Ignite Creation Date:
2025-12-24 @ 11:38 PM
Ignite Modification Date:
2026-03-02 @ 4:01 PM
Study NCT ID:
NCT04268251
Status:
COMPLETED
Last Update Posted:
2024-05-14
First Post:
2020-01-13
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Evaluation of Cavernous Sinus Invasion by Pituitary Adenoma Using Deep Learning Based Denoising MR
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'interventionBrowseModule': {'meshes': [{'id': 'D008279', 'term': 'Magnetic Resonance Imaging'}], 'ancestors': [{'id': 'D014054', 'term': 'Tomography'}, {'id': 'D003952', 'term': 'Diagnostic Imaging'}, {'id': 'D019937', 'term': 'Diagnostic Techniques and Procedures'}, {'id': 'D003933', 'term': 'Diagnosis'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'NA', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'DIAGNOSTIC', 'interventionModel': 'SINGLE_GROUP'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 67}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2020-01-12', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-05', 'completionDateStruct': {'date': '2022-02-28', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2024-05-12', 'studyFirstSubmitDate': '2020-01-13', 'studyFirstSubmitQcDate': '2020-02-11', 'lastUpdatePostDateStruct': {'date': '2024-05-14', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2020-02-13', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2020-08-30', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Cavernous sinus invasion', 'timeFrame': 'Within 1 week', 'description': 'Presence or absence of cavernous sinus invasion determined surgically'}], 'secondaryOutcomes': [{'measure': 'Size of pituitary adenoma (in mm), laterality of pituitary adenoma (unilateral or bilateral) on the MRI', 'timeFrame': 'Within 1 week', 'description': 'Size of the tumor (in mm), laterality of the tumor (unilateral or bilateral) on the MRI'}, {'measure': 'Margin of pituitary adenoma (well-delineated, poorly delineated) on the MRI', 'timeFrame': 'Within 1 week', 'description': 'Margin of pituitary adenoma (well-delineated, poorly delineated) on the MRI'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Cavernous Sinus Invasion by Pituitary Adenoma']}, 'referencesModule': {'references': [{'pmid': '34992127', 'type': 'BACKGROUND', 'citation': '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.'}]}, 'descriptionModule': {'briefSummary': '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.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Patients undergoing preoperative brain MR for pituitary adenoma\n\nExclusion Criteria:\n\n* 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\n* Patients who are pregnant or breast feeding; urine pregnancy test will be performed on women of child bearing potential\n* Poor MRI image quality due to artifacts'}, 'identificationModule': {'nctId': 'NCT04268251', 'briefTitle': 'Evaluation of Cavernous Sinus Invasion by Pituitary Adenoma Using Deep Learning Based Denoising MR', 'organization': {'class': 'OTHER', 'fullName': 'Asan Medical Center'}, 'officialTitle': 'Prospective MRI Evaluation of Cavernous Sinus Invasion by Pituitary Adenoma Using Deep Learning Based Denoising', 'orgStudyIdInfo': {'id': 'AsanMCHSKim_06'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Deep learning based denoising MR', 'description': '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', 'interventionNames': ['Diagnostic Test: MRI with deep learning based denoising']}], 'interventions': [{'name': 'MRI with deep learning based denoising', 'type': 'DIAGNOSTIC_TEST', 'description': '1-mm coronal contrast-enhanced T1 weighted image with deep learning based denoising', 'armGroupLabels': ['Deep learning based denoising MR']}]}, 'contactsLocationsModule': {'locations': [{'city': 'Seoul', 'country': 'South Korea', 'facility': 'Asan Medical Center', 'geoPoint': {'lat': 37.566, 'lon': 126.9784}}], 'overallOfficials': [{'name': 'Ho Sung Kim, MD PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Asan Medical Center'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Asan Medical Center', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Professor', 'investigatorFullName': 'Ho Sung Kim', 'investigatorAffiliation': 'Asan Medical Center'}}}}