Clin Transl Radiat Oncol
September 2025
We report the case of exceptional response of massive liver metastases of a patient with synchronous lung adenocarcinoma and small cell lung cancer following lattice radiotherapy (L-RT). After a single irradiation of 16 Gy to 1 % of the metastatic liver burden, the patient reported improved abdominal symptoms within a week. Within two weeks liver volume decreased by 50 %, and liver enzyme levels stabilized or improved.
View Article and Find Full Text PDFBackground: Non-coplanarity and mixed beam modality could be combined to further enhance dosimetric treatment plan quality. We introduce dynamic mixed beam arc therapy (DYMBARC) as an innovative technique that combines non-coplanar photon and electron arcs, dynamic gantry and collimator rotations, and intensity modulation with photon multileaf collimator (MLC). However, finding favorable beam directions for DYMBARC is challenging due to the large solution space, machine component constraints, and optimization parameters, posing a highly non-convex optimization problem.
View Article and Find Full Text PDFPhys Med Biol
September 2024
Dynamic trajectory radiotherapy (DTRT) and dynamic mixed-beam arc therapy (DYMBARC) exploit non-coplanarity and, for DYMBARC, simultaneously optimized photon and electron beams. Margin concepts to account for set-up uncertainties during delivery are ill-defined for electron fields. We develop robust optimization for DTRT&DYMBARC and compare dosimetric plan quality and robustness for both techniques and both optimization strategies for four cases.
View Article and Find Full Text PDFPhys Imaging Radiat Oncol
April 2024
Background And Purpose: Dynamic trajectory radiotherapy (DTRT) has been shown to improve healthy tissue sparing compared to volumetric arc therapy (VMAT). This study aimed to assess and compare the robustness of DTRT and VMAT treatment-plans for head and neck (H&N) cancer to patient-setup (PS) and machine-positioning uncertainties.
Materials And Methods: The robustness of DTRT and VMAT plans previously created for 46 H&N cases, prescribed 50-70 Gy to 95 % of the planning-target-volume, was assessed.
We compared dynamic trajectory radiotherapy (DTRT) to state-of-the-art volumetric modulated arc therapy (VMAT) for 46 head and neck cancer cases. DTRT had lower dose to salivary glands and swallowing structure, resulting in lower predicted xerostomia and dysphagia compared to VMAT. DTRT is deliverable on C-arm linacs with high dosimetric accuracy.
View Article and Find Full Text PDFBackground: Non-coplanar techniques have shown to improve the achievable dose distribution compared to standard coplanar techniques for multiple treatment sites but finding optimal beam directions is challenging. Dynamic collimator trajectory radiotherapy (colli-DTRT) is a new intensity modulated radiotherapy technique that uses non-coplanar partial arcs and dynamic collimator rotation.
Purpose: To solve the beam angle optimization (BAO) problem for colli-DTRT and non-coplanar VMAT (NC-VMAT) by determining the table-angle and the gantry-angle ranges of the partial arcs through iterative 4π fluence map optimization (FMO) and beam direction elimination.
. Electron arcs in mixed-beam radiotherapy (Arc-MBRT) consisting of intensity-modulated electron arcs with dynamic gantry rotation potentially reduce the delivery time compared to mixed-beam radiotherapy containing electron beams with static gantry angle (Static-MBRT). This study aims to develop and investigate a treatment planning process (TPP) for photon multileaf collimator (pMLC) based Arc-MBRT.
View Article and Find Full Text PDFNon-coplanar radiotherapy treatment techniques on C-arm linear accelerators have the potential to reduce dose to organs-at-risk in comparison with coplanar treatment techniques. Accurately predicting possible collisions between gantry, table and patient during treatment planning is needed to ensure patient safety. We offer a freely available collision prediction tool using Blender, a free and open-source 3D computer graphics software toolset.
View Article and Find Full Text PDFBackground: Dynamic trajectory radiotherapy (DTRT) extends state-of-the-art volumetric modulated arc therapy (VMAT) by dynamic table and collimator rotations during beam-on. The effects of intrafraction motion during DTRT delivery are unknown, especially regarding the possible interplay between patient and machine motion with additional dynamic axes.
Purpose: To experimentally assess the technical feasibility and quantify the mechanical and dosimetric accuracy of respiratory gating during DTRT delivery.
Background: Dynamic trajectory radiotherapy (DTRT) extends volumetric modulated arc therapy (VMAT) with dynamic table and collimator rotation during beam-on. The aim of the study is to establish DTRT path-finding strategies, demonstrate deliverability and dosimetric accuracy and compare DTRT to state-of-the-art VMAT for common head and neck (HN) cancer cases.
Methods: A publicly available library of seven HN cases was created on an anthropomorphic phantom with all relevant organs-at-risk (OARs) delineated.
Background And Purpose: To assess the feasibility of postoperative stereotactic body radiation therapy (SBRT) for patients with hybrid implants consisting of carbon fiber reinforced polyetheretherketone and titanium (CFP-T) using CyberKnife.
Materials And Methods: All essential steps within a radiation therapy (RT) workflow were evaluated. First, the contouring process of target volumes and organs at risk (OAR) was done for patients with CFP-T implants.
Background: Evaluating plan robustness is a key step in radiotherapy.
Purpose: To develop a flexible Monte Carlo (MC)-based robustness calculation and evaluation tool to assess and quantify dosimetric robustness of intensity-modulated radiotherapy (IMRT) treatment plans by exploring the impact of systematic and random uncertainties resulting from patient setup, patient anatomy changes, and mechanical limitations of machine components.
Methods: The robustness tool consists of two parts: the first part includes automated MC dose calculation of multiple user-defined uncertainty scenarios to populate a robustness space.