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

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

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT02370290
Enrollment
74
Registered
2015-02-24
Start date
2014-04-30
Completion date
2016-02-29
Last updated
2016-03-03

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Renal Cell Carcinoma

Brief 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.

Detailed 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.

Interventions

OTHERMedical Chart Review

Clinical and imaging information collected

OTHERInformational Intervention

Clinical and imaging data collected

Sponsors

National Cancer Institute (NCI)
CollaboratorNIH
University of Southern California
Lead SponsorOTHER

Study design

Observational model
CASE_ONLY
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

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

Design outcomes

Primary

MeasureTime frameDescription
Agreement between QIM predicted and pathologically determined tumor class (clear cell renal cell carcinoma [ccRCC] vs papillary [p]RCC)BaselineCohen's kappa coefficient will be used to examine the agreement between QIM predicted and pathologically determined tumor class (ccRCC vs. pRCC).
Agreement between QIM predicted and pathologically determined tumor (Fuhrman) gradeBaselineExamined using weighted kappa coefficient.
Agreement between QIM predicted and clinically observed perioperative measurements such as blood loss, operative time, and eGFRBaselineExamined using two-way random single measure with absolute agreement.
Agreement between QIM predicted and clinical determined postoperative eGFRBaselineExamined using two-way random single measure with absolute agreement.

Countries

United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026