Parametric Response Mapping of Coregistered Positron Emission Tomography and Dynamic Contrast Enhanced Computed Tomography to Identify Radioresistant Subvolumes in Locally Advanced Cervical Cancer

Abstract

Purpose: To identify subvolumes that may predict treatment response to definitive concurrent chemoradiation therapy using parametric response mapping (PRM) of coregistered positron emission tomography (PET) and dynamic contrast-enhanced (DCE) computed tomography (CT) in locally advanced cervical carcinoma.

Methods and materials: Pre- and midtreatment (after 23 ± 4 days of concurrent chemoradiation therapy) DCE CT and PET imaging were performed on 21 patients with cervical cancer who were enrolled in a pilot study to evaluate the prognostic value of CT perfusion for primary cervical cancer (NCT01805141). Three-dimensional coregistered maps of PET/CT standardized uptake value (SUV) and DCE CT blood flow (BF) were generated. PRM was performed using voxel-wise joint histogram analysis to classify voxels within the tumor as highly metabolic and perfused (SUV^hiBF^hi), highly metabolic and hypoxic (SUV^hiBF^lo), low metabolic activity and hypoxic (SUV^loBF^lo), or low metabolic activity and perfused (SUV^loBF^hi) tissue based on thresholds determined from population means of pretreatment PET SUV and DCE CT BF. Relationships between baseline pretreatment imaging metrics and relative changes in metabolic tumor volume (ΔMTV), calculated from before treatment and during treatment imaging, were determined using univariable and multivariable linear regression models.

Results: The relative volume of three PRM subvolumes significantly changed during treatment (SUV^hiBF^hi: P = .04; SUV^hiBF^lo: P = .0008; SUV^loBF^hi: P = .02), whereas SUV^loBF^lo did not (P = .9). Pretreatment PET SUV_max (r = -.58, P = .006), PET SUV_mean (ρ = -.59, P = .005), DCE CT BF_mean (r = -.50, P = .02), tumor volume (ρ = -.65, P = .001) and PRM SUV^hiBF^hi (ρ = -.59, P = .004) were negatively correlated with ΔMTV, whereas PRM SUV^loBF^lo was positively related to ΔMTV (r = .77, P < .0001). In a multivariable model that predicted ΔMTV, PRM SUV^loBF^lo, which combines both PET/CT and DCE CT, was the only significant variable (β = 1.825, P = .03), dominating both imaging modalities independently.

Conclusions: PRM was applied in locally advanced cervical carcinoma treated definitively with chemoradiation, and radioresistant subvolumes were identified that correlated with changes in MTV and predicted treatment response. Identification of these subvolumes may assist in clinical decision making to tailor therapies, such as brachytherapy, in an effort to improve patient outcomes.