Virtual Bronchoscopy System Research Articles

Combined virtual-assisted lung mapping (VAL-MAP) with CT-guided localization in thoracoscopic pulmonary segmentectomy

Virtual assisted lung mapping (VAL-MAP) is a bronchoscopic lung marking technique developed to assist in navigational lung resection. It can be used for nodule localization and segmental identification. This article presents our initial experience of thoracoscopic pulmonary segmentectomy using combined VAL-MAP and computed tomography (CT)-guided localization. Markings with India Ink were made bronchoscopically, before surgery, using a virtual bronchoscopy system (LungPoint® Planner) without fluoroscopy guidance. Post VAL-MAP CT scans localized the actual markings. All data on patients, markings, and outcomes were retrospectively collected, and the contribution of VAL-MAP to the operation was graded by the surgeon. From March 2017 to September 2017, 24 consecutive patients received the VAL-MAP marking procedure before thoracoscopic segmentectomy. Nineteen patients also received pre-operative CT-guided percutaneous localization after VAL-MAP; fifteen patients received CT-guided localization with dye (patent blue V) and microcoil, and four patients received with dye only. Of the 101 marking attempts made in all the patients, 71 (70.3%) were identified as contributing to the surgery. No clinically evident complications were associated with the procedure. A total of 24 segmentectomies were thoracoscopically conducted for 18 cases of lung cancer and six cases of benign diseases. The combination of VAL-MAP and CT-guided percutaneous localization contribute to precise thoracoscopic pulmonary segmentectomy.

Virtual Bronchoscopy-Guided Treatment Planning to Map and Mitigate Radiation-Induced Airway Injury in Lung SAbR

Radiation injury to the bronchial tree is an important yet poorly understood potential side effect in lung stereotactic ablative radiation therapy (SAbR). We investigate the integration of virtual bronchoscopy in radiation therapy planning to quantify dosage to individual airways. We develop a risk model of airway collapse and develop treatment plans that reduce the risk of radiation-induced airway injury. Pre- and post-SAbR diagnostic-quality computerized tomography (CT) scans were retrospectively collected from 26 lung cancer patients. From each scan, the bronchial tree was segmented using a virtual bronchoscopy system and registered deformably to the planning CT. Univariate and stepwise multivariate Cox regressions were performed, examining factors such as age, comorbidities, smoking pack years, airway diameter, and maximum point dosage (Dmax). Logistic regression was utilized to formulate a risk function of segmental collapse based on Dmax and diameter. The risk function was incorporated into the objective function along with clinical dosage volume constraints for planning target volume (PTV) and organs at risk (OARs). Univariate analysis showed that segmental diameter (P=.014) and Dmax (P=.007) were significantly correlated with airway segment collapse. Multivariate stepwise Cox regression showed that diameter (P=.015), Dmax (P<.0001), and pack/years of smoking (P=.02) were significant independent factors associated with collapse. Risk management-based plans enabled significant dosage reduction to individual airway segments while fulfilling clinical dosimetric objectives. To our knowledge, this is the first systematic investigation of functional avoidance in lung SAbR based on mapping and minimizing doses to individual bronchial segments. Our early results show that it is possible to substantially lower airway dosage. Such dosage reduction may potentially reduce the risk of radiation-induced airway injury, while satisfying clinically prescribed dosimetric objectives.

Pre-clinical validation of virtual bronchoscopy using 3D Slicer

Lung cancer still represents the leading cause of cancer-related death, and the long-term survival rate remains low. Computed tomography (CT) is currently the most common imaging modality for lung diseases recognition. The purpose of this work was to develop a simple and easily accessible virtual bronchoscopy system to be coupled with a customized electromagnetic (EM) tracking system for navigation in the lung and which requires as little user interaction as possible, while maintaining high usability. The proposed method has been implemented as an extension to the open-source platform, 3D Slicer. It creates a virtual reconstruction of the airways starting from CT images for virtual navigation. It provides tools for pre-procedural planning and virtual navigation, and it has been optimized for use in combination with a [Formula: see text] of freedom EM tracking sensor. Performance of the algorithm has been evaluated in ex vivo and in vivo testing. During ex vivo testing, nine volunteer physicians tested the implemented algorithm to navigate three separate targets placed inside a breathing pig lung model. In general, the system proved easy to use and accurate in replicating the clinical setting and seemed to help choose the correct path without any previous experience or image analysis. Two separate animal studies confirmed technical feasibility and usability of the system. This work describes an easily accessible virtual bronchoscopy system for navigation in the lung. The system provides the user with a complete set of tools that facilitate navigation towards user-selected regions of interest. Results from ex vivo and in vivo studies showed that the system opens the way for potential future work with virtual navigation for safe and reliable airway disease diagnosis.

Catheter Position Tracking System Using Planar Magnetics and Closed Loop Current Control

This paper presents an electromagnetic system for five degrees of freedom position and orientation sensing with application in a virtual bronchoscopy system. Planar magnetic source coils were manufactured on printed circuit boards for reproducibility and low-cost manufacturing. The exact magnetic field of each coil is calculated using a filament-based approach. A constant ac current amplifier is used to drive each coil at an independent frequency and a synchronous demodulator calculates each associated magnetic field component using the current waveform as a reference signal. Commercially available search coil sensors are used and a comparison between shielded and unshielded probes is presented. Extensive testing with two separate methods has shown the accuracy of the system to be between 1 and 2 mm. The use of a novel closed loop coil driver has been found to offer excellent magnetic field stability and significant reduction in crosstalk interference.

Haptic-based navigation for the virtual bronchoscopy

AbstractIn order to help in the diagnosis of peripheral lung lesions, this paper presents a virtual bronchoscopy system that allows the navigation within a 3D reconstruction of the tracheobronchial tree using a haptic device whose permitted motions mimics those done with the real bronchoscope, and that is able to feedback forces resulting from contacts with the walls. The system reconstructs the 3D model from CT images, and computes a path from the trachea to the peripheral target to be analyzed in order to guide the exploration. The execution of the virtual bronchoscopy with the proposed system, prior to the execution of the real one, may increase the confidence of pulmonologists and is expected to result in an improvement in the final lung cancer diagnosis.

Hybrid segmentation and virtual bronchoscopy based on CT images 1

Rationale and objectives Introduction of combination of the segmentation tool SegoMeTex and the virtual endoscopy system VIVENDI to perform virtual endoscopic inspections of the human lung. This virtual bronchoscopy system enables visualization of the tracheobronchial tree down to seventh generation. Furthermore, the modified virtual system visualizes hidden structures such as segmented vascular system or tumors. Materials and methods The segmentation is based on image data acquired by a multislice computed tomography scanner. SegoMeTex is used to segment the tracheobronchial tree by a hybrid system with minimal user action. Similarly, the complementary pulmonary arterial can be segmented, whereas additional structures such as tumors are marked manually. On this dataset, s subsequently, data structures of the inner surface for virtual endoscopy are generated. Finally, the dataset can be explored by a virtual bronchoscopy procedure using the VIVENDI system. Results The segmentation method was successfully tested on 22 patients. The hybrid segmentation system identified bronchi up to the sixth generation with a sensitivity of more than 58%, and a positive predictive value of more than 90%. After the segmentation, the datasets are explored interactively (>30 fps on a standard personal computer platform in real-time rendering) using the virtual endoscopy software. The exploration exposed a high-quality reconstruction, even of small structures throughout the dataset. Conclusion Virtual bronchoscopy in combining with a highly sensitive segmentation is a valuable tool for the localization and measurement of stenosis for resection planning.

Automated anatomical labeling of the bronchial branch and its application to the virtual bronchoscopy system.

This paper describes a method for the automated anatomical labeling of the bronchial branch extracted from a three-dimensional (3-D) chest X-ray CT image and its application to a virtual bronchoscopy system (VBS). Automated anatomical labeling is necessary for implementing an advanced computer-aided diagnosis system of 3-D medical images. This method performs the anatomical labeling of the bronchial branch using the knowledge base of the bronchial branch name. The knowledge base holds information on the bronchial branch as a set of rules for its anatomical labeling. A bronchus region is automatically extracted from a given 3-D CT image. A tree structure representing the essential structure of the extracted bronchus is recognized from the bronchus region. Anatomical labeling is performed by comparing this tree structure of the bronchus with the knowledge base. As an application, we implemented the function to automatically present the anatomical names of the branches that are shown in the currently rendered image in real time on the VBS. The result showed that the method could segment about 57% of the branches from CT images and extracted a tree structure of about 91% in branches in the segmented bronchus. The anatomical labeling method could assign the correct branch name to about 93% of the branches in the extracted tree structure. Anatomical names were appropriately displayed in the endoscopic view.

Virtual Bronchoscopy

Patients potentially suffer and are exposed to danger during invasive bronchoscopic diagnosis and surgery. In order to reduce this hazardous risk, we have developed an interactive virtual environment for the simulation of bronchoscopy (in short, called "virtual bronchoscopy"). Because of this state-of-the-art application, medical doctors can now obtain pre-operative information and perform pilot examinations in a virtual environment without any invasive or needless surgery. This 3D lung volume data of the patient is first acquired from CT and/or MRI scanning, without any pain being inflicted upon the patient. Then a vessel-tracking process is used to extract the patient's bronchial tree from the data. It is important to note that while manual tracking is tedious and labor-intensive, fully automatic tracking may not be as reliable in such a critical medical application. Thus a semi-automatic tracking technique called the Intelligent Path Tracker, which provides automation and sufficient user control during the tracking process, is most useful. This methodology is applied to a virtual bronchoscopy session, where doctors can use a 3D pen input device to navigate and visualize the bronchial tree of patients in a natural and interactive manner. To support an interactive frame rate, we also propose a new volume rendering acceleration technique, named IsoRegion Leaping. Through this technique visualization is further accelerated using a distributed rendering process based upon a TCP/IP network of low-cost PCs. Combining these approaches enables a 256x256x256 volumetric data representation of a human lung to be navigated and visualized at a frame rate of over 10 Hz in our virtual bronchoscopy system.