Human performance in the task of port placement for biosensor use

Background We conducted a study of participants' abilities to place a laparoscopic port for in vivo biosensor use. Biosensors have physical limitations that make port placement crucial to proper data collection. A new port placement algorithm enabled evaluation of port locations, using segmented patient data in a virtual environment. Methods Port placement scoring algorithms were integrated into an image-guided surgery system. Virtual test scenes were created to evaluate various scenarios encountered during biosensor use. Participants were scored based on their ability to choose a port location from which points of interest could be scanned with a biosensor. Participants' scores were also compared to those of a port placement algorithm. Results The port placement algorithm consistently outscored participants by 10–25%. Participants were inconsistent from trial to trial and from participant to participant. Conclusion Port placement for biosensor procedures could be improved through training or augmentation. Copyright © 2010 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75793/1/300_ftp.pd

Image-guided port placement for minimally invasive cardiac surgery

Minimally invasive surgery is becoming popular for a number of interventions. Use of robotic surgical systems in coronary artery bypass intervention offers many benefits to patients, but is however limited by remaining challenges in port placement. Choosing the entry ports for the robotic tools has a large impact on the outcome of the surgery, and can be assisted by pre-operative planning and intra-operative guidance techniques. In this thesis, pre-operative 3D computed tomography (CT) imaging is used to plan minimally invasive robotic coronary artery bypass (MIRCAB) surgery. From a patient database, port placement optimization routines are implemented and validated. Computed port placement configurations approximated past expert chosen configurations with an error of 13.7 ±5.1 mm. Following optimization, statistical classification was used to assess patient candidacy for MIRCAB. Various pattern recognition techniques were used to predict MIRCAB success, and could be used in the future to reduce conversion rates to conventional open-chest surgery. Gaussian, Parzen window, and nearest neighbour classifiers all proved able to detect ‘candidate’ and ‘non-candidate’ MIRCAB patients. Intra-operative registration and laser projection of port placements was validated on a phantom and then evaluated in four patient cases. An image-guided laser projection system was developed to map port placement plans from pre-operative 3D images. Port placement mappings on the phantom setup were accurate with an error of 2.4 ± 0.4 mm. In the patient cases, projections remained within 1 cm of computed port positions. Misregistered port placement mappings in human trials were due mainly to the rigid-body registration assumption and can be improved by non-rigid techniques. Overall, this work presents an integrated approach for: 1) pre-operative port placement planning and classification of incoming MIRCAB patients; and 2) intra-operative guidance of port placement. Effective translation of these techniques to the clinic will enable MIRCAB as a more efficacious and accessible procedure

Optimal Port Placement And Automated Robotic Positioning For Instrumented Laparoscopic Biosensors

OPTIMAL SURGICAL PORT PLACEMENT AND AUTOMATED ROBOTIC POSITIONING FOR RAMAN AND OTHER BIOSENSORS by BRADY KING January 2011 Advisors: Dr. Abhilash Pandya, Dr. Darin Ellis, Dr. Le Yi Wang, and Dr. Greg Auner Major: Computer Engineering Degree: Doctor of Philosophy Medical biosensors can provide new information during minimally invasive and robotic surgical procedures. However, these biosensors have significant physical limitations that make it difficult to find optimal port locations and place them in vivo. This dissertation explores the application of robotics and virtual/augmented reality to biosensors to enable their optimal use in vivo. In the first study, human performance in the task of port placement was evaluated to determine if computer intervention and assistance was needed. Using a virtual surgical environment, we present a number of targets on one or more tissue surfaces. A human factors study was conducted with 20 subjects that analyzed the subject\u27s placement of a port with the goal of scanning as many targets as possible with a biosensor. The study showed performance to be less than optimal with significant degradation in several specific scenarios. In the second study, an automated intelligent port placement system for biosensor use was developed. Patient data was displayed in an environment in which a surgeon could indicate areas of interest. The system utilized biosensor physical limitations and provided the best port location from which the biosensor could reach the targets on a collision-free path. The study showed that it is possible to find an optimal port location for proper biosensor data capture. In the final study, a surgical robot was investigated for potential use in holding and positioning a biosensor in vivo. A full control suite was developed for an AESOP 1000, enabling the positioning of the biosensor without hand manipulation. It was found that the robot lacks the accuracy needed for proper biosensor utilization. Specific causes for the inaccuracies were identified for analysis and consideration in future robotic platforms. Overall, the results show that the application of medical robotics and virtual/augmented reality is able to overcome of the significant physical limitations inherent to biosensor design that currently limit their use in surgery. We conjecture that a complete system, with a more accurate robot, could be used in vivo. We believe that results taken from the individual studies will result in improvements to pre-operative port placement and robotic design

Design and Validation of an Augmented Reality System for Laparoscopic Surgery in a Real Environment

Purpose. This work presents the protocol carried out in the development and validation of an augmented reality system which was installed in an operating theatre to help surgeons with trocar placement during laparoscopic surgery. The purpose of this validation is to demonstrate the improvements that this system can provide to the field of medicine, particularly surgery. Method. Two experiments that were noninvasive for both the patient and the surgeon were designed. In one of these experiments the augmented reality system was used, the other one was the control experiment, and the system was not used. The type of operation selected for all cases was a cholecystectomy due to the low degree of complexity and complications before, during, and after the surgery. The technique used in the placement of trocars was the French technique, but the results can be extrapolated to any other technique and operation. Results and Conclusion. Four clinicians and ninety-six measurements obtained of twenty-four patients (randomly assigned in each experiment) were involved in these experiments.The final results show an improvement in accuracy and variability of 33% and 63%, respectively, in comparison to traditional methods, demonstrating that the use of an augmented reality system offers advantages for trocar placement in laparoscopic surgery.This work has been supported by Centro para el Desarrollo Tecnologico Industrial (CDTI) under the project Oncotic (IDI-20101153) and the Hospital Clinica Benidorm(HCB) and partially supported by the Ministry of Education and Science of Spain (TIN2010-20999-C04-01), the project Consolider-C (SEJ2006-14301/PSIC) and the "CIBER of Physiopathology of Obesity Nutrition, an initiative of ISCIII" Prometheus and Excellence Research Program (Generalitat Valenciana, Department of Education, 2008-157). The authors would like to express their gratitude to the Hospital Clinica Benidorm and to the Hospital Univeritari i Politecnic la Fe (especially the surgical team) for their participation and involvement in this work.López-Mir, F.; Naranjo Ornedo, V.; Fuertes Cebrián, JJ.; Alcañiz Raya, ML.; Bueno, J.; Pareja, E. (2013). Design and Validation of an Augmented Reality System for Laparoscopic Surgery in a Real Environment. BioMed Research International. 2013:1-12. https://doi.org/10.1155/2013/758491S1122013Rowe, C. K., Pierce, M. W., Tecci, K. C., Houck, C. S., Mandell, J., Retik, A. B., & Nguyen, H. T. (2012). A Comparative Direct Cost Analysis of Pediatric Urologic Robot-Assisted Laparoscopic Surgery Versus Open Surgery: Could Robot-Assisted Surgery Be Less Expensive? Journal of Endourology, 26(7), 871-877. doi:10.1089/end.2011.0584Azuma, R. T. (1997). A Survey of Augmented Reality. Presence: Teleoperators and Virtual Environments, 6(4), 355-385. doi:10.1162/pres.1997.6.4.355Shuhaiber, J. H. (2004). Augmented Reality in Surgery. Archives of Surgery, 139(2), 170. doi:10.1001/archsurg.139.2.170Kersten-Oertel, M., Jannin, P., & Collins, D. L. (2012). DVV: A Taxonomy for Mixed Reality Visualization in Image Guided Surgery. IEEE Transactions on Visualization and Computer Graphics, 18(2), 332-352. doi:10.1109/tvcg.2011.50Cannon, J. W., Stoll, J. A., Selha, S. D., Dupont, P. E., Howe, R. D., & Torchiana, D. F. (2003). Port placement planning in robot-assisted coronary artery bypass. IEEE Transactions on Robotics and Automation, 19(5), 912-917. doi:10.1109/tra.2003.817502Adhami, L., & Coste-Manirei, E. (2003). Optimal planning for minimally invasive surgical robots. IEEE Transactions on Robotics and Automation, 19(5), 854-863. doi:10.1109/tra.2003.817061Bichlmeier, C., Heining, S. M., Feuerstein, M., & Navab, N. (2009). The Virtual Mirror: A New Interaction Paradigm for Augmented Reality Environments. IEEE Transactions on Medical Imaging, 28(9), 1498-1510. doi:10.1109/tmi.2009.2018622Feuerstein, M., Mussack, T., Heining, S. M., & Navab, N. (2008). Intraoperative Laparoscope Augmentation for Port Placement and Resection Planning in Minimally Invasive Liver Resection. IEEE Transactions on Medical Imaging, 27(3), 355-369. doi:10.1109/tmi.2007.907327Abdominal and Laparoscopic Surgery. (2010). International Journal of Computer Assisted Radiology and Surgery, 5(S1), 122-130. doi:10.1007/s11548-010-0446-3Ferrari, V., Megali, G., Troia, E., Pietrabissa, A., & Mosca, F. (2009). A 3-D Mixed-Reality System for Stereoscopic Visualization of Medical Dataset. IEEE Transactions on Biomedical Engineering, 56(11), 2627-2633. doi:10.1109/tbme.2009.2028013McSherry, C. K. (1989). Cholecystectomy: The gold standard. The American Journal of Surgery, 158(3), 174-178. doi:10.1016/0002-9610(89)90246-8Kum, C.-K., Eypasch, E., Aljaziri, A., & Troidl, H. (1996). Randomized comparison of pulmonary function after the ‘French’ and ‘American’ techniques of laparoscopic cholecystectomy. British Journal of Surgery, 83(7), 938-941. doi:10.1002/bjs.1800830716Mischkowski, R. A., Zinser, M. J., Kübler, A. C., Krug, B., Seifert, U., & Zöller, J. E. (2006). Application of an augmented reality tool for maxillary positioning in orthognathic surgery – A feasibility study. Journal of Cranio-Maxillofacial Surgery, 34(8), 478-483. doi:10.1016/j.jcms.2006.07.862Kawamata, T., Iseki, H., Shibasaki, T., & Hori, T. (2002). Endoscopic Augmented Reality Navigation System for Endonasal Transsphenoidal Surgery to Treat Pituitary Tumors: Technical Note. Neurosurgery, 50(6), 1393-1397. doi:10.1097/00006123-200206000-00038Vogt, S., Khamene, A., & Sauer, F. (2006). Reality Augmentation for Medical Procedures: System Architecture, Single Camera Marker Tracking, and System Evaluation. International Journal of Computer Vision, 70(2), 179-190. doi:10.1007/s11263-006-7938-1Nicolau, S., Soler, L., Mutter, D., & Marescaux, J. (2011). Augmented reality in laparoscopic surgical oncology. Surgical Oncology, 20(3), 189-201. doi:10.1016/j.suronc.2011.07.002Zhang, Z. (2000). A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(11), 1330-1334. doi:10.1109/34.888718Martín-Gutiérrez, J., Luís Saorín, J., Contero, M., Alcañiz, M., Pérez-López, D. C., & Ortega, M. (2010). Design and validation of an augmented book for spatial abilities development in engineering students. Computers & Graphics, 34(1), 77-91. doi:10.1016/j.cag.2009.11.003Marquardt, D. W. (1963). An Algorithm for Least-Squares Estimation of Nonlinear Parameters. Journal of the Society for Industrial and Applied Mathematics, 11(2), 431-441. doi:10.1137/011103

Advanced techniques in medical image segmentation of the liver

Tesis por compendio[EN] Image segmentation is, along with multimodal and monomodal registration, the operation with the greatest applicability in medical image processing. There are many operations and filters, as much as applications and cases, where the segmentation of an organic tissue is the first step. The case of liver segmentation in radiological images is, after the brain, that on which the highest number of scientific publications can be found. This is due, on the one hand, to the need to continue innovating in existing algorithms and, on the other hand, to the applicability in many situations related to diagnosis, treatment and monitoring of liver diseases but also for clinical planning. In the case of magnetic resonance imaging (MRI), only in recent years some solutions have achieved good results in terms of accuracy and robustness in the segmentation of the liver. However these algorithms are generally not user-friendly. In the case of computed tomography (CT) scans more methodologies and solutions have been developed but it is difficult to find a good trade-off between accuracy and practical clinical use. To improve the state-of-the-art in both cases (MRI and CT), a common methodology to design and develop two liver segmentation algorithms in those imaging modalities has been proposed in this thesis. The second step has been the validation of both algorithms. In the case of CT images, there exist public databases with images segmented manually by experts that the scientific community uses as a common link for the validation and comparison of their algorithms. The validation is done by obtaining certain coefficients of similarity between the manual and the automatic segmentation. This way of validating the accuracy of the algorithm has been followed in this thesis, except in the case of magnetic resonance imaging because, at present, there are no databases publicly available. In this case, there aren't public or accessible images. Accordingly, a private database has been created where several expert radiologists have manually segmented different studies of patients that have been used as a reference. This database is composed by 17 studies (with more than 1,500 images), so the validation of this method in MRI is one of the more extensive currently published. In the validation stage, an accuracy above 90% in the Jaccard and Dice coefficients has been achieved. The vast majority of the compared authors achieves similar values. However, in general, the algorithms proposed in this thesis are more user-friendly for clinical environments because the computational cost is lower, the clinical interaction is non-existent and it is not necessary an initiation in the case of the magnetic resonance algorithm and a small initiation (it is only necessary to introduce a manual seed) for the computed tomography algorithm. In this thesis, a third hypothesis that makes use of the results of liver segmentation in MRI combined to augmented reality algorithms has also been developed. Specifically, a real and innocuous study, non-invasive for clinician and patient has been designed and validated through it has been shown that the use of this technology creates benefits in terms of greater accuracy and less variability versus the non-use in a particular case of laparoscopic surgery.[ES] La segmentación de imágenes es, junto al registro multimodal y monomodal, la operación con mayor aplicabilidad en tratamiento digital de imagen médica. Son multitud las operaciones y filtros, así como las aplicaciones y casuística, que derivan de una segmentación de un tejido orgánico. El caso de segmentación del hígado en imágenes radiológicas es, después del cerebro, la que mayor número de publicaciones científicas podemos encontrar. Esto es debido por un lado a la necesidad de seguir innovando en los algoritmos ya existentes y por otro a la gran aplicabilidad que tiene en muchas situaciones relacionadas con el diagnóstico, tratamiento y seguimiento de patologías hepáticas pero también para la planificación clínica de las mismas. En el caso de imágenes de resonancia magnética, sólo en los últimos años han aparecido soluciones que consiguen buenos resultados en cuanto a precisión y robustez en la segmentación del hígado. Sin embargo dichos algoritmos, por lo general son poco utilizables en el ambiente clínico. En el caso de imágenes de tomografía computarizada encontramos mucha más variedad de metodologías y soluciones propuestas pero es difícil encontrar un equilibrio entre precisión y uso práctico clínico. Es por ello que para mejorar el estado del arte en ambos casos (imágenes de resonancia magnética y tomografía computarizada) en esta tesis se ha planteado una metodología común a la hora de diseñar y desarrollar sendos algoritmos de segmentación del hígado en las citadas modalidades de imágenes anatómicas. El segundo paso ha sido la validación de ambos algoritmos. En el caso de imágenes de tomografía computarizada existen bases de datos públicas con imágenes segmentadas manualmente por expertos y que la comunidad científica suele utilizar como nexo común a la hora de validar y posteriormente comparar sus algoritmos. La validación se hace mediante la obtención de determinados coeficientes de similitud entre la imagen segmentada manualmente por los expertos y las que nos proporciona el algoritmo. Esta forma de validar la precisión del algoritmo ha sido la seguida en esta tesis, con la salvedad que en el caso de imágenes de resonancia magnética no existen bases de datos de acceso público. Por ello, y para este caso, lo que se ha hecho es la creación previa de una base de datos propia donde diferentes expertos radiólogos han segmentado manualmente diferentes estudios de pacientes con el fin de que puedan servir como referencia y se pueda seguir la misma metodología que en el caso anterior. Dicha base de datos ha hecho posible que la validación se haga en 17 estudios (con más de 1.500 imágenes), lo que convierte la validación de este método de segmentación del hígado en imágenes de resonancia magnética en una de las más extensas publicadas hasta la fecha. La validación y posterior comparación han dejado patente una precisión superior al 90% reflejado en el coeficiente de Jaccard y Dice, muy en consonancia con valores publicados por la inmensa mayoría de autores que se han podido comparar. Sin embargo, y en general, los algoritmos planteados en esta tesis han obtenido unos criterios de uso mucho mayores, ya que en general presentan menores costes de computación, una interacción clínica casi nula y una iniciación nula en el caso del algoritmo de resonancia magnética y casi nula en el caso de algoritmos de tomografía computarizada. En esta tesis, también se ha abordado un tercer punto que hace uso de los resultados obtenidos en la segmentación del hígado en imágenes de resonancia magnética. Para ello, y haciendo uso de algoritmos de realidad aumentada, se ha diseñado y validado un estudio real inocuo y no invasivo para el clínico y para el paciente donde se ha demostrado que la utilización de esta tecnología reporta mayores beneficios en cuanto a mayor precisión y menor variabilidad frente a su no uso en un caso concreto de ciru[CA] La segmentació d'imatges és, al costat del registre multimodal i monomodal, l'operació amb major aplicabilitat en tractament digital d'imatge mèdica. Són multitud les operacions i filtres, així com les aplicacions i casuística, que comencen en la segmentació d'un teixit orgànic. El cas de segmentació del fetge en imatges radiològiques és, després del cervell, la que major nombre de publicacions científiques podem trobar. Això és degut per una banda a la necessitat de seguir innovant en els algoritmes ja existents i per un altre a la gran aplicabilitat que té en moltes situacions relacionades amb el diagnòstic, tractament i seguiment de patologies hepàtiques però també per a la planificació clínica de les mateixes. En el cas d'imatges de ressonància magnètica, només en els últims anys han aparegut solucions que aconsegueixen bons resultats quant a precisió i robustesa en la segmentació del fetge. No obstant això aquests algoritmes, en general són poc utilitzables en l'ambient clínic. En el cas d'imatges de tomografia computeritzada trobem molta més varietat de metodologies i solucions proposades però és difícil trobar un equilibri entre precisió i ús pràctic clínic. És per això que per millorar l'estat de l'art en els dos casos (imatges de ressonància magnètica i tomografia computeritzada) en aquesta tesi s'ha plantejat una metodologia comuna a l'hora de dissenyar i desenvolupar dos algoritmes de segmentació del fetge en les esmentades modalitats d'imatges anatòmiques. El segon pas ha estat la validació de tots dos algoritmes. En el cas d'imatges de tomografia computeritzada hi ha bases de dades públiques amb imatges segmentades manualment per experts i que la comunitat científica sol utilitzar com a nexe comú a l'hora de validar i posteriorment comparar els seus algoritmes. La validació es fa mitjançant l'obtenció de determinats coeficients de similitud entre la imatge segmentada manualment pels experts i les que ens proporciona l'algoritme. Aquesta forma de validar la precisió de l'algoritme ha estat la seguida en aquesta tesi, amb l'excepció que en el cas d'imatges de ressonància magnètica no hi ha bases de dades d'accés públic. Per això, i per a aquest cas, el que s'ha fet és la creació prèvia d'una base de dades pròpia on diferents experts radiòlegs han segmentat manualment diferents estudis de pacients amb la finalitat que puguen servir com a referència i es puga seguir la mateixa metodologia que en el cas anterior. Aquesta base de dades ha fet possible que la validació es faja en 17 estudis (amb més de 1.500 imatges), cosa que converteix la validació d'aquest mètode de segmentació del fetge en imatges de ressonància magnètica en una de les més extenses publicades fins a la data. La validació i posterior comparació han deixat patent una precisió superior al 90 \% reflectit en el coeficient de \ textit {Jaccard} i \ textit {Dice}, molt d'acord amb valors publicats per la immensa majoria d'autors en que s'ha pogut comparar. No obstant això, i en general, els algoritmes plantejats en aquesta tesi han obtingut uns criteris d'ús molt més grans, ja que en general presenten menors costos de computació, una interacció clínica quasi nul·la i una iniciació nul·la en el cas de l'algoritme de ressonància magnètica i quasi nul·la en el cas d'algoritmes de tomografia computeritzada. En aquesta tesi, també s'ha abordat un tercer punt que fa ús dels resultats obtinguts en la segmentació del fetge en imatges de ressonància magnètica. Per a això, i fent ús d'algoritmes de realitat augmentada, s'ha dissenyat i validat un estudi real innocu i no invasiu per al clínic i per al pacient on s'ha demostrat que la utilització d'aquesta tecnologia reporta més beneficis pel que fa a major precisió i menor variabilitat enfront del seu no ús en un cas concret de cirurgia amb laparoscòpia.López Mir, F. (2015). Advanced techniques in medical image segmentation of the liver [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/59428TESISPremios Extraordinarios de tesis doctoralesCompendi

Port placement planning in robot-assisted coronary artery bypass

Properly selected port sites for robot-assisted coronary artery bypass graft (CABG) improve the efficiency and quality of these procedures. In clinical practice, surgeons select port locations using external anatomic landmarks to estimate a patient’s internal anatomy. This paper proposes an automated approach to port selection based on a preoperative image of the patient, thus avoiding the need to estimate internal anatomy. Using this image as input, port sites are chosen from a grid of surgeon-approved options by defining a performance measure for each possible port triad. This measure seeks to minimize the weighted squared deviation of the instrument and endoscope angles from their optimal orientations at each internal surgical site. This performance measure proves insensitive to perturbations in both its weighting factors and moderate intraoperative displacements of the patient’s internal anatomy. A validation study of this port site selection was performed. cardiac algorithm also Six surgeons dissected model vessels using the port triad selected by this algorithm with performance compared to dissection using a surgeon-selected port triad and a port triad template described by Tabaie et al., 1999. With the algorithm-selected ports, dissection speed increased by up to 43% (p = 0.046) with less overall vessel trauma. Thus, this algorithmic approach to port site selection has important clinical implications for robot-assisted CABG which warrant further investigation

Wissensbasierte Planung für die minimal-invasive Chirurgie

In der minimal-invasiven Chirurgie ist die Wahl der Zugänge für den Erfolg einer Operation entscheidend. Beim Einsatz eines Robotersystems besteht Kollisionsgefahr der Roboterarme. Die vorgestellte wissensbasierte Planung ermöglicht effizientere und effektivere Operationen. Der Operationsablauf wird erlernt und in einer probabilistischen Wissensbasis gespeichert. Das Wissen wird zudem für ein prädiktives Kameraführungssystem genutzt. Die Metaheuristik STO wird vorgestellt