Ignite Creation Date:
2025-12-25 @ 12:31 AM
Ignite Modification Date:
2025-12-25 @ 10:38 PM
Study NCT ID:
NCT07202767
Status:
NOT_YET_RECRUITING
Last Update Posted:
2025-10-02
First Post:
2025-09-23
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Intraocular Lens Calculation Using Artificial Intelligence
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D002386', 'term': 'Cataract'}], 'ancestors': [{'id': 'D007905', 'term': 'Lens Diseases'}, {'id': 'D005128', 'term': 'Eye Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 170}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2025-11-01', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-10', 'completionDateStruct': {'date': '2028-10-30', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-10-01', 'studyFirstSubmitDate': '2025-09-23', 'studyFirstSubmitQcDate': '2025-10-01', 'lastUpdatePostDateStruct': {'date': '2025-10-02', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2025-10-02', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2027-07-30', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Prediction model to estimate lens diameter with different measurement tools (swept-AS segment OCT; anterior segment-OCT and Placido topography with OCT-based anterior segment tomography; wave-front abberometry; swept-source OCT and optical biometer)', 'timeFrame': 'preoperatively, 4 and 12 weeks post cataract surgery', 'description': 'Developing a prediction model to accurately estimate the lens diameter using biometric parameters (swept-source anterior segment Optical Coherence Topography (Casia-2), Placido topography combined with Optical Coherenece Topography-based anterior segment tomography (MS-39), wave-front abberometry (OSIRIS), Swept-Source Optical Coherence Tomography (IOLMaster 700) and anterior segment swept-source OCT (Anterion).'}, {'measure': 'Prediction model to estimate lens diameter with cerebral Magnetic Resonance Imaging', 'timeFrame': '12 weeks post cataract surgery', 'description': 'Developing a prediction model to accurately estimate the lens diameter using cerebral Magnetic Resonance Imaging to examine ocular configuration'}], 'secondaryOutcomes': [{'measure': 'IOL calculation concept an artificial intelligence approach', 'timeFrame': 'preoperatively, 4 and 12 weeks post cataract surgery', 'description': 'Development of a new IOL calculation concept which includes the lens diameter using an artificial intelligence approach'}, {'measure': 'Different measurement modalities for the biometry of the eye', 'timeFrame': '4 and 12 weeks post cataract surgery', 'description': 'Comparison of different measurement modalities (swept-source anterior segment Optical Coherence Topography; anterior segment-Optical Coherence Tomography and Placido topography with Optical Coherenece Topography-based anterior segment tomography; wave-front abberometry; swept-source Optical Coherence Tomography and optical biometer) for the biometry of the eye'}]}, 'oversightModule': {'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['cataract', 'lens diameter', 'artificial intelligence'], 'conditions': ['Cataract']}, 'descriptionModule': {'briefSummary': "The aim of this study is to investigate the lens diameter (LD) as a useful parameter in intraocular lens (IOL) power calculation by using several different non-invasive imaging techniques. The aim is to establish an accurate model for lens diameter estimation and subsequently evaluate the influence of the LD on the effective postoperative lens position. The comparability of the different devices in terms of variability between the biometric measurements will also be assessed.\n\nBy then combining these two approaches with artificial intelligence, the aim is to develop a new approach to effectively incorporate the LD in IOL power calculation and improve patient's outcome in the long run.", 'detailedDescription': "During uncomplicated cataract operation, the clouded natural lens is being removed and replaced with an artificial intraocular lens (IOL). To achieve optimal postoperative outcomes for patients, the power of the implanted artificial lens is calculated prior to surgery.\n\nSignificant progress has been made in calculation concepts over the past 20 years, including the introduction of regression, vergence and ray tracing. More recently, approaches incorporating artificial intelligence have emerged.\n\nAll these formulae are based on the biometric data of the eye. This includes parameters such as axial eye length, corneal curvature, central corneal thickness, anterior chamber depth and the refractive indices of the eye's optical segments. By including all these variables, modern formulas aim to deliver the best possible postoperative outcomes.\n\nOne variable that has not been included in the calculation thus far is the diameter of the natural lens. Large parts of the lens are covered by the iris. Even with medically dilated pupils the peripheral parts cannot be visualized, and subsequently not adequately reproduced using established imaging methods. This has made implementation in IOL power calculation difficult.\n\nIn everyday clinical practice, however, anterior segment OCT imaging devices are equipped with features that allow for an estimation of lens diameter. This is achieved by extrapolating the anterior and posterior curvature of the natural lens, which unfortunately makes this approach prone to error. Other imaging techniques, such as magnetic resonance imaging, are impractical in routine clinical practice due to time and cost considerations. However, they could be highly beneficial for future predictive approaches of the lens diameter The aim of this study is to develop a model for incorporating the lens diameter into IOL calculation. This will be achieved by using different imaging technologies to determine the actual lens diameter. The diameter will then be predicted using available biometric variables."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '21 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'The participants will be selected at Kepler University Clinic Linz at the Departement of Ophthalmology and Optometry.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion criteria\n\n* age 21 years and older\n* planned uncomplicated bilateral cataract surgery\n* availability, willingness, ability and sufficient cognitive awareness to comply with examination procedures and study visits\n* ability to consent to the participation in the study\n* signed informed consent\n\nExclusion criteria\n\n* multifocal IOL\n* combined surgery (cataract plus glaucoma/vitreoretinal/corneal surgery)\n* PEX, previous ocular surgery, severe trauma or any pathology that could lead to an unstable capsular bag\n* glaucoma or any other retinal disease that may affect visual acuity significantly\n* pregnancy\n* pre-operative visual acuity below 0.1 Snellen decimal (1.0 Log MAR)\n* pupil diameter \\<4mm'}, 'identificationModule': {'nctId': 'NCT07202767', 'briefTitle': 'Intraocular Lens Calculation Using Artificial Intelligence', 'organization': {'class': 'OTHER', 'fullName': 'Johannes Kepler University of Linz'}, 'officialTitle': 'Intraocular Lens Calculation Using Artificial Intelligence', 'orgStudyIdInfo': {'id': 'KUK-Ophthalmology-015'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Study Cohort with MRI', 'description': 'Patients who are included in this study who additionally receive a cerebral MRI', 'interventionNames': ['Device: Swept-Source Anterior Segment OCT']}, {'label': 'Study cohort without MRI', 'description': "Study cohort who doesn't receive an MRI", 'interventionNames': ['Device: Swept-Source Anterior Segment OCT']}], 'interventions': [{'name': 'Swept-Source Anterior Segment OCT', 'type': 'DEVICE', 'description': 'Device: Swept-Source Anterior Segment OCT The CASIA-2 (Tomey, Japan) is a high-resolution swept-source anterior segment OCT with CE certification. The device allows for incomplete visualization of the lens, including the anterior and posterior lens curvature.\n\nDevice: AS-OCT + Placido disc corneal topography The MS-39 (CSO, Italy) is a non-invasive device that combines Placido topography with OCT-based anterior segment tomography.\n\nDevice: Wave-front abberomtery The OSIRIS aberrometer is a standard tool for examining corneal aberration and measuring the ocular wavefront.\n\nDevice: Swept-Source OCT The IOLMaster 700 (Carl Zeiss Meditec, Germany) is a standard swept-source OCT used for eye examinations.\n\nDevice: AS-OCT The ANTERION (Heidelberg Engineering, Germany) is an anterior segment swept-source OCT.\n\nDiagnostic Test: Refraction Subjective Refraction evaluation using the cross-cylinder method', 'armGroupLabels': ['Study Cohort with MRI', 'Study cohort without MRI']}]}, 'contactsLocationsModule': {'locations': [{'zip': '4020', 'city': 'Linz', 'country': 'Austria', 'contacts': [{'name': 'Nino Hirnschall, MD, PhD', 'role': 'CONTACT', 'email': 'nino.hirnschall@kepleruniklinikum.at', 'phone': '0043(0)5768083', 'phoneExt': '1056'}, {'name': 'Leon Pomberger, MD', 'role': 'CONTACT', 'email': 'nino.hirnschall@kepleruniklinikum.at', 'phone': '0043(0)5768083', 'phoneExt': '1056'}], 'facility': 'Kepler University Clinic, Linz', 'geoPoint': {'lat': 48.30639, 'lon': 14.28611}}], 'centralContacts': [{'name': 'Nino Hirnschall, MD PhD', 'role': 'CONTACT', 'email': 'nino.hirnschall@kepleruniklinikum.at', 'phone': '0043(0)5768083', 'phoneExt': '1056'}, {'name': 'Leon Pomberger, MD', 'role': 'CONTACT', 'email': 'leon.pomberger@kepleruniklinikum.at', 'phone': '0043(0)5768083', 'phoneExt': '1056'}], 'overallOfficials': [{'name': 'Nino Hirnschall, MD PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'JKU Linz'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Johannes Kepler University of Linz', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}