Currently, treatment and prognostic assessment for non-small cell lung cancer (NSCLC) depend primarily on the UICC/AJCC TNM (tumor, node, and metastasis) staging system. Modern 18F-FDG PET/CT plays an important role in the diagnosis, staging, and restaging of patients with NSCLC and provides three-dimensional (3D) metabolic and volumetric image data. However, the TNM staging system, based on surgical resectability of the tumor, has no mechanism to incorporate tumor volumetric data. Recently, we and other groups have found that baseline metabolic tumor burden (MTB) is a prognostic indicator of survival and is better than tumor standardized uptake value (SUV) measurement, in both surgically and non-surgically treated NSCLC patients, after adjusting for TNM stage, tumor SUV, and other clinical prognostic indicators including age, gender, performance status, treatment type, and tumor histology. Measurement of MTB on PET/CT is practical and reproducible with low inter-observer variability-with a mean concordance correlation coefficient greater than 0.94. It takes about 3.6 minutes to measure whole-body MTBs in each surgically treated patient with reference of clinical PET/CT and CT reports based our retrospective study. However, despite these promising findings, there is currently no effective method to incorporate MTB measurement into the TNM staging system or clinical management of NSCLC patients. To that end, we propose to develop a PET/CT-based volumetric prognostic (PVP) staging system that combines MTB measurements and the current TNM staging system for better prognostication in NSCLC. We propose two specific aims: (1) to develop a new PET/CT-based PVP staging system for NSCLC by developing two different competing mathematical models, and (2) to validate the novel PVP staging system with new datasets of patients from different institutions. Our long-term objective is to synergize the prognostic value of the current TNM staging system and volumetric MTB measurement. The public health significance is expected in the following three areas: 1) to improve patient treatment selection in NSCLC by providing more accurate tumor staging and risk- stratification, 2) to assist clinicians and patients by providing more accurate prognostic assessment, and 3) to help better define patient selection criteria in clinical trials. The innovations of the proposal include the following: 1) the proposed new PET/CT-based PVP staging system for more accurate prognostication in NSCLC is innovative;2) making use of 3D volumetric and metabolic data from PET/CT for NSCLC staging is innovative;and 3) making NSCLC staging more quantitative with the PVP staging system is innovative.

Public Health Relevance

Current treatment of the most common form of lung cancer depends on whether the cancer is confined within one lung or has spread to near-by lymph nodes or even distant organs, but does not take into account the size and metabolic activity of the cancer either in its original site or in lymph nodes or other organs. PET/CT scans provide tumor metabolic volume information, which we will use to develop a new staging method for doctors to use in determining more appropriate treatment for lung cancer. Our new staging method with tumor metabolic volume information can potentially lead to better cancer- treatment outcomes, thereby benefiting many patients who suffer from this most common form of cancer in the world.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21CA181885-01A1
Application #
8758482
Study Section
Special Emphasis Panel (ZCA1-PCRB-G (M1))
Program Officer
Zhang, Huiming
Project Start
2014-09-22
Project End
2016-08-31
Budget Start
2014-09-22
Budget End
2015-08-31
Support Year
1
Fiscal Year
2014
Total Cost
$219,501
Indirect Cost
$80,098
Name
University of Chicago
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
005421136
City
Chicago
State
IL
Country
United States
Zip Code
60637
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Finkle, Joshua H; Jo, Stephanie Y; Ferguson, Mark K et al. (2017) Risk-stratifying capacity of PET/CT metabolic tumor volume in stage IIIA non-small cell lung cancer. Eur J Nucl Med Mol Imaging 44:1275-1284
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