Automatic 3D seed location and orientation in CT images for prostate brachytherapy

International audienceIn prostate brachytherapy, the analysis of the 3D pose information of each individual implanted seed is one of the critical issues for dose calculation and procedure quality assessment. This paper addresses the development of an automatic image processing solution for the separation, localization and 3D orientation estimation of prostate seeds. This solution combines an initial detection of a set of seed candidates in CT images (using a thresholding and connected component method) with an orientation estimation using principal components analysis (PCA). The main originality of the work is the ability to classify the detected objects based on a priori intensity and volume information and to separate groups of seeds using a modified k-means method. Experiments were carried out on CT images of a phantom and a patient aiming to compare the proposed solution with manual segmentation or other previous work in terms of detection performance and calculation time

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

A Study of Image-based C-arm Tracking Using Minimal Fiducials

Image-based tracking of the c-arm continues to be a critical and challenging problem for many clinical applications due to its widespread use in many computer-assisted procedures that rely upon its accuracy for further planning, registration, and reconstruction tasks. In this thesis, a variety of approaches are presented to improve current c-arm tracking methods and devices for intra-operative procedures. The first approach presents a novel two-dimensional fiducial comprising a set of coplanar conics and an improved single-image pose estimation algorithm that addresses segmentation errors using a mathematical equilibration approach. Simulation results show an improvement in the mean rotation and translation errors by factors of 4 and 1.75, respectively, as a result of using the proposed algorithm. Experiments using real data obtained by imaging a simple precisely machined model consisting of three coplanar ellipses retrieve pose estimates that are in good agreement with those obtained by a ground truth optical tracker. This two-dimensional fiducial can be easily placed under the patient allowing a wide field of view for the motion of the c-arm. The second approach employs learning-based techniques to two-view geometrical theories. A demonstrative algorithm is used to simultaneously tackle matching and segmentation issues of features segmented from pairs of acquired images. The corrected features can then be used to retrieve the epipolar geometry which can ultimately provide pose parameters using a one-dimensional fiducial. The problem of match refinement for epipolar geometry estimation is formulated in a reinforcement-learning framework. Experiments demonstrate the ability to both reject false matches and fix small localization errors in the segmentation of true noisy matches in a minimal number of steps. The third approach presents a feasibility study for an approach that entirely eliminates the use of tracking fiducials. It relies only on preoperative data to initialize a point-based model that is subsequently used to iteratively estimate the pose and the structure of the point-like intraoperative implant using three to six images simultaneously. This method is tested in the framework of prostate brachytherapy in which preoperative data including planned 3-D locations for a large number of point-like implants called seeds is usually available. Simultaneous pose estimation for the c-arm for each image and localization of the seeds is studied in a simulation environment. Results indicate mean reconstruction errors that are less than 1.2 mm for noisy plans of 84 seeds or fewer. These are attained when the 3D mean error introduced to the plan as a result of adding Gaussian noise is less than 3.2 mm

Brachytherapy Seed and Applicator Localization via Iterative Forward Projection Matching Algorithm using Digital X-ray Projections

Interstitial and intracavitary brachytherapy plays an essential role in management of several malignancies. However, the achievable accuracy of brachytherapy treatment for prostate and cervical cancer is limited due to the lack of intraoperative planning and adaptive replanning. A major problem in implementing TRUS-based intraoperative planning is an inability of TRUS to accurately localize individual seed poses (positions and orientations) relative to the prostate volume during or after the implantation. For the locally advanced cervical cancer patient, manual drawing of the source positions on orthogonal films can not localize the full 3D intracavitary brachytherapy (ICB) applicator geometry. A new iterative forward projection matching (IFPM) algorithm can explicitly localize each individual seed/applicator by iteratively matching computed projections of the post-implant patient with the measured projections. This thesis describes adaptation and implementation of a novel IFPM algorithm that addresses hitherto unsolved problems in localization of brachytherapy seeds and applicators. The prototype implementation of 3-parameter point-seed IFPM algorithm was experimentally validated using a set of a few cone-beam CT (CBCT) projections of both the phantom and post-implant patient’s datasets. Geometric uncertainty due to gantry angle inaccuracy was incorporated. After this, IFPM algorithm was extended to 5-parameter elongated line-seed model which automatically reconstructs individual seed orientation as well as position. The accuracy of this algorithm was tested using both the synthetic-measured projections of clinically-realistic Model-6711 125I seed arrangements and measured projections of an in-house precision-machined prostate implant phantom that allows the orientations and locations of up to 100 seeds to be set to known values. The seed reconstruction error for simulation was less than 0.6 mm/3o. For the physical phantom experiments, IFPM absolute accuracy for position, polar angle, and azimuthal angel were (0.78 ± 0.57) mm, (5.8 ± 4.8)o, and (6.8 ± 4.0)o, respectively. It avoids the need to match corresponding seeds in each projection and accommodates incomplete data, overlapping seed clusters, and highly-migrated seeds. IFPM was further generalized from 5-parameter to 6-parameter model which was needed to reconstruct 3D pose of arbitrary-shape applicators. The voxelized 3D model of the applicator was obtained from external complex combinatorial geometric modeling. It is then integrated into the forward projection matching method for computing the 2D projections of the 3D ICB applicators, iteratively. The applicator reconstruction error for simulation was about 0.5 mm/2o. The residual 2D registration error (positional difference) between computed and actual measured applicator images was less than 1 mm for the intrauterine tandem and about 1.5 mm for the bilateral colpostats in each detector plane. By localizing the applicator’s internal structure and the sources, the effect of intra and inter-applicator attenuation can be included in the resultant dose distribution and CBCT metal streaking artifact mitigation. The localization accuracy of better than 1 mm and 6o has the potential to support more accurate Monte Carlo-based or 2D TG-43 dose calculations in clinical practice. It is hoped the clinical implementation of IFPM approach to localize elongated line-seed/applicator for intraoperative brachytherapy planning may have a positive impact on the treatment of prostate and cervical cancers

SEED LOCALIZATION IN IMAGE-GUIDED PROSTATE BRACHYTHERAPY INTRAOPERATIVE DOSIMETRY SYSTEMS

Prostate cancer is the most common cancer among men in the United States. Many treatments are available, but prostate brachytherapy is acknowledged as a standard treatment for patients with localized cancer. Prostate brachytherapy is a minimally invasive surgery involving the permanent implantation of approximately 100 grain-sized radioactive seeds into the prostate. While effective, contemporary practice of brachytherapy is suboptimal because it spreads the stages of planning, implant, and dosimetry over several weeks. Although brachytherapy is now moving towards intraoperative treatment planning (ITP) which integrates all three stages into a single day in the operating room,the American Brachytherapy Society states, “the major current limitation of ITP is the inability to localize the seeds in relation to the prostate.” While the procedure is traditionally guided by transrectal ultrasound (TRUS), poor image quality prevents TRUS from accurately localizing seeds to compute dosimetry intraoperatively. Alternative methods exist, but are generally impractical to implement in clinics worldwide. The subject of this dissertation is the development of two intraoperative dosimetry systems to practically solve the problem of seed localization in ITP. The first system fuses TRUS with X-ray fluoroscopy using the ubiquitous non-isocentric mobile C-arm.The primary contributions of this dissertation include an automatic fiducial and seed segmentation algorithm for fluoroscopic images, as well as a next generation intraoperative dosimetry system based on a fiducial with seed-like markers. Results from over 30 patients prove that both contributions are significant for localizing seeds with high accuracy and demonstrate the capability of detecting cold spots. The second intraoperative dosimetry system is based on photoacoustic imaging, and uses the already implemented TRUS probe to detect ultrasonic waves converted from electromagnetic waves generated by a laser. The primary contributions of this dissertation therefore also include a prototype benchtop photoacoustic system and an improved clinical version usable in the operating room. Results from gelatin phantoms, an ex vivo dog prostate, and an in vivo dog study reveal that multiple seeds are clearly visible with high contrast using photoacoustic imaging at clinically safe laser energies.Together, both systems significantly progress the latest technologies to provide optimal care to patients through ITP

A 3D US Guidance System for Permanent Breast Seed Implantation: Development and Validation

Permanent breast seed implantation (PBSI) is a promising breast radiotherapy technique that suffers from operator dependence. We propose and have developed an intraoperative 3D ultrasound (US) guidance system for PBSI. A tracking arm mounted to a 3D US scanner registers a needle template to the image. Images were validated for linear and volumetric accuracy, and image quality in a volunteer. The tracking arm was calibrated, and the 3D image registered to the scanner. Tracked and imaged needle positions were compared to assess accuracy and a patient-specific phantom procedure guided with the system. Median/mean linear and volumetric error was ±1.1% and ±4.1%, respectively, with clinically suitable volunteer scans. Mean tracking arm error was 0.43mm and 3D US target registration error ≤0.87mm. Mean needle tip/trajectory error was 2.46mm/1.55°. Modelled mean phantom procedure seed displacement was 2.50mm. To our knowledge, this is the first reported PBSI phantom procedure with intraoperative 3D image guidance

Image Guided Robots for Urology

This dissertation addresses the development of medical image-guided robots and their applications in urology. Image-guided robots integrate medical image information with robotic precision to assist the planning and execution of the image-guided interventions. Robots guided by two different image modalities, ultrasound and MR image, were developed. Ultrasound image-guided robots manipulate an ultrasound probe and a needle-guide that are calibrated with respect to the robot for image-guided targeting. A method for calibration was developed and verified through the image-guided targeting experiments. Robotic manipulation of the calibrated probe allows acquisition of image slices at precise location, which can be combined to generate a 3D ultrasound image. Software for 3D ultrasound image acquisition, processing, and segmentation was developed as a part of the image-guided robot system. The feasibility of several image-guided intervention procedures using the ultrasound image-guided robot system was tested. The robot was used in a clinical trial of intraoperative transrectal ultrasound (TRUS) guided prostatectomy. The accuracy of TRUS-guided prostate biopsy using the robot was evaluated in a comparative study versus the classic human operation of the probe. Robot controlled palpation and image processing methods were developed for ultrasound elastography imaging of the prostate. An ultrasound to CT image-fusion method using the robot as a common reference was developed for percutaneous access of the kidney. MRI-guided robots were developed for transrectal and transperineal prostate biopsy. Extensive in-vitro tests were performed to ensure MRI compatibility and image-guided accuracy of the robots. The transrectal robot was evaluated in an animal study and the transperineal robot is undergoing a clinical trial. The collection of methods and algorithms presented in this dissertation can contribute to the development of image-guided robots that may provide less invasive and more precise interventions in urology, interventional radiology, and other fields

Utilisation de la tomodensitométrie à deux énergies pour le calcul de dose en curiethérapie à bas débit

Dans la pratique actuelle de la curiethérapie à bas débit, l'évaluation de la dose dans la prostate est régie par le protocole défini dans le groupe de travail 43 (TG-43) de l'American Association of Physicists in Medicine. Ce groupe de travail suppose un patient homogène à base d'eau de même densité et néglige les changements dans l'atténuation des photons par les sources de curiethérapie. En considérant ces simplifications, les calculs de dose se font facilement à l'aide d'une équation, indiquée dans le protocole. Bien que ce groupe de travail ait contribué à l'uniformisation des traitements en curiethérapie entre les hôpitaux, il ne décrit pas adéquatement la distribution réelle de la dose dans le patient. La publication actuelle du TG-186 donne des recommandations pour étudier des distributions de dose plus réalistes. Le but de ce mémoire est d'appliquer ces recommandations à partir du TG-186 pour obtenir une description plus réaliste de la dose dans la prostate. Pour ce faire, deux ensembles d'images du patient sont acquis simultanément avec un tomodensitomètre à double énergie (DECT). Les artéfacts métalliques présents dans ces images, causés par les sources d’iode, sont corrigés à l'aide d’un algorithme de réduction d'artefacts métalliques pour DECT qui a été développé dans ce travail. Ensuite, une étude Monte Carlo peut être effectuée correctement lorsque l'image est segmentée selon les différents tissus humains. Cette segmentation est effectuée en évaluant le numéro atomique effectif et la densité électronique de chaque voxel, par étalonnage stoechiométrique propre au DECT, et en y associant le tissu ayant des paramètres physiques similaires. Les résultats montrent des différences dans la distribution de la dose lorsqu'on compare la dose du protocole TG-43 avec celle retrouvée avec les recommandations du TG-186.In current low dose rate brachytherapy practice, dose evaluation within the prostate is govern by the protocol defined by the task group 43 (TG-43) of the American Association of Physicist in Medicine. This task group assumes a homogeneous water based patient with invariable density. They also disregard the changes in photon attenuation through neighbouring brachytherapy sources. With the introduction of these simplifications, dose calculations are easily solved using an equation proposed in this protocol. Although this task group helped create a uniform practice of brachytherapy treatments between hospitals, it does not properly described the actual dose distribution within the patient. The current publication of TG-186 gives recommendations to study these dose distribution more realistically. The purpose of this Master's thesis is to apply these recommendations from TG-186 to obtain a more realistic description of the dose. In order to proceed, two sets of patient images are acquired with a dual energy computed tomography (DECT). These images are corrected for metallic artifacts, which are highly present in the scanned images, using DECT metallic artifact reduction algortithm, developped in this work. Afterwords, a Monte Carlo study can be performed by properly identifying the environment with human tissues. This segmentation is performed by evaluating the effective atomic number and electronic density of each voxel using a DECT stoichiometric calibration, and allocating the tissue having the closest resemblance to these physical parameters. The results show clear differences in dose distribution when comparing TG-43 protocole with TG-186 recommendations

Segmentierung medizinischer Bilddaten und bildgestützte intraoperative Navigation

Die Entwicklung von Algorithmen zur automatischen oder semi-automatischen Verarbeitung von medizinischen Bilddaten hat in den letzten Jahren mehr und mehr an Bedeutung gewonnen. Das liegt zum einen an den immer besser werdenden medizinischen Aufnahmemodalitäten, die den menschlichen Körper immer feiner virtuell abbilden können. Zum anderen liegt dies an der verbesserten Computerhardware, die eine algorithmische Verarbeitung der teilweise im Gigabyte-Bereich liegenden Datenmengen in einer vernünftigen Zeit erlaubt. Das Ziel dieser Habilitationsschrift ist die Entwicklung und Evaluation von Algorithmen für die medizinische Bildverarbeitung. Insgesamt besteht die Habilitationsschrift aus einer Reihe von Publikationen, die in drei übergreifende Themenbereiche gegliedert sind: -Segmentierung medizinischer Bilddaten anhand von vorlagenbasierten Algorithmen -Experimentelle Evaluation quelloffener Segmentierungsmethoden unter medizinischen Einsatzbedingungen -Navigation zur Unterstützung intraoperativer Therapien Im Bereich Segmentierung medizinischer Bilddaten anhand von vorlagenbasierten Algorithmen wurden verschiedene graphbasierte Algorithmen in 2D und 3D entwickelt, die einen gerichteten Graphen mittels einer Vorlage aufbauen. Dazu gehört die Bildung eines Algorithmus zur Segmentierung von Wirbeln in 2D und 3D. In 2D wird eine rechteckige und in 3D eine würfelförmige Vorlage genutzt, um den Graphen aufzubauen und das Segmentierungsergebnis zu berechnen. Außerdem wird eine graphbasierte Segmentierung von Prostatadrüsen durch eine Kugelvorlage zur automatischen Bestimmung der Grenzen zwischen Prostatadrüsen und umliegenden Organen vorgestellt. Auf den vorlagenbasierten Algorithmen aufbauend, wurde ein interaktiver Segmentierungsalgorithmus, der einem Benutzer in Echtzeit das Segmentierungsergebnis anzeigt, konzipiert und implementiert. Der Algorithmus nutzt zur Segmentierung die verschiedenen Vorlagen, benötigt allerdings nur einen Saatpunkt des Benutzers. In einem weiteren Ansatz kann der Benutzer die Segmentierung interaktiv durch zusätzliche Saatpunkte verfeinern. Dadurch wird es möglich, eine semi-automatische Segmentierung auch in schwierigen Fällen zu einem zufriedenstellenden Ergebnis zu führen. Im Bereich Evaluation quelloffener Segmentierungsmethoden unter medizinischen Einsatzbedingungen wurden verschiedene frei verfügbare Segmentierungsalgorithmen anhand von Patientendaten aus der klinischen Routine getestet. Dazu gehörte die Evaluierung der semi-automatischen Segmentierung von Hirntumoren, zum Beispiel Hypophysenadenomen und Glioblastomen, mit der frei verfügbaren Open Source-Plattform 3D Slicer. Dadurch konnte gezeigt werden, wie eine rein manuelle Schicht-für-Schicht-Vermessung des Tumorvolumens in der Praxis unterstützt und beschleunigt werden kann. Weiterhin wurde die Segmentierung von Sprachbahnen in medizinischen Aufnahmen von Hirntumorpatienten auf verschiedenen Plattformen evaluiert. Im Bereich Navigation zur Unterstützung intraoperativer Therapien wurden Softwaremodule zum Begleiten von intra-operativen Eingriffen in verschiedenen Phasen einer Behandlung (Therapieplanung, Durchführung, Kontrolle) entwickelt. Dazu gehört die erstmalige Integration des OpenIGTLink-Netzwerkprotokolls in die medizinische Prototyping-Plattform MeVisLab, die anhand eines NDI-Navigationssystems evaluiert wurde. Außerdem wurde hier ebenfalls zum ersten Mal die Konzeption und Implementierung eines medizinischen Software-Prototypen zur Unterstützung der intraoperativen gynäkologischen Brachytherapie vorgestellt. Der Software-Prototyp enthielt auch ein Modul zur erweiterten Visualisierung bei der MR-gestützten interstitiellen gynäkologischen Brachytherapie, welches unter anderem die Registrierung eines gynäkologischen Brachytherapie-Instruments in einen intraoperativen Datensatz einer Patientin ermöglichte. Die einzelnen Module führten zur Vorstellung eines umfassenden bildgestützten Systems für die gynäkologische Brachytherapie in einem multimodalen Operationssaal. Dieses System deckt die prä-, intra- und postoperative Behandlungsphase bei einer interstitiellen gynäkologischen Brachytherapie ab

Realistic tool-tissue interaction models for surgical simulation and planning

Surgical simulators present a safe and potentially effective method for surgical training, and can also be used in pre- and intra-operative surgical planning. Realistic modeling of medical interventions involving tool-tissue interactions has been considered to be a key requirement in the development of high-fidelity simulators and planners. The soft-tissue constitutive laws, organ geometry and boundary conditions imposed by the connective tissues surrounding the organ, and the shape of the surgical tool interacting with the organ are some of the factors that govern the accuracy of medical intervention planning.\ud \ud This thesis is divided into three parts. First, we compare the accuracy of linear and nonlinear constitutive laws for tissue. An important consequence of nonlinear models is the Poynting effect, in which shearing of tissue results in normal force; this effect is not seen in a linear elastic model. The magnitude of the normal force for myocardial tissue is shown to be larger than the human contact force discrimination threshold. Further, in order to investigate and quantify the role of the Poynting effect on material discrimination, we perform a multidimensional scaling study. Second, we consider the effects of organ geometry and boundary constraints in needle path planning. Using medical images and tissue mechanical properties, we develop a model of the prostate and surrounding organs. We show that, for needle procedures such as biopsy or brachytherapy, organ geometry and boundary constraints have more impact on target motion than tissue material parameters. Finally, we investigate the effects surgical tool shape on the accuracy of medical intervention planning. We consider the specific case of robotic needle steering, in which asymmetry of a bevel-tip needle results in the needle naturally bending when it is inserted into soft tissue. We present an analytical and finite element (FE) model for the loads developed at the bevel tip during needle-tissue interaction. The analytical model explains trends observed in the experiments. We incorporated physical parameters (rupture toughness and nonlinear material elasticity) into the FE model that included both contact and cohesive zone models to simulate tissue cleavage. The model shows that the tip forces are sensitive to the rupture toughness. In order to model the mechanics of deflection of the needle, we use an energy-based formulation that incorporates tissue-specific parameters such as rupture toughness, nonlinear material elasticity, and interaction stiffness, and needle geometric and material properties. Simulation results follow similar trends (deflection and radius of curvature) to those observed in macroscopic experimental studies of a robot-driven needle interacting with gels