The Influence of Radiographic Phenotype and Smoking Status on Peripheral Blood Biomarker Patterns in Chronic Obstructive Pulmonary Disease

Background: Chronic obstructive pulmonary disease (COPD) is characterized by both airway remodeling and parenchymal destruction. The identification of unique biomarker patterns associated with airway dominant versus parenchymal dominant patterns would support the existence of unique phenotypes representing independent biologic processes. A cross-sectional study was performed to examine the association of serum biomarkers with radiographic airway and parenchymal phenotypes of COPD. Methodology/Principal Findings: Serum from 234 subjects enrolled in a CT screening cohort was analyzed for 33 cytokines and growth factors using a multiplex protein array. The association of serum markers with forced expiratory volume in one second percent predicted (FEV1%) and quantitative CT measurements of airway thickening and emphysema was assessed with and without stratification for current smoking status. Significant associations were found with several serum inflammatory proteins and measurements of FEV1%, airway thickening, and parenchymal emphysema independent of smoking status. The association of select analytes with airway thickening and emphysema was independent of FEV1%. Furthermore, the relationship between other inflammatory markers and measurements of physiologic obstruction or airway thickening was dependent on current smoking status. Conclusions/Significance: Airway and parenchymal phenotypes of COPD are associated with unique systemic serum biomarker profiles. Serum biomarker patterns may provide a more precise classification of the COPD syndrome, provide insights into disease pathogenesis and identify targets for novel patient-specific biological therapies. © 2009 Bon et al

Image Texture Characterization Using the Discrete Orthonormal S-Transform

We present a new efficient approach for characterizing image texture based on a recently published discrete, orthonormal space-frequency transform known as the DOST. We develop a frequency-domain implementation of the DOST in two dimensions for the case of dyadic frequency sampling. Then, we describe a rapid and efficient approach to obtain local spatial frequency information for an image and show that this information can be used to characterize the horizontal and vertical frequency patterns in synthetic images. Finally, we demonstrate that DOST components can be combined to obtain a rotationally invariant set of texture features that can accurately classify a series of texture patterns. The DOST provides the computational efficiency and multi-scale information of wavelet transforms, while providing texture features in terms of Fourier frequencies. It outperforms leading wavelet-based texture analysis methods

Treatment Planning and Volumetric Response Assessment for Yttrium-90 Radioembolization: Semiautomated Determination of Liver Volume and Volume of Tumor Necrosis in Patients with Hepatic Malignancy

PurposeThe primary purpose of this study was to demonstrate intraobserver/interobserver reproducibility for novel semiautomated measurements of hepatic volume used for Yttrium-90 dose calculations as well as whole-liver and necrotic-liver (hypodense/nonenhancing) tumor volume after radioembolization. The secondary aim was to provide initial comparisons of tumor volumetric measurements with linear measurements, as defined by Response Evaluation Criteria in Solid Tumors criteria, and survival outcomes.MethodsBetween 2006 and 2009, 23 consecutive radioembolization procedures were performed for 14 cases of hepatocellular carcinoma and 9 cases of hepatic metastases. Baseline and follow-up computed tomography obtained 1 month after treatment were retrospectively analyzed. Three observers measured liver, whole-tumor, and tumor-necrosis volumes twice using semiautomated software.ResultsGood intraobserver/interobserver reproducibility was demonstrated (intraclass correlation [ICC] > 0.9) for tumor and liver volumes. Semiautomated measurements of liver volumes were statistically similar to those obtained with manual tracing (ICC = 0.868), but they required significantly less time to perform (p < 0.0001, ICC = 0.088). There was a positive association between change in linear tumor measurements and whole-tumor volume (p < 0.0001). However, linear measurements did not correlate with volume of necrosis (p > 0.05). Dose, change in tumor diameters, tumor volume, and necrotic volume did not correlate with survival (p > 0.05 in all instances). However, Kaplan-Meier curves suggest that a >10% increase in necrotic volume correlated with survival (p = 0.0472).ConclusionSemiautomated volumetric analysis of liver, whole-tumor, and tumor-necrosis volume can be performed with good intraobserver/interobserver reproducibility. In this small retrospective study, measurements of tumor necrosis were suggested to correlate with survival

Prediction of Glioblastoma Multiform Response to Bevacizumab Treatment Using Multi-Parametric MRI

Glioblastoma multiform (GBM) is a highly malignant brain tumor. Bevacizumab is a recent therapy for stopping tumor growth and even shrinking tumor through inhibition of vascular development (angiogenesis). This paper presents a non-invasive approach based on image analysis of multi-parametric magnetic resonance images (MRI) to predict response of GBM to this treatment. The resulting prediction system has potential to be used by physicians to optimize treatment plans of the GBM patients. The proposed method applies signal decomposition and histogram analysis methods to extract statistical features from Gd-enhanced regions of tumor that quantify its microstructural characteristics. MRI studies of 12 patients at multiple time points before and up to four months after treatment are used in this work. Changes in the Gd-enhancement as well as necrosis and edema after treatment are used to evaluate the response. Leave-one-out cross validation method is applied to evaluate prediction quality of the models. Predictive models developed in this work have large regression coefficients (maximum R2 = 0.95) indicating their capability to predict response to therapy

Success rates for computed tomography-guided musculoskeletal biopsies performed using a low-dose technique

Objective To evaluate the success rate of a low-dose (50 % mAs reduction) computed tomography (CT) biopsy technique. This protocol was adopted based on other successful reduced-CT radiation dose protocols in our department, which were implemented in conjunction with quality improvement projects. Materials and methods The technique included a scout view and initial localizing scan with standard dose. Additional scans obtained for further guidance or needle adjustment were acquired by reducing the tube current-time product (mAs) by 50 %. The radiology billing data were searched for CT-guided musculoskeletal procedures performed over a period of 8 months following the initial implementation of the protocol. These were reviewed for the type of procedure and compliance with the implemented protocol. The compliant CT-guided biopsy cases were then retrospectively reviewed for patient demographics, tumor pathology, and lesion size. Pathology results were compared to the ultimate diagnoses and were categorized as diagnostic, accurate, or successful. Results Of 92 CT-guided procedures performed during this period, two were excluded as they were not biopsies (one joint injection and one drainage), 19 were excluded due to non-compliance (operators neglected to follow the protocol), and four were excluded due to lack of available follow-up in our electronic medical records. A total of 67 compliant biopsies were performed in 63 patients (two had two biopsies, and one had three biopsies). There were 32 males and 31 females with an average age of 50 (range, 15-84 years). Of the 67 biopsies, five were non-diagnostic and inaccurate and thus unsuccessful (7 %); five were diagnostic but inaccurate and thus unsuccessful (7 %); 57 were diagnostic and accurate thus successful (85 %). These results were comparable with results published in the radiology literature. Conclusions The success rate of CT-guided biopsies using a low-dose protocol is comparable to published rates for conventional dose biopsies. The implemented low-dose protocol did not change the success rate of CT-guided musculoskeletal biopsies. © 2014 ISS

Variability in CT lung-nodule quantification: Effects of dose reduction and reconstruction methods on density and texture based features.

PurposeTo investigate the effects of dose level and reconstruction method on density and texture based features computed from CT lung nodules.MethodsThis study had two major components. In the first component, a uniform water phantom was scanned at three dose levels and images were reconstructed using four conventional filtered backprojection (FBP) and four iterative reconstruction (IR) methods for a total of 24 different combinations of acquisition and reconstruction conditions. In the second component, raw projection (sinogram) data were obtained for 33 lung nodules from patients scanned as a part of their clinical practice, where low dose acquisitions were simulated by adding noise to sinograms acquired at clinical dose levels (a total of four dose levels) and reconstructed using one FBP kernel and two IR kernels for a total of 12 conditions. For the water phantom, spherical regions of interest (ROIs) were created at multiple locations within the water phantom on one reference image obtained at a reference condition. For the lung nodule cases, the ROI of each nodule was contoured semiautomatically (with manual editing) from images obtained at a reference condition. All ROIs were applied to their corresponding images reconstructed at different conditions. For 17 of the nodule cases, repeat contours were performed to assess repeatability. Histogram (eight features) and gray level co-occurrence matrix (GLCM) based texture features (34 features) were computed for all ROIs. For the lung nodule cases, the reference condition was selected to be 100% of clinical dose with FBP reconstruction using the B45f kernel; feature values calculated from other conditions were compared to this reference condition. A measure was introduced, which the authors refer to as Q, to assess the stability of features across different conditions, which is defined as the ratio of reproducibility (across conditions) to repeatability (across repeat contours) of each feature.ResultsThe water phantom results demonstrated substantial variability among feature values calculated across conditions, with the exception of histogram mean. Features calculated from lung nodules demonstrated similar results with histogram mean as the most robust feature (Q ≤ 1), having a mean and standard deviation Q of 0.37 and 0.22, respectively. Surprisingly, histogram standard deviation and variance features were also quite robust. Some GLCM features were also quite robust across conditions, namely, diff. variance, sum variance, sum average, variance, and mean. Except for histogram mean, all features have a Q of larger than one in at least one of the 3% dose level conditions.ConclusionsAs expected, the histogram mean is the most robust feature in their study. The effects of acquisition and reconstruction conditions on GLCM features vary widely, though trending toward features involving summation of product between intensities and probabilities being more robust, barring a few exceptions. Overall, care should be taken into account for variation in density and texture features if a variety of dose and reconstruction conditions are used for the quantification of lung nodules in CT, otherwise changes in quantification results may be more reflective of changes due to acquisition and reconstruction conditions than in the nodule itself