A generalized total effective entrapment metric (gTEE) to quantify burden of homogeneous and heterogeneous tumors in PET imaging for enhanced clinical outcome prediction
Oncoloc PET images provide valuable information that can enable enhanced prognosis of disease. Nonetheless, such information is commonly simplified significantly in routine clinical assessment to meet workflow constraints. Examples for typical FDG PET metrics include: (i) SUVmax, (2) total lesion glycolysis (TLG), and (3) metabolic tumor volume (MTV). We have derived and implemented a novel metric for quantification of tumor burden, inspired in essence by a model of generalized effective uniform dose (gEUD) as used in radiation therapy. The proposed metric, denoted generalized total effective entrapment (gTEE), is particularly attractive as it encompasses the abovementioned commonly invoked metrics, and generalizes them, for both homogeneous and heterogeneous tumors, using a single parameter a. We evaluated this new metric on 113 patients with T2, T3 and T4 squamous cell cancer of the oropharynx (85 males and 28 females; mean-age: 58.8+/-10.3). Primary tumors were segmented from FDG PET images using three different segmentation methods. We utilized overall survival (OS), progression-free survival (PFS) and event-free survival (EFS) as patient-related outcomes for imaging biomarker derivation. Kaplan-Meier survival analysis was performed, where the subjects, given any specific parameter a, were subdivided into two groups using the median threshold, from which the hazard ratios (HR) were computed. Our results indicated enhanced patient outcome prediction for the gTEE parameter a around 1. Overall, the methodology enables placement of differing degrees of emphasis on tumor volume vs. uptake for different studies to enable enhanced clinical outcome prediction.
