The value of magnetic resonance imaging for radiotherapy planning

Quantitative imaging for radiotherapy purposes

Quantitative imaging biomarkers show great potential for use in radiotherapy. Quantitative images based on microscopic tissue properties and tissue function can be used to improve contouring of the radiotherapy targets. Furthermore, quantitative imaging biomarkers might be used to predict treatment response for several treatment regimens and hence be used as a tool for treatment stratification, either to determine which treatment modality is most promising or to determine patient-specific radiation dose. Finally, patient-specific radiation doses can be further tailored to a tissue/voxel specific radiation dose when quantitative imaging is used for dose painting. In this review, published standards, guidelines and recommendations on quantitative imaging assessment using CT, PET and MRI are discussed. Furthermore, critical issues regarding the use of quantitative imaging for radiation oncology purposes and resultant pending research topics are identified.

Deep learning-based MR-to-CT synthesis: The influence of varying gradient echo-based MR images as input channels

PURPOSE

To study the influence of gradient echo-based contrasts as input channels to a 3D patch-based neural network trained for synthetic CT (sCT) generation in canine and human populations.

METHODS

Magnetic resonance images and CT scans of human and canine pelvic regions were acquired and paired using nonrigid registration. Magnitude MR images and Dixon reconstructed water, fat, in-phase and opposed-phase images were obtained from a single T1 -weighted multi-echo gradient-echo acquisition. From this set, 6 input configurations were defined, each containing 1 to 4 MR images regarded as input channels. For each configuration, a UNet-derived deep learning model was trained for synthetic CT generation. Reconstructed Hounsfield unit maps were evaluated with peak SNR, mean absolute error, and mean error. Dice similarity coefficient and surface distance maps assessed the geometric fidelity of bones. Repeatability was estimated by replicating the training up to 10 times.

RESULTS

Seventeen canines and 23 human subjects were included in the study. Performance and repeatability of single-channel models were dependent on the TE-related water-fat interference with variations of up to 17% in mean absolute error, and variations of up to 28% specifically in bones. Repeatability, Dice similarity coefficient, and mean absolute error were statistically significantly better in multichannel models with mean absolute error ranging from 33 to 40 Hounsfield units in humans and from 35 to 47 Hounsfield units in canines.

CONCLUSION

Significant differences in performance and robustness of deep learning models for synthetic CT generation were observed depending on the input. In-phase images outperformed opposed-phase images, and Dixon reconstructed multichannel inputs outperformed single-channel inputs.

Patch-based generative adversarial neural network models for head and neck MR-only planning

PURPOSE

To evaluate pix2pix and CycleGAN and to assess the effects of multiple combination strategies on accuracy for patch-based synthetic computed tomography (sCT) generation for magnetic resonance (MR)-only treatment planning in head and neck (HN) cancer patients.

MATERIALS AND METHODS

Twenty-three deformably registered pairs of CT and mDixon FFE MR datasets from HN cancer patients treated at our institution were retrospectively analyzed to evaluate patch-based sCT accuracy via the pix2pix and CycleGAN models. To test effects of overlapping sCT patches on estimations, we (a) trained the models for three orthogonal views to observe the effects of spatial context, (b) we increased effective set size by using per-epoch data augmentation, and (c) we evaluated the performance of three different approaches for combining overlapping Hounsfield unit (HU) estimations for varied patch overlap parameters. Twelve of twenty-three cases corresponded to a curated dataset previously used for atlas-based sCT generation and were used for training with leave-two-out cross-validation. Eight cases were used for independent testing and included previously unseen image features such as fused vertebrae, a small protruding bone, and tumors large enough to deform normal body contours. We analyzed the impact of MR image preprocessing including histogram standardization and intensity clipping on sCT generation accuracy. Effects of mDixon contrast (in-phase vs water) differences were tested with three additional cases. The sCT generation accuracy was evaluated using mean absolute error (MAE) and mean error (ME) in HU between the plan CT and sCT images. Dosimetric accuracy was evaluated for all clinically relevant structures in the independent testing set and digitally reconstructed radiographs (DRRs) were evaluated with respect to the plan CT images.

RESULTS

The cross-validated MAEs for the whole-HN region using pix2pix and CycleGAN were 66.9 ± 7.3 vs 82.3 ± 6.4 HU, respectively. On the independent testing set with additional artifacts and previously unseen image features, whole-HN region MAEs were 94.0 ± 10.6 and 102.9 ± 14.7 HU for pix2pix and CycleGAN, respectively. For patients with different tissue contrast (water mDixon MR images), the MAEs increased to 122.1 ± 6.3 and 132.8 ± 5.5 HU for pix2pix and CycleGAN, respectively. Our results suggest that combining overlapping sCT estimations at each voxel reduced both MAE and ME compared to single-view non-overlapping patch results. Absolute percent mean/max dose errors were 2% or less for the PTV and all clinically relevant structures in our independent testing set, including structures with image artifacts. Quantitative DRR comparison between planning CTs and sCTs showed agreement of bony region positions to <1 mm.

CONCLUSIONS

The dosimetric and MAE based accuracy, along with the similarity between DRRs from sCTs, indicate that pix2pix and CycleGAN are promising methods for MR-only treatment planning for HN cancer. Our methods investigated for overlapping patch-based HU estimations also indicate that combining transformation estimations of overlapping patches is a potential method to reduce generation errors while also providing a tool to potentially estimate the MR to CT aleatoric model transformation uncertainty. However, because of small patient sample sizes, further studies are required.

Magnetic resonance imaging sequence evaluation of an MR Linac system; early clinical experience

OBJECTIVES

To systematically identify the preferred magnetic resonance imaging (MRI) sequences following volunteer imaging on a 1.5 Tesla (T) MR-Linear Accelerator (MR Linac) for future protocol development.

METHODS

Non-patient volunteers were recruited to a Research and Ethics committee approved prospective MR-only imaging study on a 1.5T MR Linac system. Volunteers attended 1-3 imaging sessions that included a combination of mDixon, T1w, T2w sequences using 2-dimensional (2D) and 3-dimensional (3D) acquisitions. Each sequence was acquired over 2-7 minutes and reviewed by a panel of 3 observers to evaluate image quality using a visual grading analysis based on a 4-point Likert scale. Sequences were acquired and modified iteratively until deemed fit for purpose (online image matching or re-planning) and all observers agreed they were suitable in 3 volunteers.

RESULTS

26 volunteers underwent 31 imaging sessions of six general anatomical regions. Images were acquired in one or two of six general anatomical regions: male pelvis (n = 9), female pelvis (n = 4), chestwall/breast (n = 5), lung/oesophagus (n = 5), abdomen (n = 3) and head and neck (n = 5). Images were acquired using a pre-defined exam-card that on average, included six sequences (range 2-10), with a maximum scan time of approximately one hour. The majority of observers preferred T2-weighted sequences. The thorax teams were the only groups to prefer T1-weighted imaging.

CONCLUSIONS

An iterative process identified sequence agreement in all anatomical regions. These sequences will now be evaluated in patient volunteers.

ADVANCES IN KNOWLEDGE

This manuscript is the first publication sharing the results of the first systematic selection of MRI sequences for use in on-board MRI-guided radiotherapy by end-users (therapeutic radiographers and clinical oncologists) in healthy volunteers.

Synthetic CT Generation Based on T2 Weighted MRI of Nasopharyngeal Carcinoma (NPC) Using a Deep Convolutional Neural Network (DCNN)

Purpose: There is an emerging interest of applying magnetic resonance imaging (MRI) to radiotherapy (RT) due to its superior soft tissue contrast for accurate target delineation as well as functional information for evaluating treatment response. MRI-based RT planning has great potential to enable dose escalation to tumors while reducing toxicities to surrounding normal tissues in RT treatments of nasopharyngeal carcinoma (NPC). Our study aims to generate synthetic CT from T2-weighted MRI using a deep learning algorithm.

Methods: Thirty-three NPC patients were retrospectively selected for this study with local IRB's approval. All patients underwent clinical CT simulation and 1.5T MRI within the same week in our hospital. Prior to CT/MRI image registration, we had to normalize two different modalities to a similar intensity scale using the histogram matching method. Then CT and T2 weighted MRI were rigidly and deformably registered using intensity-based registration toolbox elastix (version 4.9). A U-net deep learning algorithm with 23 convolutional layers was developed to generate synthetic CT (sCT) using 23 NPC patients' images as the training set. The rest 10 NPC patients were used as the test set (~1/3 of all datasets). Mean absolute error (MAE) and mean error (ME) were calculated to evaluate HU differences between true CT and sCT in bone, soft tissue and overall region.

Results: The proposed U-net algorithm was able to create sCT based on T2-weighted MRI in NPC patients, which took 7 s per patient on average. Compared to true CT, MAE of sCT in all tested patients was 97 ± 13 Hounsfield Unit (HU) in soft tissue, 131 ± 24 HU in overall region, and 357 ± 44 HU in bone, respectively. ME was −48 ± 10 HU in soft tissue, −6 ± 13 HU in overall region, and 247 ± 44 HU in bone, respectively. The majority soft tissue and bone region was reconstructed accurately except the interface between soft tissue and bone and some delicate structures in nasal cavity, where the inaccuracy was induced by imperfect deformable registration. One patient example was shown with almost no difference in dose distribution using true CT vs. sCT in the PTV regions in the sinus area with fine bone structures.

Conclusion: Our study indicates that it is feasible to generate high quality sCT images based on T2-weighted MRI using the deep learning algorithm in patients with nasopharyngeal carcinoma, which may have great clinical potential for MRI-only treatment planning in the future.

Evaluation of proton and photon dose distributions recalculated on 2D and 3D Unet-generated pseudoCTs from T1-weighted MR head scans

Introduction: The recent developments of magnetic resonance (MR) based adaptive strategies for photon and, potentially for proton therapy, require a fast and reliable conversion of MR images to X-ray computed tomography (CT) values. CT values are needed for photon and proton dose calculation. The improvement of conversion results employing a 3D deep learning approach is evaluated. Material and methods: A database of 89 T1-weighted MR head scans with about 100 slices each, including rigidly registered CTs, was created. Twenty-eight validation patients were randomly sampled, and four patients were selected for application. The remaining patients were used to train a 2D and a 3D U-shaped convolutional neural network (Unet). A stack size of 32 slices was used for 3D training. For all application cases, volumetric modulated arc therapy photon and single-field uniform dose pencil-beam scanning proton plans at four different gantry angles were optimized for a generic target on the CT and recalculated on 2D and 3D Unet-based pseudoCTs. Mean (absolute) error (MAE/ME) and a gradient sharpness estimate were used to quantify the image quality. Three-dimensional gamma and dose difference analyses were performed for photon (gamma criteria: 1%, 1 mm) and proton dose distributions (gamma criteria: 2%, 2 mm). Range (80% fall off) differences for beam's eye view profiles were evaluated for protons. Results: Training 36 h for 1000 epochs in 3D (6 h for 200 epochs in 2D) yielded a maximum MAE of 147 HU (135 HU) for the application patients. Except for one patient gamma pass rates for photon and proton dose distributions were above 96% for both Unets. Slice discontinuities were reduced for 3D training at the cost of sharpness. Conclusions: Image analysis revealed a slight advantage of 2D Unets compared to 3D Unets. Similar dose calculation performance was reached for the 2D and 3D network.

MRI-Based Proton Treatment Planning for Base of Skull Tumors

Purpose

To introduce a novel, deep-learning method to generate synthetic computed tomography (SCT) scans for proton treatment planning and evaluate its efficacy.

Materials and Methods

50 Patients with base of skull tumors were divided into 2 nonoverlapping training and study cohorts. Computed tomography and magnetic resonance imaging pairs for patients in the training cohort were used for training our novel 3-dimensional generative adversarial network (cycleGAN) algorithm. Upon completion of the training phase, SCT scans for patients in the study cohort were predicted based on their magnetic resonance images only. The SCT scans obtained were compared against the corresponding original planning computed tomography scans as the ground truth, and mean absolute errors (in Hounsfield units [HU]) and normalized cross-correlations were calculated. Proton plans of 45 Gy in 25 fractions with 2 beams per plan were generated for the patients based on their planning computed tomographies and recalculated on SCT scans. Dose-volume histogram endpoints were compared. A γ-index analysis along 3 cardinal planes intercepting at the isocenter was performed. Proton distal range along each beam was calculated.

Results

Image quality metrics show agreement between the generated SCT scans and the ground truth with mean absolute error values ranging from 38.65 to 65.12 HU and an average of 54.55 ± 6.81 HU and a normalized cross-correlation average of 0.96 ± 0.01. The dosimetric evaluation showed no statistically significant differences (p > 0.05) within planning target volumes for dose-volume histogram endpoints and other metrics studied, with the exception of the dose covering 95% of the target volume, with a relative difference of 0.47%. The γ-index analysis showed an average passing rate of 98% with a 10% threshold and 2% and 2-mm criteria. Proton ranges of 48 of 50 beams (96%) in this study were within clinical tolerance adopted by 4 institutions.

Conclusions

This study shows our method is capable of generating SCT scans with acceptable image quality, dose distribution agreement, and proton distal range compared with the ground truth. Our results set a promising approach for magnetic resonance imaging-based proton treatment planning.

Dosimetric study for spine stereotactic body radiation therapy: magnetic resonance guided linear accelerator versus volumetric modulated arc therapy

Background Stereotactic body radiation therapy (SBRT) given in 1-5 fractions is an effective treatment for vertebral metastases. Real-time magnetic resonance-guided radiotherapy (MRgRT) improves soft tissue contrast, which translates into accurate delivery of spine SBRT. Here we report on clinical implementation of MRgRT for spine SBRT, the quality of MRgRT plans compared to TrueBeam based volumetric modulated arc therapy (VMAT) plans in the treatment of spine metastases and benefits of MRgRT MR scan. Patients and methods Ten metastatic lesions were included in this study for plan comparison. Lesions were spread across thoracic spine and lumbosacral spine. Three fraction spine SBRT plans: 27Gy to planning target volume (PTV) and 30Gy to gross tumor volume (GTV) were generated on the ViewRay MRIdian Linac system and compared to TrueBeamTM STx based VMAT plans. Plans were compared using metrics such as minimum dose, maximum dose, mean dose, ratio of the dose to 50% of the volume (R50), conformity index, homogeneity index and dose to the spinal cord. Results MRIdian plans achieved equivalent target coverage and spinal cord dose compared to VMAT plans. The maximum and minimum PTV doses and homogeneity index were equivalent for both planning systems. R50 was lower for MRIdian plans compared to VMAT plans, indicating a lower spread of intermediate doses with MRIdian system (5.16 vs. 6.11, p = 0.03). Conclusions MRgRT can deliver high-quality spine SBRT plans comparable to TrueBeam volumetric modulated arc therapy (VMAT) plans.

The rationale for MR-only treatment planning for external radiotherapy

•MR-only treatment planning could improve the spatial accuracy of radiotherapy.•The benefit compared to a mixed MR-CT workflow will vary between patient groups.•Further development of QA tools is needed before the procedure will save resources.

Chest Magnetic Resonance Imaging Decreases Inter-observer Variability of Gross Target Volume for Lung Tumors

Purpose: PET/CT is a standard medical imaging used in the delineation of gross tumor volume (GTV) in case of radiation therapy for lung tumors. However, PET/CT could present some limitations such as resolution and standardized uptake value threshold. Moreover, chest MRI has shown good potential in diagnosis for thoracic oncology. Therefore, we investigated the influence of chest MRI on inter-observer variability of GTV delineation.

Methods and Materials: Five observers contoured the GTV on CT for 14 poorly defined lung tumors during three contouring phases based on true daily clinical routine and acquisition: CT phase, with only CT images; PET phase, with PET/CT; and MRI phase, with both PET/CT and MRI. Observers waited at least 1 week between each phases to decrease memory bias. Contours were compared using descriptive statistics of volume, coefficient of variation (COV), and Dice similarity coefficient (DSC).

Results: MRI phase volumes (median 4.8 cm³) were significantly smaller than PET phase volumes (median 6.4 cm³, p = 0.015), but not different from CT phase volumes (median 5.7 cm³, p = 0.30). The mean COV was improved for the MRI phase (0.38) compared to the CT (0.58, p = 0.024) and PET (0.53, p = 0.060) phases. The mean DSC of the MRI phase (0.67) was superior to those of the CT and PET phases (0.56 and 0.60, respectively; p < 0.001 for both).

Conclusions: The addition of chest MRI seems to decrease inter-observer variability of GTV delineation for poorly defined lung tumors compared to PET/CT alone and should be explored in further prospective studies.

MRI basics for radiation oncologists

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Issues of MRI that are relevant for radiation oncologists are addressed.

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Radiation oncology requires dedicated scan protocols.

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Use of diagnostic protocols is not recommended for radiotherapy.

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MR images must be made in treatment position with the standard positioning devices.

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Safety screening prior to entering the MRI room is crucial.

MRI is increasingly used in radiation oncology to facilitate tumor and organ-at-risk delineation and image guidance. In this review, we address issues of MRI that are relevant for radiation oncologists when interpreting MR images offered for radiotherapy. Whether MRI is used in combination with CT or in an MRI-only workflow, it is generally necessary to ensure that MR images are acquired in treatment position, using the positioning and fixation devices that are commonly applied in radiotherapy. For target delineation, often a series of separate image sets are used with distinct image contrasts, acquired within a single exam. MR images can suffer from image distortions. While this can be avoided with dedicated scan protocols, in a diagnostic setting geometrical fidelity is less relevant and is therefore less accounted for. Since geometrical fidelity is of utmost importance in radiation oncology, it requires dedicated scan protocols. The strong magnetic field of an MRI scanner and the use of radiofrequency radiation can cause safety hazards if not properly addressed. Safety screening is crucial for every patient and every operator prior to entering the MRI room.

Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging

PURPOSE

The improved soft tissue contrast of magnetic resonance imaging (MRI) compared to computed tomography (CT) makes it a useful imaging modality for radiotherapy treatment planning. Even when MR images are acquired for treatment planning, the standard clinical practice currently also requires a CT for dose calculation and x-ray-based patient positioning. This increases workloads, introduces uncertainty due to the required inter-modality image registrations, and involves unnecessary irradiation. While it would be beneficial to use exclusively MR images, a method needs to be employed to estimate a synthetic CT (sCT) for generating electron density maps and patient positioning reference images. We investigated 2D and 3D convolutional neural networks (CNNs) to generate a male pelvic sCT using a T1-weighted MR image and compare their performance.

METHODS

A retrospective study was performed using CTs and T1-weighted MR images of 20 prostate cancer patients. CTs were deformably registered to MR images to create CT-MR pairs for training networks. The proposed 2D CNN, which contained 27 convolutional layers, was modified from the state-of-the-art 2D CNN to save computational memory and prepare for building the 3D CNN. The proposed 2D and 3D models were trained from scratch to map intensities of T1-weighted MR images to CT Hounsfield Unit (HU) values. Each sCT was generated in a fivefold cross-validation framework and compared with the corresponding deformed CT (dCT) using voxel-wise mean absolute error (MAE). The sCT geometric accuracy was evaluated by comparing bone regions, defined by thresholding at 150 HU in the dCTs and the sCTs, using dice similarity coefficient (DSC), recall, and precision. To evaluate sCT patient positioning accuracy, bone regions in dCTs and sCTs were rigidly registered to the corresponding cone-beam CTs. The resulting paired Euler transformation vectors were compared by calculating translation vector distances and absolute differences of Euler angles. Statistical tests were performed to evaluate the differences among the proposed models and Han's model.

RESULTS

Generating a pelvic sCT required approximately 5.5 s using the proposed models. The average MAEs within the body contour were 40.5 ± 5.4 HU (mean ± SD) and 37.6 ± 5.1 HU for the 2D and 3D CNNs, respectively. The average DSC, recall, and precision for the bone region (thresholding the CT at 150 HU) were 0.81 ± 0.04, 0.85 ± 0.04, and 0.77 ± 0.09 for the 2D CNN, and 0.82 ± 0.04, 0.84 ± 0.04, and 0.80 ± 0.08 for the 3D CNN, respectively. For both models, mean translation vector distances are less than 0.6 mm with mean absolute differences of Euler angles less than 0.5°.

CONCLUSIONS

The 2D and 3D CNNs generated accurate pelvic sCTs for the 20 patients using T1-weighted MR images. Statistical tests indicated that the proposed 3D model was able to generate sCTs with smaller MAE and higher bone region precision compared to 2D models. Results of patient alignment tests suggested that sCTs generated by the proposed CNNs can provide accurate patient positioning. The accuracy of the dose calculation using generated sCTs will be tested and compared for the proposed models in the future.

MR-based treatment planning in radiation therapy using a deep learning approach

Purpose

To develop and evaluate the feasibility of deep learning approaches for MR‐based treatment planning (deepMTP) in brain tumor radiation therapy.

Methods and materials

A treatment planning pipeline was constructed using a deep learning approach to generate continuously valued pseudo CT images from MR images. A deep convolutional neural network was designed to identify tissue features in volumetric head MR images training with co‐registered kVCT images. A set of 40 retrospective 3D T1‐weighted head images was utilized to train the model, and evaluated in 10 clinical cases with brain metastases by comparing treatment plans using deep learning generated pseudo CT and using an acquired planning kVCT. Paired‐sample Wilcoxon signed rank sum tests were used for statistical analysis to compare dosimetric parameters of plans made with pseudo CT images generated from deepMTP to those made with kVCT‐based clinical treatment plan (CTTP).

Results

deepMTP provides an accurate pseudo CT with Dice coefficients for air: 0.95 ± 0.01, soft tissue: 0.94 ± 0.02, and bone: 0.85 ± 0.02 and a mean absolute error of 75 ± 23 HU compared with acquired kVCTs. The absolute percentage differences of dosimetric parameters between deepMTP and CTTP was 0.24% ± 0.46% for planning target volume (PTV) volume, 1.39% ± 1.31% for maximum dose and 0.27% ± 0.79% for the PTV receiving 95% of the prescribed dose (V95). Furthermore, no significant difference was found for PTV volume (P = 0.50), the maximum dose (P = 0.83) and V95 (P = 0.19) between deepMTP and CTTP.

Conclusions

We have developed an automated approach (deepMTP) that allows generation of a continuously valued pseudo CT from a single high‐resolution 3D MR image and evaluated it in partial brain tumor treatment planning. The deepMTP provided dose distribution with no significant difference relative to a kVCT‐based standard volumetric modulated arc therapy plans.

Assessment of dosimetric and positioning accuracy of a magnetic resonance imaging-only solution for external beam radiotherapy of pelvic anatomy

BACKGROUND AND PURPOSE

The clinical feasibility of synthetic computed tomography (sCT) images derived from magnetic resonance imaging (MRI) images for external beam radiation therapy (EBRT) planning have been studied and adopted into clinical use recently. This paper evaluates the dosimetric and positioning performance of a sCT approach for different pelvic cancers.

MATERIALS AND METHODS

Seventy-five patients receiving EBRT at Turku University Hospital (Turku, Finland) were enrolled in the study. The sCT images were generated as part of a clinical MRI-simulation procedure. Dose calculation accuracy was assessed by comparing the sCT-based calculation with a CT-based calculation. In addition, we evaluated the patient position verification accuracy for both digitally reconstructed radiograph (DRR) and cone beam computed tomography (CBCT) -based image guidance using a subset of the cohort. Furthermore, the relevance of using continuous Hounsfield unit values was assessed.

RESULTS

The mean (standard deviation) relative dose difference in the planning target volume mean dose computed over various cancer groups was less than 0.2 (0.4)% between sCT and CT. Among all groups, the average minimum gamma-index pass-rates were better than 95% with a 2%/2mm gamma-criteria. The difference between sCT- and CT-DRR-based patient positioning was less than 0.3 (1.4) mm in all directions. The registrations of sCT to CBCT produced similar results as compared with CT to CBCT registrations.

CONCLUSIONS

The use of sCT for clinical EBRT dose calculation and patient positioning in the investigated types of pelvic cancers was dosimetrically and geometrically accurate for clinical use.

Development of a contouring guide for three different types of optic chiasm: A practical approach

INTRODUCTION

Sparing of the organs at risk (OARs) is a crucial task in daily radiotherapy practice. Irradiation of the optic chiasm (OC) results in radiation-induced optic neuropathy (RION). The structure of the OC is complex, and OC morphology can vary in axial images. Therefore, a standard atlas can result in inaccurate descriptions of OC morphology in different patients. The aim of our study was to provide a guide based on computed tomography (CT) for the delineation of different types of OC.

METHODS

Thirty-six patients were selected to participate in our study. These patients underwent CT analysis of the brain, head and neck regions in a supine position. Axial images 3 mm in thickness were obtained at 3-mm intervals. A magnetic resonance imaging (MRI) study was also performed using the same set-up. The OC was then delineated. The contours were revised by three neuroradiologists and nine radiation oncologists with > 5 years of expertise.

RESULTS

Three types of OC were distinguished by magnetic resonance (MR). The location and boundaries of normal, prefixed and postfixed chiasms were developed with a CT-based atlas. Discrepancies were observed in the delineation of the prefixed and postfixed OC.

CONCLUSIONS

Our guide allows improved definitions of the anatomical boundaries for different types of OC. Our experience could provide useful information for radiation oncologists in daily practice.

Keeping Up with the Hybrid Magnetic Resonance Linear Accelerators: How Do Radiation Therapists Stay Current in the Era of Hybrid Technologies?

The benefits of integrating magnetic resonance imaging (MRI) into radiotherapy planning have long been extolled, first appearing in the literature as early as 1986. Most often described as a tool to be used when registered to a planning computed tomography to improve target and organ at risk delineation, the use of MRI for on-board image guidance and as a sole imaging modality throughout the entire radiotherapy pathway is quickly becoming a reality for appropriately selected patient populations in academic centres throughout the world. With the commercialization of these integrated magnetic resonance - radiotherapy delivery systems, an MRI-only workflow will prove beneficial, with MRI being used for treatment planning, localization, and on-treatment plan adaptation. Despite these technological advancements, recent surveys indicate uptake of MRI in radiotherapy as a routine practice has proven challenging. Reasons cited for this slow uptake were primarily related to health economics and/or accessibility. Furthermore, these surveys, like much of the academic literature, shy away from focusing on safe, sustainable staffing models enabled by comprehensive and appropriate education and training. In stark contrast to conebeam computed tomography guided therapy, magnetic resonance - radiotherapy systems are currently being operated by teams of physicians, radiographers, and physicists because of the diverse and complex tasks required to deliver treatment. The pace of innovation in RT remains high and unfortunately the window of opportunity to implement appropriate education continues to narrow. It is vital that we establish a framework to future-proof our profession. In the era of magnetic resonance-guided radiotherapy, we have yet to address the question of how to devise a consensus on the requisite knowledge, skills, and competence for radiation therapists and therapy radiographers using and/or operating MRI that provides guidance, without becoming prohibitively costly or time consuming.

Basic concepts and applications of functional magnetic resonance imaging for radiotherapy of prostate cancer

Recently, the interest to integrate magnetic resonance imaging (MRI) in radiotherapy for prostate cancer has increased considerably. MRI can contribute in all steps of the radiotherapy workflow from diagnosis, staging, and target definition to treatment follow-up. Of particular interest is the ability of MRI to provide a wide range of functional measures. The complexity of MRI as an imaging modality combined with the growing interest of the application to prostate cancer radiotherapy, emphasize the need for dedicated education within the radiation oncology community. In this context, an overview of the most common as well as a few upcoming functional MR imaging techniques is presented: the basic methodology and measurement is described, the link between the functional measures and the underlying biology is established, and finally relevant applications of functional MRI useful for prostate cancer radiotherapy are given.

Dose evaluation of MRI-based synthetic CT generated using a machine learning method for prostate cancer radiotherapy

Magnetic resonance imaging (MRI)-only radiotherapy treatment planning is attractive since MRI provides superior soft tissue contrast over computed tomographies (CTs), without the ionizing radiation exposure. However, it requires the generation of a synthetic CT (SCT) from MRIs for patient setup and dose calculation. In this study, we aim to investigate the accuracy of dose calculation in prostate cancer radiotherapy using SCTs generated from MRIs using our learning-based method. We retrospectively investigated a total of 17 treatment plans from 10 patients, each having both planning CTs (pCT) and MRIs acquired before treatment. The SCT was registered to the pCT for generating SCT-based treatment plans. The original pCT-based plans served as ground truth. Clinically-relevant dose volume histogram (DVH) metrics were extracted from both ground truth and SCT-based plans for comparison and evaluation. Gamma analysis was performed for the comparison of absorbed dose distributions between SCT- and pCT-based plans of each patient. Gamma analysis of dose distribution on pCT and SCT within 1%/1 mm at 10% dose threshold showed greater than 99% pass rate. The average differences in DVH metrics for planning target volumes (PTVs) were less than 1%, and similar metrics for organs at risk (OAR) were not statistically different. The SCT images created from MR images using our proposed machine learning method are accurate for dose calculation in prostate cancer radiation treatment planning. This study also demonstrates the great potential for MRI to completely replace CT scans in the process of simulation and treatment planning. However, MR images are needed to further analyze geometric distortion effects. Digitally reconstructed radiograph (DRR) can be generated within our method, and their accuracy in patient setup needs further analysis.

Assessment of the Impact of Deformable Registration of Diagnostic MRI to Planning CT on GTV Delineation for Radiotherapy for Oropharyngeal Carcinoma in Routine Clinical Practice

Background: Aim of study was to assess impact of deformable registration of diagnostic MRI to planning CT upon gross tumour volume (GTV) delineation of oropharyngeal carcinoma in routine practice. Methods: 22 consecutive patients with oropharyngeal squamous cell carcinoma treated with definitive (chemo)radiotherapy between 2015 and 2016, for whom primary GTV delineation had been performed by a single radiation oncologist using deformable registration of diagnostic MRI to planning CT, were identified. Separate GTVs were delineated as part of routine clinical practice (all diagnostic imaging available side-by-side for each delineation) using: CT (GTV_CT), MRI (GTV_MR), and CT and MRI (GTV_CTMR). Volumetric and positional metric analyses were undertaken using contour comparison metrics (Dice conformity index, centre of gravity distance, mean distance to conformity). Results: Median GTV volumes were 13.7 cm³ (range 3.5–41.7), 15.9 cm³ (range 1.6–38.3), 19.9 cm³ (range 5.5–44.5) for GTV_CT, GTV_MR and GTV_CTMR respectively. There was no significant difference in GTV_CT and GTV_MR volumes; GTV_CTMR was found to be significantly larger than both GTV_MR and GTV_CT. Based on positional metrics, GTV_CT and GTV_MR were the least similar (mean Dice similarity coefficient (DSC) 0.71, 0.84, 0.82 for GTV_CT–GTV_MR, GTV_CTMR–GTV_CT and GTV_CTMR–GTV_MR respectively). Conclusions: These data suggest a complementary role of MRI to CT to reduce the risk of geographical misses, although they highlight the potential for larger target volumes and hence toxicity.

Feasibility of magnetic resonance imaging-only rectum radiotherapy with a commercial synthetic computed tomography generation solution

Background and purpose

Synthetic computed tomography (sCT) images enable magnetic resonance (MR)-based dose calculations. This work investigated whether a commercially available sCT generation solution was suitable for accurate dose calculations and position verification on patients with rectal cancer.

Material and methods

For twenty rectal cancer patients computed tomography (CT) images were rigidly registered to sCT images. Clinical volumetric modulated arc therapy plans were recalculated on registered CT and sCT images. Dose deviations were determined through gamma and voxelwise analysis. The impact on position verification was investigated by identifying differences in translations and rotation between cone-beam CT (CBCT) to CT and CBCT to sCT registrations.

Results

Across twenty patients, within a threshold of 90% of the prescription dose, a gamma analysis (2%, 2 mm) mean pass rate of 95.2 ± 4.0% (±1σ) and mean dose deviation of −0.3 ± 0.2% of prescription dose were obtained. The mean difference of translations and rotations over ten patients (76 CBCTs) was <1 mm and <0.5° in all directions. In the sole posterior-anterior direction a mean systematic shift of 0.7 ± 0.6 mm was found.

Conclusions

Accurate MR-based dose calculations using a commercial sCT generation method were clinically feasible for treatment of rectal cancer patients. The accuracy of position verification was clinically acceptable. However, before clinical implementation future investigations will be performed to determine the origin of the systematic shift.

Magnetic Resonance Imaging only Workflow for Radiotherapy Simulation and Planning in Prostate Cancer

Magnetic resonance imaging (MRI) is often combined with computed tomography (CT) in prostate radiotherapy to optimise delineation of the target and organs-at-risk (OAR) while maintaining accurate dose calculation. Such a dual-modality workflow requires two separate imaging sessions, and it has some fundamental and logistical drawbacks. Due to the availability of new MRI hardware and software solutions, CT examinations can be omitted for prostate radiotherapy simulations. All information for treatment planning, including electron density maps and bony anatomy, can nowadays be obtained with MRI. Such an MRI-only simulation workflow reduces delineation ambiguities, eases planning logistics, and improves patient comfort; however, careful validation of the complete MRI-only workflow is warranted. The first institutes are now adopting this MRI-only workflow for prostate radiotherapy. In this article, we will review technology and workflow requirements for an MRI-only prostate simulation workflow.

Geometric and dosimetric evaluations of atlas-based segmentation methods of MR images in the head and neck region

Owing to its excellent soft-tissue contrast, magnetic resonance (MR) imaging has found an increased application in radiation therapy (RT). By harnessing these properties for treatment planning, automated segmentation methods can alleviate the manual workload burden to the clinical workflow. We investigated atlas-based segmentation methods of organs at risk (OARs) in the head and neck (H&N) region using one approach that selected the most similar atlas from a library of segmented images and two multi-atlas approaches. The latter were based on weighted majority voting and an iterative atlas-fusion approach called STEPS. We built the atlas library from pre-treatment T1-weighted MR images of 12 patients with manual contours of the parotids, spinal cord and mandible, delineated by a clinician. Following a leave-one-out cross-validation strategy, we measured the geometric accuracy by calculating Dice similarity coefficients (DSC), standard and 95% Hausdorff distances (HD and HD95), and the mean surface distance (MSD), whereby the manual contours served as the gold standard. To benchmark the algorithm, we determined the inter-observer variability (IOV) between three observers. To investigate the dosimetric effect of segmentation inaccuracies, we implemented an auto-planning strategy within the treatment planning system Monaco (Elekta AB, Stockholm, Sweden). For each set of auto-segmented OARs, we generated a plan for a 9-beam step and shoot intensity modulated RT treatment, designed according to our institution's clinical H&N protocol. Superimposing the dose distributions on the gold standard OARs, we calculated dose differences to OARs caused by delineation differences between auto-segmented and gold standard OARs. We investigated the correlations between geometric and dosimetric differences. The mean DSC was larger than 0.8 and the mean MSD smaller than 2 mm for the multi-atlas approaches, resulting in a geometric accuracy comparable to previously published results and within the range of the IOV. While dosimetric differences could be as large as 23% of the clinical goal, treatment plans fulfilled all imposed clinical goals for the gold standard OARs. Correlations between geometric and dosimetric measures were low with R2  <  0.5. The geometric accuracy and the ability to achieve clinically acceptable treatment plans indicate the suitability of using atlas-based contours for RT treatment planning purposes. The low correlations between geometric and dosimetric measures suggest that geometric measures alone are not sufficient to predict the dosimetric impact of segmentation inaccuracies on treatment planning for the data utilised in this study.

Geometric and dosimetric evaluations of atlas-based segmentation methods of MR images in the head and neck region

Owing to its excellent soft-tissue contrast, magnetic resonance (MR) imaging has found an increased application in radiation therapy (RT). By harnessing these properties for treatment planning, automated segmentation methods can alleviate the manual workload burden to the clinical workflow. We investigated atlas-based segmentation methods of organs at risk (OARs) in the head and neck (H&N) region using one approach that selected the most similar atlas from a library of segmented images and two multi-atlas approaches. The latter were based on weighted majority voting and an iterative atlas-fusion approach called STEPS. We built the atlas library from pre-treatment T1-weighted MR images of 12 patients with manual contours of the parotids, spinal cord and mandible, delineated by a clinician. Following a leave-one-out cross-validation strategy, we measured the geometric accuracy by calculating Dice similarity coefficients (DSC), standard and 95% Hausdorff distances (HD and HD95), and the mean surface distance (MSD), whereby the manual contours served as the gold standard. To benchmark the algorithm, we determined the inter-observer variability (IOV) between three observers. To investigate the dosimetric effect of segmentation inaccuracies, we implemented an auto-planning strategy within the treatment planning system Monaco (Elekta AB, Stockholm, Sweden). For each set of auto-segmented OARs, we generated a plan for a 9-beam step and shoot intensity modulated RT treatment, designed according to our institution's clinical H&N protocol. Superimposing the dose distributions on the gold standard OARs, we calculated dose differences to OARs caused by delineation differences between auto-segmented and gold standard OARs. We investigated the correlations between geometric and dosimetric differences. The mean DSC was larger than 0.8 and the mean MSD smaller than 2 mm for the multi-atlas approaches, resulting in a geometric accuracy comparable to previously published results and within the range of the IOV. While dosimetric differences could be as large as 23% of the clinical goal, treatment plans fulfilled all imposed clinical goals for the gold standard OARs. Correlations between geometric and dosimetric measures were low with R²  <  0.5. The geometric accuracy and the ability to achieve clinically acceptable treatment plans indicate the suitability of using atlas-based contours for RT treatment planning purposes. The low correlations between geometric and dosimetric measures suggest that geometric measures alone are not sufficient to predict the dosimetric impact of segmentation inaccuracies on treatment planning for the data utilised in this study.

MRI-only based radiation therapy of prostate cancer: workflow and early clinical experience

BACKGROUND

Magnetic resonance imaging (MRI) is the most comprehensive imaging modality for radiation therapy (RT) target delineation of most soft tissue tumors including prostate cancer. We have earlier presented step by step the MRI-only based workflow for RT planning and image guidance for localized prostate cancer. In this study we present early clinical experiences of MRI-only based planning.

MATERIAL AND METHODS

We have analyzed the technical planning workflow of the first 200 patients having received MRI-only planned radiation therapy for localized prostate cancer in Helsinki University Hospital Cancer center. Early prostate specific antigen (PSA) results were analyzed from n = 125 MRI-only patients (n = 25 RT only, n = 100 hormone treatment + RT) and were compared with the corresponding computed tomography (CT) planned patient group.

RESULTS

Technically the MRI-only planning procedure was suitable for 92% of the patients, only 8% of the patients required supplemental CT imaging. Early PSA response in the MRI-only planned group showed similar treatment results compared with the CT planned group and with an equal toxicity level.

CONCLUSION

Based on this retrospective study, MRI-only planning procedure is an effective and safe way to perform RT for localized prostate cancer. It is suitable for the majority of the patients.

Evaluation of gold fiducial marker manual localisation for magnetic resonance-only prostate radiotherapy

BACKGROUND

The use of intraprostatic gold fiducial markers (FMs) ensures highly accurate and precise image-guided radiation therapy for patients diagnosed with prostate cancer thanks to the ease of localising FMs on photon-based imaging, like Computed Tomography (CT) images. Recently, Magnetic Resonance (MR)-only radiotherapy has been proposed to simplify the workflow and reduce possible systematic uncertainties. A critical, determining factor in the accuracy of such an MR-only simulation will be accurate FM localisation using solely MR images.

PURPOSE

The aim of this study is to evaluate the performances of manual MR-based FM localisation within a clinical environment.

METHODS

We designed a study in which 5 clinically involved radiation therapy technicians (RTTs) independently localised the gold FMs implanted in 16 prostate cancer patients in two scenarios: employing a single MR sequence or a combination of sequences. Inter-observer precision and accuracy were assessed for the two scenarios for localisation in terms of 95% limit of agreement on single FMs (LoA)/ centre of mass (LoA _CM) and inter-marker distances (IDs), respectively.

RESULTS

The number of precisely located FMs (LoA <2 mm) increased from 38/48 to 45/48 FMs when localisation was performed using multiple sequences instead of single one. When performing localisation on multiple sequences, imprecise localisation of the FMs (3/48 FMs) occurred for 1/3 implanted FMs in three different patients. In terms of precision, we obtained LoA _CM within 0.25 mm in all directions over the precisely located FMs. In terms of accuracy, IDs difference of manual MR-based localisation versus CT-based localisation was on average (±1 STD) 0.6 ±0.6 mm.

CONCLUSIONS

For both the investigated scenarios, the results indicate that when FM classification was correct, the precision and accuracy are high and comparable to CT-based FM localisation. We found that use of multiple sequences led to better localisation performances compared with the use of single sequence. However, we observed that, due to the presence of calcification and motion, the risk of mislocated patient positioning is still too high to allow the sole use of manual FM localisation. Finally, strategies to possibly overcome the current challenges were proposed.

Feasibility of polymer gel-based measurements of radiation isocenter accuracy in magnetic fields

For conventional irradiation devices, the radiation isocenter accuracy is determined by star shot measurements on films. In magnetic resonance (MR)-guided radiotherapy devices, the results of this test may be altered by the magnetic field and the need to align the radiation and imaging isocenter may require a modification of measurement procedures. Polymer dosimetry gels (PG) may offer a way to perform both, the radiation and imaging isocenter test, however, first it has to be shown that PG reveal results comparable to the conventionally applied films. Therefore, star shot measurements were performed at a linear accelerator using PG as well as radiochromic films. PG were evaluated using MR imaging and the isocircle radius and the distance between the isocircle center and the room isocenter were determined. Two different types of experiments were performed: i) a standard star-shot isocenter test and (ii) a star shot, where the detectors were placed between the pole shoes of an experimental electro magnet operated either at 0 T or 1 T. For the standard star shot, PG evaluation was independent of the time delay after irradiation (1 h, 24 h, 48 h and 216 h) and the results were comparable to those of film measurements. Within the electro magnet, the isocircle radius increased from 0.39  ±  0.01 mm to 1.37  ±  0.01 mm for the film and from 0.44  ±  0.02 mm to 0.97  ±  0.02 mm for the PG-measurements, respectively. The isocenter distance was essentially dependent on the alignment of the magnet to the isocenter and was between 0.12  ±  0.02 mm and 0.82  ±  0.02 mm. The study demonstrates that evaluation of the PG directly after irradiation is feasible, if only geometrical parameters are of interest. This allows using PG for star shot measurements to evaluate the radiation isocenter accuracy with comparable accuracy as with radiochromic films.

Molecular Imaging-Guided Radiotherapy for the Treatment of Head-and-Neck Squamous Cell Carcinoma: Does it Fulfill the Promises?

With the routine use of intensity modulated radiation therapy for the treatment of head-and-neck squamous cell carcinoma allowing highly conformed dose distribution, there is an increasing need for refining both the selection and the delineation of gross tumor volumes (GTV). In this framework, molecular imaging with positron emission tomography and magnetic resonance imaging offers the opportunity to improve diagnostic accuracy and to integrate tumor biology mainly related to the assessment of tumor cell density, tumor hypoxia, and tumor proliferation into the treatment planning equation. Such integration, however, requires a deep comprehension of the technical and methodological issues related to image acquisition, reconstruction, and segmentation. Until now, molecular imaging has had a limited value for the selection of nodal GTV, but there are increasing evidences that both FDG positron emission tomography and diffusion-weighted magnetic resonance imaging has a potential value for the delineation of the primary tumor GTV, effecting on dose distribution. With the apprehension of the heterogeneity in tumor biology through molecular imaging, growing evidences have been collected over the years to support the concept of dose escalation/dose redistribution using a planned heterogeneous dose prescription, the so-called "dose painting" approach. Validation trials are ongoing, and in the coming years, one may expect to position the dose painting approach in the armamentarium for the treatment of patients with head-and-neck squamous cell carcinoma.

The role of imaging in the clinical practice of radiation oncology for pancreatic cancer

Advances in technology have enabled the delivery of high doses of radiation therapy for pancreatic ductal adenocarcinoma (PDAC) with low rates of toxicity. Although the role of radiation for pancreatic cancer continues to evolve, encouraging results with newer techniques indicate that radiation may benefit selected patient populations. Imaging has been central to the modern successes of radiation therapy for PDAC. Here, we review the role of diagnostic imaging, imaging-based planning, and image guidance in radiation oncology practice for PDAC.

Feasibility of MR-only proton dose calculations for prostate cancer radiotherapy using a commercial pseudo-CT generation method

A magnetic resonance (MR)-only radiotherapy workflow can reduce cost, radiation exposure and uncertainties introduced by CT-MRI registration. A crucial prerequisite is generating the so called pseudo-CT (pCT) images for accurate dose calculation and planning. Many pCT generation methods have been proposed in the scope of photon radiotherapy. This work aims at verifying for the first time whether a commercially available photon-oriented pCT generation method can be employed for accurate intensity-modulated proton therapy (IMPT) dose calculation. A retrospective study was conducted on ten prostate cancer patients. For pCT generation from MR images, a commercial solution for creating bulk-assigned pCTs, called MR for Attenuation Correction (MRCAT), was employed. The assigned pseudo-Hounsfield Unit (HU) values were adapted to yield an increased agreement to the reference CT in terms of proton range. Internal air cavities were copied from the CT to minimise inter-scan differences. CT- and MRCAT-based dose calculations for opposing beam IMPT plans were compared by gamma analysis and evaluation of clinically relevant target and organ at risk dose volume histogram (DVH) parameters. The proton range in beam's eye view (BEV) was compared using single field uniform dose (SFUD) plans. On average, a [Formula: see text] mm) gamma pass rate of 98.4% was obtained using a [Formula: see text] dose threshold after adaptation of the pseudo-HU values. Mean differences between CT- and MRCAT-based dose in the DVH parameters were below 1 Gy ([Formula: see text]). The median proton range difference was [Formula: see text] mm, with on average 96% of all BEV dose profiles showing a range agreement better than 3 mm. Results suggest that accurate MR-based proton dose calculation using an automatic commercial bulk-assignment pCT generation method, originally designed for photon radiotherapy, is feasible following adaptation of the assigned pseudo-HU values.

Automated, reference-free local error assessment of multimodal deformable image registration for radiotherapy in the head and neck

BACKGROUND

Head and neck MR-CT deformable image registration (DIR) for radiotherapy planning is hindered by the lack of both ground-truth and per-patient accuracy assessment methods. This study assesses novel post-registration reference-free error assessment algorithms, based on local rigid re-registration of native and pseudomodality images.

METHODS

Head and neck MR obtained in and out of the treatment position underwent DIR to planning CT. Block-wise mutual information (b-MI) and pseudomodality mutual information (b-pmMI) algorithms were validated against applied rotations and translations. Inherent registration error detection was compared across 14 patient datasets.

RESULTS

Using radiotherapy position MR-CT DIR, quantitative comparison of applied rotations and translations revealed that errors between 1 and 4 mm were accurately determined by both algorithms. Using diagnostic position MR-CT DIR, translations of up to 5 mm were accurately detected within the gross tumour volume by both methods. In 14 patient datasets, b-MI and b-pmMI detected similar errors with improved stability in regions of low contrast or CT artefact and a 10-fold speedup for b-pmMI.

CONCLUSIONS

b-MI and b-pmMI algorithms have been validated as providing accurate reference-free quantitative assessment of DIR accuracy on a per-patient basis. b-pmMI is faster and more robust in the presence of modality-specific information.

Adaptive radiation dose escalation in rectal adenocarcinoma: a review

Total mesorectal excision (TME) after neoadjuvant chemoradiotherapy (CRT) has offered superior control for patients with locally advanced rectal cancer, but can carry a quality of life cost. Fortunately, some patients achieve a complete response after CRT alone without the added morbidity caused by surgery. Efforts to increase fidelity of radiation treatment planning and delivery may allow for escalated doses of radiotherapy (RT) with limited off-target toxicity and elicit more pathological complete responses (pCR) to CRT thereby sparing more rectal cancer patients from surgery. In this review, methods of delivering escalated RT boost above 45-50.4 Gy are discussed including: 3D conformal, intensity-modulated radiotherapy (IMRT), and brachytherapy. Newly developed adaptive boost strategies and imaging modalities used in RT planning and response evaluation such as magnetic resonance imaging (MRI) and positron emission tomography (PET) are also discussed.

Systematic Review of Synthetic Computed Tomography Generation Methodologies for Use in Magnetic Resonance Imaging-Only Radiation Therapy

Magnetic resonance imaging (MRI) offers superior soft-tissue contrast as compared with computed tomography (CT), which is conventionally used for radiation therapy treatment planning (RTP) and patient positioning verification, resulting in improved target definition. The 2 modalities are co-registered for RTP; however, this introduces a systematic error. Implementing an MRI-only radiation therapy workflow would be advantageous because this error would be eliminated, the patient pathway simplified, and patient dose reduced. Unlike CT, in MRI there is no direct relationship between signal intensity and electron density; however, various methodologies for MRI-only RTP have been reported. A systematic review of these methods was undertaken. The PRISMA guidelines were followed. Embase and Medline databases were searched (1996 to March, 2017) for studies that generated synthetic CT scans (sCT)s for MRI-only radiation therapy. Sixty-one articles met the inclusion criteria. This review showed that MRI-only RTP techniques could be grouped into 3 categories: (1) bulk density override; (2) atlas-based; and (3) voxel-based techniques, which all produce an sCT scan from MR images. Bulk density override techniques either used a single homogeneous or multiple tissue override. The former produced large dosimetric errors (>2%) in some cases and the latter frequently required manual bone contouring. Atlas-based techniques used both single and multiple atlases and included methods incorporating pattern recognition techniques. Clinically acceptable sCTs were reported, but atypical anatomy led to erroneous results in some cases. Voxel-based techniques included methods using routine and specialized MRI sequences, namely ultra-short echo time imaging. High-quality sCTs were produced; however, use of multiple sequences led to long scanning times increasing the chances of patient movement. Using nonroutine sequences would currently be problematic in most radiation therapy centers. Atlas-based and voxel-based techniques were found to be the most clinically useful methods, with some studies reporting dosimetric differences of <1% between planning on the sCT and CT and <1-mm deviations when using sCTs for positional verification.

Magnetic resonance only workflow and validation of dose calculations for radiotherapy of prostate cancer

BACKGROUND

Current state of the art radiotherapy planning of prostate cancer utilises magnetic resonance (MR) for soft tissue delineation and computed tomography (CT) to provide an electron density map for dose calculation. This dual scan workflow is prone to setup and registration error. This study evaluates the feasibility of an MR-only workflow and the validity of dose calculation from an MR derived pseudo CT.

MATERIAL AND METHODS

Thirty prostate cancer patients were CT and MR scanned. Clinical treatment plans were generated on CT using a single 18 MV arc volumetric modulated arc therapy (VMAT) with a prescription of 78 Gy/39 fractions. Dose was recalculated on pseudo CT and assuming uniform water density. Pseudo CT and uniform density based dose calculations were compared to CT dose calculations by gamma analysis. One patient was treated with a plan based solely on MR and pseudo CT including daily image guided radiotherapy (IGRT) performed by manual match of implanted gold markers.

RESULTS

A pseudo CT was generated for 29 of the 30 patients. Median gamma pass rates for 1%/1 mm passing criteria for dose calculated on pseudo CT when compared to CT were 100% for most evaluated structures. Dose calculated on uniform density also yielded high median pass rates, but with a higher occurrence of pass rates below 95%. Cases of pass rate below 95% on pseudo CT proved to originate from the presence of rectal air on CT, not represented by the pseudo CT. Treatment based on MR alone was successfully delivered to one patient, including manually performed daily IGRT.

CONCLUSIONS

Median gamma pass rates were high for pseudo CT and proved superior to uniform density. Local differences in dose calculations were concluded not to have clinical relevance. Feasibility of the MR-only workflow was demonstrated through successful delivery of a treatment course planned based on MR alone.

MRI micturating urethrography for improved urethral delineation in prostate radiotherapy planning: a case study

Stereotactic ablative body radiotherapy is used in prostate cancer to deliver a high dose of radiation to the tumour over a small number of treatments. This involves the simulation of the patient using both CT and MRI. Current practice is to insert an indwelling catheter (IDC) during CT to assist with visualisation of the urethra and subsequently minimise dose to this highly critical structure. However, this procedure is invasive and has an associated risk of infection. This is a case study, which demonstrates our initial experience of using a real-time non-invasive MRI technique to replace the use of IDC for prostate cancer patients. The patient was scanned on a dedicated 3T MRI and was instructed to micturate in their own time whereupon a sagittal T2 weighted HASTE sequence was acquired every 5 s. This was subsequently followed by T2 weighted axial imaging at the level of mid prostate to provide improved urethral definition. Acquired images showed bladder voidance in real-time and an increase in signal intensity in the proximal urethra post voiding allowing for delineation of the urethra. The dimension and shape of the proximal urethra was well visualised and accumulation time of urine in the urethra was sufficient to enable optimum timing of the scanning technique. We have presented for the first time a micturating urethography technique using MRI, which has allowed us to visualise the urethra without contrast and with minimal invasiveness to the patient.

Feasibility of MRI-only treatment planning for proton therapy in brain and prostate cancers: Dose calculation accuracy in substitute CT images

PURPOSE

Magnetic resonance imaging (MRI) is increasingly used for radiotherapy target delineation, image guidance, and treatment response monitoring. Recent studies have shown that an entire external x-ray radiotherapy treatment planning (RTP) workflow for brain tumor or prostate cancer patients based only on MRI reference images is feasible. This study aims to show that a MRI-only based RTP workflow is also feasible for proton beam therapy plans generated in MRI-based substitute computed tomography (sCT) images of the head and the pelvis.

METHODS

The sCTs were constructed for ten prostate cancer and ten brain tumor patients primarily by transforming the intensity values of in-phase MR images to Hounsfield units (HUs) with a dual model HU conversion technique to enable heterogeneous tissue representation. HU conversion models for the pelvis were adopted from previous studies, further extended in this study also for head MRI by generating anatomical site-specific conversion models (a new training data set of ten other brain patients). This study also evaluated two other types of simplified sCT: dual bulk density (for bone and water) and homogeneous (water only). For every clinical case, intensity modulated proton therapy (IMPT) plans robustly optimized in standard planning CTs were calculated in sCT for evaluation, and vice versa. Overall dose agreement was evaluated using dose-volume histogram parameters and 3D gamma criteria.

RESULTS

In heterogeneous sCTs, the mean absolute errors in HUs were 34 (soft tissues: 13, bones: 92) and 42 (soft tissues: 9, bones: 97) in the head and in the pelvis, respectively. The maximum absolute dose differences relative to CT in the brain tumor clinical target volume (CTV) were 1.4% for heterogeneous sCT, 1.8% for dual bulk sCT, and 8.9% for homogenous sCT. The corresponding maximum differences in the prostate CTV were 0.6%, 1.2%, and 3.6%, respectively. The percentages of dose points in the head and pelvis passing 1% and 1 mm gamma index criteria were over 91%, 85%, and 38% with heterogeneous, dual bulk, and homogeneous sCTs, respectively. There were no significant changes to gamma index pass rates for IMPT plans first optimized in CT and then calculated in heterogeneous sCT versus IMPT plans first optimized in heterogeneous sCT and then calculated on standard CT.

CONCLUSIONS

This study demonstrates that proton therapy dose calculations on heterogeneous sCTs are in good agreement with plans generated with standard planning CT. An MRI-only based RTP workflow is feasible in IMPT for brain tumors and prostate cancers.

The integration of MRI in radiation therapy: collaboration of radiographers and radiation therapists

The increased utilisation of magnetic resonance imaging (MRI) in radiation therapy (RT) has led to the implementation of MRI simulators for RT treatment planning and influenced the development of MRI-guided treatment systems. There is extensive literature on the advantages of MRI for tumour volume and organ-at-risk delineation compared to computed tomography. MRI provides both anatomical and functional information for RT treatment planning (RTP) as well as quantitative information to assess tumour response for adaptive treatment. Despite many advantages of MRI in RT, introducing an MRI simulator into a RT department is a challenge. Collaboration between radiographers and radiation therapists is paramount in making the best use of this technology. The cross-disciplinary training of radiographers and radiation therapists alike is an area rarely discussed; however, it is becoming an important requirement due to detailed imaging needs for advanced RT treatment techniques and with the emergence of hybrid treatment systems. This article will discuss the initial experiences of a radiation oncology department in implementing a dedicated MRI simulator for RTP, with a focus on the training required for both radiographer and RT staff. It will also address the future of MRI in RT and the implementation of MRI-guided treatment systems, such as MRI-Linacs, and the role of both radiation therapists and radiographers in this technology.

Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI

BACKGROUND

Radiomics or computer - extracted texture features have been shown to achieve superior performance than multiparametric MRI (mpMRI) signal intensities alone in targeting prostate cancer (PCa) lesions. Radiomics along with deformable co-registration tools can be used to develop a framework to generate targeted focal radiotherapy treatment plans.

METHODS

The Rad-TRaP framework comprises three distinct modules. Firstly, a module for radiomics based detection of PCa lesions on mpMRI via a feature enabled machine learning classifier. The second module comprises a multi-modal deformable co-registration scheme to map tissue, organ, and delineated target volumes from MRI onto CT. Finally, the third module involves generation of a radiomics based dose plan on MRI for brachytherapy and on CT for EBRT using the target delineations transferred from the MRI to the CT.

RESULTS

Rad-TRaP framework was evaluated using a retrospective cohort of 23 patient studies from two different institutions. 11 patients from the first institution were used to train a radiomics classifier, which was used to detect tumor regions in 12 patients from the second institution. The ground truth cancer delineations for training the machine learning classifier were made by an experienced radiation oncologist using mpMRI, knowledge of biopsy location and radiology reports. The detected tumor regions were used to generate treatment plans for brachytherapy using mpMRI, and tumor regions mapped from MRI to CT to generate corresponding treatment plans for EBRT. For each of EBRT and brachytherapy, 3 dose plans were generated - whole gland homogeneous ([Formula: see text]) which is the current clinical standard, radiomics based focal ([Formula: see text]), and whole gland with a radiomics based focal boost ([Formula: see text]). Comparison of [Formula: see text] against conventional [Formula: see text] revealed that targeted focal brachytherapy would result in a marked reduction in dosage to the OARs while ensuring that the prescribed dose is delivered to the lesions. [Formula: see text] resulted in only a marginal increase in dosage to the OARs compared to [Formula: see text]. A similar trend was observed in case of EBRT with [Formula: see text] and [Formula: see text] compared to [Formula: see text].

CONCLUSIONS

A radiotherapy planning framework to generate targeted focal treatment plans has been presented. The focal treatment plans generated using the framework showed reduction in dosage to the organs at risk and a boosted dose delivered to the cancerous lesions.

What are the current and future requirements for magnetic resonance imaging interpretation skills in radiotherapy? A critical review

Purpose

Increasing usage of magnetic resonance imaging (MRI) in radiotherapy (RT) and the advent of MRI-based image-guided radiotherapy (IGRT) suggests a need for additional training within the RT profession. This critical review aimed to identify potential gaps in knowledge by evaluating the current skill base in MRI among therapeutic radiographers as evidenced by published research.

Methods

Papers related to MRI usage were retrieved. Topic areas included outlining, planning and IGRT; diagnosis, follow-up and staging-related papers were excluded. After selection and further text analysis, papers were grouped by tumour site and year of publication.

Results

The literature search and filtering resulted in a total of 123 papers, of which 66 were related to ‘outlining’, 37 to ‘planning’ and 20 to ‘IGRT’. The main sites of existing MRI expertise in RT were brain, central nervous system, prostate, and head and neck tumours. Expertise was clearly related to regions where MRI offered improved soft-tissue contrast. MRI studies within RT have been published from 2007 onwards at a steadily increasing rate.

Conclusion

Current use of MRI in RT is mainly restricted to sites where MRI offers a considerable imaging advantage over computed tomography. Given the changing use of MRI for image guidance, emerging therapeutic radiographers will require training in MRI interpretation across a wider range of anatomical regions.

Anatomic and dosimetric changes in patients with head and neck cancer treated with an integrated MRI-tri-60Co teletherapy device

OBJECTIVE

Prior studies have relied on CT to assess alterations in anatomy among patients undergoing radiation for head and neck cancer. We sought to determine the feasibility of using MRI-based image-guided radiotherapy to quantify these changes and to ascertain their potential dosimetric implications.

METHODS

6 patients with head and neck cancer were treated with intensity-modulated radiotherapy (IMRT) on a novel tri-⁶⁰Co teletherapy system equipped with a 0.35-T MRI (VR, ViewRay Incorporated, Oakwood Village, OH) to 66-70 Gy in 33 fractions (fx). Pre-treatment MRIs on Fx 1, 5, 10, 15, 20, 25, 30 and 33 were imported into a contouring interface, where the primary gross tumour volume (GTV) and parotid glands were delineated. The centre of mass (COM) shifts for these structures were assessed relative to Day 1. Dosimetric data were co-registered with the MRIs, and doses to the GTV and parotid glands were assessed.

RESULTS

Primary GTVs decreased significantly over the course of IMRT (median % volume loss, 38.7%; range, 29.5-72.0%; p < 0.05) at a median rate of 1.2%/fx (range, 0.92-2.2%/fx). Both the ipsilateral and contralateral parotid glands experienced significant volume loss (p < 0.05, for all) and shifted medially during IMRT. Weight loss correlated significantly with parotid gland volume loss and medial COM shift (p < 0.05).

CONCLUSION

Integrated on-board MRI can be used to accurately contour and analyze primary GTVs and parotid glands over the course of IMRT. COM shifts and significant volume reductions were observed, confirming the results of prior CT-based exercises. Advances in knowledge: The superior resolution of on-board MRI may facilitate online adaptive replanning in the future.

Therapy Monitoring with Functional and Molecular MR Imaging

Cancer therapy is mainly based on different combinations of surgery, radiotherapy, and chemotherapy. Additionally, targeted therapies (designed to disrupt specific tumor hallmarks, such as angiogenesis, metabolism, proliferation, invasiveness, and immune evasion), hormonotherapy, immunotherapy, and interventional techniques have emerged as alternative oncologic treatments. Conventional imaging techniques and current response criteria do not always provide the necessary information regarding therapy success particularly to targeted therapies. In this setting, MR imaging offers an attractive combination of anatomic, physiologic, and molecular information, which may surpass these limitations, and is being increasingly used for therapy response assessment.

Magnetic resonance imaging in lung: a review of its potential for radiotherapy

MRI has superior soft-tissue definition compared with existing imaging modalities in radiation oncology; this has the added benefit of functional as well as anatomical imaging. This review aimed to evaluate the current use of MRI for lung cancer and identify the potential of a MRI protocol for lung radiotherapy (RT). 30 relevant studies were identified. Improvements in MRI technology have overcome some of the initial limitations of utilizing MRI for lung imaging. A number of commercially available and novel sequences have shown image quality to be adequate for the detection of pulmonary nodules with the potential for tumour delineation. Quantifying tumour motion is also feasible and may be more representative than that seen on four-dimensional CT. Functional MRI sequences have shown correlation with flu-deoxy-glucose positron emission tomography (FDG-PET) in identifying malignant involvement and treatment response. MRI can also be used as a measure of pulmonary function. While there are some limitations for the adoption of MRI in RT-planning process for lung cancer, MRI has shown the potential to compete with both CT and PET for tumour delineation and motion definition, with the added benefit of functional information. MRI is well placed to become a significant imaging modality in RT for lung cancer.