Iterative framework for the joint segmentation and CT synthesis of MR images: application to MRI-only radiotherapy treatment planning

To tackle the problem of magnetic resonance imaging (MRI)-only radiotherapy treatment planning (RTP), we propose a multi-atlas information propagation scheme that jointly segments organs and generates pseudo x-ray computed tomography (CT) data from structural MR images (T1-weighted and T2-weighted). As the performance of the method strongly depends on the quality of the atlas database composed of multiple sets of aligned MR, CT and segmented images, we also propose a robust way of registering atlas MR and CT images, which combines structure-guided registration, and CT and MR image synthesis. We first evaluated the proposed framework in terms of segmentation and CT synthesis accuracy on 15 subjects with prostate cancer. The segmentations obtained with the proposed method were compared using the Dice score coefficient (DSC) to the manual segmentations. Mean DSCs of 0.73, 0.90, 0.77 and 0.90 were obtained for the prostate, bladder, rectum and femur heads, respectively. The mean absolute error (MAE) and the mean error (ME) were computed between the reference CTs (non-rigidly aligned to the MRs) and the pseudo CTs generated with the proposed method. The MAE was on average [Formula: see text] HU and the ME [Formula: see text] HU. We then performed a dosimetric evaluation by re-calculating plans on the pseudo CTs and comparing them to the plans optimised on the reference CTs. We compared the cumulative dose volume histograms (DVH) obtained for the pseudo CTs to the DVH obtained for the reference CTs in the planning target volume (PTV) located in the prostate, and in the organs at risk at different DVH points. We obtained average differences of [Formula: see text] in the PTV for [Formula: see text], and between [Formula: see text] and 0.05% in the PTV, bladder, rectum and femur heads for D mean and [Formula: see text]. Overall, we demonstrate that the proposed framework is able to automatically generate accurate pseudo CT images and segmentations in the pelvic region, potentially bypassing the need for CT scan for accurate RTP.

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.

Complementary physical therapies for movement disorders in Parkinson's disease: a systematic review

BACKGROUND

The growth and popularity of complementary physical therapies for Parkinson's disease (PD) attempt to fill the gap left by conventional exercises, which does not always directly target wellbeing, enjoyment and social participation.

AIM

To evaluate the effects of complementary physical therapies on motor performance, quality of life and falls in people living with PD.

DESIGN

Systematic review with meta-analysis.

POPULATION

Outpatients--adults diagnosed with idiopathic PD, male or female, modified Hoehn and Yahr scale I-IV, any duration of PD, any duration of physical treatment or exercise.

METHODS

Randomized controlled trials, non-randomized controlled trials and case series studies were identified by systematic searching of health and rehabilitation electronic databases. A standardized form was used to extract key data from studies by two independent researchers.

RESULTS

1210 participants from 20 randomized controlled trials, two non-randomized controlled trials and 13 case series studies were included. Most studies had moderately strong methodological quality. Dancing, water exercises and robotic gait training were an effective adjunct to medical management for some people living with PD. Virtual reality training, mental practice, aerobic training, boxing and Nordic walking training had a small amount of evidence supporting their use in PD.

CONCLUSION

On balance, alternative physical therapies are worthy of consideration when selecting treatment options for people with this common chronic disease.

CLINICAL REHABILITATION IMPACT

Complementary physical therapies such as dancing, hydrotherapy and robotic gait training appear to afford therapeutic benefits, increasing mobility and quality of life, in some people living with PD.

Toward adaptive radiotherapy for head and neck patients: Feasibility study on using CT-to-CBCT deformable registration for "dose of the day" calculations

PURPOSE

The aim of this study was to evaluate the appropriateness of using computed tomography (CT) to cone-beam CT (CBCT) deformable image registration (DIR) for the application of calculating the "dose of the day" received by a head and neck patient.

METHODS

NiftyReg is an open-source registration package implemented in our institution. The affine registration uses a Block Matching-based approach, while the deformable registration is a GPU implementation of the popular B-spline Free Form Deformation algorithm. Two independent tests were performed to assess the suitability of our registrations methodology for "dose of the day" calculations in a deformed CT. A geometric evaluation was performed to assess the ability of the DIR method to map identical structures between the CT and CBCT datasets. Features delineated in the planning CT were warped and compared with features manually drawn on the CBCT. The authors computed the dice similarity coefficient (DSC), distance transformation, and centre of mass distance between features. A dosimetric evaluation was performed to evaluate the clinical significance of the registrations errors in the application proposed and to identify the limitations of the approximations used. Dose calculations for the same intensity-modulated radiation therapy plan on the deformed CT and replan CT were compared. Dose distributions were compared in terms of dose differences (DD), gamma analysis, target coverage, and dose volume histograms (DVHs). Doses calculated in a rigidly aligned CT and directly in an extended CBCT were also evaluated.

RESULTS

A mean value of 0.850 in DSC was achieved in overlap between manually delineated and warped features, with the distance between surfaces being less than 2 mm on over 90% of the pixels. Deformable registration was clearly superior to rigid registration in mapping identical structures between the two datasets. The dose recalculated in the deformed CT is a good match to the dose calculated on a replan CT. The DD is smaller than 2% of the prescribed dose on 90% of the body's voxels and it passes a 2% and 2 mm gamma-test on over 95% of the voxels. Target coverage similarity was assessed in terms of the 95%-isodose volumes. A mean value of 0.962 was obtained for the DSC, while the distance between surfaces is less than 2 mm in 95.4% of the pixels. The method proposed provided adequate dose estimation, closer to the gold standard than the other two approaches. Differences in DVH curves were mainly due to differences in the OARs definition (manual vs warped) and not due to differences in dose estimation (dose calculated in replan CT vs dose calculated in deformed CT).

CONCLUSIONS

Deforming a planning CT to match a daily CBCT provides the tools needed for the calculation of the "dose of the day" without the need to acquire a new CT. The initial clinical application of our method will be weekly offline calculations of the "dose of the day," and use this information to inform adaptive radiotherapy (ART). The work here presented is a first step into a full implementation of a "dose-driven" online ART.

Challenges of radiotherapy: report on the 4D treatment planning workshop 2013

This report, compiled by experts on the treatment of mobile targets with advanced radiotherapy, summarizes the main conclusions and innovations achieved during the 4D treatment planning workshop 2013. This annual workshop focuses on research aiming to advance 4D radiotherapy treatments, including all critical aspects of time resolved delivery, such as in-room imaging, motion detection, motion managing, beam application, and quality assurance techniques. The report aims to revise achievements in the field and to discuss remaining challenges and potential solutions. As main achievements advances in the development of a standardized 4D phantom and in the area of 4D-treatment plan optimization were identified. Furthermore, it was noticed that MR imaging gains importance and high interest for sequential 4DCT/MR data sets was expressed, which represents a general trend of the field towards data covering a longer time period of motion. A new point of attention was work related to dose reconstructions, which may play a major role in verification of 4D treatment deliveries. The experimental validation of results achieved by 4D treatment planning and the systematic evaluation of different deformable image registration methods especially for inter-modality fusions were identified as major remaining challenges. A challenge that was also suggested as focus for future 4D workshops was the adaptation of image guidance approaches from conventional radiotherapy into particle therapy. Besides summarizing the last workshop, the authors also want to point out new evolving demands and give an outlook on the focus of the next workshop.

Building motion models of lung tumours from cone-beam CT for radiotherapy applications

A method is presented to build a surrogate-driven motion model of a lung tumour from a cone-beam CT scan, which does not require markers. By monitoring an external surrogate in real time, it is envisaged that the motion model be used to drive gated or tracked treatments. The motion model would be built immediately before each fraction of treatment and can account for inter-fraction variation. The method could also provide a better assessment of tumour shape and motion prior to delivery of each fraction of stereotactic ablative radiotherapy. The two-step method involves enhancing the tumour region in the projections, and then fitting the surrogate-driven motion model. On simulated data, the mean absolute error was reduced to 1 mm. For patient data, errors were determined by comparing estimated and clinically identified tumour positions in the projections, scaled to mm at the isocentre. Averaged over all used scans, the mean absolute error was under 2.5 mm in superior-inferior and transverse directions.

Establishing spatial correspondence for the analysis of images from highly deforming anatomy

This invited presentation summarizes recent advances in the incorporation of knowledge of the geometry, tissue mechanical properties and imaging characteristics in establishing spatial correspondence between multiple images of highly deforming, soft tissue structures. Spatial correspondence is used to aid diagnosis and in the extraction of quantitative parameters for disease detection, monitoring disease progression and assessing therapeutic response. The work is illustrated through clinical examples of multi-modal imaging of the breast, assessment of small bowel motility and polyp detection in the large bowel.

Computational models in image guided interventions

In image-guided surgery and image-directed therapy a plan based on pre-procedure imaging is registered to the patient in the operating or treatment room using a 3D spatial localizer. The plan can be used as long as the transformation between plan and patient remains valid. Most systems use a rigid-body transformation restricting guidance to bony structures (e.g. orthopaedic surgery or maxillo-facial surgery) or structures that are rigidly related to bone (e.g. neurosurgery). Fully 3D intra-operative imaging such as interventional MR allows image guidance to be extended to structures that move or deform during an intervention. However, this technology is expensive, interferes significantly with standard surgical protocols and requires computationally expensive non-rigid registration of the plan to the current patient scan. This talk will describe four examples where computational models of motion and anatomy are combined with 2D intra-operative imaging to extend the scope of image directed methods. In the first, image guided neurosurgery, we show how intra-operative imaging may account for distortion caused by the intervention itself. In two further applications - percutaneous ablation of metastatic liver disease and external beam radiotherapy of the lung - we show how computational models of motion might be used in conjunction with a therapy plan to guide the intervention. In the final example, selected from orthopaedic surgery, we show recent advances that demonstrate how a statistical shape model generated from example 3D images, can be used to provide image guidance without any pre-operative 3D imaging.

WE-E-213CD-03: Inverse-Consistent Symmetric Registration of Inner Colon Surfaces Derived from Prone and Supine CT Colonography

PURPOSE

Robust registration of prone and supine colonie surfaces acquired during CT colonography may lead to faster and more accurate detection of colorectal cancer and polyps. Any directional bias when registering one surface to the other could precipitate incorrect anatomical correspondence and engender reader error. Despite this, non-rigid registration methods are often implemented asymmetrically, which could negatively influence the registration. We aimed to reduce directional bias and so increase robustness by adapting a cylindrical registration algorithm to be both symmetric and inverse-consistent.

METHODS

The registration task can be simplified by mapping both prone and supine colonie surfaces onto regular cylinders. Spatial correspondence can then be established in cylindrical space using the original surfaces' local shape indices. We implemented a symmetric formulation of the popular non-rigid B-spline image registration method in cylindrical space. A symmetric similarity measure computes the sum of squared differences between both cylindrical representations of prone-to-supine and supine-to-prone directions simultaneously. Inverse consistency of the transformation is enforced by adding an appropriately weighted penalty term to the optimisation function.

RESULTS

We selected 8 CT colonography patient cases with marked variation in luminal distension and surface morphology. We randomly allocated 4 of these for tuning an optimal set of registration parameters and 4 for validation. The mean inverse-consistency error was reduced by 32% from 4.8mm to 3.2mm by the new symmetric formulation. The mean registration error improved from 8.2mm to 7.3mm for 330 manually chosen reference points on the 4 validation sets.

CONCLUSIONS

A symmetric formulation of prone and supine surface registration improves the quality of registration. Information from both prone-to-supine and supine-to-prone directions helps enforce convergence towards a more accurate solution due to reduced directional bias. A more robust and accurate registration will facilitate interpretation of CT colonography and has the potential to improve existing computer-aided detection methods. The authors gratefully acknowledge financial support for this work from the NIHR program: “Imaging diagnosis of colorectal cancer: Interventions for efficient and acceptable diagnosis in symptomatic and screening populationsâ€.