Impact of annotation imperfections and auto-curation for deep learning-based organ-at-risk segmentation.

Background And Purpose: Segmentation imperfections (noise) in radiotherapy organ-at-risk segmentation naturally arise from specialist experience and image quality. Using clinical contours can result in sub-optimal convolutional neural network (CNN) training and performance, but manual curation is costly. We address the impact of simulated and clinical segmentation noise on CNN parotid gland (PG) segmentation performance and provide proof-of-concept for an easily implemented auto-curation countermeasure.

Clinical Implementation of Cone Beam Computed Tomography-Guided Online Adaptive Radiation Therapy in Whole Breast Irradiation.

Purpose: In postoperative breast irradiation, changes in the breast contour and arm positioning can result in patient positioning errors and offline replanning. This can lead to increased treatment burden and strain on departmental logistics because of the need for additional cone beam computed tomography (CBCT) images or even a new radiation therapy treatment plan (TP). Online daily adaptive radiation therapy (oART) could provide a solution to these challenges.

Technical note: Dosimetry and FLASH potential of UHDR proton PBS for small lung tumors: Bragg-peak-based delivery versus transmission beam and IMPT.

Background: High-energy transmission beams (TBs) are currently the main delivery method for proton pencil beam scanning ultrahigh dose-rate (UHDR) FLASH radiotherapy. TBs place the Bragg-peaks behind the target, outside the patient, making delivery practical and achievement of high dose-rates more likely. However, they lead to higher integral dose compared to conventional intensity-modulated proton therapy (IMPT), in which Bragg-peaks are placed within the tumor.

Efficacy and safety of SBRT for spine metastases: A systematic review and meta-analysis for preparation of an ESTRO practice guideline.

Background And Purpose: Advances in characterizing cancer biology and the growing availability of novel targeted agents and immune therapeutics have significantly changed the prognosis of many patients with metastatic disease. Palliative radiotherapy needs to adapt to these developments. In this study, we summarize the available evidence for stereotactic body radiotherapy (SBRT) in the treatment of spinal metastases.

ESTRO clinical practice guideline: Stereotactic body radiotherapy for spine metastases.

Background And Purpose: Recent progress in diagnostics and treatment of metastatic cancer patients have improved survival substantially. These developments also affect local therapies, with treatment aims shifting from short-term palliation to long-term symptom or disease control. There is consequently a need to better define the value of stereotactic body radiotherapy (SBRT) for the treatment of spinal metastases.

Dose distribution prediction for head-and-neck cancer radiotherapy using a generative adversarial network: influence of input data.

Purpose: A three-dimensional deep generative adversarial network (GAN) was used to predict dose distributions for locally advanced head and neck cancer radiotherapy. Given the labor- and time-intensive nature of manual planning target volume (PTV) and organ-at-risk (OAR) segmentation, we investigated whether dose distributions could be predicted without the need for fully segmented datasets.

Materials And Methods: GANs were trained/validated/tested using 320/30/35 previously segmented CT datasets and treatment plans.

The NCS code of practice for the quality assurance of treatment planning systems (NCS-35).

A subcommittee of the Netherlands Commission on Radiation Dosimetry (NCS) was initiated in 2018 with the task to update and extend a previous publication (NCS-15) on the quality assurance of treatment planning systems (TPS) (Bruinvis2005). The field of treatment planning has changed considerably since 2005. Whereas the focus of the previous report was more on the technical aspects of the TPS, the scope of this report is broader with a focus on a department wide implementation of the TPS.

Spine Stereotactic Body Radiation Therapy Without Immobilization: Detailed Analysis of Intrafraction Motion Using High-Frequency kV Imaging During Irradiation.

Purpose: Spine stereotactic body radiation therapy (SBRT) requires high positioning accuracy and a stable patient to maximize target coverage and reduce excessive irradiation to organs at risk. Positional verification during spine SBRT delivery helps to ensure accurate positioning for all patients. We report our experience with noninvasive 3-dimensional target position monitoring during volumetric modulated arc therapy of spine metastases in nonimmobilized patients positioned using only a thin mattress and simple arm and knee supports.

Deep learning-based markerless lung tumor tracking in stereotactic radiotherapy using Siamese networks.

Background: Radiotherapy (RT) is involved in about 50% of all cancer patients, making it a very important treatment modality. The most common type of RT is external beam RT, which consists of delivering the radiation to the tumor from outside the body. One novel treatment delivery method is volumetric modulated arc therapy (VMAT), where the gantry continuously rotates around the patient during the radiation delivery.

Impact of imperfection in medical imaging data on deep learning-based segmentation performance: An experimental study using synthesized data.

Background: Clinical data used to train deep learning models are often not clean data. They can contain imperfections in both the imaging data and the corresponding segmentations.

Purpose: This study investigates the influence of data imperfections on the performance of deep learning models for parotid gland segmentation.

Same-day adaptive palliative radiotherapy without prior CT simulation: Early outcomes in the FAST-METS study.

Background And Purpose: Standard palliative radiotherapy workflows involve waiting times or multiple clinic visits. We developed and implemented a rapid palliative workflow using diagnostic imaging (dCT) for pre-planning, with subsequent on-couch target and plan adaptation based on a synthetic computed tomography (CT) obtained from cone-beam CT imaging (CBCT).

Materials And Methods: Patients with painful bone metastases and recent diagnostic imaging were eligible for inclusion in this prospective, ethics-approved study.

Evaluation of a workflow for cone-beam CT-guided online adaptive palliative radiotherapy planned using diagnostic CT scans.

Purpose: Single-visit radiotherapy (RT) is beneficial for patients requiring pain control and can limit interruptions to systemic treatments. However, the requirement for a dedicated planning CT (pCT)-scan can result in treatment delays. We developed a workflow involving preplanning on available diagnostic CT (dCT) imaging, followed by online plan adaption using a cone-beam CT (CBCT)-scan prior to RT-delivery, in order to account for any changes in anatomy and target position.

Deep Learning for Automated Elective Lymph Node Level Segmentation for Head and Neck Cancer Radiotherapy.

Depending on the clinical situation, different combinations of lymph node (LN) levels define the elective LN target volume in head-and-neck cancer (HNC) radiotherapy. The accurate auto-contouring of individual LN levels could reduce the burden and variability of manual segmentation and be used regardless of the primary tumor location. We evaluated three deep learning approaches for the segmenting individual LN levels I−V, which were manually contoured on CT scans from 70 HNC patients.

Influence of Beam Angle on Normal Tissue Complication Probability of Knowledge-Based Head and Neck Cancer Proton Planning.

Knowledge-based planning solutions have brought significant improvements in treatment planning. However, the performance of a proton-specific knowledge-based planning model in creating knowledge-based plans (KBPs) with beam angles differing from those used to train the model remains unexplored. We used a previously validated RapidPlanPT model and scripting to create nine KBPs, one with default and eight with altered beam angles, for 10 recent oropharynx cancer patients.

Single-fraction 34 Gy Lung Stereotactic Body Radiation Therapy Using Proton Transmission Beams: FLASH-dose Calculations and the Influence of Different Dose-rate Methods and Dose/Dose-rate Thresholds.

Purpose: Research suggests that in addition to the dose-rate, a dose threshold is also important for the reduction in normal tissue toxicity with similar tumor control after ultrahigh dose-rate radiation therapy (UHDR-RT). In this analysis we aimed to identify factors that might limit the ability to achieve this "FLASH"-effect in a scenario attractive for UHDR-RT (high fractional beam dose, small target, few organs-at-risk): single-fraction 34 Gy lung stereotactic body radiation therapy.

Methods And Materials: Clinical volumetric-modulated arc therapy (VMAT) plans, intensity modulated proton therapy (IMPT) plans and transmission beam (TB) plans were compared for 6 small and 1 large lung lesion.

Fast, Automated, Knowledge-Based Treatment Planning for Selecting Patients for Proton Therapy Based on Normal Tissue Complication Probabilities.

Purpose: Selecting patients who will benefit from proton therapy is laborious and subjective. We demonstrate a novel automated solution for creating high-quality knowledge-based plans (KBPs) using proton and photon beams to identify patients for proton treatment based on their normal tissue complication probabilities (NTCP).

Methods And Materials: Two previously validated RapidPlan PT models for locally advanced head and neck cancer were used in combination with scripting to automatically create proton and photon KBPs for 72 patients with recent oropharynx cancer.

Determining Planning Priorities for SABR for Oligometastatic Disease: A Secondary Analysis of the SABR-COMET Phase II Randomized Trial.

Purpose: SABR may improve survival in patients with oligometastases, but for some lesions, safe delivery of SABR may require a reduction in delivered dose or target coverage. This study assessed the association between target coverage compromise and oncologic and survival outcomes.

Methods And Materials: Patients with a controlled primary malignancy and 1 to 5 oligometastases were randomized (1:2) between standard of care (SOC) treatment and SOC plus SABR.

The markerless lung target tracking AAPM Grand Challenge (MATCH) results.

Purpose: Lung stereotactic ablative body radiotherapy (SABR) is a radiation therapy success story with level 1 evidence demonstrating its efficacy. To provide real-time respiratory motion management for lung SABR, several commercial and preclinical markerless lung target tracking (MLTT) approaches have been developed. However, these approaches have yet to be benchmarked using a common measurement methodology.

Relationship between Treatment Plan Dosimetry, Toxicity, and Survival following Intensity-Modulated Radiotherapy, with or without Chemotherapy, for Stage III Inoperable Non-Small Cell Lung Cancer.

Concurrent chemoradiotherapy (cCRT) is the preferred treatment for stage III NSCLC because surgery containing multimodality treatment is often not appropriate. Alternatives, often for less fit patients, include sequential CRT and RT alone. Many reports describing the relationship between overall survival (OS), toxicity, and dosimetry are based on clinical trials, with strict criteria for patient selection.

The Impact of the Availability of Immunotherapy on Patterns of Care in Stage III NSCLC: A Dutch Multicenter Analysis.

Introduction: Treatment patterns in stage III NSCLC can vary considerably between countries. The PACIFIC trial reported improvements in progression-free and overall survival with adjuvant durvalumab after concurrent chemoradiotherapy (CCRT). We studied treatment decision-making by three Dutch regional thoracic multidisciplinary tumor boards between 2015 and 2019, to identify changes in practice when adjuvant durvalumab became available.

Markerless 3D tumor tracking during single-fraction free-breathing 10MV flattening-filter-free stereotactic lung radiotherapy.

Background And Purpose: Positional verification during single fraction lung SBRT could increase confidence and reduce the chance of geographic miss. As planar 2DkV imaging during VMAT irradiation is already available on current linear accelerators, markerless tracking based on these images could offer widely available and low-cost verification. We evaluated treatment delivery data and template matching and triangulation for 3D-positional verification during free-breathing, single fraction (34 Gy), 10 MV flattening-filter-free VMAT lung SBRT.

National Protocol for Model-Based Selection for Proton Therapy in Head and Neck Cancer.

In the Netherlands, the model-based approach is used to identify patients with head and neck cancer who may benefit most from proton therapy in terms of prevention of late radiation-induced side effects in comparison with photon therapy. To this purpose, a National Indication Protocol Proton therapy for Head and Neck Cancer patients (NIPP-HNC) was developed, which has been approved by the health care authorities. When patients qualify according to the guidelines of the NIPP-HNC, proton therapy is fully reimbursed.