Stability of metabolic tumor volume may enable radiotherapy dose painting in anal cancer.

PURPOSE: To evaluate the variability of the 18F-FDG-PET/CT-based metabolic tumor volume (MTV) in anal cancers during fractionated chemoradiotherapy (CRT), and assess the impact of this variability on dosimetric accuracy in MTV-targeted dose painting. METHODS: Eleven patients with anal squamous cell carcinoma who received fractionated chemoradiotherapy with curative intent were included. 18F-FDG PET/CT images were acquired at pre- and mid-treatment. Target volumes and organs at risk (OARs) were contoured manually on both image series. The MTV was generated from the PET images by thresholding. Treatment plans were retrospectively optimized for both image series using volumetric modulated arc therapy (VMAT). Standard plans prescribed 48.6 Gy, 54 Gy and 57.5 Gy in 27 fractions to elective regions, lymph node metastases and primary tumor, respectively. Dose painting plans included an extra dose level of 65 Gy to the MTV. Pre-treatment plans were transferred and re-calculated at mid-treatment basis. RESULTS: MTV decreased from pre- to mid-treatment in 10 of the 11 patients. On average, 71 % of MTVmid overlapped with MTVpre. The median and mean doses to the MTV were robust against anatomical changes, but the transferred dose painting plans had lower D98% values than the original and re-optimized plans. No major differences were found between standard and dose painting plans for OARs. CONCLUSIONS: Despite volumetric changes in the MTV, adequate dose coverage was observed in most dose painting plans. The findings indicate little or no need for adaptive dose painting at mid-treatment. Dose painting appears to be a safe treatment alternative with similar dose sparing of OARs.

Deep learning-based automatic delineation of anal cancer gross tumour volume: a multimodality comparison of CT, PET and MRI.

BACKGROUND: Accurate target volume delineation is a prerequisite for high-precision radiotherapy. However, manual delineation is resource-demanding and prone to interobserver variation. An automatic delineation approach could potentially save time and increase delineation consistency. In this study, the applicability of deep learning for fully automatic delineation of the gross tumour volume (GTV) in patients with anal squamous cell carcinoma (ASCC) was evaluated for the first time. An extensive comparison of the effects single modality and multimodality combinations of computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI) have on automatic delineation quality was conducted. MATERIAL AND METHODS: 18F-fluorodeoxyglucose PET/CT and contrast-enhanced CT (ceCT) images were collected for 86 patients with ASCC. A subset of 36 patients also underwent a study-specific 3T MRI examination including T2- and diffusion-weighted imaging. The resulting two datasets were analysed separately. A two-dimensional U-Net convolutional neural network (CNN) was trained to delineate the GTV in axial image slices based on single or multimodality image input. Manual GTV delineations constituted the ground truth for CNN model training and evaluation. Models were evaluated using the Dice similarity coefficient (Dice) and surface distance metrics computed from five-fold cross-validation. RESULTS: CNN-generated automatic delineations demonstrated good agreement with the ground truth, resulting in mean Dice scores of 0.65-0.76 and 0.74-0.83 for the 86 and 36-patient datasets, respectively. For both datasets, the highest mean Dice scores were obtained using a multimodal combination of PET and ceCT (0.76-0.83). However, models based on single modality ceCT performed comparably well (0.74-0.81). T2W-only models performed acceptably but were somewhat inferior to the PET/ceCT and ceCT-based models. CONCLUSION: CNNs provided high-quality automatic GTV delineations for both single and multimodality image input, indicating that deep learning may prove a versatile tool for target volume delineation in future patients with ASCC.

The FLUKA Monte Carlo code coupled with an OER model for biologically weighted dose calculations in proton therapy of hypoxic tumors.

INTRODUCTION: The increased radioresistance of hypoxic cells compared to well-oxygenated cells is quantified by the oxygen enhancement ratio (OER). In this study we created a FLUKA Monte Carlo based tool for inclusion of both OER and relative biological effectiveness (RBE) in biologically weighted dose (ROWD) calculations in proton therapy and applied this to explore the impact of hypoxia. METHODS: The RBE-weighted dose was adapted for hypoxia by making RBE model parameters dependent on the OER, in addition to the linear energy transfer (LET). The OER depends on the partial oxygen pressure (pO2) and LET. To demonstrate model performance, calculations were done with spread-out Bragg peaks (SOBP) in water phantoms with pO2 ranging from strongly hypoxic to normoxic (0.01-30 mmHg) and with a head and neck cancer proton plan optimized with an RBE of 1.1 and pO2 estimated voxel-by-voxel using [18F]-EF5 PET. An RBE of 1.1 and the Rørvik RBE model were used for the ROWD calculations. RESULTS: The SOBP in water had decreasing ROWD with decreasing pO2. In the plans accounting for oxygenation, the median target doses were approximately a factor 1.1 lower than the corresponding plans which did not consider the OER. Hypoxia adapted target ROWDs were considerably more heterogeneous than the RBE1.1-weighted doses. CONCLUSION: We realized a Monte Carlo based tool for calculating the ROWD. Read-in of patient pO2 and estimation of ROWD with flexibility in choice of RBE model was achieved, giving a tool that may be useful in future clinical applications of hypoxia-guided particle therapy.

Anal cancer chemoradiotherapy outcome prediction using 18F-fluorodeoxyglucose positron emission tomography and clinicopathological factors.

OBJECTIVE: To assess the role of [18F]fluorodeoxyglucose (FDG) positron emission tomography (PET), obtained before and during chemoradiotherapy, in predicting locoregional failure relative to clinicopathological factors for patients with anal cancer. METHODS: 93 patients with anal squamous cell carcinoma treated with chemoradiotherapy were included in a prospective observational study (NCT01937780). FDG-PET/CT was performed for all patients before treatment, and for a subgroup (n = 39) also 2 weeks into treatment. FDG-PET was evaluated with standardized uptake values (SUVmax/peak/mean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and a proposed Z-normalized combination of MTV and SUVpeak (ZMP). The objective was to predict locoregional failure using FDG-PET, tumor and lymph node stage, gross tumor volume (GTV) and human papilloma virus (HPV) status in univariate and bivariate Cox regression analysis. RESULTS: N3 lymph node stage, HPV negative tumor, GTV, MTV, TLG and ZMP were in univariate analysis significant predictors of locoregional failure (p < 0.01), while SUVmax/peak/mean were not (p > 0.2). In bivariate analysis HPV status was the most independent predictor in combinations with N3 stage, ZMP, TLG, and MTV (p < 0.02). The FDG-PET parameters at 2 weeks into radiotherapy decreased by 30-40 % of the initial values, but neither absolute nor relative decrease improved the prediction models. CONCLUSION: Pre-treatment PET parameters are predictive of chemoradiotherapy outcome in anal cancer, although HPV negativity and N3 stage are the strongest single predictors. Predictions can be improved by combining HPV with PET parameters such as MTV, TLG or ZMP. PET 2 weeks into treatment does not provide added predictive value. ADVANCES IN KNOWLEDGE: Pre-treatment PET parameters of anal cancer showed a predictive role independent of clinicopathological factors. Although the PET parameters show substantial reduction from pre- to mid-treatment, the changes were not predictive of chemoradiotherapy outcome.

Target volume delineation of anal cancer based on magnetic resonance imaging or positron emission tomography.

PURPOSE: To compare target volume delineation of anal cancer using positron emission tomography (PET) and magnetic resonance imaging (MRI) with respect to inter-observer and inter-modality variability. METHODS: Nineteen patients with anal cancer undergoing chemoradiotherapy were prospectively included. Planning computed tomography (CT) images were co-registered with 18F-fluorodexocyglucose (FDG) PET/CT images and T2 and diffusion weighted (DW) MR images. Three oncologists delineated the Gross Tumor Volume (GTV) according to national guidelines and the visible tumor tissue (GTVT). MRI and PET based delineations were evaluated by absolute volumes and Dice similarity coefficients. RESULTS: The median volume of the GTVs was 27 and 31 cm3 for PET and MRI, respectively, while it was 6 and 11 cm3 for GTVT. Both GTV and GTVT volumes were highly correlated between delineators (r = 0.90 and r = 0.96, respectively). The median Dice similarity coefficient was 0.75 when comparing the GTVs based on PET/CT (GTVPET) with the GTVs based on MRI and CT (GTVMRI). The median Dice coefficient was 0.56 when comparing the visible tumor volume evaluated by PET (GTVT_PET) with the same volume evaluated by MRI (GTVT_MRI). Margins of 1-2 mm in the axial plane and 7-8 mm in superoinferior direction were required for coverage of the individual observer's GTVs. CONCLUSIONS: The rather good agreement between PET- and MRI-based GTVs indicates that either modality may be used for standard target delineation of anal cancer. However, larger deviations were found for GTVT, which may impact future tumor boost strategies.

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.

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.