DOI: 10.1007/s00259-017-3753-xPages: 1-15

Optimal FDG PET/CT volumetric parameters for risk stratification in patients with locally advanced non-small cell lung cancer: results from the ACRIN 6668/RTOG 0235 trial

1. Hospital of the University of Pennsylvania, Department of Radiology

2. University of Minnesota, Department of Radiology

3. Brown University School of Public Health, Department of Biostatistics and Center for Statistical Sciences

4. Brown University School of Public Health, Center for Statistical Sciences

5. Emory University, Department of Biostatistics, Rollins School of Public Health

6. Mahidol University, Division of Nuclear Medicine, Department of Radiology, Faculty of Medicine Siriraj Hospital

7. ACR Center for Research and Innovation, American College of Radiology

8. University of Maryland Medical Center, Department of Radiation Oncology

9. Washington University School of Medicine, Mallinckrodt Institute of Radiology and the Alvin J. Siteman Cancer Center

10. Case Western Reserve University and University Hospitals Case Medical Center, Department of Radiation Oncology

Correspondence to:
Abass Alavi




In recent years, multiple studies have demonstrated the value of volumetric FDG-PET/CT parameters as independent prognostic factors in patients with non-small cell lung cancer (NSCLC). We aimed to determine the optimal cut-off points of pretreatment volumetric FDG-PET/CT parameters in predicting overall survival (OS) in patients with locally advanced NSCLC and to recommend imaging biomarkers appropriate for routine clinical applications.


Patients with inoperable stage IIB/III NSCLC enrolled in ACRIN 6668/RTOG 0235 were included. Pretreatment FDG-PET scans were quantified using semiautomatic adaptive contrast-oriented thresholding and local-background partial-volume-effect-correction algorithms. For each patient, the following indices were measured: metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUVmax, SUVmean, partial-volume-corrected TLG (pvcTLG), and pvcSUVmean for the whole-body, primary tumor, and regional lymph nodes. The association between each index and patient outcome was assessed using Cox proportional hazards regression. Optimal cut-off points were estimated using recursive binary partitioning in a conditional inference framework and used in Kaplan-Meier curves with log-rank testing. The discriminatory ability of each index was examined using time-dependent receiver operating characteristic (ROC) curves and corresponding area under the curve (AUC(t)).


The study included 196 patients. Pretreatment whole-body and primary tumor MTV, TLG, and pvcTLG were independently prognostic of OS. Optimal cut-off points were 175.0, 270.9, and 35.5 cm3 for whole-body TLG, pvcTLG, and MTV, and were 168.2, 239.8, and 17.4 cm3 for primary tumor TLG, pvcTLG, and MTV, respectively. In time-dependent ROC analysis, AUC(t) for MTV and TLG were uniformly higher than that of SUV measures over all time points. Primary tumor and whole-body parameters demonstrated similar patterns of separation for those patients above versus below the optimal cut-off points in Kaplan-Meier curves and in time-dependent ROC analysis.


We demonstrated that pretreatment whole-body and primary tumor volumetric FDG-PET/CT parameters, including MTV, TLG, and pvcTLG, are strongly prognostic for OS in patients with locally advanced NSCLC, and have similar discriminatory ability. Therefore, we believe that, after validation in future trials, the derived optimal cut-off points for primary tumor volumetric FDG-PET/CT parameters, or their more refined versions, could be incorporated into routine clinical practice, and may provide more accurate prognostication and staging based on tumor metabolic features.

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  • Accepted: Jun 5, 2017
  • Online: Jul 8, 2017

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