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..

A framework for medical physics compensation in an academic department.

Compensation is a key component of career satisfaction and professional growth. A new compensation model was developed to provide a framework for career growth and a compensation ladder for medical physicists with clinical responsibilities in an academic radiation oncology department. The goals for the new model were: (1) create a market competitive plan to support recruitment and retention of top physics talent, (2) incentivize clinical effort, innovation, citizenship/professional service, and academic achievement, (3) provide compensation growth opportunities separate from medical school promotions, and (4) create consistent, transparent, and fair metrics applicable to all clinical physicists in the department.

Validation of dual-energy CT-based composition analysis using fresh animal tissues and composition-optimized tissue equivalent samples.

Proton therapy allows for highly conformal dose deposition, but is sensitive to range uncertainties. Several approaches currently under development measure composition-dependent secondary radiation to monitor the delivered proton range. To fully utilize these methods, an estimate of the elemental composition of the patient's tissue is often needed.

Diffusion tensor transformation for personalizing target volumes in radiation therapy.

Diffusion tensor imaging (DTI) is used in tumor growth models to provide information on the infiltration pathways of tumor cells into the surrounding brain tissue. When a patient-specific DTI is not available, a template image such as a DTI atlas can be transformed to the patient anatomy using image registration. This study investigates a model, the invariance under coordinate transform (ICT), that transforms diffusion tensors from a template image to the patient image, based on the principle that the tumor growth process can be mapped, at any point in time, between the images using the same transformation function that we use to map the anatomy.

Integrating muscle fiber orientation from visible human data into radiotherapy target volumes.

A major challenge in treatment of tumors near skeletal muscle is defining the target volume for suspected tumor invasion into the muscle. This study develops a framework that generates radiation target volumes with muscle fiber orientation directly integrated into their definition. The framework is applied to nineteen sacral tumor patients with suspected infiltration into surrounding muscles.

A reference-point-method-based online proton treatment plan re-optimization strategy and a novel solution to planning constraint infeasibility problem.

. Propose a highly automated treatment plan re-optimization strategy suitable for online adaptive proton therapy. The strategy includes a rapid re-optimization method that generates quality replans and a novel solution that efficiently addresses the planning constraint infeasibility issue that can significantly prolong the re-optimization process.

Embedding machine learning based toxicity models within radiotherapy treatment plan optimization.

This study addresses radiation-induced toxicity (RIT) challenges in radiotherapy (RT) by developing a personalized treatment planning framework. It leverages patient-specific data and dosimetric information to create an optimization model that limits adverse side effects using constraints learned from historical data.The study uses the optimization with constraint learning (OCL) framework, incorporating patient-specific factors into the optimization process.

The influence of anisotropy on the clinical target volume of brain tumor patients.

Current radiotherapy guidelines for glioma target volume definition recommend a uniform margin expansion from the gross tumor volume (GTV) to the clinical target volume (CTV), assuming uniform infiltration in the invaded brain tissue. However, glioma cells migrate preferentially along white matter tracts, suggesting that white matter directionality should be considered in an anisotropic CTV expansion. We investigate two models of anisotropic CTV expansion and evaluate their clinical feasibility.

Validation of an MR-based multimodal method for molecular composition and proton stopping power ratio determination using animal tissues and tissue-mimicking phantoms.

. Range uncertainty in proton therapy is an important factor limiting clinical effectiveness. Magnetic resonance imaging (MRI) can measure voxel-wise molecular composition and, when combined with kilovoltage CT (kVCT), accurately determine mean ionization potential (), electron density, and stopping power ratio (SPR).

Automated Segmentation of Sacral Chordoma and Surrounding Muscles Using Deep Learning Ensemble.

Purpose: The manual segmentation of organ structures in radiation oncology treatment planning is a time-consuming and highly skilled task, particularly when treating rare tumors like sacral chordomas. This study evaluates the performance of automated deep learning (DL) models in accurately segmenting the gross tumor volume (GTV) and surrounding muscle structures of sacral chordomas.

Methods And Materials: An expert radiation oncologist contoured 5 muscle structures (gluteus maximus, gluteus medius, gluteus minimus, paraspinal, piriformis) and sacral chordoma GTV on computed tomography images from 48 patients.

Simultaneous T -weighted real-time MRI of two orthogonal slices.

Purpose: MR guidance is used during therapy to detect and compensate for lesion motion. T -weighted MRI often has a superior lesion contrast in comparison to T -weighted real-time imaging. The purpose of this work was to design a fast T -weighted sequence capable of simultaneously acquiring two orthogonal slices, enabling real-time tracking of lesions.

Global democratisation of proton radiotherapy.

Proton radiotherapy is an advanced treatment option compared with conventional x-ray treatment, delivering much lower doses of radiation to healthy tissues surrounding the tumour. However, proton therapy is currently not widely available. In this Review, we summarise the evolution of proton therapy to date, together with the benefits to patients and society.

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.

Online adaptive planning methods for intensity-modulated radiotherapy.

Online adaptive radiation therapy aims at adapting a patient's treatment plan to their current anatomy to account for inter-fraction variations before daily treatment delivery. As this process needs to be accomplished while the patient is immobilized on the treatment couch, it requires time-efficient adaptive planning methods to generate a quality daily treatment plan rapidly. The conventional planning methods do not meet the time requirement of online adaptive radiation therapy because they often involve excessive human intervention, significantly prolonging the planning phase.

Recurrence analysis of glioblastoma cases based on distance and dose information.

Background And Purpose: Radiation therapy for glioblastoma (GBM) typically involves large target volumes. The aim of this study was to examine the recurrence pattern of GBM following modern radiochemotherapy according to EORTC guidelines and provide dose and distance information for the choice of optimal target volume margins.

Materials And Methods: In this study, the recurrences of 97 GBM patients, treated with radiochemotherapy from 2013 to 2017 at the Medical Center- University of Freiburg, Germany were analysed.

Our journeys through the fascinating world of proton radiation therapy.

The purpose of this article is to share the excitement of the science of proton therapy, told by two physicists, who started their career in this area at different times. The authors' journey spans the evolution of proton therapy over the past 30 years, taking the reader from the time when it was an extremely exotic treatment modality until its more common use today. Over this time period, the authors' research and development aimed at an improved understanding of the physical benefits of intensity-modulated proton therapy and arc therapy, treatment planning and optimization to take proton-specific uncertainties into account, and imaging to measure the proton range in the patient.

Exploring trade-offs in treatment planning for brain tumor cases with a probabilistic definition of the clinical target volume.

Purpose: This study demonstrates how a novel probabilistic clinical target volume (CTV) concept-the clinical target distribution (CTD)-can be used to navigate the trade-off between target coverage and organ sparing with a semi-interactive treatment planning approach.

Methods: Two probabilistic treatment planning methods are presented that use tumor probabilities to balance tumor control with organ-at-risk (OAR) sparing. The first method explores OAR dose reduction by systematically discarding of CTD voxels with an unfavorable dose-to-probability ratio from the minimum dose coverage objective.

Combined clinical and research training in medical physics in a multi-institutional setting: 13-year experience of Harvard Medical Physics Residency Program.

Purpose: This manuscript describes the structure, management and outcomes of a multi-institutional clinical and research medical physics residency program (Harvard Medical Physics Residency Program, or HMPRP) to provide potentially useful information to the centers considering a multi-institutional approach for their training programs.

Methods: Data from the program documents and public records was used to describe HMPRP and obtain statistics about participating faculty, enrolled residents, and graduates. Challenges associated with forming and managing a multi-institutional program and developed solutions for effective coordination between several clinical centers are described.

Validation of prompt gamma-ray spectroscopy for proton range verification in tissue-mimicking and porcine samples.

. Proton therapy of cancer improves dose conformality to the target and sparing of surrounding healthy tissues compared to conventional photon treatments. However, proton therapy's advantage could be even larger if proton range uncertainties were reduced.

Personalized mid-course FDG-PET based adaptive treatment planning for non-small cell lung cancer using machine learning and optimization.

. Traditional radiotherapy (RT) treatment planning of non-small cell lung cancer (NSCLC) relies on population-wide estimates of organ tolerance to minimize excess toxicity. The goal of this study is to develop a personalized treatment planning based on patient-specific lung radiosensitivity, by combining machine learning and optimization.

Feasibility study of clinical target volume definition for soft-tissue sarcoma using muscle fiber orientations derived from diffusion tensor imaging.

Soft-tissue sarcoma spreads preferentially along muscle fibers. We explore the utility of deriving muscle fiber orientations from diffusion tensor MRI (DT-MRI) for defining the boundary of the clinical target volume (CTV) in muscle tissue.We recruited eight healthy volunteers to acquire MR images of the left and right thigh.

Modeling the propagation of tumor fronts with shortest path and diffusion models-implications for the definition of the clinical target volume.

The overarching objective is to make the definition of the clinical target volume (CTV) in radiation oncology less subjective and more scientifically based. The specific objective of this study is to investigate similarities and differences between two methods that model tumor spread beyond the visible gross tumor volume (GTV): (1) the shortest path model, which is the standard method of adding a geometric GTV-CTV margin, and (2) the reaction-diffusion model.These two models to capture the invisible tumor 'fire front' are defined and compared in mathematical terms.

Range uncertainty reductions in proton therapy may lead to the feasibility of novel beam arrangements which improve organ-at-risk sparing.

Purpose: In proton therapy, dose distributions are currently often conformed to organs at risk (OARs) using the less sharp dose fall-off at the lateral beam edge to reduce the effects of uncertainties in the in vivo proton range. However, range uncertainty reductions may make greater use of the sharper dose fall-off at the distal beam edge feasible, potentially improving OAR sparing. We quantified the benefits of such novel beam arrangements.