NCT06167863 is a clinical trial of radiomics in Radiomics, sponsored by Zhen Li.

Who is sponsoring NCT06167863?

NCT06167863 is sponsored by Zhen Li.

What drugs are being tested in NCT06167863?

Interventions in NCT06167863: radiomics.

What condition does NCT06167863 study?

NCT06167863 studies Radiomics, Deep Learning, Artificial Intelligence, Body Composition.

Is NCT06167863 still recruiting?

NCT06167863 is currently completed. Last updated 13 December 2023.

Last reviewed 2023-12-13 · How we verify

NCT06167863

Name: Drug Landscape Pharmaceutical Database
Creator: Drug Landscape
Published: 2026-01-01
License: https://creativecommons.org/licenses/by/4.0/

Retrospective Analysis of the Correlation Between Imaging Features and Pathology, Prognosis in Renal Tumors

Completed Last updated 13 December 2023

What this trial tests

trial testing radiomics in Radiomics in 1,000 participants. Completed in 31 October 2023.

Timeline

31 August 2023

Primary endpoint
31 October 2023

31 October 2023

Quick facts

Lead sponsor	Zhen Li
Status	Completed
Study type	OBSERVATIONAL
Enrollment	1,000
Start date	31 August 2023
Primary completion	31 October 2023
Estimated completion	31 October 2023
Sites	1 location across China

Drugs / interventions tested

radiomics

Conditions studied

Radiomics — all drugs for Radiomics →
Deep Learning — all drugs for Deep Learning →
Artificial Intelligence — all drugs for Artificial Intelligence →
Body Composition — all drugs for Body Composition →

Sponsor

Zhen Li — full company profile →

Who can join

Eligibility, any sex, with Radiomics or Deep Learning. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

Renal cell carcinoma (RCC) is the most common malignant tumor in the kidney with a high mortality rate. Traditional imaging techniques are limited in capturing the internal heterogeneity of the tumor. Radiomics provides internal features of lesions for precise diagnosis, prognosis prediction, and personalized treatment planning. Early and accurate diagnosis of renal tumors is crucial, but it's challenging due to morphological and pathological overlap between benign and malignant lesions. The accurate diagnosis of RCC, especially for small tumors, remains a significant challenge. Recent studies have shown a relationship between body composition, obesity, and renal tumors. Common indicators like body weight and BMI fail to reflect body composition accurately. Research on the role of body composition, including adipose tissue, in tumor pathology could improve clinical diagnosis and treatment planning.

Publications & conference data

1 peer-reviewed publication reference this trial (live from Europe PMC):

Incremental value of automatically segmented perirenal adipose tissue for pathological grading of clear cell renal cell carcinoma: a multicenter cohort study.
Li S, Zhou Z, Gao M, Liao Z, et al · · 2024 · cited 13× · PMID 38573065 · DOI 10.1097/js9.0000000000001358

Verify or expand the search:

Other trials of radiomics

Trials testing the same drug.

NCT05400304 — Radiomics Combined With Frozen Section Prediction Model for Spread Through Air Space in Lung Adenocarcinoma · unknown
NCT05387460 — Radiomics Based Multimodal Transvaginal Ultrasound Imaging in Endometrial Cancer · unknown
NCT04955522 — Multimodal Imaging Analysis of Spinal Tumors · completed
NCT03872362 — Radiomics Multifactorial Biomarker for Pulmonary Nodules · completed
NCT03221049 — Radiomics for Diagnosing Liver Diseases and Evaluating Progression · unknown

Other recruiting trials for Radiomics

Currently open trials in the same condition.

NCT07531446 — Construction of a Clinico-Imaging Collaborative Diagnostic Model for Dermatomyositis Combined With Interstitial Lung Dis · active not recruiting
NCT05761912 — Application of Ultrasound Radiomics in Ultrasound Fusion Targeted Prostate Biopsy · active not recruiting
NCT07332923 — Predicting HIF-2α Levels in Clear Cell Kidney Cancer Using Machine Learning · active not recruiting
NCT07050576 — Lymph Node Metastasis in Early Esophageal Squamous Cell Carcinoma · recruiting
NCT07030569 — RADIomics to Predict HER2 Status And T-DXd Efficacy in Metastatic Breast Cancer: the RADIOSPHER2 Study · recruiting

Other Zhen Li trials

Trials by the same sponsor.

NCT07001917 — To Explore the Value of Magnetic Resonance Imaging in Noninvasive Quantitative Evaluation of Graft Function After Simult · enrolling by invitation
NCT06946771 — Exploring the Correlation Between MRI Image Characteristics and Diagnosis, Pathology and Prognosis in Patients With Pros · recruiting

Verify against primary sources

ClinicalTrials.gov — authoritative US registry record
WHO ICTRP — international registry index
EU Clinical Trials Register
Sponsor press releases (Google)

Data sources for this page

Trial protocol + status: ClinicalTrials.gov NCT06167863 (US National Library of Medicine, public domain)
Publications: Europe PMC API search by NCT ID, retrieved 10 June 2026
Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
Sponsor: as reported to ClinicalTrials.gov by Zhen Li
Last refreshed: 13 December 2023

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06167863.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing