Towards a European prospective data registry for particle therapy

The evidence for the value of particle therapy (PT) is still sparse. While randomized trials remain a cornerstone for robust comparisons with photon-based radiotherapy, data registries collecting real-world data can play a crucial role in building evidence for new developments. This Perspective describes how the European Particle Therapy Network (EPTN) is actively working on establishing a prospective data registry encompassing all patients undergoing PT in European centers. Several obstacles and hurdles are discussed, for instance harmonization of nomenclature and structure of technical and dosimetric data and data protection issues. A preferred approach is the adoption of a federated data registry model with transparent and agile governance to meet European requirements for data protection, transfer, and processing. Funding of the registry, especially for operation after the initial setup process, remains a major challenge.

Correlation of microscopic tumor extension with tumor microenvironment in esophageal cancer patients

OBJECTIVE

In the era of image-guided adaptive radiotherapy, definition of the clinical target volume (CTV) is a challenge in various solid tumors, including esophageal cancer (EC). Many tumor microenvironmental factors, e.g., tumor cell proliferation or cancer stem cells, are hypothesized to be involved in microscopic tumor extension (MTE). Therefore, this study assessed the expression of FAK, ILK, CD44, HIF-1α, and Ki67 in EC patients after neoadjuvant radiochemotherapy followed by tumor resection (NRCHT+R) and correlated these markers with the MTE.

METHODS

Formalin-fixed paraffin-embedded tumor resection specimens of ten EC patients were analyzed using multiplex immunofluorescence staining. Since gold fiducial markers had been endoscopically implanted at the proximal and distal tumor borders prior to NRCHT+R, correlation of the markers with the MTE was feasible.

RESULTS

In tumor resection specimens of EC patients, the overall percentages of FAK+, CD44+, HIF-1α+, and Ki67+ cells were higher in tumor nests than in the tumor stroma, with the outcome for Ki67+ cells reaching statistical significance (p < 0.001). Conversely, expression of ILK+ cells was higher in tumor stroma, albeit not statistically significantly. In three patients, MTE beyond the fiducial markers was found, reaching up to 31 mm.

CONCLUSION

Our findings indicate that the overall expression of FAK, HIF-1α, Ki67, and CD44 was higher in tumor nests, whereas that of ILK was higher in tumor stroma. Differences in the TME between patients with residual tumor cells in the original CTV compared to those without were not found. Thus, there is insufficient evidence that the TME influences the required CTV margin on an individual patient basis.

TRIAL REGISTRATION NUMBER AND DATE

BO-EK-148042017 and BO-EK-177042022 on 20.06.2022, DRKS00011886, https://drks.de/search/de/trial/DRKS00011886 .

High-precision stereotactic irradiation for focal drug-resistant epilepsy versus standard treatment: a randomized waitlist-controlled trial (the PRECISION trial)

INTRODUCTION

The standard treatment for patients with focal drug-resistant epilepsy (DRE) who are not eligible for open brain surgery is the continuation of anti-seizure medication (ASM) and neuromodulation. This treatment does not cure epilepsy but only decreases severity. The PRECISION trial offers a non-invasive, possibly curative intervention for these patients, which consist of a single stereotactic radiotherapy (SRT) treatment. Previous studies have shown promising results of SRT in this patient population. Nevertheless, this intervention is not yet available and reimbursed in the Netherlands. We hypothesize that: SRT is a superior treatment option compared to palliative standard of care, for patients with focal DRE, not eligible for open surgery, resulting in a higher reduction of seizure frequency (with 50% of the patients reaching a 75% seizure frequency reduction at 2 years follow-up).

METHODS

In this waitlist-controlled phase 3 clinical trial, participants are randomly assigned in a 1:1 ratio to either receive SRT as the intervention, while the standard treatments consist of ASM continuation and neuromodulation. After 2-year follow-up, patients randomized for the standard treatment (waitlist-control group) are offered SRT. Patients aged ≥ 18 years with focal DRE and a pretreatment defined epileptogenic zone (EZ) not eligible for open surgery will be included. The intervention is a LINAC-based single fraction (24 Gy) SRT treatment. The target volume is defined as the epileptogenic zone (EZ) on all (non) invasive examinations. The seizure frequency will be monitored on a daily basis using an electronic diary and an automatic seizure detection system during the night. Potential side effects are evaluated using advanced MRI, cognitive evaluation, Common Toxicity Criteria, and patient-reported outcome questionnaires. In addition, the cost-effectiveness of the SRT treatment will be evaluated.

DISCUSSION

This is the first randomized trial comparing SRT with standard of care in patients with DRE, non-eligible for open surgery. The primary objective is to determine whether SRT significantly reduces the seizure frequency 2 years after treatment. The results of this trial can influence the current clinical practice and medical cost reimbursement in the Netherlands for patients with focal DRE who are not eligible for open surgery, providing a non-invasive curative treatment option.

TRIAL REGISTRATION

Clinicaltrials.gov Identifier: NCT05182437. Registered on September 27, 2021.

A Phase 1 Study of the DNA-PK Inhibitor Peposertib in Combination With Radiation Therapy With or Without Cisplatin in Patients With Advanced Head and Neck Tumors

PURPOSE

DNA-dependent protein kinase (DNA-PK) plays a key role in the repair of DNA double strand breaks via nonhomologous end joining. Inhibition of DNA-PK can enhance the effect of DNA double strand break inducing anticancer therapies. Peposertib (formerly "M3814") is an orally administered, potent, and selective small molecule DNA-PK inhibitor that has demonstrated radiosensitizing and antitumor activity in xenograft models and was well-tolerated in monotherapy. This phase 1 trial (National Clinical Trial 02516813) investigated the maximum tolerated dose, recommended phase 2 dose (RP2D), safety, and tolerability of peposertib in combination with palliative radiation therapy (RT) in patients with thoracic or head and neck tumors (arm A) and of peposertib in combination with cisplatin and curative-intent RT in patients with squamous cell carcinoma of the head and neck (arm B).

METHODS AND MATERIALS

Patients received peposertib once daily in ascending dose cohorts as a tablet or capsule in combination with palliative RT (arm A) or in combination with intensity modulated curative-intent RT and cisplatin (arm B).

RESULTS

The most frequently observed treatment-emergent adverse events were radiation skin injury, fatigue, and nausea in arm A (n = 34) and stomatitis, nausea, radiation skin injury, and dysgeusia in arm B (n = 11). Based on evaluations of dose-limiting toxicities, tolerability, and pharmacokinetic data, RP2D for arm A was declared as 200 mg peposertib tablet once daily in combination with RT. In arm B (n = 11), 50 mg peposertib was declared tolerable in combination with curative-intent RT and cisplatin. However, enrollment was discontinued because of insufficient exposure at that dose, and the RP2D was not formally declared.

CONCLUSIONS

Peposertib in combination with palliative RT was well-tolerated up to doses of 200 mg once daily as tablet with each RT fraction. When combined with RT and cisplatin, a tolerable peposertib dose yielded insufficient exposure.

Radiomics for residual tumour detection and prognosis in newly diagnosed glioblastoma based on postoperative [11C] methionine PET and T1c-w MRI

Personalized treatment strategies based on non-invasive biomarkers have potential to improve patient management in patients with newly diagnosed glioblastoma (GBM). The residual tumour burden after surgery in GBM patients is a prognostic imaging biomarker. However, in clinical patient management, its assessment is a manual and time-consuming process that is at risk of inter-rater variability. Furthermore, the prediction of patient outcome prior to radiotherapy may identify patient subgroups that could benefit from escalated radiotherapy doses. Therefore, in this study, we investigate the capabilities of traditional radiomics and 3D convolutional neural networks for automatic detection of the residual tumour status and to prognosticate time-to-recurrence (TTR) and overall survival (OS) in GBM using postoperative [11C] methionine positron emission tomography (MET-PET) and gadolinium-enhanced T1-w magnetic resonance imaging (MRI). On the independent test data, the 3D-DenseNet model based on MET-PET achieved the best performance for residual tumour detection, while the logistic regression model with conventional radiomics features performed best for T1c-w MRI (AUC: MET-PET 0.95, T1c-w MRI 0.78). For the prognosis of TTR and OS, the 3D-DenseNet model based on MET-PET integrated with age and MGMT status achieved the best performance (Concordance-Index: TTR 0.68, OS 0.65). In conclusion, we showed that both deep-learning and conventional radiomics have potential value for supporting image-based assessment and prognosis in GBM. After prospective validation, these models may be considered for treatment personalization.

Prediction of radiation pneumonitis using the effective α/β of lungs and heart in NSCLC patients treated with proton beam therapy

PURPOSE

Radiation pneumonitis (RP) remains a major complication in non-small cell lung cancer (NSCLC) patients undergoing radiochemotherapy (RCHT). Traditionally, the mean lung dose (MLD) and the volume of the total lung receiving at least 20 Gy (V20Gy) are used to predict RP in patients treated with normo-fractionated photon therapy. However, other models, including the actual dose-distribution in the lungs using the effective α/β model or a combination of radiation doses to the lungs and heart, have been proposed for predicting RP. Moreover, the models established for photons may not hold for patients treated with passively-scattered proton therapy (PSPT). Therefore, we here tested and validated novel predictive parameters for RP in NSCLC patient treated with PSPT.

METHODS

Data on the occurrence of RP, structure files and dose-volume histogram parameters for lungs and heart of 96 NSCLC patients, treated with PSPT and concurrent chemotherapy, was retrospectively retrieved from prospective clinical studies of two international centers. Data was randomly split into a training set (64 patients) and a validation set (32 patients). Statistical analyses were performed using binomial logistic regression.

RESULTS

The biologically effective dose (BED) of the'lungs - GTV' significantly predicted RP ≥ grade 2 in the training-set using both a univariate model (p = 0.019, AUCtrain = 0.72) and a multivariate model in combination with the effective α/β parameter of the heart (pBED = 0.006, [Formula: see text] = 0.043, AUCtrain = 0.74). However, these results did not hold in the validation-set (AUCval = 0.52 andAUCval = 0.50, respectively). Moreover, these models were found to neither outperform a model built with the MLD (p = 0.015, AUCtrain = 0.73, AUCval = 0.51), nor a multivariate model additionally including the V20Gy of the heart (pMLD = 0.039, pV20Gy,heart = 0.58, AUCtrain = 0.74, AUCval = 0.53).

CONCLUSION

Using the effective α/β parameter of the lungs and heart we achieved similar performance to commonly used models built for photon therapy, such as MLD, in predicting RP ≥ grade 2. Therefore, prediction models developed for photon RCHT still hold for patients treated with PSPT.

Multitask Learning with Convolutional Neural Networks and Vision Transformers Can Improve Outcome Prediction for Head and Neck Cancer Patients

Neural-network-based outcome predictions may enable further treatment personalization of patients with head and neck cancer. The development of neural networks can prove challenging when a limited number of cases is available. Therefore, we investigated whether multitask learning strategies, implemented through the simultaneous optimization of two distinct outcome objectives (multi-outcome) and combined with a tumor segmentation task, can lead to improved performance of convolutional neural networks (CNNs) and vision transformers (ViTs). Model training was conducted on two distinct multicenter datasets for the endpoints loco-regional control (LRC) and progression-free survival (PFS), respectively. The first dataset consisted of pre-treatment computed tomography (CT) imaging for 290 patients and the second dataset contained combined positron emission tomography (PET)/CT data of 224 patients. Discriminative performance was assessed by the concordance index (C-index). Risk stratification was evaluated using log-rank tests. Across both datasets, CNN and ViT model ensembles achieved similar results. Multitask approaches showed favorable performance in most investigations. Multi-outcome CNN models trained with segmentation loss were identified as the optimal strategy across cohorts. On the PET/CT dataset, an ensemble of multi-outcome CNNs trained with segmentation loss achieved the best discrimination (C-index: 0.29, 95% confidence interval (CI): 0.22-0.36) and successfully stratified patients into groups with low and high risk of disease progression (p=0.003). On the CT dataset, ensembles of multi-outcome CNNs and of single-outcome ViTs trained with segmentation loss performed best (C-index: 0.26 and 0.26, CI: 0.18-0.34 and 0.18-0.35, respectively), both with significant risk stratification for LRC in independent validation (p=0.002 and p=0.011). Further validation of the developed multitask-learning models is planned based on a prospective validation study, which has recently completed recruitment.

Normo- or Hypo-Fractionated Photon or Proton Radiotherapy in the Management of Locally Advanced Unresectable Pancreatic Cancer: A Systematic Review

LAPC is associated with a poor prognosis and requires a multimodal treatment approach. However, the role of radiation therapy in LAPC treatment remains controversial. This systematic review aimed to explore the role of proton and photon therapy, with varying radiation techniques and fractionation, in treatment outcomes and their respective toxicity profiles.

METHODS

Clinical studies published from 2012 to 2022 were systematically reviewed using PubMed, MEDLINE (via PubMed) and Cochrane databases. Different radiotherapy-related data were extracted and analyzed.

RESULTS

A total of 31 studies matched the inclusion criteria. Acute toxicity was less remarkable in stereotactic body radiotherapy (SBRT) compared to conventionally fractionated radiotherapy (CFRT), while in proton beam therapy (PBT) grade 3 or higher acute toxicity was observed more commonly with doses of 67.5 Gy (RBE) or higher. Late toxicity was not reported in most studies; therefore, comparison between groups was not possible. The range of median overall survival (OS) for the CFRT and SBRT groups was 9.3-22.9 months and 8.5-20 months, respectively. For the PBT group, the range of median OS was 18.4-22.3 months.

CONCLUSION

CFRT and SBRT showed comparable survival outcomes with a more favorable acute toxicity profile for SBRT. PBT is a promising new treatment modality; however, additional clinical studies are needed to support its efficacy and safety.

Lung cancer multi-omics digital human avatars for integrating precision medicine into clinical practice: the LANTERN study

BACKGROUND

The current management of lung cancer patients has reached a high level of complexity. Indeed, besides the traditional clinical variables (e.g., age, sex, TNM stage), new omics data have recently been introduced in clinical practice, thereby making more complex the decision-making process. With the advent of Artificial intelligence (AI) techniques, various omics datasets may be used to create more accurate predictive models paving the way for a better care in lung cancer patients.

METHODS

The LANTERN study is a multi-center observational clinical trial involving a multidisciplinary consortium of five institutions from different European countries. The aim of this trial is to develop accurate several predictive models for lung cancer patients, through the creation of Digital Human Avatars (DHA), defined as digital representations of patients using various omics-based variables and integrating well-established clinical factors with genomic data, quantitative imaging data etc. A total of 600 lung cancer patients will be prospectively enrolled by the recruiting centers and multi-omics data will be collected. Data will then be modelled and parameterized in an experimental context of cutting-edge big data analysis. All data variables will be recorded according to a shared common ontology based on variable-specific domains in order to enhance their direct actionability. An exploratory analysis will then initiate the biomarker identification process. The second phase of the project will focus on creating multiple multivariate models trained though advanced machine learning (ML) and AI techniques for the specific areas of interest. Finally, the developed models will be validated in order to test their robustness, transferability and generalizability, leading to the development of the DHA. All the potential clinical and scientific stakeholders will be involved in the DHA development process. The main goals aim of LANTERN project are: i) To develop predictive models for lung cancer diagnosis and histological characterization; (ii) to set up personalized predictive models for individual-specific treatments; iii) to enable feedback data loops for preventive healthcare strategies and quality of life management.

DISCUSSION

The LANTERN project will develop a predictive platform based on integration of multi-omics data. This will enhance the generation of important and valuable information assets, in order to identify new biomarkers that can be used for early detection, improved tumor diagnosis and personalization of treatment protocols.

ETHICS COMMITTEE APPROVAL NUMBER

5420 - 0002485/23 from Fondazione Policlinico Universitario Agostino Gemelli IRCCS - Università Cattolica del Sacro Cuore Ethics Committee.

TRIAL REGISTRATION

clinicaltrial.gov - NCT05802771.

STereotactic Arrhythmia Radioablation (STAR): the Standardized Treatment and Outcome Platform for Stereotactic Therapy Of Re-entrant tachycardia by a Multidisciplinary consortium (STOPSTORM.eu) and review of current patterns of STAR practice in Europe

The EU Horizon 2020 Framework-funded Standardized Treatment and Outcome Platform for Stereotactic Therapy Of Re-entrant tachycardia by a Multidisciplinary (STOPSTORM) consortium has been established as a large research network for investigating STereotactic Arrhythmia Radioablation (STAR) for ventricular tachycardia (VT). The aim is to provide a pooled treatment database to evaluate patterns of practice and outcomes of STAR and finally to harmonize STAR within Europe. The consortium comprises 31 clinical and research institutions. The project is divided into nine work packages (WPs): (i) observational cohort; (ii) standardization and harmonization of target delineation; (iii) harmonized prospective cohort; (iv) quality assurance (QA); (v) analysis and evaluation; (vi, ix) ethics and regulations; and (vii, viii) project coordination and dissemination. To provide a review of current clinical STAR practice in Europe, a comprehensive questionnaire was performed at project start. The STOPSTORM Institutions' experience in VT catheter ablation (83% ≥ 20 ann.) and stereotactic body radiotherapy (59% > 200 ann.) was adequate, and 84 STAR treatments were performed until project launch, while 8/22 centres already recruited VT patients in national clinical trials. The majority currently base their target definition on mapping during VT (96%) and/or pace mapping (75%), reduced voltage areas (63%), or late ventricular potentials (75%) during sinus rhythm. The majority currently apply a single-fraction dose of 25 Gy while planning techniques and dose prescription methods vary greatly. The current clinical STAR practice in the STOPSTORM consortium highlights potential areas of optimization and harmonization for substrate mapping, target delineation, motion management, dosimetry, and QA, which will be addressed in the various WPs.

Unchanged perfusion in normal-appearing white and grey matter of glioma patients nine months after proton beam irradiation

Purpose: Radio(chemo)therapy is used as a standard treatment for glioma patients. The surrounding normal tissue is inevitably affected by the irradiation. The aim of this longitudinal study was to investigate perfusion alterations in the normal-appearing tissue after proton irradiation and assess the dose sensitivity of the normal tissue perfusion.Methods: In 14 glioma patients, a sub-cohort of a prospective clinical trial (NCT02824731), perfusion changes in normal-appearing white matter (WM), grey matter (GM) and subcortical GM structures, i.e. caudate nucleus, hippocampus, amygdala, putamen, pallidum and thalamus, were evaluated before treatment and at three-monthly intervals after proton beam irradiation. The relative cerebral blood volume (rCBV) was assessed with dynamic susceptibility contrast MRI and analysed as the percentage ratio between follow-up and baseline image (ΔrCBV). Radiation-induced alterations were evaluated using Wilcoxon signed rank test. Dose and time correlations were investigated with univariate and multivariate linear regression models.Results: No significant ΔrCBV changes were found in any normal-appearing WM and GM region after proton beam irradiation. A positive correlation with radiation dose was observed in the multivariate regression model applied to the combined ΔrCBV values of low (1-20 Gy), intermediate (21-40 Gy) and high (41-60 Gy) dose regions of GM (p < 0.001), while no time dependency was detected in any normal-appearing area.Conclusion: The perfusion in normal-appearing brain tissue remained unaltered after proton beam therapy. In further studies, a direct comparison with changes after photon therapy is recommended to confirm the different effect of proton therapy on the normal-appearing tissue.

Increased relative biological effectiveness and periventricular radiosensitivity in proton therapy of glioma patients

PURPOSE

Currently, there is an intense debate on variations in intra-cerebral radiosensitivity and relative biological effectiveness (RBE) in proton therapy of primary brain tumours. Here, both effects were retrospectively investigated using late radiation-induced brain injuries (RIBI) observed in follow-up after proton therapy of patients with diagnosed glioma.

METHODS

In total, 42 WHO grade 2-3 glioma patients out of a consecutive patient cohort having received (adjuvant) proton radio(chemo)therapy between 2014 and 2017 were eligible for analysis. RIBI lesions (symptomatic or clinically asymptomatic) were diagnosed and delineated on contrast-enhanced T1-weighted magnetic resonance imaging scans obtained in the first two years of follow-up. Correlation of RIBI location and occurrence with dose (D), proton dose-averaged linear energy transfer (LET) and variable RBE dose parameters were tested in voxel- and in patient-wise logistic regression analyses. Additionally, anatomical and clinical parameters were considered. Model performance was estimated through cross-validated area-under-the-curve (AUC) values.

RESULTS

In total, 64 RIBI lesions were diagnosed in 21 patients. The median time between start of proton radio(chemo)therapy and RIBI appearance was 10.2 months. Median distances of the RIBI volume centres to the cerebral ventricles and to the clinical target volume border were 2.1 mm and 1.3 mm, respectively. In voxel-wise regression, the multivariable model with D, D × LET and periventricular region (PVR) revealed the highest AUC of 0.90 (95 % confidence interval: 0.89-0.91) while the corresponding model without D × LET revealed a value of 0.84 (0.83-0.86). In patient-level analysis, the equivalent uniform dose (EUD₁₁, a = 11) in the PVR using a variable RBE was the most prominent predictor for RIBI with an AUC of 0.63 (0.32-0.90).

CONCLUSIONS

In this glioma cohort, an increased radiosensitivity within the PVR was observed as well as a spatial correlation of RIBI with an increased RBE. Both need to be considered when delivering radio(chemo)therapy using proton beams.

Ultrasonic bone cement removal efficiency in total joint arthroplasty revision: A computer tomographic-based cadaver study

Polymethylmethacrylate (PMMA) removal during septic total joint arthroplasty revision is associated with a high fracture and perforation risk. Ultrasonic cement removal is considered a bone-preserving technique. Currently, there is still a lack of sound data on efficacy as it is difficult to detect smaller residues with reasonable technical effort. However, incomplete removal is associated with the risk of biofilm coverage of the residue. Therefore, the study aimed to investigate the efficiency of ultrasonic-based PMMA removal in a human cadaver model. The femoral components of a total hip and a total knee prosthesis were implanted in two cadaver femoral canals by 3rd generation cement fixation technique. Implants were then removed. Cement mantle extraction was performed with the OSCAR-3-System ultrasonic system (Orthofix®). Quantitative analysis of cement residues was carried out with dual-energy and microcomputer tomography. With a 20 µm resolution, in vitro microcomputer tomography visualized tiniest PMMA residues. For clinical use, dual-energy computer tomography tissue decomposition with 0.75 mm resolution is suitable. With ultrasound, more than 99% of PMMA was removed. Seven hundred thirty-four residues with a mean volume of 0.40 ± 4.95 mm³ were identified with only 4 exceeding 1 cm in length in at least one axis. Ultrasonic cement removal of PMMA was almost complete and can therefore be considered a highly effective technique. For the first time, PMMA residues in the sub-millimetre range were detected by computer tomography. Clinical implications of the small remaining PMMA fraction on the eradication rate of periprosthetic joint infection warrants further investigations.

Orthotopic Glioblastoma Models for Evaluation of the Clinical Target Volume Concept

Simple Summary

The accurate and precise definition of the target volume is of enormous importance for the treatment success of radiotherapy. In glioblastoma, the microscopic tumor extension is unclear, which limits the specificity of irradiation leading to either increased risk of local failure or enhanced toxicity rates. In this study, we investigated the microscopic tumor extensions of two different untreated and irradiated orthotopic brain tumor models and correlated this with histologically stained cancer stem cell markers as well as invasion markers and analyses using Matrix-Assisted Laser Desorption/Ionization (MALDI). We found specific MALDI peaks as potential markers for normal brain tissue but also others for demarcation of tumor areas. Furthermore, MMP14 staining revealed mainly positive cells in the tumor border, which could reflect the invasive front in both models. Altogether, the results of this study indicate that an individualized target volume definition for radiotherapy based on biological tumor characteristics in glioblastoma models seems possible.

Abstract

In times of high-precision radiotherapy, the accurate and precise definition of the primary tumor localization and its microscopic spread is of enormous importance. In glioblastoma, the microscopic tumor extension is uncertain and, therefore, population-based margins for Clinical Target Volume (CTV) definition are clinically used, which could either be too small—leading to increased risk of loco-regional recurrences—or too large, thus, enhancing the probability of normal tissue toxicity. Therefore, the aim of this project is to investigate an individualized definition of the CTV in preclinical glioblastoma models based on specific biological tumor characteristics. The microscopic tumor extensions of two different orthotopic brain tumor models (U87MG_mCherry; G7_mCherry) were evaluated before and during fractionated radiotherapy and correlated with corresponding histological data. Representative tumor slices were analyzed using Matrix-Assisted Laser Desorption/Ionization (MALDI) and stained for putative stem-like cell markers as well as invasion markers. The edges of the tumor are clearly shown by the MALDI segmentation via unsupervised clustering of mass spectra and are consistent with the histologically defined border in H&E staining in both models. MALDI component analysis identified specific peaks as potential markers for normal brain tissue (e.g., 1339 m/z), whereas other peaks demarcated the tumors very well (e.g., 1562 m/z for U87MG_mCherry) irrespective of treatment. MMP14 staining revealed only a few positive cells, mainly in the tumor border, which could reflect the invasive front in both models. The results of this study indicate that MALDI information correlates with microscopic tumor spread in glioblastoma models. Therefore, an individualized CTV definition based on biological tumor characteristics seems possible, whereby the visualization of tumor volume and protein heterogeneity can be potentially used to define radiotherapy-sensitive and resistant areas.

18F-Fluorodeoxyglucose Positron Emission Tomography of Head and Neck Cancer: Location and HPV Specific Parameters for Potential Treatment Individualization

Purpose

18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is utilized for staging and treatment planning of head and neck squamous cell carcinomas (HNSCC). Some older publications on the prognostic relevance showed inconclusive results, most probably due to small study sizes. This study evaluates the prognostic and potentially predictive value of FDG-PET in a large multi-center analysis.

Methods

Original analysis of individual FDG-PET and patient data from 16 international centers (8 institutional datasets, 8 public repositories) with 1104 patients. All patients received curative intent radiotherapy/chemoradiation (CRT) and pre-treatment FDG-PET imaging. Primary tumors were semi-automatically delineated for calculation of SUV_max, SUV_mean, metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Cox regression analyses were performed for event-free survival (EFS), overall survival (OS), loco-regional control (LRC) and freedom from distant metastases (FFDM).

Results

FDG-PET parameters were associated with patient outcome in the whole cohort regarding clinical endpoints (EFS, OS, LRC, FFDM), in uni- and multivariate Cox regression analyses. Several previously published cut-off values were successfully validated. Subgroup analyses identified tumor- and human papillomavirus (HPV) specific parameters. In HPV positive oropharynx cancer (OPC) SUV_max was well suited to identify patients with excellent LRC for organ preservation. Patients with SUV_max of 14 or less were unlikely to develop loco-regional recurrence after definitive CRT. In contrast FDG PET parameters deliver only limited prognostic information in laryngeal cancer.

Conclusion

FDG-PET parameters bear considerable prognostic value in HNSCC and potential predictive value in subgroups of patients, especially regarding treatment de-intensification and organ-preservation. The potential predictive value needs further validation in appropriate control groups. Further research on advanced imaging approaches including radiomics or artificial intelligence methods should implement the identified cut-off values as benchmark routine imaging parameters.

Analysis of MRI and CT-based radiomics features for personalized treatment in locally advanced rectal cancer and external validation of published radiomics models

Radiomics analyses commonly apply imaging features of different complexity for the prediction of the endpoint of interest. However, the prognostic value of each feature class is generally unclear. Furthermore, many radiomics models lack independent external validation that is decisive for their clinical application. Therefore, in this manuscript we present two complementary studies. In our modelling study, we developed and validated different radiomics signatures for outcome prediction after neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC) based on computed tomography (CT) and T2-weighted (T2w) magnetic resonance (MR) imaging datasets of 4 independent institutions (training: 122, validation 68 patients). We compared different feature classes extracted from the gross tumour volume for the prognosis of tumour response and freedom from distant metastases (FFDM): morphological and first order (MFO) features, second order texture (SOT) features, and Laplacian of Gaussian (LoG) transformed intensity features. Analyses were performed for CT and MRI separately and combined. Model performance was assessed by the area under the curve (AUC) and the concordance index (CI) for tumour response and FFDM, respectively. Overall, intensity features of LoG transformed CT and MR imaging combined with clinical T stage (cT) showed the best performance for tumour response prediction, while SOT features showed good performance for FFDM in independent validation (AUC = 0.70, CI = 0.69). In our external validation study, we aimed to validate previously published radiomics signatures on our multicentre cohort. We identified relevant publications on comparable patient datasets through a literature search and applied the reported radiomics models to our dataset. Only one of the identified studies could be validated, indicating an overall lack of reproducibility and the need of further standardization of radiomics before clinical application.

Assessment of gene expressions from squamous cell carcinoma of the head and neck to predict radiochemotherapy-related xerostomia and dysphagia

PURPOSE

We tested the hypothesis that gene expressions from biopsies of locally advanced head and neck squamous cell carcinoma (HNSCC) patients can supplement dose-volume parameters to predict dysphagia and xerostomia following primary radiochemotherapy (RCTx).

MATERIAL AND METHODS

A panel of 178 genes previously related to radiochemosensitivity of HNSCC was considered for nanoString analysis based on tumour biopsies of 90 patients with locally advanced HNSCC treated by primary RCTx. Dose-volume parameters were extracted from the parotid, submandibular glands, oral cavity, larynx, buccal mucosa, and lips. Normal tissue complication probability (NTCP) models were developed for acute, late, and for the improvement of xerostomia grade ≥2 and dysphagia grade ≥3 using a cross-validation-based least absolute shrinkage and selection operator (LASSO) approach combined with stepwise logistic regression for feature selection. The final signatures were included in a logistic regression model with optimism correction. Performance was assessed by the area under the receiver operating characteristic curve (AUC).

RESULTS

NTCP models for acute and late xerostomia and the improvement of dysphagia resulted in optimism-corrected AUC values of 0.84, 0.76, and 0.70, respectively. The minimum dose to the contralateral parotid was selected for both acute and late xerostomia and the minimum dose to the larynx was selected for dysphagia improvement. For the xerostomia endpoints, the following gene expressions were selected: RPA2 (cellular response to DNA damage), TCF3 (salivary gland cells development), GBE1 (glycogen storage and regulation), and MAPK3 (regulation of cellular processes). No gene expression features were selected for the prediction of dysphagia.

CONCLUSION

This hypothesis-generating study showed the potential of improving NTCP models using gene expression data for HNSCC patients. The presented models require independent validation before potential application in clinical practice.

Treatment planning comparison in the PROTECT-trial randomising proton versus photon beam therapy in oesophageal cancer: results from eight european centres

PURPOSE

To compare dose distributions and robustness in treatment plans from eight European centres in preparation for the European randomized phase-III PROTECT-trial investigating the effect of proton therapy (PT) versus photon therapy (XT) for oesophageal cancer.

MATERIALS AND METHODS

All centres optimized one PT and one XT nominal plan using delineated 4DCT scans for four patients receiving 50.4Gy(RBE) in 28 fractions. Target volume receiving 95% of prescribed dose (V95%_iCTVtotal) should be >99%. Robustness towards setup, range, and respiration was evaluated. The plans were recalculated on a surveillance 4DCT (sCT) acquired at fraction ten and robustness evaluation was performed to evaluate the effect of respiration and inter-fractional anatomical changes.

RESULTS

All PT and XT plans complied with V95%_iCTVtotal>99% for the nominal plan and V95%_iCTVtotal>97% for all respiratory and robustness scenarios. Lung and heart dose varied considerably between centres for both modalities. The difference in mean lung dose and mean heart dose between each pair of XT and PT plans was in median [range] 4.8Gy [1.1;7.6] and 8.4Gy [1.9;24.5], respectively. Patients B and C showed large inter-fractional anatomical changes on sCT. For patient B, the minimum V95%_iCTVtotal in the worst-case robustness scenario was 45% and 94% for XT and PT, respectively. For patient C, the minimum V95%_iCTVtotal was 57% and 72% for XT and PT, respectively. Patient A and D showed minor inter-fractional changes and the minimum V95%_iCTVtotal was >85%.

CONCLUSION

Large variability in dose to the lungs and heart was observed for both modalities. Inter-fractional anatomical changes led to larger target dose deterioration for XT than PT plans.

Experimental validation of 4D log file-based proton dose reconstruction for interplay assessment considering amplitude-sorted 4DCTs

PURPOSE

The unpredictable interplay between dynamic proton therapy delivery and target motion in the thorax can lead to severe dose distortions. A fraction-wise four-dimensional (4D) dose reconstruction workflow allows for the assessment of the applied dose after patient treatment while considering the actual beam delivery sequence extracted from machine log files, the recorded breathing pattern and the geometric information from a 4D computed tomography scan (4DCT). Such an algorithm capable of accounting for amplitude-sorted 4DCTs was implemented and its accuracy as well as its sensitivity to input parameter variations was experimentally evaluated.

METHODS

An anthropomorphic thorax phantom with a movable insert containing a target surrogate and a radiochromic film was irradiated with a monoenergetic field for various 1D target motion forms (sin, sin4) and peak-to-peak amplitudes (5/10/15/20/30 mm). The measured characteristic film dose distributions were compared to the respective sections in the 4D reconstructed doses using a 2D γ-analysis (3mm, 3%); γ-pass rates were derived for different dose grid resolutions (1mm/3mm) and deformable image registrations (DIR, automatic/manual) applied during the 4D dose reconstruction process. In an additional analysis, the sensitivity of reconstructed dose distributions against potential asynchronous timing of the motion and machine log files was investigated for both a monoenergetic field and more realistic 4D robustly optimized fields by artificially introduced offsets of ± 1/5/25/50/250 ms. The resulting dose distributions with asynchronized log files were compared to those with synchronized log files by means of a 3D γ-analysis (1mm, 1%) and the evaluation of absolute dose differences.

RESULTS

The induced characteristic interplay patterns on the films were well reproduced by the 4D dose reconstruction with 2D γ-pass rates ≥95% for almost all cases with motion magnitudes ≤15 mm. In general, the 2D γ-pass rates showed a significant decrease for larger motion amplitudes and increase when using a finer dose grid resolution but were not affected by the choice of motion form (sin, sin4). There was also a trend, though not statistically significant, towards the manually defined DIR for better quality of the reconstructed dose distributions in the area imaged by the film. The 4D dose reconstruction results for the monoenergetic as well as the 4D robustly optimized fields were robust against small asynchronies between motion and machine log files of up to 5 ms, which is in the order of potential network latencies.

CONCLUSIONS

We have implemented a 4D log file-based proton dose reconstruction that accounts for amplitude-sorted 4DCTs. Its accuracy was proven to be clinically acceptable for target motion magnitudes of up to 15 mm. Particular attention should be paid to the synchronization of the log file generating systems as the reconstructed dose distribution may vary with log file asynchronies larger than those caused by realistic network delays. This article is protected by copyright. All rights reserved.

Joint EANM/SNMMI/ESTRO practice recommendations for the use of 2-[18F]FDG PET/CT external beam radiation treatment planning in lung cancer V1.0

Purpose

2-[¹⁸F]FDG PET/CT is of utmost importance for radiation treatment (RT) planning and response monitoring in lung cancer patients, in both non-small and small cell lung cancer (NSCLC and SCLC). This topic has been addressed in guidelines composed by experts within the field of radiation oncology. However, up to present, there is no procedural guideline on this subject, with involvement of the nuclear medicine societies.

Methods

A literature review was performed, followed by a discussion between a multidisciplinary team of experts in the different fields involved in the RT planning of lung cancer, in order to guide clinical management. The project was led by experts of the two nuclear medicine societies (EANM and SNMMI) and radiation oncology (ESTRO).

Results and conclusion

This guideline results from a joint and dynamic collaboration between the relevant disciplines for this topic. It provides a worldwide, state of the art, and multidisciplinary guide to 2-[¹⁸F]FDG PET/CT RT planning in NSCLC and SCLC. These practical recommendations describe applicable updates for existing clinical practices, highlight potential flaws, and provide solutions to overcome these as well. Finally, the recent developments considered for future application are also reviewed.

Perspective paper about the joint EANM/SNMMI/ESTRO practice recommendations for the use of 2-[18F]FDG-PET/CT external beam radiation treatment planning in lung cancer

In “Joint EANM/SNMMI/ESTRO Practice Recommendations for the Use of 2-[18F]FDG-PET/CT External Beam Radiation Treatment Planning in Lung Cancer V1.0” clinical indications for PET-CT in (non-)small cell lung cancer are highlighted and selective nodal irradiation is discussed. Additionally, concepts about target definition, target delineation and treatment evaluation are reviewed.

Current practice in proton therapy delivery in adult cancer patients across Europe

BACKGROUND AND PURPOSE

Major differences exist among proton therapy (PT) centres regarding PT delivery in adult cancer patient. To obtain insight into current practice in Europe, we performed a survey among European PT centres.

MATERIALS AND METHODS

We designed electronic questionnaires for eight tumour sites, focusing on four main topics: 1) indications and patient selection methods; 2) reimbursement; 3) on-going or planned studies, 4) annual number of patients treated with PT.

RESULTS

Of 22 centres, 19 (86%) responded. In total, 4233 adult patients are currently treated across Europe annually, of which 46% consists of patients with central nervous system tumours (CNS), 15% head and neck cancer (HNC), 15% prostate, 9% breast, 5% lung, 5% gastrointestinal, 4% lymphoma, 0.3% gynaecological cancers. CNS are treated in all participating centres (n = 19) using PT, HNC in 16 centres, lymphoma in 10 centres, gastrointestinal in 10 centres, breast in 7 centres, prostate in 6 centres, lung in 6 centres, and gynaecological cancers in 3 centres. Reimbursement is provided by national health care systems for the majority of commonly treated tumour sites. Approximately 74% of centres enrol patients for prospective data registration programs. Phase II-III trials are less frequent, due to reimbursement and funding problems. Reasons for not treating certain tumour types with PT are lack of evidence (30%), reimbursement issues (29%) and/or technical limitations (20%).

CONCLUSION

Across European PT centres, CNS tumours and HNC are the most frequently treated tumour types. Most centres use indication protocols. Lack of evidence for PT and reimbursement issues are the most reported reasons for not treating specific tumour types with PT.