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Consortium for Imaging and Biomarkers (CIB)

The Consortium for Imaging and Biomarkers (CIB) seeks to improve cancer screening, early detection of aggressive cancer, assessment of cancer risk, and cancer diagnosis by integrating imaging strategies with biomarkers into complementary approaches.

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About CIB

The Consortium for Imaging and Biomarkers aims to integrate imaging strategies and biomarker methodologies into a singular complementary approach to cancer detection. Investigators Work in multi-disciplinary teams to perform collaborative studies, exchange information, share knowledge and leverage common resources.

Overdiagnosis (finding cancers that will never affect a person’s health) and false positives (test results that show cancer when none is there) present significant clinical problems in the prevention, detection and treatment of cancer. There is a need to more accurately identify early-stage aggressive cancers and distinguish lesions that are life threatening from those that are not.

The Consortium for imaging and Biomarkers Research Units develop, optimize, and clinically validate novel methods to:

  • Detect aggressive cancers at the earliest stages possible;
  • Reduce overdiagnosis;
  • Reduce false positive tests; and
  • Identify lethal cancers from non-lethal disease.

The goal of the Consortium for imaging and Biomarkers is to develop improved methods for the early detection of aggressive cancer by managing overdiagnosis, reducing false positives and identifying lethal cancers from non-lethal disease using strategies aimed at effective integration and validation of imaging and biomarkers.

Funding Opportunities

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Grantee Details

PI Name Sort descending PI Organization Title Grant Number Program Official
Badve, Sunil S.

Emory University
United States

Early prediction of lethal phenotypes in triple negative breast cancer using multiscale, multi-modality platforms 5R01CA281932-02 Wendy Wang, Ph.D., M.Sc.
Barton, Jennifer Kehlet

University Of Arizona
United States

Ovarian Cancer Detection with Blood- and Imaging-Based Biomarkers 5R01CA260399-04 Guillermo Marquez, Ph.D.
Beretta, Laura

University Of Tx Md Anderson Can Ctr
United States

Early Detection of Hepatocellular Carcinoma 5R01CA195524-09 Matthew Young, Ph.D.
Grimm, Lars J

Duke University
United States

Dynamic imaging and tissue biomarker models to delineate indolent from aggressive breast calcifications 4R01CA271237-04 Guillermo Marquez, Ph.D.
Lampe, Paul D.

Fred Hutchinson Cancer Center
United States

Autoantibodies to tumor-derived neoepitopes as biomarkers and immunoPET agents for the early detection of small cell lung cancer 5R01CA281801-03 Guillermo Marquez, Ph.D.
Maldonado, Fabien

Vanderbilt University Medical Center
United States

Novel Integrative Approach for the Early Detection of Lung Cancer using Repeated Measures 5R01CA253923-05
Mallick, Parag Kumar

Stanford University
United States

Pathomic Predictors of Prostate Cancer Progression 5R01CA249899-05
Nappi, Lucia

Provincial Health Services Authority
United States

Integrating investigational miR371a-3p with conventional radiology imaging for earlier and more precise detection of active germ cell malignancy: A BCC/SWOG/S1823 secondary use of data collaboration. 5R37CA264798-03 Guillermo Marquez, Ph.D.
Saenger, Yvonne Margaret

Albert Einstein College Of Medicine
United States

Applying pathomics to establish a biosignature for aggressive skin melanoma 5R01CA260375-05 Guillermo Marquez, Ph.D.
Shah, Sohrab P

Sloan-Kettering Inst Can Research
United States

Exploiting markers of genomic instability in high-risk pre-invasive ovarian cancer 5R01CA281928-03 Christos Patriotis, Ph.D., M.Sc.
Taouli, Bachir

Icahn School Of Medicine At Mount Sinai
United States

Abbreviated MRI for HCC screening in cirrhotic patients 5R01CA249765-05 Guillermo Marquez, Ph.D.
Tewari, Ashutosh K

Icahn School Of Medicine At Mount Sinai
United States

Artificial intelligence enabled Stroma-Weighted Automated Grading system to improve risk stratification in Black Men 1R01CA290438-01A1 Indu Kohaar, Ph.D., M.Phil., M.Sc.
Thakur, Mathew Laxman

Thomas Jefferson University
United States

Noninvasive, Uniplex, Molecular, Pathomic Urinary Assay for Detection of Prostate Cancer 5R01CA249921-05
Wang, Thomas D

University Of Michigan At Ann Arbor
United States

Early detection of colorectal cancer in the traditional and serrated pathways 5R01CA249851-05 Guillermo Marquez, Ph.D.
Wang, Thomas D

University Of Michigan At Ann Arbor
United States

Peptide multimer for early detection of hepatocellular carcinoma 5R01CA285303-02 Guillermo Marquez, Ph.D.

Program Contact(s)

Sudhir Srivastava, Ph.D., M.P.H.
Email: sudhir.srivastava@nih.gov

Guillermo Marquez, Ph.D.
Email: guillermo.marquez@nih.gov