Evaluation of ion recombination and polarity effect on photon depth dose measurements using mini- and micro-ion chamber.

Purpose: To investigate the effect of ion recombination ( ) and polarity ( ) correction factors on percentage depth dose (PDD) curves for three ion chambers, using flat and flattening filter free (FFF) beams, across different broad field sizes. A method to assess these effects and their corresponding corrections is proposed.

Methods: and were evaluated following the IAEA TRS-398 protocol for three ion chambers: PTW Semiflex-3D-31021, PinPoint-3D-31022, and Semiflex-31010.

Machine learning and lean six sigma for targeted patient-specific quality assurance of volumetric modulated arc therapy plans.

Background And Purpose: Radiotherapy plans with excessive complexity exhibit higher uncertainties and worse patient-specific quality assurance (PSQA) results, while the workload of measurement-based PSQA can impact the efficiency of the radiotherapy workflow. Machine Learning (ML) and Lean Six Sigma, a process optimization method, were implemented to adopt a targeted PSQA approach, aiming to reduce workload, risk of failures, and monitor complexity.

Materials And Methods: Lean Six Sigma was applied using DMAIC (define, measure, analyze, improve, and control) steps.

Deep learning-based optimization of field geometry for total marrow irradiation delivered with volumetric modulated arc therapy.

Background: Total marrow (lymphoid) irradiation (TMI/TMLI) is a radiotherapy treatment used to selectively target the bone marrow and lymph nodes in conditioning regimens for allogeneic hematopoietic stem cell transplantation. A complex field geometry is needed to cover the large planning target volume (PTV) of TMI/TMLI with volumetric modulated arc therapy (VMAT). Five isocenters and ten overlapping fields are needed for the upper body, while, for patients with large anatomical conformation, two specific isocenters are placed on the arms.

Deep learning and atlas-based models to streamline the segmentation workflow of total marrow and lymphoid irradiation.

Purpose: To improve the workflow of total marrow and lymphoid irradiation (TMLI) by enhancing the delineation of organs at risk (OARs) and clinical target volume (CTV) using deep learning (DL) and atlas-based (AB) segmentation models.

Materials And Methods: Ninety-five TMLI plans optimized in our institute were analyzed. Two commercial DL software were tested for segmenting 18 OARs.

Long term update on toxicity and survival of a phase II trial of linac-based stereotactic body radiation therapy for low-intermediate risk prostate cancer.

Background: In 2016 we published a phase II study exploring safety and efficacy of Stereotactic Body Radiation Therapy (SBRT) delivered with Volumetric Modulated Arc Therapy (VMAT) and Flattening Filter Free (FFF) beams techniques in prostate cancer (PC) patients. We present herein the updated results on late toxicity and long-term survival.

Methods: Patients enrolled in the study had a biopsy-confirmed localized PC and the features of a low- or intermediate-risk disease (National Comprehensive Network Criteria).