Integrating diagnostic B-mode ultrasonography into CT-based radiation treatment planning

The Potential of Photoacoustic Imaging in Radiation Oncology

Radiotherapy is recognized globally as a mainstay of treatment in most solid tumors and is essential in both curative and palliative settings. Ionizing radiation is frequently combined with surgery, either preoperatively or postoperatively, and with systemic chemotherapy. Recent advances in imaging have enabled precise targeting of solid lesions yet substantial intratumoral heterogeneity means that treatment planning and monitoring remains a clinical challenge as therapy response can take weeks to manifest on conventional imaging and early indications of progression can be misleading. Photoacoustic imaging (PAI) is an emerging modality for molecular imaging of cancer, enabling non-invasive assessment of endogenous tissue chromophores with optical contrast at unprecedented spatio-temporal resolution. Preclinical studies in mouse models have shown that PAI could be used to assess response to radiotherapy and chemoradiotherapy based on changes in the tumor vascular architecture and blood oxygen saturation, which are closely linked to tumor hypoxia. Given the strong relationship between hypoxia and radio-resistance, PAI assessment of the tumor microenvironment has the potential to be applied longitudinally during radiotherapy to detect resistance at much earlier time-points than currently achieved by size measurements and tailor treatments based on tumor oxygen availability and vascular heterogeneity. Here, we review the current state-of-the-art in PAI in the context of radiotherapy research. Based on these studies, we identify promising applications of PAI in radiation oncology and discuss the future potential and outstanding challenges in the development of translational PAI biomarkers of early response to radiotherapy.

Combined Ultrasound and Photoacoustic Image Guidance of Spinal Pedicle Cannulation Demonstrated With Intact ex vivo Specimens

OBJECTIVE

Spinal fusion surgeries require accurate placement of pedicle screws in anatomic corridors without breaching bone boundaries. We are developing a combined ultrasound and photoacoustic image guidance system to avoid pedicle screw misplacement and accidental bone breaches, which can lead to nerve damage.

METHODS

Pedicle cannulation was performed on a human cadaver, with co-registered photoacoustic and ultrasound images acquired at various time points during the procedure. Bony landmarks obtained from coherence-based ultrasound images of lumbar vertebrae were registered to post-operative CT images. Registration methods were additionally tested on an ex vivo caprine vertebra.

RESULTS

Locally weighted short-lag spatial coherence (LW-SLSC) ultrasound imaging enhanced the visualization of bony structures with generalized contrast-to-noise ratios (gCNRs) of 0.99 and 0.98-1.00 in the caprine and human vertebrae, respectively. Short-lag spatial coherence (SLSC) and amplitude-based delay-and-sum (DAS) ultrasound imaging generally produced lower gCNRs of 0.98 and 0.84, respectively, in the caprine vertebra and 0.84-0.93 and 0.34-0.99, respectively, in the human vertebrae. The mean ± standard deviation of the area of -6 dB contours created from DAS photoacoustic images acquired with an optical fiber inserted in prepared pedicle holes (i.e., fiber surrounded by cancellous bone) and holes created after intentional breaches (i.e., fiber exposed to cortical bone) was 10.06 ±5.22 mm ² and 2.47 ±0.96 mm ², respectively (p 0.01).

CONCLUSIONS

Coherence-based LW-SLSC and SLSC beamforming improved visualization of bony anatomical landmarks for ultrasound-to-CT registration, while amplitude-based DAS beamforming successfully distinguished photoacoustic signals within the pedicle from less desirable signals characteristic of impending bone breaches.

SIGNIFICANCE

These results are promising to improve visual registration of ultrasound and photoacoustic images with CT images, as well as to assist surgeons with identifying and avoiding impending bone breaches during pedicle cannulation in spinal fusion surgeries.

The Stacked-Ellipse Algorithm: An Ultrasound-Based 3-D Uterine Segmentation Tool for Enabling Adaptive Radiotherapy for Uterine Cervix Cancer

The stacked-ellipse (SE) algorithm was developed to rapidly segment the uterus on 3-D ultrasound (US) for the purpose of enabling US-guided adaptive radiotherapy (RT) for uterine cervix cancer patients. The algorithm was initialised manually on a single sagittal slice to provide a series of elliptical initialisation contours in semi-axial planes along the uterus. The elliptical initialisation contours were deformed according to US features such that they conformed to the uterine boundary. The uterus of 15 patients was scanned with 3-D US using the Clarity System (Elekta Ltd.) at multiple days during RT and manually contoured (n = 49 images and corresponding contours). The median (interquartile range) Dice similarity coefficient and mean surface-to-surface-distance between the SE algorithm and manual contours were 0.80 (0.03) and 3.3 (0.2) mm, respectively, which are within the ranges of reported inter-observer contouring variabilities. The SE algorithm could be implemented in adaptive RT to precisely segment the uterus on 3-D US.

GPU-based volume reconstruction for freehand 3D ultrasound imaging

Volume reconstruction plays an important role in improving image quality for freehand three-dimensional (3D) ultrasound imaging. The kernel regression provides an effective method for volume reconstruction in 3D ultrasound imaging, but it requires heavily computational time-cost. In this paper, a programmable graphic-processor-unit-(GPU) based fast kernel regression method is proposed for freehand 3D ultrasound volume reconstruction. The most significant aspect of our method is the adopting of powerful data-parallel computing capability of GPU to improve the overall efficiency. To produce higher image quality, the results of the kernel regression with various parameter settings is deeply investigated under the help of the fast implementation of the algorithm. Experimental results demonstrate that the computational performance of the proposed GPU-based method can be over 200 times faster than that on CPU. Better image quality for speckle reduction and details preservation can be obtained with the parameter setting of kernel window size of 5×5×5 and kernel bandwidth of 1.0.

Review of ultrasound image guidance in external beam radiotherapy: I. Treatment planning and inter-fraction motion management

In modern radiotherapy, verification of the treatment to ensure the target receives the prescribed dose and normal tissues are optimally spared has become essential. Several forms of image guidance are available for this purpose. The most commonly used forms of image guidance are based on kilovolt or megavolt x-ray imaging. Image guidance can also be performed with non-harmful ultrasound (US) waves. This increasingly used technique has the potential to offer both anatomical and functional information.This review presents an overview of the historical and current use of two-dimensional and three-dimensional US imaging for treatment verification in radiotherapy. The US technology and the implementation in the radiotherapy workflow are described. The use of US guidance in the treatment planning process is discussed. The role of US technology in inter-fraction motion monitoring and management is explained, and clinical studies of applications in areas such as the pelvis, abdomen and breast are reviewed. A companion review paper (O'Shea et al 2015 Phys. Med. Biol. submitted) will extensively discuss the use of US imaging for intra-fraction motion quantification and novel applications of US technology to RT.

Magnetic microbubble-mediated ultrasound-MRI registration based on robust optical flow model

Background

As a dual-modality contrast agent, magnetic microbubbles (MMBs) can not only improve contrast of ultrasound (US) image, but can also serve as a contrast agent of magnetic resonance image (MRI). With the help of MMBs, a new registration method between US image and MRI is presented.

Methods

In this method, MMBs were used in both ultrasound and magnetic resonance imaging process to enhance the most important information of interest. In order to reduce the influence of the speckle noise to registration, semi-automatic segmentations of US image and MRI were carried out by using active contour model. After that, a robust optical flow model between US image segmentation (floating image) and MRI segmentation (reference image) was built, and the vector flow field was estimated by using the Coarse-to-fine Gaussian pyramid and graduated non-convexity (GNC) schemes.

Results

Qualitative and quantitative analyses of multiple group comparison experiments showed that registration results using all methods tested in this paper without MMBs were unsatisfactory. On the contrary, the proposed method combined with MMBs led to the best registration results.

Conclusion

The proposed algorithm combined with MMBs contends with larger deformation and performs well not only for local deformation but also for global deformation. The comparison experiments also demonstrated that ultrasound-MRI registration using the above-mentioned method might be a promising method for obtaining more accurate image information.

Hybrid feature-based diffeomorphic registration for tumor tracking in 2-D liver ultrasound images

Real-time ultrasound image acquisition is a pivotal resource in the medical community, in spite of its limited image quality. This poses challenges to image registration methods, particularly to those driven by intensity values. We address these difficulties in a novel diffeomorphic registration technique for tumor tracking in series of 2-D liver ultrasound. Our method has two main characteristics: 1) each voxel is described by three image features: intensity, local phase, and phase congruency; 2) we compute a set of forces from either local information (Demons-type of forces), or spatial correspondences supplied by a block-matching scheme, from each image feature. A family of update deformation fields which are defined by these forces, and inform upon the local or regional contribution of each image feature are then composed to form the final transformation. The method is diffeomorphic, which ensures the invertibility of deformations. The qualitative and quantitative results yielded by both synthetic and real clinical data show the suitability of our method for the application at hand.

Ultrasound confidence maps using random walks

Advances in ultrasound system development have led to a substantial improvement of image quality and to an increased use of ultrasound in clinical practice. Nevertheless, ultrasound attenuation and shadowing artifacts cannot be entirely avoided and continue to challenge medical image computing algorithms. We introduce a method for estimating a per-pixel confidence in the information depicted by ultrasound images, referred to as an ultrasound confidence map, which emphasizes uncertainty in attenuated and/or shadow regions. Our main novelty is the modeling of the confidence estimation problem within a random walks framework by taking into account ultrasound specific constraints. The solution to the random walks equilibrium problem is global and takes the entire image content into account. As a result, our method is applicable to a variety of ultrasound image acquisition setups. We demonstrate the applicability of our confidence maps for ultrasound shadow detection, 3D freehand ultrasound reconstruction, and multi-modal image registration.

Multiscaled combination of MR and SPECT images in neuroimaging: A simplex method based variable-weight fusion

Single-photon emission computed tomography (SPECT) images alone are difficult to understand in diagnosis, since anatomical structures are absent from the data. Studies on combination attempt to locate functional changes of the SPECT image by the magnetic resonance (MR) image. Due to the low similarity between original images, fused results are always darkened, obscured or loss some crucial anatomical structures. This paper has solved these problems by the variable-weight matrix which is estimated by minimizing the cost function using the simplex method. Under the generalized intensity-hue-saturation (GIHS) framework, the multiscaled analysis is presented for a better detail preservation. Besides, interactive approaches are discussed for the gradual variation between original images and the control of detail performance. The similarity assessment evaluates several different methods on a normal brain atlas. Two clips show the interactive property of the proposed method, while two medical cases demonstrate its clinical values. We conclude that the proposed method is superior to traditional methods, when considering the definition and the information capacity of fused results.

Ultrasonic image analysis and image-guided interventions

The fields of medical image analysis and computer-aided interventions deal with reducing the large volume of digital images (X-ray, computed tomography, magnetic resonance imaging (MRI), positron emission tomography and ultrasound (US)) to more meaningful clinical information using software algorithms. US is a core imaging modality employed in these areas, both in its own right and used in conjunction with the other imaging modalities. It is receiving increased interest owing to the recent introduction of three-dimensional US, significant improvements in US image quality, and better understanding of how to design algorithms which exploit the unique strengths and properties of this real-time imaging modality. This article reviews the current state of art in US image analysis and its application in image-guided interventions. The article concludes by giving a perspective from clinical cardiology which is one of the most advanced areas of clinical application of US image analysis and describing some probable future trends in this important area of ultrasonic imaging research.

Keep breathing! Common motion helps multi-modal mapping

We propose an unconventional approach for transferring of information between multi-modal images. It exploits the temporal commonality of multi-modal images acquired from the same organ during free-breathing. Strikingly there is no need for capturing the same region by the modalities. The method is based on extracting a low-dimensional description of the image sequences, selecting the common cause signal (breathing) for both modalities and finding the most similar sub-sequences for predicting image feature location. The approach was evaluated for 3 volunteers on sequences of 2D MRI and 2D US images of the liver acquired at different locations. Simultaneous acquisition of these images allowed for quantitative evaluation (predicted versus ground truth MRI feature locations). The best performance was achieved with signal extraction by slow feature analysis resulting in an average error of 2.6 mm (4.2 mm) for sequences acquired at the same (a different) time.

Registering preprocedure volumetric images with intraprocedure 3-D ultrasound using an ultrasound imaging model

For many image-guided interventions there exists a need to compute the registration between preprocedure image(s) and the physical space of the intervention. Real-time intraprocedure imaging such as ultrasound (US) can be used to image the region of interest directly and provide valuable anatomical information for computing this registration. Unfortunately, real-time US images often have poor signal-to-noise ratio and suffer from imaging artefacts. Therefore, registration using US images can be challenging and significant preprocessing is often required to make the registrations robust. In this paper we present a novel technique for computing the image-to-physical registration for minimally invasive cardiac interventions using 3-D US. Our technique uses knowledge of the physics of the US imaging process to reduce the amount of preprocessing required on the 3-D US images. To account for the fact that clinical US images normally undergo significant image processing before being exported from the US machine our optimization scheme allows the parameters of the US imaging model to vary. We validated our technique by computing rigid registrations for 12 cardiac US/magnetic resonance imaging (MRI) datasets acquired from six volunteers and two patients. The technique had mean registration errors of 2.1-4.4 mm, and 75% capture ranges of 5-30 mm. We also demonstrate how the same approach can be used for respiratory motion correction: on 15 datasets acquired from five volunteers the registration errors due to respiratory motion were reduced by 45%-92%.

Recent advances in image-guided radiotherapy for head and neck carcinoma

Radiotherapy has a well-established role in the management of head and neck cancers. Over the past decade, a variety of new imaging modalities have been incorporated into the radiotherapy planning and delivery process. These technologies are collectively referred to as image-guided radiotherapy and may lead to significant gains in tumor control and radiation side effect profiles. In the following review, these techniques as they are applied to head and neck cancer patients are described, and clinical studies analyzing their use in target delineation, patient positioning, and adaptive radiotherapy are highlighted. Finally, we conclude with a brief discussion of potential areas of further radiotherapy advancement.

Towards real time 2D to 3D registration for ultrasound-guided endoscopic and laparoscopic procedures

PURPOSE

A method to register endoscopic and laparoscopic ultrasound (US) images in real time with pre-operative computed tomography (CT) data sets has been developed with the goal of improving diagnosis, biopsy guidance, and surgical interventions in the abdomen.

METHODS

The technique, which has the potential to operate in real time, is based on a new phase correlation technique: LEPART, which specifies the location of a plane in the CT data which best corresponds to the US image. Validation of the method was carried out using an US phantom with cyst regions and with retrospective analysis of data sets from animal model experiments.

RESULTS

The phantom validation study shows that local translation displacements can be recovered for each US frame with a root mean squared error of 1.56 +/- 0.78 mm in less than 5 sec, using non-optimized algorithm implementations.

CONCLUSION

A new method for multimodality (preoperative CT and intraoperative US endoscopic images) registration to guide endoscopic interventions was developed and found to be efficient using clinically realistic datasets. The algorithm is inherently capable of being implemented in a parallel computing system so that full real time operation appears likely.

A novel method for registration of US/MR of the liver based on the analysis of US dynamics

Radiofrequency ablation of liver cancer is a minimally invasive alternative to open surgery. Typically, the preoperative planning is done on an MR (or CT) scan, while the intervention relies on ultrasound (US) guidance. Registration of intra-operative US and preoperative MR (or CT) would assist navigation and increase the confidence of RFA needle positioning. In this paper we present a novel method for registration of US and MR images of the liver. Hepatic vessels are extracted from 2D US by an algorithm that models US dynamics. It generates 2D probability maps representing hepatic vessels which are then combined into probability volumes. A multi-resolution registration framework performs registration of the pre-processed MR with two 3D vessel probability images. The accuracy, robustness and speed of the method were assessed by registering eight US/MR datasets. High robustness (86%) and reasonable accuracy (1.98 degrees, 4.10 mm), acceptable for the RFA clinical application, suggest that the method has a good potential for intra-operative use.

Evaluation of targeting errors in ultrasound-assisted radiotherapy

A method for validating the start-to-end accuracy of a 3-D ultrasound (US)-based patient positioning system for radiotherapy is described. A radiosensitive polymer gel is used to record the actual dose delivered to a rigid phantom after being positioned using 3-D US guidance. Comparison of the delivered dose with the treatment plan allows accuracy of the entire radiotherapy treatment process, from simulation to 3-D US guidance, and finally delivery of radiation, to be evaluated. The 3-D US patient positioning system has a number of features for achieving high accuracy and reducing operator dependence. These include using tracked 3-D US scans of the target anatomy acquired using a dedicated 3-D ultrasound probe during both the simulation and treatment sessions, automatic 3-D US-to-US registration and use of infrared LED (IRED) markers of the optical position-sensing system for registering simulation computed tomography to US data. The mean target localization accuracy of this system was 2.5 mm for four target locations inside the phantom, compared with 1.6 mm obtained using the conventional patient positioning method of laser alignment. Because the phantom is rigid, this represents the best possible set-up accuracy of the system. Thus, these results suggest that 3-D US-based target localization is practically feasible and potentially capable of increasing the accuracy of patient positioning for radiotherapy in sites where day-to-day organ shifts are greater than 1 mm in magnitude.