publications (1)

Kim M, Kim HS, Park JE, Park SY, Kim YH, Kim SJ, Lee J, Lebel MR. Thin-Slice Pituitary MRI with Deep Learning-Based Reconstruction for Preoperative Prediction of Cavernous Sinus Invasion by Pituitary Adenoma: A Prospective Study. AJNR Am J Neuroradiol. 2022 Feb;43(2):280-285. doi: 10.3174/ajnr.A7387. Epub 2022 Jan 6. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Cavernous sinus invasion	Presence or absence of cavernous sinus invasion determined surgically	Within 1 week
Secondary	Size of pituitary adenoma (in mm), laterality of pituitary adenoma (unilateral or bilateral) on the MRI	Size of the tumor (in mm), laterality of the tumor (unilateral or bilateral) on the MRI	Within 1 week
Secondary	Margin of pituitary adenoma (well-delineated, poorly delineated) on the MRI	Margin of pituitary adenoma (well-delineated, poorly delineated) on the MRI	Within 1 week