Trachea marking

#Technical Field

#The present disclosure relates to the treatment of patients with lung diseases and, more particularly, to devices, systems, and methods for marking the trachea in a three-dimensional (3D) model generated based on CT scan image data of a patient's lungs.

#Discussion of Related Art

#Various aspects and features of the present disclosure are described herein below with references to the drawings, wherein:

#FIG. 1 is a schematic diagram of an example device which may be used to mark a trachea in a 3D model of a patient's lungs, in accordance with an embodiment of the present disclosure;

#FIG. 2 depicts 2D slice images generated from the 3D model showing the trachea in the axial and coronal orientations, in accordance with embodiments of the present disclosure;

#The present disclosure is related to devices, systems, and methods for identifying and manually marking a trachea and main carina on slice images of a patient's lungs when automatic detection of the trachea fails. Identifying the trachea may be a necessary component of pathway planning for performing an ELECTROMAGNETIC NAVIGATION BRONCHOSCOPY® (ENB) procedure using an electromagnetic navigation (EMN) system.

#An ENB procedure generally involves at least two phases: (1) planning a pathway to a target located within, or adjacent to, the patient's lungs; and (2) navigating a probe to the target along the planned pathway. These phases are generally referred to as (1) “planning” and (2) “navigation.” Prior to the planning phase, the patient's lungs are imaged by, for example, a computed tomography (CT) scan, although additional applicable methods of imaging will be known to those skilled in the art. The image data assembled during the CT scan may then be stored in, for example, the Digital Imaging and Communications in Medicine (DICOM) format, although additional applicable formats will be known to those skilled in the art. The CT scan image data may then be loaded into a planning software application (“application”) to be processed for generating a 3D model which may be used during the planning phase of the ENB procedure.

#The application may use the CT scan image data to generate a 3D model of the patient's lungs. The 3D model may include, among other things, a model airway tree corresponding to the actual airways of the patient's lungs, and showing the various passages, branches, and bifurcations of the patient's actual airway tree. While the CT scan image data may have gaps, omissions, and/or other imperfections included in the image data, the 3D model is a smooth representation of the patient's airways, with any such gaps, omissions, and/or imperfections in the CT scan image data filled in or corrected. As described in more detail below, the 3D model may be viewed in various orientations. For example, if a clinician desires to view a particular section of the patient's airways, the clinician may view the 3D model represented in a 3D rendering and rotate and/or zoom in on the particular section of the patient's airways. Additionally, the clinician may view the 3D model represented in two-dimensional (2D) slice images generated along the axial, sagittal, and coronal planes, and may “scroll through” such 2D slice images to a “depth” showing the particular section of the patient's airways. The planning phase generally involves identifying at least one target nodule in the 3D model, and generating a pathway to the target. The pathway will generally run from the patient's mouth, through the trachea and connected airways, to the target. However, in order to generate the pathway to the target, the location of the trachea within the 3D model must be known. Generally, the application will automatically detect the trachea within the 3D model. This process is more fully described in commonly-owned U.S. Provisional Patent Application Ser. No. 62/020,257 entitled “Automatic Detection of Human Lung Trachea”, filed on Jul. 2, 2014, by Markov et al., the entire contents of which are hereby incorporated by reference. However, there may be instances where automatic detection of the trachea fails. The present disclosure is directed to devices, systems, and methods for manually marking the trachea in such instances.