Review on different experimental techniques developed for recording force-deformation behaviour of soft tissues; with a view to surgery simulation applications

Enhancing the Localization of Uterine Leiomyomas Through Cutaneous Softness Rendering for Robot-Assisted Surgical Palpation Applications

Integrating tactile feedback for lump localization in Robot-assisted Minimally Invasive Surgery (RMIS) represents an open research issue, which is still far to be solved. Main reasons for this are related e.g. to the need for a transparent connection with the teleoperating console, and an intuitive decoding of the delivered information. In this article, we focus on the specific case of RMIS treatment of uterine leiomyomas or fibroids, where little has been done in haptics to improve the outcomes of robotics-enabled palpation tasks. In this article, we propose the usage of a wearable haptic interface for softness rendering as a lump display. The device was integrated in a teleoperation architecture that simulates a robot-assisted surgical palpation task of leiomyomas. This article moved from an ex-vivo sample characterization of uterine tissues to show the effectiveness of our interface in conveying meaningful softness information. We extensively tested our system with gynecologic surgeons in palpation tasks with silicone specimens, which replicated the characteristics of uterine tissues with embedded leyomiomas. Results show that our system enables a softness-based discrimination of the embedded fibroids comparable to the one that physicians would achieve using directly their fingers in palpation tasks. Furthermore, the feedback provided by the haptic interface was perceived as comfortable, intuitive, and highly useful for fibroid localization.

The identification of the unloaded configuration of breast tissue with unknown non-homogenous stiffness parameters using surface measured data in deformed configuration

Large deformation analysis of the breast is known as a useful approach for locating the tumor and treatment strategies of breast cancer, for which knowing the breast stiffness parameters and unloaded configuration is crucial to obtain reliable results. In this study, an iterative inverse finite element algorithm is developed to identify the unloaded configuration of the breast while its stiffness constants are unknown and its internal structure is assumed to be non-homogeneous. The position vector of surface points in the deformed configuration of the breast is employed to obtain the unknowns of the inverse problem. An objective function based on the difference between the position vector of the calculated and measured deformed configurations is defined. Thereafter, the objective function is minimized using a gradient-based method. The sensitivity analysis for material parameters is performed using an analytic direct differentiation approach. Through several numerical examples, the effectiveness of the proposed inverse method for identifying the unloaded configuration of a uniform, a computational breast phantom with a single inclusion as well as a computational breast phantom with randomly distributed stiffness, is demonstrated. The effects of the number of load cases, measurement error, and initial guesses on the results of the inverse problem are investigated, as well. It is observed that the unloaded configuration of the computational breast phantom with a single inclusion or heterogeneous breast tissues can be accurately found by considering an equivalent homogenous material for the tissue.

Integrated bioinformatics analysis to identify 15 hub genes in breast cancer

The aim of the present study was to identify the hub genes and provide insight into the tumorigenesis and development of breast cancer. To examine the hub genes in breast cancer, integrated bioinformatics analysis was performed. Gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database and the differentially expressed genes (DEGs) were identified using the ‘limma’ package in R. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis was used to determine the functional annotations and potential pathways of the DEGs. Subsequently, a protein-protein interaction network analysis and weighted correlation network analysis (WGCNA) were conducted to identify hub genes. To confirm the reliability of the identified hub genes, RNA gene expression profiles were obtained from The Cancer Genome Atlas (TCGA)-breast cancer database, and WGCNA was used to screen for genes that were markedly correlated with breast cancer. By combining the results from the GEO and TCGA datasets, 15 hub genes were identified to be associated with breast cancer pathophysiology. Overall survival analysis was performed to examine the association between the expression of hub genes and the overall survival time of patients with breast cancer. Higher expression of all hub genes was associated with significantly shorter overall survival in patients with breast cancer compared with patients with lower levels of expression of the respective gene.

Head-mounted display augmented reality to guide pedicle screw placement utilizing computed tomography

PURPOSE

Augmented reality has potential to enhance surgical navigation and visualization. We determined whether head-mounted display augmented reality (HMD-AR) with superimposed computed tomography (CT) data could allow the wearer to percutaneously guide pedicle screw placement in an opaque lumbar model with no real-time fluoroscopic guidance.

METHODS

CT imaging was obtained of a phantom composed of L1-L3 Sawbones vertebrae in opaque silicone. Preprocedural planning was performed by creating virtual trajectories of appropriate angle and depth for ideal approach into the pedicle, and these data were integrated into the Microsoft HoloLens using the Novarad OpenSight application allowing the user to view the virtual trajectory guides and CT images superimposed on the phantom in two and three dimensions. Spinal needles were inserted following the virtual trajectories to the point of contact with bone. Repeat CT revealed actual needle trajectory, allowing comparison with the ideal preprocedural paths.

RESULTS

Registration of AR to phantom showed a roughly circular deviation with maximum average radius of 2.5 mm. Users took an average of 200 s to place a needle. Extrapolation of needle trajectory into the pedicle showed that of 36 needles placed, 35 (97%) would have remained within the pedicles. Needles placed approximated a mean distance of 4.69 mm in the mediolateral direction and 4.48 mm in the craniocaudal direction from pedicle bone edge.

CONCLUSION

To our knowledge, this is the first peer-reviewed report and evaluation of HMD-AR with superimposed 3D guidance utilizing CT for spinal pedicle guide placement for the purpose of cannulation without the use of fluoroscopy.