Spatiotemporal analysis of tumor uptake patterns in dynamic (18)FDG-PET and dynamic contrast enhanced CT

Dynamic 2-Deoxy-2-[18F]Fluoro-D-Glucose Positron Emission Tomography for Chemotherapy Response Monitoring of Breast Cancer Xenografts

PURPOSE

Non-invasive response monitoring can potentially be used to guide therapy selection for breast cancer patients. We employed dynamic 2-deoxy-2-[¹⁸F]fluoro-D-glucose positron emission tomography ([¹⁸F]FDG PET) to evaluate changes in three breast cancer xenograft lines in mice following three chemotherapy regimens.

PROCEDURES

Sixty-six athymic nude mice bearing bilateral breast cancer xenografts (two basal-like and one luminal-like subtype) underwent three 60 min [¹⁸F]FDG PET scans. Scans were performed prior to and 3 and 10 days after treatment with doxorubicin, paclitaxel, or carboplatin. Tumor growth was monitored in parallel. A pharmacokinetic compartmental model was fitted to the tumor uptake curves, providing estimates of transfer rates between the vascular, non-metabolized, and metabolized compartments. Early and late standardized uptake values (SUV_E and SUV_L, respectively); the rate constants k ₁, k ₂, and k ₃, and the intravascular fraction v _B were estimated. Changes in tumor volume were used as a response measure. Multivariate partial least-squares regression (PLSR) was used to assess if PET parameters could model tumor response and to identify PET parameters with the largest impact on response.

RESULTS

Treatment responders had significantly larger perfusion-related parameters (k ₁ and k ₂) and lower metabolism-related parameter (k ₃) than non-responders 10 days after the start of treatment. These findings were further supported by the PLSR analysis, which showed that k ₁ and k ₂ at day 10 and changes in k ₃ explained most of the variability in response to therapy, whereas SUV_L and particularly SUV_E were of lesser importance.

CONCLUSIONS

Overall, rate parameters related to both tumor perfusion and metabolism were associated with tumor response. Conventional metrics of [¹⁸F]FDG uptake such as SUV_E and SUV_L apparently had little relation to tumor response, thus necessitating full dynamic scanning and pharmacokinetic analysis for optimal evaluation of chemotherapy-induced changes in breast cancers.

Hypoxia in cervical cancer: from biology to imaging

PURPOSE

Hypoxia imaging may improve identification of cervical cancer patients at risk of treatment failure and be utilized in treatment planning and monitoring, but its clinical potential is far from fully realized. Here, we briefly describe the biology of hypoxia in cervix tumors of relevance for imaging, and evaluate positron emission tomography (PET) and magnetic resonance imaging (MRI) techniques that have shown promise for assessing hypoxia in a clinical setting. We further discuss emerging imaging approaches, and how imaging can play a role in future treatment strategies to target hypoxia.

METHODS

We performed a PubMed literature search, using keywords related to imaging and hypoxia in cervical cancer, with a particular emphasis on studies correlating imaging with other hypoxia measures and treatment outcome.

RESULTS

Only a few and rather small studies have utilized PET with tracers specific for hypoxia, and no firm conclusions regarding preferred tracer or clinical potential can be drawn so far. Most studies address indirect hypoxia imaging with dynamic contrast-enhanced techniques. Strong evidences for a role of these techniques in hypoxia imaging have been presented. Pre-treatment images have shown significant association to outcome in several studies, and images acquired during fractionated radiotherapy may further improve risk stratification. Multiparametric MRI and multimodality PET/MRI enable combined imaging of factors of relevance for tumor hypoxia and warrant further investigation.

CONCLUSIONS

Several imaging approaches have shown promise for hypoxia imaging in cervical cancer. Evaluation in large clinical trials is required to decide upon the optimal modality and approach.

Variability of dynamic 18F-FDG-PET data in breast cancer xenografts

BACKGROUND

A murine breast cancer xenograft model was employed to evaluate inter- and intra-variability of various parameters derived from dynamic positron emission tomography with [18F]-fluorodeoxyglucose as tracer (FDG-PET).

MATERIAL AND METHODS

Seventeen female athymic nude foxn1/nu mice with bilaterally implanted triple-negative basal-like ductal carcinoma (MAS98.12) breast cancer xenografts underwent a dynamic PET scan over an hour after injection of approximately 10 MBq FDG. Inter-animal data were obtained from the entire animal cohort, while intra-animal data were from four mice receiving an additional scan after one or two days. Standardised uptake values (SUVmax, SUVmean and SUVmedian) were estimated for all tumours at different time points. Tumour uptake was analysed with a kinetic two-compartment model for estimation of pharmacokinetic parameters. The coefficient of variation (CV) was calculated for all PET-derived metrics.

RESULTS

The CVs for SUVmean and SUVmedian were typically 10-20% for the tumours, depending on the time post-injection and group (intra vs. inter). The CV for SUVmax was mostly higher. The variability in the pharmacokinetic parameters ranged from 23 to almost 150%.

CONCLUSIONS

SUVmean and SUVmedian show less variability than SUVmax. The pharmacokinetic tumour metrics again display much greater variability than the SUV-based metrics. However, it is generally not known which of these metrics that best represents cancer aggressiveness and their use may still depend on the research questions addressed.

Biologic targets identified from dynamic 18FDG-PET and implications for image-guided therapy

PURPOSE

The outcome of biologic image-guided radiotherapy depends on the definition of the biologic target. The purpose of the current work was to extract hyperperfused and hypermetabolic regions from dynamic positron emission tomography (D-PET) images, to dose escalate either region and to discuss implications of such image guided strategies.

METHODS

Eleven patients with soft tissue sarcomas were investigated with D-PET. The images were analyzed using a two-compartment model producing parametric maps of perfusion and metabolic rate. The two image series were segmented and exported to a treatment planning system, and biological target volumes BTVper and BTVmet (perfusion and metabolism, respectively) were generated. Dice's similarity coefficient was used to compare the two biologic targets. Intensity-modulated radiation therapy (IMRT) plans were generated for a dose painting by contours regime, where planning target volume (PTV) was planned to 60 Gy and BTV to 70 Gy. Thus, two separate plans were created for each patient with dose escalation of either BTVper or BTVmet.

RESULTS

BTVper was somewhat smaller than BTVmet (209 ± 170 cm(3) against 243 ± 143 cm(3), respectively; population-based mean and s.d.). Dice's coefficient depended on the applied margin, and was 0.72 ± 0.10 for a margin of 10 mm. Boosting BTVper resulted in mean dose of 69 ± 1.0 Gy to this region, while BTVmet received 67 ± 3.2 Gy. Boosting BTVmet gave smaller dose differences between the respective non-boost DVHs (such as D98).

CONCLUSIONS

Dose escalation of one of the BTVs results in a partial dose escalation of the other BTV as well. If tumor aggressiveness is equally pronounced in hyperperfused and hypermetabolic regions, this should be taken into account in the treatment planning.

Dynamic (18)F-FDG-PET for monitoring treatment effect following anti-angiogenic therapy in triple-negative breast cancer xenografts

INTRODUCTION

Dynamic (18)F-FDG PET allows the study of glucose distribution in tissues as a function of time and space. Using pharmacokinetics, the temporal uptake pattern of (18)F-FDG may be separated into components reflecting perfusion and metabolism. Bevacizumab is an angiogenesis inhibitor which prevents the growth of new blood vessels, and may potentially lead to normalization of the blood circulation in the tumor. The purpose of the study was to explore the use of dynamic PET as a tool for monitoring treatment effect, reflected by changes in perfusion and metabolism.

MATERIALS AND METHODS

Twelve athymic nude mice, bearing the bilateral triple-negative human breast cancer xenograft MAS98.12 were treated with bevacizumab (5 mg/kg i.p.). Dynamic PET data was acquired prior to and 24 and 72 hours after treatment for 1 hour after injection of 10 MBq (18)F-FDG and fitted with a FDG two-tissue compartment model. The changes in the rate constants k1, k3, MRFDG and the vascular fraction νB were assessed. To evaluate the effect of treatment regimes, 30 mice, randomized in 5 groups, received either vehicle (0.9% NaCl), bevacizumab (5 mg/kg i.p.), doxorubicin (8 mg/kg i.v.) or bevacizumab and doxorubicin either together, or doxorubicin 24 hours after bevacizumab treatment. Tumor volume was measured twice a week.

RESULTS

The perfusion-related rate parameter k1 and the metabolic rate constant k3 decreased significantly 24 hours after treatment. This decrease was followed by an increase, albeit non-significant, at 72 hours post treatment. Doxorubicin given 24 hours after bevacizumab showed less antitumor effect compared to concomitant treatment.

CONCLUSIONS

Dynamic PET can detect changes in tumor perfusion and metabolism following anti-angiogenic therapy in mouse xenograft models. Longitudinal dynamic PET, used to assess the efficacy of anti-angiogenic treatment, can identify the time frame of potential tumor vasculature re-normalization and allow optimal timing of supplementary therapy (radiation or chemotherapy).

Functional imaging to monitor vascular and metabolic response in canine head and neck tumors during fractionated radiotherapy

Radiotherapy causes alterations in tumor biology, and non-invasive early assessment of such alterations may become useful for identifying treatment resistant disease. The purpose of the current work is to assess changes in vascular and metabolic features derived from functional imaging of canine head and neck tumors during fractionated radiotherapy. Material and methods. Three dogs with spontaneous head and neck tumors received intensity-modulated radiotherapy (IMRT). Contrast-enhanced cone beam computed tomography (CE-CBCT) at the treatment unit was performed at five treatment fractions. Dynamic (18)FDG-PET (D-PET) was performed prior to the start of radiotherapy, at mid-treatment and at 3-12 weeks after the completion of treatment. Tumor contrast enhancement in the CE-CBCT images was used as a surrogate for tumor vasculature. Vascular and metabolic tumor parameters were further obtained from the D-PET images. Changes in these tumor parameters were assessed, with emphasis on intra-tumoral distributions. Results. For all three patients, metabolic imaging parameters obtained from D-PET decreased from the pre- to the inter-therapy session. Correspondingly, for two of three patients, vascular imaging parameters obtained from both CE-CBCT and D-PET increased. Only one of the tumors showed a clear metabolic response after therapy. No systematic changes in the intra-tumor heterogeneity in the imaging parameters were found. Conclusion. Changes in vascular and metabolic parameters could be detected by the current functional imaging methods. Vascular tumor features from CE-CBCT and D-PET corresponded well. CE-CBCT is a potential method for easy response assessment when the patient is at the treatment unit.

Quantitative dynamic ¹⁸FDG-PET and tracer kinetic analysis of soft tissue sarcomas

PURPOSE

To study soft tissue sarcomas using dynamic positron emission tomography (PET) with the glucose analog tracer [(18)F]fluoro-2-deoxy-D-glucose ((18)FDG), to investigate correlations between derived PET image parameters and clinical characteristics, and to discuss implications of dynamic PET acquisition (D-PET).

MATERIAL AND METHODS

D-PET images of 11 patients with soft tissue sarcomas were analyzed voxel-by-voxel using a compartment tracer kinetic model providing estimates of transfer rates between the vascular, non-metabolized, and metabolized compartments. Furthermore, standard uptake values (SUVs) in the early (2 min p.i.; SUVE) and late (45 min p.i.; SUVL) phases of the PET acquisition were obtained. The derived transfer rates K1, k2 and k3, along with the metabolic rate of (18)FDG (MRFDG) and the vascular fraction νp, was fused with the computed tomography (CT) images for visual interpretation. Correlations between D-PET imaging parameters and clinical parameters, i.e. tumor size, grade and clinical status, were calculated with a significance level of 0.05.

RESULTS

The temporal uptake pattern of (18)FDG in the tumor varied considerably from patient to patient. SUVE peak was higher than SUVL peak for four patients. The images of the rate constants showed a systematic pattern, often with elevated intensity in the tumors compared to surrounding tissue. Significant correlations were found between SUVE/L and some of the rate parameters.

CONCLUSIONS

Dynamic (18)FDG-PET may provide additional valuable information on soft tissue sarcomas not obtainable from conventional (18)FDG-PET. The prognostic role of dynamic imaging should be investigated.