Diagnostic Yield of Deep Learning Based Denoising MRI in Cushing's Disease

Terminated

• Conditions: Pituitary ACTH Secreting Adenoma
• Interventions: Diagnostic Test: MRI

• Registration Number: NCT04121988
• Lead Sponsor: Asan Medical Center

Brief Summary

Negative MRI findings may occur in up to 40% of cases of ACTH producing microadenomas. The aim of the study is to evaluate if detection of ACTH producing microadenomas can be increased using deep learning based denoising MRI.

Detailed Description

Detecting ACTH producing microadenoma in MRI is important in establishing the diagnosis of Cushing disease and may enable patients to avoid additional diagnostic tests such as inferior petrosal sinus sampling. However, detecting ACTH producing microadenoma in MRI remains as a diagnostic challenge due its small size with its median diameter of 5-mm. Many attempts have been made in order to improve the sensitivity of detecting ACTH producing microadenoma. It is generally accepted as standard clinical practice to perform dynamic contrast enhanced T1 weighted image to delineate delayed enhancing microadenonoma in comparison to the background enhancement of the normal gland. Despite these attempts, negative MRI findings may occur in up to 40% of cases of ACTH producing microadenomas and there is a need to improve its detection rate. Theoretically, performing thin slice thickness scans should help detecting the lesion but this is unavoidably accompanied with increased level of noise. Deep learning based denoising algorithm can be applied to reduce the noise level and potentially increase the detection rate of ACTH producing microadenomas. The aim of the study is to evaluate if detection of ACTH producing microadenomas can be increased using deep learning based denoising MRI.

Study Timeline

• Study First Submitted: 2019-10-08
• Study First Submitted QC: 2019-10-08
• Study First Posted: 2019-10-10
• Study Start: 2020-01-10
• Primary Completion: 2023-02-28
• Study Completion: 2023-02-28
• Status Verified: 2024-05
• Last Update Submitted: 2024-05-12
• Last Update Posted: 2024-05-14

Recruitment & Eligibility

• Status: TERMINATED
• Sex: All
• Target Recruitment: 15

Inclusion Criteria

• Patients suspected of Cushing disease undergoing MRI
• Signed informed consent

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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

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Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Denoising MRI group	MRI	Patients suspected of Cushing disease undergoing deep learning based denoising MRI

Primary Outcome Measures

Name	Time	Method
Detection rate of ACTH producing microadenoma	2 months	Proportion of positive MRI with visible microadenoma as percentage (%)

Secondary Outcome Measures

Name	Time	Method
Proportion of patients undergoing additional diagnostic tests	6 months	Proportion of patients undergoing additional diagnostic tests as percentage (%)

Trial Locations

Locations (1)

Asan Medical Center; 🇰🇷 Seoul, Korea, Republic of