Three-dimensional finite-element based deformable image registration for evaluation of pleural cavity irradiation during photodynamic therapy

Abstract

Purpose: Photodynamic therapy (PDT) is used after surgical resection to treat the microscopic disease for malignant pleural mesothelioma and to increase survival rates. As accurate light delivery is imperative to PDT efficacy, the deformation of the pleural volume during the surgery is studied on its impact on the delivered light fluence. In this study, a three-dimensional finite element-based (3D FEM) deformable image registration is proposed to directly match the volume of lung to the volume of pleural cavity obtained during PDT to have accurate representation of the light fluence accumulated in the lung, heart and liver (organs-at-risk) during treatment.

Methods: A wand, comprised of a modified endotrachial tube filled with Intralipid and an optical fiber inside the tube, is used to deliver the treatment light. The position of the treatment is tracked using an optical tracking system with an attachment comprised of nine reflective passive markers that are seen by an infrared camera-based navigation system. This information is used to obtain the surface contours of the plural cavity and the cumulative light fluence on every point of the cavity surface that is being treated. The lung, heart, and liver geometry are also reconstructed from a series of computed tomography (CT) scans of the organs acquired in the same patient before and after the surgery. The contours obtained with the optical tracking system and CTs are imported into COMSOL Multiphysics, where the 3D FEM-based deformable image registration is obtained. The delivered fluence values are assigned to the respective positions (x, y, and z) on the optical tracking contour. The optical tracking contour is considered as the reference, and the CT contours are used as the target, which will be deformed. The data from three patients formed the basis for this study.

Results: The physical correspondence between the CT and optical tracking geometries, taken at different times, from different imaging devices was established using the 3D FEM-based image deformable registration. The volume of lung was matched to the volume of pleural cavity and the distribution of light fluence on the surface of the heart, liver and deformed lung volumes was obtained.

Conclusion: The method used is appropriate for analyzing problems over complicated domains, such as when the domain changes (as in a solid-state reaction with a moving boundary), when the desired precision varies over the entire domain, or when the solution lacks smoothness. Implementing this method in real-time for clinical applications and in situ monitoring of the under- or over- exposed regions to light during PDT can significantly improve the treatment for mesothelioma.

Keywords: CT; 3D FEM-based image deformable registration; heart; liver; lung; mesothelioma PDT; pleural cavity volume.

Figure 1

(a) 3D geometry of the plural cavity (gray) acquired from the optical tracking system. The surface geometry was reconstructed from a point cloud obtained by using an infrared camera that monitors movement of a point in a 3D volume in the operating room. (b) 3D lung (blue, upper left), heart (red, middle right), and liver (purple, lower left) contours obtained from CTs after the segmentation with Aria software. (c) The registered optical tracking and CT contours in COMSOL Multiphysics 5.0 software. The images are presented with the grids for the finite element (FEM) analyses mesh. [Color figure can be viewed at wileyonlinelibrary.com]

Figure 2

Image deformable registration for matching of the volumes of lung obtained from the CT images to the optical tracking volume. The surface stress vectors, deformed mesh, and element quality has been shown for the deformed lung volume. [Color figure can be viewed at wileyonlinelibrary.com]

Figure 3

Axial and sagittal cross‐sections of the transformation error in terms of corresponding nodal distance between optical tracking surface (dark black line) and the transformed CT (light red line). Transformation error at (a) z = 30, 35, 40, 45 cm and (b) x = −2, 0, 2, 4 cm. [Color figure can be viewed at wileyonlinelibrary.com]

Figure 4

Image deformable registration for matching of the volumes of lung obtained from the CT images before PDT (Pre‐PDT CT) and the lung volume obtained from the CT images after the PDT (Post‐PDT CT). The surface stress vectors, deformed mesh, and element quality have been shown for the deformed lung volume. [Color figure can be viewed at wileyonlinelibrary.com]

Figure 5

Light fluence distribution on the surface of the deformed lung, and organs‐at‐risk (heart, and liver) during PDT. The color bar represents the different light fluence values in J/cm². [Color figure can be viewed at wileyonlinelibrary.com]