Inter-center comparison of proton range verification prototypes with an anthropomorphic head phantom.

. To compare in reproducible and equalized conditions the performance of two independent proton range verification systems based on prompt gamma-ray detectors from two different proton therapy centers..

Split-filter dual energy computed tomography radiotherapy: From calibration to image guidance.

Background And Purpose: Dual-energy computed tomography (DECT) is an emerging technology in radiotherapy (RT). Here, we investigate split-filter DECT throughout the RT treatment chain as compared to single-energy CT (SECT).

Materials And Methods: DECT scans were acquired with a tin-gold split-filter at 140 kV resulting in a low- and high-energy CT reconstruction (recon).

Consensus guide on CT-based prediction of stopping-power ratio using a Hounsfield look-up table for proton therapy.

Background And Purpose: Studies have shown large variations in stopping-power ratio (SPR) prediction from computed tomography (CT) across European proton centres. To standardise this process, a step-by-step guide on specifying a Hounsfield look-up table (HLUT) is presented here.

Materials And Methods: The HLUT specification process is divided into six steps: Phantom setup, CT acquisition, CT number extraction, SPR determination, HLUT specification, and HLUT validation.

Dual- and multi-energy CT for particle stopping-power estimation: current state, challenges and potential.

Range uncertainty has been a key factor preventing particle radiotherapy from reaching its full physical potential. One of the main contributing sources is the uncertainty in estimating particle stopping power () within patients. Currently, thedistribution in a patient is derived from a single-energy CT (SECT) scan acquired for treatment planning by converting CT number expressed in Hounsfield units (HU) of each voxel tousing a Hounsfield look-up table (HLUT), also known as the CT calibration curve.

In vivo assessment of tissue-specific radiological parameters with intra- and inter-patient variation using dual-energy computed tomography.

Purpose/objective: Experimental in vivo determination of radiological tissue parameters of organs in the head and pelvis within a large patient cohort, expanding on the current standard human tissue database summarized in ICRU46.

Material/methods: Relative electron density (RED), effective atomic number (EAN) and stopping-power ratio (SPR) were obtained from clinical dual-energy CT scans using a clinically validated DirectSPR implementation and organ segmentations of 107 brain-tumor (brain, brainstem, spinal cord, chiasm, optical nerve, lens) and 120 pelvic cancer patients (prostate, kidney, liver, bladder). The impact of contamination by surrounding tissues on the tissue parameters was reduced with a dedicated contour adaption routine.

Reduction of clinical safety margins in proton therapy enabled by the clinical implementation of dual-energy CT for direct stopping-power prediction.

Purpose: To quantifiy the range uncertainty in proton treatment planning using dual-energy computed tomography (DECT) for a direct stopping-power prediction (DirectSPR) algorithm and its clinical implementation.

Methods And Materials: To assess the overall uncertainty in stopping-power ratio (SPR) prediction of a DirectSPR implementation calibrated for different patient geometries, the influencing factors were categorized in imaging, modeling as well as others. The respective SPR uncertainty was quantified for lung, soft tissue and bone and translated into range uncertainty for several tumor types.

Experimental assessment of inter-centre variation in stopping-power and range prediction in particle therapy.

Purpose: Experimental assessment of inter-centre variation and absolute accuracy of stopping-power-ratio (SPR) prediction within 17 particle therapy centres of the European Particle Therapy Network.

Material And Methods: A head and body phantom with seventeen tissue-equivalent materials were scanned consecutively at the participating centres using their individual clinical CT scan protocol and translated into SPR with their in-house CT-number-to-SPR conversion. Inter-centre variation and absolute accuracy in SPR prediction were quantified for three tissue groups: lung, soft tissues and bones.

First-In-Human Validation of CT-Based Proton Range Prediction Using Prompt Gamma Imaging in Prostate Cancer Treatments.

Purpose: Uncertainty in computed tomography (CT)-based range prediction substantially impairs the accuracy of proton therapy. Direct determination of the stopping-power ratio (SPR) from dual-energy CT (DECT) has been proposed (DirectSPR), and initial validation studies in phantoms and biological tissues have proven a high accuracy. However, a thorough validation of range prediction in patients has not yet been achieved by any means.

Roadmap: proton therapy physics and biology.

The treatment of cancer with proton radiation therapy was first suggested in 1946 followed by the first treatments in the 1950s. As of 2020, almost 200 000 patients have been treated with proton beams worldwide and the number of operating proton therapy (PT) facilities will soon reach one hundred. PT has long moved from research institutions into hospital-based facilities that are increasingly being utilized with workflows similar to conventional radiation therapy.

Impact of range uncertainty on clinical distributions of linear energy transfer and biological effectiveness in proton therapy.

Purpose: Increased radiation response after proton irradiation, such as late radiation-induced toxicity, is determined by high dose and elevated linear energy transfer (LET). Steep dose-averaged LET (LET ) gradients and elevated LET occur at the end of proton range and might be particularly sensitive to uncertainties in range prediction. Therefore, this study quantified LET distributions and the impact of range uncertainty in robust dose-optimized proton treatment plans and assessed the biological effect in normal tissues and tumors of patients.

Material assignment for proton range prediction in Monte Carlo patient simulations using stopping-power datasets.

Unlabelled: Motivation and objective. For each institute, the selection and calibration of the most suitable approach to assign material properties for Monte Carlo (MC) patient simulation in proton therapy is a major challenge. Current conventional approaches based on computed tomography (CT) depend on CT acquisition and reconstruction settings.

Refinement of the Hounsfield look-up table by retrospective application of patient-specific direct proton stopping-power prediction from dual-energy CT.

Background And Purpose: Proton treatment planning relies on an accurate determination of stopping-power ratio (SPR) from x-ray computed tomography (CT). A refinement of the heuristic CT-based SPR prediction using a state-of-the-art Hounsfield look-up table (HLUT) is proposed, which incorporates patient SPR information obtained from dual-energy CT (DECT) in a retrospective patient-cohort analysis.

Material And Methods: SPR datasets of 25 brain-tumor patients, 25 prostate-cancer patients, and three nonsmall cell lung-cancer (NSCLC) patients were calculated from clinical DECT scans with the comprehensively validated DirectSPR approach.

Status and innovations in pre-treatment CT imaging for proton therapy.

Pre-treatment CT imaging is a topic of growing importance in particle therapy. Improvements in the accuracy of stopping-power prediction are demanded to allow for a dose conformality that is not inferior to state-of-the-art image-guided photon therapy. Although range uncertainty has been kept practically constant over the last decades, recent technological and methodological developments, like the clinical application of dual-energy CT, have been introduced or arise at least on the horizon to improve the accuracy and precision of range prediction.

Dual-Energy Computed Tomography to Assess Intra- and Inter-Patient Tissue Variability for Proton Treatment Planning of Patients With Brain Tumor.

Purpose: Range prediction in particle therapy is associated with an uncertainty originating from calculating the stopping-power ratio (SPR) based on x-ray computed tomography (CT). Here, we assessed the intra- and inter-patient variability of tissue properties in patients with primary brain tumor using dual-energy CT (DECT) and quantified its influence on current SPR prediction.

Methods And Materials: For 102 patients' DECT scans, SPR distributions were derived from a patient-specific DECT-based approach (DirectSPR).

Dual-energy CT for automatic organs-at-risk segmentation in brain-tumor patients using a multi-atlas and deep-learning approach.

In radiotherapy, computed tomography (CT) datasets are mostly used for radiation treatment planning to achieve a high-conformal tumor coverage while optimally sparing healthy tissue surrounding the tumor, referred to as organs-at-risk (OARs). Based on CT scan and/or magnetic resonance images, OARs have to be manually delineated by clinicians, which is one of the most time-consuming tasks in the clinical workflow. Recent multi-atlas (MA) or deep-learning (DL) based methods aim to improve the clinical routine by an automatic segmentation of OARs on a CT dataset.

Clinical Feasibility of Single-Source Dual-spiral 4D Dual-Energy CT for Proton Treatment Planning Within the Thoracic Region.

Purpose: Single-source dual-spiral dual-energy computed tomography (DECT) provides additional patient information but is prone to motion between the 2 consecutively acquired computed tomography (CT) scans. Here, the clinical applicability of dual-spiral time-resolved DECT (4D-DECT) for proton treatment planning within the thoracic region was evaluated.

Methods And Materials: Dual-spiral 4D-DECT scans of 3 patients with lung cancer were acquired.

Inter-centre variability of CT-based stopping-power prediction in particle therapy: Survey-based evaluation.

Background And Purpose: Stopping-power ratios (SPRs) are used in particle therapy to calculate particle range in patients. The heuristic CT-to-SPR conversion (Hounsfield Look-Up-Table, HLUT), needed for treatment planning, depends on CT-scan and reconstruction parameters as well as the specific HLUT definition. To assess inter-centre differences in these parameters, we performed a survey-based qualitative evaluation, as a first step towards better standardisation of CT-based SPR derivation.

On the equivalence of image-based dual-energy CT methods for the determination of electron density and effective atomic number in radiotherapy.

Dual-energy computed tomography enables the determination of relative electron density and effective atomic number. As this can increase accuracy in radiotherapy treatment planning, a substantial number of algorithms for the determination of the two quantities has been suggested - most of them based on reconstructed CT images. We show that many of these methods share a common theoretical framework.

Experimental verification of stopping-power prediction from single- and dual-energy computed tomography in biological tissues.

An experimental setup for consecutive measurement of ion and x-ray absorption in tissue or other materials is introduced. With this setup using a 3D-printed sample container, the reference stopping-power ratio (SPR) of materials can be measured with an uncertainty of below 0.1%.

Sensitivity of a prompt-gamma slit-camera to detect range shifts for proton treatment verification.

Background And Purpose: A prompt-gamma imaging (PGI) slit-camera was recently applied successfully in clinical proton treatments using pencil beam scanning (PBS) and double scattering (DS). However, its full capability under clinical conditions has still to be systematically evaluated. Here, the performance of the slit-camera is systematically assessed in well-defined error scenarios using realistic treatment deliveries to an anthropomorphic head phantom.

Evaluation of Stopping-Power Prediction by Dual- and Single-Energy Computed Tomography in an Anthropomorphic Ground-Truth Phantom.

Purpose: To determine the accuracy of particle range prediction for proton and heavier ion radiation therapy based on dual-energy computed tomography (DECT) in a realistic inhomogeneous geometry and to compare it with the state-of-the-art clinical approach.

Methods And Materials: A 3-dimensional ground-truth map of stopping-power ratios (SPRs) was created for an anthropomorphic head phantom by assigning measured SPR values to segmented structures in a high-resolution CT scan. This reference map was validated independently comparing proton transmission measurements with Monte Carlo transport simulations.