A clinically applicable laser-based image-guided system for laparoscopic liver procedures

Fusaglia, Matteo; Hess, Hanspeter; Schwalbe, Marius; Peterhans, Matthias; Tinguely, Pascale Marie-Pia; Weber, Stefan; Lu, Huanxiang

doi:10.1007/s11548-015-1309-8

Cited by 11 publications

(5 citation statements)

References 33 publications

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“…Approaches that have been investigated typically utilize rigid registrations, which cannot account for intraoperative soft tissue deformation. [8][9][10][11][12][13] One major source of deformation in laparoscopic procedures is the process of insufflation where the abdominal cavity is pressurized with carbon dioxide. Insufflation has been shown to cause distension and displacement of the ventral wall and diaphragm, 14,15 to which the liver is attached by the falciform ligament and the left and right triangular ligaments, respectively [ Fig.…”

Section: Introductionmentioning

confidence: 99%

Characterization and correction of intraoperative soft tissue deformation in image-guided laparoscopic liver surgery

et al. 2017

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Laparoscopic liver surgery is challenging to perform due to a compromised ability of the surgeon to localize subsurface anatomy in the constrained environment. While image guidance has the potential to address this barrier, intraoperative factors, such as insufflation and variable degrees of organ mobilization from supporting ligaments, may generate substantial deformation. The severity of laparoscopic deformation in humans has not been characterized, and current laparoscopic correction methods do not account for the mechanics of how intraoperative deformation is applied to the liver. We first measure the degree of laparoscopic deformation at two insufflation pressures over the course of laparoscopic-to-open conversion in 25 patients. With this clinical data alongside a mock laparoscopic phantom setup, we report a biomechanical correction approach that leverages anatomically load-bearing support surfaces from ligament attachments to iteratively reconstruct and account for intraoperative deformations. Laparoscopic deformations were significantly larger than deformations associated with open surgery, and our correction approach yielded subsurface target error of [Formula: see text] and surface error of [Formula: see text] using only sparse surface data with realistic surgical extent. Laparoscopic surface data extents were examined and found to impact registration accuracy. Finally, we demonstrate viability of the correction method with clinical data.

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Section: Introductionmentioning

confidence: 99%

Characterization and correction of intraoperative soft tissue deformation in image-guided laparoscopic liver surgery

et al. 2017

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“…(2015b ). Similarly to the structured light technology, endoscopic laser range scanners may also be used to recover the surface of an organ ( Fusaglia et al, 2015 ).…”

Section: Active Techniquesmentioning

confidence: 99%

The status of augmented reality in laparoscopic surgery as of 2016

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et al. 2017

Medical Image Analysis

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“…Finally, fully automated techniques have been proposed in [ 7 , 17 ]. Fusaglia et al [ 17 ] developed an exhaustive search over the principal directions of the intraoperative surface, which is acquired using a laparoscopic laser pointer. While their proposed approach is promising, it still introduces additional tools into the clinical workflow.…”

Section: Introductionmentioning

confidence: 99%

“…Their approach was validated on a phantom of the human liver and on an ex-vivo porcine liver with accuracy better than 1 cm and computation time ranging from one minute to 5.5 h. While their phantom validation under deformation from breathing motion can be sufficient for open surgery, livers in laparoscopic interventions undergo significant general deformation due to pneumoperitoneum. Furthermore, it is unclear how both methods [ 7 , 17 ] would be translated to laparoscopic interventions since they rely on large surfaces of the liver being visible.…”

Section: Introductionmentioning

confidence: 99%

Global rigid registration of CT to video in laparoscopic liver surgery

et al. 2018

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PurposeImage-guidance systems have the potential to aid in laparoscopic interventions by providing sub-surface structure information and tumour localisation. The registration of a preoperative 3D image with the intraoperative laparoscopic video feed is an important component of image guidance, which should be fast, robust and cause minimal disruption to the surgical procedure. Most methods for rigid and non-rigid registration require a good initial alignment. However, in most research systems for abdominal surgery, the user has to manually rotate and translate the models, which is usually difficult to perform quickly and intuitively.MethodsWe propose a fast, global method for the initial rigid alignment between a 3D mesh derived from a preoperative CT of the liver and a surface reconstruction of the intraoperative scene. We formulate the shape matching problem as a quadratic assignment problem which minimises the dissimilarity between feature descriptors while enforcing geometrical consistency between all the feature points. We incorporate a novel constraint based on the liver contours which deals specifically with the challenges introduced by laparoscopic data.ResultsWe validate our proposed method on synthetic data, on a liver phantom and on retrospective clinical data acquired during a laparoscopic liver resection. We show robustness over reduced partial size and increasing levels of deformation. Our results on the phantom and on the real data show good initial alignment, which can successfully converge to the correct position using fine alignment techniques. Furthermore, since we can pre-process the CT scan before surgery, the proposed method runs faster than current algorithms.ConclusionThe proposed shape matching method can provide a fast, global initial registration, which can be further refined by fine alignment methods. This approach will lead to a more usable and intuitive image-guidance system for laparoscopic liver surgery.

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A clinically applicable laser-based image-guided system for laparoscopic liver procedures

Abstract: We believe that the presented approach will lead to a faster integration of LRS-based registration techniques in the surgical environment. Further studies will focus on optimizing scanning time and on the respiratory motion compensation.

Cited by 11 publications

References 33 publications

Characterization and correction of intraoperative soft tissue deformation in image-guided laparoscopic liver surgery

Characterization and correction of intraoperative soft tissue deformation in image-guided laparoscopic liver surgery

The status of augmented reality in laparoscopic surgery as of 2016

Global rigid registration of CT to video in laparoscopic liver surgery

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