Final Report: Closeout of the Award NO. DE-FG02-98ER62618 (M.S. Fox-Rabinovitz, P.I.)

The final report describes the study aimed at exploring the variable-resolution stretched-grid (SG) approach to decadal regional climate modeling using advanced numerical techniques. The obtained results have shown that variable-resolution SG-GCMs using stretched grids with fine resolution over the area(s) of interest, is a viable established approach to regional climate modeling. The developed SG-GCMs have been extensively used for regional climate experimentation. The SG-GCM simulations are aimed at studying the U.S. regional climate variability with an emphasis on studying anomalous summer climate events, the U.S. droughts and floods

An accurate, nontraumatic ultrasonic method to monitor myocardial wall thickening in patients undergoing cardiac surgery

AbstractMeasurement of systolic wall thickening by sonomicrometry provides an accurate index of regional left ventricular function, but the trauma of crystal insertion limits its widespread clinical use. The first clinical application of a 10 MHz ultrasonic Doppler probe that can be either sutured or applied by suction to the epicardium and can measure wall thickening at any depth of the left ventricular wall is described. In 18 dogs, measurements obtained with the suction probe correlated well (r = 0.97) with those of a previously validated sutured probe.To assess clinical feasibility, the probe was applied to the epicardium of patients undergoing coronary bypass surgery. Good quality wall thickening signals were obtained with no complications. Transmural left ventricular thickening fraction before bypass surgery was 34 ± 3% (mean value ± SE) at the mid-ventricular lateral wall, 33 ± 4% at the anterior basal wall and 26 ± 4% at the mid-ventricular posterior wall. Right ventricular thickening fraction averaged 25 ± 3%. Endocardial thickening fraction tended to exceed epicardial thickening fraction, although the difference attained statistical significance (p < 0.05) only at the anterior basal wall.On average, thickening fraction during the immediate postoperative period remained unchanged compared with the preoperutive values, but a marked individual variability was observed, with 7 of 15 patients exhibiting a decrease and 8 an increase. Exteriorization of the wires attached to the sutured probe allowed continuous in situ monitoring of wall thickening in the postoperative period and subsequent removal of the probe, in six patients the crystal was left in place for 48 to 72 h after surgery and then removed without complications; good wall thickening signals were obtained for the entire period during which the probe was implanted.Thus, the Doppler probe is an accurate, atraumatic method for measuring right and left ventricular regional function. Transmural, endocardial and epicardial function can be mapped at various sites during surgery, and postoperatively one can monitor serial changes of regional function and assess the effects of cardioplegia and other therapeutic interventions. This technique should be useful for both investigative and clinical purposes

Automatic Detection of Blue-White Veil and Related Structures in Dermoscopy Images

Dermoscopy is a non-invasive skin imaging technique, which permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. One of the most important features for the diagnosis of melanoma in dermoscopy images is the blue-white veil (irregular, structureless areas of confluent blue pigmentation with an overlying white "ground-glass" film). In this article, we present a machine learning approach to the detection of blue-white veil and related structures in dermoscopy images. The method involves contextual pixel classification using a decision tree classifier. The percentage of blue-white areas detected in a lesion combined with a simple shape descriptor yielded a sensitivity of 69.35% and a specificity of 89.97% on a set of 545 dermoscopy images. The sensitivity rises to 78.20% for detection of blue veil in those cases where it is a primary feature for melanoma recognition

Orthotopic liver transplantation for alcoholic liver disease

Alcohol abuse is the most common cause of end‐stage liver disease in the United States, but many transplant centers are unwilling to accept alcoholic patients because of their supposed potential for recidivism, poor compliance with the required immunosuppression regimen and resulting failure of the allograft. There is also concern that alcohol‐induced injury in other organs will preclude a good result. From July 1, 11982, to April 30, 1988, 73 patients received orthotopic liver transplants at the University of Pittsburgh for end‐stage alcoholic liver disease. Fifty‐two (71%) of these were alive at 25 ± 9 mo (mean ± S. D.) after transplantation, when a phone survey of these patients, their wives/husbands, and their physicians was performed to evaluate their subsequent use of alcohol, current medical condition and employment. Data obtained were compared with those for nonalcoholic patients selected as transplant controls. The recidivism rate has been 11.5%, with most patients drinking only socially. Fifty‐four percent of the survivors are employed, 21% classify themselves as homemakers and only 11 (21%) are unable to work. Twenty‐one patients died after transplantation; the most frequent cause of death was sepsis (43%), and intraoperative death was the next most common cause (28.6%). These data demonstrate that alcoholic patients can be transplanted successfully and achieve good health not significantly different from that of individuals transplanted for other causes. Thus orthotopic liver transplantation is a therapeutic option that should be considered for individuals with end‐stage alcoholic liver disease who desire such therapy. Copyright © 1990 American Association for the Study of Liver Disease

Dark homogeneous streak dermoscopic pattern correlating with specific KIT mutations in melanoma

Mutations driving melanoma growth have diagnostic, prognostic, and therapeutic implications. Traditional classification systems do not correlate optimally with underlying melanoma growth-promoting mutations. Our objective was to determine whether unique dermoscopic growth patterns directly correlate with driving mutations. OBSERVATIONS: We evaluated common driving mutations in 4 different dermoscopic patterns (rhomboidal, negative pigmented network, polygonal, and dark homogeneous streaks) of primary cutaneous melanomas; 3 melanomas per pattern were tested. Three of the 4 patterns lacked common mutations in BRAF, NRAS, KIT, GNAQ, and HRAS. One pattern, the dark homogeneous streaks pattern, had unique KIT mutations in the second catalytic domain of KIT in exon 17 for all 3 samples tested. Two tumors with the dark homogeneous streaks pattern turned out to be different primary melanomas from the same patient and had different sequence mutations but had an impact on the same KIT domain. CONCLUSIONS AND RELEVANCE: While future study is required, these results have multiple implications. (1) The underlying melanoma-driving mutations may give rise to specific dermoscopic growth patterns, (2) BRAF/NRAS mutations in early melanomas may not be as common as previously thought, and (3) patients may be predisposed to developing specific driving mutations giving rise to melanomas or nevi of similar growth patterns

Checking bounded reachability in asynchronous systems by symbolic event tracing

This report presents a new symbolic technique for checking reachability properties of asynchronous systems by reducing the problem to satisfiability in restrained difference logic. The analysis is bounded by fixing a finite set of potential events, each of which may occur at most once in any order. The events are specified using high-level Petri nets. The logic encoding describes the space of possible causal links between events rather than possible sequences of states as in Bounded Model Checking. Independence between events is exploited intrinsically without partial order reductions, and the handling of data is symbolic. On a family of benchmarks, the proposed approach is consistently faster than Bounded Model Checking. In addition, this report presents a compact encoding of the restrained subset of difference logic in propositional logic

Sector Expansion and Elliptical Modeling of Blue-Gray Ovoids for Basal Cell Carcinoma Discrimination in Dermoscopy Images

Background: Blue-gray ovoids (B-GOs), a critical dermoscopic structure for basal cell carcinoma (BCC), offer an opportunity for automatic detection of BCC. Due to variation in size and color, B-GOs can be easily mistaken for similar structures in benign lesions. Analysis of these structures could afford accurate characterization and automatic recognition of B-GOs, furthering the goal of automatic BCC detection. This study utilizes a novel segmentation method to discriminate B-GOs from their benign mimics. Methods: Contact dermoscopy images of 68 confirmed BCCs with B-GOs were obtained. Another set of 131 contact dermoscopic images of benign lesions possessing B-GO mimics provided a benign competitive set. A total of 22 B-GO features were analyzed for all structures: 21 color features and one size feature. Regarding segmentation, this study utilized a novel sector-based, non-recursive segmentation method to expand the masks applied to the B-GOs and mimicking structures. Results: Logistic regression analysis determined that blue chromaticity was the best feature for discriminating true B-GOs in BCC from benign, mimicking structures. Discrimination of malignant structures was optimal when the final B-GO border was approximated by a best-fit ellipse. Using this optimal configuration, logistic regression analysis discriminated the expanded and fitted malignant structures from similar benign structures with a classification rate as high as 96.5%. Conclusions: Experimental results show that color features allow accurate expansion and localization of structures from seed areas. Modeling these structures as ellipses allows high discrimination of B-GOs in BCCs from similar structures in benign images

Fast and Accurate Border Detection in Dermoscopy Images Using Statistical Region Merging

Copyright 2007 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.As a result of advances in skin imaging technology and the development of suitable image processing techniques during the last decade, there has been a significant increase of interest in the computer-aided diagnosis of melanoma. Automated border detection is one of the most important steps in this procedure, since the accuracy of the subsequent steps crucially depends on it. In this paper, a fast and unsupervised approach to border detection in dermoscopy images of pigmented skin lesions based on the Statistical Region Merging algorithm is presented. The method is tested on a set of 90 dermoscopy images. The border detection error is quantified by a metric in which a set of dermatologist-determined borders is used as the ground-truth. The proposed method is compared to six state-of-the-art automated methods (optimized histogram thresholding, orientation-sensitive fuzzy c-means, gradient vector flow snakes, dermatologist-like tumor extraction algorithm, meanshift clustering, and the modified JSEG method) and borders determined by a second dermatologist. The results demonstrate that the presented method achieves both fast and accurate border detection in dermoscopy images.http://dx.doi.org/10.1117/12.70907