Imaging-Based Treatment Adaptation in Radiation Oncology

How Imaging Advances Are Defining the Future of Precision Radiation Therapy

Radiation therapy is fundamental in the treatment of cancer. Imaging has always played a central role in radiation oncology. Integrating imaging technology into irradiation devices has increased the precision and accuracy of dose delivery and decreased the toxic effects of the treatment. Although CT has become the standard imaging modality in radiation therapy, the development of recently introduced next-generation imaging techniques has improved diagnostic and therapeutic decision making in radiation oncology. Functional and molecular imaging techniques, as well as other advanced imaging modalities such as SPECT, yield information about the anatomic and biologic characteristics of tumors for the radiation therapy workflow. In clinical practice, they can be useful for characterizing tumor phenotypes, delineating volumes, planning treatment, determining patients' prognoses, predicting toxic effects, assessing responses to therapy, and detecting tumor relapse. Next-generation imaging can enable personalization of radiation therapy based on a greater understanding of tumor biologic factors. It can be used to map tumor characteristics, such as metabolic pathways, vascularity, cellular proliferation, and hypoxia, that are known to define tumor phenotype. It can also be used to consider tumor heterogeneity by highlighting areas at risk for radiation resistance for focused biologic dose escalation, which can impact the radiation planning process and patient outcomes. The authors review the possible contributions of next-generation imaging to the treatment of patients undergoing radiation therapy. In addition, the possible roles of radio(geno)mics in radiation therapy, the limitations of these techniques, and hurdles in introducing them into clinical practice are discussed. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas

We develop a methodology to create data-driven predictive digital twins for optimal risk-aware clinical decision-making. We illustrate the methodology as an enabler for an anticipatory personalized treatment that accounts for uncertainties in the underlying tumor biology in high-grade gliomas, where heterogeneity in the response to standard-of-care (SOC) radiotherapy contributes to sub-optimal patient outcomes. The digital twin is initialized through prior distributions derived from population-level clinical data in the literature for a mechanistic model's parameters. Then the digital twin is personalized using Bayesian model calibration for assimilating patient-specific magnetic resonance imaging data. The calibrated digital twin is used to propose optimal radiotherapy treatment regimens by solving a multi-objective risk-based optimization under uncertainty problem. The solution leads to a suite of patient-specific optimal radiotherapy treatment regimens exhibiting varying levels of trade-off between the two competing clinical objectives: (i) maximizing tumor control (characterized by minimizing the risk of tumor volume growth) and (ii) minimizing the toxicity from radiotherapy. The proposed digital twin framework is illustrated by generating an in silico cohort of 100 patients with high-grade glioma growth and response properties typically observed in the literature. For the same total radiation dose as the SOC, the personalized treatment regimens lead to median increase in tumor time to progression of around six days. Alternatively, for the same level of tumor control as the SOC, the digital twin provides optimal treatment options that lead to a median reduction in radiation dose by 16.7% (10 Gy) compared to SOC total dose of 60 Gy. The range of optimal solutions also provide options with increased doses for patients with aggressive cancer, where SOC does not lead to sufficient tumor control.

Functional brain imaging interventions for radiation therapy planning in patients with glioblastoma: a systematic review

RATIONALE

This systematic review aims to synthesise the outcomes of different strategies of incorporating functional biological markers in the radiation therapy plans of patients with glioblastoma to support clinicians and further research.

METHODS

The systematic review protocol was registered on PROSPERO (CRD42021221021). A structured search for publications was performed following PRISMA guidelines. Quality assessment was performed using the Newcastle-Ottawa Scale. Study characteristics, intervention methodology and outcomes were extracted using Covidence. Data analysis focused on radiation therapy target volumes, toxicity, dose distributions, recurrence and survival mapped to functional image-guided radiotherapy interventions.

RESULTS

There were 5733 citations screened, with 53 citations (n = 32 studies) meeting review criteria. Studies compared standard radiation therapy planning volumes with functional image-derived volumes (n = 20 studies), treated radiation therapy volumes with recurrences (n = 15 studies), the impact on current standard target delineations (n = 9 studies), treated functional volumes and survival (n = 8 studies), functionally guided dose escalation (n = 8 studies), radiomics (n = 4 studies) and optimal organ at risk sparing (n = 3 studies). The approaches to target outlining and dose escalation were heterogeneous. The analysis indicated an improvement in median overall survival of over two months compared with a historical control group. Simultaneous-integrated-boost dose escalation of 72-76 Gy in 30 fractions appeared to have an acceptable toxicity profile when delivered with inverse planning to a volume smaller than 100 cm[Formula: see text].

CONCLUSION

There was significant heterogeneity between the approaches taken by different study groups when implementing functional image-guided radiotherapy. It is recommended that functional imaging data be incorporated into the gross tumour volume with appropriate technology-specific margins used to create the clinical target volume when designing radiation therapy plans for patients with glioblastoma.

Multi-parametric MRI (mpMRI) for treatment response assessment of radiation therapy

Magnetic resonance imaging (MRI) plays an important role in the modern radiation therapy (RT) workflow. In comparison with computed tomography (CT) imaging, which is the dominant imaging modality in RT, MRI possesses excellent soft-tissue contrast for radiographic evaluation. Based on quantitative models, MRI can be used to assess tissue functional and physiological information. With the developments of scanner design, acquisition strategy, advanced data analysis, and modeling, multiparametric MRI (mpMRI), a combination of morphologic and functional imaging modalities, has been increasingly adopted for disease detection, localization, and characterization. Integration of mpMRI techniques into RT enriches the opportunities to individualize RT. In particular, RT response assessment using mpMRI allows for accurate characterization of both tissue anatomical and biochemical changes to support decision-making in monotherapy of radiation treatment and/or systematic cancer management. In recent years, accumulating evidence have, indeed, demonstrated the potentials of mpMRI in RT response assessment regarding patient stratification, trial benchmarking, early treatment intervention, and outcome modeling. Clinical application of mpMRI for treatment response assessment in routine radiation oncology workflow, however, is more complex than implementing an additional imaging protocol; mpMRI requires additional focus on optimal study design, practice standardization, and unified statistical reporting strategy to realize its full potential in the context of RT. In this article, the mpMRI theories, including image mechanism, protocol design, and data analysis, will be reviewed with a focus on the radiation oncology field. Representative works will be discussed to demonstrate how mpMRI can be used for RT response assessment. Additionally, issues and limits of current works, as well as challenges and potential future research directions, will also be discussed.

Towards an Image-Informed Mathematical Model of In Vivo Response to Fractionated Radiation Therapy

Simple Summary

Using medical imaging data and computational models, we develop a modeling framework to provide personalized treatment response forecasts to fractionated radiation therapy for individual tumors. We evaluate this approach in an animal model of brain cancer and forecast changes in tumor cellularity and vasculature.

Abstract

Fractionated radiation therapy is central to the treatment of numerous malignancies, including high-grade gliomas where complete surgical resection is often impractical due to its highly invasive nature. Development of approaches to forecast response to fractionated radiation therapy may provide the ability to optimize or adapt treatment plans for radiotherapy. Towards this end, we have developed a family of 18 biologically-based mathematical models describing the response of both tumor and vasculature to fractionated radiation therapy. Importantly, these models can be personalized for individual tumors via quantitative imaging measurements. To evaluate this family of models, rats (n = 7) with U-87 glioblastomas were imaged with magnetic resonance imaging (MRI) before, during, and after treatment with fractionated radiotherapy (with doses of either 2 Gy/day or 4 Gy/day for up to 10 days). Estimates of tumor and blood volume fractions, provided by diffusion-weighted MRI and dynamic contrast-enhanced MRI, respectively, were used to calibrate tumor-specific model parameters. The Akaike Information Criterion was employed to select the most parsimonious model and determine an ensemble averaged model, and the resulting forecasts were evaluated at the global and local level. At the global level, the selected model’s forecast resulted in less than 16.2% error in tumor volume estimates. At the local (voxel) level, the median Pearson correlation coefficient across all prediction time points ranged from 0.57 to 0.87 for all animals. While the ensemble average forecast resulted in increased error (ranging from 4.0% to 1063%) in tumor volume predictions over the selected model, it increased the voxel wise correlation (by greater than 12.3%) for three of the animals. This study demonstrates the feasibility of calibrating a model of response by serial quantitative MRI data collected during fractionated radiotherapy to predict response at the conclusion of treatment.

Quantitative FDG PET Assessment for Oncology Therapy

Simple Summary

PET enables quantitative assessment of tumour biology in vivo. Accumulation of F-18 fluorodeoxyglucose (FDG) may reflect tumour metabolic activity. Quantitative assessment of FDG uptake can be applied for treatment monitoring. Numerous studies indicated biochemical change assessed by FDG-PET as a more sensitive marker than morphological change. Those with complete metabolic response after therapy may show better prognosis. Assessment of metabolic change may be performed using absolute FDG uptake or metabolic tumour volume. More recently, radiomics approaches have been applied to FDG PET. Texture analysis quantifies intratumoral heterogeneity in a voxel-by-voxel basis. Combined with various machine learning techniques, these new quantitative parameters hold a promise for assessing tissue characterization and predicting treatment effect, and could also be used for future prognosis of various tumours.

Abstract

Positron emission tomography (PET) has unique characteristics for quantitative assessment of tumour biology in vivo. Accumulation of F-18 fluorodeoxyglucose (FDG) may reflect tumour characteristics based on its metabolic activity. Quantitative assessment of FDG uptake can often be applied for treatment monitoring after chemotherapy or chemoradiotherapy. Numerous studies indicated biochemical change assessed by FDG PET as a more sensitive marker than morphological change estimated by CT or MRI. In addition, those with complete metabolic response after therapy may show better disease-free survival and overall survival than those with other responses. Assessment of metabolic change may be performed using absolute FDG uptake in the tumour (standardized uptake value: SUV). In addition, volumetric parameters such as metabolic tumour volume (MTV) have been introduced for quantitative assessment of FDG uptake in tumour. More recently, radiomics approaches that focus on image-based precision medicine have been applied to FDG PET, as well as other radiological imaging. Among these, texture analysis extracts intratumoral heterogeneity on a voxel-by-voxel basis. Combined with various machine learning techniques, these new quantitative parameters hold a promise for assessing tissue characterization and predicting treatment effect, and could also be used for future prognosis of various tumours, although multicentre clinical trials are needed before application in clinical settings.

Adherence to pretreatment and intratreatment imaging of head and neck squamous cell carcinoma patients undergoing (chemo) radiotherapy in a research setting

PURPOSE

The emerge of improved personalized treatment adaptations and outcome prediction is accompanied with increasing non-invasive assessments in early treatment phase, leading to increased patient burden. This study assessed the adherence of patients with head and neck squamous cell carcinoma (HNSCC) to undergo pretreatment and research-related intratreatment imaging, and assessed which factors caused drop-out.

METHOD

Between 2013 and 2019, advanced-staged HNSCC patients were prospectively included, underwent (chemo) radiotherapy with curative intent and planned for both pre-treatment and intratreatment sequential 18F-FDG-PET/CT, 18F-FDG-PET/MRI and thereafter MRI (including DWI/DCE). Drop-out-factors were described as healthcare-related (logistics and imaging-system defects) and patient-related (psychological, physical, not-specified). Common Toxicity Criteria (CTC) were routinely scored by radiation/medical oncologists throughout the first 3 weeks, and compared between patient drop-outs and who complete imaging.

RESULTS

Ninety-seven patients (mean age 61 ± 6.8 years) were included; 95 patients (97.9%) underwent pretreatment imaging and 63 (64.9%) intratreatment imaging. For 18F-FDG-PET/CT, 18F-FDG-PET/MRI and MRI pretreatment drop-outs were 2, 10 and 3 patients and for intratreatment drop-outs were 34, 39 and 35 patients, respectively. Patient-related drop-out-factors were physical (n = 16, e.g. dysphagia), psychological (n = 6, e.g. claustrophobia) and non-specified (n = 12). Healthcare-related drop-out-factors were logistics (n = 6) and 18F-FDG-PET/CT-/MRI-system defects (n = 2). The CTC mucosal toxicity was significantly higher (p = 0.023) at week 2 of (chemo)radiotherapy in patient drop-outs than with complete imaging.

CONCLUSIONS

The drop-out frequency of advanced-staged HNSCC patients for imaging during (chemo)radiotherapy in a research-setting was high and mainly patient-related. Treatment of patient-related inconveniences, communication of rationale and healthcare-related imaging protocol efficiency improvements may contribute to improved adherence.

Quantitative imaging for radiotherapy purposes

Quantitative imaging biomarkers show great potential for use in radiotherapy. Quantitative images based on microscopic tissue properties and tissue function can be used to improve contouring of the radiotherapy targets. Furthermore, quantitative imaging biomarkers might be used to predict treatment response for several treatment regimens and hence be used as a tool for treatment stratification, either to determine which treatment modality is most promising or to determine patient-specific radiation dose. Finally, patient-specific radiation doses can be further tailored to a tissue/voxel specific radiation dose when quantitative imaging is used for dose painting. In this review, published standards, guidelines and recommendations on quantitative imaging assessment using CT, PET and MRI are discussed. Furthermore, critical issues regarding the use of quantitative imaging for radiation oncology purposes and resultant pending research topics are identified.

Radiation-Induced Lung Injury: Assessment and Management

Radiation-induced lung injury (RILI) encompasses any lung toxicity induced by radiation therapy (RT) and manifests acutely as radiation pneumonitis and chronically as radiation pulmonary fibrosis. Because most patients with thoracic and breast malignancies are expected to undergo RT in their lifetime, many with curative intent, the population at risk is significant. Furthermore, indications for thoracic RT are expanding given the advent of stereotactic body radiation therapy (SBRT) or stereotactic ablative radiotherapy (SABR) for early-stage lung cancer in nonsurgical candidates as well as oligometastatic pulmonary disease from any solid tumor. Fortunately, the incidence of serious pulmonary complications from RT has decreased secondary to advances in radiation delivery techniques. Understanding the temporal relationship between RT and injury as well as the patient, disease, and radiation factors that help distinguish RILI from other etiologies is necessary to prevent misdiagnosis. Although treatment of acute pneumonitis is dependent on clinical severity and typically responds completely to corticosteroids, accurately diagnosing and identifying patients who may progress to fibrosis is challenging. Current research advances include high-precision radiation techniques, an improved understanding of the molecular basis of RILI, the development of small and large animal models, and the identification of candidate drugs for prevention and treatment.

Functional Adaptation in Radiation Therapy

The promise of adaptive therapy to improve outcomes in radiation oncology has been an area of interest and research in the community for many years. One of the sources of data that can be used to drive adaptive therapy is functional information about the tumor or normal tissues. This avenue of adaptation includes many potential sources of data including global markers and functional imaging. Global markers can be assessments derived from blood measurements, patient functional testing, and circulating tumor material and functional imaging data comprises spatial physiological information from various imaging studies such as positron emission tomography, magnetic resonance imaging, and single photon emission computed tomography. The goal of functional adaptation is to use these functional data to adapt radiation therapy to improve patient outcomes. While functional adaptation holds a lot of promise, there are challenges such as quantifying and minimizing uncertainties, streamlining clinical implementation, determining the ideal way to incorporate information within treatment plan optimization, and proving the clinical benefit through trials. This paper will discuss the types of functional information currently being used for adaptation, highlight several areas where functional adaptation has been studied, and introduce some of the barriers to more widespread clinical implementation.

[18F]-SuPAR: A Radiofluorinated Probe for Noninvasive Imaging of DNA Damage-Dependent Poly(ADP-ribose) Polymerase Activity

Poly(ADP ribose) polymerase (PARP) enzymes generate poly(ADP ribose) post-translational modifications on target proteins for an array of functions centering on DNA and cell stress. PARP isoforms 1 and 2 are critically charged with the surveillance of DNA integrity and are the first line guardians of the genome against DNA breaks. Here we present a novel probe ([¹⁸F]-SuPAR) for noninvasive imaging of PARP-1/2 activity using positron emission tomography (PET). [¹⁸F]-SuPAR is a radiofluorinated nicotinamide adenine dinucleotide (NAD) analog that can be recognized by PARP-1/2 and incorporated into the long branched polymers of poly(ADP ribose) (PAR). The measurement of PARP-1/2 activity was supported by a reduction of radiotracer uptake in vivo following PARP-1/2 inhibition with talazoparib treatment, a potent PARP inhibitor recently approved by FDA for treatment of breast cancer, as well as ex vivo colocalization of radiotracer analog and poly(ADP ribose). With [¹⁸F]-SuPAR, we were able to map the dose- and time-dependent activation of PARP-1/2 following radiation therapy in breast and cervical cancer xenograft mouse models. Tumor response to therapy was determined by [¹⁸F]-SuPAR PET within 8 h of administration of a single dose of radiation equivalent to one round of stereotactic ablative radiotherapy.

Potentials and challenges of diffusion-weighted magnetic resonance imaging in radiotherapy

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Discussion of DW imaging protocols and imaging setup.

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Discussion of mono- and bi-exponential models for quantitative parameter extraction.

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Review of recent publications investigating potential benefits of using DWI in RT, including detailed synoptic table.

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Detailed discussion of geometric and quantitative accuracy of DW imaging and DW-derived parameters.

Purpose

To review the potential and challenges of integrating diffusion weighted magnetic resonance imaging (DWI) into radiotherapy (RT).

Content

Details related to image acquisition of DWI for RT purposes are discussed, along with the challenges with respect to geometric accuracy and the robustness of quantitative parameter extraction. An overview of diffusion- and perfusion-related parameters derived from mono- and bi-exponential models is provided, and their role as potential RT biomarkers is discussed. Recent studies demonstrating potential of DWI in different tumor sites such as the head and neck, rectum, cervix, prostate, and brain, are reviewed in detail.

Conclusion

DWI has shown promise for RT outcome prediction, response assessment, as well as for tumor delineation and characterization in several cancer types. Geometric and quantification robustness is challenging and has to be addressed adequately. Evaluation in larger clinical trials with well designed imaging protocol and advanced analysis models is needed to develop the optimal strategy for integrating DWI in RT.

Evaluating the Use of 18F-FDG PET CT for External Beam Radiotherapy Planning in Gynaecological Malignancies

PURPOSE OF REVIEW

To evaluate the evidence for the use of fluorine-18-fluorodeoyglucose (18F-FDG) PET CT in external beam radiotherapy planning for treatment of gynaecological malignancies.

RECENT FINDINGS

Our review confirms that the incorporation of 18F-FDG PET CT during radiotherapy planning may decrease inter-observer variability during target delineation. It can also provide useful functional information regarding the tumour, which may facilitate the development of techniques for dose escalation and 'dose painting' not only for primary disease, especially in cervical cancer, but also nodal metastasis. The utilisation of this functional modality in external beam radiotherapy planning, particularly in locally advanced cervical malignancy, is an exciting topic that warrants further prospective research. Perhaps the most valuable role may be the potential to deliver dose escalation to 18F-FDG PET CT avid targets previously limited by organ at risk constraints, now that we have significantly more advanced radiotherapy planning tools at our disposal.

Multiple-CT optimization of intensity-modulated proton therapy - Is it possible to eliminate adaptive planning?

BACKGROUND AND PURPOSE

We hypothesized that a plan's robustness to anatomical changes can be improved by optimizing with multiple CT scans of a patient. The purpose of this study was to determine whether an intensity modulated proton therapy (IMPT) plan could be developed to meet dose criteria on both planning and adaptive CT plans.

MATERIAL AND METHODS

Eight lung cancer patients who underwent adaptive IMPT were retrospectively selected. Each patient had two CTs: a primary planning CT (PCT) and an adaptive planning CT (ACT), and IMPT plans associated with the scans. PCT and ACT were then used in combination to optimize one plan (MCT plan). The doses to the target and organs at risk from the PCT plan, ACT plan, P-ACT plan (PCT plan calculated on ACT data), and MCT plans calculated on both CTs were compared.

RESULTS

The MCT plan maintained the D_95% on both CTs (mean, 65.99 Gy on PCT and 66.02 Gy on ACT). Target dose coverage on ACT was significantly better with the MCT plan than with the P-ACT plan (p = 0.01). MCT plans had slightly higher lung V₂₀ (0.6%, p = 0.02) than did PCT plans. The various plans showed no statistically significant difference in heart and spinal cord dose.

CONCLUSIONS

The results of this study indicate that an IMPT plan can meet the dose criteria on both PCT and ACT, and that MCT optimization can improve the plan's robustness to anatomical change.

Residual tumour hypoxia in head-and-neck cancer patients undergoing primary radiochemotherapy, final results of a prospective trial on repeat FMISO-PET imaging

BACKGROUND

Hypoxia is a well recognised parameter of tumour resistance to radiotherapy, a number of anticancer drugs and potentially immunotherapy. In a previously published exploration cohort of 25 head and neck squamous cell carcinoma (HNSCC) patients on [¹⁸F]fluoromisonidazole positron emission tomography (FMISO-PET) we identified residual tumour hypoxia during radiochemotherapy, not before start of treatment, as the driving mechanism of hypoxia-mediated therapy resistance. Several quantitative FMISO-PET parameters were identified as potential prognostic biomarkers. Here we present the results of the prospective validation cohort, and the overall results of the study.

METHODS

FMISO-PET/CT images of further 25 HNSCC patients were acquired at four time-points before and during radiochemotherapy (RCHT). Peak standardised uptake value, tumour-to-background ratio, and hypoxic volume were analysed. The impact of the potential prognostic parameters on loco-regional tumour control (LRC) was validated by the concordance index (ci) using univariable and multivariable Cox models based on the exploration cohort. Log-rank tests were employed to compare the endpoint between risk groups.

RESULTS

The two cohorts differed significantly in several baseline parameters, e.g., tumour volume, hypoxic volume, HPV status, and intercurrent death. Validation was successful for several FMISO-PET parameters and showed the highest performance (ci=0.77-0.81) after weeks 1 and 2 of treatment. Cut-off values for the FMISO-PET parameters could be validated after week 2 of RCHT. Median values for the residual hypoxic volume, defined as the ratio of the hypoxic volume in week 2 of RCHT and at baseline, stratified patients into groups of significantly different LRC when applied to the respective other cohort.

CONCLUSION

Our study validates that residual tumour hypoxia during radiochemotherapy is a major driver of therapy resistance of HNSCC, and that hypoxia after the second week of treatment measured by FMISO-PET may serve as biomarker for selection of patients at high risk of loco-regional recurrence after state-of-the art radiochemotherapy.

The clinical target volume in lung, head-and-neck, and esophageal cancer: Lessons from pathological measurement and recurrence analysis

Radiotherapy research has achieved remarkable progress in target volume definition. Advances in medical imaging facilitate more precise localization of the gross tumor volume, alongside a more detailed understanding of the geometric uncertainties associated with treatment delivery that has enabled robust safety margins to be customized to the specific treatment scenario at hand. By contrast, the clinical target volume, meant to encompass gross tumor, as well as, adjacent sub-clinical disease, has evolved very little. It is more often defined by clinician experience and institutional convention than on a patient-specific basis. This disparity arises from the inherent invisibility of sub-clinical disease in current medical imaging. Its incidence and expanse can only be ascertained via indirect means. This article reviews two such strategies: histopathological measurements on resection specimen and analyses of locoregional recurrences after radiotherapy.

Radiation Toxicity to the Cardiovascular System

Radiation therapy is an important component of cancer treatment, and today, it is applied to approximately 50% of malignancies, including valvular, myocardial, pericardial, coronary or peripheral vascular disease, and arrhythmias. An increased clinical suspicion and knowledge of those mechanisms is important to initiate appropriate screening for the optimal diagnosis and treatment. As the number of cancer survivors has been steadily increasing over the last decades, cardio-oncology, an evolving subspecialty of cardiology, will soon play a pivotal role in raising awareness of the increased cardiovascular risk and formulate strategies to optimally manage patients in this unique population.

Functional Imaging in Radiotherapy in the Netherlands: Availability and Impact on Clinical Practice

AIMS

Functional imaging with positron emission tomography/computed tomography (PET/CT) and multiparametric magnetic resonance (mpMR) is increasingly applied for radiotherapy purposes. However, evidence and experience are still limited, and this may lead to clinically relevant differences in accessibility, interpretation and decision making. We investigated the current patterns of care in functional imaging for radiotherapy in the Netherlands in a care evaluation study.

MATERIALS AND METHODS

The availability of functional imaging in radiotherapy centres in the Netherlands was evaluated; features available in >80% of academic and >80% of non-academic centres were considered standard of care. The impact of functional imaging on clinical decision making was evaluated using case questionnaires on lung, head/neck, breast and prostate cancer, with multiple-choice questions on primary tumour delineation, nodal involvement, distant metastasis and incidental findings. Radiation oncologists were allowed to discuss cases in a multidisciplinary approach. Ordinal answers were evaluated by median and interquartile range (IQR) to identify the extent and variability of clinical impact; additional patterns were evaluated descriptively.

RESULTS

Information was collected from 18 radiotherapy centres in the Netherlands (all except two). PET/CT was available for radiotherapy purposes to 94% of centres; 67% in the treatment position and 61% with integrated planning CT. mpMR was available to all centres; 61% in the treatment position. Technologists collaborated between departments to acquire PET/CT or mpMR for radiotherapy in 89%. All sites could carry out image registration for target definition. Functional imaging generally showed a high clinical impact (average median 4.3, scale 1-6) and good observer agreement (average IQR 1.1, scale 0-6). However, several issues resulted in ignoring functional imaging (e.g. positional discrepancies, central necrosis) or poor observer agreement (atelectasis, diagnostic discrepancies, conformation strategies).

CONCLUSIONS

Access to functional imaging with PET/CT and mpMR for radiotherapy purposes, with collaborating technologists and multimodal delineation, can be considered standard of care in the Netherlands. For several specific clinical situations, the interpretation of images may benefit from further standardisation.