Clinical trials: Radiomics
Deep Endometriosis
Radiological Diagnostics in Patients With Deep Endometriosis
Endometriosis is a benign, chronic, recurrent disease characterised by the presence of endometrial glands and stroma outside the uterine cavity.
- Trial name
- NCT06799767
- Where
- Italy
- Volunteers
- 94 people
- Sponsor
- IRCCS Azienda Ospedaliero-Universitaria di Bologna
Renal Neoplasms, Pathology
Optimising Renal Tumour Management Through Artificial Intelligence Modules
The goal of this observational study is to improve the management of people with renal tumour by multimodal artificial intelligence(AI). It will also measure the accuracy of the predictions from AI models.
- Conditions
- Renal Neoplasms, Pathology, Renal Cell Cancer
- Trial name
- NCT06714916
- Where
- China
- Volunteers
- 2,100 people
- Sponsor
- Shao Pengfei
Refractory or Relapsed Non-Hodgkin's Lymphoma
Radiomics and Metabolomics in the Follow-up of CAR T-cells for Refractory or Relapsed Non-Hodgkin's Lymphoma
This is an interventionnal pilot study to investigate whether 18FDG radiomics or serum metabolomic signatures could be predictive or prognostic factors in the follow-up of patients receiving CAR T-cell therapy for refractory…
- Trial name
- CART-Omic (NCT05422521)
- Testing
- blood samples and 18FDG PET-CT exams
- Where
- France
- Volunteers
- 20 people
- Sponsor
- Centre Hospitalier Universitaire de Nice
Lung Cancer, Blood Biomarkers
AI for Lung Cancer Risk Definition in Computed Tomography Screening Programs
Low-dose computed tomography (LDCT) lung cancer (LC) screening can reduce mortality among heavy smokers, but there is a critical need to better identify people at higher risk and to reduce harms related to management of benign…
- Trial name
- NCT06320184
- Testing
- Artificial Intelligence risk model
- Where
- Italy
- Volunteers
- 650 people, healthy volunteers welcome
- Sponsor
- Fondazione IRCCS Istituto Nazionale dei Tumori, Milano
Renal Clear Cell Carcinoma, HIF-2α
Predicting HIF-2α Levels in Clear Cell Kidney Cancer Using Machine Learning
This project aims to conduct a multicenter retrospective study to collect clinical, CT imaging, and pathological data from patients.
- Conditions
- Renal Clear Cell Carcinoma, HIF-2α, Radiomics, Nomogram
- Trial name
- NCT07332923
- Where
- China
- Volunteers
- 500 people
- Sponsor
- First Affiliated Hospital of Fujian Medical University
NPC Patients, Nasopharyngeal Cancinoma (NPC)
Prospective Immuno-Radiomic Profiling in Nasopharyngeal Carcinoma Treated With Proton or Photon Chemoradiotherapy
To prospectively investigate and integrate radiomic and immunologic signatures in patients with nasopharyngeal carcinoma (NPC) treated with either proton or photon radiotherapy, with the aim of identifying biomarkers associated…
- Trial name
- IMPRINT (NCT07232680)
- Testing
- Proton chemoradiotherapy, Photon chemoradiotherapy
- Where
- Taiwan
- Volunteers
- 500 people
- Sponsor
- Cheng-En Hsieh
Non-Small Cell Lung Cancer
A Perioperative Comprehensive Diagnosis and Treatment System for Lung Cancer in the Era of Neoadjuvant Immunotherapy
The goal of this study is to develop and refine an integrated minimally invasive care pathway for resectable lung cancer in the immunotherapy era, establishing a novel precision perioperative immunotherapy paradigm encompassing…
- Trial name
- NCT07119190
- Volunteers
- 350 people
- Sponsor
- Peking University People's Hospital
Breast Cancer
Clinical Validation of Radiomics Artificial Intelligence: Application to Breast Cancer Treatment Planning
RadioVal will develop and implement interoperable solutions for clinical deployment of the radiomics tools, including information, training, and communication packages for clinicians and patients, as well as standard operating…
- Trial name
- RADIOVAL (NCT05070884)
- Testing
- The development of new clinical AI solutions to predict treatment response to neoadjuvant chemotherapy (NAC) in breast cancer
- Where
- 8 sites in Argentina, Austria and 6 more
- Volunteers
- 5,000 people
- Sponsor
- Instituto de Investigacion Sanitaria La Fe
Metastatic Colorectal Cancer
EORTC-endorsed, Prospective European Multicenter Imaging Survey and Protocol
A prospective, multicenter imaging Delphi survey among European radiological societies for mCRC imaging standardization.
- Trial name
- NCT04656782
- Testing
- Imaging survey, Facilitation
- Where
- Germany
- Volunteers
- 40 people
- Sponsor
- Ludwig-Maximilians - University of Munich
Anatomic Stage IV Breast Cancer AJCC v8, Clinical Stage IV Cutaneous Melanoma AJCC v8
18F-FMAU PET/CT and MRI for the Detection of Brain Tumors in Patients With Brain Cancer or Brain Metastases
This early phase I trial tests the use of a radioactive tracer (a drug that is visible during an imaging test) known as 18F-FMAU, for imaging with positron emission tomography/computed tomography (PET/CT) in patients with brain…
- Conditions
- Anatomic Stage IV Breast Cancer AJCC v8, Clinical Stage IV Cutaneous Melanoma AJCC v8, Glioma, Malignant Brain Neoplasm
- Trial name
- NCT04752267
- Testing
- Computed Tomography, 18F-FMAU, Multiparametric Magnetic Resonance Imaging
- Where
- United States
- Volunteers
- 10 people
- Sponsor
- University of Southern California
Glioma
MR Based Survival Prediction of Glioma Patients Using Artificial Intelligence
This registry aims to collect clinical, molecular and radiologic data including detailed survival data, clinical parameters, molecular pathology (1p/19q codeletion, MGMT methylation, IDH and TERTp mutations, etc) and…
- Trial name
- NCT04215211
- Testing
- Survival prediction for glioma patients
- Where
- China
- Volunteers
- 2,500 people
- Sponsor
- The First Affiliated Hospital of Zhengzhou University
Breast Diseases, Artificial Intelligence
Diagnosis Predictive Modle for Dense Density Breast Tissue Based on Radiomics
It is a prospective, observational cohort study of patients with dense breast tissue. The study was based on the radiomics and other clinicopathological information of patients to establish the diagnostic system for breast…
- Conditions
- Breast Diseases, Artificial Intelligence, Dense Breast Density, Predictive Cancer Model
- Trial name
- NCT04535466
- Where
- China
- Volunteers
- 1,000 people
- Sponsor
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Head and Neck Cancer, Neoadjuvant Therapy
Application of MRI Radiomics Features in Neoadjuvant Therapy of Head and Neck Squamous Cell Carcinoma
Head and neck squamous cell carcinoma is the sixth most common malignant tumor in the world. Neoadjuvant therapy, including neoadjuvant chemotherapy and immunotherapy, is recommended for patients with locally advanced head and…
- Conditions
- Head and Neck Cancer, Neoadjuvant Therapy, Immunotherapy, Chemotherapy
- Trial name
- NCT06755567
- Testing
- MRI-based radiomics-clinical model
- Where
- China
- Volunteers
- 750 people
- Sponsor
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Breast Cancer, Radiomics
Radiomics of Mp-MRI Assessing NAC Outcome in Breast Cancer
This is a single-arm, multicentre study that aims to assess whether Radiomics combining multiparametric MRI and clinical data could be a good predictor of the responses to neoadjuvant chemotherapy in Breast Cancer.
- Conditions
- Breast Cancer, Radiomics, Neoadjuvant Chemotherapy, Multi-parametric MRI
- Trial name
- NCT03592004
- Testing
- neoadjuvant chemotherapy
- Where
- China
- Volunteers
- 500 people
- Sponsor
- Chinese Academy of Sciences
Ovarian Cysts, Ovarian Cancer
Radiomics and Machine Learning in the Diagnosis of Ovarian Masses
The correct differential diagnosis between benign and malignant adnexal masses is the main goal of preoperative ultrasound diagnostics and is very important to plan the correct treatment for the patient in terms of surgical team…
- Trial name
- Multi-AROMA (NCT06342934)
- Testing
- Ultrasound
- Where
- Italy
- Volunteers
- 1,000 people
- Sponsor
- Fondazione IRCCS Istituto Nazionale dei Tumori, Milano
Liver Neoplasms, Radiation-Induced Liver Injury
Radiotherapy Safety for Liver Malignancies Using Post-Treatment Imaging
The goal of this retrospective observational study is to investigate the safety of radiation therapy for liver malignancies by analyzing data from patients who have already completed this treatment .
- Trial name
- NCT07346573
- Testing
- Clinically Delivered Radiation Therapy (e.g., SBRT/IMRT) for Liver Cancer
- Where
- China
- Volunteers
- 274 people
- Sponsor
- Cao peiguo
Lung Cancer (Diagnosis)
Predicting Immunotherapy Response and Survival of Lung Cancer Patients Using Artificial Intelligence and Radiomics (Radiology-AI-Lung)
CT imaging data from lung cancer (NSCLC and SCLC) patients prior to the initiation of immunotherapy (and possibly also after treatment) will be collected.
- Trial name
- NCT07059923
- Where
- China
- Volunteers
- 400 people
- Sponsor
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Digestive System Diseases, Gastrointestinal Neoplasms
Radiomics for Prediction of Lymph Node Metastasis in Gastric Cancer（RPLNM）(GIPMCS-1701)
This study proposes to establish a CT radiomics-based prediction model for identifying metastasis of each station lymph nodes in gastric cancer.
- Conditions
- Digestive System Diseases, Gastrointestinal Neoplasms, Digestive System Neoplasms, Gastrointestinal Diseases
- Trial name
- NCT03488446
- Where
- China
- Volunteers
- 500 people
- Sponsor
- Nanfang Hospital, Southern Medical University
Rectal Cancer
Radiomics-based Artificial Intelligence System to Predict Neoadjuvant Treatment Response in Rectal Cancer
In this study, investigators utilize a radiomics prediction model to predict the tumor response to neoadjuvant chemoradiotherapy (nCRT) before the nCRT is administered for patients with locally advanced rectal cancer (LARC).
- Trial name
- MRAI-pCR (NCT04273477)
- Where
- 3 sites in China
- Volunteers
- 100 people
- Sponsor
- Sixth Affiliated Hospital, Sun Yat-sen University
Hepatocellular Carcinoma (HCC), Downstaging
Radiomics Subtyping to Guide Surgery vs. Maintenance Therapy After HCC Downstaging
The goal of this observational study is to learn about the long-term treatment outcomes for patients with initially unresectable hepatocellular carcinoma (HCC) who achieve successful downstaging with the combination therapy of…
- Conditions
- Hepatocellular Carcinoma (HCC), Downstaging, Liver Resection, Lenvatinib
- Trial name
- NCT07581769
- Testing
- Liver resection, TACE plus Lenvatinib and PD1 inhibiter
- Where
- 2 sites in China
- Volunteers
- 500 people
- Sponsor
- First Affiliated Hospital, Sun Yat-Sen University