Multi-institutional generalizability of a plan complexity machine learning model for predicting pre-treatment quality assurance results in radiotherapy.

Background And Purpose: Treatment plans in radiotherapy are subject to measurement-based pre-treatment verifications. In this study, plan complexity metrics (PCMs) were calculated per beam and used as input features to develop a predictive model. The aim of this study was to determine the robustness against differences in machine type and institutional-specific quality assurance (QA).

A geometry and dose-volume based performance monitoring of artificial intelligence models in radiotherapy treatment planning for prostate cancer.

Background And Purpose: Clinical Artificial Intelligence (AI) implementations lack ground-truth when applied on real-world data. This study investigated how combined geometrical and dose-volume metrics can be used as performance monitoring tools to detect clinically relevant candidates for model retraining.

Materials And Methods: Fifty patients were analyzed for both AI-segmentation and planning.

Quality assurance and safety of hippocampal avoidance prophylactic cranial irradiation in the multicenter randomized phase III trial (NCT01780675).

Objective: NCT01780675, a multicenter randomized phase III trial of prophylactic cranial irradiation (PCI) versus PCI with hippocampal sparing in small cell lung cancer (SCLC) investigated neurocognitive decline and safety. As part of quality assurance, we evaluated if hippocampal avoidance (HA)-PCI was performed according to the NCT01780675 trial protocol instructions, and performed a safety analysis to study the incidence and location of brain metastases for patients treated with HA-PCI.

Methods: This retrospective analysis evaluated the quality of the irradiation given in the randomized controlled trial (RCT) comparing SCLC patients receiving PCI with or without hippocampal avoidance, using intensity modulated radiotherapy (IMRT) or volumetric modulated arc therapy (VMAT).

Machine learning-based treatment couch parameter prediction in support of surface guided radiation therapy.

Purpose: A fully independent, machine learning-based automatic treatment couch parameters prediction was developed to support surface guided radiation therapy (SGRT)-based patient positioning protocols. Additionally, this approach also acts as a quality assurance tool for patient positioning.

Materials/methods: Setup data of 183 patients, divided into four different groups based on used setup devices, was used to calculate the difference between the predicted and the acquired treatment couch value.

Machine learning-based detection of aberrant deep learning segmentations of target and organs at risk for prostate radiotherapy using a secondary segmentation algorithm.

The output of a deep learning (DL) auto-segmentation application should be reviewed, corrected if needed and approved before being used clinically. This verification procedure is labour-intensive, time-consuming and user-dependent, which potentially leads to significant errors with impact on the overall treatment quality. Additionally, when the time needed to correct auto-segmentations approaches the time to delineate target and organs at risk from scratch, the usability of the DL model can be questioned.

Probabilistic dose prediction using mixture density networks for automated radiation therapy treatment planning.

We demonstrate the application of mixture density networks (MDNs) in the context of automated radiation therapy treatment planning. It is shown that an MDN can produce good predictions of dose distributions as well as reflect uncertain decision making associated with inherently conflicting clinical tradeoffs, in contrast to deterministic methods previously investigated in the literature. A two-component Gaussian MDN is trained on a set of treatment plans for postoperative prostate patients with varying extents to which rectum dose sparing was prioritized over target coverage.

Outcome and toxicity of hypofractionated image-guided SABR for spinal oligometastases.

Background: To investigate progression free survival (PFS), local control (LC) and overall survival (OS) outcomes for patients treated with spine hypofractionated stereotactic ablative radiotherapy (SABR) and to evaluate possible predictors of rapid progression in view of a correct patient selection for this potentially curative SABR.

Materials And Methods: A cohort of 59 patients with spinal metastases were treated with SABR. Patient selection criteria were the following: histologically proven diagnosis of a solid tumor, a World Health Organization (WHO) score ≤ 2, life expectancy > 6 months, Spinal Instability Neoplastic Score (SINS) ≤ 12 points and presenting with radically treated oligometastatic disease (≤5 lesions) or stable polymetastatic disease with an oligoprogressive lesion.

A novel procedure for determining the optimal MLC configuration parameters in treatment planning systems based on measurements with a Farmer chamber.

Modelling of the multi-leaf collimator (MLC) in treatment planning systems (TPS) is crucial for the dose calculation accuracy of intensity-modulated radiation therapy plans. However, no standardised methodology for their configuration exists to date. In this study we present a method that separates the effect of each dosimetric characteristic of the MLC, offering comprehensive equations for the determination of the configuration parameters used in the TPS model.

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.

A feasibility study on adaptive F-FDG-PET-guided radiotherapy for recurrent and second primary head and neck cancer in the previously irradiated territory.

Purpose: To evaluate feasibility, disease control, survival, and toxicity after adaptive F-fluorodeoxyglucose (FDG) positron emisson tomography (PET) guided radiotherapy in patients with recurrent and second primary head and neck squamous cell carcinoma.

Methods: A prospective trial investigated the feasibility of adaptive intensity modulated radiotherapy (IMRT) ± concomitant cetuximab in 10 patients. The primary endpoint was achieving a 2-year survival free of grade >3 toxicity in ≥30% of patients.

Fast Helical Tomotherapy in a head and neck cancer planning study: is time priceless?

Background: The last few years, in radiotherapy there has been a growing focus on speed of treatment delivery (largely driven by economical and commercial interests). This study investigates the influence of treatment time on plan quality for helical tomotherapy (HT), using delivery times with Volumetric Modulated Arc Therapy (VMAT; Rapid Arc [RA]) as reference.

Methods: In a previous study, double arc RA (Eclipse) and standard HT plans (TomoHD™) were created for five oropharyngeal cancer patients and reported according to ICRU 83 guidelines.

Evaluation of the optimal combinations of modulation factor and pitch for Helical TomoTherapy plans made with TomoEdge using Pareto optimal fronts.

Background: Modulation factor (MF) and pitch have an impact on Helical TomoTherapy (HT) plan quality and HT users mostly use vendor-recommended settings. This study analyses the effect of these two parameters on both plan quality and treatment time for plans made with TomoEdge planning software by using the concept of Pareto optimal fronts.

Methods: More than 450 plans with different combinations of pitch [0.

Helical tomotherapy in head and neck cancer: a European single-center experience.

Background: We report on a retrospective analysis of 147 patients with early and locoregionally advanced squamous cell head and neck cancer (SCCHN) treated with helical tomotherapy (HT).

Patients And Methods: Included were patients with SCCHN of the oral cavity (OC), oropharynx (OP), hypopharynx (HP), or larynx (L) consecutively treated in one radiotherapy center in 2008 and 2009. The prescribed HT dose was 60-66 Gy in the postoperative setting (group A) and 66-70 Gy when given as primary treatment (group B).

The potential of helical tomotherapy in the treatment of head and neck cancer.

A decade after its first introduction into the clinic, little is known about the clinical impact of helical tomotherapy (HT) on head and neck cancer (HNC) treatment. Therefore, we analyzed the basics of this technique and reviewed the literature regarding HT's potential benefit in HNC. The past two decades have been characterized by a huge technological evolution in photon beam radiotherapy (RT).