Ignite Creation Date:
2025-12-24 @ 7:52 PM
Ignite Modification Date:
2025-12-29 @ 9:07 PM
Study NCT ID:
NCT07091604
Status:
RECRUITING
Last Update Posted:
2025-08-01
First Post:
2025-07-21
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
An Observational Study to Assess Objective Skin Pigmentation Variation.
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D012871', 'term': 'Skin Diseases'}, {'id': 'D010859', 'term': 'Pigmentation Disorders'}], 'ancestors': [{'id': 'D017437', 'term': 'Skin and Connective Tissue Diseases'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 600}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2025-07-22', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-07', 'completionDateStruct': {'date': '2027-01-22', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-07-29', 'studyFirstSubmitDate': '2025-07-21', 'studyFirstSubmitQcDate': '2025-07-21', 'lastUpdatePostDateStruct': {'date': '2025-08-01', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-07-29', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2027-01-22', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Melanin index', 'timeFrame': 'At baseline study visit (single time point)', 'description': 'Melanin index as measured by skin colorimetry and multispectral imaging.'}], 'secondaryOutcomes': [{'measure': 'Fitzpatrick skin type', 'timeFrame': 'At baseline study visit (single time point)', 'description': 'Self-questionnaire and assessed by dermatologist'}, {'measure': 'Age', 'timeFrame': 'At baseline study visit (single time point)'}, {'measure': 'Ethnicity', 'timeFrame': 'At baseline study visit (single time point)', 'description': 'Self-reported'}, {'measure': 'Line-Field Confocal Optical Coherence Tomography (LC-OCT)', 'timeFrame': 'At baseline study visit (single time point)', 'description': 'LC-OCT is a non-invasive optical imaging technique based on a combination of the optical principles of optical coherence tomography and reflectance confocal microscopy with line-field illumination, which can generate cell-resolved images of the skin, in vivo, in vertical section, horizontal section and in three dimensions.'}, {'measure': '3D Multispectral imaging', 'timeFrame': 'At baseline study visit (single time point)', 'description': 'The redness, melanin and superficial morphology of (non-)lesional skin sites and healthy skin will be determined using a 3D multispectral imaging system.'}, {'measure': 'Colorimetry', 'timeFrame': 'At baseline study visit (single time point)', 'description': 'The melanin, redness and surface characteristics of (non-)lesional and healthy skin will be assessed using a colorimetry device that quantitatively measures skin color parameters, including melanin, based on reflected light.'}, {'measure': 'Skin barrier function by Skin Barrier Pro', 'timeFrame': 'At baseline study visit (single time point)', 'description': 'The barrier status by trans epidermal water loss of (non-)lesional skin and healthy skin will be determined using Skin Barrier Pro'}, {'measure': 'VISIA', 'timeFrame': 'At baseline study visit (single time point)', 'description': 'VISIA is a non-invasive imaging system designed for in vivo analysis of facial skin, utilizing multi-spectral imaging and digital analysis to assess various skin features, including pigmentation, porphyrins, texture, and wrinkles. The system captures standardized, high-resolution images under different lighting conditions (including cross-polarized and UV light), allowing for both surface and subsurface visualization of the skin. It provides quantitative and comparative assessments of skin health and damage, supporting both clinical evaluation and cosmetic or dermatological research.'}, {'measure': 'Patient and Observer Scar Assessment Scale', 'timeFrame': 'At baseline study visit (single time point)', 'description': 'POSAS is a validated scar assessment tool that combines both patient-reported outcomes and clinical evaluation to provide a comprehensive assessment of scar quality. It consists of two complementary parts: the Observer Scale, completed by a clinician, which evaluates vascularity, pigmentation, thickness, relief, pliability, and surface area; and the Patient Scale, completed by the individual, which captures subjective symptoms such as pain, itching, and overall opinion of the scar. POSAS enables standardized, semi-quantitative scoring of scars, facilitating both clinical monitoring and research on scar treatment outcomes.'}, {'measure': 'Laser speckle contrast imaging', 'timeFrame': 'At baseline study visit (single time point)', 'description': 'Laser speckle contrast imaging (LSCI) is a non-invasive optical imaging technique used to assess microvascular blood flow in vivo by analyzing the speckle pattern produced when coherent laser light is scattered by moving red blood cells. The resulting speckle contrast is inversely related to the velocity of blood flow, enabling real-time, high-resolution visualization of perfusion over large skin areas without the need for contrast agents. LSCI is particularly suited for dynamic monitoring of vascular responses in dermatology, wound healing, and inflammatory skin conditions.'}, {'measure': 'Scarletred® Vision', 'timeFrame': 'At baseline study visit (single time point)', 'description': 'Scarletred® Vision is a digital, non-invasive skin imaging and analysis platform that enables objective and standardized quantification of skin conditions over time using smartphone-based photography combined with a calibrated color patch and proprietary software. The system captures high-resolution images under controlled lighting conditions and applies automated analysis algorithms to quantify parameters such as erythema, pigmentation, and lesion area. By providing reproducible, color-calibrated data, Scarletred® Vision supports longitudinal skin monitoring in clinical trials and dermatological research, including evaluation of treatment effects in inflammatory and pigmentary disorders.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Skin pigmentation', 'Melanin index', 'Colorimetry', 'Multispectral imaging', 'Line-Field Confocal Optical Coherence Tomography', 'Skin parameters', 'Skin colour', 'Skin color', 'Etnicity', 'TEWL', 'Erythema index', 'Non-invasieve measurement', 'Skin Disease', 'Skin of Colour', 'Laser speckle contrast imaging'], 'conditions': ['Skin Diseases', 'Healthy Skin']}, 'descriptionModule': {'briefSummary': 'Accurate assessment of skin pigmentation is essential in dermatology for properly diagnosing and managing a wide range of skin conditions. Traditionally, skin colour has been evaluated through visual inspection or by using classifications like the Fitzpatrick skin type. However, these methods can be subjective, culturally biased, and often are centered around lighter skin tones, which may lead to misdiagnosis or inappropriate treatment for individuals with darker skin.\n\nWith advances in technology, non-invasive imaging tools such as colorimetry and multispectral imaging now offer more precise and objective ways to measure skin pigmentation. These methods can help provide consistent and unbiased information about skin tone, benefiting both clinical care and research. Despite these technological advances, there is currently no agreed-upon standard for how to measure skin pigmentation objectively in everyday clinical practice or research settings.\n\nThis study aims to explore better, more accurate ways to measure skin pigmentation using modern, non-invasive imaging technologies. Traditional methods for assessing skin colour, like visual inspection or classifying by ethnicity, are often unreliable and biased. In this study, researchers will use tools such as colorimetry and multispectral imaging to measure skin pigmentation more objectively.\n\nThe study includes two groups of participants: healthy adults and adults with skin conditions. Researchers will measure a value called the melanin index, which reflects the amount of pigment in the skin, and compare it across different areas of the body and among people with different skin tones and conditions.\n\nThe goal is to understand how skin pigmentation varies and to see if these new technologies can help doctors more accurately diagnose and manage skin diseases for people of all skin types.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'For study cohort #1 (healthy volunteers): adult subjects will be recruited at multiple locations to ensure a diverse study population reflecting the full spectrum of skin colour types. Firstly, volunteers will be recruited using flyers at the campus of Leiden University. Along with that, partners of patients visiting the outpatient dermatology clinic of the LUMC. Lastly, subjects will be asked to partake in the study at public spaces (e.g. museums, festivals) that have given consent for this. Thus, subjects will be recruited in person by researchers at the aforementioned sites, through physical advertisements and digital advertisements.\n\nFor study cohort #2 (patients with any skin disease): adult subjects with be recruited at the outpatient dermatology clinic of the LUMC and the affiliated hospitals of the CONNECTED (Clinical Network for Trials in Dermatology) in the Randstad region (e.g., The Hague, Zoetermeer, and Amsterdam).', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:-\n\n* Age ≥ 18 years\n* Ability to understand oral and written Dutch or English\n\nExclusion Criteria:\n\nFor study cohort #1 (Healthy volunteers):\n\n* Extensive tattoos covering \\>50% of the total body area\n* Recent extensive sun exposure (e.g. sun tanning booth or stay in a tropical country) in the last 3 weeks\n* Use of self-tanner products in the last 3 weeks\n\nFor study cohort #2 (Patients):\n\n* Extensive tattoos covering \\>50% of the total body area\n* Extensive skin lesions covering \\>50% of the total body area\n* Recent extensive sun exposure (e.g. sun tanning booth or stay in a tropical country) in the last 3 weeks\n* Use of self-tanner products in the last 3 weeks'}, 'identificationModule': {'nctId': 'NCT07091604', 'acronym': 'SKIN-IMAGING', 'briefTitle': 'An Observational Study to Assess Objective Skin Pigmentation Variation.', 'organization': {'class': 'OTHER', 'fullName': 'Leiden University Medical Center'}, 'officialTitle': 'Objective Skin Pigmentation Assessment in Healthy Volunteers and in Patients With Skin Disease: An Observational Study Using Non-invasive Skin Imaging', 'orgStudyIdInfo': {'id': 'NL-009794'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Healthy volunteers', 'description': 'Healthy volunteers with diverse skin tones'}, {'label': 'Patients', 'description': 'Any patient with a skin condition under treatment by a dermatologist with active lesions.'}]}, 'contactsLocationsModule': {'locations': [{'zip': '2333 ZG', 'city': 'Leiden', 'state': 'Leiden', 'status': 'RECRUITING', 'country': 'Netherlands', 'contacts': [{'name': 'Deepak M.W. Balak', 'role': 'CONTACT', 'email': 'd.m.w.balak@lumc.nl', 'phone': '+31715296273'}], 'facility': 'Leiden University Medical Center', 'geoPoint': {'lat': 52.15833, 'lon': 4.49306}}], 'centralContacts': [{'name': 'Deepak M.W. Balak', 'role': 'CONTACT', 'email': 'd.m.w.balak@lumc.nl', 'phone': '+31715296273'}, {'name': 'Lotte J. van den Oord', 'role': 'CONTACT', 'email': 'l.j.van_den_oord@lumc.nl', 'phone': '+31611164067'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Leiden University Medical Center', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Principal Investigator', 'investigatorFullName': 'dmwbalak', 'investigatorAffiliation': 'Leiden University Medical Center'}}}}