Medical image computing and computer-aided medical interventions applied to soft tissues. Work in progress in urology

Until recently, Computer-Aided Medical Interventions (CAMI) and Medical Robotics have focused on rigid and non deformable anatomical structures. Nowadays, special attention is paid to soft tissues, raising complex issues due to their mobility and deformation. Mini-invasive digestive surgery was probably one of the first fields where soft tissues were handled through the development of simulators, tracking of anatomical structures and specific assistance robots. However, other clinical domains, for instance urology, are concerned. Indeed, laparoscopic surgery, new tumour destruction techniques (e.g. HIFU, radiofrequency, or cryoablation), increasingly early detection of cancer, and use of interventional and diagnostic imaging modalities, recently opened new challenges to the urologist and scientists involved in CAMI. This resulted in the last five years in a very significant increase of research and developments of computer-aided urology systems. In this paper, we propose a description of the main problems related to computer-aided diagnostic and therapy of soft tissues and give a survey of the different types of assistance offered to the urologist: robotization, image fusion, surgical navigation. Both research projects and operational industrial systems are discussed

Atlas-Based Prostate Segmentation Using an Hybrid Registration

Purpose: This paper presents the preliminary results of a semi-automatic method for prostate segmentation of Magnetic Resonance Images (MRI) which aims to be incorporated in a navigation system for prostate brachytherapy. Methods: The method is based on the registration of an anatomical atlas computed from a population of 18 MRI exams onto a patient image. An hybrid registration framework which couples an intensity-based registration with a robust point-matching algorithm is used for both atlas building and atlas registration. Results: The method has been validated on the same dataset that the one used to construct the atlas using the "leave-one-out method". Results gives a mean error of 3.39 mm and a standard deviation of 1.95 mm with respect to expert segmentations. Conclusions: We think that this segmentation tool may be a very valuable help to the clinician for routine quantitative image exploitation.Comment: International Journal of Computer Assisted Radiology and Surgery (2008) 000-99

Segmentation, separation and pose estimation of prostate brachytherapy seeds in CT images.

International audienceIn this paper, we address the development of an automatic approach for the computation of pose information (position + orientation) of prostate brachytherapy loose seeds from 3D CT images. From an initial detection of a set of seed candidates in CT images using a threshold and connected component method, the orientation of each individual seed is estimated by using the principal components analysis (PCA) method. The main originality of this approach is the ability to classify the detected objects based on a priori intensity and volume information and to separate groups of closely spaced seeds using three competing clustering methods: the standard and a modified k-means method and a Gaussian mixture model with an Expectation-Maximization algorithm. Experiments were carried out on a series of CT images of two phantoms and patients. The fourteen patients correspond to a total of 1063 implanted seeds. Detections are compared to manual segmentation and to related work in terms of detection performance and calculation time. This automatic method has proved to be accurate and fast including the ability to separate groups of seeds in a reliable way and to determine the orientation of each seed. Such a method is mandatory to be able to compute precisely the real dose delivered to the patient post-operatively instead of assuming the alignment of seeds along the theoretical insertion direction of the brachytherapy needles

Tools for improving high-dose-rate prostate cancer brachytherapy using three-dimensional ultrasound and magnetic resonance imaging

High-dose-rate brachytherapy (HDR-BT) is an interstitial technique for the treatment of intermediate and high-risk localized prostate cancer that involves placement of a radiation source directly inside the prostate using needles. Dose-escalated whole-gland treatments have led to improvements in survival, and tumour-targeted treatments may offer future improvements in therapeutic ratio. The efficacy of tumour-targeted HDR-BT depends on imaging tools to enable accurate dose delivery to prostate sub-volumes. This thesis is focused on implementing ultrasound tools to improve HDR-BT needle localization accuracy and efficiency, and evaluating dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) for tumour localization. First, we implemented a device enabling sagittally-reconstructed 3D (SR3D) ultrasound, which provides sub-millimeter resolution in the needle insertion direction. We acquired SR3D and routine clinical images in a cohort of 12 consecutive eligible HDR-BT patients, with a total of 194 needles. The SR3D technique provided needle insertion depth errors within 5 mm for 93\% of needles versus 76\% for the clinical imaging technique, leading to increased precision in dose delivered to the prostate. Second, we implemented an algorithm to automatically segment multiple HDR-BT needles in a SR3D image. The algorithm was applied to the SR3D images from the first patient cohort, demonstrating mean execution times of 11.0 s per patient and successfully segmenting 82\% of needles within 3 mm. Third, we augmented SR3D imaging with live-2D sagittal ultrasound for needle tip localization. This combined technique was applied to another cohort of 10 HDR-BT patients, reducing insertion depth errors compared to routine imaging from a range of [-8.1 mm, 7.7 mm] to [-6.2 mm, 5.9 mm]. Finally, we acquired DCE-MRI in 16 patients scheduled to undergo prostatectomy, using either high spatial resolution or high temporal resolution imaging, and compared the images to whole-mount histology. The high spatial resolution images demonstrated improved high-grade cancer classification compared to the high temporal resolution images, with areas under the receiver operating characteristic curve of 0.79 and 0.70, respectively. In conclusion, we have translated and evaluated specialized imaging tools for HDR-BT which are ready to be tested in a clinical trial investigating tumour-targeted treatment

Towards clinical application of RayStretch for heterogeneity corrections in LDR permanent 125-I prostate brachytherapy

Purpose: RayStretch is a simple algorithm proposed for heterogeneity corrections in low-dose-rate brachytherapy. It is built on top of TG-43 consensus data, and it has been validated with Monte Carlo (MC) simulations. In this study, we take a real clinical prostate implant with 71 125I seeds as reference and we apply RayStretch to analyze its performance in worst-case scenarios. Methods and Materials: To do so, we design two cases where large calcifications are located in the prostate lobules. RayStretch resilience under various calcification density values is also explored. Comparisons against MC calculations are performed. Results: Dose-volume histogram-related parameters like prostate D90, rectum D2cc, or urethra D10 obtained with RayStretch agree within a few percent with the detailed MC results for all cases considered. Conclusions: The robustness and compatibility of RayStretch with commercial treatment planning systems indicate its applicability in clinical practice for dosimetric corrections in prostate calcifications. Its use during intraoperative ultrasound planning is foreseen