[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"radiology\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:radiology":24},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,6,0,[8,42,74,101,119,144],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":13,"acronym":4,"eligibilityCriteria":14,"healthyVolunteers":15,"sex":16,"minAge":4,"maxAge":4,"enrollmentInfo":17,"targetDuration":4,"studyType":20,"phases":4,"briefSummary":21,"conditions":22,"keywords":27,"overallStatus":29,"whyStopped":4,"lastUpdateSubmitDate":30,"lastUpdatePostDateStruct":31,"startDateStruct":34,"completionDateStruct":36,"leadSponsor":38,"locationsCount":41},"100599663","ai-driven-multimodal-imaging-integration-for-diagnosis-and-prognostication-of-digestive-system-diseases-100599663",false,"NCT07087418","AI-Driven Multimodal Imaging Integration for Diagnosis and Prognostication of Digestive System Diseases","Inclusion Criteria:\n\n* Patients with multimodal-confirmed diagnoses (clinical, imaging, endoscopic, and pathological) of:\n\n  * Inflammatory bowel disease (IBD; Crohn's disease or ulcerative colitis)\n  * Intestinal tuberculosis\n  * Behçet's disease\n* Availability of ≥1 technically adequate CT or MR scan with high-quality colonoscopy performed within ±1 month of imaging.\n\nExclusion Criteria:\n\n* ・Suboptimal imaging quality (e.g., low-dose artifacts, metal artifacts)\n\n  * Inadequate bowel preparation for endoscopy\n  * Incomplete examinations due to poor tolerance",true,"ALL",{"count":18,"type":19},5000,"ESTIMATED","OBSERVATIONAL","The goal of this observational, retrospective and prospective study is to develop a noninvasive disease assessment system by leveraging artificial intelligence (AI) to comprehensively analyze multi-modal imaging features, including magnetic resonance enterography (MRE) and computed tomography enterography (CTE), for the diagnosis and prognostication of digestive diseases. To this end, the investigators retrospectively enrolled imaging, endoscopic, and clinical data from 21 centers across China to construct and iteratively optimize the AI model. The model's performance will be prospectively validated in two centers, and its accuracy in lesion localization will be verified through real-world deployment in endoscopy suites.",[23,24,25,26],"Digestive Diseases","Radiology","AI (Artificial Intelligence)","Imaging",[24,26,23,28],"Artificial Intelligence","RECRUITING","2026-04-08",{"date":32,"type":33},"2026-04-13","ACTUAL",{"date":35,"type":33},"2025-07-01",{"date":37,"type":19},"2026-08-01",{"name":39,"class":40},"First Affiliated Hospital, Sun Yat-Sen University","OTHER",1,{"id":43,"slug":44,"hasResults":11,"nctId":45,"briefTitle":46,"officialTitle":46,"acronym":47,"eligibilityCriteria":48,"healthyVolunteers":11,"sex":49,"minAge":50,"maxAge":4,"enrollmentInfo":51,"targetDuration":53,"studyType":20,"phases":4,"briefSummary":54,"conditions":55,"keywords":59,"overallStatus":29,"whyStopped":4,"lastUpdateSubmitDate":64,"lastUpdatePostDateStruct":65,"startDateStruct":67,"completionDateStruct":69,"leadSponsor":71,"locationsCount":73},"100543512","national-registry-of-surgical-treatment-and-percutaneous-cryoablation-of-parietal-endometriosis-100543512","NCT06356831","National Registry of Surgical Treatment and Percutaneous Cryoablation of Parietal Endometriosis","Endomercyo","Inclusion Criteria:\n\n* Presence of parietal endometriosis: with suggestive clinical and imaging criteria (MRI and ultrasound)\n* Symptomatic parietal endometriosis (VAS \\> 3 OR bothersome bleeding OR reported impact on quality of life)\n\nExclusion Criteria:\n\n* Endometriosis not affecting the anterior wall of the abdomen (as deep pelvic muscle: ilio-psoas, obturators, perineal, ischio-anal fossa)\n* Minor patient (\\\u003C 18 years)\n* Pregnant patient at any trimester\n* Patient with hemostasis disorders (constitutional or acquired)\n* Patient with systemic infection or localized scar infection upon inclusion.\n* Patient with contraindications to MRI\n* Female patient with a planned medical or surgical procedure for the duration of the study that may interfere with the proper conduct of the study.\n* Patient unable to understand the information provided\n* Patient who is not affiliated to the social security system\n* Patient under curatorship or tutorship\n* Patient with a nodule of primary or secondary malignant tumor origin","FEMALE","18 Years",{"count":52,"type":19},300,"3 Years","National multicentric registry of a cohort of patient with suffering parietal endometriosis, carried out by a multidisciplinary radiosurgery team",[56,57,58,24],"Endometriosis","Cryotherapy Effect","Surgical",[60,61,62,63],"endometriosis","Cryo ablation","Surgical operation","radiology","2025-11-26",{"date":66,"type":33},"2025-11-28",{"date":68,"type":33},"2024-06-15",{"date":70,"type":19},"2028-01-31",{"name":72,"class":40},"Centre Hospitalier Intercommunal Creteil",18,{"id":75,"slug":76,"hasResults":11,"nctId":77,"briefTitle":78,"officialTitle":79,"acronym":4,"eligibilityCriteria":80,"healthyVolunteers":11,"sex":16,"minAge":50,"maxAge":81,"enrollmentInfo":82,"targetDuration":84,"studyType":20,"phases":4,"briefSummary":85,"conditions":86,"keywords":88,"overallStatus":91,"whyStopped":4,"lastUpdateSubmitDate":92,"lastUpdatePostDateStruct":93,"startDateStruct":95,"completionDateStruct":97,"leadSponsor":99,"locationsCount":41},"100584524","three-in-one-stop-computed-topography-angiographycta-and-ct-perfusionctp-in-cerebrovascular-disease-100584524","NCT06890468","Three-in-One Stop Computed Topography Angiography(CTA) and CT Perfusion(CTP) in Cerebrovascular Disease","Three-in-One Stop Computed Topography Angiography and CT Perfusion in Cerebrovascular Disease","Inclusion Criteria:\n\n* Age≥18 \\\u003C100years\n* Head and neck artery stenosis\u002Focclusion, moyamoya disease, aneurysm, artery dissection, etc., may include patients with acute stroke, chronic cerebral ischemia, and asymptomatic patients. After clinical assessment, CT perfusion imaging is required\n* The image quality meets the requirements of diagnosis and post-processing\n* Patients who follow the scanning strategy to complete the examination\n* The patient or his or her family agrees to provide clinical data and follow-up\n* Patients or their families sign informed consent forms\n\nExclusion Criteria:\n\n* \\\u003C 18 years old\n* People who are allergic to iodine contrast agents, or who cannot be tested temporarily due to taking metformin or aminoglycoside drugs\n* Renal failure patient\n* Severe cardiac insufficiency\n* Severe liver damage\n* Patients with an expected survival of less than 1 year\n* Patients with cerebrovascular diseasePregnant woman","100 Years",{"count":83,"type":19},1000,"1 Year","This research takes patients with cerebrovascular diseases as the research subjects and employs the experimental design of a prospective cohort study, aiming to innovatively develop and validate a \"one-stop\" multimodal CT examination scheme. The 301-CTAP multimodal CT technique implies that three modalities are acquired through a single collection, including head and neck CTA (head and neck CTA), multiphase CTA imaging of the brain (multiphase CTA), and CT perfusion imaging of the brain (CT perfusion).",[24,87],"Vascular Diseases",[89,90],"CTP","head and neck CTA","NOT_YET_RECRUITING","2025-03-21",{"date":94,"type":33},"2025-03-24",{"date":96,"type":19},"2025-03-16",{"date":98,"type":19},"2029-12-30",{"name":100,"class":40},"Xin Lou",{"id":102,"slug":103,"hasResults":11,"nctId":104,"briefTitle":105,"officialTitle":105,"acronym":4,"eligibilityCriteria":106,"healthyVolunteers":11,"sex":16,"minAge":50,"maxAge":81,"enrollmentInfo":107,"targetDuration":4,"studyType":20,"phases":4,"briefSummary":109,"conditions":110,"keywords":4,"overallStatus":91,"whyStopped":4,"lastUpdateSubmitDate":111,"lastUpdatePostDateStruct":112,"startDateStruct":114,"completionDateStruct":116,"leadSponsor":118,"locationsCount":4},"100561413","artificial-intelligent-image-processing-and-diagnosis-of-pulmonary-vessels-in-ct-100561413","NCT06589843","Artificial Intelligent Image Processing and Diagnosis of Pulmonary Vessels in CT","Inclusion Criteria:\n\n* Age ≥18≤100 years old Scan the pulmonary artery and its major branches Patients with suspected pulmonary embolism who received CTPA had a set of CTPA and CT scans The image quality meets the requirements of diagnosis and post-processing Patients who completed the examination in accordance with the data collection criteria Clinical data and follow-up were complete\n\nExclusion Criteria:\n\n* Age \\<18 years or age \\>100 years The image is incomplete or incorrect Pulmonary artery absent or underenhanced Severe motion artifacts or image noise affect evaluation of pulmonary embolism History of aortic reconstruction, replacement, or stent implantation Congenital variations in the whole or important branches of the aorta in adults (e.g. bovine aortic arch, abnormal right subclavian artery) Severe hypovolemia and hemodynamic instability Severe heart failure with low ejection fraction Dialysis patient",{"count":108,"type":19},15000,"In this study, patients with chest pain, lung cancer, pulmonary embolism, and routine inpatient physical examination were selected as the research objects, and the experimental design of retrospective cohort study was adopted to carry out artificial intelligence analysis related to pulmonary vascular diseases in patients with multi-dimensional big data. The multi-modal CT acquisition process included plain scan CT(NCCT) and CT pulmonary angiography (CTPA). Ctpa-like image effects can be simulated or reconstructed by non-enhanced plain scan CT images, so that CTPA-like image quality can be obtained without injecting contrast agent. The synthetic CTPA images were further analyzed by artificial intelligence to assist doctors in the intelligent diagnosis of pulmonary vascular diseases.",[24,87],"2024-09-06",{"date":113,"type":33},"2024-09-19",{"date":115,"type":19},"2024-09-10",{"date":117,"type":19},"2029-09-01",{"name":100,"class":40},{"id":120,"slug":121,"hasResults":11,"nctId":122,"briefTitle":123,"officialTitle":123,"acronym":4,"eligibilityCriteria":124,"healthyVolunteers":11,"sex":16,"minAge":50,"maxAge":81,"enrollmentInfo":125,"targetDuration":4,"studyType":20,"phases":4,"briefSummary":126,"conditions":127,"keywords":129,"overallStatus":29,"whyStopped":4,"lastUpdateSubmitDate":135,"lastUpdatePostDateStruct":136,"startDateStruct":138,"completionDateStruct":140,"leadSponsor":142,"locationsCount":41},"100486447","deep-enhanced-imaging-in-stroke-and-vascular-neurology-100486447","NCT05614193","Deep Enhanced Imaging in Stroke and Vascular Neurology","Inclusion Criteria:\n\n* suspecting to have experienced stroke or cerebral ischemia and needed to undergo brain imaging and vascular imaging including CT or MRI\n* no history of kidney failure\n* a minimum age of 18 years\n* obtained written informed consent\n\nExclusion Criteria:\n\n* severe movement artifacts\n* incidental finding of tumor lesion or craniocerebral surgery history\n* poor imaging failed to perform deep learning method\n* women who pregnancy",{"count":83,"type":19},"To investigate the performance of enhanced computed tomography (CT) or magnetic resonance (MR) imaging by deep learning relative to conventional CT or MR imaging in brain stroke and vascular neurology. We expect that the deep enhanced imaging method can shorten the time stay in the imaging session of stroke patients, optimize the overall imaging quality and improve the patients' care in imaging session.",[24,128,87],"Cerebral Stroke",[130,131,132,133,134],"Deep learning","Medical imaging","Cerebral stroke","Cerebrovascular disease","Vascular imaging","2023-02-07",{"date":137,"type":33},"2023-02-08",{"date":139,"type":33},"2022-12-01",{"date":141,"type":19},"2027-12-31",{"name":143,"class":40},"Chinese PLA General Hospital",{"id":145,"slug":146,"hasResults":11,"nctId":147,"briefTitle":148,"officialTitle":148,"acronym":4,"eligibilityCriteria":149,"healthyVolunteers":11,"sex":16,"minAge":50,"maxAge":150,"enrollmentInfo":151,"targetDuration":153,"studyType":20,"phases":4,"briefSummary":154,"conditions":155,"keywords":4,"overallStatus":29,"whyStopped":4,"lastUpdateSubmitDate":159,"lastUpdatePostDateStruct":160,"startDateStruct":162,"completionDateStruct":164,"leadSponsor":166,"locationsCount":41},"100367949","correlation-of-radiological-lesions-with-vestibular-function-in-patients-with-bilateral-vestibulopathy-100367949","NCT04070937","Correlation of Radiological Lesions With Vestibular Function in Patients With Bilateral Vestibulopathy","Inclusion Criteria:\n\n* must meet the Barany criteria for bilateral vestibulopathy: bilaterally pathological horizontal angu- lar VOR gain \\\u003C0.6, measured by the video-HIT5 or scleral-coil technique and\u002For\n* reduced caloric response6 (sum of bither- mal max. peak SPV on each side \\\u003C6◦\u002Fsec7) and\u002For\n* reduced horizontal angular VOR gain \\\u003C0.1 upon sinusoidal stimulation on a rota- tory chair (0.1 Hz, Vmax = 50◦ \u002Fsec) and a phase lead \\>68 degrees (time constant \\\u003C5 sec).\n* must be 18 or older\n\nExclusion Criteria:\n\n* \\\u003C 18 y\n* does not meet Barany criteria for BV\n* contraindication for CT and MR imaging","90 Years",{"count":152,"type":19},40,"2 Years","In 2014 radiologic lesions were detected at one or more semicircular canals using CT and MR imaging of temporal bone in subjects carrying the p.P51S mutation in COCH. These lesions are believed to present at more advanced stages of the hearing and vestibular deterioration. Since then, other authors have described similar lesions in advanced non-genetic hearing and vestibular impairment as well.\n\nThe purpose of this study is therefore to assess the radiologic investigation using CT and MR imaging of temporal bone to all subjects presenting with bilateral vestibulopathy, using the Barany criteria, compared to the p.P51S population.",[156,157,158,24],"Hearing Loss, Sensorineural","Bilateral Vestibular Deficiency","DFNA9","2021-08-24",{"date":161,"type":33},"2021-08-25",{"date":163,"type":33},"2019-09-01",{"date":165,"type":19},"2026-10-30",{"name":167,"class":40},"Jessa Hospital"]