Automated segmentation of tissue structures in optical coherence tomography data

Clinical feasibility of optical coherence micro-elastography for imaging tumor margins in breast-conserving surgery

It has been demonstrated that optical coherence micro-elastography (OCME) provides additional contrast of tumor compared to optical coherence tomography (OCT) alone. Previous studies, however, have predominantly been performed on mastectomy specimens. Such specimens typically differ substantially in composition and geometry from the more clinically relevant wide-local excision (WLE) specimens excised during breast-conserving surgery. As a result, it remains unclear if the mechanical contrast observed is maintained in WLE specimens. In this manuscript, we begin to address this issue by performing a feasibility study of OCME on 17 freshly excised, intact WLE specimens. In addition, we present two developments required to sustain the progression of OCME towards intraoperative deployment. First, to enable the rapid visualization of en face images required for intraoperative assessment, we describe an automated segmentation algorithm to fuse en face micro-elastograms with OCT images to provide dual contrast images. Secondly, to validate contrast in micro-elastograms, we present a method that enables co-registration of en face images with histology of WLE specimens, sectioned in the orthogonal plane, without any modification to the standard clinical workflow. We present a summary of the observations across the 17 specimens imaged in addition to representative micro-elastograms and OCT images demonstrating contrast in a number of tumor margins, including those involved by invasive ductal carcinoma, mucinous carcinoma, and solid-papillary carcinoma. The results presented here demonstrate the potential of OCME for imaging tumor margins.

Computer aided preoperative evaluation of the residual liver volume using computed tomography images

Major hepatectomy causes a risk of postoperative liver dysfunction, failure, and infections like surgical site infection. Preoperative assessment of the liver volume and function of the remnant liver is a mandatory prerequisite before performing such surgery. The aim of this work is to develop and test a software application for evaluation of the residual function of the liver prior to the intervention of the surgeons. For this purpose, a technique for evaluation of liver volume from computed tomography (CT) images has been developed. Furthermore, the methodology algorithms were implemented and incorporated within a software tool with three basic functionalities: volume determination based on segmentation of liver from CT images, virtual tumour resection and estimation of the residual liver function and 3D visualisation. Forty-one sets of abdominal CT images consisting of different number of tomographic slice images were used to test and evaluate the proposed approach. Volumes that were obtained after manual tracing by two surgeon experts showed a relative difference of 3.5 %. The suggested methodology was encapsulated within an application with user-friendly interface that allows surgeons interactively to perform virtual tumour resection, to evaluate the relative residual liver and render the final result. Thereby, it is a tool in the surgeons' hands that significantly facilitates their duties, saves time, and allows them to objectively evaluate the situation and take the right decisions. At the same time, the tool appears to be appropriate educational instrument for virtual training of young surgeon specialists.

Automatic scanning of large tissue areas in neurosurgery using optical coherence tomography

BACKGROUND

With its high spatial and temporal resolution, optical coherence tomography (OCT) is an ideal modality for intra-operative imaging. One possible application is to detect tumour invaded tissue in neurosurgery, e.g. during complete resection of glioblastoma. Ideally, the whole resection cavity is scanned. However, OCT is limited to a small field of view (FOV) and scanning perpendicular to the tissue surface.

METHODS

We present a new method to use OCT for scanning of the resection cavity during neurosurgical resection of brain tumours. The main challenges are creating a map of the cavity, scanning perpendicular to the surface and merging the three-dimensional (3D) data for intra-operative visualization and detection of residual tumour cells.

RESULTS

Our results indicate that the proposed method enables creating high-resolution maps of the resection cavity. An overlay of these maps with the microscope images provides the surgeon with important information on the location of residual tumour tissue underneath the surface.

CONCLUSION

We demonstrated that it is possible to automatically acquire an OCT image of the complete resection cavity. Overlaying microscopy images with depth information from OCT could lead to improved detection of residual tumour cells.