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Radiomics involves the extraction of information from medical images that are not visible to the human eye. There is evidence that these features can be used for treatment stratification and outcome prediction. However, there is much discussion about the reproducibility of results between different studies. This paper studies the reproducibility of CT texture features used in radiomics, comparing two feature extraction implementations, namely the MATLAB toolkit and Pyradiomics, when applied to independent datasets of CT scans of patients: (i) the open access RIDER dataset containing a set of repeat CT scans taken 15 min apart for 31 patients (RIDER Scan 1 and Scan 2, respectively) treated for lung cancer; and (ii) the open access HN1 dataset containing 137 patients treated for head and neck cancer. Gross tumor volume (GTV), manually outlined by an experienced observer available on both datasets, was used. The 43 common radiomics features available in MATLAB and Pyradiomics were calculated using two intensity-level quantization methods with and without an intensity threshold. Cases were ranked for each feature for all combinations of quantization parameters, and the Spearman’s rank coefficient, rs, calculated. Reproducibility was defined when a highly correlated feature in the RIDER dataset also correlated highly in the HN1 dataset, and vice versa. A total of 29 out of the 43 reported stable features were found to be highly reproducible between MATLAB and Pyradiomics implementations, having a consistently high correlation in rank ordering for RIDER Scan 1 and RIDER Scan 2 (rs > 0.8). 18/43 reported features were common in the RIDER and HN1 datasets, suggesting they may be agnostic to disease site. Useful radiomics features should be selected based on reproducibility. This study identified a set of features that meet this requirement and validated the methodology for evaluating reproducibility between datasets.

Background: Whole-breast radiotherapy (WBRT) is the standard treatment for breast cancer following breast-conserving surgery. Evidence shows that tumour recurrences occur near the original cancer: the tumour bed. New treatment developments include increasing dose to the tumour bed during WBRT (synchronous integrated boost) and irradiating only the region around the tumour bed, for patients at high and low risk of tumour recurrence, respectively. Currently, standard imaging uses bony anatomy to ensure accurate delivery of WBRT. It is debatable whether or not more targeted treatments such as synchronous integrated boost and partial-breast radiotherapy require image-guided radiotherapy (IGRT) focusing on implanted tumour bed clips (clip-based IGRT). Objectives: Primary – to compare accuracy of patient set-up using standard imaging compared with clip-based IGRT. Secondary – comparison of imaging techniques using (1) tumour bed radiotherapy safety margins, (2) volume of breast tissue irradiated around tumour bed, (3) estimated breast toxicity following development of a normal tissue control probability model and (4) time taken. Design: Multicentre observational study embedded within a national randomised trial: IMPORT-HIGH (Intensity Modulated and Partial Organ Radiotherapy – HIGHer-risk patient group) testing synchronous integrated boost and using clip-based IGRT. Setting: Five radiotherapy departments, participating in IMPORT-HIGH. Participants: Two-hundred and eighteen patients receiving breast radiotherapy within IMPORT-HIGH. Interventions: There was no direct intervention in patients’ treatment. Experimental and control intervention were clip-based IGRT and standard imaging, respectively. IMPORT-HIGH patients received clip-based IGRT as routine; standard imaging data were obtained from clip-based IGRT images. Main outcome measures: Difference in (1) set-up errors, (2) safety margins, (3) volume of breast tissue irradiated, (4) breast toxicity and (5) time, between clip-based IGRT and standard imaging. Results: The primary outcome of overall mean difference in clip-based IGRT and standard imaging using daily set-up errors was 2–2.6 mm (p

A technique is presented to allow a breathing pattern to be obtained from any multi-slice CT, cone-beam or other series of sequential chest x-ray image sets. The technique requires no extra signals to be recorded and does not need specific external or internal oscillating structures to be visible in the field of view. The breathing pattern is instead acquired from analysing the variation in pixel values between projection images. For cone-beam image sets, slowly varying changes, due to an angular attenuation dependence, must be corrected before the breathing trace analysis can begin. All the results of the new technique were checked visually and were in good agreement. If the studied image set could be analysed using the existing 'Amsterdam shroud' technique, then the results it provided were also used for comparison. In cases that allowed comparison by both techniques, the results were in agreement. The new technique was also shown to provide a usable signal when applied to cardiac motion. [ABSTRACT FROM AUTHOR]

Proton imaging is a promising technology for proton radiotherapy as it can be used for: (1) direct sampling of the tissue stopping power, (2) input information for multi-modality RSP reconstruction, (3) gold-standard calibration against concurrent techniques, (4) tracking motion and (5) pre-treatment positioning. However, no end-to-end characterization of the image quality (signal-to-noise ratio and spatial resolution, blurring uncertainty) against the dose has been done. This work aims to establish a model relating these characteristics and to describe their relationship with proton energy and object size. The imaging noise originates from two processes: the Coulomb scattering with the nucleus, producing a path deviation, and the energy loss straggling with electrons. The noise is found to increases with thickness crossed and, independently, decreases with decreasing energy. The scattering noise is dominant around high-gradient edge whereas the straggling noise is maximal in homogeneous regions. Image quality metrics are found to behave oppositely against energy: lower energy minimizes both the noise and the spatial resolution, with the optimal energy choice depending on the application and location in the imaged object. In conclusion, the model presented will help define an optimal usage of proton imaging to reach the promised application of this technology and establish a fair comparison with other imaging techniques. [ABSTRACT FROM AUTHOR]

Radiotherapy treatment plans using dynamic couch rotation during volumetric modulated arc therapy (DCR-VMAT) reduce the dose to organs at risk (OARs) compared to coplanar VMAT, while maintaining the dose to the planning target volume (PTV). This paper seeks to validate this finding with measurements. DCR-VMAT treatment plans were produced for five patients with primary brain tumours and delivered using a commercial linear accelerator (linac). Dosimetric accuracy was assessed using point dose and radiochromic film measurements. Linac-recorded mechanical errors were assessed by extracting deviations from log files for multi-leaf collimator (MLC), couch, and gantry positions every 20 ms. Dose distributions, reconstructed from every fifth log file sample, were calculated and used to determine deviations from the treatment plans. Median (range) treatment delivery times were 125 s (123–133 s) for DCR-VMAT, compared to 78 s (64–130 s) for coplanar VMAT. Absolute point doses were 0.8% (0.6%–1.7%) higher than prediction. For coronal and sagittal films, respectively, 99.2% (96.7%–100%) and 98.1% (92.9%–99.0%) of pixels above a 20% low dose threshold reported gamma  <1 for 3% and 3 mm criteria. Log file analysis showed similar gantry rotation root-mean-square error (RMSE) for VMAT and DCR-VMAT. Couch rotation RMSE for DCR-VMAT was 0.091° (0.086–0.102°). For delivered dose reconstructions, 100% of pixels above a 5% low dose threshold reported gamma  <1 for 2% and 2 mm criteria in all cases. DCR-VMAT, for the primary brain tumour cases studied, can be delivered accurately using a commercial linac. [ABSTRACT FROM AUTHOR]