Longitudinal Image Data for Outcome Modeling.

In oncology, medical imaging is crucial for diagnosis, treatment planning and therapy execution. Treatment responses can be complex and varied and are known to involve factors of treatment, patient characteristics and tumor microenvironment. Longitudinal image analysis is able to track temporal changes, aiding in disease monitoring, treatment evaluation, and outcome prediction.

Improving shared decision making for lung cancer treatment by developing and validating an open-source web based patient decision aid for stage I-II non-small cell lung cancer.

The aim of this study was to develop and evaluate a proof-of-concept open-source individualized Patient Decision Aid (iPDA) with a group of patients, physicians, and computer scientists. The iPDA was developed based on the International Patient Decision Aid Standards (IPDAS). A previously published questionnaire was adapted and used to test the user-friendliness and content of the iPDA.

Intra- and inter-fraction breath-hold variations and margins for radiotherapy of abdominal targets.

Radiotherapy in expiration breath-hold (EBH) has the potential to reduce treatment volumes of abdominal targets compared to an internal target volume concept in free-breathing. The reproducibility of EBH and required safety margins were investigated to quantify this volumetric benefit. Pre- and post-treatment diaphragm position difference and the positioning variability were determined on computed tomography.

Effect of 0.35 T and 1.5 T magnetic fields on superficial dose in MR-guided radiotherapy of laryngeal cancer.

Background: Treatment of head and neck cancer on linear accelerators with on-board magnetic resonance imaging (MR-linac) might be beneficial to reduce side effects and increase accuracy. For many head and neck cancer patients, dose coverage of the often superficially located planning target volumes (PTVs) is required. This study examines the impact of the electron return effect (ERE) on the surface dose in MR-guided radiotherapy (MRgRT) compared to conventional radiotherapy.

Interfractional dose accumulation for MR-guided liver SBRT: Variation among algorithms is highly patient- and fraction-dependent.

Background And Purpose: Daily plan adaptations could take the dose delivered in previous fractions into account. Due to high dose delivered per fraction, low number of fractions, steep dose gradients, and large interfractional organ deformations, this might be particularly important for liver SBRT. This study investigates inter-algorithm variation of interfractional dose accumulation for MR-guided liver SBRT.

Predicting Adverse Radiation Effects in Brain Tumors After Stereotactic Radiotherapy With Deep Learning and Handcrafted Radiomics.

Introduction: There is a cumulative risk of 20-40% of developing brain metastases (BM) in solid cancers. Stereotactic radiotherapy (SRT) enables the application of high focal doses of radiation to a volume and is often used for BM treatment. However, SRT can cause adverse radiation effects (ARE), such as radiation necrosis, which sometimes cause irreversible damage to the brain.

Automated detection and segmentation of non-small cell lung cancer computed tomography images.

Detection and segmentation of abnormalities on medical images is highly important for patient management including diagnosis, radiotherapy, response evaluation, as well as for quantitative image research. We present a fully automated pipeline for the detection and volumetric segmentation of non-small cell lung cancer (NSCLC) developed and validated on 1328 thoracic CT scans from 8 institutions. Along with quantitative performance detailed by image slice thickness, tumor size, image interpretation difficulty, and tumor location, we report an in-silico prospective clinical trial, where we show that the proposed method is faster and more reproducible compared to the experts.

Comprehensive summary and retrospective evaluation of prognostic scores for patients with newly diagnosed brain metastases treated with upfront radiosurgery in a modern patient collective.

Background: Numerous prognostic scores (PS) for patients with brain metastases (BM) have been developed. Recently, PS based on laboratory parameters were introduced to better predict overall survival (OS). A comprehensive comparison of the wide range of scores in a modern patient collective is still missing.

Gating has a negligible impact on dose delivered in MRI-guided online adaptive radiotherapy of prostate cancer.

Background And Purpose: MR-guided radiotherapy (MRgRT) allows real-time beam-gating to compensate for intra-fractional target position variations. This study investigates the dosimetric impact of beam-gating and the impact of PTV margin on prostate coverage for prostate cancer patients treated with online-adaptive MRgRT.

Materials And Methods: 20 consecutive prostate cancer patients were treated with online-adaptive MRgRT SBRT with 36.

Evaluation of the prognostic value of the ESTRO EORTC classification of oligometastatic disease in patients treated with stereotactic body radiotherapy: A retrospective single center study.

Purpose: To explore the prognostic value of the oligometastatic disease (OMD) states as proposed by the European Society for Radiotherapy and Oncology (ESTRO) European Organisation for Research and Treatment of Cancer (EORTC) classification system.

Materials And Methods: This retrospective single-institution study included patients with 1-5 extracranial metastases from any solid malignancy treated with SBRT to all metastases. OMD states were defined according to the ESTRO EORTC classification.

Dental extraction, intensity-modulated radiotherapy of head and neck cancer, and osteoradionecrosis : A systematic review and meta-analysis.

Objective: To seek evidence for osteoradionecrosis (ORN) after dental extractions before or after intensity-modulated radiotherapy (IMRT) for head and neck cancer (HNC).

Methods: Medline/PubMed, Embase, and Cochrane Library were searched from 2000 until 2020. Articles on HNC patients treated with IMRT and dental extractions were analyzed by two independent reviewers.

A 2.5D convolutional neural network for HPV prediction in advanced oropharyngeal cancer.

Background: Infection with human papilloma virus (HPV) is one of the most relevant prognostic factors in advanced oropharyngeal cancer (OPC) treatment. In this study we aimed to assess the diagnostic accuracy of a deep learning-based method for HPV status prediction in computed tomography (CT) images of advanced OPC.

Method: An internal dataset and three public collections were employed (internal: n = 151, HNC1: n = 451; HNC2: n = 80; HNC3: n = 110).

Single-isocenter versus multiple-isocenters for multiple lung metastases: Evaluation of lung dose.

Background And Purpose: A potential challenge in single-isocenter multi-lesion lung stereotactic body radiotherapy (SBRT) is that patient positioning is not based on each lesion individually, but on the average position of all lesions. This may lead to larger margins compared to treating with one isocenter per lesion, but increases workflow efficiency. The aim of this study was to investigate whether a single-isocenter technique leads to increased normal lung dose compared to a conventional multiple-isocenters technique.

MR-Guided Adaptive Radiotherapy for Head and Neck Cancer: Prospective Evaluation of Migration and Anatomical Changes of the Major Salivary Glands.

The aim of this study was to quantify anatomical changes of parotids and submandibular glands and evaluate potential dosimetric advantages during weekly adaptive MR-guided radiotherapy (MRgRT) for the definitive treatment of head and neck cancer (HNC). The data and plans of 12 patients treated with bilateral intensity-modulated radiotherapy for HNC using MR-linac, with weekly offline adaptations, were prospectively evaluated. The positional and volumetric changes of the salivary glands were analyzed by manual segmentation in weekly MRI images and the dosimetric impact of these anatomical changes on the adapted treatment plans was assessed.

Quantification of the spatial distribution of primary tumors in the lung to develop new prognostic biomarkers for locally advanced NSCLC.

The anatomical location and extent of primary lung tumors have shown prognostic value for overall survival (OS). However, its manual assessment is prone to interobserver variability. This study aims to use data driven identification of image characteristics for OS in locally advanced non-small cell lung cancer (NSCLC) patients.

Machine learning for grading and prognosis of esophageal dysplasia using mass spectrometry and histological imaging.

Background: Barrett's esophagus (BE) is a precursor lesion of esophageal adenocarcinoma and may progress from non-dysplastic through low-grade dysplasia (LGD) to high-grade dysplasia (HGD) and cancer. Grading BE is of crucial prognostic value and is currently based on the subjective evaluation of biopsies. This study aims to investigate the potential of machine learning (ML) using spatially resolved molecular data from mass spectrometry imaging (MSI) and histological data from microscopic hematoxylin and eosin (H&E)-stained imaging for computer-aided diagnosis and prognosis of BE.

Margin calculation for multiple lung metastases treated with single-isocenter SBRT.

Background And Purpose: A single-isocenter stereotactic body radiotherapy (SBRT) approach for multiple lung metastases has the potential to lower cumulative patient dose and reduce overall treatment time. However, the magnitude of inter-lesion position variation is currently unknown and not incorporated in margin calculations. The aim of this study was to quantify inter-lesion position variation and calculate safety margins for single-isocenter lung SBRT.

A Prospectively Validated Prognostic Model for Patients with Locally Advanced Squamous Cell Carcinoma of the Head and Neck Based on Radiomics of Computed Tomography Images.

Background: Locoregionally advanced head and neck squamous cell carcinoma (HNSCC) patients have high relapse and mortality rates. Imaging-based decision support may improve outcomes by optimising personalised treatment, and support patient risk stratification. We propose a multifactorial prognostic model including radiomics features to improve risk stratification for advanced HNSCC, compared to TNM eighth edition, the gold standard.

Systematic Review on the Association of Radiomics with Tumor Biological Endpoints.

Radiomics supposes an alternative non-invasive tumor characterization tool, which has experienced increased interest with the advent of more powerful computers and more sophisticated machine learning algorithms. Nonetheless, the incorporation of radiomics in cancer clinical-decision support systems still necessitates a thorough analysis of its relationship with tumor biology. Herein, we present a systematic review focusing on the clinical evidence of radiomics as a surrogate method for tumor molecular profile characterization.

Comparison of beam segment versus full plan re-optimization in daily magnetic resonance imaging-guided online-adaptive radiotherapy.

The optimal approach for magnetic resonance imaging-guided online adaptive radiotherapy is currently unknown and needs to consider patient on-couch time constraints. The aim of this study was to compare two different plan optimization approaches. The comparison was performed in 238 clinically applied online-adapted treatment plans from 55 patients, in which the approach of re-optimization was selected based on the physician's choice.

Head and neck radiotherapy on the MR linac: a multicenter planning challenge amongst MRIdian platform users.

Purpose: Purpose of this study is to evaluate plan quality on the MRIdian (Viewray Inc., Oakwood Village, OH, USA) system for head and neck cancer (HNC) through comparison of planning approaches of several centers.

Methods: A total of 14 planners using the MRIdian planning system participated in this treatment challenge, centrally organized by ViewRay, for one contoured case of oropharyngeal carcinoma with standard constraints for organs at risk (OAR).

MR-Guided Radiotherapy for Head and Neck Cancer: Current Developments, Perspectives, and Challenges.

Based on the development of new hybrid machines consisting of an MRI and a linear accelerator, magnetic resonance image guided radiotherapy (MRgRT) has revolutionized the field of adaptive treatment in recent years. Although an increasing number of studies have been published, investigating technical and clinical aspects of this technique for various indications, utilizations of MRgRT for adaptive treatment of head and neck cancer (HNC) remains in its infancy. Yet, the possible benefits of this novel technology for HNC patients, allowing for better soft-tissue delineation, intra- and interfractional treatment monitoring and more frequent plan adaptations appear more than obvious.

Distance to isocenter is not associated with an increased risk for local failure in LINAC-based single-isocenter SRS or SRT for multiple brain metastases.

Purpose: To evaluate the impact of the distance between treatment isocenter and brain metastases on local failure in patients treated with a frameless linear-accelerator-based single-isocenter volumetric modulated arc (VMAT) SRS/SRT for multiple brain metastases.

Methods And Materials: Patients treated with SRT for brain metastases (BM) between April 2014 and May 2019 were included in this retrospective study. BM treated with a single-isocenter multiple-target (SIMT) SRT were evaluated for local recurrence-free intervals in dependency to their distance to the treatment isocenter.

Cochlea sparing optimized radiotherapy for nasopharyngeal carcinoma.

Background: Definitive chemoradiotherapy (CRT) is standard of care for nasopharyngeal carcinoma. Due to the tumor localization and concomitant platinum-based chemotherapy, hearing impairment is a frequent complication, without defined dose-threshold. In this study, we aimed to achieve the maximum possible cochleae sparing.