Patient-specific respiratory models using dynamic 3D MRI: preliminary volunteer results.

Organ and tumour motion has a significant impact on the planning and delivery of radiotherapy treatment. At present imaging modality such as four-dimensional computer tomography (4DCT) cannot be used to measure the variability of motion between different respiratory cycles. To create reliable motion models, one needs to acquire volumetric data sets of the lungs with sufficient sampling of the breathing cycle. In this paper we investigate the use of highly parallel MRI to acquire such data. A 32 channel coil in conjunction with a balanced SSFP sequence and a SENSE factor of 6 were used to acquire volumetric data sets in five healthy volunteers. The acquisition was repeated for seven series of different breathing patterns. The data acquired was of sufficient spatial resolution (5 × 5 × 5 mm(3)) and image quality to carry out automated non-rigid registration. The acquisition rate (c.a. 2 volumes per second) allowed for a meaningful sampling of the different respiratory curves that were automatically obtained from the skin surface motion. This acquisition technique should provide images of high enough quality to create statistical respiratory models.

A comparison of internal target volume definition by limited four-dimensional computed tomography, the addition of patient-specific margins, or the addition of generic margins when planning radical radiotherapy for lymph node-positive non-small cell lung cancer.

AIMS: Radical radiotherapy for stage II/III non-small cell lung cancer (NSCLC) includes the primary tumour and positive mediastinal lymph nodes in the clinical target volume (CTV). These move independently of each other in magnitude and direction during respiration. To prevent a geographical miss, a generic margin is usually added to the CTV to create an internal target volume (ITV). Previous studies have investigated the use of additional breath-hold computed tomography to generate patient-specific ITVs for primary tumours alone. We used a similar technique to investigate the generation of patient-specific and generic ITVs for CTVs that include mediastinal lymph nodes. MATERIALS AND METHODS: Thirteen patients with node-positive NSCLC had two limited end-tidal breath-hold computed tomography scans in addition to their planning computed tomography. The CTV was segmented in each scan and a rigid registration was carried out on the vertebral columns to align them. Different methods for generating an ITV were then analysed. RESULTS: Generic margins provided >95% mean coverage of the reference ITV. However, with the exception of 1cm expansion margins, there were cases of inadequate coverage (<95%) for each ITV. With increasing ITV margins there was a small increase in reference ITV coverage, but at the expense of a large increase in the volume of normal tissue within the ITV. DISCUSSION: For stage II/III NSCLC, ITV generation by the addition of a generic margin is not optimal. It can result in both geographical miss and excessive irradiation of normal tissue in the same treatment plan. A simple method for producing a patient-specific ITV is to co-register end-tidal breath-hold computed tomography scans to the planning scan. CONCLUSIONS: Further work is required to determine whether end-tidal breath-hold scans are representative of the anatomy at the limits of tidal respiration. Planning strategies are also needed to account for breathing cycle variation during a course of radiotherapy.

MRI-based measurements of respiratory motion variability and assessment of imaging strategies for radiotherapy planning.

Respiratory organ motion has a significant impact on the planning and delivery of radiotherapy (RT) treatment for lung cancer. Currently widespread techniques, such as 4D-computed tomography (4DCT), cannot be used to measure variability of this motion from one cycle to the next. In this paper, we describe the use of fast magnetic resonance imaging (MRI) techniques to investigate the intra- and inter-cycle reproducibility of respiratory motion and also to estimate the level of errors that may be introduced into treatment delivery by using various breath-hold imaging strategies during lung RT planning. A reference model of respiratory motion is formed to enable comparison of different breathing cycles at any arbitrary position in the respiratory cycle. This is constructed by using free-breathing images from the inhale phase of a single breathing cycle, then co-registering the images, and thereby tracking landmarks. This reference model is then compared to alternative models constructed from images acquired during the exhale phase of the same cycle and the inhale phase of a subsequent cycle, to assess intra- and inter-cycle variability ('hysteresis' and 'reproducibility') of organ motion. The reference model is also compared to a series of models formed from breath-hold data at exhale and inhale. Evaluation of these models is carried out on data from ten healthy volunteers and five lung cancer patients. Free-breathing models show good levels of intra- and inter-cycle reproducibility across the tidal breathing range. Mean intra-cycle errors in the position of organ surface landmarks of 1.5(1.4)-3.5(3.3) mm for volunteers and 2.8(1.8)-5.2(5.2) mm for patients. Equivalent measures of inter-cycle variability across this range are 1.7(1.0)-3.9(3.3) mm for volunteers and 2.8(1.8)-3.3(2.2) mm for patients. As expected, models based on breath-hold sequences do not represent normal tidal motion as well as those based on free-breathing data, with mean errors of 4.4(2.2)-7.7(3.9) mm for volunteers and 10.1(6.1)-12.5(6.3) mm for patients. Errors are generally larger still when using a single breath-hold image at either exhale or inhale to represent the lung. This indicates that account should be taken of intra- and inter-cycle respiratory motion variability and that breath-hold-based methods of obtaining data for RT planning may potentially introduce large errors. This approach to analysis of motion and variability has potential to inform decisions about treatment margins and optimize RT planning.

Using combined x-ray and MR imaging for prostate I-125 post-implant dosimetry: phantom validation and preliminary patient work.

Post-implantation dosimetry is an important element of permanent prostate brachytherapy. This process relies on accurate localization of implanted seeds relative to the surrounding organs. Localization is commonly achieved using CT images, which provide suboptimal prostate delineation. On MR images, conversely, prostate visualization is excellent but seed localization is imprecise due to distortion and susceptibility artefacts. This paper presents a method based on fused MR and x-ray images acquired consecutively in a combined x-ray and MRI interventional suite. The method does not rely on any explicit registration step but on a combination of system calibration and tracking. A purpose-built phantom was imaged using MRI and x-rays, and the images were successfully registered. The same protocol was applied to three patients where combining soft tissue information from MRI with stereoscopic seed identification from x-ray imaging facilitated post-implant dosimetry. This technique has the potential to improve on dosimetry using either CT or MR alone.

Tissue deformation and shape models in image-guided interventions: a discussion paper.

This paper promotes the concept of active models in image-guided interventions. We outline the limitations of the rigid body assumption in image-guided interventions and describe how intraoperative imaging provides a rich source of information on spatial location of anatomical structures and therapy devices, allowing a preoperative plan to be updated during an intervention. Soft tissue deformation and variation from an atlas to a particular individual can both be determined using non-rigid registration. Established methods using free-form deformations have a very large number of degrees of freedom. Three examples of deformable models--motion models, biomechanical models and statistical shape models--are used to illustrate how prior information can be used to restrict the number of degrees of freedom of the registration algorithm and thus provide active models for image-guided interventions. We provide preliminary results from applications for each type of model.

Registration of freehand 3D ultrasound and magnetic resonance liver images.

We present a method to register a preoperative MR volume to a sparse set of intraoperative ultrasound slices. Our aim is to allow the transfer of information from preoperative modalities to intraoperative ultrasound images to aid needle placement during thermal ablation of liver metastases. The spatial relationship between ultrasound slices is obtained by tracking the probe using a Polaris optical tracking system. Images are acquired at maximum exhalation and we assume the validity of the rigid body transformation. An initial registration is carried out by picking a single corresponding point in both modalities. Our strategy is to interpret both sets of images in an automated pre-processing step to produce evidence or probabilities of corresponding structure as a pixel or voxel map. The registration algorithm converts the intensity values of the MR and ultrasound images into vessel probability values. The registration is then carried out between the vessel probability images. Results are compared to a "bronze standard" registration which is calculated using a manual point/line picking algorithm and verified using visual inspection. Results show that our starting estimate is within a root mean square target registration error (calculated over the whole liver) of 15.4 mm to the "bronze standard" and this is improved to 3.6 mm after running the intensity-based algorithm.