Region-based Analysis Research Articles

1178TiP - Prospective Evaluation of Planar Bone Scintigraphy, SPECT/CT, 18F NAF PET/CT and Whole Body 1.5T MRI for Detection of Bone Metastases in High Risk Breast and Prostate Cancer Patients

ABSTRACT Purpose The aim of the study was to compare the diagnostic accuracy of 99mTc methylene-diphosphonate planar bone scintigraphy (99mTc-MDP BS), 99mTc methylene-diphosphonate single photon emission tomography/computed tomography (99mTc-MDP SPECT/CT), 18F NaF positron emission tomography/computed tomography (PET/CT) and whole body 1.5 Tesla magnetic resonance imaging (1.5T MRI) for the detection of bone metastases in high risk breast and prostate cancer patients. Materials and methods Twenty breast cancer patients and eight prostate cancer patients at high risk of bone metastases prospectively underwent 99mTc-MDP BS, 99mTc-MDP SPECT/CT, 18F NaF PET/CT and whole body 1.5T MRI using spine and surface coils. Four independent reviewers interpreted each individual modality without the knowledge of other imaging findings. The final metastatic status was based on the consensus reading of all imaging modalities. The findings were compared on patient and region basis. In the region based analysis, the skeleton was divided into five regions. Results Based on the consensus reading, 13 (46%) patients and 42 (30%) regions had presence of bone metastases while 15 patients and 98 regions were free of bone metastases. 99mTc-MDP BS was false negative in four patients. In the patient/region based analysis, the sensitivity for 99mTc-MDP BS, 99mTc-MDP SPECT/CT, 18F NaF PET/CT and whole body 1.5T MRI was 69%/44%, 77%/76%, 92%/90% and 77%/71%, respectively, while the accuracy was 86%/82%, 89%/92%, 96%/97% and 86%/91%, respectively. Conclusions 99mTc-MDP SPECT/CT, 18F NaF PET/CT and whole body MRI including diffusion weighted imaging demonstrated higher sensitivity and accuracy in detection of bone metastasis compared to planar bone scintigraphy. Observed difference between imaging modalities might potentially affect the patient management. Clinical relevance statement: 99mTc-MDP SPECT/CT, 18F NaF PET/CT and whole body MRI including diffusion weighted imaging showed higher sensitivity for detecting bone metastases in high risk breast and prostate cancer patients to planar bone scintigraphy. Disclosure All authors have declared no conflicts of interest.

Assessment of anemia during CT pulmonary angiography

ObjectivesAnemia is associated with increased mortality in patients with acute symptomatic pulmonary embolism (PE). The purpose of this study was to evaluate the feasibility of Hounsfield unit (HU) measurements on the single unenhanced trigger slice of pulmonary CT angiography scans for diagnosis of anemia. Material and Methods150 consecutive patients (median age 64±16 years) with suspected PE underwent pulmonary CT angiography. Two radiologists, blinded to laboratory results, performed HU measurements in the single unenhanced trigger scan independently by region-based analysis (ROI). HU values from ascending and descending aorta and the calculated mean of both were correlated with serum hemoglobin levels. Inter- and intraobserver variability was determined for HU measurements, and ROC analysis was performed for diagnosis of anemia. Calculated linear models were used to assess formulas for estimation of hemoglobin levels from HU measurements. ResultsHU measurements revealed high intra- and interrater reliability (ICC>0.981 and ICC>0.965, respectively). Calculated mean HU values showed a strong correlation with serum hemoglobin levels (r=0.734), which allowed generation of different formulas for calculation of hemoglobin levels from HU measurements. ROC analyses confirmed a high sensitivity (80.4 for men; 91.3 for women) and specificity (84.0 for men; 84.9 for women) for diagnosing anemia. ConclusionDiagnosis of anemia and quantification of hemoglobin levels upon a single unenhanced trigger scan of pulmonary CT angiography is feasible. We suggest disclosing the anemic state in the radiological report, independent of the presence of PE, since anemia carries increased risks of morbidity and mortality.

A multi-center study: Intra-scan and inter-scan variability of diffusion spectrum imaging

The objective of this study was to investigate whether it is possible to pool together diffusion spectrum imaging data from four different scanners, located at three different sites. Two of the scanners had identical configuration whereas two did not. To measure the variability, we extracted three scalar maps (ADC, FA and GFA) from the DSI and utilized a region and a tract-based analysis. Additionally, a phantom study was performed to rule out some potential factors arising from the scanner performance in case some systematic bias occurred in the subject study. This work was split into three experiments: intra-scanner reproducibility, reproducibility with twin-scanner settings and reproducibility with other configurations. Overall for the intra-scanner and twin-scanner experiments, the region-based analysis coefficient of variation (CV) was in a range of 1%-4.2% and below 3% for almost every bundle for the tract-based analysis. The uncinate fasciculus showed the worst reproducibility, especially for FA and GFA values (CV 3.7-6%). For the GFA and FA maps, an ICC value of 0.7 and above is observed in almost all the regions/tracts. Looking at the last experiment, it was found that there is a very high similarity of the outcomes from the two scanners with identical setting. However, this was not the case for the two other imagers. Given the fact that the overall variation in our study is low for the imagers with identical settings, our findings support the feasibility of cross-site pooling of DSI data from identical scanners.

SNPnexus: a web server for functional annotation of novel and publicly known genetic variants (2012 update)

Broader functional annotation of single nucleotide variations is a valuable mean for prioritizing targets in further disease studies and large-scale genotyping projects. We originally developed SNPnexus to assess the potential significance of known and novel SNPs on the major transcriptome, proteome, regulatory and structural variation models in order to identify the phenotypically important variants. Being committed to providing continuous support to the scientific community, we have substantially improved SNPnexus over time by incorporating a broader range of variations such as insertions/deletions, block substitutions, IUPAC codes submission and region-based analysis, expanding the query size limit, and most importantly including additional categories for the assessment of functional impact. SNPnexus provides a comprehensive set of annotations for genomic variation data by characterizing related functional consequences at the transcriptome/proteome levels of seven major annotation systems with in-depth analysis of potential deleterious effects, inferring physical and cytogenetic mapping, reporting information on HapMap genotype/allele data, finding overlaps with potential regulatory elements, structural variations and conserved elements, and retrieving links with previously reported genetic disease studies. SNPnexus has a user-friendly web interface with an improved query structure, enhanced functional annotation categories and flexible output presentation making it practically useful for biologists. SNPnexus is freely available at http://www.snp-nexus.org.

Linking white matter integrity loss to associated cortical regions using structural connectivity information in Alzheimer's disease and fronto-temporal dementia: The Loss in Connectivity (LoCo) score

It is well known that gray matter changes occur in neurodegenerative diseases like Alzheimer's (AD) and fronto-temporal dementia (FTD), and several studies have investigated their respective patterns of atrophy progression. Recent work, however, has revealed that diffusion MRI that is able to detect white matter integrity changes may be an earlier or more sensitive biomarker in both diseases. However, studies that examine white matter changes only are limited in that they do not provide the functional specificity of GM region-based analysis. In this study, we develop a new metric called the Loss in Connectivity (LoCo) score that gives the amount of structural network disruption incurred by a gray matter region for a particular pattern of white matter integrity loss. Leveraging the relative strengths of WM and GM markers, this metric links areas of WM integrity loss to their connected GM regions as a first step in understanding their functional implications. The LoCo score is calculated for three groups: 18AD, 18 FTD, and 19 age-matched normal controls. We show significant correlations of the LoCo with the respective atrophy patterns in AD (R=0.51, p=2.2 × 10(-9)) and FTD (R=0.49, p=2.5 × 10(-8)) for a standard 116 region gray matter atlas. In addition, we demonstrate that the LoCo outperforms a measure of gray matter atrophy when classifying individuals into AD, FTD, and normal groups.

Diagnostic Value of Software-Based Image Fusion of Computed Tomography and F18-FDG PET Scans in Patients with Malignant Lymphoma

Aim. The purpose of this study was to evaluate the accuracy of 2-deoxy-2-[fluorine-18]fluoro-D-glucose (FDG) positron emission tomography (PET), computed tomography (CT), and software-based image fusion of both modalities in the imaging of non-Hodgkin's lymphoma (NHL) and Hodgkin's disease (HD). Methods. 77 patients with NHL (n = 58) or HD (n = 19) underwent a FDG PET scan, a contrast-enhanced CT, and a subsequent digital image fusion during initial staging or followup. 109 examinations of each modality were evaluated and compared to each other. Conventional staging procedures, other imaging techniques, laboratory screening, and follow-up data constituted the reference standard for comparison with image fusion. Sensitivity and specificity were calculated for CT and PET separately. Results. Sensitivity and specificity for detecting malignant lymphoma were 90% and 76% for CT and 94% and 91% for PET, respectively. A lymph node region-based analysis (comprising 14 defined anatomical regions) revealed a sensitivity of 81% and a specificity of 97% for CT and 96% and 99% for FDG PET, respectively. Only three of 109 image fusion findings needed further evaluation (false positive). Conclusion. Digital fusion of PET and CT improves the accuracy of staging, restaging, and therapy monitoring in patients with malignant lymphoma and may reduce the need for invasive diagnostic procedures.

Clinical Value of Absolute Quantification of Myocardial Perfusion With 15 O-Water in Coronary Artery Disease

The standard interpretation of perfusion imaging is based on the assessment of relative perfusion distribution. The limitations of that approach have been recognized in patients with multivessel disease and endothelial dysfunction. To date, however, no large clinical studies have investigated the value of measuring quantitative blood flow and compared that with relative uptake. One hundred four patients with moderate (30%-70%) pretest likelihood of coronary artery disease (CAD) underwent PET imaging during adenosine stress using (15)O-water and dynamic imaging. Absolute myocardial blood flow was calculated from which both standard relative myocardial perfusion images and images scaled to a known absolute scale were produced. The patients and the regions then were classified as normal or abnormal and compared against the reference of conventional angiography with fractional flow reserve. In patient-based analysis, the positive predictive value, negative predictive value, and accuracy of absolute perfusion in the detection of any obstructive CAD were 86%, 97%, and 92%, respectively, with absolute quantification. The corresponding values with relative analysis were 61%, 83%, and 73%, respectively. In region-based analysis, the receiver operating characteristic curves confirmed that the absolute quantification was superior to relative assessment. In particular, the specificity and positive predictive value were low using just relative differences in flow. Only 9 of 24 patients with 3-vessel disease were correctly assessed using relative analysis. The measurement of myocardial blood flow in absolute terms has a significant impact on the interpretation of myocardial perfusion. As expected, multivessel disease is more accurately detected.

Contrasting the processes of texture segmentation and discrimination with static and phase-reversing stimuli

Regions of visual texture can be automatically segregated from one another when they abut but also discriminated from one another if they are separated in space or time. A difference in mean orientation between two textures serves to facilitate their segmentation, whereas a difference in orientation variance does not. The present study further supports this notion, by replicating the findings of Wolfson and Landy (1998) in showing that judgments (odd-one-out) made for textures that differ in mean orientation were more accurate (and more rapid) when the textures were abutting than when separated, whereas judgments of variance were made no more accurately for abutting relative to separated textures. Interestingly, however, responses were overall faster for textures differing in variance when they were separated compared to when they were abutting. This is perhaps due to the clear separation boundary, which serves to delineate the regions on which to perform some regional estimation of orientation variance. A second experiment highlights the phase-insensitivity of texture segmentation, in that locating a texture edge (defined by a difference in mean orientation) in high frequency orientation-reversing stimuli can be performed at much higher frequencies than the discrimination of the same regions but with the texture contour masked. Textures that differed in variance did not exhibit this effect. A final experiment demonstrates that the phase-insensitive perception of texture borders improves with eccentric viewing relative to the fovea, whereas perception of the texture regions does not. Together, these experiments show dissociations between edge- and region-based texture analysis mechanisms and suggest a fast, sign-invariant contour extraction system mediating texture segmentation, which may be closely linked to the magnocellular subdivision of visual processing.

Preoperative nodal staging of uterine cancer: is contrast-enhanced PET/CT more accurate than non-enhanced PET/CT or enhanced CT alone?

To determine whether contrast-enhanced PET/CT is more accurate than either non-enhanced PET/CT or enhanced CT alone for nodal staging of uterine cancer. Forty patients with endometrial cancer and cervical cancer underwent conventional PET/CT scan with low-dose CT (ldCT), followed by full-dose CT with IV contrast (ceCT) before radical hysterectomy with pelvic and, when applicable, para-aortic lymphadenectomy. Three data sets of PET/ldCT, PET/ceCT, and enhanced CT images were interpreted separately by two readers. For region-specific comparisons, para-aortic and pelvic lymph nodes were divided into the bilateral para-aortic, common iliac, external iliac, internal iliac, and obturator areas. Based on histopathological findings as the gold standard, we compared the diagnostic accuracy between the three methods using McNemar test with Bonferroni's adjustment. Of the 40 patients, 21 underwent pelvic lymphadenectomy only. Region-based analysis showed that the sensitivity, specificity, and accuracy of PET/ceCT were 61.4% (27/44), 98.1% (308/314), and 93.6% (335/358), respectively, whereas those of PET/ldCT were 52.3% (23/44), 96.8% (304/314), and 91.3% (327/358), respectively, and those of enhanced CT were 40.9% (18/44), 97.8% (307/314), and 90.8% (325/358), respectively. Although PET/ceCT had the best sensitivity among the three imaging modalities, a significant difference was observed only between PET/ceCT and enhanced CT (p=0.0027). Although PET/ceCT had better sensitivity and accuracy than PET/ldCT, the differences between the two imaging methods did not reach statistical significance (p=0.046 and p=0.047, respectively). PET/ceCT is slightly but not significantly superior to PET/ldCT for nodal staging of uterine cancer. Nodal metastasis cannot be excluded even if PET/ceCT gives negative findings.

Region-based statistical analysis of 2D PAGE images

A new comprehensive procedure for statistical analysis of two-dimensional polyacrylamide gel electrophoresis (2D PAGE) images is proposed, including protein region quantification, normalization and statistical analysis. Protein regions are defined by the master watershed map that is obtained from the mean gel. By working with these protein regions, the approach bypasses the current bottleneck in the analysis of 2D PAGE images: it does not require spot matching. Background correction is implemented in each protein region by local segmentation. Two-dimensional locally weighted smoothing (LOESS) is proposed to remove any systematic bias after quantification of protein regions. Proteins are separated into mutually independent sets based on detected correlations, and a multivariate analysis is used on each set to detect the group effect. A strategy for multiple hypothesis testing based on this multivariate approach combined with the usual Benjamini–Hochberg FDR procedure is formulated and applied to the differential analysis of 2D PAGE images. Each step in the analytical protocol is demonstrated by using an actual dataset. The effectiveness of the proposed methodology is shown using simulated gels in comparison with the commercial software packages PDQuest and Dymension. We also introduce a new procedure for simulating gel images.

Prospective Evaluation of 11C-Choline Positron Emission Tomography/Computed Tomography and Diffusion-Weighted Magnetic Resonance Imaging for the Nodal Staging of Prostate Cancer with a High Risk of Lymph Node Metastases

BackgroundContrast-enhanced computed tomography (CT) and magnetic resonance (MR) imaging for lymph node (LN) staging of prostate cancer (PCa) are largely inadequate. ObjectiveOur aim was to assess prospectively the sensitivity, specificity, and positive and negative predictive values for the LN staging by 11C-choline positron emission tomography (PET)-CT and MR diffusion-weighted imaging (DWI) of the pelvis before retropubic radical prostatectomy (RRP) with extended pelvic LN dissection (PLND). Design, setting, and participantsFrom February 2008 to August 2009, 36 patients with histologically proven PCa and no pelvic LN involvement on contrast-enhanced CT with a risk ≥10% but ≤35% at LN metastasis according to the Partin tables were enrolled in this study. InterventionPatients preoperatively underwent 11C-choline PET-CT and DWI. Subsequently all patients underwent a wide RRP and an extended PLND. MeasurementsSensitivity, specificity, and positive and negative predictive values (PPV and NPV) for LN status of 11C-choline PET-CT and DWI were calculated with the final histopathology of the LNs as comparator. Results and limitationsSeventeen patients (47%) had a pN1 stage, and 38 positive LNs were identified. On a LN region-based analysis, sensitivity, specificity, PPV, NPV, and the number of correctly recognised cases at 11C-choline PET-CT were 9.4%, 99.7%, 75.0%, 91.0%, and 7.9%, respectively, and at DWI these numbers were 18.8%, 97.6%, 46.2%, 91.7%, and 15.8%, respectively. Twelve LN regions containing macrometastases, of which 2 had capsular penetration, were not detected by 11C-choline PET-CT; 11 LNs, of which 2 had capsular penetration, were not detected by DWI. This is a small study with 36 patients, but we intend to recruit more patients. ConclusionsFrom this prospective histopathology-based evaluation of 11C-choline PET-CT and DWI for LN staging in high-risk PCa patients, it is concluded that these techniques cannot be recommended at present to detect occult LN metastases before initial treatment.

Segment-Based Real Time Stereo Vision Matching Using Characteristic Vectors

Stereo vision is the normal method to obtain the depth information from images. The problems encountered when applying well established algorithms to real time applications are due to the high computational load required. In this article, the authors address this issue by performing a region-based analysis which considers each pixel only once. Additionally, matching is carried out over statistical descriptors of the image regions. In this article, the authors present a new algorithm that has been specifically designed to solve some commonly observed problems which arise from other well known techniques. This algorithm was designed using a previous algorithm implemented by the authors. The complete analysis has been carried out over gray scale images. The results obtained from both real and synthetic images are presented in terms of matching quality and time consumption and are compared with other published results. Finally, a discussion of additional features related to the matching process is provided.

모바일하버 운영을 위한 국내 무역항 후보지 분석

In this study, a new concept of ocean transport system, called the mobile harbor serving for a short distance transport of containers with cargo handling cranes between mother containerships and coastal ports, is introduced. Instead of direct berthing a very large containership at the coastal port, Mobile Harbor is moving to the offshore mooring basin with enough water depth condition. Therefore, investigation of the coastal environment, technical condition and limitation of the domestic trade ports for the application of Mobile Harbor, is essential process. To figure out the accessibility of mobile harbor, the environmental conditions, the cargo handling capacity and marine traffic volume and flow pattern has been analyzed with the tools for marine traffic simulation and virtual navigation aids system. The most proper Mobile Harbor mooring areas among trade ports of the south and east coast are selected by analyzing the obtained information and evaluating its application: (1) Under natural environmental conditions such as air and sea weather, three candidate areas are selected such as Masan port, Ulsan port, and Busan(New port) port. (2) Under marine traffic and appropriateness of water facilities, three candidate areas are selected as Mokpo port, Busan(New port) port, and Donghae & Mookho port (3) For a region-based analysis considering handling capacity and the local managed trade ports in vicinity, three candidate areas are selected as Busan region, Yosu & KwangYang region, and Mokpo region. Through this study, the basic guideline for selection of optimum trade port and offshore mooring basin for mothership and Mobile Harbor is recommended. In order to apply the Mobile Harbor to the real water, navigaton aids as the virtual route identification with AIS must be introduced for maritime safety in the vicinity of Mobile Harbor area which berthing and cargo handling is being conducted.

Comparison of 18F-FDG and 11C-choline PET/CT for detecting recurrences in patients with nonsquamous cell head and neck malignancies

The aim of this retrospective study was to evaluate the usefulness of F-fluorodeoxyglucose (FDG) and C-choline positron emission tomography (PET)/computed tomography (CT) for detecting recurrences of nonsquamous cell head and neck malignancies after chemotherapy and radiotherapy. Fourteen patients (10 men and four women; mean age: 53.7 ± 14.5 years) with advanced nonsquamous cell head and neck malignancies other than squamous cell carcinoma were recruited. F-FDG and C-choline PET/CT examinations were performed in all the patients after chemotherapy and radiotherapy. The PET/CT images were evaluated using a visual analysis and a region-based analysis. After the posttreatment PET/CT examination, all the patients underwent further surveillance using the conventional imaging methods. Recurrences were eventually confirmed in eight patients after the posttreatment PET/CT examination. The region-based analysis showed that the maximum standardized uptake values for F-FDG and C-choline were strongly correlated with each other (R=0.84). The C-choline PET/CT clearly detected the lesions in two patients, one with severe diabetes mellitus and one with a brain lesion. The abilities of F-FDG and C-choline PET/CT to detect lesions were almost the same in this study. In addition, choline has a superior potential for imaging skull base and intracranial lesions because the normal brain is not choline avid.

A visual analytics approach to diagnosis of breast DCE-MRI data

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast is the most sensitive image modality for the detection of invasive breast cancer. To increase the moderate specificity of DCE-MRI, and therefore, the distinction of benign and malignant tumors, the tumor's heterogeneity and the tumor's enhancement kinetics have to be evaluated. In clinical practice, the tumor's enhancement kinetics are analyzed via time-intensity curves after manual placement of regions of interest (ROI). A substantial limitation of the ROI analysis is the inter-observer variability as well as the potential distortion of the ROI's average curve, e.g. if the ROI covers benign and malignant tumor tissue. We present a visual analytics approach for breast tumors in DCE-MRI data that comprises a voxel-wise glyph-based overview and and a region-based analysis. The regions are extracted via region merging and each region contains voxels with similar perfusion characteristics. As a result, we avoid the inter-observer variability and reduce distortion due to averaging over differently perfused tissue. A comparative study of 20 datasets was carried out to test our approach and an adapted time-intensity curve classification method. Moreover, the influence of similarity measurements and a potential region-based exploration are discussed. In conclusion, the presented features as similarity criteria yield the best results regarding the finer classification of the early contrast agent accumulation and the region's enhancement kinetics in the intermediate and late postcontrast phase since spatial information is included and the merging of regions with different perfusion characteristics is impeded.

Prostate cancer detection with 3 T MRI: Comparison of diffusion‐weighted imaging and dynamic contrast‐enhanced MRI in combination with T2‐weighted imaging

To evaluate the diagnostic ability of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced imaging (DCEI) in combination with T2-weighted imaging (T2WI) for the detection of prostate cancer using 3 T magnetic resonance imaging (MRI) with a phased-array body coil. Fifty-three patients with elevated serum levels of prostate-specific antigen (PSA) were evaluated by T2WI, DWI, and DCEI prior to needle biopsy. The obtained data from T2WI alone (protocol A), a combination of T2WI and DWI (protocol B), a combination T2WI and DCEI (protocol C), and a combination of T2WI plus DWI and DCEI (protocol D) were subjected to receiver operating characteristic (ROC) curve analysis. The sensitivity, specificity, accuracy, and area under the ROC curve (Az) for region-based analysis were: 61%, 91%, 84%, and 0.8415, respectively, in protocol A; 76%, 94%, 90%, and 0.8931, respectively, in protocol B; 77%, 93%, 89%, and 0.8655, respectively, in protocol C; and 81%, 96%, 92%, and 0.8968, respectively in protocol D. ROC analysis revealed significant differences between protocols A and B (P = 0.0008) and between protocols A and D (P = 0.0004). In patients with elevated PSA levels the combination of T2WI, DWI, DCEI using 3 T MRI may be a reasonable approach for the detection of prostate cancer.

Region-based analysis in genome-wide association study of Framingham Heart Study blood lipid phenotypes

Due to the high-dimensionality of single-nucleotide polymorphism (SNP) data, region-based methods are an attractive approach to the identification of genetic variation associated with a certain phenotype. A common approach to defining regions is to identify the most significant SNPs from a single-SNP association analysis, and then use a gene database to obtain a list of genes proximal to the identified SNPs. Alternatively, regions may be defined statistically, via a scan statistic. After categorizing SNPs as significant or not (based on the single-SNP association p-values), a scan statistic is useful to identify regions that contain more significant SNPs than expected by chance. Important features of this method are that regions are defined statistically, so that there is no dependence on a gene database, and both gene and inter-gene regions can be detected. In the analysis of blood-lipid phenotypes from the Framingham Heart Study (FHS), we compared statistically defined regions with those formed from the top single SNP tests. Although we missed a number of single SNPs, we also identified many additional regions not found as SNP-database regions and avoided issues related to region definition. In addition, analyses of candidate genes for high-density lipoprotein, low-density lipoprotein, and triglyceride levels suggested that associations detected with region-based statistics are also found using the scan statistic approach.

Automated Radiation Targeting in Head-and-Neck Cancer Using Region-Based Texture Analysis of PET and CT Images

A co-registered multimodality pattern analysis segmentation system (COMPASS) was developed to automatically delineate the radiation targets in head-and-neck cancer (HNC) using both (18)F-fluoro-deoxy glucose-positron emission tomography (PET) and computed tomography (CT) images. The performance of the COMPASS was compared with the results of existing threshold-based methods and radiation oncologist-drawn contours. The COMPASS extracted texture features from corresponding PET and CT voxels. Using these texture features, a decision-tree-based K-nearest-neighbor classifier labeled each voxel as either "normal" or "abnormal." The COMPASS was applied to the PET/CT images of 10 HNC patients. Automated segmentation results were validated against the manual segmentations of three radiation oncologists using the volume, sensitivity, and specificity. The performance of the COMPASS was compared with three PET-based threshold methods: standard uptake value of 2.5, 50% maximal intensity, and signal/background ratio. The tumor delineations of the COMPASS were both quantitatively and qualitatively more similar to those of the radiation oncologists than the delineations from the other methods. The specificity was 95% +/- 2%, 84% +/- 9%, 98% +/- 3%, and 96% +/- 4%, and the sensitivity was 90% +/- 12%, 93% +/- 10%, 48% +/- 20%, and 68% +/- 25% for the COMPASS, for a standard uptake value of 2.5, 50% maximal intensity, and signal/background ratio, respectively. The COMPASS distinguished HNC from adjacent normal tissues with high physiologic uptake and consistently defined tumors with large variability in (18)F-fluoro-deoxy glucose uptake, which are often problematic with the threshold-based methods. Automated segmentation using texture analysis of PET/CT images has the potential to provide accurate delineation of HNC. This could lead to reduced interobserver variability, reduced uncertainty in target delineation, and improved treatment planning accuracy.

Spatially discordant voltage alternans cause wavebreaks in ventricular fibrillation

Ventricular fibrillation (VF) is characterized by complex ECG patterns emanating from multiple, short-lived, reentrant electrical waves. The incessant breakup and creation of new daughter waves (wavebreaks) perpetuate VF. Dispersion of refractoriness (static or dynamic) has been implicated as a mechanism underlying wavebreaks. The purpose of this study was to investigate the mechanisms underlying wavefront instability in VF by localizing wave fractionation sites (the appearance of multiple waves) and their relationship to local spatial dispersion of voltage (V(m)) oscillations. Wave fractionations were identified by tracking V(m) oscillations optically at unprecedented spatial (100 x 100 pixels) and temporal (2,000 frames per second) resolution using a CMOS camera viewing the surface (1 x 1 cm(2)) of perfused guinea pig hearts (n = 6). VF was induced by burst stimulation, and wavefront dynamics were highlighted using region-based image analysis to automatically detect wavebreaks. Direct detection of wavebreak locations by image analysis was more reliable than the phase reconstruction method because baseline noise obstructed the correct identification of phase singularities by detecting false-positives. Wave fractionations (34 +/- 4 splits/s.cm(2)) fell into three categories: decremental conduction (49% +/- 7%), wave collisions (32% +/- 8%), and wavebreaks (17 +/- 2%). Wavebreaks occurred at a frequency of 5.8 +/- 1 splits/s.cm(2) and did not preferentially occur at anatomic obstacles (i.e., coronary vessels) but coincided with discordant alternans where V(m) amplitudes and durations shifted from high to low to from low to high on opposite sides of wavebreak sites. Spatial discordant alternans cause wavebreaks most likely because they are sites of abrupt dispersion of refractoriness.

Binary Partition Tree Analysis Based on Region Evolution and Its Application to Tree Simplification

Pyramid image representations via tree structures are recognized methods for region-based image analysis. Binary partition trees can be applied which document the merging process with small details found at the bottom levels and larger ones close to the root. Hindsight of the merging process is stored within the tree structure and provides the change histories of an image property from the leaf to the root node. In this work, the change histories are modelled by evolvement functions and their second order statistics are analyzed by using a knee function. Knee values show the reluctancy of each merge. We have systematically formulated these findings to provide a novel framework for binary partition tree analysis, where tree simplification is demonstrated. Based on an evolvement function, for each upward path in a tree, the tree node associated with the first reluctant merge is considered as a pruning candidate. The result is a simplified version providing a reduced solution space and still complying with the definition of a binary tree. The experiments show that image details are preserved whilst the number of nodes is dramatically reduced. An image filtering tool also results which preserves object boundaries and has applications for segmentation.