Monitoring early response to chemoradiotherapy with 18F-FMISO dynamic PET in head and neck cancer

Abstract

Purpose: There is growing recognition that biologic features of the tumor microenvironment affect the response to cancer therapies and the outcome of cancer patients. In head and neck cancer (HNC) one such feature is hypoxia. We investigated the utility of ¹⁸F-fluoromisonidazole (FMISO) dynamic positron emission tomography (dPET) for monitoring the early microenvironmental response to chemoradiotherapy in HNC.

Experimental design: Seventy-two HNC patients underwent FMISO dPET scans in a customized immobilization mask (0-30 min dynamic acquisition, followed by 10 min static acquisitions starting at ∼95 min and ∼160 min post-injection) at baseline and early into treatment where patients have already received one cycle of chemotherapy and anywhere from five to ten fractions of 2 Gy per fraction radiation therapy. Voxelwise pharmacokinetic modeling was conducted using an irreversible one-plasma two-tissue compartment model to calculate surrogate biomarkers of tumor hypoxia (k ₃ and Tumor-to-Blood Ratio (TBR)), perfusion (K ₁ ) and FMISO distribution volume (DV). Additionally, Tumor-to-Muscle Ratios (TMR) were derived by visual inspection by an experienced nuclear medicine physician, with TMR > 1.2 defining hypoxia.

Results: One hundred and thirty-five lesions in total were analyzed. TBR, k ₃ and DV decreased on early response scans, while no significant change was observed for K ₁ . The k ₃ -TBR correlation decreased substantially from baseline scans (Pearson's r = 0.72 and 0.76 for mean intratumor and pooled voxelwise values, respectively) to early response scans (Pearson's r = 0.39 and 0.40, respectively). Both concordant and discordant examples of changes in intratumor k ₃ and TBR were identified; the latter partially mediated by the change in DV. In 13 normoxic patients according to visual analysis (all having lesions with TMR = 1.2), subvolumes were identified where k ₃ indicated the presence of hypoxia.

Conclusion: Pharmacokinetic modeling of FMISO dynamic PET reveals a more detailed characterization of the tumor microenvironment and assessment of response to chemoradiotherapy in HNC patients than a single static image does. In a clinical trial where absence of hypoxia in primary tumor and lymph nodes would lead to de-escalation of therapy, the observed disagreement between visual analysis and pharmacokinetic modeling results would have affected patient management in <20% cases. While simple static PET imaging is easily implemented for clinical trials, the clinical applicability of pharmacokinetic modeling remains to be investigated.

Keywords: 18F-FMISO; Dynamic PET; Head and neck cancer; Hypoxia; Treatment response.

Figure 1.

Flowchart of patient selection and inclusion. *According to the visual analysis by nuclear medicine physician.

Figure 2.. Voxelwise distributions of investigated parameters derived from baseline and early response FMISO dynamic PET scans.

(A) Normalized distribution histogram of voxelwise TBR values at baseline (blue) and after 1 cycle of chemoradiotherapy (red), derived from pooled data. (B) Equivalent histogram for k₃. (C) Equivalent histogram for DV. (D) Equivalent histogram for K₁. (E) Equivalent histogram for v_B.

Figure 3.. Correlation between k₃ and TBR as derived from baseline and early response FMISO dynamic PET scans.

(A) Scatterplot (one point per patient tumor) of the mean intratumor k₃ versus TBR at baseline, with linear regression fit (solid line). The points are color-coded according to the magnitude of the mean intratumor DV at baseline. (B) k₃-TBR intensity histogram consisting of the pooled voxels from all tumors from baseline data, with the linear regression fit (solid line). (C) Scatterplot of mean intratumor k₃ and TBR from early response scans, with included linear regression fit (dashed line). Superimposed is the linear regression fit from baseline data (A; solid line). (D) Corresponding intensity histogram from early response scans, with included linear regression fit (dashed line). Superimposed is the linear regression fit from baseline data (B; solid line).

Figure 4.. Example of concordant and discordant changes in k₃ and TBR.

(A) Patient #1 with 37 cm³ T4aN2c, HPV-positive, p16-positive tumor originating in the tonsil. Results from baseline and early response scans are presented in top and bottom rows, respectively. From left to right: Sagittal view of the late 10-min FMISO PET/CT scan, tumor-to-blood ratio (TBR) map of intratumor voxels, k₃ map representing hypoxia-mediated entrapment of FMISO and FMISO distribution volume (DV), representing overall concentration of unbound FMISO relative to blood. For this patient, both TBR and k₃ decreased after 1 cycle of chemoradiotherapy, while DV did not change substantially. ΔTBR = −1.26 (ΔTBR_max = −2.82), Δk₃ = −0.0066 min⁻¹ (Δk_3,max = −0.0160 min⁻¹), ΔDV =−0.01. (B) Corresponding images for Patient #2 with 44 cm³ T1N2b, HPV-negative, p16-negative tumor originating in the supraglottic larynx. For this patient, TBR decreased, while k₃ increased. Decreased DV further contributed to underestimation of TBR. ΔTBR = −0.17 (ΔTBR_max = −0.71), Δk₃ = 0.0026 min⁻¹ (Δk_3,max = 0.0059 min⁻¹), ΔDV =−0.24.