Cone beam CT dose optimisation: A review and expert consensus by the 2022 ESTRO Physics Workshop IGRT working group.

Image guided radiotherapy (IGRT) using kilovoltage cone-beam CT (CBCT) has become an indispensable tool to ensure the geometric accuracy of radiotherapy treatment delivery. Although significant technical advances have been made in reducing imaging dose, the repeated imaging procedures can still accumulate significant dose to healthy tissues. Despite the widespread use, we still lack clear guidance for optimisation and widely accepted frameworks for evaluating the quality and suitability of CBCT imaging protocols.

3D-Printed Organ-Realistic Phantoms to Verify Quantitative SPECT/CT Accuracy for 177Lu-PSMA-617 Treatment Planning.

Accurate patient-specific dosimetry is essential for optimizing radiopharmaceutical therapy (RPT), but current tools lack validation in clinically realistic conditions. This work aimed to develop a workflow for designing and fabricating patient-derived, organ-realistic RPT phantoms and evaluate their feasibility for commissioning patient-specific RPT radioactivity quantification. We used computed tomographic (CT) and magnetic resonance (MR) imaging of representative patients, computer-aided design, and in-house 3D printing technology to design and fabricate anthropomorphic kidney and parotid phantoms with realistic organ spacing, anatomically correct orientation, and surrounding tissue heterogeneities.

Optimization Processes of Clinical Chelation-Based Radiopharmaceuticals for Pathway-Directed Targeted Radionuclide Therapy in Oncology.

Targeted radionuclide therapy (TRT) for internal pathway-directed treatment is a game changer for precision medicine. TRT improves tumor control while minimizing damage to healthy tissue and extends the survival for patients with cancer. The application of theranostic-paired TRT along with cellular phenotype and genotype correlative analysis has the potential for malignant disease management.

CT- and MR-based image-based data mining are consistent in the brain.

Purpose: Image-based data mining (IBDM) is a voxel-based analysis technique to investigate dose-response. Most often, IBDM uses radiotherapy planning CTs because of their broad accessibility, however, it was unknown whether CT provided sufficient soft tissue contrast for brain IBDM. This study evaluates whether MR-based IBDM improves upon CT-based IBDM for studies of children with brain tumours.

Machine intelligence for radiation science: summary of the Radiation Research Society 67th annual meeting symposium.

The era of high-throughput techniques created big data in the medical field and research disciplines. Machine intelligence (MI) approaches can overcome critical limitations on how those large-scale data sets are processed, analyzed, and interpreted. The 67 Annual Meeting of the Radiation Research Society featured a symposium on MI approaches to highlight recent advancements in the radiation sciences and their clinical applications.

Treatment-planning approaches to intensity modulated proton therapy and the impact on dose-weighted linear energy transfer.

Purpose: We quantified the effect of various forward-based treatment-planning strategies in proton therapy on dose-weighted linear energy transfer (LETd). By maintaining the dosimetric quality at a clinically acceptable level, we aimed to evaluate the differences in LETd among various treatment-planning approaches and their practicality in minimizing biologic uncertainties associated with LETd.

Method: Eight treatment-planning strategies that are achievable in commercial treatment-planning systems were applied on a cylindrical water phantom and four pediatric brain tumor cases.

Image-based data mining applies to data collected from children.

Purpose: Image-based data mining (IBDM) is a novel voxel-based method for analyzing radiation dose responses that has been successfully applied in adult data. Because anatomic variability and side effects of interest differ for children compared to adults, we investigated the feasibility of IBDM for pediatric analyses.

Methods: We tested IBDM with CT images and dose distributions collected from 167 children (aged 10 months to 20 years) who received proton radiotherapy for primary brain tumors.

Pre- and Posttherapy Risk Factors for Vasculopathy in Pediatric Patients With Craniopharyngioma Treated With Surgery and Proton Radiation Therapy.

Purpose: Vasculopathy (VAS) is a significant complication associated with radiation therapy in patients treated for brain tumors. We studied the type, location, severity, timing, and resolution of VAS in children with craniopharyngioma treated with proton radiation therapy (PRT) and evaluated predictors of stenosis (STN) using a novel patient and imaging-based modeling approach.

Methods And Materials: Children with craniopharyngioma (n = 94) were treated with 54 Gy relative biological effectiveness PRT in a clinical trial, NCT01419067.

Acknowledging and overcoming barriers to entry into radiation science for women.

Purpose: Radiation science is a unique field that brings together various disciplines to understand nature, develop new technologies, and cure diseases. Our field is a prime example of advancement through a diverse pool of competencies. Similarly, studies show that the power of diversity requires proportionate representation of sex and gender, minorities, or other groups.

Proton therapy delivery method affects dose-averaged linear energy transfer in patients.

The dosimetric advantages of proton therapy have led to its rapid proliferation in recent decades. This has been accompanied by a shift in technology from older units that deliver protons by passive scattering (PS) to newer units that increasingly use pencil-beam scanning (PBS). The biologic effectiveness of proton physical dose purportedly rises with increasing dose-weighted average linear energy transfer (LET).

Generalized approach for radiotherapy treatment planning by optimizing projected health outcome: preliminary results for prostate radiotherapy patients.

Research in cancer care increasingly focuses on survivorship issues, e.g. managing disease- and treatment-related morbidity and mortality occurring during and after treatment.

Justification and optimization of radiation exposures: a new framework to aggregate arbitrary detriments and benefits.

Myriad radiation effects, including benefits and detriments, complicate justifying and optimizing radiation exposures. The purpose of this study was to develop a comprehensive conceptual framework and corresponding quantitative methods to aggregate the detriments and benefits of radiation exposures to individuals, groups, and populations. In this study, concepts from the ICRP for low dose were integrated with clinical techniques focused on high dose to develop a comprehensive figure of merit (FOM) that takes into account arbitrary host- and exposure-related factors, endpoints, and time points.

Automation of Monte Carlo-based treatment plan verification for proton therapy.

Purpose: Independent calculations of proton therapy plans are an important quality control procedure in treatment planning. When using custom Monte Carlo (MC) models of the beamline, deploying the calculations can be laborious, time consuming, and require in-depth knowledge of the computational environment. We developed an automated framework to remove these barriers and integrate our MC model into the clinical workflow.

Method to quickly and accurately calculate absorbed dose from therapeutic and stray photon exposures throughout the entire body in individual patients.

Purpose: Photon radiotherapy techniques typically devote considerable attention to limiting the exposure of healthy tissues outside of the target volume. Numerous studies have shown, however, that commercial treatment planning systems (TPSs) significantly underestimate the absorbed dose outside of the treatment field. The purpose of this study was to test the feasibility of quickly and accurately calculating the total absorbed dose to the whole body from photon radiotherapy in individual patients.

A physics-based analytical model of absorbed dose from primary, leakage, and scattered photons from megavoltage radiotherapy with MLCs.

A burgeoning population of cancer survivors is at risk of late health effects following radiation therapy including second cancers, with the majority of these cancers occurring outside of the treatment volume of the primary cancer. Commercial radiotherapy treatment planning systems underestimate the out-of-field dose. Previous analytical models of out-of-field dose have assumed radial symmetry and/or approximated the dimensions of collimators as semi-infinite planes.

An objective method to evaluate radiation dose distributions varying by three orders of magnitude.

Purpose: Modern radiotherapy practices typically report the absorbed dose (D) within the 5% relative isodose volume (i.e., the therapeutic dose region) to an accuracy of 3%-5%.

A descriptive and broadly applicable model of therapeutic and stray absorbed dose from 6 to 25 MV photon beams.

Purpose: To develop a simple model of therapeutic and stray absorbed dose for a variety of treatment machines and techniques without relying on proprietary machine-specific parameters.

Methods: Dosimetry measurements conducted in this study and from the literature were used to develop an analytical model of absorbed dose from a variety of treatment machines and techniques in the 6 to 25 MV interval. A modified one-dimensional gamma-index analysis was performed to evaluate dosimetric accuracy of the model on an independent dataset consisting of measured dose profiles from seven treatment units spanning four manufacturers.