Functional imaging for radiotherapy treatment planning: current status and future directions-a review

Interim 18F-FDG-PET based response-adaptive dose escalation of proton therapy for head and neck cancer: a treatment planning feasibility study

BACKGROUND

Image-driven dose escalation to tumor subvolumes has been proposed to improve treatment outcome in head and neck cancer (HNC). We used 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) acquired at baseline and into treatment (interim) to identify biologic target volumes (BTVs). We assessed the feasibility of interim dose escalation to the BTV with proton therapy by simulating the effects to organs at risk (OARs).

METHODS

We used the semiautomated just-enough-interaction (JEI) method to identify BTVs in 18F-FDG-PET images from nine HNC patients. Between baseline and interim FDG-PET, patients received photon radiotherapy. BTV was identified assuming that high standardized uptake value (SUV) at interim reflected tumor radioresistance. Using Eclipse (Varian Medical Systems), we simulated a 10% (6.8 Gy(RBE1.1)) and 20% (13.6 Gy(RBE1.1)) dose escalation to the BTV with protons and compared results with proton plans without dose escalation.

RESULTS

At interim 18F-FDG-PET, radiotherapy resulted in reduced SUV compared to baseline. However, spatial overlap between high-SUV regions at baseline and interim allowed for BTV identification. Proton therapy planning demonstrated that dose escalation to the BTV was feasible, and except for some 20% dose escalation plans, OAR doses did not significantly increase.

CONCLUSION

Our in silico analysis demonstrated the potential for interim 18F-FDG-PET response-adaptive dose escalation to the BTV with proton therapy. This approach may give more efficient treatment to HNC with radioresistant tumor subvolumes without increasing normal tissue toxicity. Studies in larger cohorts are required to determine the full potential for interim 18F-FDG-PET-guided dose escalation of proton therapy in HNC.

The significance of partial volume effect on the estimation of hypoxic tumour volume with [18F]FMISO PET/CT

BACKGROUND

The purpose of this study was to evaluate how a retrospective correction of the partial volume effect (PVE) in [18F]fluoromisonidazole (FMISO) PET imaging, affects the hypoxia discoverability within a gross tumour volume (GTV). This method is based on recovery coefficients (RC) and is tailored for low-contrast tracers such as FMISO. The first stage was the generation of the scanner's RC curves, using spheres with diameters from 10 to 37 mm, and the same homogeneous activity concentration, positioned in lower activity concentration background. Six sphere-to-background contrast ratios were used, from 10.0:1, down to 2.0:1, in order to investigate the dependence of RC on both the volume and the contrast ratio. The second stage was to validate the recovery-coefficient correction method in a more complex environment of non-spherical lesions of different volumes and inhomogeneous activity concentration. Finally, we applied the correction method to a clinical dataset derived from a prospective imaging trial (DRKS00003830): forty nine head and neck squamous cell carcinoma (HNSCC) cases who had undergone FMISO PET/CT scanning for the quantification of tumour hypoxia before (W0), 2 weeks (W2) and 5 weeks (W5) after the beginning of radiotherapy. Here, PVE was found to cause an underestimation of the activity in small volumes with high FMISO signal.

RESULTS

The application of the proposed correction method resulted in a statistically significant increase of both the hypoxic subvolume (171% at W0, 691% at W2 and 4.60 × 103% at W5 with p < 0.001) and the FMISO standardised uptake value (SUV) (27% at W0, 21% at W2 and by 25% at W5 with p < 0.001) within the primary GTV.

CONCLUSIONS

The proposed PVE-correction method resulted in a statistically significant increase of the hypoxic fraction (HF) with p < 0.001 and demonstrated results in better agreement with published HF data for HNSCC. To summarise, the proposed RC-based correction method can be a useful tool for a retrospective compensation against PVE.

The influence of patient positioning and immobilization equipment on MR image quality and image registration in radiation therapy

INTRODUCTION

MRI is preferred for brain tumor assessment, while CT is used for radiotherapy simulation. This study evaluated immobilization equipment's impact on CT-MRI registration accuracy and MR image quality in RT setup.

METHODS

We included CT and MR images from 11 patients with high-grade glioma, all of whom were immobilized with a thermoplastic mask and headrest. T1- and T2-weighted MR images were acquired using an MR head coil in a diagnostic setup (DS) and a body matrix coil in RT setup. To assess MR image quality, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were considered in some dedicated regions of interest. We also evaluated the impact of immobilization equipment on CT-MRI rigid registration using line profile and external contour methods.

RESULTS

The CNR and SNR reduction was in the RT setup of imaging. This was more evident in T1-weighted images than in T2-weighted ones. The SNR decreased by 14.91% and 12.09%, while CNR decreased by 25.12% and 20.15% in T1- and T2-weighted images, respectively. The immobilization equipment in the RT setup decreased the mean error in rigid registration by 1.02 mm. The external contour method yielded Dice similarity coefficients (DSC) of 0.84 and 0.92 for CT-DS MRI and CT-RT MRI registration, respectively.

CONCLUSION

The image quality reduction in the RT setup was due to the imaged region's anatomy and its position relative to the applied coil. Furthermore, optimizing the pulse sequence is crucial for MR imaging in RT applications. Although the use of immobilization equipment may decrease the image quality in the RT setup, it does not affect organ delineation, and the image quality is still satisfactory for this purpose. Also, the use of immobilization equipment in the RT setup has increased registration accuracy.

Effect of synthetic CT on dose-derived toxicity predictors for MR-only prostate radiotherapy

Objectives

Toxicity-driven adaptive radiotherapy (RT) is enhanced by the superior soft tissue contrast of magnetic resonance (MR) imaging compared with conventional computed tomography (CT). However, in an MR-only RT pathway synthetic CTs (sCT) are required for dose calculation. This study evaluates 3 sCT approaches for accurate rectal toxicity prediction in prostate RT.

Methods

Thirty-six patients had MR (T2-weighted acquisition optimized for anatomical delineation, and T1-Dixon) with same day standard-of-care planning CT for prostate RT. Multiple sCT were created per patient using bulk density (BD), tissue stratification (TS, from T1-Dixon) and deep-learning (DL) artificial intelligence (AI) (from T2-weighted) approaches for dose distribution calculation and creation of rectal dose volume histograms (DVH) and dose surface maps (DSM) to assess grade-2 (G2) rectal bleeding risk.

Results

Maximum absolute errors using sCT for DVH-based G2 rectal bleeding risk (risk range 1.6% to 6.1%) were 0.6% (BD), 0.3% (TS) and 0.1% (DL). DSM-derived risk prediction errors followed a similar pattern. DL sCT has voxel-wise density generated from T2-weighted MR and improved accuracy for both risk-prediction methods.

Conclusions

DL improves dosimetric and predicted risk calculation accuracy. Both TS and DL methods are clinically suitable for sCT generation in toxicity-guided RT, however, DL offers increased accuracy and offers efficiencies by removing the need for T1-Dixon MR.

Advances in knowledge

This study demonstrates novel insights regarding the effect of sCT on predictive toxicity metrics, demonstrating clear accuracy improvement with increased sCT resolution. Accuracy of toxicity calculation in MR-only RT should be assessed for all treatment sites where dose to critical structures will guide adaptive-RT strategies.

Clinical trial registration number

Patient data were taken from an ethically approved (UK Health Research Authority) clinical trial run at Guy's and St Thomas' NHS Foundation Trust. Study Name: MR-simulation in Radiotherapy for Prostate Cancer. ClinicalTrials.gov Identifier: NCT03238170.

The Use of MR-Guided Radiation Therapy for Head and Neck Cancer and Recommended Reporting Guidance

Although magnetic resonance imaging (MRI) has become standard diagnostic workup for head and neck malignancies and is currently recommended by most radiological societies for pharyngeal and oral carcinomas, its utilization in radiotherapy has been heterogeneous during the last decades. However, few would argue that implementing MRI for annotation of target volumes and organs at risk provides several advantages, so that implementation of the modality for this purpose is widely accepted. Today, the term MR-guidance has received a much broader meaning, including MRI for adaptive treatments, MR-gating and tracking during radiotherapy application, MR-features as biomarkers and finally MR-only workflows. First studies on treatment of head and neck cancer on commercially available dedicated hybrid-platforms (MR-linacs), with distinct common features but also differences amongst them, have also been recently reported, as well as "biological adaptation" based on evaluation of early treatment response via functional MRI-sequences such as diffusion weighted ones. Yet, all of these approaches towards head and neck treatment remain at their infancy, especially when compared to other radiotherapy indications. Moreover, the lack of standardization for reporting MR-guided radiotherapy is a major obstacle both to further progress in the field and to conduct and compare clinical trials. Goals of this article is to present and explain all different aspects of MR-guidance for radiotherapy of head and neck cancer, summarize evidence, as well as possible advantages and challenges of the method and finally provide a comprehensive reporting guidance for use in clinical routine and trials.

Real-time motion management in MRI-guided radiotherapy: Current status and AI-enabled prospects

MRI-guided radiotherapy (MRIgRT) is a highly complex treatment modality, allowing adaptation to anatomical changes occurring from one treatment day to the other (inter-fractional), but also to motion occurring during a treatment fraction (intra-fractional). In this vision paper, we describe the different steps of intra-fractional motion management during MRIgRT, from imaging to beam adaptation, and the solutions currently available both clinically and at a research level. Furthermore, considering the latest developments in the literature, a workflow is foreseen in which motion-induced over- and/or under-dosage is compensated in 3D, with minimal impact to the radiotherapy treatment time. Considering the time constraints of real-time adaptation, a particular focus is put on artificial intelligence (AI) solutions as a fast and accurate alternative to conventional algorithms.

Multi-organ segmentation of CT via convolutional neural network: impact of training setting and scanner manufacturer

Objective. Automated organ segmentation on CT images can enable the clinical use of advanced quantitative software devices, but model performance sensitivities must be understood before widespread adoption can occur. The goal of this study was to investigate performance differences between Convolutional Neural Networks (CNNs) trained to segment one (single-class) versus multiple (multi-class) organs, and between CNNs trained on scans from a single manufacturer versus multiple manufacturers.Methods. The multi-class CNN was trained on CT images obtained from 455 whole-body PET/CT scans (413 for training, 42 for testing) taken with Siemens, GE, and Phillips PET/CT scanners where 16 organs were segmented. The multi-class CNN was compared to 16 smaller single-class CNNs trained using the same data, but with segmentations of only one organ per model. In addition, CNNs trained on Siemens-only (N = 186) and GE-only (N = 219) scans (manufacturer-specific) were compared with CNNs trained on data from both Siemens and GE scanners (manufacturer-mixed). Segmentation performance was quantified using five performance metrics, including the Dice Similarity Coefficient (DSC).Results. The multi-class CNN performed well compared to previous studies, even in organs usually considered difficult auto-segmentation targets (e.g., pancreas, bowel). Segmentations from the multi-class CNN were significantly superior to those from smaller single-class CNNs in most organs, and the 16 single-class models took, on average, six times longer to segment all 16 organs compared to the single multi-class model. The manufacturer-mixed approach achieved minimally higher performance over the manufacturer-specific approach.Significance. A CNN trained on contours of multiple organs and CT data from multiple manufacturers yielded high-quality segmentations. Such a model is an essential enabler of image processing in a software device that quantifies and analyzes such data to determine a patient's treatment response. To date, this activity of whole organ segmentation has not been adopted due to the intense manual workload and time required.

Clinical use of positron emission tomography for radiotherapy planning - Medical physics considerations

PET/CT imaging plays an increasing role in radiotherapy treatment planning. The aim of this article was to identify the major use cases and technical as well as medical physics challenges during integration of these data into treatment planning. Dedicated aspects, such as (i) PET/CT-based radiotherapy simulation, (ii) PET-based target volume delineation, (iii) functional avoidance to optimized organ-at-risk sparing and (iv) functionally adapted individualized radiotherapy are discussed in this article. Furthermore, medical physics aspects to be taken into account are summarized and presented in form of check-lists.

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.

To see or not to see: Evaluation of magnetic resonance imaging sequences for use in MR Linac-based radiotherapy treatment

BACKGROUND/PURPOSE

This work evaluated the suitability of MR derived sequences for use in online adaptive RT workflows on a 1.5 Tesla (T) MR-Linear Accelerator (MR Linac).

MATERIALS/METHODS

Non-patient volunteers were recruited to an ethics approved MR Linac imaging study. Participants attended 1-3 imaging sessions in which a combination of DIXON, 2D and 3D volumetric T1 and T2 weighted images were acquired axially, with volunteers positioned using immobilisation devices typical for radiotherapy to the anatomical region being scanned. Images from each session were appraised by three independent reviewers to determine optimal sequences over six anatomical regions: head and neck, female and male pelvis, thorax (lung), thorax (breast/chest wall) and abdomen. Site specific anatomical structures were graded by the perceived ability to accurately contour a typical organ at risk. Each structure was independently graded on a 4-point Likert scale as 'Very Clear', 'Clear', 'Unclear' or 'Not visible' by observers, consisting of radiographers (therapeutic and diagnostic) and clinicians.

RESULTS

From July 2019 to September 2019, 18 non-patient volunteers underwent 24 imaging sessions in the following anatomical regions: head and neck (n=3), male pelvis (n=4), female pelvis (n=5), lung/oesophagus (n=5) abdomen (n=4) and chest wall/breast (n=3). T2 sequences were the most preferred for perceived ability to contour anatomy in both male and female pelvis. For all other sites T1 weighted DIXON sequences were most favourable.

CONCLUSION

This study has determined the preferential sequence selection for organ visualisation, as a pre-requisite to our institution adopting MR-guided radiotherapy for a more diverse range of disease sites.

The patients view on genetics and functional imaging for precision medicine: a willingness-to-pay analysis

Purpose: Willingness-to-pay (WTP) analyses can support allocation processes considering the patients preferences in personalized medicine. However, genetic testing especially might imply ethical concerns that have to be considered. Methods: A WTP questionnaire was designed to compare preferences for imaging and genetic testing in cancer patients and to evaluate potential ethical concerns. Results: Comparing the options of imaging and genetics showed comparable WTP values. Ethical concerns about genetic testing seemed to be minor. Treatment success was the top priority irrespective of the diagnostic modality. In general, the majority of patients considered personalized medicine to be beneficial. Conclusion: Most patients valued personalized approaches and rated the benefits of precision medicine of overriding importance irrespective of modality or ethical concerns.

Development of nanotechnology-mediated precision radiotherapy for anti-metastasis and radioprotection

Radiotherapy (RT), including external beam RT and internal radiation therapy, uses high-energy ionizing radiation to kill tumor cells.

Improving radiation physics, tumor visualisation, and treatment quantification in radiotherapy with spectral or dual-energy CT

Over the past decade, spectral or dual‐energy CT has gained relevancy, especially in oncological radiology. Nonetheless, its use in the radiotherapy (RT) clinic remains limited. This review article aims to give an overview of the current state of spectral CT and to explore opportunities for applications in RT.

In this article, three groups of benefits of spectral CT over conventional CT in RT are recognized. Firstly, spectral CT provides more information of physical properties of the body, which can improve dose calculation. Furthermore, it improves the visibility of tumors, for a wide variety of malignancies as well as organs‐at‐risk OARs, which could reduce treatment uncertainty. And finally, spectral CT provides quantitative physiological information, which can be used to personalize and quantify treatment.

Comparison of different deep learning architectures for synthetic CT generation from MR images

PURPOSE

Among the different available methods for synthetic CT generation from MR images for the task of MR-guided radiation planning, the deep learning algorithms have and do outperform their conventional counterparts. In this study, we investigated the performance of some most popular deep learning architectures including eCNN, U-Net, GAN, V-Net, and Res-Net for the task of sCT generation. As a baseline, an atlas-based method is implemented to which the results of the deep learning-based model are compared.

METHODS

A dataset consisting of 20 co-registered MR-CT pairs of the male pelvis is applied to assess the different sCT production methods' performance. The mean error (ME), mean absolute error (MAE), Pearson correlation coefficient (PCC), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR) metrics were computed between the estimated sCT and the ground truth (reference) CT images.

RESULTS

The visual inspection revealed that the sCTs produced by eCNN, V-Net, and ResNet, unlike the other methods, were less noisy and greatly resemble the ground truth CT image. In the whole pelvis region, the eCNN yielded the lowest MAE (26.03 ± 8.85 HU) and ME (0.82 ± 7.06 HU), and the highest PCC metrics were yielded by the eCNN (0.93 ± 0.05) and ResNet (0.91 ± 0.02) methods. The ResNet model had the highest PSNR of 29.38 ± 1.75 among all models. In terms of the Dice similarity coefficient, the eCNN method revealed superior performance in major tissue identification (air, bone, and soft tissue).

CONCLUSIONS

All in all, the eCNN and ResNet deep learning methods revealed acceptable performance with clinically tolerable quantification errors.

Robustness and Generalizability of Deep Learning Synthetic Computed Tomography for Positron Emission Tomography/Magnetic Resonance Imaging-Based Radiation Therapy Planning of Patients With Head and Neck Cancer

Purpose

Radiotherapy planning based only on positron emission tomography/magnetic resonance imaging (PET/MRI) lacks computed tomography (CT) information required for dose calculations. In this study, a previously developed deep learning model for creating synthetic CT (sCT) from MRI in patients with head and neck cancer was evaluated in 2 scenarios: (1) using an independent external dataset, and (2) using a local dataset after an update of the model related to scanner software-induced changes to the input MRI.

Methods and Materials

Six patients from an external site and 17 patients from a local cohort were analyzed separately. Each patient underwent a CT and a PET/MRI with a Dixon MRI sequence over either one (external) or 2 (local) bed positions. For the external cohort, a previously developed deep learning model for deriving sCT from Dixon MRI was directly applied. For the local cohort, we adapted the model for an upgraded MRI acquisition using transfer learning and evaluated it in a leave-one-out process. The sCT mean absolute error for each patient was assessed. Radiotherapy dose plans based on sCT and CT were compared by assessing relevant absorbed dose differences in target volumes and organs at risk.

Results

The MAEs were 78 ± 13 HU and 76 ± 12 HU for the external and local cohort, respectively. For the external cohort, absorbed dose differences in target volumes were within ± 2.3% and within ± 1% in 95% of the cases. Differences in organs at risk were <2%. Similar results were obtained for the local cohort.

Conclusions

We have demonstrated a robust performance of a deep learning model for deriving sCT from MRI when applied to an independent external dataset. We updated the model to accommodate a larger axial field of view and software-induced changes to the input MRI. In both scenarios dose calculations based on sCT were similar to those of CT suggesting a robust and reliable method.

Value of PET imaging for radiation therapy

This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.

Value of PET imaging for radiation therapy

This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.

Oncology Information System: A Qualitative Study to Identify Cancer Patient Care Workflows

Oncology information systems provide solutions for managing the information of cancer patients and enable monitoring of different aspects of cancer patient care. Since the use of oncology information systems enhances the quality of care, improves documentation, optimizes resource allocation, and increases the cost-effectiveness of care services, attention to these systems' performance and their adaptation to workflows seems necessary. The purpose of this study was to identify cancer patient care workflows to design an oncology information system for Iran. This study employed a qualitative design and was conducted in 2019. Semi-structured interviews were conducted with 25 experts to determine their views on identifying workflows for cancer patients' care. The participants were clinical and non-clinical staff at six university hospitals equipped with oncology wards. The method of data analysis was framework analysis. The cancer patient care workflows consisted of two categories, including cancer diagnosis workflows and cancer treatment workflows. Cancer diagnosis workflows fall into three subcategories, i.e., the patient's referral to the clinic, an examination of the patient's condition, and pathology workflows. On the other hand, cancer treatment workflows are divided into various treatments offered to cancer patients and workflows in the chemotherapy and radiotherapy wards. Given the variety of services and the complexity of caring for cancer patients as well as the involvement of various specialists in the process of care, identifying and optimizing workflows in the oncology information system reduces errors, enhances data accuracy, eliminates unnecessary steps, and ultimately improve the service delivery to cancer patients.

Assessment of the Probability of Tumour Control for Prescribed Doses Based on Imaging of Oxygen Partial Pressure

In radiotherapy, hypoxia is a known negative factor, occurring especially in solid malignant tumours. Nitroimidazole-based positron emission tomography (PET) tracers, due to their selective binding to hypoxic cells, could be used as surrogates to image and quantify the underlying oxygen distributions in tissues. The spatial resolution of a clinical PET image, however, is much larger than the cellular spatial scale where hypoxia occurs. A question therefore arises regarding the possibility of quantifying different hypoxia levels based on PET images, and the aim of the present study is the prescription of corresponding therapeutic doses and its exploration.A tumour oxygenation model was created consisting of two concentric spheres with different oxygen partial pressure (pO₂) distributions. In order to mimic a PET image of the simulated tumour, given the relation between uptake and pO₂, fundamental effects that limit spatial resolution in a PET imaging system were considered: the uptake distribution was processed with a Gaussian 3D filter, and a re-binning to reach a typical PET image voxel size was performed. Prescription doses to overcome tumour hypoxia and predicted tumour control probability (TCP) were calculated based on the processed images for several fractionation schemes. Knowing the underlying oxygenation at microscopic scale, the actual TCP expected after the delivery of the calculated prescription doses was evaluated. Results are presented for three different dose painting strategies: by numbers, by contours and by using a voxel grouping-based approach.The differences between predicted TCP and evaluated TCP indicate that careful consideration must be taken on the dose prescription strategy and the selection of the number of fractions, depending on the severity of hypoxia.

Combining imaging- and gene-based hypoxia biomarkers in cervical cancer improves prediction of chemoradiotherapy failure independent of intratumour heterogeneity

Background

Emerging biomarkers from medical imaging or molecular characterization of tumour biopsies open up for combining the two and exploiting their synergy in treatment planning of cancer patients. We generated a paired data set of imaging- and gene-based hypoxia biomarkers in cervical cancer, appraised the influence of intratumour heterogeneity in patient classification, and investigated the benefit of combining the methodologies in prediction of chemoradiotherapy failure.

Methods

Hypoxic fraction from dynamic contrast enhanced (DCE)-MR images and an expression signature of six hypoxia-responsive genes were assessed as imaging- and gene-based biomarker, respectively in 118 patients.

Findings

Dichotomous biomarker cutoff to yield similar hypoxia status by imaging and genes was defined in 41 patients, and the association was validated in the remaining 77 patients. The two biomarkers classified 75% of 118 patients with the same hypoxia status, and inconsistent classification was not related to imaging-defined intratumour heterogeneity in hypoxia. Gene-based hypoxia was independent on tumour cell fraction in the biopsies and showed minor heterogeneity across multiple samples in 9 tumours. Combining imaging- and gene-based classification gave a significantly better prediction of PFS than one biomarker alone. A combined dichotomous biomarker optimized in 77 patients showed a large separation in PFS between more and less hypoxic tumours, and separated the remaining 41 patients with different PFS. The combined biomarker showed prognostic value together with tumour stage in multivariate analysis.

Interpretation

Combining imaging- and gene-based biomarkers may enable more precise and informative assessment of hypoxia-related chemoradiotherapy resistance in cervical cancer.

Funding

10.13039/100008730Norwegian Cancer Society, South-Eastern Norway Regional Health Authority, and Norwegian Research Council.

Simultaneous Metabolic and Perfusion Imaging Using Hyperpolarized 13C MRI Can Evaluate Early and Dose-Dependent Response to Radiation Therapy in a Prostate Cancer Mouse Model

PURPOSE

To investigate use of a novel imaging approach, hyperpolarized (HP) ¹³C magnetic resonance imaging (MRI) for simultaneous metabolism and perfusion assessment, to evaluate early and dose-dependent response to radiation therapy (RT) in a prostate cancer mouse model.

METHODS AND MATERIALS

Transgenic Adenocarcinoma of Mouse Prostate (TRAMP) mice (n = 18) underwent single-fraction RT (4-14 Gy steep dose across the tumor) and were imaged serially at pre-RT baseline and 1, 4, and 7 days after RT using HP ¹³C MRI with combined [1-¹³C]pyruvate (metabolic active agent) and [¹³C]urea (perfusion agent), coupled with conventional multiparametric ¹H MRI including T2-weighted, dynamic contrast-enhanced, and diffusion-weighted imaging. Tumor tissues were collected 4 and 7 days after RT for biological correlative studies.

RESULTS

We found a significant decrease in HP pyruvate-to-lactate conversion in tumors responding to RT, with concomitant significant increases in HP pyruvate-to-alanine conversion and HP urea signal; the opposite changes were observed in tumors resistant to RT. Moreover, HP lactate change was dependent on radiation dose; tumor regions treated with higher radiation doses (10-14 Gy) exhibited a greater decrease in HP lactate signal than low-dose regions (4-7 Gy) as early as 1 day post-RT, consistent with lactate dehydrogenase enzyme activity and expression data. We also found that HP [¹³C]urea MRI provided assessments of tumor perfusion similar to those provided by ¹H dynamic contrast-enhanced MRI in this animal model. However, apparent diffusion coefficien , a conventional ¹H MRI functional biomarker, did not exhibit statistically significant changes within 7 days after RT.

CONCLUSION

These results demonstrate the ability of HP ¹³C MRI to monitor radiation-induced physiologic changes in a timely and dose-dependent manner, providing the basic science premise for further clinical investigation and translation.

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).

Accuracy of deformable image registration techniques for alignment of longitudinal cholangiocarcinoma CT images

PURPOSE

Response assessment of radiotherapy for the treatment of intrahepatic cholangiocarcinoma (IHCC) across longitudinal images is challenging due to anatomical changes. Advanced deformable image registration (DIR) techniques are required to correlate corresponding tissues across time. In this study, the accuracy of five commercially available DIR algorithms in four treatment planning systems (TPS) was investigated for the registration of planning images with posttreatment follow-up images for response assessment or re-treatment purposes.

METHODS

Twenty-nine IHCC patients treated with hypofractionated radiotherapy and with pretreatment and posttreatment contrast-enhanced computed tomography (CT) images were analyzed. Liver segmentations were semiautomatically generated on all CTs and the posttreatment CT was then registered to the pretreatment CT using five commercially available algorithms (Demons, B-splines, salient feature-based, anatomically constrained and finite element-based) in four TPSs. This was followed by an in-depth analysis of 10 DIR strategies (plus global and liver-focused rigid registration) in one of the TPSs. Eight of the strategies were variants of the anatomically constrained DIR while the two were based on a finite element-based biomechanical registration. The anatomically constrained techniques were combinations of: (a) initializations with the two rigid registrations; (b) two similarity metrics - correlation coefficient (CC) and mutual information (MI); and (c) with and without a controlling region of interest (ROI) - the liver. The finite element-based techniques were initialized by the two rigid registrations. The accuracy of each registration was evaluated using target registration error (TRE) based on identified vessel bifurcations. The results were statistically analyzed with a one-way analysis of variance (ANOVA) and pairwise comparison tests. Stratified analysis was conducted on the inter-TPS data (plus the liver-focused rigid registration) using treatment volume changes, slice thickness, time between scans, and abnormal lab values as stratifying factors.

RESULTS

The complex deformation observed following treatment resulted in average TRE exceeding the image voxel size for all techniques. For the inter-TPS comparison, the Demons algorithm had the lowest TRE, which was significantly superior to all the other algorithms. The respective mean (standard deviation) TRE (in mm) for the Demons, B-splines, salient feature-based, anatomically constrained, and finite element-based algorithms were 4.6 (2.0), 7.4 (2.7), 7.2 (2.6), 6.3 (2.3), and 7.5 (4.0). In the follow-up comparison of the anatomically constrained DIR, the strategy with liver-focused rigid registration initialization, CC as similarity metric and liver as a controlling ROI had the lowest mean TRE - 6.0 (2.0). The maximum TRE for all techniques exceeded 10 mm. Selection of DIR strategy was found to be a statistically significant factor for registration accuracy. Tumor volume change had a significant effect on TRE for finite element-based registration and B-splines DIR. Time between scans had a substantial effect on TRE for all registrations but was only significant for liver-focused rigid, finite element-based and salient feature-based DIRs.

CONCLUSIONS

This study demonstrates the limitations of commercially available DIR techniques in TPSs for alignment of longitudinal images of liver cancer presenting complex anatomical changes including local hypertrophy and fibrosis/necrosis. DIR in this setting should be used with caution and careful evaluation.

Molecular Imaging for Particle Therapy: Current Approach and Future Directions

During the last decades, radiation oncology has been subject to a number of technological innovations. Particle therapy has evolved in parallel to the modern high-precision photon radiotherapy techniques and offers a superior dose distribution with decreased integral dose to healthy tissues. With advancing precision of treatment, the necessity for accurate and confident target volume delineation is rising. When morphological imaging reaches its limitations, molecular imaging can provide valuable information.

Imaging for Response Assessment in Radiation Oncology: Current and Emerging Techniques

Imaging in radiation oncology is essential for the evaluation of treatment response in tumors and organs at risk. This influences further treatment decisions and could possibly be used to adapt therapy. This review article focuses on the currently used imaging modalities for response assessment in radiation oncology and gives an overview of new and promising techniques within this field.

Attenuation correction of a flat table top for radiation therapy in hybrid PET/MR using CT- and 68Ge/68Ga transmission scan-based μ-maps

Hybrid PET/MR offers new opportunities in radiation oncology for tissue/tumour characterisation and response assessment. Attenuation correction (AC) is an important issue especially in the presence of immobilization devices and flat table tops (FTT). The goal of this study was to compare two methods of AC using CT- and ⁶⁸Ge/⁶⁸Ga transmission scan-based attenuation maps (μ-maps) for a custom-designed FTT. Measurements were performed in the mMR PET/MR and TrueV PET/CT Biograph Siemens scanners with three different phantoms, namely the Siemens MR-QA, a cubic canister and the NEMA IEC body phantom. The study revealed that the MR image quality is not hampered by the presence of the FTT. For cubic canister applying the scanner's inherent AC alone resulted in inaccuracies in PET images, with up to -4.0% underestimation of the activity. The mean NEMA sphere activity measurements without FTT, agreed within 3.5% with the respective inserted activity. Placing the FTT in the PET/MR scanner resulted in a difference to the injected activity of 4.5% when the table was not corrected for. By introducing the μ-maps the discrepancy between the used activity and the measurements decreased down to 2.6%. To improve the AC of the FTT the creation of a dedicated μ-map was necessary while the CT-based μ-map performed equally good as the source transmission scan-based one.

PET and MRI based RT treatment planning: Handling uncertainties

Imaging provides the basis for radiotherapy. Multi-modality images are used for target delineation (primary tumor and nodes, boost volume) and organs at risk, treatment guidance, outcome prediction, and treatment assessment. Next to anatomical information, more and more functional imaging is being used. The current paper provides a brief overview of the different applications of imaging techniques used in the radiotherapy process, focusing on uncertainties and QA. The paper mainly focuses on PET and MRI, but also provides a short discussion on DCE-CT. A close collaboration between radiology, nuclear medicine and radiotherapy departments provides the key to improve the quality of radiotherapy. Jointly developed imaging protocols (RT position setup, immobilization tools, lasers, flat table…), and QA programs are mandatory. For PET, suitable windowing in consultation with a Nuclear Medicine Physician is crucial (differentiation benign/malignant lesions, artifacts…). A basic knowledge of MRI sequences is required, in such a way that geometrical distortions are easily recognized by all members the RT and RT physics team. If this is not the case, then the radiologist should be introduced systematically in the delineation process and multidisciplinary meetings need to be organized regularly. For each image modality and each image registration process, the associated uncertainties need to be determined and integrated in the PTV margin. When using functional information for dose painting, response assessment or outcome prediction, collaboration between the different departments is even more important. Limitations of imaging based biomarkers (specificity, sensitivity) should be known.

The Continuing Evolution of Molecular Functional Imaging in Clinical Oncology: The Road to Precision Medicine and Radiogenomics (Part I)

The present era of precision medicine sees 'cancer' as a consequence of molecular derangements occurring at the commencement of the disease process, with morphologic changes happening much later in the process of tumorigenesis. Conventional imaging techniques, such as computed tomography (CT), ultrasound, and magnetic resonance imaging (MRI), play an integral role in the detection of disease at a macroscopic level. However, molecular functional imaging (MFI) techniques entail the visualisation and quantification of biochemical and physiological processes occurring during tumorigenesis, and thus has the potential to play a key role in heralding the transition from the concept of 'one size fits all' to 'precision medicine'. Integration of MFI with other fields of tumour biology such as genomics has spawned a novel concept called 'radiogenomics', which could serve as an indispensable tool in translational cancer research. With recent advances in medical image processing, such as texture analysis, deep learning, and artificial intelligence (AI), the future seems promising; however, their clinical utility remains unproven at present. Despite the emergence of novel imaging biomarkers, a majority of these require validation before clinical translation is possible. In this two-part review, we discuss the systematic collaboration across structural, anatomical, and molecular imaging techniques that constitute MFI. Part I reviews positron emission tomography, radiogenomics, AI, and optical imaging, while part II reviews MRI, CT and ultrasound, their current status, and recent advances in the field of precision oncology.

Technical feasibility of [18F]FET and [18F]FAZA PET guided radiotherapy in a F98 glioblastoma rat model

Background

Glioblastoma (GB) is the most common primary malignant brain tumor. Standard medical treatment consists of a maximal safe surgical resection, subsequently radiation therapy (RT) and chemotherapy with temozolomide (TMZ). An accurate definition of the tumor volume is of utmost importance for guiding RT. In this project we investigated the feasibility and treatment response of subvolume boosting to a PET-defined tumor part.

Method

F98 GB cells inoculated in the rat brain were imaged using T2- and contrast-enhanced T1-weighted (T1w) MRI. A dose of 20 Gy (5 × 5 mm²) was delivered to the target volume delineated based on T1w MRI for three treatment groups. Two of those treatment groups received an additional radiation boost of 5 Gy (1 × 1 mm²) delivered to the region either with maximum [¹⁸F]FET or [¹⁸F]FAZA PET tracer uptake, respectively. All therapy groups received intraperitoneal (IP) injections of TMZ. Finally, a control group received no RT and only control IP injections. The average, minimum and maximum dose, as well as the D₉₀-, D₅₀- and D₂- values were calculated for nine rats using both RT plans. To evaluate response to therapy, follow-up tumor volumes were delineated based on T1w MRI.

Results

When comparing the dose volume histograms, a significant difference was found exclusively between the D₂-values. A significant difference in tumor growth was only found between active therapy and sham therapy respectively, while no significant differences were found when comparing the three treatment groups.

Conclusion

In this study we showed the feasibility of PET guided subvolume boosting of F98 glioblastoma in rats. No evidence was found for a beneficial effect regarding tumor response. However, improvements for dose targeting in rodents and studies investigating new targeted drugs for GB treatment are mandatory.

Electronic supplementary material

The online version of this article (10.1186/s13014-019-1290-4) contains supplementary material, which is available to authorized users.

Emerging Functional Imaging Biomarkers of Tumour Responses to Radiotherapy

Tumour responses to radiotherapy are currently primarily assessed by changes in size. Imaging permits non-invasive, whole-body assessment of tumour burden and guides treatment options for most tumours. However, in most tumours, changes in size are slow to manifest and can sometimes be difficult to interpret or misleading, potentially leading to prolonged durations of ineffective treatment and delays in changing therapy. Functional imaging techniques that monitor biological processes have the potential to detect tumour responses to treatment earlier and refine treatment options based on tumour biology rather than solely on size and staging. By considering the biological effects of radiotherapy, this review focusses on emerging functional imaging techniques with the potential to augment morphological imaging and serve as biomarkers of early response to radiotherapy.

Dosimetric Impact of MRI Distortions: A Study on Head and Neck Cancers

PURPOSE

To evaluate the effect of magnetic resonance (MR) imaging (MRI) geometric distortions on head and neck radiation therapy treatment planning (RTP) for an MRI-only RTP. We also assessed the potential benefits of patient-specific shimming to reduce the magnitude of MR distortions for a 3-T scanner.

METHODS AND MATERIALS

Using an in-house Matlab algorithm, shimming within entire imaging volumes and user-defined regions of interest were simulated. We deformed 21 patient computed tomography (CT) images with MR distortion fields (gradient nonlinearity and patient-induced susceptibility effects) to create distorted CT (dCT) images using bandwidths of 122 and 488 Hz/mm at 3 T. Field parameters from volumetric modulated arc therapy plans initially optimized on dCT data sets were transferred to CT data to compute a new plan. Both plans were compared to determine the impact of distortions on dose distributions.

RESULTS

Shimming across entire patient volumes decreased the percentage of voxels with distortions of more than 2 mm from 15.4% to 2.0%. Using the user-defined region of interest (ROI) shimming strategy, (here the Planning target volume (PTV) was the chosen ROI volume) led to increased geometric for volumes outside the PTV, as such voxels within the spinal cord with geometric shifts above 2 mm increased from 11.5% to 32.3%. The worst phantom-measured residual system distortions after 3-dimensional gradient nonlinearity correction within a radial distance of 200 mm from the isocenter was 2.17 mm. For all patients, voxels with distortion shifts of more than 2 mm resulting from patient-induced susceptibility effects were 15.4% and 0.0% using bandwidths of 122 Hz/mm and 488 Hz/mm at 3 T. Dose differences between dCT and CT treatment plans in D₅₀ at the planning target volume were 0.4% ± 0.6% and 0.3% ± 0.5% at 122 and 488 Hz/mm, respectively.

CONCLUSIONS

The overall effect of MRI geometric distortions on data used for RTP was minimal. Shimming over entire imaging volumes decreased distortions, but user-defined subvolume shimming introduced significant errors in nearby organs and should probably be avoided.

What is the prognostic impact of FDG PET in locally advanced head and neck squamous cell carcinoma treated with concomitant chemo-radiotherapy? A systematic review and meta-analysis

PURPOSE

Evidence is conflicting on the prognostic value of 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in head and neck squamous cell carcinoma. The aim of our study was to determine the impact of semiquantitative and qualitative metabolic parameters on the outcome in patients managed with standard treatment for locally advanced disease.

METHODS

A systematic review of the literature was conducted. A meta-analysis was performed of studies providing estimates of relative risk (RR) for the association between semiquantitative metabolic parameters and efficacy outcome measures.

RESULTS

The analysis included 25 studies, for a total of 2,223 subjects. The most frequent primary tumour site was the oropharynx (1,150/2,223 patients, 51.7%). According to the available data, the majority of patients had stage III/IV disease (1,709/1,799, 94.9%; no information available in four studies) and were treated with standard concurrent chemoradiotherapy (1,562/2,009 patients, 77.7%; only one study without available information). A total of 11, 8 and 4 independent studies provided RR estimates for the association between baseline FDG PET metrics and overall survival (OS), progression-free survival (PFS) and locoregional control (LRC), respectively. High pretreatment metabolic tumour volume (MTV) was significantly associated with a worse OS (summary RR 1.86, 95% CI 1.08-3.21), PFS (summary RR 1.81, 95% CI 1.14-2.89) and LRC (summary RR 3.49, 95% CI 1.65-7.35). Given the large heterogeneity (I2 > 50%) affecting the summary measures, no cumulative threshold for an unfavourable prognosis could be defined. No statistically significant association was found between SUVmax and any of the outcome measures.

CONCLUSION

FDG PET has prognostic relevance in the context of locally advanced head and neck squamous cell carcinoma. Pretreatment MTV is the only metabolic variable with a significant impact on patient outcome. Because of the heterogeneity and the lack of standardized methodology, no definitive conclusions on optimal cut-off values can be drawn.

Comparison of treatment plans for a high-field MRI-linac and a conventional linac for esophageal cancer

PURPOSE

To compare radiotherapy treatments plans in esophageal cancer calculated for a high-field magnetic resonance imaging (MRI)-linac with plans for a conventional linac.

MATERIALS AND METHODS

Ten patients with esophageal squamous cell carcinomas were re-planned retrospectively using the research version of Monaco (V 5.19.03, Elekta AB, Stockholm, Sweden). Intensity modulated radiotherapy (IMRT) plans with a nine-field step-and-shoot technique and two-arc volumetric modulated arc therapy (VMAT) plans were created for the Elekta MRI-linac and a conventional linac, respectively. The prescribed dose was 60 Gy to the primary tumor (PTV₆₀) and 50 Gy to elective volumes (PTV₅₀). Plans were optimized for optimal coverage of the 60 Gy volume and compared using dose-volume histogram parameters.

RESULTS

All calculated treatment plans met predefined criteria for target volume coverage and organs at risk dose both for MRI-linac and conventional linac. Plans for the MRI-linac had a lower number of segments and monitor units. No significant differences between both plans were seen in terms of V_20Gy of the lungs and V_40Gy of the heart with slightly higher mean doses to the heart (14.0 Gy vs. 12.5 Gy) and lungs (12.8 Gy vs. 12.2 Gy).

CONCLUSION

Applying conventional target volume and margin concepts as well as dose-fractionation prescription reveals clinically acceptable dose distributions using hybrid MRI-linac in its current configuration compared to standard IMRT/VMAT. This represents an important prerequisite for future studies to investigate the clinical benefit of MRI-guided radiotherapy exploiting the conceptional advantages such as reduced margins, plan adaptation and biological individualization and hypofractionation.

Assessment of image quality of a radiotherapy-specific hardware solution for PET/MRI in head and neck cancer patients

BACKGROUND AND PURPOSE

Functional PET/MRI has great potential to improve radiotherapy planning (RTP). However, data integration requires imaging with radiotherapy-specific patient positioning. Here, we investigated the feasibility and image quality of radiotherapy-customized PET/MRI in head-and-neck cancer (HNC) patients using a dedicated hardware setup.

MATERIAL AND METHODS

Ten HNC patients were examined with simultaneous PET/MRI before treatment, with radiotherapy and diagnostic scan setup, respectively. We tested feasibility of radiotherapy-specific patient positioning and compared the image quality between both setups by pairwise image analysis of 18F-FDG-PET, T1/T2-weighted and diffusion-weighted MRI. For image quality assessment, similarity measures including average symmetric surface distance (ASSD) of PET and MR-based tumor contours, MR signal-to-noise ratio (SNR) and mean apparent diffusion coefficient (ADC) value were used.

RESULTS

PET/MRI in radiotherapy position was feasible - all patients were successfully examined. ASSD (median/range) of PET and MR contours was 0.6 (0.4-1.2) and 0.9 (0.5-1.3) mm, respectively. For T2-weighted MRI, a reduced SNR of -26.2% (-39.0--11.7) was observed with radiotherapy setup. No significant difference in mean ADC was found.

CONCLUSIONS

Simultaneous PET/MRI in HNC patients using radiotherapy positioning aids is clinically feasible. Though SNR was reduced, the image quality obtained with a radiotherapy setup meets RTP requirements and the data can thus be used for personalized RTP.

Technical Note: Adapting a GE SIGNA PET/MR scanner for radiotherapy

PURPOSE

Simultaneous collection of PET and MR data for radiotherapy purposes are useful for, for example, target definition and dose escalations. However, a prerequisite for using PET/MR in the radiotherapy workflow is the ability to image the patient in treatment position. The aim of this work was to adapt a GE SIGNA PET/MR scanner to image patients for radiotherapy treatment planning and evaluate the impact on signal-to-noise (SNR) of the MR images, and the accuracy of the PET attenuation correction.

METHOD

A flat tabletop and a coil holder were developed to image patients in the treatment position, avoid patient contour deformation, and facilitate attenuation correction of flex coils. Attenuation corrections for the developed hardware and an anterior array flex coil were also measured and implemented to the PET/MR system to minimize PET quantitation errors. The reduction of SNR in the MR images due to the added distance between the coils and the patient was evaluated using a large homogenous saline-doped water phantom, and the activity quantitation errors in PET imaging were evaluated with and without the developed attenuation corrections.

RESULT

We showed that the activity quantitation errors in PET imaging were within ±5% when correcting for attenuation of the flat tabletop, coil holder, and flex coil. The SNR of the MRI images were reduced to 74% using the tabletop, and 66% using the tabletop and coil holders.

CONCLUSION

We present a tabletop and coil holder for an anterior array coil to be used with a GE SIGNA PET/MR scanner, for scanning patients in the radiotherapy work flow. Implementing attenuation correction of the added hardware from the radiotherapy setup leads to acceptable PET image quantitation. The drop in SNR in MR images may require adjustment of the imaging protocols.

Evaluating the repeatability and set-up sensitivity of a large field of view distortion phantom and software for magnetic resonance-only radiotherapy

BACKGROUND AND PURPOSE

Magnetic Resonance (MR)-only radiotherapy requires geometrically accurate MR images over the full scanner Field of View (FoV). This study aimed to investigate the repeatability of distortion measurements made using a commercial large FoV phantom and analysis software and the sensitivity of these measurements to small set-up errors.

MATERIALS AND METHODS

Geometric distortion was measured using a commercial phantom and software with 2D and 3D acquisition sequences on three different MR scanners. Two sets of repeatability measurements were made: three scans acquired without moving the phantom between scans (single set-up) and five scans acquired with the phantom re-set up in between each scan (repeated set-up). The set-up sensitivity was assessed by scanning the phantom with an intentional 1 mm lateral offset and independently an intentional 1° rotation.

RESULTS

The mean standard deviation of distortion for all phantom markers for the repeated set-up scans was < 0.4 mm for all scanners and sequences. For the 1 mm lateral offset scan 90 % of the markers agreed within two standard deviations of the mean of the repeated set-up scan (median of all scanners and sequences, range 78%-93%). For the 1° rotation scan, 80% of markers agreed within two standard deviations of the mean (range 69%-93%).

CONCLUSIONS

Geometric distortion measurements using a commercial phantom and associated software appear repeatable, although with some sensitivity to set-up errors. This suggests the phantom and software are appropriate for commissioning a MR-only radiotherapy workflow.

Molecular Imaging Using PET/CT for Radiation Therapy Planning for Adult Cancers: Current Status and Expanding Applications

Accurate tumor delineation is a priority in radiation therapy (RT). Metabolic imaging has a key and evolving role in target volume selection and delineation. This is especially so for non-small cell lung cancer, squamous cell cancer of the head and neck, and lymphoma, for which positron emission tomography/computed tomography (PET/CT) is complimentary to structural imaging modalities, not only in delineating primary tumors, but also often in revealing previously undiagnosed regional nodal disease. At some sites, PET/CT has been confirmed to enable target size reduction compared with structural imaging alone, with enhanced normal tissue sparing and potentially allowing for dose escalation. These contributions often dramatically affect RT strategies. However, some limitations exist to the use of fluorodeoxyglucose-PET in RT planning, including its relatively poor spatial resolution and partial voluming effects for small tumors. A role is developing for contributions from metabolic imaging to RT planning at other tumor sites and exciting new applications for the use of non-fluorodeoxyglucose metabolic markers for RT planning.

18-Fluorodeoxy-Glucose Positron Emission Tomography- Computed Tomography (18-FDG-PET/CT) for Gross Tumor Volume (GTV) Delineation in Gastric Cancer Radiotherapy

Purpose:

Evaluation of the 18-fluorodeoxy-glucose positron emission tomography-computed tomography (18-FDG-PET/_CT) for gross tumor volume (GTV) delineation in gastric cancer patients undergoing radiotherapy.

Methods:

In this study, 29 gastric cancer patients (17 unresectable and 7 inoperable) were initially enrolled for radical chemoradiotherapy (45Gy/25 fractions + chemotherapy based on 5 fluorouracil) or radiotherapy alone (45Gy/25 fractions) with planning based on the 18-FDG-PET/CT images. Five patients were excluded due to excess blood glucose levels (1), false-negative positron emission tomography (1) and distant metastases revealed by 18-FDG-PET/CT (3). The analysis involved measurement of metabolic tumor volumes (MTVs) performed on PET/CT workstations. Different threshold levels of the standardized uptake value (SUV) and liver uptake were set to obtain MTVs. Secondly, GTV_PET values were derived manually using the positron emission tomography (PET) dataset blinded to the computed tomography (CT) data. Subsequently, GTV_CT values were delineated using a radiotherapy planning system based on the CT scans blinded to the PET data. The referenced GTV_CT values were correlated with the GTV_PET and were compared with a conformality index (CI).

Results:

The mean CI was 0.52 (range, 0.12-0.85). In 13/24 patients (54%), the GTV_PET was larger than GTV_CT, and in the remainder, GTV_PET was smaller. Moreover, the cranio-caudal diameter of GTV_PET in 16 cases (64%) was larger than that of GTV_CT, smaller in 7 cases (29%), and unchanged in one case. Manual PET delineation (GTVPET) achieved the best correlation with GTV_CT (Pearson correlation = 0.76, p <0.0001). Among the analyzed MTVs, a statistically significant correlation with GTV_CT was revealed for MTV_10%SUVmax (r = 0.63; p = 0.0014), MTV_liv (r = 0.60; p = 0.0021), MTV_SUV2.5 (r = 0.54; p = 0.0063); MTV_20%SUVmax (r = 0.44; p = 0.0344); MTV_30%SUVmax (r = 0.44; p = 0.0373).

Conclusion:

18-FDG-PET/_CT in gastric cancer radiotherapy planning may affect the GTV delineation.

The need for multidisciplinarity in specialist training to optimize future patient care

Harmonious interactions between radiation, medical, interventional and surgical oncologists, as well as other members of multidisciplinary teams, are essential for the optimization of patient care in oncology. This multidisciplinary approach is particularly important in the current landscape, in which standard-of-care approaches to cancer treatment are evolving towards highly targeted treatments, precise image guidance and personalized cancer therapy. Herein, we highlight the importance of multidisciplinarity and interdisciplinarity at all levels of clinical oncology training. Potential deficits in the current career development pathways and suggested strategies to broaden clinical training and research are presented, with specific emphasis on the merits of trainee involvement in functional multidisciplinary teams. Finally, the importance of training in multidisciplinary research is discussed, with the expectation that this awareness will yield the most fertile ground for future discoveries. Our key message is for cancer professionals to fulfil their duty in ensuring that trainees appreciate the importance of multidisciplinary research and practice.

Amino-acid PET versus MRI guided re-irradiation in patients with recurrent glioblastoma multiforme (GLIAA) - protocol of a randomized phase II trial (NOA 10/ARO 2013-1)

Background

The higher specificity of amino-acid positron emission tomography (AA-PET) in the diagnosis of gliomas, as well as in the differentiation between recurrence and treatment-related alterations, in comparison to contrast enhancement in T1-weighted MRI was demonstrated in many studies and is the rationale for their implementation into radiation oncology treatment planning. Several clinical trials have demonstrated the significant differences between AA-PET and standard MRI concerning the definition of the gross tumor volume (GTV). A small single-center non-randomized prospective study in patients with recurrent high grade gliomas treated with stereotactic fractionated radiotherapy (SFRT) showed a significant improvement in survival when AA-PET was integrated in target volume delineation, in comparison to patients treated based on CT/MRI alone.

Methods

This protocol describes a prospective, open label, randomized, multi-center phase II trial designed to test if radiotherapy target volume delineation based on FET-PET leads to improvement in progression free survival (PFS) in patients with recurrent glioblastoma (GBM) treated with re-irradiation, compared to target volume delineation based on T1Gd-MRI. The target sample size is 200 randomized patients with a 1:1 allocation ratio to both arms. The primary endpoint (PFS) is determined by serial MRI scans, supplemented by AA-PET-scans and/or biopsy/surgery if suspicious of progression. Secondary endpoints include overall survival (OS), locally controlled survival (time to local progression or death), volumetric assessment of GTV delineated by either method, topography of progression in relation to MRI- or PET-derived target volumes, rate of long term survivors (>1 year), localization of necrosis after re-irradiation, quality of life (QoL) assessed by the EORTC QLQ-C15 PAL questionnaire, evaluation of safety of FET-application in AA-PET imaging and toxicity of re-irradiation.

Discussion

This is a protocol of a randomized phase II trial designed to test a new strategy of radiotherapy target volume delineation for improving the outcome of patients with recurrent GBM. Moreover, the trial will help to develop a standardized methodology for the integration of AA-PET and other imaging biomarkers in radiation treatment planning.

Trial registration

The GLIAA trial is registered with ClinicalTrials.gov (NCT01252459, registration date 02.12.2010), German Clinical Trials Registry (DRKS00000634, registration date 10.10.2014), and European Clinical Trials Database (EudraCT-No. 2012-001121-27, registration date 27.02.2012).

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.

Brain Tumors: An Update on Clinical PET Research in Gliomas

A previous review published in 2012 demonstrated the role of clinical PET for diagnosis and management of brain tumors using mainly FDG, amino acid tracers, and ¹⁸F-fluorothymidine. This review provides an update on clinical PET studies, most of which are motivated by prediction of prognosis and planning and monitoring of therapy in gliomas. For FDG, there has been additional evidence supporting late scanning, and combination with ¹³N ammonia has yielded some promising results. Large neutral amino acid tracers have found widespread applications mostly based on ¹⁸F-labeled compounds fluoroethyltyrosine and fluorodopa for targeting biopsies, therapy planning and monitoring, and as outcome markers in clinical trials. ¹¹C-alpha-methyltryptophan (AMT) has been proposed as an alternative to ¹¹C-methionine, and there may also be a role for cyclic amino acid tracers. ¹⁸F-fluorothymidine has shown strengths for tumor grading and as an outcome marker. Studies using ¹⁸F-fluorocholine (FCH) and ⁶⁸Ga-labeled compounds are promising but have not yet clearly defined their role. Studies on radiotherapy planning have explored the use of large neutral amino acid tracers to improve the delineation of tumor volume for irradiation and the use of hypoxia markers, in particular ¹⁸F-fluoromisonidazole. Many studies employed the combination of PET with advanced multimodal MR imaging methods, mostly demonstrating complementarity and some potential benefits of hybrid PET/MR.