Jane M. Blackall

University College London, Londinium, England, United Kingdom

Are you Jane M. Blackall?

Claim your profile

Publications (36)45.21 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: 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.
    Physica Medica 03/2012; · 1.17 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: 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. 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. 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. 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. 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.
    Clinical Oncology 06/2008; 20(4):293-300. · 2.86 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Summary Respiratory-induced tumour motion shows marked intra- and inter-fraction variability over a course of radiotherapy. This has implications for Internal Target Volume definition, and the delivery of gated or tracked radiotherapy. We investigated a novel method of respiratory coaching to see if this could reduce variability. 15 subjects participated in 2 different assessments of coaching: Spirometry based and VisionRT-Tracked-Point based. The order of participation was randomised. For each assessment subjects were monitored breathing in 3 modes: normal breathing; self-coached regular breathing; sine-wave coached breathing. The sine-wave parameters were based on the subjects own normal breathing, and the wave was displayed on a set of goggles worn by the subject. Their own breathing trace superimposed, and they were instructed to follow the wave.The results demonstrated that the impact of respiratory coaching varied between patients and across the breathing cycle. There were also differences depending on the assessment technique. Sine wave coaching was beneficial in more cases than it was detrimental, whereas the reverse was true for instructing patients to breathe regularly. However, in the majority of cases the coaching interventions had no impact. Patient selection is important to determine who might benefit from respiratory coaching.
    01/2008;
  • Medical Physics 01/2008; 35(6). · 2.91 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper describes recent progress in developing motion and biomechanical models for image guided interventions. The challenge is to provide navigational support for interventions and image directed therapies on soft or mobile structures. We describe our recent progress in generating and testing models of respiratory motion for image directed radiotherapy and focal ablation in the lung and liver, and the development of biomechanical models for image guided local excision in breast surgery.
    Proceedings of the 2007 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Washington, DC, USA, April 12-16, 2007; 01/2007
  • Medical Physics 01/2007; 34(6). · 2.91 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Respiratory motion causes errors when planning and delivering radiotherapy treatment to lung cancer patients. To reduce these errors, methods of acquiring and using four-dimensional computed tomography (4DCT) datasets have been developed. We have developed a novel method of constructing computational motion models from 4DCT. The motion models attempt to describe an average respiratory cycle, which reduces the effects of variation between different cycles. They require substantially less memory than a 4DCT dataset, are continuous in space and time, and facilitate automatic target propagation and combining of doses over the respiratory cycle. The motion models are constructed from CT data acquired in cine mode while the patient is free breathing (free breathing CT - FBCT). A "slab" of data is acquired at each couch position, with 3-4 contiguous slabs being acquired per patient. For each slab a sequence of 20 or 30 volumes was acquired over 20 seconds. A respiratory signal is simultaneously recorded in order to calculate the position in the respiratory cycle for each FBCT. Additionally, a high quality reference CT volume is acquired at breath hold. The reference volume is nonrigidly registered to each of the FBCT volumes. A motion model is then constructed for each slab by temporally fitting the nonrigid registration results. The value of each of the registration parameters is related to the position in the respiratory cycle by fitting an approximating B spline to the registration results. As an approximating function is used, and the data is acquired over several respiratory cycles, the function should model an average respiratory cycle. This can then be used to calculate the value of each degree of freedom at any desired position in the respiratory cycle. The resulting nonrigid transformation will deform the reference volume to predict the contents of the slab at the desired position in the respiratory cycle. The slab model predictions are then concatenated to produce a combined prediction over the entire region of interest. We have performed a number of experiments to assess the accuracy of the nonrigid registration results and the motion model predictions. The individual slab models were evaluated by expert visual assessment and the tracking of easily identifiable anatomical points. The combined models were evaluated by calculating the discontinuities between the transformations at the slab boundaries. The experiments were performed on five patients with a total of 18 slabs between them. For the point tracking experiments, the mean distance between where a clinician manually identified a point and where the registration results located the point, the target registration error (TRE), was 1.3 mm. The mean distance between a manually identified point and the models prediction of the point's location, the target model error (TME), was 1.6 mm. The mean discontinuity between model predictions at the slab boundaries, the Continuity Error, was 2.2 mm. The results show that the motion models perform with a level of accuracy comparable to the slice thickness of 1.5 mm.
    Medical Physics 10/2006; 33(9):3348-58. · 2.91 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: 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.
    Physics in Medicine and Biology 10/2006; 51(17):4147-69. · 2.70 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This study investigated the sensitivity of static planning of intensity-modulated beams (IMBs) to intrafraction deformable organ motion and assessed whether smoothing of the IMBs at the treatment-planning stage can reduce this sensitivity. The study was performed with a 4D computed tomography (CT) data set for an IMRT treatment of a patient with liver cancer. Fluence profiles obtained from inverse-planning calculations on a standard reference CT scan were redelivered on a CT scan from the 4D data set at a different part of the breathing cycle. The use of a nonrigid registration model on the 4D data set additionally enabled detailed analysis of the overall intrafraction motion effects on the IMRT delivery during free breathing. Smoothing filters were then applied to the beam profiles within the optimization process to investigate whether this could reduce the sensitivity of IMBs to intrafraction organ motion. In addition, optimal fluence profiles from calculations on each individual phase of the breathing cycle were averaged to mimic the convolution of a static dose distribution with a motion probability kernel and assess its usefulness. Results from nonrigid registrations of the CT scan data showed a maximum liver motion of 7 mm in superior-inferior direction for this patient. Dose-volume histogram (DVH) comparison indicated a systematic shift when planning treatment on a motion-frozen, standard CT scan but delivering over a full breathing cycle. The ratio of the dose to 50% of the normal liver to 50% of the planning target volume (PTV) changed up to 28% between different phases. Smoothing beam profiles with a median-window filter did not overcome the substantial shift in dose due to a difference in breathing phase between planning and delivery of treatment. Averaging of optimal beam profiles at different phases of the breathing cycle mainly resulted in an increase in dose to the organs at risk (OAR) and did not seem beneficial to compensate for organ motion compared with using a large margin. Additionally, the results emphasized the need for 4D CT scans when aiming to reduce the internal margin (IM). Using only a single planning scan introduces a systematic shift in the dose distribution during delivery. Smoothing beam profiles either based on a single scan or over the different breathing phases was not beneficial for reducing this shift.
    Medical Physics 09/2006; 33(8):2809-18. · 2.91 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: 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.
    Physics in Medicine and Biology 04/2006; 51(5):1129-37. · 2.70 Impact Factor
  • Radiotherapy & Oncology, ISSN 0167-8140. 01/2006; 81(1):S209.
  • Source
    J.M. Blackall, G.P. Penney, A.P. King, D.J. Hawkes
    [Show abstract] [Hide abstract]
    ABSTRACT: We present a method for alignment of an interventional plan to optically tracked two-dimensional intraoperative ultrasound (US) images of the liver. Our clinical motivation is to enable the accurate transfer of information from three-dimensional (3D) preoperative imaging modalities [magnetic resonance (MR) or computed tomography (CT)] to intraoperative US to aid needle placement for thermal ablation of liver metastases. An initial rigid registration to intraoperative coordinates is obtained using a set of US images acquired at maximum exhalation. A preprocessing step is applied to both the preoperative images and the US images to produce evidence of corresponding structures. This yields two sets of images representing classification of regions as vessels. The registration then proceeds using these images. The preoperative images and plan are then warped to correspond to a single US slice acquired at an unknown point in the breathing cycle where the liver is likely to have moved and deformed relative to the preoperative image. Alignment is constrained using a patient-specific model of breathing motion and deformation. Target registration error is estimated by carrying out simulation experiments using resliced MR volumes to simulate real US and comparing the registration results to a "bronze-standard" registration performed on the full MR volume. Finally, the system is tested using real US and verified using visual inspection.
    IEEE Transactions on Medical Imaging 12/2005; · 4.03 Impact Factor
  • Radiotherapy and Oncology 09/2005; 76. · 4.52 Impact Factor
  • Lung Cancer 07/2005; 49. · 3.39 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Respiratory motion causes problems of tumour localisation in radiotherapy treatment planning for lung cancer patients. We have developed a novel method of building patient specific motion models, which model the movement and non-rigid deformation of a lung tumour and surrounding lung tissue over the respiratory cycle. Free-breathing (FB) CT scans are acquired in cine mode, using 3 couch positions to acquire contiguous 'slabs' of 16 slices covering the region of interest. For each slab, 20 FB volumes are acquired over approx 20s. A reference volume acquired at Breath Hold (BH) and covering the whole lung, is non-rigidly registered to each of the FB volumes. The FB volumes are assigned a position in the respiratory cycle (PRC) calculated from the displacement of the chest wall. A motion model is then constructed for each slab, by fitting functions that temporally interpolate the registration results over the respiratory cycle. This can produce a prediction of the lung and tumour within the slab at any arbitrary PRC. The predictions for each of the slabs are then combined to produce a volume covering the whole region of interest. Results indicate that the motion modelling method shows considerable promise, offering significant improvement over current clinical practice, and potential advantages over alternative 4D CT imaging techniques. Using this framework, we examined and evaluated several different functions for performing the temporal interpolation. We believe the results of these comparisons will aid future model building for this and other applications.© (2005) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
    04/2005;
  • [Show abstract] [Hide abstract]
    ABSTRACT: 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.
    Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 02/2005; 7:7246-9.
  • [Show abstract] [Hide abstract]
    ABSTRACT: 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.
    Medical Image Analysis 01/2005; 9:163-175. · 4.09 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Respiratory motion causes problems of tumour localisation in radiotherapy treatment planning for lung cancer patients. We have developed a novel method of building patient specific motion models, which model the movement and non-rigid deformation of a lung tumour and surrounding lung tissue over the respiratory cycle. Free-breathing (FB) CT scans are acquired in cine mode, using 3 couch positions to acquire contiguous 'slabs' of 16 slices covering the region of interest. For each slab, 20 FB volumes are acquired over approx 20s. A reference volume acquired at Breath Hold (BH) and covering the whole lung, is non-rigidly registered to each of the FB volumes. The FB volumes are assigned a position in the respiratory cycle (PRC) calculated from the displacement of the chest wall. A motion model is then constructed for each slab, by fitting functions that temporally interpolate the registration results over the respiratory cycle. This can produce a prediction of the lung and tumour within the slab at any arbitrary PRC. The predictions for each of the slabs are then combined to produce a volume covering the whole region of interest. Results indicate that the motion modelling method shows considerable promise, offering significant improvement over current clinical practice, and potential advantages over alternative 4D CT imaging techniques. Using this framework, we examined and evaluated several different functions for performing the temporal interpolation. We believe the results of these comparisons will aid future model building for this and other applications.
    Proc SPIE 01/2005;
  • Radiotherapy and Oncology - RADIOTHER ONCOL. 01/2005; 76.
  • [Show abstract] [Hide abstract]
    ABSTRACT: We present a method for non-rigid registration of preoperative magnetic resonance (MR) images and an interventional plan to sparse intraoperative ultrasound (US) of the liver. Our clinical motivation is to enable the accurate transfer of information from preoperative imaging modalities to intraoperative ultrasound to aid needle placement for thermal ablation of liver metastases. An inital rigid registration to intraoperative coordinates is obtained using a set of ultrasound images acquired at maximum exhalation. A pre-processing step is applied to both the MR and US images. The preoperative image and plan are then aligned to a single ultrasound slice acquired at an unknown point in the breathing cycle where the liver is likely to have moved and deformed relative to the preoperative image. Alignment is constrained using a patient-specific model of breathing motion and deformation. Target registration error is estimated by carrying out simulation experiments using sparsely re-sliced MR volumes in place of real ultrasound and comparing the registration results to a gold-standard registration performed on the full MR volume. Experiments using real ultrasound are then carried out and verified using visual inspection.
    Proc SPIE 05/2004;

Publication Stats

828 Citations
45.21 Total Impact Points

Institutions

  • 2006–2012
    • University College London
      • Centre for Medical Image Computing
      Londinium, England, United Kingdom
    • Guy's and St Thomas' NHS Foundation Trust
      • Department of Medical Physics
      Londinium, England, United Kingdom
  • 2005
    • King's College London
      • Division of Imaging Sciences and Biomedical Engineering
      Londinium, England, United Kingdom