Anti-CTLA-4 Antibody Might Be Effective Against Non-small Cell Lung Cancer With Large Size Tumor.

Background/aim: Immunotherapy using immune checkpoint inhibitors (ICIs) has revolutionized the treatment of advanced non-small cell lung cancer (NSCLC). Although several ICI options are available, the treatment regimen for NSCLC with large size tumors (large NSCLC) is controversial and the efficacy of anti-CTLA-4 antibody is unclear. This study thus investigated potential biomarkers for CTLA-4 blockade.

SR-CycleGAN: super-resolution of clinical CT to micro-CT level with multi-modality super-resolution loss.

We propose a super-resolution (SR) method, named SR-CycleGAN, for SR of clinical computed tomography (CT) images to the micro-focus x-ray CT CT ( ) level. Due to the resolution limitations of clinical CT (about ), it is challenging to obtain enough pathological information. On the other hand, scanning allows the imaging of lung specimens with significantly higher resolution (about or higher), which allows us to obtain and analyze detailed anatomical information.

Depth-based branching level estimation for bronchoscopic navigation.

Purpose: Bronchoscopists rely on navigation systems during bronchoscopy to reduce the risk of getting lost in the complex bronchial tree-like structure and the homogeneous bronchus lumens. We propose a patient-specific branching level estimation method for bronchoscopic navigation because it is vital to identify the branches being examined in the bronchus tree during examination.

Methods: We estimate the branching level by integrating the changes in the number of bronchial orifices and the camera motions among the frames.

Unsupervised colonoscopic depth estimation by domain translations with a Lambertian-reflection keeping auxiliary task.

Purpose: A three-dimensional (3D) structure extraction technique viewed from a two-dimensional image is essential for the development of a computer-aided diagnosis (CAD) system for colonoscopy. However, a straightforward application of existing depth-estimation methods to colonoscopic images is impossible or inappropriate due to several limitations of colonoscopes. In particular, the absence of ground-truth depth for colonoscopic images hinders the application of supervised machine learning methods.

A visual SLAM-based bronchoscope tracking scheme for bronchoscopic navigation.

Purpose: Due to the complex anatomical structure of bronchi and the resembling inner surfaces of airway lumina, bronchoscopic examinations require additional 3D navigational information to assist the physicians. A bronchoscopic navigation system provides the position of the endoscope in CT images with augmented anatomical information. To overcome the shortcomings of previous navigation systems, we propose using a technique known as visual simultaneous localization and mapping (SLAM) to improve bronchoscope tracking in navigation systems.

Realistic endoscopic image generation method using virtual-to-real image-domain translation.

A realistic image generation method for visualisation in endoscopic simulation systems is proposed in this study. Endoscopic diagnosis and treatment are performed in many hospitals. To reduce complications related to endoscope insertions, endoscopic simulation systems are used for training or rehearsal of endoscope insertions.

Automated mediastinal lymph node detection from CT volumes based on intensity targeted radial structure tensor analysis.

This paper presents a local intensity structure analysis based on an intensity targeted radial structure tensor (ITRST) and the blob-like structure enhancement filter based on it (ITRST filter) for the mediastinal lymph node detection algorithm from chest computed tomography (CT) volumes. Although the filter based on radial structure tensor analysis (RST filter) based on conventional RST analysis can be utilized to detect lymph nodes, some lymph nodes adjacent to regions with extremely high or low intensities cannot be detected. Therefore, we propose the ITRST filter, which integrates the prior knowledge on detection target intensity range into the RST filter.

Assessment of COPD severity by combining pulmonary function tests and chest CT images.

Purpose: Chronic obstructive pulmonary disease (COPD) is characterized by airflow limitations. Physicians frequently assess the stage using pulmonary function tests and chest CT images. This paper describes a novel method to assess COPD severity by combining measurements of pulmonary function tests (PFT) and the results of chest CT image analysis.

Automatic segmentation of pulmonary blood vessels and nodules based on local intensity structure analysis and surface propagation in 3D chest CT images.

Purpose: Pulmonary nodules may indicate the early stage of lung cancer, and the progress of lung cancer causes associated changes in the shape and number of pulmonary blood vessels. The automatic segmentation of pulmonary nodules and blood vessels is desirable for chest computer-aided diagnosis (CAD) systems. Since pulmonary nodules and blood vessels are often attached to each other, conventional nodule detection methods usually produce many false positives (FPs) in the blood vessel regions, and blood vessel segmentation methods may incorrectly segment the nodules that are attached to the blood vessels.

Development and comparison of new hybrid motion tracking for bronchoscopic navigation.

This paper presents a new hybrid camera motion tracking method for bronchoscopic navigation combining SIFT, epipolar geometry analysis, Kalman filtering, and image registration. In a thorough evaluation, we compare it to state-of-the-art tracking methods. Our hybrid algorithm for predicting bronchoscope motion uses SIFT features and epipolar constraints to obtain an estimate for inter-frame pose displacements and Kalman filtering to find an estimate for the magnitude of the motion.

Selective image similarity measure for bronchoscope tracking based on image registration.

We propose a selective method of measurement for computing image similarities based on characteristic structure extraction and demonstrate its application to flexible endoscope navigation, in particular to a bronchoscope navigation system. Camera motion tracking is a fundamental function required for image-guided treatment or therapy systems. In recent years, an ultra-tiny electromagnetic sensor commercially became available, and many image-guided treatment or therapy systems use this sensor for tracking the camera position and orientation.

Digital bowel cleansing free colonic polyp detection method for fecal tagging CT colonography.

Rationale And Objectives: Fecal tagging computed tomographic colonography (ftCTC) reduces the discomfort and the inconvenience of patients associated with bowel cleansing procedures before CT scanning. In conventional colonic polyp detection techniques for ftCTC, a digital bowel cleansing (DBC) technique is applied to detect polyps in tagged fecal materials (TFM). However, DBC removes the surface of soft tissues and hampers polyp detection.

Automated anatomical labeling of bronchial branches extracted from CT datasets based on machine learning and combination optimization and its application to bronchoscope guidance.

This paper presents a method for the automated anatomical labeling of bronchial branches extracted from 3D CT images based on machine learning and combination optimization. We also show applications of anatomical labeling on a bronchoscopy guidance system. This paper performs automated labeling by using machine learning and combination optimization.

Improvement of accuracy of marker-free bronchoscope tracking using electromagnetic tracker based on bronchial branch information.

This paper presents a study of tracking accuracy improvement of marker-free bronchoscope tracking using an electromagnetic tracking system. Bronchoscope tracking is an important function in a bronchoscope navigation system that assists a physician during bronchoscopic examination. Several research groups have presented a method for bronchoscope tracking using an ultra-tiny electromagnetic tracker (UEMT) that can be inserted into the working channel of a bronchoscope.

Bronchoscope tracking without fiducial markers using ultra-tiny electromagnetic tracking system and its evaluation in different environments.

This paper presents a method for bronchoscope tracking without any fiducial markers using an ultra-tiny electromagnetic tracker (UEMT) for a bronchoscopy guidance system. The proposed method calculates the transformation matrix, which shows the relationship between the coordinates systems of the pre-operative CT images and the UEMT, by registering bronchial branches segmented from CT images and points measured by the UEMT attached at the tip of a bronchoscope. We dynamically compute the transformation matrix for every pre-defined number of measurements.

Bronchoscope tracking based on image registration using multiple initial starting points estimated by motion prediction.

This paper presents a method for tracking a bronchoscope based on motion prediction and image registration from multiple initial starting points as a function of a bronchoscope navigation system. We try to improve performance of bronchoscope tracking based on image registration using multiple initial guesses estimated using motion prediction. This method basically tracks a bronchoscopic camera by image registration between real bronchoscopic images and virtual ones derived from CT images taken prior to the bronchoscopic examinations.

A method for bronchoscope tracking by combining a position sensor and image registration.

This paper describes a method for tracking a bronchoscope by combining a position sensor and image registration. A bronchoscopy guidance system is a tool for providing real-time navigation information acquired from pre-operative CT images to a physician during a bronchoscopic examination. In this system, one of the fundamental functions is tracking a bronchoscope's camera motion.

Solitary capillary hemangioma of the lung: report of 2 resected cases detected by high-resolution CT.

We report 2 cases of capillary hemangioma, each presenting as a solitary nodule in the peripheral lung. Both of the patients were asymptomatic with a small solitary nodule that had revealed by computed tomography. In both cases, the nodule was resected surgically under a clinical diagnosis of early lung cancer.

Automated nomenclature of bronchial branches extracted from CT images and its application to biopsy path planning in virtual bronchoscopy.

We propose a novel anatomical labeling algorithm for bronchial branches extracted from CT images. This method utilizes multiple branching models for anatomical labeling. In the actual labeling process, the method selects the best candidate models at each branching point.

Hybrid bronchoscope tracking using a magnetic tracking sensor and image registration.

In this paper, we propose a hybrid method for tracking a bronchoscope that uses a combination of magnetic sensor tracking and image registration. The position of a magnetic sensor placed in the working channel of the bronchoscope is provided by a magnetic tracking system. Because of respiratory motion, the magnetic sensor provides only the approximate position and orientation of the bronchoscope in the coordinate system of a CT image acquired before the examination.

Phase I study of carboplatin, irinotecan and docetaxel on a divided schedule with recombinant human granulocyte colony stimulating factor support in patients with stage IIIB or IV non-small cell lung cancer.

A phase I study was conducted to determine dose-limiting toxicity (DLT) and maximum tolerated dose (MTD) of carboplatin combined with irinotecan and docetaxel on a divided schedule with recombinant human granulocyte colony stimulating factor (rhG-CSF) support in patients with stage IIIB or IV non-small cell lung cancer. Carboplatin was given at the dose of AUC5 on day 1. Irinotecan and docetaxel on days 1 and 8 were administered at a starting dose of 40 and 30 mg/m2 as level 1.