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

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

3D BrachyView System

Prostate cancer is quickly becoming the most common form of cancer across the globe, and is commonly treated with low dose rate brachytherapy due to its curative measures and highly conformal dose delivery. It is important to ensure there is a means of real time monitoring of the dose and seed placements when radioactive seeds are implanted in the prostate gland during a low dose rate brachytherapy treatment. The BrachyView system presents as a unique system that provides the capability of 3D seed reconstruction within an intraoperative setting. In this thesis the BrachyView system is tested for its suitability, accuracy and the system is further developed so that its application in real-time intraoperative dosime-try can become a reality. The system was tested with a clinically relevant number of seeds, 98, where previously the system had only been tested with a maximum number of 30 seeds. The BrachyView system was able to reconstruct 91.8% of implanted seeds from the 98 seed dataset with an average overall discrepancy of 3.65 mm without the application of the baseline subtraction algorithm, however with its application to the data the detection efficiency was improved to 100% and an overall positional accuracy of 11.5%, correlating to a reduced overall discrepancy of 3.23 mm, was noted. It was found that with seed numbers of 30 or lower that the addition of a background subtrac-tion algorithm was not necessary, whereas for datasets containing a clinically relevant number of seeds the application of a background subtraction algorithm was paramount to reducing the noise, scatter and means for identification of newly implanted seeds that may be masked by those seed previously implanted

Transrectal ultrasound image processing for brachytherapy applications

In this thesis, we propose a novel algorithm for detecting needles and their corresponding implanted radioactive seed locations in the prostate. The seed localization process is carried out efficiently using separable Gaussian filters in a probabilistic Gibbs random field framework. An approximation of the needle path through the prostate volume is obtained using a polynomial fit. The seeds are then detected and assigned to their corresponding needles by calculating local maxima of the voronoi region around the needle position. In our experiments, we were able to successfully localize over 85% of the implanted seeds. Furthermore, as a regular part of a brachytherapy cancer treatment, patient’s prostate is scanned using a trans-rectal ultrasound probe, its boundary is manually outlined, and its volume is estimated for dosimetry purposes. In this thesis, we also propose a novel semi-automatic segmentation algorithm for prostate boundary detection that requires a reduced amount of radiologist’s input, and thus speeds up the surgical procedure. Saved time can be used to re-scan the prostate during the operation and accordingly adjust the treatment plan. The proposed segmentation algorithm utilizes texture differences between ultrasound images of the prostate tissue and the surrounding tissues. It is carried out in 5 the polar coordinate system and it uses three-dimensional data correlation to improve the smoothness and reliability of the segmentation. Test results show that the boundary segmentation obtained from the algorithm can reduce manual input by the factor of 3, without significantly affecting the accuracy of the segmentation (i.e. semi-automatically estimated prostate volume is within 90% of the original estimate)

Robot-Assisted Prostate Brachytherapy

Abstract: In contemporary brachytherapy procedures, needle placement at the desired target is challenging due to a variety of reasons. A robot-assisted brachytherapy system can potentially improve needle placement and seed delivery, resulting in enhanced therapeutic delivery. In this paper we present a 16 DOF (degrees-of-freedom) robotic system (9DOF positioning module and 7DOF surgery module) developed and fabricated for prostate brachytherapy. Strategies to reduce needle deflection and target movement were incorporated after extensive experimental validation. Provisions for needle motion and force feedback were included into the system for improving robot control and seed delivery. Preliminary experimental results reveal that the prototype system is sufficiently accurate in placing brachytherapy needles

InterNAV3D: A Navigation Tool for Robot-Assisted Needle-Based Intervention for the Lung

Lung cancer is one of the leading causes of cancer deaths in North America. There are recent advances in cancer treatment techniques that can treat cancerous tumors, but require a real-time imaging modality to provide intraoperative assistive feedback. Ultrasound (US) imaging is one such modality. However, while its application to the lungs has been limited because of the deterioration of US image quality (due to the presence of air in the lungs); recent work has shown that appropriate lung deflation can help to improve the quality sufficiently to enable intraoperative, US-guided robotics-assisted techniques to be used. The work described in this thesis focuses on this approach. The thesis describes a project undertaken at Canadian Surgical Technologies and Advanced Robotics (CSTAR) that utilizes the image processing techniques to further enhance US images and implements an advanced 3D virtual visualization software approach. The application considered is that for minimally invasive lung cancer treatment using procedures such as brachytherapy and microwave ablation while taking advantage of the accuracy and teleoperation capabilities of surgical robots, to gain higher dexterity and precise control over the therapy tools (needles and probes). A number of modules and widgets are developed and explained which improve the visibility of the physical features of interest in the treatment and help the clinician to have more reliable and accurate control of the treatment. Finally the developed tools are validated with extensive experimental evaluations and future developments are suggested to enhance the scope of the applications

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

Encapsulated Contrast Agent Markers for MRI-based Post-implant Dosimetry

Low-dose-rate prostate brachytherapy involves the implantation of tiny radioactive seeds into the prostate to treat prostate cancer. The current standard post-implant imaging modality is computed tomography (CT). On CT images, the radioactive seeds can be distinctively localized but delineation of the prostate and surrounding soft tissue is poor. Magnetic resonance imaging (MRI) provides better prostate and soft tissue delineation, but seed localization is difficult. To aid with seed localization, MRI markers with encapsulated contrast agent that provide positive-contrast on MRI images (Sirius MRI markers; C4 Imaging, Houston, TX) have been proposed to be placed adjacent to the negative-contrast seeds. This dissertation describes the development of the Sirius MRI markers for prostate post-implant dosimetry. First, I compared the dose-volume histogram and other dosimetry parameters generated by MIM Symphony (a brachytherapy treatment planning system that allow the use of MRI images for treatment planning; MIM Software Inc., Cleveland, OH) and VariSeed (a widely used brachytherapy treatment planning system; Varian Medical Systems, Inc., Palo Alto, CA), and found the dosimetry between both brachytherapy treatment planning systems to be comparable. To gain more insight into the MRI contrast characteristics of the Sirius MRI markers, I measured the Sirius MRI marker contrast agent\u27s spin-lattice and spin-spin relaxivities, and studied the relaxation characteristics\u27 dependence on MRI field strength, temperature, and orientation. From the Sirius MRI marker\u27s contrast agent relaxation characteristics, I systematically studied the effect of varying MRI scan parameters such as flip angle, number of excitations, bandwidth, field of view, slice thickness, and encoding steps, on the Sirius MRI markers\u27 signal and contrast, as well as image noise, artifact and scan time. On patients implanted with Sirius MRI markers, I evaluated the visibility of the Sirius MRI markers and image artifacts. Lastly, I semi-automated the localization of markers and seeds to more enable the efficient incorporation of Sirius MRI markers as part of the clinical post-implant workflow. Ultimately, the Sirius MRI markers may change the paradigm from CT-based to MRI-based post-implant dosimetry, for a more accurate understanding of dose-response relationships in patients undergoing low dose rate prostate brachytherapy

New Mechatronic Systems for the Diagnosis and Treatment of Cancer

Both two dimensional (2D) and three dimensional (3D) imaging modalities are useful tools for viewing the internal anatomy. Three dimensional imaging techniques are required for accurate targeting of needles. This improves the efficiency and control over the intervention as the high temporal resolution of medical images can be used to validate the location of needle and target in real time. Relying on imaging alone, however, means the intervention is still operator dependent because of the difficulty of controlling the location of the needle within the image. The objective of this thesis is to improve the accuracy and repeatability of needle-based interventions over conventional techniques: both manual and automated techniques. This includes increasing the accuracy and repeatability of these procedures in order to minimize the invasiveness of the procedure. In this thesis, I propose that by combining the remote center of motion concept using spherical linkage components into a passive or semi-automated device, the physician will have a useful tracking and guidance system at their disposal in a package, which is less threatening than a robot to both the patient and physician. This design concept offers both the manipulative transparency of a freehand system, and tremor reduction through scaling currently offered in automated systems. In addressing each objective of this thesis, a number of novel mechanical designs incorporating an remote center of motion architecture with varying degrees of freedom have been presented. Each of these designs can be deployed in a variety of imaging modalities and clinical applications, ranging from preclinical to human interventions, with an accuracy of control in the millimeter to sub-millimeter range

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