The Australian Magnetic Resonance Imaging (MRI) Linear Accelerator program (MRI linac) was a major research project that aimed to build and test a unique MRI linac prototype for cancer treatment. It aimed to improve radiotherapy anatomical targeting and explore physiological targeting. The purpose of this report is to summarise the development and achievements of the program so as to provide an example of a successful large-scale research project in Australian radiation oncology. The project involved six Australian universities and international collaborators. We developed and built a unique MRI linac configuration comprising a 1 T magnetic field and a 6 MV accelerator, with the beam delivered in line with B0 and the patient placed across B0 in the split between the two halves of the magnet. The broad research domains were personalised disease targeting, medical device innovation, and biodiscovery. Specific projects included Artificial Intelligence image enhancement, radiation dosimetry in high magnetic fields, MRI characterisation of cancer heterogeneity in human tumours, and animal and human studies. Over $27 million was obtained to support the program from competitive sources. The program published over 120 papers and supported 25 PhD completions. The learnings from the Australian MRI linac program are that Australia has world-class radiotherapy research in physics and engineering, that major projects need a lot of time and a lot of collaboration, and that large, novel radiotherapy projects can attract significant funding and produce significant results.

An understanding of the repeatability of imaging biomarkers is key to their implementation as clinical tools. In this study we calculate the repeatability and inter-correlation of radiomic features derived from quantitative MRI (qMRI) of Glioblastoma (GBM) patients and assess the effect of image standardisation methods on these factors. We analysed scan-rescan Diffusion Weighted MR Images (DWI) and Dynamic Contrast Enhanced MR Images (DCE) from 36 GBM patients obtained from The Cancer Imaging Archive (TCIA). These included 17 patients, from the QIN-GBM-Treatment-Response patient cohort, scanned post surgery and prior to chemo-radiation therapy and 19 patients, from the RIDER Neuro MRI patient cohort, scanned at diagnosis of tumour recurrence. For both patient cohorts, two sets of scans were taken 2-6 days apart. Each of these patient cohorts was analysed independently to determine if findings were consistent across different acquisition parameters. Parametric maps of Apparent Diffusion Coefficient (ADC) and Cerebral Blood Volume (CBV) were obtained from DWI and DCE data, respectively. Intensity normalisation and noise filtering were applied to the parametric maps in multiple permutations to give 7 distinct standardisation methods. Shape, first order and second order radiomic features for the parametric maps were calculated within the Gross Tumour Volume (GTV). The Intraclass Correlation Coefficient (ICC) was calculated between the feature value at each imaging timepoint. The ICC of first and second order features derived from images with each standardisation method was compared to the ICC of corresponding features derived from images without standardisation. Based on the average ICC of features derived from ADC images without image standardisation, first order features were the most repeatable in both patient cohorts. For ADC derived features in the QIN cohort, shape features were the second most repeatable followed by second order features. For ADC derived features in the RIDER cohort, second order features were the second most repeatable followed by shape features. In CBV images, shape features were the most repeatable followed by second order and then first order in both patient cohorts. No image standardisation method implemented in this study was found to significantly increase the repeatability of ADC-derived first or second order features. For first order CBV features z-score normalisation without noise filtering produced a significant improvement in feature repeatability in both patient cohorts. Radiomic feature repeatability is impacted by feature class. Image standardisation methods implemented in this study were not found to be effective at improving the repeatability of ADC-derived features and had limited utility for improving CBV derived features. Future radiomic studies should consider feature repeatability as an important factor in feature selection.

This study assesses the updated Monaco TPS virtual source model (VSM) 2.0, which removes multileaf collimator (MLC) and jaw characterization as editable factors from the MLC geometry section within Monaco. The focus is on the impact of changes to stereotactic radiotherapy (SRT) cases for spinal and intracranial treatments for two beam matched linear accelerators. A validated custom VSM 1.6 model optimized for SRT was compared with the Elekta Accelerated Go Live 6 MV flattening filter-free (FFF) and VSM 2.0. Evaluations included measured MLC characteristics with a high-resolution detector, measured output factors (OPF), ion chamber fields in the thorax phantom, and recalculations of clinically relevant SRT cases. VSM 2.0 improves MLC modelling. Ion chamber measurements for IAEA TD1583 measurements were found to be within expected tolerances. Gamma pass rates for two matched LINACs evidenced improvement at 1%, 1 mm and 10% threshold for single and multi-SRS brain and SABR Spine treatments. VSM 2.0 represents a meaningful advancement in beam modelling within a Monte Carlo-based TPS environment, offering improved dosimetric performance and operational simplicity. Commercially available detectors were used to demonstrate that VSM 2.0 enhances agility MLC modelling, supporting more precise SRT and SABR delivery for matched LINACs. Removing configurable dependencies from the beam model will result in more consistent high quality beam models, an improves workflows for commissioning of the Monaco TPS.

BACKGROUND:Diffusion-weighted imaging (DWI), a quantitative magnetic resonance imaging (qMRI) technique, has the potential to aid in disease characterization and treatment response monitoring. MR-Linacs (MRLs) enable simultaneous DWI acquisitions during radiotherapy, uniquely aiding in the collection of large-scale datasets for imaging biomarkers, such as the DWI-derived apparent diffusion coefficient (ADC), without additional patient burden. However, the limited data reporting on variability in MRL scanner performance characteristics, and a lack of established clinical trial quality assurance (QA) procedures, are barriers to this route for biomarker validation. PURPOSE:This study aims to quantify the accuracy, intra-scanner repeatability, and inter-scanner reproducibility of ADC measurements across three MRLs in Australia in both a phantom and in vivo. These measurements will inform the feasibility of carrying out prospective multi-center studies in Australia investigating ADC as a biomarker and form a core set of QA procedures and baselines to assess biomarker and sequence suitability. METHODS:An isotropic diffusion phantom (at 0°C) and one healthy volunteer were scanned on three Unity MRLs (Elekta AB, Stockholm, Sweden). Standardized (QIBA Diffusion Profile) and anatomy-specific DWI sequences, including sequences recommended by the MR-Linac Consortium Imaging Biomarker Working Group, were used to image the phantom and volunteer. ADC maps generated using the MRL scanner software (inline ADC) and diffusion-weighted (b-value) images were exported from the scanner console. The latter was used to generate ADC maps using commercial software (offline ADC) for a separate comparative analysis. Performance metrics were computed for each sequence, including a coefficient of variation to assess between-session intra-scanner repeatability (CVBS) and inter-scanner reproducibility (CV), for each phantom vial and contoured organ. Additionally, using the phantoms' known ADC vial values, a percentage bias (bias) was calculated to determine ADC accuracy. RESULTS:Phantom-based measurements for the standardized QIBA sequence had intra- and inter-scanner CV and bias well within recommended guideline (QIBA Diffusion Profile) tolerance limits of 2.2% and ±3.6%, respectively. All anatomy-specific phantom DWI sequences were also within these tolerances, except for the cervix sequence at one site which showed an average intra-scanner bias of +4.5%. Both accuracy and reproducibility for all sequences were worse for lower diffusivity vials measured in the phantom. Additionally, inline and offline ADC maps had high similarity with average percent differences of +0.2%. Volunteer-based results had worse reproducibility, with the average inter-scanner CV for the brain and pancreas sequences within 9.0%, however, reaching up to 27.1% for pelvis and abdomen sequences. CONCLUSIONS:This study demonstrated accuracy, intra-scanner repeatability, and inter-scanner reproducibility comparable to metrics reported in the literature, using both the phantom and volunteer datasets. The cervix sequence had the largest variability in both phantom and volunteer results and was recommended for further investigation. This study suggests that qMRI techniques utilizing DWI could be a viable option for future multi-centered patient-based studies utilizing Australian MRLs, with phantom-based quality assurance recommended alongside patient imaging.

BACKGROUND:Current studies assessing the reproducibility of radiomic features from gynaecological magnetic resonance images (MRIs) with interobserver contour variation (IOV) have been limited to ≤3 observers. This number of observers is insufficient to demonstrate the full range of IOV. PURPOSE:To assess the impact of observer numbers when investigating the reproducibility of gynaecological T2W-MRI radiomic features with IOV. METHODS:20 gynaecological cancer T2W-MRIs had the gross tumor volume (GTV), bladder, rectum, uterus, parametrium, and vagina delineated by 6 observers to create a 2-, 3-, 4-, 5-, and 6-observer dataset for each patient. IOV was assessed for each observer dataset and structure using the dice similarity coefficient, mean surface distance, and mean volume overlap variance. 107 radiomic features were extracted from each observer contour using PyRadiomics. The reproducibility of each radiomic feature was assessed for each observer dataset and structure using an intraclass correlation coefficient (ICC). An ICC estimate greater than 0.75 or 0.90 was classified as having good or excellent reproducibility, respectively. RESULTS:The GTV had a decrease in the number of features with good/excellent reproducibility when the number of observers in the dataset increased. Volumes with less IOV, such as the bladder and uterus, did not show this same trend, with consistent numbers of features with good/excellent reproducibility across all observer datasets. CONCLUSION:Determining the reproducibility of gynaecological T2W-MRI radiomic features to IOV with three or fewer observers is not adequate to display the full impact of IOV for GTVs.

PURPOSE:To evaluate the accuracy of different dosimeters and the treatment planning system (TPS) for assessing the skin dose due to the electron streaming effect (ESE) on a 1.5 T magnetic resonance (MR)-linac. METHOD:Skin dose due to the ESE on an MR-linac (Unity, Elekta) was investigated using a solid water phantom rotated 45° in the x-y plane (IEC61217) and centered at the isocenter. The phantom was irradiated with 1 × 1, 3 × 3, 5 × 5, 10 × 10, and 22 × 22 cm2 fields, gantry at 90°. Out-of-field doses (OFDs) deposited by electron streams generated at the entry and exit surface of the angled phantom were measured on the surface of solid water slabs placed ±20.0 cm from the isocenter along the x-direction. A high-resolution MOSkin™ detector served as a benchmark due to its shallower depth of measurement that matches the International Commission on Radiological Protection (ICRP) recommended depth for skin dose assessment (0.07 mm). MOSkin™ doses were compared to EBT3 film, OSLDs, a diamond detector, and the TPS where the experimental setup was modeled using two separate calculation parameters settings: a 0.1 cm dose grid with 0.2% statistical uncertainty (0.1 cm, 0.2%) and a 0.2 cm dose grid with 3.0% statistical uncertainty (0.2 cm, 3.0%). RESULTS:OSLD, film, the 0.1 cm, 0.2%, and 0.2 cm, 3.0% TPS ESE doses, underestimated skin doses measured by the MOSkin™ by as much as -75.3%, -7.0%, -24.7%, and -41.9%, respectively. Film results were most similar to MOSkin™ skin dose measurements. CONCLUSIONS:These results show that electron streams can deposit significant doses outside the primary field and that dosimeter choice and TPS calculation settings greatly influence the reported readings. Due to the steep dose gradient of the ESE, EBT3 film remains the choice for accurate skin dose assessment in this challenging environment.

This study aimed to identify potential anatomical variation triggers using magnetic resonance imaging for plan adaption of cervical cancer patients to ensure dose requirements were met over an external beam radiotherapy course. Magnetic resonance images (MRIs) acquired before and during treatment were rigidly registered to a pre-treatment computerised tomography (CT) image for 11 retrospective cervix cancer datasets. Target volumes (TVs) and organs at risk (OARs) were delineated on both MRIs and propagated onto the CT. Treatment plans were generated based on the pre-treatment contours and applied to the mid-treatment contours. Anatomical and dosimetric changes between each timepoint were assessed. The anatomical changes included the change in centroid position and volume size. Dosimetric changes included the V30Gy and V40Gy for the OARs, and V95%, V100%, D95% and D98% for the TVs. Correlation with dosimetric and anatomical changes were assessed to determine potential replan triggers. Changes in the bowel volume and position in the superior-inferior direction, and the high-risk CTV anterior posterior position were highly correlated with a change in dose to the bowel and target, respectively. Hence changes in bowel and high-risk CTV could be used as a potential replan triggers.

BackgroundImage guided radiotherapy (IGRT) with cone-beam computed tomography (CBCT) is limited by the sub-optimal soft-tissue contrast and spatial resolution of energy-integrating flat panel detectors (FPDs) which produce quasi-quantitative CT numbers. Spectral CT with high resolution photon-counting detectors (PCDs) could improve tumor delineation by enhancing the soft-tissue contrast, spatial resolution, dose-efficiency, and CT number accuracy.PurposeThis study presents the first linac-mounted PCD. On the journey to developing spectral cone-beam CT for IGRT, the planar image quality of a linac-mounted PCD is first fundamentally characterized and compared to an FPD in terms of the 2D spatial resolution, noise, and contrast.MethodsA Medipix3RX-based PCD was mounted to the kV FPD of an x-ray volume imaging (XVI) system on an Elekta linac and the PCD acquisition was synchronized with the pulsed kV source. The energy calibration of the Medipix3RX was determined with various radioisotope gamma emissions up to 60 keV. To compare the 2D spatial resolution and noise between the PCD and FPD, the pre-sampling modulation transfer function (MTF) and normalized noise power spectrum (NPS) were measured using an RQA5 spectrum and a fluoroscopy phantom was imaged to determine the limiting resolution of line pairs. Spectral planar images of phantom inserts containing two different concentrations of calcium (60 and 240 mg/cc) and iodine (5 and 15 mg/cc) were optimally energy weighted to maximize the contrast using tube voltages of 60, 80, 100, and 120 kV. To account for drifts in the sensor temperature, the PCD was dynamically translated in and out of the insert shadow during acquisitions to obtain flat field corrections per frame. The raw contrast of the resultant planar images was compared to the energy-integrating FPD.ResultsThe energy calibration of the Medipix3RX was observed to be linear up to 60 keV. The limiting resolution observed on the fluoroscopy phantom was 2 lp/mm for the FPD and 5 lp/mm for the PCD. The pre-sampling MTF was higher across all frequencies comparing the PCD to the FPD. The normalized NPS of the PCD did not vary with frequency, whereas the spectrum for the FPD decreased monotonically and was lower than the PCD noise power across most of the spatial frequency range studied due to optical light spreading. Optimal energy weights were applied to the dynamically acquired PCD images and the raw contrast of the 60 mg/cc calcium insert increased by factors of 1.12 +/- 0.09$1.12\pm 0.09$ and 1.52 +/- 0.22$1.52\pm 0.22$ at 60 and 120 kV respectively compared to the FPD.ConclusionsA Medipix3RX-based PCD was successfully integrated with the kilovoltage imaging system on an Elekta linac. The initial planar image quality characterization indicated improvements in the MTF and energy-weighted contrast compared to the FPD. Future work will focus on obtaining linac-mounted spectral CBCT images with a translate-rotate geometry, however this initial study indicates that variations in the PCD sensor response during acquisitions must be addressed to realise the full potential of linac-mounted spectral CBCT.

The magnetic field of a transverse MR-linac alters electron trajectories as the photon beam transits through materials, causing lower doses at flat entry surfaces and increased doses at flat beam-exiting surfaces. This study investigated the response of a MOSFET detector, known as the MOSkin™, for high-resolution surface and near-surface percentage depth dose measurements on an Elekta Unity. Simulations with Geant4 and the Monaco treatment planning system (TPS), and EBT-3 film measurements, were also performed for comparison. Measured MOSkin™ entry surface doses, relative to Dmax, were (9.9 ± 0.2)%, (10.1 ± 0.3)%, (11.3 ± 0.6)%, (12.9 ± 1.0)%, and (13.4 ± 1.0)% for 1 × 1 cm2, 3 × 3 cm2, 5 × 5 cm2, 10 × 10 cm2, and 22 × 22 cm2 fields, respectively. For the investigated fields, the maximum percent differences of Geant4, TPS, and film doses extrapolated and interpolated to a depth suitable for skin dose assessment at the beam entry, relative to MOSkin™ measurements at an equivalent depth were 1.0%, 2.8%, and 14.3%, respectively, and at a WED of 199.67 mm at the beam exit, 3.2%, 3.7% and 5.7%, respectively. The largest measured increase in exit dose, due to the electron return effect, was 15.4% for the 10 × 10 cm2 field size using the MOSkin™ and 17.9% for the 22 × 22 cm2 field size, using Geant4 calculations. The results presented in the study validate the suitability of the MOSkin™ detector for transverse MR-linac surface dosimetry.

Non-small cell lung cancer (NSCLC) patients with the metastatic spread of disease to the bone have high morbidity and mortality. Stereotactic ablative body radiotherapy increases the progression free survival and overall survival of these patients with oligometastases. FDG-PET/CT, a functional imaging technique combining positron emission tomography (PET) with 18 F-fluorodeoxyglucose (FDG) and computer tomography (CT) provides improved staging and identification of treatment response. It is also associated with reduction in size of the radiotherapy tumour volume delineation compared with CT based contouring in radiotherapy, thus allowing for dose escalation to the target volume with lower doses to the surrounding organs at risk. FDG-PET/CT is increasingly being used for the clinical management of NSCLC patients undergoing radiotherapy and has shown high sensitivity and specificity for the detection of bone metastases in these patients. Here, we present a software tool for detection, delineation and quantification of bone metastases using FDG-PET/CT images. The tool extracts standardised uptake values (SUV) from FDG-PET images for auto-segmentation of bone lesions and calculates volume of each lesion and associated mean and maximum SUV. The tool also allows automatic statistical validation of the auto-segmented bone lesions against the manual contours of a radiation oncologist. A retrospective review of FDG-PET/CT scans of more than 30 candidate NSCLC patients was performed and nine patients with one or more metastatic bone lesions were selected for the present study. The SUV threshold prediction model was designed by splitting the cohort of patients into a subset of ‘development’ and ‘validation’ cohorts. The development cohort yielded an optimum SUV threshold of 3.0 for automatic detection of bone metastases using FDG-PET/CT images. The validity of the derived optimum SUV threshold on the validation cohort demonstrated that auto-segmented and manually contoured bone lesions showed strong concordance for volume of bone lesion ( r = 0.993) and number of detected lesions ( r = 0.996). The tool has various applications in radiotherapy, including but not limited to studies determining optimum SUV threshold for accurate and standardised delineation of bone lesions and in scientific studies utilising large patient populations for instance for investigation of the number of metastatic lesions that can be treated safety with an ablative dose of radiotherapy without exceeding the normal tissue toxicity.

Abstract INTRODUCTION Radiomics in glioblastoma (GBM) imaging incorporates mathematical and statistical quantification of complex imaging features as surrogate biomarkers of tumour physiology. Delta-radiomics extends this capability by monitoring changes in these features over time. This study aims to evaluate selected radiomic and delta-radiomic features of diffusion-weighted imaging (DWI) as potential early predictors of overall survival (OS) in GBM patients undergoing adjuvant chemo-radiotherapy (aCRT). METHODS Imaging and data from n=12 newly diagnosed GBM patients prospectively recruited at Liverpool Hospital, New South Wales, were retrospectively analysed. Patients underwent serial MRI via 3.0T Siemens Magnetom-Skyra scanner, including anatomical and DWI sequences, before aCRT (baseline), and at 3 (FU1) and 6 weeks (FU2) post aCRT commencement. Gross tumour volume (GTV) was manually segmented on contrast-enhanced T1-weighted images. Four first-order histogram radiomic features (mean, skewness, entropy and 10th-percentile) and volume were extracted from the GTV on DWI sequences at each timepoint. Delta-radiomic features were calculated from the difference between measurements at baseline and each follow-up. Linear correlation between OS versus baseline and delta-radiomic features were calculated with Pearson’s coefficient (r). Statistically significant correlations were tested on an external validation dataset of n=8 GBM cases from The Cancer Imaging Archive (ACRIN-FMISO-Brain and ACRIN-DSC-MR-Brain datasets). RESULTS A significant positive correlation was found between OS and delta-entropy at FU2 (r = 0.639, p = 0.02). No significant correlation was found between OS and baseline or delta mean, skewness, or 10th percentile (p > 0.05). No significant correlation was found between OS and delta-volume at FU1 (r = 0.134, p = 0.68) or FU2 (r = 0.100, p = 0.76). CONCLUSION Our results indicate a potential utility of delta-entropy for prediction of overall survival. RESULTS will be validated on an external dataset. Further evaluation of radiomic and delta-radiomic features on a larger sample size is warranted.

Background and Purpose In the current and rapidly evolving era of real-time MRI-guided radiotherapy, our radiation biology and dosimetry knowledge is being tested in a novel way. This paper presents the successful design and implementation of a portable device used to generate strong localized magnetic fields. These are ideally suited for small-scale experiments that mimic the magnetic field environment inside an MRI-linac system, or more broadly MRI-guided particle therapy as well. Materials and Methods A portable permanent magnet-based device employing an adjustable steel yoke and magnetic field focusing cones has been designed, constructed, and tested. The apparatus utilizes two banks of Nd2$_{2}$Fe14$_{14}$B permanent magnets totaling around 50 kg in mass to generate a strong magnetic field throughout a small volume between two pole tips. The yoke design allows adjustment of the pole tip gap and exchanging of the focusing cones. Further to this, beam portal holes are present in the yoke and focusing cones, allowing for radiation beams of up to 5 x$\times$ 5 cm2$<^>{2}$ to pass through the region of high magnetic field between the focusing cone tips. Finite element magnetic modeling was performed to design and characterize the performance of the device. Automated physical measurements of the magnetic field components at various locations were measured to confirm the performance. The adjustable pole gap and interchangeable cones allows rapid changing of the experimental set-up to allow different styles of measurements to be performed. Results A mostly uniform magnetic field of 1.2 T can be achieved over a volume of at least 3 x$\times$ 3 x$\times$ 3 cm3$<^>{3}$. This can be reduced in strength to 0.3 T but increased in volume to 10 x$\times$ 10 x$\times$ 10 cm3$<^>{3}$ via removal of the cone tips and/or adjustment of the steel yoke. Although small, these volumes are sufficient to house radiation detectors, cell culture dishes, and various phantom arrangements targeted at examining small radiation field dosimetry inside magnetic field strengths that can be changed with ease. Most important is the ability to align the magnetic field both perpendicular to, or inline with, the radiation beam. To date, the system has been successfully used to conduct published research in the areas of radiation detector performance, lung phantom dosimetry, and how small clinical electron beams behave in these strong magnetic fields. Conclusions A portable, relatively inexpensive, and simple to operate device has successfully been constructed and used for performing radiation oncology studies around the theme of MRI-guided radiotherapy. This can be in either inline and perpendicular magnetic fields of up to 1.2 T with x-ray and particle beams.

AbstractPurposeThe aim of this study is to investigate off‐axis irradiation on the Australian MRI‐Linac using experiments and Monte Carlo simulations. Simulations are used to verify experimental measurements and to determine the minimum offset distance required to separate electron contamination from the photon field.MethodsDosimetric measurements were performed using a microDiamond detector, Gafchromic® EBT3 film, and MOSkinTM. Three field sizes were investigated including 1.9 × 1.9, 5.8 × 5.8, and 9.7 × 9.6 cm2. Each field was offset a maximum distance, approximately 10 cm, from the central magnetic axis (isocenter). Percentage depth doses (PDDs) were collected at a source‐to‐surface distance (SSD) of 1.8 m for fields collimated centrally and off‐axis. PDD measurements were also acquired at isocenter for each off‐axis field to measure electron contamination. Monte Carlo simulations were used to verify experimental measurements, determine the minimum field offset distance, and demonstrate the use of a spoiler to absorb electron contamination.ResultsOff‐axis irradiation separates the majority of electron contamination from an x‐ray beam and was found to significantly reduce in‐field surface dose. For the 1.9 × 1.9, 5.8 × 5.8, and 9.7 × 9.6 cm2 field, surface dose was reduced from 120.9% to 24.9%, 229.7% to 39.2%, and 355.3% to 47.3%, respectively. Monte Carlo simulations generally were within experimental error to MOSkinTM and microDiamond, and used to determine the minimum offset distance, 2.1 cm, from the field edge to isocenter. A water spoiler 2 cm thick was shown to reduce electron contamination dose to near zero.ConclusionsExperimental and simulation data were acquired for a range of field sizes to investigate off‐axis irradiation on an inline MRI‐Linac. The skin sparing effect was observed with off‐axis irradiation, a feature that cannot be achieved to the same extent with other methods, such as bolusing, for beams at isocenter.

Radiomics is a field of medical imaging analysis that focuses on the extraction of many quantitative imaging features related to shape, intensity and texture. These features are incorporated into models designed to predict important clinical or biological endpoints for patients. Attention for radiomics research has recently grown dramatically due to the increased use of imaging and the availability of large, publicly available imaging datasets. Glioblastoma multiforme (GBM) patients stand to benefit from this emerging research field as radiomics has the potential to assess the biological heterogeneity of the tumour, which contributes significantly to the inefficacy of current standard of care therapy. Radiomics models still require further development before they are implemented clinically in GBM patient management. Challenges relating to the standardisation of the radiomics process and the validation of radiomic models impede the progress of research towards clinical implementation. In this manuscript, we review the current state of radiomics in GBM, and we highlight the barriers to clinical implementation and discuss future validation studies needed to advance radiomics models towards clinical application.

Purpose Computational dosimetry software is routinely used to evaluate the organ and effective doses from computed tomography (CT) examinations. Studies have shown a significant variation in dose estimates between software in adult cohorts, and few studies have evaluated software for pediatric dose estimates. This study aims to compare the primary organ and effective doses estimated by four commercially available CT dosimetry software to thermoluminescent dosimeter (TLD) measurements in a 1-year-old phantom. Methods One hundred fifteen calibrated LiF (Mg, Cu, P)-TLD 100-H chips were embedded within an anthropomorphic phantom representing a 1-year-old child at positions that matched the approximate location of organs within an infant. The phantom was scanned under three protocols, each with whole-body coverage. The mean absorbed doses from 25 radiosensitive organs and skeletal tissues were determined from the TLD readings. Effective doses for each of the protocols were subsequently calculated using ICRP 103 formalism. Dose estimates by the four Monte Carlo-based dose calculation systems were determined and compared to the directly measured doses. Results Most organ doses determined by computation dosimetry software aligned to phantom measurements within 20%. Additionally, comparisons between effective doses are calculated using computational and direct measurement methods aligned within 20% across the three protocols. Significant variances were found in bone surface dose estimations among dosimetry methods, likely caused by differences in bone tissue modeling. Conclusion All four-dosimetry software evaluated in this study provide adequate primary organ and effective dose estimations. Users should be aware, however, of the possible estimated uncertainty associated with each of the programs.

The Australian MRI-Linac prototype radiotherapy system has been shown to generate significant entry skin or surface dose increases. This arises from electron contamination focusing toward the isocenter caused by the 1 T MRI field being in-line with the x-ray beam. The aim of this study is to present accurate Monte Carlo modeling of these skin dose changes and to compare them with previous experimental measurements. Accurate skin dose modeling will improve confidence in the pathway forward to treatment planning for clinical trials. A COMSOL Multiphysics model of the Australian MRI-Linac system was used to generate a 3D magnetic field map to be used in corresponding Geant4 Monte Carlo simulations. The Geant4 simulations included the x-ray source (6 MV Linac), multileaf collimators (MLCs), and a 30 cm × 30 cm × 30 cm water phantom located with its front surface at the beam isocenter. Simulations were performed with a source to surface distance (SSD) of 1,819 mm for nominal field sizes 2 cm × 2 cm, 6 cm × 6 cm, and 10 cm × 10 cm. Central axis percentage depth dose (PDD) and surface (or skin) doses at 70 μm depth were calculated by using high-resolution scoring voxels of 10 μm thickness. The results were compared with corresponding experimental data collected using MOSkin™ on the Australian MRI-Linac prototype system. The accurate modeling provides great detail into how the electron contamination is heavily confined and focused toward the beam central axis due to the presence of in-line magnetic field. This concentration significantly increases the skin dose up to 320% for the field size of 10 cm × 10 cm. For 2 cm × 2 cm and 6 cm × 6 cm, the surface skin dose is 128% and 217%, respectively, as compared to the skin dose in the absence of the magnetic field. The simulation results are in generally good agreement, ±10%, with previously collected experimental data for the same nominal field sizes. For the first time, detailed Geant4 Monte Carlo simulations of the electron contamination in the Australian MRI-Linac system have been performed and confirmed to be sufficiently accurate. These simulations will provide a solid framework for estimating the skin dose changes in more clinically relevant treatment plan scenarios that are envisaged in the near future.

Abstract BACKGROUND Accurate and repeatable imaging segmentation of glioblastomas is important for effective radiomics modelling of clinical endpoints such as survival and treatment response. Manual and even automated segmentation are prone to variability. The primary objective of this study is to evaluate the repeatability of manually segmented glioblastomas on MRI which will serve as quality assurance for a quantitative MRI radiomics repeatability study. METHODS MRI datasets from n=19 patients with recurrent glioblastoma extracted from The Cancer Imaging Archive (RIDER Neuro MRI dataset) comprised of test-retest scans (time-point 1 and 2) acquired on average 2 days apart. The MRI protocol consisted of dynamic contrast-enhanced 3D FLASH using 0.1mmol/kg Magnevist intravenous injection at 3cc/second (TR 3.8ms, TE 1.8ms, 5mm slices, flip angle 25°), contrast-enhanced 3D FLASH (TR 8.6ms, TE 4.1ms, 1mm slices, flip angle 20°) and contrast-enhanced 3D FLAIR (TR 6000ms, TE 353ms, TI 2200ms, 1mm slices, flip angle 180°) on a 1.5T magnet. Contrast enhancing tumour from n=38 MRI scans were manually segmented by a radiologist slice by slice using contrast-enhanced 3D FLASH T1-weighted images on MIM software (v6.9.5). All cases at time-point 1 were contoured before contouring commenced for time-point 2 in the same order. Repeatability and spatial overlap was assessed by Dice similarity coefficient (DSC), Hausdorff distance (HD) and centroid shift. RESULTS A comparison of time-point 1 and 2 demonstrated the median DSC for n=19 cases was 0.84 (interquartile range 0.07), mean HD was only 0.1cm and mean centroid shift was 0.2cm. CONCLUSION High repeatability and spatial overlap of manually segmented contrast enhancing regions of recurrent glioblastoma were achieved on serial MRI. This substantiates a high level of repeatability which forms a core component of an MRI radiomics platform under development.

AbstractPurposeTo assess the technical performance of the apparent diffusion coefficient (ADC) on a dedicated 3T radiotherapy scanner, using a standardized phantom and sequences. Investigations into factors that could impact the technical performance of ADC in the clinic were also completed, including changing the slice‐encoded imaging direction and the reference sample ADC value.MethodsADC acquisitions were performed monthly on an isotropic diffusion phantom over 1 year. Measurements of ADC %bias, coefficients of variation for short‐/long‐term repeatability and precision (CVST/CVLT and CVP), and b‐value dependency (Depb) were calculated. The measurements were then assessed according to the Quantitative Imaging Biomarker Alliance (QIBA) Diffusion Profile specifications.ResultsThe average of all measurements over the year was within Profile recommended ranges. This included when testing was performed in different imaging directions, and on samples that had different ADC reference values (0.4–1.1 μm2/ms). Results in the axial plane for the central water vial included a bias of +0.05%, CVST /CVLT/CVP = 0.1%/ 0.9%/0.4% and Depb = 0.4%.ConclusionsThe technical performance of ADC on a radiotherapy dedicated MRI scanner over the course of 12 months was considered conformant to the QIBA Profile. Quantifying these metrics and factors that may affect the performance is essential in progressing the use of ADC clinically: ensuring that the observed change of ADC in a tissue is due to a physiological response and not measurement variability.