Target coverage and organs at risk dose in hypofractionated salvage radiotherapy after prostatectomy.

Background And Purpose: Introducing moderately hypofractionated salvage radiotherapy (SRT) following prostatectomy obligates investigation of its effects on clinical target volume (CTV) coverage and organ-at-risk (OAR) doses. This study assessed interfractional volume and dose changes in OARs and CTV in moderately hypofractionated SRT and evaluated the 8-mm planning target volume (PTV) margin.

Materials And Methods: Twenty patients from the PERYTON-trial were included; 10 received conventional SRT (35 × 2 Gy) and 10 hypofractionated SRT (20 × 3 Gy).

Patterns of practice of image guided particle therapy for cranio-spinal irradiation: A site specific multi-institutional survey of European Particle Therapy Network.

Purpose: To investigate the current practice patterns in image-guided particle therapy (IGPT) for cranio-spinal irradiation (CSI).

Methods: A multi-institutional survey was distributed to European particle therapy centres to analyse all aspects of IGPT. Based on the survey results, a Delphi consensus analysis was developed to define minimum requirements and optimal workflow for clinical practice.

Proton PBS Planning Techniques, Robustness Evaluation, and OAR Sparing for the Whole-Brain Part of Craniospinal Axis Irradiation.

Proton therapy is a promising modality for craniospinal irradiation (CSI), offering dosimetric advantages over conventional treatments. While significant attention has been paid to spine fields, for the brain fields, only dose reduction to the lens of the eye has been reported. Hence, the objective of this study is to assess the potential gains and feasibility of adopting different treatment planning techniques for the entire brain within the CSI target.

Pretrial Quality Assurance for Hypofractionated Salvage Radiation Therapy After Prostatectomy in the Multi-Institutional PERYTON-trial.

Purpose: The PERYTON trial is a multicenter randomized controlled trial that will investigate whether the treatment outcome of salvage external beam radiation therapy (sEBRT) will be improved with hypofractionated radiation therapy. A pretrial quality assurance (QA) program was undertaken to ensure protocol compliance within the PERYTON trial and to assess variation in sEBRT treatment protocols between the participating centers.

Methods And Materials: Completion of the QA program was mandatory for each participating center (N = 8) to start patient inclusion.

Optimal timing of re-planning for head and neck adaptive radiotherapy.

Background And Purpose: Adaptive radiotherapy (ART) relies on re-planning to correct treatment variations, but the optimal timing of re-planning to account for dose changes in head and neck organs at risk (OARs) is still under investigation. We aimed to find out the optimal timing of re-planning in head and neck ART.

Materials And Methods: A total of 110 head and neck cancer patients were retrospectively enrolled.

Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography-Based Clinical Target Volume Delineation Guideline for Postprostatectomy Salvage Radiation Therapy: The PERYTON Guideline.

Purpose: Prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT) scan is the standard imaging procedure for biochemical recurrent prostate cancer postprostatectomy because of its high detection rate at low serum prostate-specific antigen levels. However, existing guidelines for clinical target volume (CTV) in prostate bed salvage external beam radiation therapy (sEBRT) are primarily based on experience-based clinical consensus and have been validated using conventional imaging modalities. Therefore, this study aimed to optimize CTV definition in sEBRT by using PSMA PET/CT-detected local recurrences (LRs).

Dose evaluation of inter- and intra-fraction prostate motion in extremely hypofractionated intensity-modulated proton therapy for prostate cancer.

Inter- and intra-fractional prostate motion can deteriorate the dose distribution in extremely hypofractionated intensity-modulated proton therapy. We used verification CTs and prostate motion data calculated from 1024 intra-fractional prostate motion records to develop a voxel-wise based 4-dimensional method, which had a time resolution of 1 s, to assess the dose impact of prostate motion. An example of 100 fractional simulations revealed that motion had minimal impact on planning dose, the accumulated dose in 95 % of the scenarios fulfilled the clinical goals for target coverage (D95 > 37.

Simple immobilization for stereotactic radiotherapy aimed at pelvic metastases.

Stereotactic body radiotherapy (SBRT) is increasingly applied for pelvic oligometastases of prostate cancer, and currently no simple immobilization method is available for cone beam computed tomography (CBCT)-guided treatment. We assessed patient set-up and intrafraction motion using simple immobilization during CBCT-guided pelvic SBRT. Forty patients were immobilized with basic arm- head- and knee support and either a thermoplastic cushion or a foam cushion.

Effects of proton therapy on regional [F]FDG uptake in non-tumor brain regions of patients treated for head and neck cancer.

Background And Purpose: Previous pre-clinical research using [F]FDG-PET has shown that whole-brain photon-based radiotherapy can affect brain glucose metabolism. This study, aimed to investigate how these findings translate into regional changes in brain [F]FDG uptake in patients with head and neck cancer treated with intensity-modulated proton therapy (IMPT).

Materials And Methods: Twenty-three head and neck cancer patients treated with IMPT and available [F]FDG scans before and at 3 months follow-up were retrospectively evaluated.

An efficient strategy to select head and neck cancer patients for adaptive radiotherapy.

Background And Purpose: Adaptive radiotherapy (ART) is workload intensive but only benefits a subgroup of patients. We aimed to develop an efficient strategy to select candidates for ART in the first two weeks of head and neck cancer (HNC) radiotherapy.

Materials And Methods: This study retrospectively enrolled 110 HNC patients who underwent modern photon radiotherapy with at least 5 weekly in-treatment re-scan CTs.

An investigation into the risk of population bias in deep learning autocontouring.

Background And Purpose: To date, data used in the development of Deep Learning-based automatic contouring (DLC) algorithms have been largely sourced from single geographic populations. This study aimed to evaluate the risk of population-based bias by determining whether the performance of an autocontouring system is impacted by geographic population.

Materials And Methods: 80 Head Neck CT deidentified scans were collected from four clinics in Europe (n = 2) and Asia (n = 2).

Accurate segmentation of head and neck radiotherapy CT scans with 3D CNNs: consistency is key.

Automatic segmentation of organs-at-risk in radiotherapy planning computed tomography (CT) scans using convolutional neural networks (CNNs) is an active research area. Very large datasets are usually required to train such CNN models. In radiotherapy, large, high-quality datasets are scarce and combining data from several sources can reduce the consistency of training segmentations.

Quality Assurance for AI-Based Applications in Radiation Therapy.

Recent advancements in artificial intelligence (AI) in the domain of radiation therapy (RT) and their integration into modern software-based systems raise new challenges to the profession of medical physics experts. These AI algorithms are typically data-driven, may be continuously evolving, and their behavior has a degree of (acceptable) uncertainty due to inherent noise in training data and the substantial number of parameters that are used in the algorithms. These characteristics request adaptive, and new comprehensive quality assurance (QA) approaches to guarantee the individual patient treatment quality during AI algorithm development and subsequent deployment in a clinical RT environment.

Clinical relevance of the radiation dose bath in lower grade glioma, a cross-sectional pilot study on neurocognitive and radiological outcome.

Aim: To investigate the clinical relevance of the radiotherapy (RT) dose bath in patients treated for lower grade glioma (LGG).

Methods: Patients (n = 17) treated with RT for LGG were assessed with neurocognitive function (NCF) tests and structural Magnetic Resonance Imaging (MRI) and categorized in subgroups based on tumour lateralisation. RT dose, volumetric results and cerebral microbleed (CMB) number were extracted for contralateral cerebrum, contralateral hippocampus, and cerebellum.

A novel semi auto-segmentation method for accurate dose and NTCP evaluation in adaptive head and neck radiotherapy.

Background And Purpose: Accurate segmentation of organs-at-risk (OARs) is crucial but tedious and time-consuming in adaptive radiotherapy (ART). The purpose of this work was to automate head and neck OAR-segmentation on repeat CT (rCT) by an optimal combination of human and auto-segmentation for accurate prediction of Normal Tissue Complication Probability (NTCP).

Materials And Methods: Human segmentation (HS) of 3 observers, deformable image registration (DIR) based contour propagation and deep learning contouring (DLC) were carried out to segment 15 OARs on 15 rCTs.

Validation of separate multi-atlases for auto segmentation of cardiac substructures in CT-scans acquired in deep inspiration breath hold and free breathing.

Background And Purpose: Developing NTCP-models for cardiac complications after breast cancer (BC) radiotherapy requires cardiac dose-volume parameters for many patients. These can be obtained by using multi-atlas based automatic segmentation (MABAS) of cardiac structures in planning CT scans. We investigated the relevance of separate multi-atlases for deep inspiration breath hold (DIBH) and free breathing (FB) CT scans.

Machine learning applications in radiation oncology: Current use and needs to support clinical implementation.

Background And Purpose: The use of artificial intelligence (AI)/ machine learning (ML) applications in radiation oncology is emerging, however no clear guidelines on commissioning of ML-based applications exist. The purpose of this study was therefore to investigate the current use and needs to support implementation of ML-based applications in routine clinical practice.

Materials And Methods: A survey was conducted among medical physicists in radiation oncology, consisting of four parts: clinical applications (1), model training, acceptance and commissioning (2), quality assurance (QA) in clinical practice and General Data Protection Regulation (GDPR) (3), and need for education and guidelines (4).

Assessment of manual adjustment performed in clinical practice following deep learning contouring for head and neck organs at risk in radiotherapy.

Background And Purpose: Auto-contouring performance has been widely studied in development and commissioning studies in radiotherapy, and its impact on clinical workflow assessed in that context. This study aimed to evaluate the manual adjustment of auto-contouring in routine clinical practice and to identify improvements regarding the auto-contouring model and clinical user interaction, to improve the efficiency of auto-contouring.

Materials And Methods: A total of 103 clinical head and neck cancer cases, contoured using a commercial deep-learning contouring system and subsequently checked and edited for clinical use were retrospectively taken from clinical data over a twelve-month period (April 2019-April 2020).

External validation of deep learning-based contouring of head and neck organs at risk.

Background And Purpose: Head and neck (HN) radiotherapy can benefit from automatic delineation of tumor and surrounding organs because of the complex anatomy and the regular need for adaptation. The aim of this study was to assess the performance of a commercially available deep learning contouring (DLC) model on an external validation set.

Materials And Methods: The CT-based DLC model, trained at the University Medical Center Groningen (UMCG), was applied to an independent set of 58 patients from the Radboud University Medical Center (RUMC).

Inter-fraction motion robustness and organ sparing potential of proton therapy for cervical cancer.

Purpose: Large-field photon radiotherapy is current standard in the treatment of cervical cancer patients. However, with the increasing availability of Pencil Beam Scanning Proton Therapy (PBS-PT) and robust treatment planning techniques, protons may have significant advantages for cervical cancer patients in the reduction of toxicity. In this study, PBS-PT and photon Volumetric Modulated Arc Therapy (VMAT) were compared, examining target coverage and organ at risk (OAR) dose, taking inter- and intra-fraction motion into account.

Improving automatic delineation for head and neck organs at risk by Deep Learning Contouring.

Introduction: Adequate head and neck (HN) organ-at-risk (OAR) delineation is crucial for HN radiotherapy and for investigating the relationships between radiation dose to OARs and radiation-induced side effects. The automatic contouring algorithms that are currently in clinical use, such as atlas-based contouring (ABAS), leave room for improvement. The aim of this study was to use a comprehensive evaluation methodology to investigate the performance of HN OAR auto-contouring when using deep learning contouring (DLC), compared to ABAS.

Evaluating the benefit of PBS vs. VMAT dose distributions in terms of dosimetric sparing and robustness against inter-fraction anatomical changes for pediatric abdominal tumors.

Background And Purpose: To evaluate the dosimetric sparing and robustness against inter-fraction anatomical changes between photon and proton dose distributions for children with abdominal tumors.

Material And Methods: Volumetric modulated arc therapy (VMAT) and intensity-modulated pencil beam scanning (PBS) proton dose distributions were calculated for 20 abdominal pediatric cases (average 3, range 1-8 years). VMAT plans were based on a full-arc while PBS plans on 2-3 posterior-oblique irradiation fields.

Feasibility of MRI-only photon and proton dose calculations for pediatric patients with abdominal tumors.

The purpose of this study was to develop a method enabling synthetic computed tomography (sCT) generation of the whole abdomen using magnetic resonance imaging (MRI) scans of pediatric patients with abdominal tumors. The proposed method relies on an automatic atlas-based segmentation of bone and lungs followed by an MRI intensity to synthetic Hounsfield unit conversion. Separate conversion algorithms were used for bone, lungs and soft-tissue.

F-FDG PET image biomarkers improve prediction of late radiation-induced xerostomia.

Background And Purpose: Current prediction of radiation-induced xerostomia 12months after radiotherapy (Xer) is based on mean parotid gland dose and baseline xerostomia (Xer) scores. The hypothesis of this study was that prediction of Xer is improved with patient-specific characteristics extracted from F-FDG PET images, quantified in PET image biomarkers (PET-IBMs).

Patients And Methods: Intensity and textural PET-IBMs of the parotid gland were collected from pre-treatment F-FDG PET images of 161 head and neck cancer patients.

Geometric Image Biomarker Changes of the Parotid Gland Are Associated With Late Xerostomia.

Purpose: To identify a surrogate marker for late xerostomia 12 months after radiation therapy (Xer), according to information obtained shortly after treatment.

Methods And Materials: Differences in parotid gland (PG) were quantified in image biomarkers (ΔIBMs) before and 6 weeks after radiation therapy in 107 patients. By performing stepwise forward selection, ΔIBMs that were associated with Xer were selected.