A systematic review of 4D magnetic resonance imaging techniques for abdominal radiotherapy treatment planning.

Background and purpose: Four-dimensional magnetic resonance imaging (4DMRI) has gained interest as an alternative to the current standard for motion management four-dimensional tomography (4DCT) in abdominal radiotherapy treatment planning (RTP). This review aims to assess the 4DMRI literature in abdomen, focusing on technical considerations and the validity of using 4DMRI for patients within radiotherapy protocols. Materials and methods: The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive search was performed across the Medline, Embase, Scopus, and Web of Science databases, covering all years up to December 31, 2023. The studies were grouped into two categories: 4DMRI reconstructed from 3DMRI acquisition; and 4DMRI reconstructed from multi-slice 2DMRI acquisition. Results: A total of 39 studies met the inclusion criteria and were analysed to provide key findings. Key findings were 4DMRI had the potential to improve abdominal RTP for patients by providing accurate tumour definition and motion assessment compared to 4DCT. 4DMRI reconstructed from 3DMRI acquisition showed promise as a feasible approach for motion management in abdominal RTP regarding spatial resolution. Currently,the slice thickness achieved on 4DMRI reconstructed from multi-slice 2DMRI acquisitions was unsuitable for clinical purposes. Lastly, the current barriers for clinical implementation of 4DMRI were the limited availability of validated commercial solutions and the lack of larger cohort comparative studies to 4DCT for target delineation and plan optimisation. Conclusion: 4DMRI showed potential improvements in abdominal RTP, but standards and guidelines for the use of 4DMRI in radiotherapy were required to demonstrate clinical benefits.

Dosimetric impact of contour editing on CT and MRI deep-learning autosegmentation for brain OARs.

PURPOSE: To establish the clinical applicability of deep-learning organ-at-risk autocontouring models (DL-AC) for brain radiotherapy. The dosimetric impact of contour editing, prior to model training, on performance was evaluated for both CT and MRI-based models. The correlation between geometric and dosimetric measures was also investigated to establish whether dosimetric assessment is required for clinical validation. METHOD: CT and MRI-based deep learning autosegmentation models were trained using edited and unedited clinical contours. Autosegmentations were dosimetrically compared to gold standard contours for a test cohort. D1%, D5%, D50%, and maximum dose were used as clinically relevant dosimetric measures. The statistical significance of dosimetric differences between the gold standard and autocontours was established using paired Student's t-tests. Clinically significant cases were identified via dosimetric headroom to the OAR tolerance. Pearson's Correlations were used to investigate the relationship between geometric measures and absolute percentage dose changes for each autosegmentation model. RESULTS: Except for the right orbit, when delineated using MRI models, the dosimetric statistical analysis revealed no superior model in terms of the dosimetric accuracy between the CT DL-AC models or between the MRI DL-AC for any investigated brain OARs. The number of patients where the clinical significance threshold was exceeded was higher for the optic chiasm D1% than other OARs, for all autosegmentation models. A weak correlation was consistently observed between the outcomes of dosimetric and geometric evaluations. CONCLUSIONS: Editing contours before training the DL-AC model had no significant impact on dosimetry. The geometric test metrics were inadequate to estimate the impact of contour inaccuracies on dose. Accordingly, dosimetric analysis is needed to evaluate the clinical applicability of DL-AC models in the brain.

Deep learning MRI-only synthetic-CT generation for pelvis, brain and head and neck cancers.

BACKGROUND AND PURPOSE: MRI-only planning relies on dosimetrically accurate synthetic-CT (sCT) generation to allow dose calculation. Here we validated the dosimetric accuracy of sCTs generated using a deep learning algorithm for pelvic, brain and head and neck (H&N) cancer sites using variable MRI data from multiple scanners. METHODS: sCT generation models were trained using a cycle-GAN algorithm, using paired MRI-CT patient data. Input MRI sequences were: T2 for pelvis, T1 with gadolinium (T1Gd) and T2 FLAIR for brain and T1 for H&N. Patient validation sCTs were generated for each site (49 - pelvis, 25 - brain and 30 - H&N). VMAT plans, following local clinical protocols, were calculated on planning CTs and recalculated on sCTs. HU and dosimetric differences were assessed, including DVH differences and gamma index (2 %/2mm). RESULTS: Mean absolute error (MAE) HU differences were; 48.8 HU (pelvis), 118 HU (T2 FLAIR brain), 126 HU (T1Gd brain) and 124 HU (H&N). Mean primary PTV D95% dose differences for all sites were < 0.2 % (range: -0.9 to 1.0 %). Mean 2 %/2mm and 1 %/1mm gamma pass rates for all sites were > 99.6 % (min: 95.3 %) and > 97.3 % (min: 80.1 %) respectively. For all OARs for all sites, mean dose differences were < 0.4 %. CONCLUSION: Generated sCTs had excellent dosimetric accuracy for all sites and sequences. The cycle-GAN model, available on the research version of a commercial treatment planning system, is a feasible method for sCT generation with high clinical utility due to its ability to use variable input data from multiple scanners and sequences.

Geometric evaluations of CT and MRI based deep learning segmentation for brain OARs in radiotherapy.

Objective.Deep-learning auto-contouring (DL-AC) promises standardisation of organ-at-risk (OAR) contouring, enhancing quality and improving efficiency in radiotherapy. No commercial models exist for OAR contouring based on brain magnetic resonance imaging (MRI). We trained and evaluated computed tomography (CT) and MRI OAR autosegmentation models in RayStation. To ascertain clinical usability, we investigated the geometric impact of contour editing before training on model quality.Approach.Retrospective glioma cases were randomly selected for training (n= 32, 47) and validation (n= 9, 10) for MRI and CT, respectively. Clinical contours were edited using international consensus (gold standard) based on MRI and CT. MRI models were trained (i) using the original clinical contours based on planning CT and rigidly registered T1-weighted gadolinium-enhanced MRI (MRIu), (ii) as (i), further edited based on CT anatomy, to meet international consensus guidelines (MRIeCT), and (iii) as (i), further edited based on MRI anatomy (MRIeMRI). CT models were trained using: (iv) original clinical contours (CTu) and (v) clinical contours edited based on CT anatomy (CTeCT). Auto-contours were geometrically compared to gold standard validation contours (CTeCT or MRIeMRI) using Dice Similarity Coefficient, sensitivity, and mean distance to agreement. Models' performances were compared using paired Student's t-testing.Main results.The edited autosegmentation models successfully generated more segmentations than the unedited models. Paired t-testing showed editing pituitary, orbits, optic nerves, lenses, and optic chiasm on MRI before training significantly improved at least one geometry metric. MRI-based DL-AC performed worse than CT-based in delineating the lacrimal gland, whereas the CT-based performed worse in delineating the optic chiasm. No significant differences were found between the CTeCT and CTu except for optic chiasm.Significance.T1w-MRI DL-AC could segment all brain OARs except the lacrimal glands, which cannot be easily visualized on T1w-MRI. Editing contours on MRI before model training improved geometric performance. MRI DL-AC in RT may improve consistency, quality and efficiency but requires careful editing of training contours.

The role and potential of using quantitative MRI biomarkers for imaging guidance in brain cancer radiotherapy treatment planning: A systematic review.

Background and purpose: Improving the accuracy of brain tumour radiotherapy (RT) treatment planning is important to optimise patient outcomes. This systematic review investigates primary studies providing clinical evidence for the integration of quantitative magnetic resonance imaging (qMRI) biomarkers and MRI radiomics to optimise brain tumour RT planning. Materials and methods: PubMed, Scopus, Embase and Web of Science databases were searched for all years until June 21, 2022. The search identified original articles demonstrating clinical evidence for the use of qMRI biomarkers and MRI radiomics for the optimization of brain cancer RT planning. Relevant information was extracted and tabulated, including qMRI metrics and techniques, impact on RT plan optimization and changes in target and normal tissue contouring and dose distribution. Results: Nineteen articles met the inclusion criteria. Studies were grouped according to the qMRI biomarkers into: 1) diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI; five studies); 2) diffusion tensor imaging (DTI; seven studies); and 3) MR spectroscopic imaging (MRSI; seven studies). No relevant MRI-based radiomics studies were identified. Integration of DTI maps offers the potential for improved organs at risk (OAR) sparing. MRSI metabolic maps are a promising technique for improving delineation accuracy in terms of heterogeneity and infiltration, with OAR sparing. No firm conclusions could be drawn regarding the integration of DWI metrics and PWI maps. Conclusions: Integration of qMRI metrics into RT planning offers the potential to improve delineation and OAR sparing. Clinical trials and consensus guidelines are required to demonstrate the clinical benefits of such approaches.

Treatment plan optimisation for reirradiation.

BACKGROUND: The STRIDeR (Support Tool for Re-Irradiation Decisions guided by Radiobiology) project aims to create a clinically viable re-irradiation planning pathway within a commercial treatment planning system (TPS). Such a pathway should account for previously delivered dose, voxel-by-voxel, taking fractionation effects, tissue recovery and anatomical changes into account. This work presents the workflow and technical solutions in the STRIDeR pathway. METHODS: The pathway was implemented in RayStation (version 9B DTK) to allow an original dose distribution to be used as background dose to guide optimisation of re-irradiation plans. Organ at risk (OAR) planning objectives in equivalent dose in 2 Gy fractions (EQD2) were applied cumulatively across the original and re-irradiation treatments, with optimisation of the re-irradiation plan performed voxel-by-voxel in EQD2. Different approaches to image registration were employed to account for anatomical change. Data from 21 patients who received pelvic Stereotactic Ablative Radiotherapy (SABR) re-irradiation were used to illustrate the use of the STRIDeR workflow. STRIDeR plans were compared to those produced using a standard manual method. RESULTS: The STRIDeR pathway resulted in clinically acceptable plans in 20/21 cases. Compared to plans produced using the laborious manual method, less constraint relaxation was required or higher re-irradiation doses could be prescribed in 3/21. CONCLUSION: The STRIDeR pathway used background dose to guide radiobiologically meaningful, anatomically-appropriate re-irradiation treatment planning within a commercial TPS. This provides a standardised and transparent approach, offering more informed re-irradiation and improved cumulative OAR dose evaluation.

The impact of a metal artefact reduction algorithm on treatment planning for patients undergoing radiotherapy of the pelvis.

Background and purpose: Metallic implants cause artefacts in computed tomography (CT) images and can introduce significant errors to structure visualisation and dosimetric calculation within the radiotherapy planning process. This study evaluated an orthopaedic metal artefact reduction algorithm and its effect on the CT number, image noise, structure delineation, and treatment dose. Methods: Raw CT data were reconstructed using standard filtered back projection and an artefact reduction algorithm to create 'standard' and 'corrected' images. A phantom containing tissue-mimicking inserts and two titanium plugs was imaged. The average CT number was compared to baseline data acquired without metal inserts. Data from 11 pelvic external beam radiotherapy (EBRT) patients with bi- or uni-lateral hip implants were retrospectively analysed. The clinically used treatment plans were re-computed on the corrected images. A prostate-mimicking phantom containing metal 'implants' was imaged, and 11 observers contoured both reconstructions. Results: The artefact reduction algorithm improved the CT number in those areas most affected by metal artefacts and decreased noise by 19 % (P =.04) Changes in dose distributions on corrected images compared to those calculated using the current clinical protocol were clinically insignificant. Volumes contoured on the corrected phantom images had larger Dice coefficients than those contoured on the standard images (P =.001), as well as a 36 % lower standard deviation in volumes. Conclusion: This study demonstrates that the metal artefact reduction software reduces the error in CT numbers, can improve delineation accuracy, and can reduce inter-observer variability. It has the potential to streamline the planning pathway and improve treatment planning accuracy.

Assessment of CBCT-based synthetic CT generation accuracy for adaptive radiotherapy planning.

PURPOSE: Cone-beam CT (CBCT)-based synthetic CT (sCT) dose calculation has the potential to make the adaptive radiotherapy (ART) pathway more efficient while removing subjectivity. This study assessed four sCT generation methods using 15 head-and-neck rescanned ART patients. Each patient's planning CT (pCT), rescan CT (rCT), and CBCT post-rCT was acquired with the CBCT deformably registered to the rCT (dCBCT). METHODS: The four methods investigated were as follows: method 1-deformably registering the pCT to the dCBCT. Method 2-assigning six mass density values to the dCBCT. Method 3-iteratively removing artifacts and correcting the dCBCT Hounsfield units (HU). Method 4-using a cycle general adversarial network machine learning model (trained with 45 paired pCT and CBCT). Treatment plans were created on the rCT and recalculated on each sCT. Planning target volume (PTV) and organ-at-risk (OAR) structures were contoured by clinicians on the rCT (high-dose PTV, low-dose PTV, spinal canal, larynx, brainstem, and parotids) to allow the assessment of dose-volume histogram statistics at clinically relevant points. RESULTS: The HU mean absolute error (MAE) and minimum dose gamma index pass rate (2%/2 mm) were calculated, and the generation time was measured for 15 patients using the rCT as the comparator. For methods 1-4 the MAE, gamma index analysis, and generation time were as follows: 59.7 HU, 100.0%, and 143 s; 164.2 HU, 95.2%, and 232 s; 75.7 HU, 99.9%, and 153 s; and 79.4 HU, 99.8%, and 112 s, respectively. Dose differences for PTVs and OARs were all <0.3 Gy except for method 2 (<0.5 Gy). CONCLUSION: All methods were considered clinically viable. The machine learning method was found to be most suitable for clinical implementation due to its high dosimetric accuracy and short generation time. Further investigation is required for larger anatomical changes between the CBCT and pCT and for other anatomical sites.

Harmonisation of scanner-dependent contrast variations in magnetic resonance imaging for radiation oncology, using style-blind auto-encoders.

Background and purpose: Magnetic Resonance Imaging (MRI) exhibits scanner dependent contrast, which limits generalisability of radiomics and machine-learning for radiation oncology. Current deep-learning harmonisation requires paired data, retraining for new scanners and often suffers from geometry-shift which alters anatomical information. The aim of this study was to investigate style-blind auto-encoders for MRI harmonisation to accommodate unpaired training data, avoid geometry-shift and harmonise data from previously unseen scanners. Materials and methods: A style-blind auto-encoder, using adversarial classification on the latent-space, was designed for MRI harmonisation. The public CC359 T1-w MRI brain dataset includes six scanners (three manufacturers, two field strengths), of which five were used for training. MRI from all six (including one unseen) scanner were harmonised to common contrast. Harmonisation extent was quantified via Kolmogorov-Smirnov testing of residual scanner dependence of 3D radiomic features, and compared to WhiteStripe normalisation. Anatomical content preservation was measured through change in structural similarity index on contrast-cycling (δSSIM). Results: The percentage of radiomics features showing statistically significant scanner-dependence was reduced from 41% (WhiteStripe) to 16% for white matter and from 39% to 27% for grey matter. δSSIM < 0.0025 on harmonisation and de-harmonisation indicated excellent anatomical content preservation. Conclusions: Our method harmonised MRI contrast effectively, preserved critical anatomical details at high fidelity, trained on unpaired data and allowed zero-shot harmonisation. Robust and clinically translatable harmonisation of MRI will enable generalisable radiomic and deep-learning models for a range of applications, including radiation oncology treatment stratification, planning and response monitoring.

Dose summation and image registration strategies for radiobiologically and anatomically corrected dose accumulation in pelvic re-irradiation.

BACKGROUND: Re-irradiation (reRT) is a promising technique for patients with localized recurrence in a previously irradiated area but presents major challenges. These include how to deal with anatomical change between two courses of radiotherapy and integration of radiobiology when summating original and re-irradiation doses. The Support Tool for Re-Irradiation Decisions guided by Radiobiology (STRIDeR) project aims to develop a software tool for use in a commercial treatment planning system to facilitate more informed reRT by accounting for anatomical changes and incorporating radiobiology. We evaluated three approaches to dose summation, incorporating anatomical change and radiobiology to differing extents. METHODS: In a cohort of 21 patients who previously received pelvic re-irradiation the following dose summation strategies were compared: (1) Rigid registration (RIR) and physical dose summation, to reflect the current clinical approach, (2) RIR and radiobiological dose summation in equivalent dose in 2 Gy fractions (EQD2), and (3) Patient-specific deformable image registration (DIR) with EQD2 dose summation. RESULTS: RIR and physical dose summation (Strategy 1) resulted in high cumulative organ at risk (OAR) doses being 'missed' in 14% of cases, which were highlighted by EQD2 dose summation (Strategy 2). DIR (with EQD2 dose summation; Strategy 3) resulted in improved OAR overlap and distance to agreement metrics compared to RIR (with EQD2 dose summation; Strategy 2) and was consistently preferred in terms of clinical utility. DIR was considered to have a clinically important impact on dose summation in 38% of cases. CONCLUSION: Re-irradiation cases require individualized assessment when considering dose summation with the previous treatment plan. Fractionation correction is necessary to meaningfully assess cumulative doses and reduce the risk of unintentional OAR overdose. DIR can add clinically relevant information in selected cases, especially for significant anatomical change. Robust solutions for cumulative dose assessment offer the potential for future improved understanding of cumulative OAR tolerances.

The benefit of MR-only radiotherapy treatment planning for anal and rectal cancers: A planning study.

INTRODUCTION: Limited evidence exists showing the benefit of magnetic resonance (MR)-only radiotherapy treatment planning for anal and rectal cancers. This study aims to assess the impact of MR-only planning on target volumes (TVs) and treatment plan doses to organs at risks (OARs) for anal and rectal cancers versus a computed tomography (CT)-only pathway. MATERIALS AND METHODS: Forty-six patients (29 rectum and 17 anus) undergoing preoperative or radical external beam radiotherapy received CT and T2 MR simulation. TV and OARs were delineated on CT and MR, and volumetric arc therapy treatment plans were optimized independently (53.2 Gy/28 fractions for anus, 45 Gy/25 fractions for rectum). Further treatment plans assessed gross tumor volume (GTV) dose escalation. Differences in TV volumes and OAR doses, in terms of Vx Gy (organ volume (%) receiving x dose (Gy)), were assessed. RESULTS: MR GTV and primary planning TV (PTV) volumes systematically reduced by 13 cc and 98 cc (anus) and 44 cc and 109 cc (rectum) respectively compared to CT volumes. Statistically significant OAR dose reductions versus CT were found for bladder and uterus (rectum) and bladder, penile bulb, and genitalia (anus). With GTV boosting, statistically significant dose reductions were found for sigmoid, small bowel, vagina, and penile bulb (rectum) and vagina (anus). CONCLUSION: Our findings provide evidence that the introduction of MR (whether through MR-only or CT-MR pathways) to radiotherapy treatment planning for anal and rectal cancers has the potential to improve treatments. MR-related OAR dose reductions may translate into less treatment-related toxicity for patients or greater ability to dose escalate.

Patient position verification in magnetic-resonance imaging only radiotherapy of anal and rectal cancers.

BACKGROUND AND PURPOSE: Magnetic resonance (MR)-only treatment pathways require either the MR-simulation or synthetic-computed tomography (sCT) as an alternative reference image for cone beam computed tomography (CBCT) patient position verification. This study assessed whether using T2 MR or sCT as CBCT reference images introduces systematic registration errors as compared to CT for anal and rectal cancers. MATERIALS AND METHODS: A total of 32 patients (18 rectum,14 anus) received pre-treatment CT- and T2 MR- simulation. Routine treatment CBCTs were acquired. sCTs were generated using a validated research model. The local clinical registration protocol, using a grey-scale registration algorithm, was performed for 216 CBCTs using CT, MR and sCT as the reference image. Linear mixed effects modelling identified systematic differences between modalities. RESULTS: Systematic translation and rotation differences to CT for MR were -0.3 to + 0.3 mm and -0.1 to 0.4° for anal cancers and -0.4 to 0.0 mm and 0.0 to 0.1° for rectal cancers, and for sCT were -0.4 to + 0.8 mm, -0.1 to 0.2° for anal cancers and -0.6 to + 0.2 mm, -0.1 to + 0.1° for rectal cancers. CONCLUSIONS: T2 MR or sCT can successfully be used as reference images for anal and rectal cancer CBCT position verification with systematic differences to CT <±1 mm and <±0.5°. Clinical enabling of alternative modalities as reference images by vendors is required to reduce challenges associated with their use.

Volumetric and dosimetric impact of post-surgical MRI-guided radiotherapy for glioblastoma: A pilot study.

Objectives: Glioblastoma (GBM) radiotherapy (RT) target delineation requires MRI, ideally concurrent with CT simulation (pre-RT MRI). Due to limited MRI availability, <72 h post-surgery MRI is commonly used instead. Whilst previous investigations assessed volumetric differences between post-surgical and pre-RT delineations, dosimetric impact remains unknown. We quantify volumetric and dosimetric impact of using post-surgical MRI for GBM target delineation. Methods: Gross tumour volumes (GTVs) for five GBM patients receiving chemo-RT with post-surgical and pre-RT MRIs were delineated by three independent observers. Planning target volumes (PTVs) and RT plans were generated for each GTV. Volumetric and dosimetric differences were assessed through: absolute volumes, volume-distance histograms and dose-volume histogram statistics. Results: Post-surgical MRI delineations had significantly (p < 0.05) larger GTV and PTV volumes (median 16.7 and 64.4 cm3, respectively). Post-surgical RT plans, applied to pre-RT delineations, had significantly decreased (p < 0.01) median PTV doses (ΔD99% = -8.1 Gy and ΔD95% = -2.0 Gy). Median organ-at-risk (OAR) dose increases (brainstem ΔD5% =+0.8, normal brain mean dose =+2.9 and normal brain ΔD10% = 5.3 Gy) were observed. Conclusion: Post-surgical MRI delineation significantly impacted RT planning, with larger normal-appearing tissue volumes irradiated and increased OAR doses, despite a reduced coverage of the pre-RT defined target. Advances in knowledge: We believe this is the first investigation assessing the dosimetric impact of using post-surgical MRI for GBM target delineation. It highlights the potential of significantly degraded RT plans, showing the clinical need for dedicated MRI for GBM RT.

Multicentre, deep learning, synthetic-CT generation for ano-rectal MR-only radiotherapy treatment planning.

BACKGROUND AND PURPOSE: Comprehensive dosimetric analysis is required prior to the clinical implementation of pelvic MR-only sites, other than prostate, due to the limited number of site specific synthetic-CT (sCT) dosimetric assessments in the literature. This study aims to provide a comprehensive assessment of a deep learning-based, conditional generative adversarial network (cGAN) model for a large ano-rectal cancer cohort. The following challenges were investigated; T2-SPACE MR sequences, patient data from multiple centres and the impact of sex and cancer site on sCT quality. METHOD: RT treatment position CT and T2-SPACE MR scans, from two centres, were collected for 90 ano-rectal patients. A cGAN model trained using a focal loss function, was trained and tested on 46 and 44 CT-MR ano-rectal datasets, paired using deformable registration, respectively. VMAT plans were created on CT and recalculated on sCT. Dose differences and gamma indices assessed sCT dosimetric accuracy. A linear mixed effect (LME) model assessed the impact of centre, sex and cancer site. RESULTS: A mean PTV D95% dose difference of 0.1% (range: -0.5% to 0.7%) was found between CT and sCT. All gamma index (1%/1 mm threshold) measurements were >99.0%. The LME model found the impact of modality, cancer site, sex and centre was clinically insignificant (effect ranges: -0.4% and 0.3%). The mean dose difference for all OAR constraints was 0.1%. CONCLUSION: Focal loss cGAN models using T2-SPACE MR sequences from multiple centres can produce generalisable, dosimetrically accurate sCTs for ano-rectal cancers.

Audit feasibility for geometric distortion in magnetic resonance imaging for radiotherapy.

BACKGROUND AND PURPOSE: Magnetic Resonance Imaging (MRI) is increasingly being used in radiotherapy (RT). However, geometric distortions are a known challenge of using MRI in RT. The aim of this study was to demonstrate feasibility of a national audit of MRI geometric distortions. This was achieved by assessing large field of view (FOV) MRI distortions on a number of scanners used clinically for RT. MATERIALS AND METHODS: MRI scans of a large FOV MRI geometric distortion phantom were acquired on 11 MRI scanners that are used clinically for RT in the UK. The mean and maximum distortions and variance between scanners were reported at different distances from the isocentre. RESULTS: For a small FOV representing a brain (100-150 mm from isocentre) all distortions were < 2 mm except for the maximum distortion of one scanner. For a large FOV representing a head and neck/pelvis (200-250 mm from isocentre) mean distortions were < 2 mm except for one scanner, maximum distortions were > 10 mm in some cases. The variance between scanners was low and was found to increase with distance from isocentre. CONCLUSIONS: This study demonstrated feasibility of the technique to be repeated in a country wide geometric distortion audit of all MRI scanners used clinically for RT. Recommendations were made for performing such an audit and how to derive acceptable limits of distortion in such an audit.

Efficacy and toxicity outcomes for patients treated with focal salvage high dose rate brachytherapy for locally recurrent prostate cancer.

INTRODUCTION: Isolated local recurrence of prostate cancer following primary radiotherapy or brachytherapy may be treated with focal salvage high dose rate brachytherapy, although there remains an absence of high quality evidence to support this approach. METHODS: Men with prostate cancer treated consecutively between 2015 and 2018 using 19 Gy in a single fraction high dose rate brachytherapy (HDR) for locally recurrent prostate cancer were identified from an institutional database. Univariable analysis was performed to evaluate the relationship between patient, disease and treatment factors with biochemical progression free survival (bPFS). RESULTS: 43 patients were eligible for evaluation. Median follow up duration was 26 months (range 1-60). Median bPFS was 35 months (95% confidence interval 25.6-44.4). Kaplan-Meier estimates for bPFS at 1, 2 and 3 years post salvage were 95.2%, 70.6% and 41.8% respectively. On univariable Cox regression analysis, only nadir PSA was significantly associated with bPFS although the majority of patients were also treated with androgen deprivation therapy. Only one late grade 3 genitourinary toxicity was observed. CONCLUSION: Focal salvage HDR brachytherapy may provide good biochemical control with a low risk of severe toxicity. Further evaluation within clinical trials are needed to establish its role in the management of locally recurrent prostate cancer.

Ten-year longitudinal health-related quality of life following iodine-125 brachytherapy monotherapy for localized prostate cancer.

PURPOSE: This prospective longitudinal study quantifies health-related quality of life (HRQoL) up to 10 years following permanent iodine-125 (125I) prostate brachytherapy alone for localized prostate cancer. MATERIAL AND METHODS: In total, 120 patients completed a validated expanded prostate cancer index composite (EPIC) questionnaire pre-treatment and at 8 time points after treatment (6 weeks, 6, 10, 18 months, and 2, 3, 5, 10 years). At each time point, clinically relevant small, moderate, and severe declines in HRQoL were defined as 0.2-0.5 SD, 0.5-0.8 SD, and > 0.8 SD of baseline function for each of urinary, bowel, and sexual domains, respectively. RESULTS: Response rates in the first two years were > 90%, but thereafter dropped to 75% and 48% at 5 and 10 years, respectively. 50 patients (41.6%) responded at all stages. Maximal deterioration in mean urinary and sexual summary scores was noted 6 weeks after implant, with severe urinary symptoms and moderate bowel/sexual symptoms. At 6 months, urinary and bowel quality of life (QoL) had improved to mild impairment, which then fully resolved at 10 months. Sexual QoL remained mildly impaired throughout the 10 years of follow-up. At 10 years, new mild impairment of urinary and bowel QoL was found. CONCLUSIONS: Clinically mild changes in urinary, bowel, and sexual QoL are found 10 years after 125I monotherapy. The impairment in sexual function persists from treatment, but urinary and bowel symptoms are new at 10 years.

A comparison of outcomes for patients with intermediate and high risk prostate cancer treated with low dose rate and high dose rate brachytherapy in combination with external beam radiotherapy.

INTRODUCTION: There is evidence to support use of external beam radiotherapy (EBRT) in combination with both low dose rate brachytherapy (LDR-EBRT) and high dose rate brachytherapy (HDR-EBRT) to treat intermediate and high risk prostate cancer. METHODS: Men with intermediate and high risk prostate cancer treated using LDR-EBRT (treated between 1996 and 2007) and HDR-EBRT (treated between 2007 and 2012) were identified from an institutional database. Multivariable analysis was performed to evaluate the relationship between patient, disease and treatment factors with biochemical progression free survival (bPFS). RESULTS: 116 men were treated with LDR-EBRT and 171 were treated with HDR-EBRT. At 5 years, bPFS was estimated to be 90.5% for the LDR-EBRT cohort and 77.6% for the HDR-EBRT cohort. On multivariable analysis, patients treated with HDR-EBRT were more than twice as likely to experience biochemical progression compared with LDR-EBRT (HR 2.33, 95% CI 1.12-4.07). Patients with Gleason ≥8 disease were more than five times more likely to experience biochemical progression compared with Gleason 6 disease (HR 5.47, 95% CI 1.26-23.64). Cumulative incidence of ≥grade 3 genitourinary and gastrointestinal toxicities for the LDR-EBRT and HDR-EBRT cohorts were 8% versus 4% and 5% versus 1% respectively, although these differences did not reach statistical significance. CONCLUSION: LDR-EBRT may provide more effective PSA control at 5 years compared with HDR-EBRT. Direct comparison of these treatments through randomised trials are recommended to investigate this hypothesis further.

A Systematic Review of the Clinical Implementation of Pelvic Magnetic Resonance Imaging-Only Planning for External Beam Radiation Therapy.

The use of magnetic resonance (MR) imaging scans alone for radiation therapy treatment planning (MR-only planning) has been highlighted as one method of improving patient outcomes. Recent technologic advances have meant that introducing MR-only planning to the clinic is becoming a reality, with several specialist radiation therapy clinics using this technique for treatment. As such, substantial efforts are being made to introduce this technique into wide-spread clinical implementation. A systematic review of publications investigating the clinical implementation of pelvic MR-only radiation therapy treatment planning was undertaken following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The Medline, Embase, Scopus, Science Direct, Cumulative Index to Nursing and Allied Health Literature, and Web of Science databases were searched (timespan: all years to January 2, 2019). Twenty-six articles met the inclusion criteria. The studies were grouped into the following categories: (1) MR acquisition and synthetic computed tomography generation verification, (2) MR distortion quantification and phantom development, (3) clinical validation of patient treatment positioning in an MR-only workflow, and (4) MR-only commissioning processes. Key conclusions from this review are (1) MR-only planning has been implemented clinically for prostate cancer treatments; (2) a substantial amount of work remains to translate MR-only planning into widespread clinical implementation for all pelvic sites; (3) MR scanner distortions are no longer a barrier to MR-only planning, but they must be managed appropriately; (4) MR-only-based patient positioning verification shows promise, but limited evidence is reported in the literature and further investigation is required; and (5) a number of MR-only commissioning processes have been reported, which can aid centers as they undertake local commissioning; however, this needs to be formalized in guidance from national bodies.