Development of a national deep learning-based auto-segmentation model for the heart on clinical delineations from the DBCG RT nation cohort.

Background: This study aimed at investigating the feasibility of developing a deep learning-based auto-segmentation model for the heart trained on clinical delineations.

Material And Methods: This study included two different datasets. The first dataset contained clinical heart delineations from the DBCG RT Nation study (1,561 patients).

Atlas-based auto-segmentation for delineating the heart and cardiac substructures in breast cancer radiation therapy.

Background: This study aimed to develop and validate an automatic multi-atlas segmentation method for delineating the heart and substructures in breast cancer radiation therapy (RT).

Material And Methods: The atlas database consisted of non-contrast-enhanced planning CT scans from 42 breast cancer patients, each with one manual delineation of the heart and 22 cardiac substructures. Half of the patients were scanned during free-breathing, the rest were scanned during a deep inspiration breath-hold.

Personal innovative approach in radiation therapy of lung cancer- functional lung avoidance SPECT-guided (ASPECT) radiation therapy: a study protocol for phase II randomised double-blind clinical trial.

Background: Radiation therapy (RT) plays a key role in curative-intent treatment for locally advanced lung cancer. Radiation induced pulmonary toxicity can be significant for some patients and becomes a limiting factor for radiation dose, suitability for treatment, as well as post treatment quality of life and suitability for the newly introduced adjuvant immunotherapy. Modern RT techniques aim to minimise the radiation dose to the lungs, without accounting for regional distribution of lung function.

Density calibrated cone beam CT as a tool for adaptive radiotherapy.

Background: Visual inspections of anatomical changes observed on daily cone-beam CT (CBCT) images are often used as triggers for radiotherapy plan adaptation to avoid unacceptable dose levels to the target or OARs. Direct CBCT dose calculations would improve the ability to adapt only those plans where dosimetric changes are observed. This study investigates the accuracy of dose calculations on CBCTs.

Strategies for Motion Robust Proton Therapy With Pencil Beam Scanning for Esophageal Cancer.

Purpose: Proton therapy of esophageal cancer is superior to photon radiation therapy in terms of normal tissue sparing. However, respiratory motion and anatomical changes may compromise target dose coverage owing to density changes, geometric misses, and interplay effects. Here we investigate the combined effect on clinical target volume (CTV) coverage and compare proton therapy with intensity modulated radiation therapy (IMRT).

Variation in current prescription practice of stereotactic body radiotherapy for peripherally located early stage non-small cell lung cancer: Recommendations for prescribing and recording according to the ACROP guideline and ICRU report 91.

Background And Purpose: In 2017 the ACROP guideline on SBRT for peripherally located early stage NSCLC was published. Later that year ICRU-91 about prescribing, recording and reporting was published. The purpose of this study is to quantify the current variation in prescription practice in the institutions that contributed to the ACROP guideline and to establish the link between the ACROP and ICRU-91 recommendations.

Validation of a robust strategy for proton spot scanning for oesophageal cancer in the presence of anatomical changes.

SFUD strategies with one or two posterior proton beams and three target coverage strategies are compared with IMRT and tested for robustness towards anatomical changes by recalculation on surveillance CTs during treatment. We find posterior beam SFUD combining PTV coverage with robust optimization increases robustness towards anatomical changes compared to IMRT.

Difference in target definition using three different methods to include respiratory motion in radiotherapy of lung cancer.

Introduction: Minimizing the planning target volume (PTV) while ensuring sufficient target coverage during the entire respiratory cycle is essential for free-breathing radiotherapy of lung cancer. Different methods are used to incorporate the respiratory motion into the PTV.

Material And Methods: Fifteen patients were analyzed.

Dosimetric assessment of an Atlas based automated segmentation for loco-regional radiation therapy of early breast cancer in the Skagen Trial 1: A multi-institutional study.

The effect of Atlas-based automated segmentation (ABAS) on dose volume histogram (DVH) parameters compared to manual segmentation (MS) in loco-regional radiotherapy (RT) of early breast cancer was investigated in patients included in the Skagen Trial 1. This analysis supports implementation of ABAS in clinical practice and multi-institutional trials.

Internal and external validation of an ESTRO delineation guideline - dependent automated segmentation tool for loco-regional radiation therapy of early breast cancer.

Background And Purpose: To internally and externally validate an atlas based automated segmentation (ABAS) in loco-regional radiation therapy of breast cancer.

Materials And Methods: Structures of 60 patients delineated according to the ESTRO consensus guideline were included in four categorized multi-atlas libraries using MIM Maestro™ software. These libraries were used for auto-segmentation in two different patient groups (50 patients from the local institution and 40 patients from other institutions).

Dosimetric evaluation of anatomical changes during treatment to identify criteria for adaptive radiotherapy in oesophageal cancer patients.

Background: Some oesophageal cancer patients undergoing chemotherapy and concomitant radiotherapy (chemoRT) show large interfractional anatomical changes during treatment. These changes may modify the dose delivered to the target and organs at risk (OARs). The aim of the presenwt study was to investigate the dosimetric consequences of anatomical changes during treatment to obtain criteria for an adaptive RT decision support system.

Clinical validation of a 4D-CT based method for lung ventilation measurement in phantoms and patients.

Background: Lung cancer patients referred to radiotherapy (RT) often present with regional lung function deficits, and it is therefore of interest to image their lung function prior to treatment. In this study a method was developed that uses a deformable image registration (DIR) between the peak-inhale and peak-exhale phases of a thoracic four-dimensional computed tomography (4D-CT) scan to extract ventilation information. The method calculates the displacement vector fields (DVFs) resulting from the DIR using the Jacobian map approach in order to extract information regarding regional lung volume change.