Renal Tumour Imaging Using MRI

NCT07173140 | Active Not Recruiting

• 1 other identifier: 162190
• Study Type: interventional
• Target: 30
• Locations: 1 country
• Sites: 1

Brief Summary

This study investigates whether new types of MRI scans can tell the difference between different kidney tumours before surgery. Currently, imaging scans can detect kidney tumours and their size, but they aren't effective at determining the tumour type or its aggressiveness. Biopsies are an option, but they are invasive and may miss important cancerous cells. The aim is to use imaging to determine which tumours are aggressive so they can be treated early while avoiding unnecessary treatment of benign tumours. Patients with small renal tumours (≤ 7 cm) who meet the other inclusion and exclusion criteria will be asked to have an additional MRI scan at University College London Hospital prior to surgery. The imaging findings will be compared to the histology result from the removed tumour. In 10 patients the histology will be targeted to a specific location in the tumour based on the imaging. 10 patients will undergo a repeat MRI \<14 d apart to test whether the MRI scans can give the same answer twice (the test repeatability). The study is expected to run for 24 months and is funded by NIHR. The chief investigator for the study is Dr Richard Hesketh (rhesketh@ucl.ac.uk).

Conditions

Renal Cancer; MRI; Small Renal Mass; Kidney Cancers

Keywords

Renal cancer; MRI; Small Renal Mass; Kidney Cancer

Outcome Measures

Primary Outcomes (2)

• Diagnostic accuracy of proton density fat fraction (PDFF) to differentiate different histological subtypes of renal tumours.

  PDFF mean values will be calculated for each tumour in arms 2 and 3. Following surgery the means for each histological subtype will be calculated and tested for statistical significance.

  1 year

• Repeatability of proton density fat fraction (PDFF) measurements.

  Participants in arm 3 will undergo repeat scanning with a short time interval between scans. The repeatability of PDFF measurements will be assessed using within subject standard deviation, repeatability coefficients and Bland-Altman analysis.

  1 year

Study Arms (3)

Histological characterisation of renal tumours

NO INTERVENTION

Histological samples of ten patients with tumour histology will be retreived from the Royal Free Hospital Biobank. Slides will be stained using H\&E and CD34 and cell size, stromal space and vascularity will be estimated and used to inform diffusion weighted imaging models.

Comparison of microstructural MRI to histology

EXPERIMENTAL

10 patients with small renal tumours will undergo microstructural MRI. Following MRI the tumours will be surgically resected. The MRI will be co-registered with histology. The degree of correlation between the MRI and underlying histology will be determined.

Diagnostic Test: MRI

Repeatability of MRI of small renal masses

EXPERIMENTAL

The repeatability of the MRI scan of the small renal mass will be determined by participants undergoing a repeat MRI examination shortly after the first (within 14 d) on the same scanner.

Diagnostic Test: MRI

Interventions

MRI DIAGNOSTIC_TEST

Participants undergo an additional MRI scan using novel MRI sequences

Comparison of microstructural MRI to histology; Repeatability of MRI of small renal masses

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Aged 18 and over
• Confirmed renal tumour ≤ 7 cm planned for surgical resection
• Willing and able to provide written informed consent
• Able to lie supine for the duration of an MRI

You may not qualify if:

• Contraindication to MRI e.g., cardiac pacemaker
• Contraindication to MR contrast agents
• Pregnancy
• Breastfeeding
• Deranged renal function (eGFR \<30) in the last three months.
• Previous treatment of the renal tumour e.g., ablation, radiotherapy

Sponsors & Collaborators

• University College, London: lead
• Royal Free Hospital NHS Foundation Trust: collaborator
• University College London Hospitals: collaborator

Study Sites (1)

University College London

London, United Kingdom

Location

Related Publications (1)

• Sen S, Smith L, Caselton L, Clemente J, Tran M, Punwani S, Atkinson D, Hesketh RL, Panagiotaki E. Dual deep learning approach for non-invasive renal tumour subtyping with VERDICT-MRI. Npj Imaging. 2026 Jan 6;4(1):2. doi: 10.1038/s44303-025-00135-6.

  PMID: 41495369 DERIVED

MeSH Terms

Conditions

Kidney Neoplasms

Condition Hierarchy (Ancestors)

Urologic Neoplasms; Urogenital Neoplasms; Neoplasms by Site; Neoplasms; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Kidney Diseases; Urologic Diseases; Male Urogenital Diseases

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NON RANDOMIZED
• Masking: NONE
• Masking Details: Scan readers are blinded to lesion histology at the time of region of interest (ROI) drawing
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: August 18, 2025
• First Posted: September 15, 2025
• Study Start: November 20, 2024
• Primary Completion: June 19, 2025
• Study Completion: September 30, 2025
• Last Updated: September 15, 2025

Record last verified: 2025-09

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, ICF
• Time Frame: Immediately

Locations

GB (1)