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

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

67 participants

Study Classification

INTERVENTIONAL

Study Start Date

2020-01-12

Study Completion Date

2022-02-28

Brief Summary

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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.

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Detailed Description

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Conditions

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Cavernous Sinus Invasion by Pituitary Adenoma

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Study Groups

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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

Group Type EXPERIMENTAL

MRI with deep learning based denoising

Intervention Type DIAGNOSTIC_TEST

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

Interventions

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MRI with deep learning based denoising

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

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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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

Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No