Neoplasms

All Conditions

Digestive System Diseases

Carcinoma

Carcinoma, Hepatocellular

Neoplasms, Glandular and Epithelial

Neoplasms by Histologic Type

Adenocarcinoma

Liver Neoplasms

Gastrointestinal Neoplasms

Digestive System Neoplasms

Gastrointestinal Diseases

Liver Diseases

All Drugs and Chemicals

Amino Acids

Immunomodulating Agents

Tyrosine Kinase Inhibitors

Tyrosine

Patients shown complete response (CR) and partial response (PR) after treatments. The clinical data and radiomics data are collected through electronic medical record system.

Patients shown progressive disease (PD) and stable disease (SD) after treatments. The clinical data and radiomics data are collected through electronic medical record system.

All patients with advanced HCC receive imaging evaluation before and after systemic treatments to assess the development of diseases.

radiological evaluation

Gang Chen, MD,PhD

As the most common type of primary liver cancer, hepatocellular carcinoma (HCC) has become a big challenge all over the world. Most patients are not available to curative resection when first diagnosed. There are a variety of treatment options for advanced HCC. However, due to the heterogeneity of HCC, the overall response rate (ORR) is not high for systemic therapies. Therefore, appropriate selection of patients who are suitable for individual systemic therapies is important for clinical decision-making.

Although major achievements have been acquired in diagnosis and treatment, the prognosis of hepatocellular carcinoma (HCC) is still unsatisfactory. Liver resection remains the main curative treatment for HCC, but most patients are at an advanced stage when first diagnosed, leading to be not available to curative therapies. There is a variety of treatment options for advanced HCC, such as transarterial chemoembolization (TACE), hepatic artery infusion chemotherapy (HAIC), targeted therapy (sorafenib and lenvatinib), immunotherapy, and the combination of different therapies. However, due to the heterogeneity of HCC, different patients respond differently to systemic therapies. The the overall response rate (ORR) is not satisfactory and most patients can not benefit from the systemic therapies. There is an urgent need to identify patients who are likely to have positive response to systemic therapies at the beginning before treatment. Therefore ,we want to collect the clinical information of patients with advanced HCC treated with systemic therapies, including demographic data , laboratory index, histological features, radiomics data. Patients are followed-up at a interval of 1 month after treatment, and the ORR, overall survival (OS), progression-free survival (PFS) are recorded. Then the treatment response are evaluated and the relationship between the clinical data and efficacy of systemic therapies are explored by machine learning methods. Then models based on clinical features or radiomics features are developed to predict response to different systemic therapies.

Predicting Response to Systemic Therapies for Hepatocellular Carcinoma(HCC)

Predicting Response to Systemic Therapies for Hepatocellular Carcinoma(HCC) Based on Clinical Variables and Radiomics Data With Machine Learning Methods

Tumor response are evaluated to the Modified Response Evaluation Criteria in Solid Tumors (mRECIST).

Overall survival was defined as the time from treatment to death for any reason.

Progression free survival was defined as the time from treatment to first progression or death.

The First Affiliated Hospital of Zhejiang Chinese Medical University

Eastern Hepatobiliary Surgery Hospital

Qilu Hospital of Shandong University

First Affiliated Hospital of Wenzhou Medical University

Clinical Professor, Principal Investigator

Musculoskeletal Diseases

Bone Neoplasms

Bone Diseases

Patients for whom follow-up data up to at least 1 year after surgery is available at the start of the study.

Both for patients not yet undergoing treatment intervention, at the start of the study, according to the inclusion criteria, both regarding those in follow-up for whom data are not available according to the time of observation required (1 year), will begin once all necessary authorizations have been obtained administrative requests

Nicola Salducca

Roberto Biagini, MD

This study aims to evaluate the osseointegration of 3D printed porous collars in hip and knee resection prostheses, in order to eliminate one of the causes of diaphyseal osteolysis, which often lead to loosening of the implants, and therefore to guarantee a further improvement in fixation of the implants in terms of both primary and secondary stability.

Non-interventional, retro-prospective, non-pharmacological multicenter pilot study.

The objective of the study is the radiological and clinical evaluation of collar osteointegration porous 3D printed in hip and knee resection prostheses.

Aims to enroll patients undergoing resection prosthesis surgery hip and knee with the use of 3D printed porous collars, performed according to normal practice clinic at the institutions participating in the study.

It is structured in a retrospective part which will evaluate the patients for whom follow-up data is available at the time of the start of the study up to at least 1 year after the operation. And a prospective part (both with regard to patients not yet subjected to intervention, at the start of the study, according to the inclusion criteria, both regarding those in follow-up for whom data are not available according to the time of observation required (1 year)) which will begin once all the necessary authorizations have been obtained administrative requests.

Radiological Evaluation of 3D Printed Porous Collars in Hip and Knee Resection Prostheses: Pilot Study.

Radiological Evaluation of 3D Printed Porous Collars in Resection Prostheses Hip and Knee: Pilot Study.

Osseointegration will be assessed by x-ray analysis 6 months and 1 year after surgery

Patient satisfaction/quality of life will be assessed 6 months and 1 year after surgery validated clinical questionnaire (Oxford score).

Bone remodeling will be evaluated by x-ray analysis 6 months and 1 year after surgery. Number of adverse events of any nature during follow-up. Highlight any inter-observer variability in the detection of radiological measurements.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Predicting Response to Systemic Therapies for Hepatocellular Carcinoma(HCC)	NCT05543304	Hepatocellular ... Effect of Drug	radiological ev...	18 Years - 80 Years	First Affiliated Hospital of Wenzhou Medical University
Predicting Response to Systemic Therapies for Hepatocellular Carcinoma(HCC)	NCT05543304	Hepatocellular ... Effect of Drug	radiological ev...	18 Years - 80 Years	First Affiliated Hospital of Wenzhou Medical University
Radiological Evaluation of 3D Printed Porous Collars in Hip and Knee Resection Prostheses: Pilot Study.	NCT06180525	Bone Tumor		18 Years -	Regina Elena Cancer Institute
Radiological Evaluation of 3D Printed Porous Collars in Hip and Knee Resection Prostheses: Pilot Study.	NCT06180525	Bone Tumor		18 Years -	Regina Elena Cancer Institute
Predicting Response to Systemic Therapies for Hepatocellular Carcinoma(HCC)	NCT05543304	Hepatocellular ... Effect of Drug	radiological ev...	18 Years - 80 Years	First Affiliated Hospital of Wenzhou Medical University
Predicting Response to Systemic Therapies for Hepatocellular Carcinoma(HCC)	NCT05543304	Hepatocellular ... Effect of Drug	radiological ev...	18 Years - 80 Years	First Affiliated Hospital of Wenzhou Medical University

Spots Global Cancer Trial Database for radiological evaluation