[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100468116":3},{"organization":4,"armGroups":7,"interventions":22,"overallOfficials":27,"centralContacts":32,"locations":41,"responsibleParty":72,"collaborators":74,"id":91,"slug":10,"hasResults":92,"nctId":93,"briefTitle":94,"officialTitle":95,"acronym":96,"eligibilityCriteria":97,"healthyVolunteers":92,"sex":98,"minAge":99,"maxAge":10,"enrollmentInfo":100,"targetDuration":10,"studyType":103,"phases":10,"briefSummary":104,"conditions":105,"keywords":10,"overallStatus":44,"whyStopped":10,"lastUpdateSubmitDate":110,"lastUpdatePostDateStruct":111,"startDateStruct":114,"completionDateStruct":116,"leadSponsor":118,"locationsCount":119},{"fullName":5,"class":6},"Royal Marsden NHS Foundation Trust","OTHER",[8,14,18],{"label":9,"type":10,"description":11,"interventionNames":12},"Benign Nodules",null,"CT scans of patients with a new lung nodule(s) subsequently confirmed to be benign and in the context of a previous history of radically treated cancer, will be identified at participating NHS sites and recruited.",[13],"Other: Non-Interventional Study",{"label":15,"type":10,"description":16,"interventionNames":17},"Metastatic Nodules","CT scans of patients with a new lung nodule(s) subsequently confirmed to be metastatic in nature and in the context of a previous history of radically treated cancer, will be identified at participating NHS sites and recruited.",[13],{"label":19,"type":10,"description":20,"interventionNames":21},"Second Primary Lung Cancers","CT scans of patients with a new lung nodule(s) subsequently confirmed to be a new second primary lung cancer and in the context of a previous history of radically treated cancer, will be identified at participating NHS sites and recruited.",[13],[23],{"type":6,"name":24,"description":25,"armGroupLabels":26,"otherNames":10},"Non-Interventional Study","First nodule detection CT scans as per eligibility criteria will be used as input into in-house software to extract multiple radiomic features and used to develop a machine learning based classifier to differentiate nodule aetiology. Scans will also be used as input in to a deep learning\u002Fconvolutional neural network models to perform automated imaging classification.",[9,15,19],[28],{"name":29,"affiliation":30,"role":31},"Richard Lee","The Royal Marsden Hospitals NHS Trust","PRINCIPAL_INVESTIGATOR",[33,38],{"name":34,"role":35,"phone":36,"phoneExt":10,"email":37},"Sejal Jain","CONTACT","020 7808 2603","sejal.jain@rmh.nhs.uk",{"name":39,"role":35,"phone":36,"phoneExt":10,"email":40},"Laura Boddy","laura.boddy@rmh.nhs.uk",[42,60],{"facility":43,"status":44,"city":45,"state":10,"zip":46,"country":47,"cosmosGeoPoint":48,"geoPoint":53,"contacts":54},"The Royal Marsden NHS Foundation Trust (Chelsea Site)","RECRUITING","London","SW3 6JJ","United Kingdom",{"type":49,"coordinates":50},"Point",[51,52],-0.12574,51.50853,{"lat":52,"lon":51},[55,57,59],{"name":34,"role":35,"phone":56,"phoneExt":10,"email":37},"02078082603",{"name":39,"role":35,"phone":58,"phoneExt":10,"email":40},"07414643915",{"name":29,"role":31,"phone":10,"phoneExt":10,"email":10},{"facility":61,"status":44,"city":45,"state":10,"zip":62,"country":47,"cosmosGeoPoint":63,"geoPoint":65,"contacts":66},"Royal Brompton Hospital","SW3 6NP",{"type":49,"coordinates":64},[51,52],{"lat":52,"lon":51},[67,70],{"name":68,"role":35,"phone":56,"phoneExt":10,"email":69},"Hardeep Kalsi","hardeep.kalsi@rmh.nhs.uk",{"name":71,"role":31,"phone":10,"phoneExt":10,"email":10},"Anand Deveraj",{"type":73,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR",[75,77,80,82,85,87,89],{"name":76,"class":6},"Institute of Cancer Research, United Kingdom",{"name":78,"class":79},"National Institute for Health Research, United Kingdom","OTHER_GOV",{"name":81,"class":6},"Royal Brompton & Harefield NHS Foundation Trust",{"name":83,"class":84},"Royal Marsden Partners Cancer Alliance","UNKNOWN",{"name":86,"class":6},"Imperial College London",{"name":88,"class":6},"Oxford University Hospitals NHS Trust",{"name":90,"class":6},"National Heart and Lung Institute","100468116",false,"NCT05375591","AI & Radiomics for Stratification of Lung Nodules After Radically Treated Cancer","Artificial Intelligence & Radiomics for Stratification Of Lung Nodules After Radically Treated Cancer (AI-SONAR)","AI-SONAR","Inclusion Criteria:\n\n* Confirmed history of previous radically or curative-intent treated solid organ cancer within 10 years of new index CT thoracic scan demonstrating a new pulmonary nodule and either of the following:\n\n  * Biopsy confirming previous malignancy with MDT consensus and successful cancer resolution\u002Fremission following anti-cancer treatment on interval imaging or blood assay analysis\n  * Where biopsy was not possible\u002Fconfirmed for previous malignancy, MDT consensus outcome confirming cancer (+\u002F- calculated Herder score \\>80% if applicable) and decision to treat as malignancy with subsequent resolution\u002Fremission following anti-cancer treatment on interval imaging or blood assay analysis\n* Radical treatment for previous cancer defined as either of the following:\n\n  * Surgical resection\n  * Radical radiotherapy or stereotactic beam radiotherapy\n  * Radical chemotherapy\n  * Radical chemo-radiotherapy\n  * Multi-modality treatment with any of the above\n* New pulmonary nodule ground truth known\n\n  * Scan data showing 2-year stability (based on diameter or volumetry) or resolution in cases of benign disease\n  * Scan data showing progressive nodule enlargement or increase in nodule number on interval imaging with MDT consensus (+\u002F- PET with Herder score \\>80% if applicable) determining metastatic disease or new primary malignancy\n  * Biopsy sampling confirming benign disease or malignancy and in cases of malignancy, metastasis or new primary lung cancer\n* CT scan slice thickness ≤ 2.5mm\n* Nodule size ≥ 5mm\n\nExclusion Criteria:\n\n* CT Imaging \\> 10 years old\n* Non-solid haematological malignancies including leukaemia\n* Cases of radically treated primary cancer disease with early oligometastatic recurrence treated radically","ALL","18 Years",{"count":101,"type":102},1000,"ESTIMATED","OBSERVATIONAL","This study will assess the utility of radiomics and artificial intelligence approaches to new lung nodules in patients who have undergone radical treatment for a previous cancer.",[106,107,108,109],"Indeterminate Pulmonary Nodules","Lung Metastases","Second Primary Cancer","Lung Cancer","2022-05-17",{"date":112,"type":113},"2022-05-24","ACTUAL",{"date":115,"type":113},"2021-10-13",{"date":117,"type":102},"2026-11-01",{"name":5,"class":6},2]