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

NCT06167863 | Completed

• 1 other identifier: TJ-IRB20230893
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Radiomics; Deep Learning; Artificial Intelligence; Body Composition

Outcome Measures

Primary Outcomes (1)

• WHO/ISUP grade pathologically

  The WHO ISUP grade of the tumor indicated in the post-operative surgical pathology report

  1 month

Secondary Outcomes (1)

• pathological T stage

  1 month

Study Arms (2)

WHO ISUP grading high

high-grade refer to Grades 3 and 4 tumours with an unfavourable prognosis

Diagnostic Test: radiomics

WHO ISUP grading low

low-grade refer to Grades 1 and 2 tumours with a promising prognosis

Diagnostic Test: radiomics

Interventions

radiomics DIAGNOSTIC_TEST

extracted image features from CT or MRI

WHO ISUP grading high; WHO ISUP grading low

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

patients diagnosed with renal tumors

You may qualify if:

• Our hospital admits patients with renal tumors in the urology department. The diagnosis is confirmed through surgical pathology, and the patients' imaging data is obtained through contrast-enhanced Computed Tomography or Magnetic Resonance examination in the radiology department.

You may not qualify if:

• Patients who have undergone puncture, microwave, interventional therapies before the examination, or who have received chemotherapy or radiotherapy;
• Patients with poor respiratory coordination, resulting in significant image artifacts;
• Lesions are cystic, without discernible regions of interest, or with multiple regions of necrosis within the lesion;
• Lesions are too small, with a diameter of less than 1cm;
• Thin-slice imaging is not available in the CT scan.

Sponsors & Collaborators

• Zhen Li: lead

Study Sites (1)

Zhen Li

Wuhan, Hubei, 430030, China

Location

Related Publications (1)

• Li S, Zhou Z, Gao M, Liao Z, He K, Qu W, Li J, Kamel IR, Chu Q, Zhang Q, Li Z. Incremental value of automatically segmented perirenal adipose tissue for pathological grading of clear cell renal cell carcinoma: a multicenter cohort study. Int J Surg. 2024 Jul 1;110(7):4221-4230. doi: 10.1097/JS9.0000000000001358.

  PMID: 38573065 DERIVED

MeSH Terms

Interventions

Radiomics

Intervention Hierarchy (Ancestors)

Diagnostic Imaging; Diagnostic Techniques and Procedures; Diagnosis

Study Officials

• Li Dr

  Tongji Hospital

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: professor

Study Record Dates

• First Submitted: November 30, 2023
• First Posted: December 13, 2023
• Study Start: August 31, 2023
• Primary Completion: October 31, 2023
• Study Completion: October 31, 2023
• Last Updated: December 13, 2023

Record last verified: 2023-12

Locations

CN (1)