Correction to: Toward clinically usable CAD for lung cancer screening with computed tomography.

The original version of this article, published on 24 July 2014, unfortunately contained a mistake. In section "Discussion," a sentence was worded incorrectly.

Using Transitional Changes on High-Resolution Computed Tomography to Monitor the Impact of Cyclophosphamide or Mycophenolate Mofetil on Systemic Sclerosis-Related Interstitial Lung Disease.

Objective: To examine changes in the extent of specific patterns of interstitial lung disease (ILD) as they transition from one pattern to another in response to immunosuppressive therapy in systemic sclerosis-related ILD (SSc-ILD).

Methods: We evaluated changes in the quantitative extent of specific lung patterns of ILD using volumetric high-resolution computed tomography (HRCT) scans obtained at baseline and after 2 years of therapy in patients treated with either cyclophosphamide (CYC) for 1 year or mycophenolate mofetil (MMF) for 2 years in Scleroderma Lung Study II. ILD patterns included lung fibrosis, ground glass, honeycombing, and normal lung.

Building a high-resolution T2-weighted MR-based probabilistic model of tumor occurrence in the prostate.

Purpose: We present a method for generating a T2 MR-based probabilistic model of tumor occurrence in the prostate to guide the selection of anatomical sites for targeted biopsies and serve as a diagnostic tool to aid radiological evaluation of prostate cancer.

Materials And Methods: In our study, the prostate and any radiological findings within were segmented retrospectively on 3D T2-weighted MR images of 266 subjects who underwent radical prostatectomy. Subsequent histopathological analysis determined both the ground truth and the Gleason grade of the tumors.

Clear Cell Renal Cell Carcinoma: Identifying the Loss of the Y Chromosome on Multiphasic MDCT.

Objective: The objective of our study was to investigate whether multiphasic MDCT enhancement can help identify clear cell renal cell carcinomas (RCCs) with the loss of the Y chromosome.

Materials And Methods: We derived a cohort of 43 clear cell RCCs in men who underwent preoperative four-phase renal mass MDCT from October 2000 to August 2013. Each lesion was segmented in its entirety on axial images.

Type 1 papillary renal cell carcinoma: differentiation from Type 2 papillary RCC on multiphasic MDCT.

Purpose: To investigate whether multiphasic MDCT enhancement can help differentiate type 1 papillary renal cell carcinoma (RCC) from type 2 papillary RCC.

Methods: With IRB approval for this HIPAA-compliant retrospective study, we derived a cohort of 36 type 1 papillary RCCs and 33 type 2 papillary RCCs with preoperative multiphasic MDCT with up to four phases (unenhanced, corticomedullary, nephrographic, and excretory) from 2000 to 2013. Following segmentation, a computer-assisted detection (CAD) algorithm selected a 0.

Radiomics of Lung Nodules: A Multi-Institutional Study of Robustness and Agreement of Quantitative Imaging Features.

Radiomics is to provide quantitative descriptors of normal and abnormal tissues during classification and prediction tasks in radiology and oncology. Quantitative Imaging Network members are developing radiomic "feature" sets to characterize tumors, in general, the size, shape, texture, intensity, margin, and other aspects of the imaging features of nodules and lesions. Efforts are ongoing for developing an ontology to describe radiomic features for lung nodules, with the main classes consisting of size, local and global shape descriptors, margin, intensity, and texture-based features, which are based on wavelets, Laplacian of Gaussians, Law's features, gray-level co-occurrence matrices, and run-length features.

Performance of Relative Enhancement on Multiphasic MRI for the Differentiation of Clear Cell Renal Cell Carcinoma (RCC) From Papillary and Chromophobe RCC Subtypes and Oncocytoma.

Objective: The objective of our study was to investigate the performance of relative enhancement on multiphasic MRI to differentiate clear cell renal cell carcinoma (RCC) from other RCC subtypes (papillary and chromophobe) and oncocytoma.

Materials And Methods: For this study, we derived a cohort of 34 clear cell RCCs, nine oncocytomas, 12 papillary RCCs, and 10 chromophobe RCCs with a preoperative multiphasic dynamic contrast-enhanced MRI study with up to four phases (i.e.

The effect of radiation dose reduction on computer-aided detection (CAD) performance in a low-dose lung cancer screening population.

Purpose: Lung cancer screening with low-dose CT has recently been approved for reimbursement, heralding the arrival of such screening services worldwide. Computer-aided detection (CAD) tools offer the potential to assist radiologists in detecting nodules in these screening exams. In lung screening, as in all CT exams, there is interest in further reducing radiation dose.

Clear cell renal cell carcinoma: identifying the gain of chromosome 12 on multiphasic MDCT.

Purpose: To determine whether multiphasic MDCT enhancement can help identify the gain of chromosome 12 in clear cell renal cell carcinomas (RCCs).

Methods: With IRB approval for this HIPAA-compliant case control study, we derived a cohort of 65 clear cell RCCs with preoperative four-phase renal mass MDCT from October 2000 to August 2013. Each lesion was segmented in its entirety on axial images in all phases.

A Novel Quantitative Computed Tomographic Analysis Suggests How Sirolimus Stabilizes Progressive Air Trapping in Lymphangioleiomyomatosis.

Rationale: The Multicenter International Lymphangioleiomyomatosis Efficacy and Safety of Sirolimus (MILES) trial demonstrated that sirolimus stabilized lung function and improved measures of functional performance and quality of life in patients with lymphangioleiomyomatosis. The physiologic mechanisms of these beneficial actions of sirolimus are incompletely understood.

Objectives: To prospectively determine the longitudinal computed tomographic lung imaging correlates of lung function change in MILES patients treated with placebo or sirolimus.

Robustness-Driven Feature Selection in Classification of Fibrotic Interstitial Lung Disease Patterns in Computed Tomography Using 3D Texture Features.

Lack of classifier robustness is a barrier to widespread adoption of computer-aided diagnosis systems for computed tomography (CT). We propose a novel Robustness-Driven Feature Selection (RDFS) algorithm that preferentially selects features robust to variations in CT technical factors. We evaluated RDFS in CT classification of fibrotic interstitial lung disease using 3D texture features.

Geodesic Atlas-Based Labeling of Anatomical Trees: Application and Evaluation on Airways Extracted From CT.

We present a fast and robust atlas-based algorithm for labeling airway trees, using geodesic distances in a geometric tree-space. Possible branch label configurations for an unlabeled airway tree are evaluated using distances to a training set of labeled airway trees. In tree-space, airway tree topology and geometry change continuously, giving a natural automatic handling of anatomical differences and noise.

Bone tumor segmentation on bone scans using context information and random forests.

Bone tumor segmentation on bone scans has recently been adopted as a basis for objective tumor assessment in several phase II and III clinical drug trials. Interpretation can be difficult due to the highly sensitive but non-specific nature of bone tumor appearance on bone scans. In this paper we present a machine learning approach to segmenting tumors on bone scans, using intensity and context features aimed at addressing areas prone to false positives.

Toward clinically usable CAD for lung cancer screening with computed tomography.

Objectives: The purpose of this study was to define clinically appropriate, computer-aided lung nodule detection (CAD) requirements and protocols based on recent screening trials. In the following paper, we describe a CAD evaluation methodology based on a publically available, annotated computed tomography (CT) image data set, and demonstrate the evaluation of a new CAD system with the functionality and performance required for adoption in clinical practice.

Methods: A new automated lung nodule detection and measurement system was developed that incorporates intensity thresholding, a Euclidean Distance Transformation, and segmentation based on watersheds.

Optimal surface segmentation using flow lines to quantify airway abnormalities in chronic obstructive pulmonary disease.

This paper introduces a graph construction method for multi-dimensional and multi-surface segmentation problems. Such problems can be solved by searching for the optimal separating surfaces given the space of graph columns defined by an initial coarse surface. Conventional straight graph columns are not well suited for surfaces with high curvature, we therefore propose to derive columns from properly generated, non-intersecting flow lines.

A hierarchical scheme for geodesic anatomical labeling of airway trees.

We present a fast and robust supervised algorithm for labeling anatomical airway trees, based on geodesic distances in a geometric tree-space. Possible branch label configurations for a given tree are evaluated based on distances to a training set of labeled trees. In tree-space, the tree topology and geometry change continuously, giving a natural way to automatically handle anatomical differences and noise.

Toward a theory of statistical tree-shape analysis.

To develop statistical methods for shapes with a tree-structure, we construct a shape space framework for tree-shapes and study metrics on the shape space. This shape space has singularities which correspond to topological transitions in the represented trees. We study two closely related metrics on the shape space, TED and QED.

Extraction of airways from CT (EXACT'09).

This paper describes a framework for establishing a reference airway tree segmentation, which was used to quantitatively evaluate fifteen different airway tree extraction algorithms in a standardized manner. Because of the sheer difficulty involved in manually constructing a complete reference standard from scratch, we propose to construct the reference using results from all algorithms that are to be evaluated. We start by subdividing each segmented airway tree into its individual branch segments.

Factors influencing the decline in lung density in a Danish lung cancer screening cohort.

Lung cancer screening trials provide an opportunity to study the natural history of emphysema by using computed tomography (CT) lung density as a surrogate parameter. In the Danish Lung Cancer Screening Trial, 2,052 participants were included. At screening rounds, smoking habits were recorded and spirometry was performed.

Toward automatic regional analysis of pulmonary function using inspiration and expiration thoracic CT.

Purpose: To analyze pulmonary function using a fully automatic technique which processes pairs of thoracic CT scans acquired at breath-hold inspiration and expiration, respectively. The following research objectives are identified to: (a) describe and systematically analyze the processing pipeline and its results; (b) verify that the quantitative, regional ventilation measurements acquired through CT are meaningful for pulmonary function analysis; (c) identify the most effective of the calculated measurements in predicting pulmonary function; and (d) demonstrate the potential of the system to deliver clinically important information not available through conventional spirometry.

Methods: A pipeline of automatic segmentation and registration techniques is presented and demonstrated on a database of 216 subjects well distributed over the various stages of COPD (chronic obstructive pulmonary disorder).

Mass preserving image registration for lung CT.

This paper presents a mass preserving image registration algorithm for lung CT images. To account for the local change in lung tissue intensity during the breathing cycle, a tissue appearance model based on the principle of preservation of total lung mass is proposed. This model is incorporated into a standard image registration framework with a composition of a global affine and several free-form B-Spline transformations with increasing grid resolution.

Texture-based analysis of COPD: a data-driven approach.

This study presents a fully automatic, data-driven approach for texture-based quantitative analysis of chronic obstructive pulmonary disease (COPD) in pulmonary computed tomography (CT) images. The approach uses supervised learning where the class labels are, in contrast to previous work, based on measured lung function instead of on manually annotated regions of interest (ROIs). A quantitative measure of COPD is obtained by fusing COPD probabilities computed in ROIs within the lung fields where the individual ROI probabilities are computed using a k nearest neighbor (kNN ) classifier.

Dissimilarity-based classification of anatomical tree structures.

A novel method for classification of abnormality in anatomical tree structures is presented. A tree is classified based on direct comparisons with other trees in a dissimilarity-based classification scheme. The pair-wise dissimilarity measure between two trees is based on a linear assignment between the branch feature vectors representing those trees.

Optimal graph based segmentation using flow lines with application to airway wall segmentation.

This paper introduces a novel optimal graph construction method that is applicable to multi-dimensional, multi-surface segmentation problems. Such problems are often solved by refining an initial coarse surface within the space given by graph columns. Conventional columns are not well suited for surfaces with high curvature or complex shapes but the proposed columns, based on properly generated flow lines, which are non-intersecting, guarantee solutions that do not self-intersect and are better able to handle such surfaces.

Short-term effect of changes in smoking behaviour on emphysema quantification by CT.

Background: The effect of smoking cessation and smoking relapse on lung density was studied using low-dose CT.

Methods: Spiral, multidetector, low-dose CT was performed on 726 current and former smokers (>20 pack-years) recruited from a cancer screening trial. Lung density was quantified by calculating the 15th percentile density (PD15), which was adjusted to predicted total lung capacity.