On biologically conformal boost dose optimization

Plan Assessment Metrics for Dose Painting in Stereotactic Radiosurgery

Purpose

As radiation therapy treatment precision increases with advancements in imaging and radiation delivery, dose painting treatment becomes increasingly feasible, where targets receive a nonuniform radiation dose. The high precision of stereotactic radiosurgery (SRS) makes it a good candidate for dose painting treatments, but no suitable metrics to assess dose painting SRS plans exist. Existing dose painting assessment metrics weigh target overdose and underdose equally but are unsuited for SRS plans, which typically avoid target underdose more. Current SRS metrics also prioritize reducing healthy tissue dose through selectivity and dose fall-off, and these metrics assume single prescriptions. We propose a set of metrics for dose painting SRS that would meet clinical needs and are calculated with nonuniform dose painting prescriptions.

Methods and Materials

Sample dose painting SRS prescriptions are first created from Gamma Knife SRS cases, apparent diffusion coefficient magnetic resonance images, and various image-to-prescription functions. Treatment plans are found through semi-infinite linear programming optimization and using clinically determined isocenters, then assessed with existing and proposed metrics. Modified versions of SRS metrics are proposed, including coverage, selectivity, conformity, efficiency, and gradient indices. Quality factor, a current dose painting metric, is applied both without changes and with modifications. A new metric, integral dose ratio, is proposed as a measure of target overdose.

Results

The merits of existing and modified metrics are demonstrated and discussed. A modified conformity index using mean or minimum prescription dose would be suitable for dose painting SRS with integral or maximum boost methods, respectively. Either modified efficiency index is a suitable replacement for the existing gradient index.

Conclusions

The proposed modified SRS metrics are appropriate measures of plan quality for dose painting SRS plans and have the advantage of giving equal values as the original SRS metrics when applied to single-prescription plans.

Probabilistic target definition and planning in patients with prostate cancer

Intro.Current radiation therapy (RT) planning guidelines handle uncertainties in RT using geometric margins. This approach is simple to use but oversimplifies complex underlying processes and is cumbersome for non-homogeneous dose prescriptions. In this work, we characterize the performance of a novel probabilistic target definition and planning (PTP) approach, which uses voxel-level tumor likelihood information in treatment plan optimization.Methods.We expanded a treatment planning system with probabilistic therapy planning functionality that utilizes non-binary target maps (TM) as voxel-level input to dose plan optimization. Different dose plans were calculated and compared for twelve prostate cancer patients with multiparametric magnetic resonance imaging derived TMs. Dose plans were created using both classical and PTP approaches for uniform and integrated dose boost prescriptions. Dose performance between the different approaches was compared using dose benchmarks on target and organ-at-risk (OAR) volumes.Results.Over all dose metrics, PTP was shown to be comparable to classical planning. For plans of uniform dose prescription, the PTP approach created plans within 1 Gy of the classical planning approach across all dose metrics, with no significant differences (p > 0.2). For plans with the integrated dose boost, PTP plans exhibited higher dose heterogeneity, but still showed target doses comparable to the classical approach, without increasing doses to OAR.Conclusion.In this work we introduce direct incorporation of probabilistic target definition into treatment planning. This treatment planning approach can produce both uniform dose plans and plans with integrated dose boosts that are comparable to ones created using classical dose planning. PTP is a flexible way to optimize external beam radiotherapy, as it is not limited by the use of margins. PTP can produce dose plans equivalent to classical planning, while also allows for greater versatility in dose prescription and direct incorporation of patient target definition uncertainty into treatment planning.

Simulated dose painting of hypoxic sub-volumes in pancreatic cancer stereotactic body radiotherapy

Dose painting of hypoxic tumour sub-volumes using positron-emission tomography (PET) has been shown to improve tumour controlin silicoin several sites, predominantly head and neck and lung cancers. Pancreatic cancer presents a more stringent challenge, given its proximity to critical gastro-intestinal organs-at-risk (OARs), anatomic motion, and impediments to reliable PET hypoxia quantification. A radiobiological model was developed to estimate clonogen survival fraction (SF), using¹⁸F-fluoroazomycin arabinoside PET (FAZA PET) images from ten patients with unresectable pancreatic ductal adenocarcinoma to quantify oxygen enhancement effects. For each patient, four simulated five-fraction stereotactic body radiotherapy (SBRT) plans were generated: (1) a standard SBRT plan aiming to cover the planning target volume with 40 Gy, (2) dose painting plans delivering escalated doses to a maximum of three FAZA-avid hypoxic sub-volumes, (3) dose painting plans with simulated spacer separating the duodenum and pancreatic head, and (4), plans with integrated boosts to geometric contractions of the gross tumour volume (GTV). All plans saturated at least one OAR dose limit. SF was calculated for each plan and sensitivity of SF to simulated hypoxia quantification errors was evaluated. Dose painting resulted in a 55% reduction in SF as compared to standard SBRT; 78% with spacer. Integrated boosts to hypoxia-blind geometric contractions resulted in a 41% reduction in SF. The reduction in SF for dose-painting plans persisted for all hypoxia quantification parameters studied, including registration and rigid motion errors that resulted in shifts and rotations of the GTV and hypoxic sub-volumes by as much as 1 cm and 10 degrees. Although proximity to OARs ultimately limited dose escalation, with estimated SFs (∼10^-5) well above levels required to completely ablate a ∼10 cm³tumour, dose painting robustly reduced clonogen survival when accounting for expected treatment and imaging uncertainties and thus, may improve local response and associated morbidity.

Robust dose-painting-by-numbers vs. nonselective dose escalation for non-small cell lung cancer patients

Purpose

Theoretical studies have shown that dose‐painting‐by‐numbers (DPBN) could lead to large gains in tumor control probability (TCP) compared to conventional dose distributions. However, these gains may vary considerably among patients due to (a) variations in the overall radiosensitivity of the tumor, (b) variations in the 3D distribution of intra‐tumor radiosensitivity within the tumor in combination with patient anatomy, (c) uncertainties of the 3D radiosensitivity maps, (d) geometrical uncertainties, and (e) temporal changes in radiosensitivity. The goal of this study was to investigate how much of the theoretical gains of DPBN remain when accounting for these factors. DPBN was compared to both a homogeneous reference dose distribution and to nonselective dose escalation (NSDE), that uses the same dose constraints as DPBN, but does not require 3D radiosensitivity maps.

Methods

A fully automated DPBN treatment planning strategy was developed and implemented in our in‐house developed treatment planning system (TPS) that is robust to uncertainties in radiosensitivity and patient positioning. The method optimized the expected TCP based on 3D maps of intra‐tumor radiosensitivity, while accounting for normal tissue constraints, uncertainties in radiosensitivity, and setup uncertainties. Based on FDG‐PETCT scans of 12 non‐small cell lung cancer (NSCLC) patients, data of 324 virtual patients were created synthetically with large variations in the aforementioned parameters. DPBN was compared to both a uniform dose distribution of 60 Gy, and NSDE. In total, 360 DPBN and 24 NSDE treatment plans were optimized.

Results

The average gain in TCP over all patients and radiosensitivity maps of DPBN was 0.54 ± 0.20 (range 0–0.97) compared to the 60 Gy uniform reference dose distribution, but only 0.03 ± 0.03 (range 0–0.22) compared to NSDE. The gains varied per patient depending on the radiosensitivity of the entire tumor and the 3D radiosensitivity maps. Uncertainty in radiosensitivity led to a considerable loss in TCP gain, which could be recovered almost completely by accounting for the uncertainty directly in the optimization.

Conclusions

Our results suggest that the gains of DPBN can be considerable compared to a 60 Gy uniform reference dose distribution, but small compared to NSDE for most patients. Using the robust DPBN treatment planning system developed in this work, the optimal DPBN treatment plan could be derived for any patient for whom 3D intra‐tumor radiosensitivity maps are known, and can be used to select patients that might benefit from DPBN. NSDE could be an effective strategy to increase TCP without requiring biological information of the tumor.

Optimal treatment plan adaptation using mid-treatment imaging biomarkers

Previous studies on personalized radiotherapy (RT) have mostly focused on baseline patient stratification, adapting the treatment plan according to mid-treatment anatomical changes, or dose boosting to selected tumor subregions using mid-treatment radiological findings. However, the question of how to find the optimal adapted plan has not been properly tackled. Moreover, the effect of information uncertainty on the resulting adaptation has not been explored. In this paper, we present a framework to optimally adapt radiation therapy treatments to early radiation treatment response estimates derived from pre- and mid-treatment imaging data while considering the information uncertainty. The framework is based on the optimal stopping in radiation therapy (OSRT) framework. Biological response is quantified using tumor control probability (TCP) and normal tissue complication probability (NTCP) models, and these are directly optimized for in the adaptation step. Two adaptation strategies are discussed: (1) uniform dose adaptation and (2) continuous dose adaptation. In the first strategy, the original fluence-map is simply scaled upwards or downwards, depending on whether dose escalation or de-escalation is deemed appropriate based on the mid-treatment response observed from the radiological images. In the second strategy, a full NTCP-TCP-based fluence map re-optimization is performed to achieve the optimal adapted plans. We retrospectively tested the performance of these strategies on 14 canine head and neck cases treated with tomotherapy, using as response biomarker the change in the 3'-deoxy-3'[(18)F]-fluorothymidine (FLT)-PET signals between the pre- and mid-treatment images, and accounting for information uncertainty. Using a 10% uncertainty level, the two adaptation strategies both yield a noteworthy average improvement in guaranteed (worst-case) TCP.

Effect of uncertainties in quantitative 18 F-FDG PET/CT imaging feedback for intratumoral dose-response assessment and dose painting by number

PURPOSE

Intratumoral dose response can be detected using serial fluoro-2-deoxyglucose-(FDG) positron emission tomography (PET)/computed tomography (CT) imaging feedback during treatment and used to guide adaptive dose painting by number (DPbN). However, to reliably implement this technique, the effect of uncertainties in quantitative PET/CT imaging feedback on tumor voxel dose-response assessment and DPbN needs to be determined and reduced.

METHODS

Three major uncertainties, induced by (a) PET imaging partial volume effect (PVE) and (b) tumor deformable image registration (DIR), and (c) variation of the time interval between FDG injection and PET image acquisition (TI), were determined using serial FDG-PET/CT images acquired during chemoradiotherapy of 18 head and neck cancer patients. PET imaging PVE was simulated using the discrepancy between with and without iterative deconvolution-based PVE corrections. Effect of tumor DIR uncertainty was simulated using the discrepancy between two DIR algorithms, including one with and one without soft-tissue mechanical correction for the voxel displacement. The effect of TI variation was simulated using linear interpolation on the dual-point PET/CT images. Tumor voxel pretreatment metabolic activity (SUV₀ ) and dose-response matrix (DRM) discrepancies induced by each of the three uncertainties were quantified, respectively. Adverse effects of tumor voxel SUV₀ and DRM discrepancies on tumor control probability (TCP) in DPbN were assessed.

RESULTS

Partial volume effect and TI variations of 10 mins induced a mean ± standard deviation (SD) of tumor voxel SUV₀ discrepancies to be -0.7% ± 9.2% and 0% ± 4.8%, respectively. Tumor voxel DRM discrepancies induced by PVE, tumor DIR discrepancy, and TI variations were 0.6% ± 8.9%, 1.7% ± 9.1%, and 0% ± 7%, respectively. Partial volume effect induced SUV₀ and DRM discrepancies correlated significantly with the tumor shape and FDG uptake heterogeneity. Tumor DIR uncertainty-induced DRM discrepancy correlated significantly with the tumor volume and shrinkage during treatment. Among the three uncertainties, PVE dominated the adverse effects on the TCP, with a mean ± SD of TCP reduction to be 12.7% ± 9.8% for all tumors if no compensation was applied for.

CONCLUSIONS

Effect of uncertainties in quantitative FDG-PET/CT imaging feedback on intratumoral dose-response quantification was not negligible. These uncertainties primarily caused by PVE and tumor DIR were highly dependent on individual tumor shape, volume, shrinkage during treatment, and pretreatment SUV heterogeneity, which can be managed individually. The adverse effects of these uncertainties could be minimized by using proper PVE corrections and DIR methods and compensated for in the clinical implementation of DPbN.

Inter/intra-tumoral dose response variations assessed using FDG-PET/CT feedback images: Impact on tumor control and treatment dose prescription

PURPOSE

To quantify inter/intra-tumoral variations of baseline metabolic activity and dose response. To evaluate their impact on tumor control and treatment dose prescription strategies.

METHODS AND MATERIALS

Tumor voxel baseline metabolic activity, SUV₀, and dose response matrix, DRM, quantified using the pre-treatment and weekly FDG-PET/CT imaging feedback for each of 34 HNSCC patients (25 HPV+ and 9 HVP-) were evaluated. Inter/intra-tumoral variations of tumor voxel (SUV₀, DRM) for each of the HPV- and HPV+ tumor groups were quantified and used to evaluate the variations of individual tumor control probabilities and the efficiency of uniform vs non-uniform treatment dose prescription strategies.

RESULTS

Tumor voxel dose response variation of all tumor voxels assessed using FDG-PET/CT imaging feedback had the mean(CV) = 0.47(47%), which was consistent with those of previously published in vitro tumor clonogenic assay. The HPV- tumors had the mean(CV) dose response, 0.53(49%), significantly larger than those of the HPV+ tumors, 0.45(43%). However, their baseline SUVs were opposite, 6.5(56%) vs 7.7(65%). Comparing to the inter-tumoral variations, both HPV-/+ tumor groups showed larger intra-tumoral variations, (53%, 58%) vs (20%, 31%) for the baseline SUV and (38%, 37%) vs (31%, 21%) for the dose response. Due to the large dose response variations, treatment dose to control the tumor voxels has very broad range with CV of TCD₅₀ = 97% for the HPV- and 67% for the HPV+ tumor group respectively. As a consequence, heterogeneous prescription dose could potentially reduce the treatment integral dose for 92% of the HPV+ tumors and 78% of the HPV- tumors.

CONCLUSIONS

The study demonstrates that tumor dose response assessed using FDG-PET/CT feedback images had a similar distribution to those assessed conventionally using in vitro tumor clonogenic assay. Inter-tumoral dose response variation seems larger for HPV- tumors, but intra-tumoral dose response variations are similar for both HPV groups. These variations cause very large variation on the individual tumor control probability and limit the efficacy of dose escalation and de-escalation in conventional clinical practice. On the other hand, heterogeneous dose prescription guided by metabolic imaging feedback has a potential advantage in radiotherapy.

Voxel-level biological optimisation of prostate IMRT using patient-specific tumour location and clonogen density derived from mpMRI

AIMS

This study aimed to develop a framework for optimising prostate intensity-modulated radiotherapy (IMRT) based on patient-specific tumour biology, derived from multiparametric MRI (mpMRI). The framework included a probabilistic treatment planning technique in the effort to yield dose distributions with an improved expected treatment outcome compared with uniform-dose planning approaches.

METHODS

IMRT plans were generated for five prostate cancer patients using two inverse planning methods: uniform-dose to the planning target volume and probabilistic biological optimisation for clinical target volume tumour control probability (TCP) maximisation. Patient-specific tumour location and clonogen density information were derived from mpMRI and geometric uncertainties were incorporated in the TCP calculation. Potential reduction in dose to sensitive structures was assessed by comparing dose metrics of uniform-dose plans with biologically-optimised plans of an equivalent level of expected tumour control.

RESULTS

The planning study demonstrated biological optimisation has the potential to reduce expected normal tissue toxicity without sacrificing local control by shaping the dose distribution to the spatial distribution of tumour characteristics. On average, biologically-optimised plans achieved 38.6% (p-value: < 0.01) and 51.2% (p-value: < 0.01) reduction in expected rectum and bladder equivalent uniform dose, respectively, when compared with uniform-dose planning.

CONCLUSIONS

It was concluded that varying the dose distribution within the prostate to take account for each patient's clonogen distribution was feasible. Lower doses to normal structures compared to uniform-dose plans was possible whilst providing robust plans against geometric uncertainties. Further validation in a larger cohort is warranted along with considerations for adaptive therapy and limiting urethral dose.

Progress towards Patient-Specific, Spatially-Continuous Radiobiological Dose Prescription and Planning in Prostate Cancer IMRT: An Overview

Advances in imaging have enabled the identification of prostate cancer foci with an initial application to focal dose escalation, with subvolumes created with image intensity thresholds. Through quantitative imaging techniques, correlations between image parameters and tumour characteristics have been identified. Mathematical functions are typically used to relate image parameters to prescription dose to improve the clinical relevance of the resulting dose distribution. However, these relationships have remained speculative or invalidated. In contrast, the use of radiobiological models during treatment planning optimisation, termed biological optimisation, has the advantage of directly considering the biological effect of the resulting dose distribution. This has led to an increased interest in the accurate derivation of radiobiological parameters from quantitative imaging to inform the models. This article reviews the progress in treatment planning using image-informed tumour biology, from focal dose escalation to the current trend of individualised biological treatment planning using image-derived radiobiological parameters, with the focus on prostate intensity-modulated radiotherapy (IMRT).

Task Group 174 Report: Utilization of [18 F]Fluorodeoxyglucose Positron Emission Tomography ([18 F]FDG-PET) in Radiation Therapy

The use of positron emission tomography (PET) in radiation therapy (RT) is rapidly increasing in the areas of staging, segmentation, treatment planning, and response assessment. The most common radiotracer is ¹⁸ F-fluorodeoxyglucose ([¹⁸ F]FDG), a glucose analog with demonstrated efficacy in cancer diagnosis and staging. However, diagnosis and RT planning are different endeavors with unique requirements, and very little literature is available for guiding physicists and clinicians in the utilization of [¹⁸ F]FDG-PET in RT. The two goals of this report are to educate and provide recommendations. The report provides background and education on current PET imaging systems, PET tracers, intensity quantification, and current utilization in RT (staging, segmentation, image registration, treatment planning, and therapy response assessment). Recommendations are provided on acceptance testing, annual and monthly quality assurance, scanning protocols to ensure consistency between interpatient scans and intrapatient longitudinal scans, reporting of patient and scan parameters in literature, requirements for incorporation of [¹⁸ F]FDG-PET in treatment planning systems, and image registration. The recommendations provided here are minimum requirements and are not meant to cover all aspects of the use of [¹⁸ F]FDG-PET for RT.

Robust maximization of tumor control probability for radicality constrained radiotherapy dose painting by numbers of head and neck cancer

BACKGROUND AND PURPOSE

Radiotherapy with dose painting by numbers (DPBN) needs another approach than conventional margins to ensure a geometrically robust dose coverage for the tumor. This study presents a method to optimize DPBN plans that as opposed to achieve a robust dose distribution instead robustly maximize the tumor control probability (TCP) for patients diagnosed with head and neck cancer.

MATERIAL AND METHODS

Volumetric-modulated arc therapy (VMAT) plans were optimized with a robust TCP maximizing objective for different dose constraints to the primary clinical target volume (CTVT) for a set of 20 patients. These plans were optimized with minimax optimization together with dose-responses driven by standardized uptake values (SUV) from 18F-fluorodeoxyglucose positron emission tomography (18FDG-PET). The robustness in TCP was evaluated through sampling treatment scenarios with isocenter displacements.

RESULTS

The average increase in TCP with DPBN compared to a homogeneous dose treatment ranged between 3 and 20 percentage points (p.p.) which depended on the different dose constraints for the CTVT. The median deviation in TCP increase was below 1p.p. for all sampled treatment scenarios versus the nominal plans. The standard deviation of SUV multiplied by the CTVT volume were found to correlate with the TCP gain with R 2 ≥ 0.9.

CONCLUSIONS

Minimax optimization of DPBN plans yield, based on the presented TCP modelling, a robust increase of the TCP compared to homogeneous dose treatments for head and neck cancers. The greatest TCP gains were found for patients with large and SUV heterogeneous tumors, which may give guidance for patient selection in prospective trials.

Hypoxia Imaging and Adaptive Radiotherapy: A State-of-the-Art Approach in the Management of Glioma

Severe hypoxia [oxygen partial pressure (pO₂) below 5–10 mmHg] is more frequent in glioblastoma multiforme (GBM) compared to lower-grade gliomas. Seminal studies in the 1950s demonstrated that hypoxia was associated with increased resistance to low–linear energy transfer (LET) ionizing radiation. In experimental conditions, the total radiation dose has to be multiplied by a factor of 3 to achieve the same cell lethality in anoxic situations. The presence of hypoxia in human tumors is assumed to contribute to treatment failures after radiotherapy (RT) in cancer patients. Therefore, a logical way to overcome hypoxia-induced radioresistance would be to deliver substantially higher doses of RT in hypoxic volumes delineated on pre-treatment imaging as biological target volumes (BTVs). Such an approach faces various fundamental, technical, and clinical challenges. The present review addresses several technical points related to the delineation of hypoxic zones, which include: spatial accuracy, quantitative vs. relative threshold, variations of hypoxia levels during RT, and availability of hypoxia tracers. The feasibility of hypoxia imaging as an assessment tool for early tumor response to RT and for predicting long-term outcomes is discussed. Hypoxia imaging for RT dose painting is likewise examined. As for the radiation oncologist's point of view, hypoxia maps should be converted into dose-distribution objectives for RT planning. Taking into account the physics and the radiobiology of various irradiation beams, preliminary in silico studies are required to investigate the feasibility of dose escalation in terms of normal tissue tolerance before clinical trials are undertaken.

A linear programming approach to inverse planning in Gamma Knife radiosurgery

PURPOSE

Leksell Gamma Knife® is a stereotactic radiosurgery system that allows fine-grained control of the delivered dose distribution. We describe a new inverse planning approach that both resolves shortcomings of earlier approaches and unlocks new capabilities.

METHODS

We fix the isocenter positions and perform sector-duration optimization using linear programming, and study the effect of beam-on time penalization on the trade-off between beam-on time and plan quality. We also describe two techniques that reduce the problem size and thus further reduce the solution time: dualization and representative subsampling.

RESULTS

The beam-on time penalization reduces the beam-on time by a factor 2-3 compared with the naïve alternative. Dualization and representative subsampling each leads to optimization time-savings by a factor 5-20. Overall, we find in a comparison with 75 clinical plans that we can always find plans with similar coverage and better selectivity and beam-on time. In 44 of these, we can even find a plan that also has better gradient index. On a standard GammaPlan workstation, the optimization times ranged from 2.3 to 26 s with a median time of 5.7 s.

CONCLUSION

We present a combination of techniques that enables sector-duration optimization in a clinically feasible time frame.

The Path Toward PET-Guided Radiation Therapy for Glioblastoma in Laboratory Animals: A Mini Review

Glioblastoma is the most aggressive and malignant primary brain tumor in adults. Despite the current state-of-the-art treatment, which consists of maximal surgical resection followed by radiation therapy, concomitant, and adjuvant chemotherapy, progression remains rapid due to aggressive tumor characteristics. Several new therapeutic targets have been investigated using chemotherapeutics and targeted molecular drugs, however, the intrinsic resistance to induced cell death of brain cells impede the effectiveness of systemic therapies. Also, the unique immune environment of the central nervous system imposes challenges for immune-based therapeutics. Therefore, it is important to consider other approaches to treat these tumors. There is a well-known dose-response relationship for glioblastoma with increased survival with increasing doses, but this effect seems to cap around 60 Gy, due to increased toxicity to the normal brain. Currently, radiation treatment planning of glioblastoma patients relies on CT and MRI that does not visualize the heterogeneous nature of the tumor, and consequently, a homogenous dose is delivered to the entire tumor. Metabolic imaging, such as positron-emission tomography, allows to visualize the heterogeneous tumor environment. Using these metabolic imaging techniques, an approach called dose painting can be used to deliver a higher dose to the tumor regions with high malignancy and/or radiation resistance. Preclinical studies are required for evaluating the benefits of novel radiation treatment strategies, such as PET-based dose painting. The aim of this review is to give a brief overview of promising PET tracers that can be evaluated in laboratory animals to bridge the gap between PET-based dose painting in glioblastoma patients.

Tumor Voxel Dose-Response Matrix and Dose Prescription Function Derived Using 18F-FDG PET/CT Images for Adaptive Dose Painting by Number

PURPOSE

To construct a tumor voxel dose response matrix (DRM) and dose prescription function (DPF) for adaptive dose painting by number (DPbN) based on treatment feedback of fluoro-2-deoxyglucose (FGD) positron emission tomography (PET)/computed tomography (CT) imaging.

METHODS AND MATERIALS

FDG-PET/CT images obtained before and after chemoradiation therapy and at weekly chemoradiation therapy sessions for each of 18 patients with head and neck cancer, as well as the treatment outcomes, were used in the modeling. All weekly and posttreatment PET/CT images were registered voxel-to-voxel to the corresponding pretreatment baseline PET/CT image. Tumor voxel DRM was created using serial FDG-PET imaging of each patient with respect to the baseline standardized uptake value (SUV₀). A tumor voxel control probability (TVCP) lookup table was created using the maximum likelihood estimation on the tumor voxel (SUV₀, DRM) domain of all tumors. Tumor voxel DPF was created from the TVCP lookup table and used as the objective function for DPbN-based inverse planning optimization.

RESULTS

Large intertumoral and intratumoral variations on both tumor voxels (SUV₀, DRM) were identified. Tumor voxel dose resistance did not show correlation with its baseline SUV₀ value and was the major cause of the tumor local failures. Tumor voxel DPF as the function of tumor voxel (SUV₀, DRM) values also showed a very large intertumoral and intratumoral heterogeneity. Most human papillomavirus-negative tumors require a treatment dose >100 Gy to certain local tumor regions. These treatment doses, which are most unlikely to be implementable in conventional radiation therapy, can be achieved using adaptive DPbN treatment. Clinical feasibility was evaluated by comparing the adaptive DPbN treatment plan with the conventional intensity modulated radiation therapy plan.

CONCLUSIONS

Tumor voxel (SUV₀, DRM) provides an intratumoral prognostic map to target tumor locoregional-resistant regions. The corresponding TVCP or DPF provides a quantitative objective to optimize the intratumoral dose distribution for the individuals. The adaptive DPbN with FDG-PET/CT imaging feedback is feasible to implement in clinics.

Impact of different biologically-adapted radiotherapy strategies on tumor control evaluated with a tumor response model

Motivated by the capabilities of modern radiotherapy techniques and by the recent developments of functional imaging techniques, dose painting by numbers (DPBN) was proposed to treat tumors with heterogeneous biological characteristics. This work studies different DPBN optimization techniques for virtual head and neck tumors assessing tumor response in terms of cell survival and tumor control probability with a previously published tumor response model (TRM). Uniform doses of 2 Gy are redistributed according to the microscopic oxygen distribution and the density distribution of tumor cells in four virtual tumors with different biological characteristics. In addition, two different optimization objective functions are investigated, which: i) minimize tumor cell survival (OF_surv) or; ii) maximize the homogeneity of the density of surviving tumor cells (OF_std). Several adaptive schemes, ranging from single to daily dose optimization, are studied and the treatment response is compared to that of the uniform dose. The results show that the benefit of DPBN treatments depends on the tumor reoxygenation capability, which strongly differed among the set of virtual tumors investigated. The difference between daily (fraction by fraction) and three weekly optimizations (at the beginning of weeks 1, 3 and 4) was found to be small, and higher benefit was observed for the treatments optimized using OF_surv. This in silico study corroborates the hypothesis that DPBN may be beneficial for treatments of tumors which show reoxygenation during treatment, and that a few optimizations may be sufficient to achieve this therapeutic benefit.

Biological imaging for individualized therapy in radiation oncology: part I physical and technical aspects

Recently, there has been an increase in the imaging modalities available for radiotherapy planning and radiotherapy prognostic outcome: dual energy computed tomography (CT), dynamic contrast enhanced CT, dynamic contrast enhanced magnetic resonance imaging (MRI), diffusion-weighted MRI, positron emission tomography-CT, dynamic contrast enhanced ultrasound, MR spectroscopy and positron emission tomography-MR. These techniques enable more precise gross tumor volume definition than CT alone and moreover allow subvolumes within the gross tumor volume to be defined which may be given a boost dose or an individual voxelized dose prescription may be derived. With increased plan complexity care must be taken to immobilize the patient in an accurate and reproducible manner. Moreover the physical and technical limitations of the entire treatment planning chain need to be well characterized and understood, interdisciplinary collaboration ameliorated (physicians and physicists within nuclear medicine, radiology and radiotherapy) and image protocols standardized.

The potential for increased tumor control probability in non-small cell lung cancer with a hypofractionated integrated boost to the gross tumor volume

Treatment outcomes in locally advanced non-small cell lung cancer (NSCLC) to date have been poor, with normal tissue toxicity often limiting the dose that can be delivered to the tumor. Treatment intensification in NSCLC via targeted dose escalation with modern delivery techniques may offer the potential for a significant increase in tumor control probability (TCP) without a clinically significant increase in organ-at-risk (OAR) toxicity. In this planning study, 20 patients were re-planned with a volumetric modulated arc therapy (VMAT) and an inhomogeneous dose distribution with iteratively escalated doses to the gross tumor volume (iGTV) (composite GTV across multiple 4-dimensional computed tomography [4DCT] phases) in a series of 20 fraction regimes. For each plan OAR doses, target coverage and predicted TCPs were collected and compared with homogenous 3-dimensional (3D) and VMAT plans, as well as with each other. In 70% of patients, it was possible to escalate to 75 Gy in 20 fractions within OAR tolerances, opening the possibility of treating these patients to a biological effective dose (BED) of 103.1 Gy₁₀. This planning study forms the basis of a clinical trial INTENSE (Inhomogeneous Targeted Dose Escalation in Non-Small CEll Lung Cancer), CTRIAL 15-47.

Dose painting by means of Monte Carlo treatment planning at the voxel level

PURPOSE

To develop a new optimization algorithm to carry out true dose painting by numbers (DPBN) planning based on full Monte Carlo (MC) calculation.

METHODS

Four configurations with different clustering of the voxel values from PET data were proposed. An optimization method at the voxel level under Lineal Programming (LP) formulation was used for an inverse planning and implemented in CARMEN, an in-house Monte Carlo treatment planning system.

RESULTS

Beamlet solutions fulfilled the objectives and did not show significant differences between the different configurations. More differences were observed between the segment solutions. The plan for the dose prescription map without clustering was the better solution.

CONCLUSIONS

LP optimization at voxel level without dose-volume restrictions can carry out true DPBN planning with the MC accuracy.

The role of necrosis, acute hypoxia and chronic hypoxia in 18F-FMISO PET image contrast: a computational modelling study

Positron emission tomography (PET) using 18F-fluoromisonidazole (FMISO) is a promising technique for imaging tumour hypoxia, and a potential target for radiotherapy dose-painting. However, the relationship between FMISO uptake and oxygen partial pressure ([Formula: see text]) is yet to be quantified fully. Tissue oxygenation varies over distances much smaller than clinical PET resolution (<100 μm versus  ∼4 mm), and cyclic variations in tumour perfusion have been observed on timescales shorter than typical FMISO PET studies (∼20 min versus a few hours). Furthermore, tracer uptake may be decreased in voxels containing some degree of necrosis. This work develops a computational model of FMISO uptake in millimetre-scale tumour regions. Coupled partial differential equations govern the evolution of oxygen and FMISO distributions, and a dynamic vascular source map represents temporal variations in perfusion. Local FMISO binding capacity is modulated by the necrotic fraction. Outputs include spatiotemporal maps of [Formula: see text] and tracer accumulation, enabling calculation of tissue-to-blood ratios (TBRs) and time-activity curves (TACs) as a function of mean tissue oxygenation. The model is characterised using experimental data, finding half-maximal FMISO binding at local [Formula: see text] of 1.4 mmHg (95% CI: 0.3-2.6 mmHg) and half-maximal necrosis at 1.2 mmHg (0.1-4.9 mmHg). Simulations predict a non-linear non-monotonic relationship between FMISO activity (4 hr post-injection) and mean tissue [Formula: see text] : tracer uptake rises sharply from negligible levels in avascular tissue, peaking at  ∼5 mmHg and declining towards blood activity in well-oxygenated conditions. Greater temporal variation in perfusion increases peak TBRs (range 2.20-5.27) as a result of smaller predicted necrotic fraction, rather than fundamental differences in FMISO accumulation under acute hypoxia. Identical late FMISO uptake can occur in regions with differing [Formula: see text] and necrotic fraction, but simulated TACs indicate that additional early-phase information may allow discrimination of hypoxic and necrotic signals. We conclude that a robust approach to FMISO interpretation (and dose-painting prescription) is likely to be based on dynamic PET analysis.

Robust PET-guided intensity-modulated radiation therapy

PURPOSE

Functional image guided intensity-modulated radiation therapy has the potential to improve cancer treatment quality by basing treatment parameters such as heterogeneous dose distributions information derived from imaging. However, such heterogeneous dose distributions are subject to imaging uncertainty. In this paper, the authors develop a robust optimization model to design plans that are desensitized to imaging uncertainty.

METHODS

Starting from the pretreatment fluorodeoxyglucose-positron emission tomography scans, the authors use the raw voxel standard uptake values (SUVs) as input into a series of intermediate functions to transform the SUV into a desired dose. The calculated desired doses were used as an input into a robust optimization model to generate beamlet intensities. For each voxel, the authors assume that the true SUV cannot be observed but instead resides in an interval centered on the nominal (i.e., observed) SUV. Then the authors evaluated the nominal and robust solutions through a simulation study. The simulation considered the effect of the true SUV being different from the nominal SUV on the quality of the treatment plan. Treatment plans were compared on the metrics of objective function value and tumor control probability (TCP).

RESULTS

Computational results demonstrate the potential for improvements in tumor control probability and deviation from the desired dose distribution compared to a nonrobust model while maintaining acceptable tissue dose.

CONCLUSIONS

Robust optimization can help design treatment plans that are more stable in the presence of image value uncertainties.

Dose painting by numbers in a standard treatment planning system using inverted dose prescription maps

BACKGROUND

Dose painting by numbers (DPBN) is a method to deliver an inhomogeneous tumor dose voxel-by-voxel with a prescription based on biological medical images. However, planning of DPBN is not supported by commercial treatment planning systems (TPS) today. Here, a straightforward method for DPBN with a standard TPS is presented.

MATERIAL AND METHODS

DPBN tumor dose prescription maps were generated from (18)F-FDG-PET images applying a linear relationship between image voxel value and dose. An inverted DPBN prescription map was created and imported into a standard TPS where it was defined as a mock pre-treated dose. Using inverse optimization for the summed dose, a planned DPBN dose distribution was created. The procedure was tested in standard TPS for three different tumor cases; cervix, lung and head and neck. The treatment plans were compared to the prescribed DPBN dose distribution by three-dimensional (3D) gamma analysis and quality factors (QFs). Delivery of the DPBN plans was assessed with portal dosimetry (PD).

RESULTS

Maximum tumor doses of 149%, 140% and 151% relative to the minimum tumor dose were prescribed for the cervix, lung and head and neck case, respectively. DPBN distributions were well achieved within the tumor whilst normal tissue doses were within constraints. Generally, high gamma pass rates (> 89% at 2%/2 mm) and low QFs (< 2.6%) were found. PD showed that all DPBN plans could be successfully delivered.

CONCLUSIONS

The presented methodology enables the use of currently available TPSs for DPBN planning and delivery and may therefore pave the way for clinical implementation.

Methodology for adaptive and robust FDG-PET escalated dose painting by numbers in head and neck tumors

OBJECTIVE

To develop a methodology for using FDG PET/CT in adaptive dose painting by numbers (DPBN) in head and neck squamous cell carcinoma (HNSCC) patients. Issues related to noise in PET and treatment robustness against geometric errors are addressed.

METHODS

Five patients with locally advanced HNSCC scheduled for chemo-radiotherapy were imaged with FDG-PET/CT at baseline and 2-3 times during radiotherapy (RT). The GTVPET was segmented with a gradient-based method. A double median filter reduces the impact of noise in the PET uptake-to-dose conversion. Filtered FDG uptake values were linearly converted into a voxel-by-voxel prescription from 70 (median uptake) to 86 Gy (highest uptake). A PTVPET was obtained by applying a dilation of 2.5 mm to the entire prescription. Seven iso-uptake thresholds led to seven sub-levels compatible with the Tomotherapy HiArt(®) Treatment Planning System. Planning aimed to deliver a median dose of 56 Gy and 70 Gy in 35 fractions on the elective and therapeutic PTVs, respectively. Plan quality was assessed with quality volume histogram (QVH). At each time point, plans were generated with a total of 3-4 plans for each patient. Deformable image registration was used for automatic contour propagation and dose summation of the 3 or 4 treatment plans (MIMvista(®)).

RESULTS

GTVPET segmentations were performed successfully until week 2 of RT but failed in two patients at week 3. QVH analysis showed high conformity for all plans (mean VQ = 0.95 93%; mean VQ = 1.05 3.9%; mean QF 2.2%). Good OAR sparing was achieved while keeping high plan quality.

CONCLUSION

Our results show that adaptive FDG-PET-based escalated dose painting in patients with locally advanced HNSCC is feasible while respecting strict dose constraints to organs at risk. Clinical studies must be conducted to evaluate toxicities and tumor response of such a strategy.

Differential hepatic avoidance radiation therapy: Proof of concept in hepatocellular carcinoma patients

PURPOSE

To evaluate the feasibility of a novel planning concept that differentially redistributes RT dose away from functional liver regions as defined by (99m)Tc-sulphur colloid (SC) uptake on patient SPECT/CT images.

MATERIALS AND METHODS

Ten HCC patients with different Child-Turcotte-Pugh scores (A5-B9) underwent SC SPECT/CT scans in treatment position prior to RT that were registered to planning CT scans. Proton pencil beam scanning (PBS) therapy plans were optimized to deliver 37.5-60.0Gy (RBE) over 5-15 fractions using single field uniform dose technique robust to range and setup uncertainty. Photon volumetrically modulated arc therapy (VMAT) plans were optimized to the same prescribed dose and minimum target coverage. For both treatment modalities, differential hepatic avoidance RT (DHART) plans were generated to decrease dose to functional liver volumes (FLV) defined by a range of thresholds relative to maximum SC uptake (43-90%) in the tumor-subtracted liver. Radiation dose was redistributed away from regions of increased SC uptake in each FLV by linearly scaling mean dose objectives during PBS or VMAT optimization. DHART planning feasibility was assessed by a significantly negative Spearman's rank correlation (RS) between dose difference and SC uptake. Patient, tumor, and treatment planning characteristics were tested for association to DHART planning feasibility using non-parametric Kruskal-Wallis ANOVA.

RESULTS

Compared to conventional plans, DHART plans achieved a 3% FLV dose reduction for every 10% SC uptake increase. DHART planning was feasible in the majority of patients with 60% of patients having RS<-0.5 (p<0.01, range -1.0 to 0.2) and was particularly effective in 30% of patients (RS<-0.9). Mean dose to FLV was reduced by up to 20% in these patients. Only fractionation regimen was associated with DHART planning feasibility: 15 fraction courses were more feasible than 5-6 fraction courses (RS<-0.93 vs. RS>-0.60, p<0.02).

CONCLUSION

Differential avoidance of functional liver regions defined on sulphur colloid SPECT/CT is achievable with either photon VMAT or proton PBS therapy. Further investigation with phantom studies and in a larger cohort of patients may validate the utility of DHART planning for HCC radiotherapy.

Towards multidimensional radiotherapy: key challenges for treatment individualisation

Functional and molecular imaging of tumours have offered the possibility of redefining the target in cancer therapy and individualising the treatment with a multidimensional approach that aims to target the adverse processes known to impact negatively upon treatment result. Following the first theoretical attempts to include imaging information into treatment planning, it became clear that the biological features of interest for targeting exhibit considerable heterogeneity with respect to magnitude, spatial, and temporal distribution, both within one patient and between patients, which require more advanced solutions for the way the treatment is planned and adapted. Combining multiparameter information from imaging with predictive information from biopsies and molecular analyses as well as in treatment monitoring of tumour responsiveness appears to be the key approach to maximise the individualisation of treatment. This review paper aims to discuss some of the key challenges for incorporating into treatment planning and optimisation the radiobiological features of the tumour derived from pretreatment PET imaging of tumour metabolism, proliferation, and hypoxia and combining them with intreatment monitoring of responsiveness and other predictive factors with the ultimate aim of individualising the treatment towards the maximisation of response.

Fusion of multi-tracer PET images for dose painting

PET imaging with FluoroDesoxyGlucose (FDG) tracer is clinically used for the definition of Biological Target Volumes (BTVs) for radiotherapy. Recently, new tracers, such as FLuoroThymidine (FLT) or FluoroMisonidazol (FMiso), have been proposed. They provide complementary information for the definition of BTVs. Our work is to fuse multi-tracer PET images to obtain a good BTV definition and to help the radiation oncologist in dose painting. Due to the noise and the partial volume effect leading, respectively, to the presence of uncertainty and imprecision in PET images, the segmentation and the fusion of PET images is difficult. In this paper, a framework based on Belief Function Theory (BFT) is proposed for the segmentation of BTV from multi-tracer PET images. The first step is based on an extension of the Evidential C-Means (ECM) algorithm, taking advantage of neighboring voxels for dealing with uncertainty and imprecision in each mono-tracer PET image. Then, imprecision and uncertainty are, respectively, reduced using prior knowledge related to defects in the acquisition system and neighborhood information. Finally, a multi-tracer PET image fusion is performed. The results are represented by a set of parametric maps that provide important information for dose painting. The performances are evaluated on PET phantoms and patient data with lung cancer. Quantitative results show good performance of our method compared with other methods.

The impact of 18 F-FET PET-CT on target definition in image-guided stereotactic radiotherapy in patients with skull base lesions

Background

18 F-fluoro-ethyl-tyrosine PET is gaining more indications in the field of oncology. We investigated the potentials of usage of FET-PET/CT in addition to MRI for definition of gross tumor volume (GTV) in stereotactic radiotherapy of lesions of skull base.

Methods

We included in a prospective setting 21 cases. An MRI was performed, completed by FET PET/CT. Different GTV’s were defined based on respective imaging tools: 1. GTVMRI, 2. GTV MRI /CT, 3. GTV composit (1 + 2), and GTVPET = GTV Boost. Lesions could be visualised by MRI and FET-PET/CT in all patients.

Results

FET tracer enhancement was found in all cases. Skull base infiltration by these lesions was observed by MRI, CT (PET/CT) and FET-PET (PET/CT) in all patients. Totally, brain tissue infiltration was seen in 10 patients. While, in 7 (out 10) cases, MRI and CT (from PET/CT) were indicating brain infiltration, FET-PET could add additional information regarding infiltrative behaviour: in 3 (out 10) patients, infiltration of the brain was displayed merely in FET-PET. An enlargement of GTVMRI/CT due to the FET-PET driven information, which revealed GTVcomposite , was necessary in 7 cases,. This enlargement was significant by definition (> 10% of GTVMRI/CT). The mean PET-effect on GTV counted for 1 ± 4 cm3. The restricted boost fields were based mainly on the GTVPET volume. In mean, about 8.5 cm3 of GTVMRI/CT, which showed no FET uptake, were excluded from target volume. GTVboost driven by only-PET-activity, was in mean by 33% smaller than the initial large treatment field, GTVcomposite, for those cases received boost treatment. FET-PET lead to significant (>10%) changes in the initial treatment fields in 11/21 patients and showed additional tumour volume relevant for radiation planning in 6/21 cases, and led to a subsequent decrease of more than 10% of the initial volumes for the boost fields.

Conclusion

The implementation of FET PET into the planning procedures showed a benefit in terms of accurate definition of skull base lesions as targets for Image-guided stereotactic Radiotherapy. This has to be investigated prospectively in larger cohorts.

Multi-modality functional image guided dose escalation in the presence of uncertainties

BACKGROUND AND PURPOSE

In order to increase local tumour control by radiotherapy without increasing toxicity, it appears promising to harness functional imaging (FI) to guide dose to sub-volumes of the target with a high tumour load and perhaps de-escalate dose to low risk volumes, in order to maximise the efficiency of the deposited radiation dose.

METHODS AND MATERIALS

A number of problems have to be solved to make focal dose escalation (FDE) efficient and safe: (1) how to combine ambiguous information from multiple imaging modalities; (2) how to take into account uncertainties of FI based tissue classification; (3) how to account for geometric uncertainties in treatment delivery; (4) how to add complementary FI modalities to an existing scheme. A generic optimisation concept addresses these points and is explicitly designed for clinical efficacy and for lowering the implementation threshold to FI-guided FDE. It combines classic tumour control probability modelling with a multi-variate logistic regression model of FI accuracy and an uncomplicated robust optimisation method.

RESULTS

Its key elements are (1) that dose is deposited optimally when it achieves equivalent expected effect everywhere in the target volume and (2) that one needs to cap the certainty about the absence of tumour anywhere in the target region. For illustration, an example of a PET/MR-guided FDE in prostate cancer is given.

CONCLUSIONS

FDE can be safeguarded against FI uncertainties, at the price of a limit on the sensible dose escalation.

Quantitative hypoxia imaging for treatment planning of radiotherapy

Tumour oxygenation is an important determinant of radiotherapy outcome as it could modulate cellular radiation sensitivity. Advanced PET imaging able to characterise this microenvironmental aspect in vivo might be used to devise counteracting therapies as it could provide information on the severity and the spatial distribution of the hypoxic regions. This study reviews the advantages and limitations of PET for imaging and quantifying tumour hypoxia and proposes a novel approach to obtain absolute levels of hypoxia from PET images through the use of EPR oximetry. This would offer a significant advantage over proposals based on empirical conversions of the intensities in the PET images to relative radiosensitivities. Thus, tumour hypoxia must be taken into account at the stage of treatment planning for photons and particle therapy by accounting for its extent and severity through the use of PET imaging combined with absolute EPR measurements.

Molecular imaging of tumor hypoxia with positron emission tomography

The problem of tumor hypoxia has been recognized and studied by the oncology community for over 60 years. From radiation and chemotherapy resistance to the increased risk of metastasis, low oxygen concentrations in tumors have caused patients with many types of tumors to respond poorly to conventional cancer therapies. It is clear that patients with high levels of tumor hypoxia have a poorer overall treatment response and that the magnitude of hypoxia is an important prognostic factor. As a result, the development of methods to measure tumor hypoxia using invasive and noninvasive techniques has become desirable to the clinical oncology community. A variety of imaging modalities have been established to visualize hypoxia in vivo. Positron emission tomography (PET) imaging, in particular, has played a key role for imaging tumor hypoxia because of the development of hypoxia-specific radiolabelled agents. Consequently, this technique is increasingly used in the clinic for a wide variety of cancer types. Following a broad overview of the complexity of tumor hypoxia and measurement techniques to date, this article will focus specifically on the accuracy and reproducibility of PET imaging to quantify tumor hypoxia. Despite numerous advances in the field of PET imaging for hypoxia, we continue to search for the ideal hypoxia tracer to both qualitatively and quantitatively define the tumor hypoxic volume in a clinical setting to optimize treatments and predict response in cancer patients.

A stochastic model for tumor geometry evolution during radiation therapy in cervical cancer

PURPOSE

To develop mathematical models to predict the evolution of tumor geometry in cervical cancer undergoing radiation therapy.

METHODS

The authors develop two mathematical models to estimate tumor geometry change: a Markov model and an isomorphic shrinkage model. The Markov model describes tumor evolution by investigating the change in state (either tumor or nontumor) of voxels on the tumor surface. It assumes that the evolution follows a Markov process. Transition probabilities are obtained using maximum likelihood estimation and depend on the states of neighboring voxels. The isomorphic shrinkage model describes tumor shrinkage or growth in terms of layers of voxels on the tumor surface, instead of modeling individual voxels. The two proposed models were applied to data from 29 cervical cancer patients treated at Princess Margaret Cancer Centre and then compared to a constant volume approach. Model performance was measured using sensitivity and specificity.

RESULTS

The Markov model outperformed both the isomorphic shrinkage and constant volume models in terms of the trade-off between sensitivity (target coverage) and specificity (normal tissue sparing). Generally, the Markov model achieved a few percentage points in improvement in either sensitivity or specificity compared to the other models. The isomorphic shrinkage model was comparable to the Markov approach under certain parameter settings. Convex tumor shapes were easier to predict.

CONCLUSIONS

By modeling tumor geometry change at the voxel level using a probabilistic model, improvements in target coverage and normal tissue sparing are possible. Our Markov model is flexible and has tunable parameters to adjust model performance to meet a range of criteria. Such a model may support the development of an adaptive paradigm for radiation therapy of cervical cancer.

Dose escalation to high-risk sub-volumes based on non-invasive imaging of hypoxia and glycolytic activity in canine solid tumors: a feasibility study

INTRODUCTION

Glycolytic activity and hypoxia are associated with poor prognosis and radiation resistance. Including both the tumor uptake of 2-deoxy-2-[18 F]-fluorodeoxyglucose (FDG) and the proposed hypoxia tracer copper(II)diacetyl-bis(N4)-methylsemithio-carbazone (Cu-ATSM) in targeted therapy planning may therefore lead to improved tumor control. In this study we analyzed the overlap between sub-volumes of FDG and hypoxia assessed by the uptake of 64Cu-ATSM in canine solid tumors, and evaluated the possibilities for dose redistribution within the gross tumor volume (GTV).

MATERIALS AND METHODS

Positron emission tomography/computed tomography (PET/CT) scans of five spontaneous canine solid tumors were included. FDG-PET/CT was obtained at day 1, 64Cu-ATSM at day 2 and 3 (3 and 24 h pi.). GTV was delineated and CT images were co-registered. Sub-volumes for 3 h and 24 h 64Cu-ATSM (Cu3 and Cu24) were defined by a threshold based method. FDG sub-volumes were delineated at 40% (FDG40) and 50% (FDG50) of SUVmax. The size of sub-volumes, intersection and biological target volume (BTV) were measured in a treatment planning software. By varying the average dose prescription to the tumor from 66 to 85 Gy, the possible dose boost (DB) was calculated for the three scenarios that the optimal target for the boost was one, the union or the intersection of the FDG and 64Cu-ATSM sub-volumes.

RESULTS

The potential boost volumes represented a fairly large fraction of the total GTV: Cu3 49.8% (26.8-72.5%), Cu24 28.1% (2.4-54.3%), FDG40 45.2% (10.1-75.2%), and FDG50 32.5% (2.6-68.1%). A BTV including the union (∪) of Cu3 and FDG would involve boosting to a larger fraction of the GTV, in the case of Cu3∪FDG40 63.5% (51.8-83.8) and Cu3∪FDG50 48.1% (43.7-80.8). The union allowed only a very limited DB whereas the intersection allowed a substantial dose escalation.

CONCLUSIONS

FDG and 64Cu-ATSM sub-volumes were only partly overlapping, suggesting that the tracers offer complementing information on tumor physiology. Targeting the combined PET positive volume (BTV) for dose escalation within the GTV results in a limited DB. This suggests a more refined dose redistribution based on a weighted combination of the PET tracers in order to obtain an improved tumor control.

Molecular PET imaging for biology-guided adaptive radiotherapy of head and neck cancer

Integration of molecular imaging PET techniques into therapy selection strategies and radiation treatment planning for head and neck squamous cell carcinoma (HNSCC) can serve several purposes. First, pre-treatment assessments can steer decisions about radiotherapy modifications or combinations with other modalities. Second, biology-based objective functions can be introduced to the radiation treatment planning process by co-registration of molecular imaging with planning computed tomography (CT) scans. Thus, customized heterogeneous dose distributions can be generated with escalated doses to tumor areas where radiotherapy resistance mechanisms are most prevalent. Third, monitoring of temporal and spatial variations in these radiotherapy resistance mechanisms early during the course of treatment can discriminate responders from non-responders. With such information available shortly after the start of treatment, modifications can be implemented or the radiation treatment plan can be adapted tailing the biological response pattern. Currently, these strategies are in various phases of clinical testing, mostly in single-center studies. Further validation in multicenter set-up is needed. Ultimately, this should result in availability for routine clinical practice requiring stable production and accessibility of tracers, reproducibility and standardization of imaging and analysis methods, as well as general availability of knowledge and expertise. Small studies employing adaptive radiotherapy based on functional dynamics and early response mechanisms demonstrate promising results. In this context, we focus this review on the widely used PET tracer (18)F-FDG and PET tracers depicting hypoxia and proliferation; two well-known radiation resistance mechanisms.

Contribution of (18)F-Fluoro-ethyl-tyrosine Positron Emission Tomography to Target Volume Delineation in Stereotactic Radiotherapy of Malignant Cranial Base Tumours: First Clinical Experience

Increased amino acid uptake has been demonstrated in intracerebral tumours and head and neck carcinomas of squamous cell origin. We investigated the potential impact of using ¹⁸F-fluoro-ethyl-tyrosine (¹⁸F-FET)-PET/CT in addition to conventional imaging for gross tumour volume (GTV) delineation in stereotactic radiotherapy of skull base tumours. The study population consisted of 14 consecutive patients with cranial base tumours (10 with squamous cell histology, 4 others). All patients underwent a FET-PET/CT examination in addition to contrast-enhanced CT and 11 patients underwent MRI. All tumours and histologic types showed increased FET uptake. The GTV was defined by all voxels showing hyperintensity in MRI or CT (GTV_MRI/CT) or enhancement in PET (GTV_PET), forming a GTV_composite that was used for the initial treatment fields. An additional volume of infiltrative growth outside the GTV_MRI/CT of about 1.0 ± 2 cm³ (5% of the conventional volume) was demonstrated by FET-PET only (GTV_PETplus) with significant enlargement (>10% of GTV_MRI/CT) in three patients. From existing data, we found correlation between cellular density and the standardized uptake value (SUV) of FET. We were able to substantially reduce the volume of escalated radiation dose (GTV_boost) by 11 ± 2 cm³ (24%) of the conventional volume.

Radiotherapy for head and neck tumours in 2012 and beyond: conformal, tailored, and adaptive?

Intensity-modulated radiation therapy (IMRT) is a conformal irradiation technique that enables steep dose gradients. In head and neck tumours this approach spares parotid-gland function without compromise to treatment efficacy. Anatomical and molecular imaging modalities may be used to tailor treatment by enabling proper selection and delineation of target volumes and organs at risk, which in turn lead to dose prescriptions that take into account the underlying tumour biology (eg, human papillomavirus status). Therefore, adaptations can be made throughout the course of radiotherapy, as required. Planned dose increases to parts of the target volumes may also be used to match the radiosensitivity of tumours (so-called dose-painting), assessed by molecular imaging. For swift implementation of tailored and adaptive IMRT, tools and procedures, such as accurate image acquisition and reconstruction, automatic segmentation of target volumes and organs at risk, non-rigid image and dose registration, and dose summation methods, need to be developed and properly validated.

Spatially resolved regression analysis of pre-treatment FDG, FLT and Cu-ATSM PET from post-treatment FDG PET: an exploratory study

PURPOSE

To quantify associations between pre-radiotherapy and post-radiotherapy PET parameters via spatially resolved regression.

MATERIALS AND METHODS

Ten canine sinonasal cancer patients underwent PET/CT scans of [(18)F]FDG (FDG(pre)), [(18)F]FLT (FLT(pre)), and [(61)Cu]Cu-ATSM (Cu-ATSM(pre)). Following radiotherapy regimens of 50 Gy in 10 fractions, veterinary patients underwent FDG PET/CT scans at 3 months (FDG(post)). Regression of standardized uptake values in baseline FDG(pre), FLT(pre) and Cu-ATSM(pre) tumour voxels to those in FDG(post) images was performed for linear, log-linear, generalized-linear and mixed-fit linear models. Goodness-of-fit in regression coefficients was assessed by R(2). Hypothesis testing of coefficients over the patient population was performed.

RESULTS

Multivariate linear model fits of FDG(pre) to FDG(post) were significantly positive over the population (FDG(post) ~ 0.17 · FDG(pre), p = 0.03), and classified slopes of RECIST non-responders and responders to be different (0.37 vs. 0.07, p = 0.01). Generalized-linear model fits related FDG(pre) to FDG(post) by a linear power law (FDG(post) ~ FDG(pre)(0.93),p<0.001). Univariate mixture model fits of FDG(pre) improved R(2) from 0.17 to 0.52. Neither baseline FLT PET nor Cu-ATSM PET uptake contributed statistically significant multivariate regression coefficients.

CONCLUSIONS

Spatially resolved regression analysis indicates that pre-treatment FDG PET uptake is most strongly associated with three-month post-treatment FDG PET uptake in this patient population, though associations are histopathology-dependent.

Dose prescription and treatment planning based on FMISO-PET hypoxia

PURPOSE

The study presents the implementation of a novel method for incorporating hypoxia information from PET-CT imaging into treatment planning and estimates the efficiency of various optimization approaches. Its focuses on the feasibility of optimizing treatment plans based on the non-linear conversion of PET hypoxia images into radiosensitivity maps from the uptake properties of the tracers used.

MATERIAL AND METHODS

PET hypoxia images of seven head-and-neck cancer patients were used to determine optimal dose distributions needed to counteract the radiation resistance associated with tumor hypoxia assuming various scenarios regarding the evolution of the hypoxic compartment during the treatment. A research planning system for advanced studies has been used to optimize IMRT plans based on hypoxia information from patient PET images. These resulting plans were compared in terms of target coverage for the same fulfilled constraints regarding the organs at risk.

RESULTS

The results of a planning study indicated the clinical feasibility of the proposed method for treatment planning based on PET hypoxia. Antihypoxic strategies would lead to small improvements in all the patients, but higher effects are expected for the fraction of patients with hypoxic tumors. For these, individualization of the treatment based on hypoxia PET imaging could lead to improved treatment outcome while creating the premises for limiting the irradiation of the surrounding normal tissues.

CONCLUSIONS

The proposed approach offers the possibility of improved treatment results as it takes into consideration the heterogeneity and the dynamics of the hypoxic regions. It also provides early identification of the clinical cases that might benefit from dose escalation as well as the cases that could benefit from other counter-hypoxic measures.

Sparse dose painting based on a dual-pass kinetic-oxygen mapping of dynamic PET images

Development of molecular imaging such as positron-emission tomography (PET) offers an opportunity to optimize radiotherapy treatment planning by conforming the dose distribution to physiological details within tumors, so called dose painting. Quantification of the acquired images and an efficient and practical dose prescription remain two key questions in this field. This paper proposes a novel framework to optimize the dose prescription based on dual-pass modeling of dynamic [18F]FMISO PET images. An optimization algorithm for sparse dose painting (SDP) is developed by minimizing a linear combination of two terms corresponding to the efficiency and total variation of the dose distribution with the constraint of a constant mean dose. Dose efficiency is defined using the linear-quadratic model. The radiosensitivity given by the oxygen tension is estimated using a dual-pass kinetic-oxygen mapping strategy. This is achieved by integrating a realistic [18F]FMISO PET imaging simulation model, which can simulate the distribution of oxygen and tracer under the same tumor microenvironment setting. The algorithm was compared with a typical dose painting by number (DPBN) method in one data set of a patient with head and neck cancer.

Functional and molecular image guidance in radiotherapy treatment planning optimization

Functional and molecular imaging techniques are increasingly being developed and used to quantitatively map the spatial distribution of parameters, such as metabolism, proliferation, hypoxia, perfusion, and ventilation, onto anatomically imaged normal organs and tumor. In radiotherapy optimization, these imaging modalities offer the promise of increased dose sparing to high-functioning subregions of normal organs or dose escalation to selected subregions of the tumor as well as the potential to adapt radiotherapy to functional changes that occur during the course of treatment. The practical use of functional/molecular imaging in radiotherapy optimization must take into cautious consideration several factors whose influences are still not clearly quantified or well understood including patient positioning differences between the planning computed tomography and functional/molecular imaging sessions, image reconstruction parameters and techniques, image registration, target/normal organ functional segmentation, the relationship governing the dose escalation/sparing warranted by the functional/molecular image intensity map, and radiotherapy-induced changes in the image intensity map over the course of treatment. The clinical benefit of functional/molecular image guidance in the form of improved local control or decreased normal organ toxicity has yet to be shown and awaits prospective clinical trials addressing this issue.