[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100592022":3},{"organization":4,"armGroups":7,"interventions":13,"overallOfficials":20,"centralContacts":24,"locations":32,"responsibleParty":49,"collaborators":51,"id":55,"slug":56,"hasResults":57,"nctId":58,"briefTitle":59,"officialTitle":60,"acronym":61,"eligibilityCriteria":62,"healthyVolunteers":57,"sex":63,"minAge":64,"maxAge":19,"enrollmentInfo":65,"targetDuration":19,"studyType":68,"phases":69,"briefSummary":71,"conditions":72,"keywords":74,"overallStatus":35,"whyStopped":19,"lastUpdateSubmitDate":79,"lastUpdatePostDateStruct":80,"startDateStruct":83,"completionDateStruct":85,"leadSponsor":87,"locationsCount":88},{"fullName":5,"class":6},"Cliniques universitaires Saint-Luc- Université Catholique de Louvain","OTHER",[8],{"label":9,"type":6,"description":10,"interventionNames":11},"Whole body MRI","There is only one cohort where each patient have the standard of care follow up (PET\u002FCT) and Whole body MRI- ZTE sequence for the study",[12],"Device: MRI",[14],{"type":15,"name":16,"description":17,"armGroupLabels":18,"otherNames":19},"DEVICE","MRI","Whole body MRI including ZTE sequences",[9],null,[21],{"name":22,"affiliation":5,"role":23},"Frédéric Lecouvet","PRINCIPAL_INVESTIGATOR",[25,29],{"name":22,"role":26,"phone":27,"phoneExt":19,"email":28},"CONTACT","+3227642793","frederic.lecouvet@saintluc.uclouvain.be",{"name":30,"role":26,"phone":19,"phoneExt":19,"email":31},"Perrine Triqueneaux","perrine.triqueneaux@saintluc.uclouvain.be",[33],{"facility":34,"status":35,"city":36,"state":19,"zip":19,"country":37,"countryCode":38,"cosmosGeoPoint":39,"geoPoint":44,"contacts":45},"Cliniques universitaires Saint-Luc","RECRUITING","Brussels","Belgium","BE",{"type":40,"coordinates":41},"Point",[42,43],4.34878,50.85045,{"lat":43,"lon":42},[46,47,48],{"name":22,"role":26,"phone":27,"phoneExt":19,"email":28},{"name":30,"role":26,"phone":19,"phoneExt":19,"email":31},{"name":22,"role":23,"phone":19,"phoneExt":19,"email":19},{"type":50,"investigatorFullName":19,"investigatorTitle":19,"investigatorAffiliation":19,"oldNameTitle":19,"oldOrganization":19},"SPONSOR",[52],{"name":53,"class":54},"General Electric","INDUSTRY","100592022","pseudo-scanner-mri-sequences-for-the-detection-of-bone-lesions-in-multiple-myeloma-100592022",false,"NCT06988020","\"Pseudo-scanner\" MRI Sequences for the Detection of Bone Lesions in Multiple Myeloma","Evaluation of Optimised Whole-body MRI Examinations Incorporating \"Pseudo-scanner\" Sequences (ZTE, \"Zero Echo Time\" AND Lava Flex) for the Detection of Bone Lesions in Multiple Myeloma","MM-ZTE-II","Inclusion Criteria:\n\nPatient with newly diagnosed multiple myeloma, for whom bone imaging is required for staging.\n\n* Recurrent patient after intensive treatment (high dose chemotherapy, bone marrow transplant, etc.).\n* Patient requiring a PET \u002F CT considered as the technique of choice in these stages of the disease.\n\nExclusion Criteria:\n\n* Implanted material incompatible with MRI.\n* Severe claustrophobia.\n* Pregnant women","ALL","18 Years",{"count":66,"type":67},45,"ESTIMATED","INTERVENTIONAL",[70],"NA","Recent work has confirmed the diagnostic performance of pseudo-CT sequences for detecting osteolytic lesions. Their integration into whole body MRI (WB MRI) could transform the diagnostic approach to MM, by allowing a combined assessment of bone marrow involvement, tissue viability and osteolysis, during a single non-irradiating imaging examination. Since the preliminary work mentioned above, optimizations have been made to the pseudo-CT sequences, including the addition of deep learning (correcting noise in the images) and the correction of chemical shift artifact (linked to the coexistence of hydrated tissue and fatty tissue), which carry real hope of improving their diagnostic potential and accuracy.",[73],"Multiple Myeloma Bone Disease",[75,76,77,78],"bone","imaging","mri","multiple myeloma","2026-04-23",{"date":81,"type":82},"2026-04-24","ACTUAL",{"date":84,"type":82},"2025-04-22",{"date":86,"type":67},"2027-11",{"name":5,"class":6},1]