[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"raman-spectroscopy\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:raman-spectroscopy":30},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,2,0,[8,48],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":4,"eligibilityCriteria":15,"healthyVolunteers":11,"sex":16,"minAge":17,"maxAge":4,"enrollmentInfo":18,"targetDuration":4,"studyType":21,"phases":22,"briefSummary":24,"conditions":25,"keywords":4,"overallStatus":35,"whyStopped":4,"lastUpdateSubmitDate":36,"lastUpdatePostDateStruct":37,"startDateStruct":40,"completionDateStruct":42,"leadSponsor":44,"locationsCount":47},"100590208","raman-spectroscopy-in-the-diagnosis-of-extrahepatic-cholangiocarcinoma---a-pilot-study-100590208",false,"NCT06964425","Raman Spectroscopy in the Diagnosis of Extrahepatic Cholangiocarcinoma - a Pilot Study","Raman Spectroscopy in the Diagnosis of Extrahepatic Cholangiocarcinoma","Inclusion Criteria:\n\n* person older than 18 years, who has known extrahepatic cholangiocarcinoma and is indicated for ERCP\n\nExclusion Criteria:\n\n* disagreement with the study","ALL","18 Years",{"count":19,"type":20},20,"ESTIMATED","INTERVENTIONAL",[23],"NA","Diagnosis of extrahepatic cholangiocarcinoma is challenging because the yield of imaging and tissue sampling is limited. Raman spectroscopy is an optical method based on the analysis of scattered monochromatic light. Raman spectroscopy is able to provide a molecular 'fingerprint' of the tissue to determine its type. The aim of this pilot study was to develop a methodology for in vivo Raman spectroscopy in bile ducts to improve the current diagnostic capabilities of extrahepatic cholangiocarcinoma.",[26,27,28,29,30,31,32,33,34],"Cholangiocarcinoma, Extrahepatic","Cholangiocarcinoma of the Extrahepatic Bile Duct","Cholangiocarcinoma, Perihilar","Diagnosis","Raman Spectroscopy","Klatskin Tumor","Endoscopy","Biliary Stricture","Malignant Biliary Stricture","RECRUITING","2025-06-29",{"date":38,"type":39},"2025-07-02","ACTUAL",{"date":41,"type":39},"2023-02-04",{"date":43,"type":20},"2025-07-30",{"name":45,"class":46},"University Hospital Olomouc","OTHER",1,{"id":49,"slug":50,"hasResults":11,"nctId":51,"briefTitle":52,"officialTitle":53,"acronym":4,"eligibilityCriteria":54,"healthyVolunteers":55,"sex":16,"minAge":4,"maxAge":4,"enrollmentInfo":56,"targetDuration":58,"studyType":59,"phases":4,"briefSummary":60,"conditions":61,"keywords":78,"overallStatus":35,"whyStopped":4,"lastUpdateSubmitDate":89,"lastUpdatePostDateStruct":90,"startDateStruct":92,"completionDateStruct":94,"leadSponsor":96,"locationsCount":98},"100579293","raman-spectroscopy-based-deep-learning-model-for-early-pan-cancer-early-diagnosis-100579293","NCT06822413","Raman Spectroscopy-Based Deep Learning Model for Early Pan-Cancer Early Diagnosis","A Novel Raman Spectroscopy-Based Method for Pan-Cancers Early Diagnosis Supported by Deep Learning: A Prospective, Single-Arm, Multicentre Study","Inclusion Criteria:\n\n* Histopathological diagnosis of malignant tumors, including colorectal cancer, gastric cancer, hepatic cancer, pancreatic cancer, and esophageal cancer.\n* Patients in normal physiological conditions without any malignant tumors or precancerous lesions.\n* Patients with malignant tumor without recieving any interventions, including chemotherapy, surgery, radiotherapy, immunotherapy or other anti-tumor treatments.\n* Patients with a histopathological diagnosis of any precancerous lesions or non-malignant disease.\n\nExclusion Criteria:\n\n* Patients with metastatic tumors or in the condition with two or more kinds of malignant tumors at the same time\n* Post-cancer treatment patients.",true,{"count":57,"type":20},600,"1 Year","OBSERVATIONAL","The goal of this observational study is to explore whether a Raman-based, deep learning-assisted approach can be used to develop an effective method for early pan-cancer screening. The study includes healthy individuals, patients at risk of cancer, and patients with diagnosed cancers. The main questions it aims to answer are:\n\n* Evaluating the deep-learning model's accuracy and specificity in identifying cancer-specific features in Raman spectral data and determining whether this method can accurately classify patients based on risk.\n* Identifying which model is more adaptable to the Raman spectrum\n* Providing an interpretable analysis of the model-generated diagnosis Participants are already being diagnosed and follow-up to determine the type of cancer.",[62,63,64,65,66,67,68,30,69,70,71,72,73,74,75,76,77],"Cancer Diagnosis","Liver Cancer, Adult","Cancer Screening","Colorectal Cancer (CRC)","Gastric Cancers","Normal Physiology","Pancreatic Cancer, Adult","Deep Learning Model","Esophageal Cancer","Malignant Tumours","Precancerous Conditions","Pancreatitis","Adenoma Colon Polyp","Gastric Ulcer","Oesophagitis","Cirrhoses, Liver",[79,80,64,30,81,82,83,70,84,85,73,86,87,76,88],"Pan-cancer","Deep Learning Models","Colorectal Cancer","Pancreatic Cancer","Gastric Cancer","malignant tumour","Precancerous Condtions","Colorectal Adenoma","Gastirc Ulcer","Cirrhoses","2025-04-19",{"date":91,"type":39},"2025-04-24",{"date":93,"type":39},"2022-09-01",{"date":95,"type":20},"2025-07-28",{"name":97,"class":46},"Second Affiliated Hospital, School of Medicine, Zhejiang University",4]