Quantitative Imaging Metrics From CECT in Measuring Disease Response or Progression in Patients With Kidney Cancer

Renal Cell Carcinoma Clinical Trial

Official title:

CT Metrology: Quantitative Imaging Metrics With Advanced Visualization Tools for Cancer Imaging

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT02370290
• Other study ID #: 4K-13-2
• Secondary ID: NCI-2014-02547HS
• Status: Completed
• Phase: N/A
• First received: February 17, 2015
• Last updated: March 1, 2016
• Start date: April 2014
• Est. completion date: February 2016

Study information

• Verified date: March 2016
• Source: University of Southern California
• Contact: n/a
• Is FDA regulated: No
• Health authority: United States: Institutional Review Board
• Study type: Observational

Clinical Trial Summary

This pilot research trial studies quantitative imaging metrics derived from contrast enhanced computed tomography (CECT) in enhancing assessment of disease status in patients with kidney cancer. Quantitative imaging is the extraction of quantifiable features from radiological images for the assessment of disease status. Collecting quantitative imaging metrics from CECT imaging may help doctors predict tumor aggressiveness and nuclear grade (tumor stage) and assess treatment response and prognosis in cancer imaging.

Description:

PRIMARY OBJECTIVES:

I. To investigate the role of quantitative imaging metrics (QIM) as a potential DIAGNOSTIC biomarker.

II. To investigate if QIM parameters can differentiate clear cell renal cell carcinoma (RCC) from papillary RCC.

III. To evaluate the tumor grade of the target lesion as assessed by QIM from CECT for agreement with the pathological (Fuhrman) grade.

IV. To investigate the role of QIM as a potential PROGNOSTIC biomarker. V. To develop a novel method of calculating renal tumor contact surface area (CSA) using advanced image-processing technology (MATLAB®, 3 dimension [D] Synapse) and predict peri-operative variables such as blood loss, operative time and post-operative estimated glomerular filtration rate (eGFR) in patients undergoing partial nephrectomy (PN).

VI. To develop QIM that would help in predicting postoperative functional outcomes such as predicted surgically resected volume and postoperative glomerular filtration rate (GFR).

OUTLINE:

Patients' clinical and imaging data are collected from routine multiphase CECT imaging and used to establish and validate the classification/prediction rule for QIM.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 74
• Est. completion date: February 2016
• Est. primary completion date: December 2015
• Accepts healthy volunteers: No
• Gender: Both
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Subjects with a renal mass who are scheduled for surgery for presumed RCC

• Subjects scheduled for standard of care contrast enhanced CT examination at USC Norris Comprehensive Cancer Center

• Subjects competent to sign study specific written informed consent

Exclusion Criteria:

• Subjects who are pregnant

• Subjects who cannot consent for themselves

Study Design

Observational Model: Case-Only, Time Perspective: Prospective

Related Conditions & MeSH terms

• Carcinoma, Renal Cell
• Renal Cell Carcinoma

Intervention

Other:
• Medical Chart Review
Clinical and imaging information collected
• Informational Intervention
Clinical and imaging data collected

Locations

Country	Name	City	State
United States	USC Norris Comprehensive Cancer Center	Los Angeles	California

Sponsors (2)

Lead Sponsor	Collaborator
University of Southern California	National Cancer Institute (NCI)

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Agreement between QIM predicted and pathologically determined tumor class (clear cell renal cell carcinoma [ccRCC] vs papillary [p]RCC)	Cohen's kappa coefficient will be used to examine the agreement between QIM predicted and pathologically determined tumor class (ccRCC vs. pRCC).	Baseline	No
Primary	Agreement between QIM predicted and pathologically determined tumor (Fuhrman) grade	Examined using weighted kappa coefficient.	Baseline	No
Primary	Agreement between QIM predicted and clinically observed perioperative measurements such as blood loss, operative time, and eGFR	Examined using two-way random single measure with absolute agreement.	Baseline	No
Primary	Agreement between QIM predicted and clinical determined postoperative eGFR	Examined using two-way random single measure with absolute agreement.	Baseline	No