Systematisation of spatial uncertainties for comparison between a MR and a CT-based radiotherapy workflow for prostate treatments

The accuracy of Magnetic Resonance - Cone Beam Computed Tomography soft-tissue matching for prostate radiotherapy

BACKGROUND AND PURPOSE

Magnetic Resonance (MR)-Only radiotherapy requires a method for matching image with on-treatment Cone Beam Computed Tomography (CBCT). This study aimed to investigate the accuracy of MR-CBCT soft-tissue matching for prostate MR-only radiotherapy.

MATERIALS AND METHODS

Three patient cohorts were used, with all patients receiving MR and CT scans. For the first cohort (10 patients) the first fraction CBCT was automatically rigidly registered to the CT and MR scans and the MR-CT registration predicted using the MR-CBCT and CT-CBCT registrations. This was compared to the automatic MR-CT registration. For the second and third cohorts (five patients each) the first fraction CBCT was independently matched to the CT and MR by four radiographers, the MR-CBCT and CT-CBCT matches compared and the inter-observer variability assessed. The second cohort used a CT-based structure set and the third a MR-based structure set with the MR relabelled as a 'CT'.

RESULTS

The mean difference between predicted and actual MR-CT registrations was Δ R All = - 0.1 ± 0.2 mm (s.e.m.). Radiographer MR-CBCT registrations were not significantly different to CT-CBCT, with mean differences in soft-tissue match ⩽ 0.2 mm and all except one difference ⩽ 3.3 mm . This was less than the MR-CBCT inter-observer limits of agreement [ 3.5 , 2.4 , 0.9 ] mm (vertical, longitudinal, lateral), which were similar ( ⩽ 0.5 mm ) to CT-CBCT.

CONCLUSIONS

MR-CBCT soft-tissue matching is not significantly different to CT-CBCT. Relabelling the MR as a 'CT' does not appear to change the automatic registration. This suggests that MR-CBCT soft-tissue matching is feasible and accurate.

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.

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.

Tissue segmentation-based electron density mapping for MR-only radiotherapy treatment planning of brain using conventional T1-weighted MR images

PURPOSE

Magnetic resonance imaging (MRI) is the primary modality for targeting brain tumors in radiotherapy treatment planning (RTP). MRI is not directly used for dose calculation since image voxel intensities of MRI are not associated with EDs of tissues as those of computed tomography (CT). The purpose of the present study is to develop and evaluate a tissue segmentation-based method to generate a synthetic-CT (sCT) by mapping EDs to corresponding tissues using only T1-weighted MR images for MR-only RTP.

METHODS

Air regions were contoured in several slices. Then, air, bone, brain, cerebrospinal fluid (CSF), and other soft tissues were automatically segmented with an in-house algorithm based on edge detection and anatomical information and relative intensity distribution. The intensities of voxels in each segmented tissue were mapped into their CT number range to generate a sCT. Twenty-five stereotactic radiosurgery and stereotactic ablative radiotherapy patients' T1-weighted MRI and coregistered CT images from two centers were retrospectively evaluated. The CT was used as ground truth. Distances between bone contours of the external skull of sCT and CT were measured. The mean error (ME) and mean absolute error (MAE) of electron density represented by standardized CT number was calculated in HU.

RESULTS

The average distance between the contour of the external skull in sCT and the contour in coregistered CT is 1.0 ± 0.2 mm (mean ± 1SD). The ME and MAE differences for air, soft tissue and whole body voxels within external body contours are -4 HU/24 HU, 2 HU/26 HU, and -2 HU/125 HU, respectively.

CONCLUSIONS

A MR-sCT generation technique was developed based on tissue segmentation and voxel-based tissue ED mapping. The generated sCT is comparable to real CT in terms of anatomical position of tissues and similarity to the ED assignment. This method provides a feasible method to generate sCT for MR-only radiotherapy treatment planning.

MRI-based treatment planning for proton radiotherapy: dosimetric validation of a deep learning-based liver synthetic CT generation method

Magnetic resonance imaging (MRI) has been widely used in combination with computed tomography (CT) radiation therapy because MRI improves the accuracy and reliability of target delineation due to its superior soft tissue contrast over CT. The MRI-only treatment process is currently an active field of research since it could eliminate systematic MR-CT co-registration errors, reduce medical cost, avoid diagnostic radiation exposure, and simplify clinical workflow. The purpose of this work is to validate the application of a deep learning-based method for abdominal synthetic CT (sCT) generation by image evaluation and dosimetric assessment in a commercial proton pencil beam treatment planning system (TPS). This study proposes to integrate dense block into a 3D cycle-consistent generative adversarial networks (cycle GAN) framework in an effort to effectively learn the nonlinear mapping between MRI and CT pairs. A cohort of 21 patients with co-registered CT and MR pairs were used to test the deep learning-based sCT image quality by leave-one-out cross validation. The CT image quality, dosimetric accuracy and the distal range fidelity were rigorously checked, using side-by-side comparison against the corresponding original CT images. The average mean absolute error (MAE) was 72.87  ±  18.16 HU. The relative differences of the statistics of the PTV dose volume histogram (DVH) metrics between sCT and CT were generally less than 1%. Mean 3D gamma analysis passing rate of 1 mm/1%, 2 mm/2%, 3 mm/3% criteria with 10% dose threshold were 90.76%  ±  5.94%, 96.98%  ±  2.93% and 99.37%  ±  0.99%, respectively. The median, mean and standard deviation of absolute maximum range differences were 0.170 cm, 0.186 cm and 0.155 cm. The image similarity, dosimetric and distal range agreement between sCT and original CT suggests the feasibility of further development of an MRI-only workflow for liver proton radiotherapy.

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.

Deep CT to MR Synthesis Using Paired and Unpaired Data

Magnetic resonance (MR) imaging plays a highly important role in radiotherapy treatment planning for the segmentation of tumor volumes and organs. However, the use of MR is limited, owing to its high cost and the increased use of metal implants for patients. This study is aimed towards patients who are contraindicated owing to claustrophobia and cardiac pacemakers, and many scenarios in which only computed tomography (CT) images are available, such as emergencies, situations lacking an MR scanner, and situations in which the cost of obtaining an MR scan is prohibitive. From medical practice, our approach can be adopted as a screening method by radiologists to observe abnormal anatomical lesions in certain diseases that are difficult to diagnose by CT. The proposed approach can estimate an MR image based on a CT image using paired and unpaired training data. In contrast to existing synthetic methods for medical imaging, which depend on sparse pairwise-aligned data or plentiful unpaired data, the proposed approach alleviates the rigid registration of paired training, and overcomes the context-misalignment problem of unpaired training. A generative adversarial network was trained to transform two-dimensional (2D) brain CT image slices into 2D brain MR image slices, combining the adversarial, dual cycle-consistent, and voxel-wise losses. Qualitative and quantitative comparisons against independent paired and unpaired training methods demonstrated the superiority of our approach.

Evaluation of the Geometric and Dosimetric Accuracy of Synthetic Computed Tomography Images for Magnetic Resonance Imaging-only Stereotactic Radiosurgery

Introduction

Stereotactic radiosurgery (SRS) plans created using synthetic computed tomography (CT) images derived from magnetic resonance imaging (MRI) data may offer the advantage of inhomogeneity correction by convolution algorithms, as is done for CT-based plans. We sought to determine and validate the clinical significance and accuracy of synthetic CT images for inhomogeneity correction in MRI-only stereotactic radiosurgery plans for treatment of brain tumors.

Methods

In this retrospective study, data from two patients with brain metastases and one with meningioma who underwent imaging with multiple modalities and received frameless SRS treatment were analyzed. The SRS plans were generated using a convolution algorithm to account for brain inhomogeneity using CT and synthetic CT images and compared with the original clinical TMR10 plans created using MRI images.

Results

Synthetic CT-derived SRS plans are comparable with CT-based plans using convolution algorithm, and for some targets, based on location, they provided better coverage and a lower maximum dose.

Conclusions

The results suggest similar dose delivery results for CT and synthetic CT-based treatment plans. Synthetic CT plans offered a noticeable improvement in target dose coverage and a more gradual dose fall-off relative to TMR10 MRI-based plans. The major disadvantage is a slightly increased dose (by 0.37%) to nearby healthy tissue (brainstem) for synthetic CT-based plans relative to those created using clinical MRI images, which may be a problem for patients undergoing high-dose treatment.

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.

Applying a commercial atlas-based synthetic Computed Tomography algorithm to patients with hip prostheses for prostate Magnetic Resonance-only radiotherapy

BACKGROUND AND PURPOSE

Magnetic Resonance (MR)-only prostate radiotherapy has recently been clinically implemented using commercial synthetic Computed Tomography (sCT) algorithms. However patients with hip prostheses have been excluded from all MR-only research to date and assumed to require dedicated sCT algorithms. This study aimed to investigate the dosimetric accuracy of applying a commercial sCT algorithm, based on an atlas of patients without hip prostheses, to patients with prostheses.

MATERIALS AND METHODS

18 patients with unilateral hip prostheses received MR and CT scans in the radiotherapy position. sCTs were generated from the MR using a commercial algorithm. The clinical Volumetric Modulated Arc Therapy (VMAT) plan, consisting of partial arcs which avoided the prosthesis, was recalculated using the sCT and the dose distribution compared.

RESULTS

The mean isocentre dose difference was ΔD = (-0.4 ± 0.2)% (mean ± standard error of the mean (sem), range - 1.9%, 1.1%) and the mean differences in Planning Target Volume, bladder and rectum mean doses were ≤0.3%. The 3D global gamma pass rate with dose difference 1% and distance to agreement 1 mm within the body was Γ_Body^1/1 = (95.0 ± 0.5)% (sem) and within the 50% isodose volume, which excluded the prosthesis, was Γ_50%^1/1 = (98.5 ± 0.4)% (sem). The pass rate within the PTV was Γ_PTV^2/2 ≥ 99.7% for all patients, although for PTVs close (≤3.5 cm) to the prosthesis Γ_PTV^1/1 < 85% for three patients. The sCT did not accurately represent the prosthesis with a mean difference in radiological isocentre depth near the prosthesis of Δd_Outside^Rad = (15.8 ± 2.6) mm (sem). However inside the treatment plan arc the difference was Δd_Inside^Rad = (-1.8 ± 0.5) mm (sem).

CONCLUSIONS

Using a commercial prostate sCT algorithm for patients with unilateral hip prostheses is dosimetrically accurate (<0.5%) as long as the routine prosthesis-avoidance treatment planning approach is used and the PTV is >3.5 cm from the prosthesis. This suggests MR-only prostate radiotherapy can be extended to patients with hip prostheses without requiring a specific sCT algorithm.

Development and evaluation of a novel MR-compatible pelvic end-to-end phantom

MR-only treatment planning and MR-IGRT leverage MRI's powerful soft tissue contrast for high-precision radiation therapy. However, anthropomorphic MR-compatible phantoms are currently limited. This work describes the development and evaluation of a custom-designed, modular, pelvic end-to-end (PETE) MR-compatible phantom to benchmark MR-only and MR-IGRT workflows. For construction considerations, subject data were assessed for phantom/skeletal geometry and internal organ kinematics to simulate average male pelvis anatomy. Various materials for the bone, bladder, and rectum were evaluated for utility within the phantom. Once constructed, PETE underwent CT-SIM, MR-Linac, and MR-SIM imaging to qualitatively assess organ visibility. Scans were acquired with various bladder and rectal volumes to assess component interactions, filling capabilities, and filling reproducibility via volume and centroid differences. PETE simulates average male pelvis anatomy and comprises an acrylic body oval (height/width = 23.0/38.1 cm) and a cast-mold urethane skeleton, with silicone balloons simulating bladder and rectum, a silicone sponge prostate, and hydrophilic poly(vinyl alcohol) foam to simulate fat/tissue separation between organs. Access ports enable retrofitting the phantom with other inserts including point/film-based dosimetry options. Acceptable contrast was achievable in CT-SIM and MR-Linac images. However, the bladder was challenging to distinguish from background in CT-SIM. The desired contrast for T1-weighted and T2-weighted MR-SIM (dark and bright bladders, respectively) was achieved. Rectum and bone exhibited no MR signal. Inputted volumes differed by <5 and <10 mL from delineated rectum (CT-SIM) and bladder (MR-SIM) volumes. Increasing bladder and rectal volumes induced organ displacements and shape variations. Reproduced volumes differed by <4.5 mL, with centroid displacements <1.4 mm. A point dose measurement with an MR-compatible ion chamber in an MR-Linac was within 1.5% of expected. A novel, modular phantom was developed with suitable materials and properties that accurately and reproducibly simulate status changes with multiple dosimetry options. Future work includes integrating more realistic organ models to further expand phantom options.

Calcium Phosphate Cement Paste Injection as a Fiducial Marker of Cervical Cancer

BACKGROUND/AIM

Calcium phosphate cement (CPC) is used to fill bone voids in dental, orthopedic, and craniofacial applications. This study evaluated CPC marker as an injectable non-metallic fiducial marker.

MATERIALS AND METHODS

Six patients received 3-5 injections of CPC paste placed at a depth of 10 mm into tumors of the cervix before treatment planning CT (TPCT). Patients were treated with external-beam radiotherapy (EBRT) and high-dose rate brachytherapy (BT). We investigated marker visibility on cone-beam CT (CBCT), T2-weighted MRI, and interfraction of the marker motion for cervical cancer patients.

RESULTS

Of a total of 22 visible CPC markers at TPCT, 17 CPC markers were visible on the first CBCT. Excluding one patient, all markers were visible on CBCT during EBRT. Of 16 visible CPC markers on CBCT, 13 CPC markers were visible on the magnetic resonance imaging (MRI) obtained before BT. For CPC marker centroid movement, the mean-of-means/systematic variation/random variation were 0.2/0.4/1.4, -1.6/5.1/4.1, and -3.4/2.1/2.8 mm for the left-right, dorsal-ventral, and cranial-caudal directions, respectively.

CONCLUSION

This is the first report of a CPC marker injected into tumors of the cervix. It can be visualized on CBCT and MRI with reductions in marker loss and artifacts.

Using C-Arm X-ray images from marker insertion to confirm the gold fiducial marker identification in an MRI-only prostate radiotherapy workflow

Prostate cancer radiotherapy workflows, solely based on magnetic resonance imaging (MRI), are now in clinical use. In these workflows, intraprostatic gold fiducial markers (GFM) show similar signal behavior as calcifications and bleeding in T2‐weighted MRI‐images. Accurate GFM identification in MRI‐only radiotherapy workflows is therefore a major challenge. C‐arm X‐ray images (CkV‐images), acquired at GFM implantation, could provide GFM position information and be used to confirm correct identification in T2‐weighted MRI‐images. This would require negligible GFM migration between implantation and MRI‐imaging. Marker migration was therefore investigated. The aim of this study was to show the feasibility of using CkV‐images to confirm GFM identification in an MRI‐only prostate radiotherapy workflow. An anterior‐posterior digitally reconstructed radiograph (DRR)‐image and a mirrored posterior‐anterior CkV‐image were acquired two weeks apart for 16 patients in an MRI‐only radiotherapy workflow. The DRR‐image originated from synthetic CT‐images (created from MRI‐images). A common image geometry was defined between the DRR‐ and CkV‐image for each patient. A rigid registration between the GFM center of mass (CoM) coordinates was performed and the distance between each of the GFM in the DRR‐ and registered CkV‐image was calculated. The same methodology was used to assess GFM migration for 31 patients in a CT‐based radiotherapy workflow. The distance calculated was considered a measure of GFM migration. A statistical test was performed to assess any difference between the cohorts. The mean absolute distance difference for the GFM CoM between the DRR‐ and CkV‐image in the MRI‐only cohort was 1.7 ± 1.4 mm. The mean GFM migration was 1.2 ± 0.7 mm. No significant difference between the measured total distances of the two cohorts could be detected (P = 0.37). This demonstrated that, a C‐Arm X‐ray image acquired from the GFM implantation procedure could be used to confirm GFM identification from MRI‐images. GFM migration was present but did not constitute a problem.

Resolution and registration in dual-plane co-RASOR MR

Magnetic resonance imaging (MRI) has superior soft tissue contrast and lower interobserver variability compared to computed tomography and advances in equipment and pseudo-CT estimation have allowed for MR-only radiation therapy planning. Dedicated MR sequences have been used to localize paramagnetic structures with positive contrast, and most implanted seeds are gold fiducial markers (GFMs). We used a fast, dual-plane co-RASOR sequence to localize implanted GFMs with positive contrast in phantom and tissue to assess their resolution and registration accuracy of registration to CT. Off-resonant reconstructions of co-RASOR images were able to resolve GFMs down to 5 mm apart at 12 cm FOV. No systematic biases were observed by comparing registration of co-RASOR and bSSFP to CT images in an MR-compatible Lego phantom with a set of highly visible known points. The standard deviations of the MR to CT distance errors were  <0.5 mm in all directions. We separated the component due to registration by comparing the two MR sequences, which had a maximum standard deviation of 0.36 mm in the SI-direction. Registration using the positive contrast points in a porcine sample phantom showed increased errors, but co-RASOR still performs acceptably with a target registration error of  <0.75 mm. The dual-plane co-RASOR sequence could then be used for both registration and image tracking when performing MR-only radiation therapy planning.

Penile bulb sparing in prostate cancer radiotherapy : Dose analysis of an in-house MRI system to improve contouring

OBJECTIVE

This study aimed to assess the reduction in dose to the penile bulb (PB) achieved by MRI-based contouring following drinking and endorectal balloon (ERB) instructions.

PATIENTS AND METHODS

A total of 17 prostate cancer patients were treated with intensity-modulated radiation therapy (IMRT) and interstitial brachytherapy (IBT). CT and MRI datasets were acquired back-to-back based on a 65 cm³ air-filled ERB and drinking instructions. After rigid co-registration of the imaging data, the CT-based planning target volume (PTV) used for treatment planning was retrospectively compared to an MRI-based adaptive PTV and the dose to the PB was determined in each case. The adapted PTV encompassed a caudally cropped CT-based PTV which was defined on the basis of the MRI-based prostate contour plus an additional 5 mm safety margin.

RESULTS

In the seven-field IMRT treatment plans, the MRI-based adapted PTV achieved mean (D_mean) and maximum (D_max) doses to the PB which were significantly lower (by 7.6 Gy and 10.9 Gy, respectively; p <0.05) than those of the CT-contoured PTV. For 6 patients, the estimated PB D_max (seven-field IMRT and IBT) for the adapted PTV was <70 Gy, whereas only 1 patient fulfilled this criterium with the CT-based PTV.

CONCLUSION

MRI-based contouring and seven-field IMRT-based treatment planning achieved dose sparing to the PB. Whereas the comparison of MRI and CT contouring only relates to external beam radiotherapy (EBRT) sparing, considering EBRT and IBT shows the improvement in PB sparing for the total treatment.

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.

Dose evaluation of fast synthetic-CT generation using a generative adversarial network for general pelvis MR-only radiotherapy

To enable magnetic resonance (MR)-only radiotherapy and facilitate modelling of radiation attenuation in humans, synthetic CT (sCT) images need to be generated. Considering the application of MR-guided radiotherapy and online adaptive replanning, sCT generation should occur within minutes. This work aims at assessing whether an existing deep learning network can rapidly generate sCT images for accurate MR-based dose calculations in the entire pelvis. A study was conducted on data of 91 patients with prostate (59), rectal (18) and cervical (14) cancer who underwent external beam radiotherapy acquiring both CT and MRI for patients' simulation. Dixon reconstructed water, fat and in-phase images obtained from a conventional dual gradient-recalled echo sequence were used to generate sCT images. A conditional generative adversarial network (cGAN) was trained in a paired fashion on 2D transverse slices of 32 prostate cancer patients. The trained network was tested on the remaining patients to generate sCT images. For 30 patients in the test set, dose recalculations of the clinical plan were performed on sCT images. Dose distributions were evaluated comparing voxel-based dose differences, gamma and dose-volume histogram (DVH) analysis. The sCT generation required 5.6 s and 21 s for a single patient volume on a GPU and CPU, respectively. On average, sCT images resulted in a higher dose to the target of maximum 0.3%. The average gamma pass rates using the 3%, 3 mm and 2%, 2 mm criteria were above 97 and 91%, respectively, for all volumes of interests considered. All DVH points calculated on sCT differed less than  ±2.5% from the corresponding points on CT. Results suggest that accurate MR-based dose calculation using sCT images generated with a cGAN trained on prostate cancer patients is feasible for the entire pelvis. The sCT generation was sufficiently fast for integration in an MR-guided radiotherapy workflow.

Emerging role of MRI in radiation therapy

Advances in multimodality imaging, providing accurate information of the irradiated target volume and the adjacent critical structures or organs at risk (OAR), has made significant improvements in delivery of the external beam radiation dose. Radiation therapy conventionally has used computed tomography (CT) imaging for treatment planning and dose delivery. However, magnetic resonance imaging (MRI) provides unique advantages: added contrast information that can improve segmentation of the areas of interest, motion information that can help to better target and deliver radiation therapy, and posttreatment outcome analysis to better understand the biologic effect of radiation. To take advantage of these and other potential advantages of MRI in radiation therapy, radiologists and MRI physicists will need to understand the current radiation therapy workflow and speak the same language as our radiation therapy colleagues. This review article highlights the emerging role of MRI in radiation dose planning and delivery, but more so for MR-only treatment planning and delivery. Some of the areas of interest and challenges in implementing MRI in radiation therapy workflow are also briefly discussed. Level of Evidence: 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018;48:1468-1478.

FMEA of MR-Only Treatment Planning in the Pelvis

Purpose

To evaluate the implementation of a magnetic resonance (MR)-only workflow (ie, implementing MR simulation as the primary planning modality) using failure mode and effects analysis (FMEA) in comparison with a conventional multimodality (MR simulation in conjunction with computed tomography simulation) workflow for pelvis external beam planning.

Methods and Materials

To perform the FMEA, a multidisciplinary 9-member team was assembled and developed process maps, identified potential failure modes (FMs), and assigned numerical values to the severity (S), frequency of occurrence (O), and detectability (D) of those FMs. Risk priority numbers (RPNs) were calculated via the product of S, O, and D as a metric for evaluating relative patient risk. An alternative 3-digit composite number (SOD) was computed to emphasize high-severity FMs. Fault tree analysis identified the causality chain leading to the highest-severity FM.

Results

Seven processes were identified, 3 of which were shared between workflows. Image fusion and target delineation subprocesses using the conventional workflow added 9 and 10 FMs, respectively, with 6 RPNs >100. By contrast, synthetic computed tomography generation introduced 3 major subprocesses and propagated 46 unique FMs, 15 with RPNs >100. For the conventional workflow, the largest RPN scores were introduced by image fusion (RPN range, 120-192). For the MR-only workflow, the highest RPN scores were from inaccuracies in target delineation resulting from misinterpretation of MR images (RPN = 240) and insufficient management of patient- and system-level distortions (RPN = 210 and 168, respectively). Underestimation (RPN = 140) or overestimation (RPN = 192) of bone volume produced higher RPN scores. The highest SODs for both workflows were related to changes in target location because of internal anatomy changes (conventional = 961, MR-only = 822).

Conclusions

FMEA identified areas for mitigating risk in MR-only pelvis RTP, and SODs identified high-severity process modes. Efforts to develop a quality management program to mitigate high FMs are underway.

Cone beam CT for QA of synthetic CT in MRI only for prostate patients

Purpose

Magnetic resonance imaging (MRI)‐only radiotherapy is performed without computed tomography (CT). A synthetic CT (sCT) is used for treatment planning. The aim of this study was to develop a clinically feasible quality assurance (QA) procedure for sCT using the kV‐cone beam CT (CBCT), in an MRI‐only workflow for prostate cancer patients.

Material and method

Three criteria were addressed; stability in Hounsfield Units (HUs), deviations in HUs between the CT and CBCT, and validation of the QA procedure. For the two first criteria, weekly phantom measurements were performed. For the third criteria, sCT, CT, and CBCT for ten patients were used. Treatment plans were created based on the sCT (MriPlanner^TM). CT and CBCT images were registered to the sCT. The treatment plan was copied to the CT and CBCT and recalculated. Dose–volume histogram (DVH) metrics were used to evaluate dosimetric differences between the sCT plan and the recalculated CT and CBCT plans. HU distributions in sCT, CT, and CBCT were compared. Well‐defined errors were introduced in the sCT for one patient to evaluate efficacy of the QA procedure.

Results

The kV‐CBCT system was stable in HU over time (standard deviation <40 HU). Variation in HUs between CT and CBCT was <60 HU. The differences between sCT–CT and sCT–CBCT dose distributions were below or equal to 1.0%. The highest mean dose difference for the CT and CBCT dose distribution was 0.6%. No statistically significant difference was found between total mean dose deviations from recalculated CT and CBCT plans, except for femoral head. Comparing HU distributions, the CBCT appeared to be similar to the CT. All introduced errors were identified by the proposed QA procedure, except all tissue compartments assigned as water.

Conclusion

The results in this study shows that CBCT can be used as a clinically feasible QA procedure for MRI‐only radiotherapy of prostate cancer patients.

MRI-based treatment planning for brain stereotactic radiosurgery: Dosimetric validation of a learning-based pseudo-CT generation method

Magnetic resonance imaging (MRI)-only radiotherapy treatment planning is attractive since MRI provides superior soft tissue contrast without ionizing radiation compared with computed tomography (CT). However, it requires the generation of pseudo CT from MRI images for patient setup and dose calculation. Our machine-learning-based method to generate pseudo CT images has been shown to provide pseudo CT images with excellent image quality, while its dose calculation accuracy remains an open question. In this study, we aim to investigate the accuracy of dose calculation in brain frameless stereotactic radiosurgery (SRS) using pseudo CT images which are generated from MRI images using the machine learning-based method developed by our group. We retrospectively investigated a total of 19 treatment plans from 14 patients, each of whom has CT simulation and MRI images acquired during pretreatment. The dose distributions of the same treatment plans were calculated on original CT simulation images as ground truth, as well as on pseudo CT images generated from MRI images. Clinically-relevant DVH metrics and gamma analysis were extracted from both ground truth and pseudo CT results for comparison and evaluation. The side-by-side comparisons on image quality and dose distributions demonstrated very good agreement of image contrast and calculated dose between pseudo CT and original CT. The average differences in Dose-volume histogram (DVH) metrics for Planning target volume (PTVs) were less than 0.6%, and no differences in those for organs at risk at a significance level of 0.05. The average pass rate of gamma analysis was 99%. These quantitative results strongly indicate that the pseudo CT images created from MRI images using our proposed machine learning method are accurate enough to replace current CT simulation images for dose calculation in brain SRS treatment. This study also demonstrates the great potential for MRI to completely replace CT scans in the process of simulation and treatment planning.

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.

Evaluating the repeatability and set-up sensitivity of a large field of view distortion phantom and software for magnetic resonance-only radiotherapy

BACKGROUND AND PURPOSE

Magnetic Resonance (MR)-only radiotherapy requires geometrically accurate MR images over the full scanner Field of View (FoV). This study aimed to investigate the repeatability of distortion measurements made using a commercial large FoV phantom and analysis software and the sensitivity of these measurements to small set-up errors.

MATERIALS AND METHODS

Geometric distortion was measured using a commercial phantom and software with 2D and 3D acquisition sequences on three different MR scanners. Two sets of repeatability measurements were made: three scans acquired without moving the phantom between scans (single set-up) and five scans acquired with the phantom re-set up in between each scan (repeated set-up). The set-up sensitivity was assessed by scanning the phantom with an intentional 1 mm lateral offset and independently an intentional 1° rotation.

RESULTS

The mean standard deviation of distortion for all phantom markers for the repeated set-up scans was < 0.4 mm for all scanners and sequences. For the 1 mm lateral offset scan 90 % of the markers agreed within two standard deviations of the mean of the repeated set-up scan (median of all scanners and sequences, range 78%-93%). For the 1° rotation scan, 80% of markers agreed within two standard deviations of the mean (range 69%-93%).

CONCLUSIONS

Geometric distortion measurements using a commercial phantom and associated software appear repeatable, although with some sensitivity to set-up errors. This suggests the phantom and software are appropriate for commissioning a MR-only radiotherapy workflow.

Accuracy and precision of patient positioning for pelvic MR-only radiation therapy using digitally reconstructed radiographs

BACKGROUND AND PURPOSE

Magnetic resonance imaging (MRI) has in recent years emerged as an imaging modality to drive precise contouring of targets and organs at risk in external beam radiation therapy. Moreover, recent advances in MRI enable treatment of cancer without computed tomography (CT) simulation. A commercially available MR-only solution, MRCAT, offers a single-modality approach that provides density information for dose calculation and generation of positioning reference images. We evaluated the accuracy of patient positioning based on MRCAT digitally reconstructed radiographs (DRRs) by comparing to standard CT based workflow.

MATERIALS AND METHODS

Twenty consecutive prostate cancer patients being treated with external beam radiation therapy were included in the study. DRRs were generated for each patient based on the planning CT and MRCAT. The accuracy assessment was performed by manually registering the DRR images to planar kV setup images using bony landmarks. A Bayesian linear mixed effects model was used to separate systematic and random components (inter- and intra-observer variation) in the assessment. In addition, method agreement was assessed using a Bland-Altman analysis.

RESULTS

The systematic difference between MRCAT and CT based patient positioning, averaged over the study population, were found to be (mean [95% CI])  -0.49 [-0.85 to  -0.13] mm, 0.11 [-0.33 to  +0.57] mm and  -0.05 [-0.23 to  +0.36] mm in vertical, longitudinal and lateral directions, respectively. The increases in total random uncertainty were estimated to be below 0.5 mm for all directions, when using MR-only workflow instead of CT.

CONCLUSIONS

The MRCAT pseudo-CT method provides clinically acceptable accuracy and precision for patient positioning for pelvic radiation therapy based on planar DRR images. Furthermore, due to the reduction of geometric uncertainty, compared to dual-modality workflow, the approach is likely to improve the total geometric accuracy of pelvic radiation therapy.

Magnetic Resonance Imaging-Guided Adaptive Radiation Therapy: A "Game Changer" for Prostate Treatment?

Radiation therapy to the prostate involves increasingly sophisticated delivery techniques and changing fractionation schedules. With a low estimated α/β ratio, a larger dose per fraction would be beneficial, with moderate fractionation schedules rapidly becoming a standard of care. The integration of a magnetic resonance imaging (MRI) scanner and linear accelerator allows for accurate soft tissue tracking with the capacity to replan for the anatomy of the day. Extreme hypofractionation schedules become a possibility using the potentially automated steps of autosegmentation, MRI-only workflow, and real-time adaptive planning. The present report reviews the steps involved in hypofractionated adaptive MRI-guided prostate radiation therapy and addresses the challenges for implementation.

Intensity-based dual model method for generation of synthetic CT images from standard T2-weighted MR images - Generalized technique for four different MR scanners

BACKGROUND AND PURPOSE

Recent studies have shown that it is possible to conduct entire radiotherapy treatment planning (RTP) workflow using only MR images. This study aims to develop a generalized intensity-based method to generate synthetic CT (sCT) images from standard T2-weighted (T2_w) MR images of the pelvis.

MATERIALS AND METHODS

This study developed a generalized dual model HU conversion method to convert standard T2_w MR image intensity values to synthetic HU values, separately inside and outside of atlas-segmented bone volume contour. The method was developed and evaluated with 20 and 35 prostate cancer patients, respectively. MR images with scanning sequences in clinical use were acquired with four different MR scanners of three vendors.

RESULTS

For the generated synthetic CT (sCT) images of the 35 prostate patients, the mean (and maximal) HU differences in soft and bony tissue volumes were 16 ± 6 HUs (34 HUs) and -46 ± 56 HUs (181 HUs), respectively, against the true CT images. The average of the PTV mean dose difference in sCTs compared to those in true CTs was -0.6 ± 0.4% (-1.3%).

CONCLUSIONS

The study provides a generalized method for sCT creation from standard T2_w images of the pelvis. The method produced clinically acceptable dose calculation results for all the included scanners and MR sequences.

Image similarity evaluation of the bulk-density-assigned synthetic CT derived from MRI of intracranial regions for radiation treatment

Objective

Various methods for radiation-dose calculation have been investigated over previous decades, focusing on the use of magnetic resonance imaging (MRI) only. The bulk-density-assignment method based on manual segmentation has exhibited promising results compared to dose-calculation with computed tomography (CT). However, this method cannot be easily implemented in clinical practice due to its time-consuming nature. Therefore, we investigated an automatic anatomy segmentation method with the intention of providing the proper methodology to evaluate synthetic CT images for a radiation-dose calculation based on MR images.

Methods

CT images of 20 brain cancer patients were selected, and their MR images including T1-weighted, T2-weighted, and PETRA were retrospectively collected. Eight anatomies of the patients, such as the body, air, eyeball, lens, cavity, ventricle, brainstem, and bone, were segmented for bulk-density-assigned CT image (_BCT) generation. In addition, water-equivalent CT images (_WCT) with only two anatomies—body and air—were generated for a comparison with _BCT. Histogram comparison and gamma analysis were performed by comparison with the original CT images, after the evaluation of automatic segmentation performance with the dice similarity coefficient (DSC), false negative dice (FND) coefficient, and false positive dice (FPD) coefficient.

Results

The highest DSC value was 99.34 for air segmentation, and the lowest DSC value was 73.50 for bone segmentation. For lens segmentation, relatively high FND and FPD values were measured. The cavity and bone were measured as over-segmented anatomies having higher FPD values than FND. The measured histogram comparison results of _BCT were better than those of _WCT in all cases. In gamma analysis, the averaged improvement of _BCT compared to _WCT was measured. All the measured results of _BCT were better than those of _WCT. Therefore, the results of this study show that the introduced methods, such as histogram comparison and gamma analysis, are valid for the evaluation of the synthetic CT generation from MR images.

Conclusions

The image similarity results showed that _BCT has superior results compared to _WCT for all measurements performed in this study. Consequently, more accurate radiation treatment for the intracranial regions can be expected when the proper image similarity evaluation introduced in this study is performed.

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.

MR-OPERA: A Multicenter/Multivendor Validation of Magnetic Resonance Imaging-Only Prostate Treatment Planning Using Synthetic Computed Tomography Images

PURPOSE

To validate the dosimetric accuracy and clinical robustness of a commercially available software for magnetic resonance (MR) to synthetic computed tomography (sCT) conversion, in an MR imaging-only workflow for 170 prostate cancer patients.

METHODS AND MATERIALS

The 4 participating centers had MriPlanner (Spectronic Medical), an atlas-based sCT generation software, installed as a cloud-based service. A T2-weighted MR sequence, covering the body contour, was added to the clinical protocol. The MR images were sent from the MR scanner workstation to the MriPlanner platform. The sCT was automatically returned to the treatment planning system. Four MR scanners and 2 magnetic field strengths were included in the study. For each patient, a CT-treatment plan was created and approved according to clinical practice. The sCT was rigidly registered to the CT, and the clinical treatment plan was recalculated on the sCT. The dose distributions from the CT plan and the sCT plan were compared according to a set of dose-volume histogram parameters and gamma evaluation. Treatment techniques included volumetric modulated arc therapy, intensity modulated radiation therapy, and conventional treatment using 2 treatment planning systems and different dose calculation algorithms.

RESULTS

The overall (multicenter/multivendor) mean dose differences between sCT and CT dose distributions were below 0.3% for all evaluated organs and targets. Gamma evaluation showed a mean pass rate of 99.12% (0.63%, 1 SD) in the complete body volume and 99.97% (0.13%, 1 SD) in the planning target volume using a 2%/2-mm global gamma criteria.

CONCLUSIONS

Results of the study show that the sCT conversion method can be used clinically, with minimal differences between sCT and CT dose distributions for target and relevant organs at risk. The small differences seen are consistent between centers, indicating that an MR imaging-only workflow using MriPlanner is robust for a variety of field strengths, vendors, and treatment techniques.

Magnetic resonance-only simulation and dose calculation in external beam radiation therapy: a feasibility study for pelvic cancers

BACKGROUND

The clinical feasibility of using pseudo-computed tomography (pCT) images derived from magnetic resonance (MR) images for external bean radiation therapy (EBRT) planning for prostate cancer patients has been well demonstrated. This paper investigates the feasibility of applying an MR-derived, pCT planning approach to additional types of cancer in the pelvis.

MATERIAL AND METHODS

Fifteen patients (five prostate cancer patients, five rectal cancer patients, and five gynecological cancer patients) receiving EBRT at Turku University Hospital (Turku, Finland) were included in the study. Images from an MRCAT (Magnetic Resonance for Calculating ATtenuation, Philips, Vantaa, Finland) pCT method were generated as a part of a clinical MR-simulation procedure. Dose calculation accuracy was assessed by comparing the pCT-based calculation with a CT-based calculation. In addition, the degree of geometric accuracy was studied.

RESULTS

The median relative difference of PTV mean dose between CT and pCT images was within 0.8% for all tumor types. When assessing the tumor site-specific accuracy, the median [range] relative dose differences to the PTV mean were 0.7 [-0.11;1.05]% for the prostate cases, 0.3 [-0.25;0.57]% for the rectal cases, and 0.09 [-0.69;0.25]% for the gynecological cancer cases. System-induced geometric distortion was measured to be less than 1 mm for all PTV volumes and the effect on the PTV median dose was less than 0.1%.

CONCLUSIONS

According to the comparison, using pCT for clinical EBRT planning and dose calculation in the three investigated types of pelvic cancers is feasible. Further studies are required to demonstrate the applicability to a larger cohort of patients.

Synthetic CT for MRI-based liver stereotactic body radiotherapy treatment planning

A technique for generating MRI-derived synthetic CT volumes (MRCTs) is demonstrated in support of adaptive liver stereotactic body radiation therapy (SBRT). Under IRB approval, 16 subjects with hepatocellular carcinoma were scanned using a single MR pulse sequence (T1 Dixon). Air-containing voxels were identified by intensity thresholding on T1-weighted, water and fat images. The envelope of the anterior vertebral bodies was segmented from the fat image and fuzzy-C-means (FCM) was used to classify each non-air voxel as mid-density, lower-density, bone, or marrow in the abdomen, with only bone and marrow classified within the vertebral body envelope. MRCT volumes were created by integrating the product of the FCM class probability with its assigned class density for each voxel. MRCTs were deformably aligned with corresponding planning CTs and 2-ARC-SBRT-VMAT plans were optimized on MRCTs. Fluence was copied onto the CT density grids, dose recalculated, and compared. The liver, vertebral bodies, kidneys, spleen and cord had median Hounsfield unit differences of less than 60. Median target dose metrics were all within 0.1 Gy with maximum differences less than 0.5 Gy. OAR dose differences were similarly small (median: 0.03 Gy, std:0.26 Gy). Results demonstrate that MRCTs derived from a single abdominal imaging sequence are promising for use in SBRT dose calculation.

Dosimetric characterization of MRI-only treatment planning for brain tumors in atlas-based pseudo-CT images generated from standard T1-weighted MR images

PURPOSE

Magnetic resonance imaging (MRI)-only radiotherapy treatment planning requires accurate pseudo-CT (pCT) images for precise dose calculation. The current work introduced an atlas-based method combined with MR intensity information. pCT analyses and Monte Carlo dose calculations for intracranial stereotactic treatments were performed.

METHODS

Twenty-two patients, representing 35 tumor targets, were scanned using a 3D T1-weighted MRI sequence according to the clinical protocol. The MR atlas image was registered to the MR patient image using a deformable algorithm, and the deformation was then applied to the atlas CT. Two methods were applied. The first method (MRdef) was based on deformations only, while the second (MRint) also used the actual MR intensities. pCT analysis was performed using the mean (absolute) error, as well as an in-house tool based on a gamma index. Dose differences between pCT and true CT were analyzed using dose-volume histogram (DVH) parameters, statistical tests, the gamma index, and probability density functions. An unusual case, where the patient underwent an operation (part of the skull bone was removed), was studied in detail.

RESULTS

Soft tissues presented a mean error inferior to 50 HUs, while low-density tissues and bones presented discrepancies up to 600 HUs for hard bone. The MRdef method led to significant dose differences compared with the true CT (p-value < 0.05; Wilcoxon-signed-rank test). The MRint method performed better. The DVH parameter differences compared with CT were between -2.9% and 3.1%, except for two cases where the tumors were located within the sphenoid bone. For these cases, the dose errors were up to 6.6% and 5.4% (D₉₈ and D₉₅). Furthermore, for 85% of the tested patients, the mean dose to the planning target volume agreed within 2% with the calculation using the actual CT. Fictitious bone was generated in the unusual case using atlas-based methods.

CONCLUSIONS

Generally, the atlas-based method led to acceptable dose distributions. The use of common T1 sequences allows the implementation of this method in clinical routine. However, unusual patient anatomy may produce large dose calculation errors. The detection of large anatomic discrepancies using MR image subtraction can be realized, but an alternative way to produce synthetic CT numbers in these regions is still required.

A patch-based pseudo-CT approach for MRI-only radiotherapy in the pelvis

PURPOSE

In radiotherapy based only on magnetic resonance imaging (MRI), knowledge about tissue electron densities must be derived from the MRI. This can be achieved by converting the MRI scan to the so-called pseudo-computed tomography (pCT). An obstacle is that the voxel intensities in conventional MRI scans are not uniquely related to electron density. The authors previously demonstrated that a patch-based method could produce accurate pCTs of the brain using conventional T1-weighted MRI scans. The method was driven mainly by local patch similarities and relied on simple affine registrations between an atlas database of the co-registered MRI/CT scan pairs and the MRI scan to be converted. In this study, the authors investigate the applicability of the patch-based approach in the pelvis. This region is challenging for a method based on local similarities due to the greater inter-patient variation. The authors benchmark the method against a baseline pCT strategy where all voxels inside the body contour are assigned a water-equivalent bulk density. Furthermore, the authors implement a parallelized approximate patch search strategy to speed up the pCT generation time to a more clinically relevant level.

METHODS

The data consisted of CT and T1-weighted MRI scans of 10 prostate patients. pCTs were generated using an approximate patch search algorithm in a leave-one-out fashion and compared with the CT using frequently described metrics such as the voxel-wise mean absolute error (MAEvox) and the deviation in water-equivalent path lengths. Furthermore, the dosimetric accuracy was tested for a volumetric modulated arc therapy plan using dose-volume histogram (DVH) point deviations and γ-index analysis.

RESULTS

The patch-based approach had an average MAEvox of 54 HU; median deviations of less than 0.4% in relevant DVH points and a γ-index pass rate of 0.97 using a 1%/1 mm criterion. The patch-based approach showed a significantly better performance than the baseline water pCT in almost all metrics. The approximate patch search strategy was 70x faster than a brute-force search, with an average prediction time of 20.8 min.

CONCLUSIONS

The authors showed that a patch-based method based on affine registrations and T1-weighted MRI could generate accurate pCTs of the pelvis. The main source of differences between pCT and CT was positional changes of air pockets and body outline.

Evaluation of a multi-atlas CT synthesis approach for MRI-only radiotherapy treatment planning

BACKGROUND AND PURPOSE

Computed tomography (CT) imaging is the current gold standard for radiotherapy treatment planning (RTP). The establishment of a magnetic resonance imaging (MRI) only RTP workflow requires the generation of a synthetic CT (sCT) for dose calculation. This study evaluates the feasibility of using a multi-atlas sCT synthesis approach (sCTa) for head and neck and prostate patients.

MATERIAL AND METHODS

The multi-atlas method was based on pairs of non-rigidly aligned MR and CT images. The sCTa was obtained by registering the MRI atlases to the patient's MRI and by fusing the mapped atlases according to morphological similarity to the patient. For comparison, a bulk density assignment approach (sCTbda) was also evaluated. The sCTbda was obtained by assigning density values to MRI tissue classes (air, bone and soft-tissue). After evaluating the synthesis accuracy of the sCTs (mean absolute error), sCT-based delineations were geometrically compared to the CT-based delineations. Clinical plans were re-calculated on both sCTs and a dose-volume histogram and a gamma analysis was performed using the CT dose as ground truth.

RESULTS

Results showed that both sCTs were suitable to perform clinical dose calculations with mean dose differences less than 1% for both the planning target volume and the organs at risk. However, only the sCTa provided an accurate and automatic delineation of bone.

CONCLUSIONS

Combining MR delineations with our multi-atlas CT synthesis method could enable MRI-only treatment planning and thus improve the dosimetric and geometric accuracy of the treatment, and reduce the number of imaging procedures.

A review of substitute CT generation for MRI-only radiation therapy

Radiotherapy based on magnetic resonance imaging as the sole modality (MRI-only RT) is an area of growing scientific interest due to the increasing use of MRI for both target and normal tissue delineation and the development of MR based delivery systems. One major issue in MRI-only RT is the assignment of electron densities (ED) to MRI scans for dose calculation and a similar need for attenuation correction can be found for hybrid PET/MR systems. The ED assigned MRI scan is here named a substitute CT (sCT). In this review, we report on a collection of typical performance values for a number of main approaches encountered in the literature for sCT generation as compared to CT. A literature search in the Scopus database resulted in 254 papers which were included in this investigation. A final number of 50 contributions which fulfilled all inclusion criteria were categorized according to applied method, MRI sequence/contrast involved, number of subjects included and anatomical site investigated. The latter included brain, torso, prostate and phantoms. The contributions geometric and/or dosimetric performance metrics were also noted. The majority of studies are carried out on the brain for 5–10 patients with PET/MR applications in mind using a voxel based method. T1 weighted images are most commonly applied. The overall dosimetric agreement is in the order of 0.3–2.5%. A strict gamma criterion of 1% and 1mm has a range of passing rates from 68 to 94% while less strict criteria show pass rates > 98%. The mean absolute error (MAE) is between 80 and 200 HU for the brain and around 40 HU for the prostate. The Dice score for bone is between 0.5 and 0.95. The specificity and sensitivity is reported in the upper 80s% for both quantities and correctly classified voxels average around 84%. The review shows that a variety of promising approaches exist that seem clinical acceptable even with standard clinical MRI sequences. A consistent reference frame for method benchmarking is probably necessary to move the field further towards a widespread clinical implementation.

Twenty Fraction Prostate Radiotherapy with Intra-prostatic Boost: Results of a Pilot Study

AIMS

For patients with high-risk, locally bulky prostate cancer, an intra-prostatic boost to tumour volumes (dose-painting) offers a risk-adapted dose escalation. We evaluated the feasibility of hypofractionated dose-painting radiotherapy and the associated toxicity. The possibility to streamline a radiobiologically optimised planning protocol was also investigated.

MATERIALS AND METHODS

Twenty-eight patients were treated using a dose-painting approach; boost volumes were identified with functional magnetic resonance imaging scans. The prostate dose outside the boost volume was 60 Gy in 20 fractions, and the maximum integrated boost dose was set to 68 Gy, provided that the dose constraints to the organs at risk could be fulfilled. Rotational intensity-modulated radiotherapy was used with daily image guidance and fiducial markers.

RESULTS

The boost dose was escalated to 68 Gy for 25 patients (median dose 69 Gy, range 68-70 Gy); for three patients the boost dose was 67 Gy, due to the proximity of the urethra and/or the rectum. The mean normal tissue complication probability for rectal bleeding was 4.7% (range 3.4-5.8%) and was 3.5% for faecal incontinence (range 2.3-5.0%). At a median follow-up of 38 months (range 32-45) there was no grade 3 toxicity. Two patients developed grade 2 genitourinary toxicity (7.1%) and none developed grade 2 gastrointestinal toxicity. The mean prostate-specific antigen (PSA) for 23 patients who had stopped the adjuvant hormone therapy with a normal testosterone was 0.27 ng/ml (0.02-0.72) at follow-up; two patients have suppressed PSA and testosterone after stopping 3 year adjuvant hormone and three patients have relapsed (one pelvic node, two PSA only) at 36, 12 and 42 months, respectively.

CONCLUSIONS

A hypofractionated radiotherapy schedule, 60 Gy in 20 fractions with intra-prostatic boost dose of 68 Gy, can be achieved without exceeding dose constraints for organs at risk. Hypofractionated dose-painting escalated radiotherapy has an acceptable safety profile. The same planning protocol was used in a phase II single-arm trial (BIOPROP20: ClinicalTrials.gov identifier NCT02125175) and will further be used in a large phase III randomised trial (PIVOTALboost): patients will be randomised standard radiotherapy (60 Gy in 20 fractions) with or without lymph node radiotherapy versus dose-painting radiotherapy with or without lymph node radiotherapy; the trial will be opened for recruitment in summer 2017.

MRI geometric distortion: Impact on tangential whole-breast IMRT

The purpose of this study was to determine the impact of magnetic resonance imaging (MRI) geometric distortions when using MRI for target delineation and planning for whole-breast, intensity-modulated radiotherapy (IMRT). Residual system distortions and combined systematic and patient-induced distortions are considered. This retrospective study investigated 18 patients who underwent whole-breast external beam radiotherapy, where both CT and MRIs were acquired for treatment planning. Distortion phantoms were imaged on two MRI systems, dedicated to radiotherapy planning (a wide, closed-bore 3T and an open-bore 1T). Patient scans were acquired on the 3T system. To simulate MRI-based planning, distortion maps representing residual system distortions were generated via deformable registration between phantom CT and MRIs. Patient CT images and structures were altered to match the residual system distortion measured by the phantoms on each scanner. The patient CTs were also registered to the corresponding patient MRI scans, to assess patient and residual system effects. Tangential IMRT plans were generated and optimized on each resulting CT dataset, then propagated to the original patient CT space. The resulting dose distributions were then evaluated with respect to the standard clinically acceptable DVH and visual assessment criteria. Maximum residual systematic distortion was measured to be 7.9 mm (95%<4.7mm) and 11.9 mm (95%<4.6mm) for the 3T and 1T scanners, respectively, which did not result in clinically unacceptable plans. Eight of the plans accounting for patient and systematic distortions were deemed clinically unacceptable when assessed on the original CT. For these plans, the mean difference in PTV V95 (volume receiving 95% prescription dose) was 0.13±2.51% and -0.73±1.93% for right- and left-sided patients, respectively. Residual system distortions alone had minimal impact on the dosimetry for the two scanners investigated. The combination of MRI systematic and patient-related distortions can result in unacceptable dosimetry for whole-breast IMRT, a potential issue when considering MRI-only radiotherapy treatment planning. PACS number(s): 87.61.-c, 87.57.cp, 87.57.nj, 87.55.D.

Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning

Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of  -1.5  ±  5.0% (mean  ±  SD) in bony structures compared to  -19.9  ±  11.8% and  -8.1  ±  8.2% achieved by MRI segmentation-based (water-only) and atlas-guided AC. Dosimetric evaluation using dose volume histograms and the average difference between minimum/maximum absorbed doses revealed a mean error of less than 1% for the both target volumes and organs at risk. Two-dimensional (2D) gamma analysis of the isocenter dose distributions at 1%/1 mm criterion revealed pass rates of 91.40  ±  7.56%, 96.00  ±  4.11% and 97.67  ±  3.6% for MRI segmentation, atlas-guided and the proposed methods, respectively. The proposed method generates accurate pseudo-CT images from conventional Dixon MRI sequences with improved bone extraction accuracy. The approach is promising for potential use in PET AC and MRI-only or hybrid PET/MRI-guided RT treatment planning.

Technical Note: Characterization and correction of gradient nonlinearity induced distortion on a 1.0 T open bore MR-SIM

PURPOSE

Distortions in magnetic resonance imaging (MRI) compromise spatial fidelity, potentially impacting delineation and dose calculation. We characterized 2D and 3D large field of view (FOV), sequence-independent distortion at various positions in a 1.0 T high-field open MR simulator (MR-SIM) to implement correction maps for MRI treatment planning.

METHODS

A 36 × 43 × 2 cm(3) phantom with 255 known landmarks (∼1 mm(3)) was scanned using 1.0 T high-field open MR-SIM at isocenter in the transverse, sagittal, and coronal axes, and a 465 × 350 × 168 mm(3) 3D phantom was scanned by stepping in the superior-inferior direction in three overlapping positions to achieve a total 465 × 350 × 400 mm(3) sampled FOV yielding >13 800 landmarks (3D Gradient-Echo, TE/TR/α = 5.54 ms/30 ms/28°, voxel size = 1 × 1 × 2 mm(3)). A binary template (reference) was generated from a phantom schematic. An automated program converted MR images to binary via masking, thresholding, and testing for connectivity to identify landmarks. Distortion maps were generated by centroid mapping. Images were corrected via warping with inverse distortion maps, and temporal stability was assessed.

RESULTS

Over the sampled FOV, non-negligible residual gradient distortions existed as close as 9.5 cm from isocenter, with a maximum distortion of 7.4 mm as close as 23 cm from isocenter. Over six months, average gradient distortions were -0.07 ± 1.10 mm and 0.10 ± 1.10 mm in the x and y directions for the transverse plane, 0.03 ± 0.64 and -0.09 ± 0.70 mm in the sagittal plane, and 0.4 ± 1.16 and 0.04 ± 0.40 mm in the coronal plane. After implementing 3D correction maps, distortions were reduced to <1 pixel width (1 mm) for all voxels up to 25 cm from magnet isocenter.

CONCLUSIONS

Inherent distortion due to gradient nonlinearity was found to be non-negligible even with vendor corrections applied, and further corrections are required to obtain 1 mm accuracy for large FOVs. Statistical analysis of temporal stability shows that sequence independent distortion maps are consistent within six months of characterization.

Dosimetric evaluation of synthetic CT relative to bulk density assignment-based magnetic resonance-only approaches for prostate radiotherapy

BACKGROUND

Magnetic resonance imaging (MRI) has been incorporated as an adjunct to CT to take advantage of its excellent soft tissue contrast for contouring. MR-only treatment planning approaches have been developed to avoid errors introduced during the MR-CT registration process. The purpose of this study is to evaluate calculated dose distributions after incorporating a novel synthetic CT (synCT) derived from magnetic resonance simulation images into prostate cancer treatment planning and to compare dose distributions calculated using three previously published MR-only treatment planning methodologies.

METHODS

An IRB-approved retrospective study evaluated 15 prostate cancer patients that underwent IMRT (n = 11) or arc therapy (n = 4) to a total dose of 70.2-79.2 Gy. Original treatment plans were derived from CT simulation images (CT-SIM). T1-weighted, T2-weighted, and balanced turbo field echo images were acquired on a 1.0 T high field open MR simulator with patients immobilized in treatment position. Four MR-derived images were studied: bulk density assignment (10 HU) to water (MRW), bulk density assignments to water and bone with pelvic bone values derived either from literature (491 HU, MRW+B491) or from CT-SIM population average bone values (300 HU, MRW+B300), and synCTs. Plans were recalculated using fixed monitor units, plan dosimetry was evaluated, and local dose differences were characterized using gamma analysis (1 %/1 mm dose difference/distance to agreement).

RESULTS

While synCT provided closest agreement to CT-SIM for D95, D99, and mean dose (<0.7 Gy (1 %)) compared to MRW, MRW+B491, and MRW+B300, pairwise comparisons showed differences were not significant (p < 0.05). Significant improvements were observed for synCT in the bladder, but not for rectum or penile bulb. SynCT gamma analysis pass rates (97.2 %) evaluated at 1 %/1 mm exceeded those from MRW (94.7 %), MRW+B300 (94.0 %), or MRW+B491 (90.4 %). One subject's synCT gamma (1 %/1 mm) results (89.9 %) were lower than MRW (98.7 %) and MRW+B300 (96.7 %) due to increased rectal gas during MR-simulation that did not affect bulk density assignment-based calculations but was reflected in higher rectal doses for synCT.

CONCLUSIONS

SynCT values provided closest dosimetric and gamma analysis agreement to CT-SIM compared to bulk density assignment-based CT surrogates. SynCTs may provide additional clinical value in treatment sites with greater air-to-soft tissue ratio.

Assessing the Dosimetric Accuracy of Magnetic Resonance-Generated Synthetic CT Images for Focal Brain VMAT Radiation Therapy

PURPOSE

The purpose of this study was to assess the dosimetric accuracy of synthetic CT (MRCT) volumes generated from magnetic resonance imaging (MRI) data for focal brain radiation therapy.

METHODS AND MATERIALS

A study was conducted in 12 patients with gliomas who underwent both MR and CT imaging as part of their simulation for external beam treatment planning. MRCT volumes were generated from MR images. Patients' clinical treatment planning directives were used to create 12 individual volumetric modulated arc therapy (VMAT) plans, which were then optimized 10 times on each of their respective CT and MRCT-derived electron density maps. Dose metrics derived from optimization criteria, as well as monitor units and gamma analyses, were evaluated to quantify differences between the imaging modalities.

RESULTS

Mean differences between planning target volume (PTV) doses on MRCT and CT plans across all patients were 0.0% (range: -0.1 to 0.2%) for D(95%); 0.0% (-0.7 to 0.6%) for D(5%); and -0.2% (-1.0 to 0.2%) for D(max). MRCT plans showed no significant changes in monitor units (-0.4%) compared to CT plans. Organs at risk (OARs) had average D(max) differences of 0.0 Gy (-2.2 to 1.9 Gy) over 85 structures across all 12 patients, with no significant differences when calculated doses approached planning constraints.

CONCLUSIONS

Focal brain VMAT plans optimized on MRCT images show excellent dosimetric agreement with standard CT-optimized plans. PTVs show equivalent coverage, and OARs do not show any overdose. These results indicate that MRI-derived synthetic CT volumes can be used to support treatment planning of most patients treated for intracranial lesions.

Camera-based independent couch height verification in radiation oncology

For specific radiation therapy (RT) treatments, it is advantageous to use the isocenter‐to‐couch distance (ICD) for initial patient setup.⁽¹⁾ Since sagging of the treatment couch is not properly taken into account by the electronic readout of the treatment machine, this readout cannot be used for initial patient positioning using the isocenter‐to‐couch distance (ICD). Therefore, initial patient positioning to the prescribed ICD has been carried out using a ruler prior to each treatment fraction in our institution. However, the ruler method is laborious and logging of data is not possible. The objective of this study is to replace the ruler‐based setup of the couch height with an independent, user‐friendly, optical camera‐based method whereby the radiation technologists have to move only the couch to the correct couch height, which is visible on a display. A camera‐based independent couch height measurement system (ICHS) was developed in cooperation with Panasonic Electric Works Western Europe. Clinical data showed that the ICHS is at least as accurate as the application of a ruler to verify the ICD. The camera‐based independent couch height measurement system has been successfully implemented in seven treatment rooms, since 10 September 2012. The benefits of this system are a more streamlined workflow, reduction of human errors during initial patient setup, and logging of the actual couch height at the isocenter. Daily QA shows that the systems are stable and operate within the set 1 mm tolerance. Regular QA of the system is necessary to guarantee that the system works correctly.

PACS number: 87.55 QR