Volume and shape in feature space on adaptive FCM in MRI segmentation.

Intensity non-uniformity (bias field) correction, contextual constraints over spatial intensity distribution and non-spherical cluster's shape in the feature space are incorporated into the fuzzy c-means (FCM) for segmentation of three-dimensional multi-spectral MR images. The bias field is modeled by a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of either intensity or membership are added into the FCM cost functions. Since the feature space is not isotropic, distance measures, other than the Euclidean distance, are used to account for the shape and volumetric effects of clusters in the feature space. The performance of segmentation is improved by combining the adaptive FCM scheme with the criteria used in Gustafson-Kessel (G-K) and Gath-Geva (G-G) algorithms through the inclusion of the cluster scatter measure. The performance of this integrated approach is quantitatively evaluated on normal MR brain images using the similarity measures. The improvement in the quality of segmentation obtained with our method is also demonstrated by comparing our results with those produced by FSL (FMRIB Software Library), a software package that is commonly used for tissue classification.

The use of unwrapped phase in MR image segmentation: A preliminary study

This paper considers the problem of tissue classification in 3D MRI. More specifically, a new set of texture features, based on phase information, is used to perform the segmentation of the bones of the knee. The phase information provides a very good discrimination between the bone and the surrounding tissues, but is usually not used due to phase unwrapping problems. We present a method to extract textural information from the phase that does not require phase unwrapping. The textural information extracted from the magnitude and the phase can be combined to perform tissue classification, and used to initialise an active shape model, leading to a more precise segmentation.

Tissue microarray study for classification of breast tumors

Clinical and pathological heterogeneity of breast cancer hinders selection of appropriate treatment for individual cases. Molecular profiling at gene or protein levels may elucidate the biological variance of tumors and provide a new classification system that correlates better with biological, clinical and prognostic parameters. We studied the immunohistochemical profile of a panel of seven important biomarkers using tumor tissue arrays. The tumor samples were then classified with a monothetic (binary variables) clustering algorithm. Two distinct groups of tumors are characterized by the estrogen receptor (ER) status and tumor grade (p = 0.0026). Four biomarkers, c-erbB2, Cox-2, p53 and VEGF, were significantly overexpressed in tumors with the ER-negative (ER-) phenotype. Eight subsets of tumors were further identified according to the expression status of VEGF, c-erbB2 and p53. The malignant potential of the ER-/VEGF+ subgroup was associated with the strong correlations of Cox-2 and c-erb132 with VEGF. Our results indicate that this molecular classification system, based on the statistical analysis of immunohistochemical profiling, is a useful approach for tumor grouping. Some of these subgroups have a relative genetic homogeneity that may allow further study of specific genetically-controlled metabolic pathways. This approach may hold great promise in rationalizing the application of different therapeutic strategies for different subgroups of breast tumors. (C) 2003 Elsevier Inc. All rights reserved.

A new approach to the classification of mammographic masses and normal breast tissue

A new approach to mammographic mass detection is presented in this paper. Although different algorithms have been proposed for such a task, most of them are application dependent. In contrast, our approach makes use of a kindred topic in computer vision adapted to our particular problem. In this sense, we translate the eigenfaces approach for face detection/classification problems to a mass detection. Two different databases were used to show the robustness of the approach. The first one consisted on a set of 160 regions of interest (RoIs) extracted from the MIAS database, being 40 of them with confirmed masses and the rest normal tissue. The second set of RoIs was extracted from the DDSM database, and contained 196 RoIs containing masses and 392 with normal, but suspicious regions. Initial results demonstrate the feasibility of using such approach with performances comparable to other algorithms, with the advantage of being a more general, simple and cost-effective approach

Automatic classification of prostate stromal tissue in histological images using Haralick descriptors and Local Binary Patterns

In this paper we presente a classification system that uses a combination of texture features from stromal regions: Haralick features and Local Binary Patterns (LBP) in wavelet domain. The system has five steps for classification of the tissues. First, the stromal regions were detected and extracted using segmentation techniques based on thresholding and RGB colour space. Second, the Wavelet decomposition was applied in the extracted regions to obtain the Wavelet coefficients. Third, the Haralick and LBP features were extracted from the coefficients. Fourth, relevant features were selected using the ANOVA statistical method. The classication (fifth step) was performed with Radial Basis Function (RBF) networks. The system was tested in 105 prostate images, which were divided into three groups of 35 images: normal, hyperplastic and cancerous. The system performance was evaluated using the area under the ROC curve and resulted in 0.98 for normal versus cancer, 0.95 for hyperplasia versus cancer and 0.96 for normal versus hyperplasia. Our results suggest that texture features can be used as discriminators for stromal tissues prostate images. Furthermore, the system was effective to classify prostate images, specially the hyperplastic class which is the most difficult type in diagnosis and prognosis.

Tissue metabolomics of hepatocellular carcinoma: Tumor energy metabolism and the role of transcriptomic classification

Hepatocellular carcinoma (HCC) is one of the commonest causes of death from cancer. A plethora of metabolomic investigations of HCC have yielded molecules in biofluids that are both up- and down-regulated but no real consensus has emerged regarding exploitable biomarkers for early detection of HCC. We report here a different approach, a combined transcriptomics and metabolomics study of energy metabolism in HCC. A panel of 31 pairs of HCC tumors and corresponding nontumor liver tissues from the same patients was investigated by gas chromatography-mass spectrometry (GCMS)-based metabolomics. HCC was characterized by ∼2-fold depletion of glucose, glycerol 3- and 2-phosphate, malate, alanine, myo-inositol, and linoleic acid. Data are consistent with a metabolic remodeling involving a 4-fold increase in glycolysis over mitochondrial oxidative phosphorylation. A second panel of 59 HCC that had been typed by transcriptomics and classified in G1 to G6 subgroups was also subjected to GCMS tissue metabolomics. No differences in glucose, lactate, alanine, glycerol 3-phosphate, malate, myo-inositol, or stearic acid tissue concentrations were found, suggesting that the Wnt/β-catenin pathway activated by CTNNB1 mutation in subgroups G5 and G6 did not exhibit specific metabolic remodeling. However, subgroup G1 had markedly reduced tissue concentrations of 1-stearoylglycerol, 1-palmitoylglycerol, and palmitic acid, suggesting that the high serum α-fetoprotein phenotype of G1, associated with the known overexpression of lipid catabolic enzymes, could be detected through metabolomics as increased lipid catabolism. Conclusion: Tissue metabolomics yielded precise biochemical information regarding HCC tumor metabolic remodeling from mitochondrial oxidation to aerobic glycolysis and the impact of molecular subtypes on this process.

Advantages of tandem LC-MS for the rapid assessment of tissue-specific metabolic complexity using a pentafluorophenylpropyl stationary phase

In this study, a tandem LC-MS (Waters Xevo TQ) MRM-based MS method was developed for rapid, broad profiling of hydrophilic metabolites from biological samples, in either positive or negative ion modes without the need for an ion pairing reagent, using a reversed-phase pentafluorophenylpropyl (PFPP) column. The developed method was successfully applied to analyze various biological samples from C57BL/6 mice, including urine, duodenum, liver, plasma, kidney, heart, and skeletal muscle. As result, a total 112 of hydrophilic metabolites were detected within 8 min of running time to obtain a metabolite profile of the biological samples. The analysis of this number of hydrophilic metabolites is significantly faster than previous studies. Classification separation for metabolites from different tissues was globally analyzed by PCA, PLS-DA and HCA biostatistical methods. Overall, most of the hydrophilic metabolites were found to have a "fingerprint" characteristic of tissue dependency. In general, a higher level of most metabolites was found in urine, duodenum, and kidney. Altogether, these results suggest that this method has potential application for targeted metabolomic analyzes of hydrophilic metabolites in a wide ranges of biological samples.

Molecular classification of familial colorectal and endometrial carcinoma

Hereditary nonpolyposis colorectal cancer (HNPCC) is the most common known clearly hereditary cause of colorectal and endometrial cancer (CRC and EC). Dominantly inherited mutations in one of the known mismatch repair (MMR) genes predispose to HNPCC. Defective MMR leads to an accumulation of mutations especially in repeat tracts, presenting microsatellite instability. HNPCC is clinically a very heterogeneous disease. The age at onset varies and the target tissue may vary. In addition, families that fulfill the diagnostic criteria for HNPCC but fail to show any predisposing mutation in MMR genes exist. Our aim was to evaluate the genetic background of familial CRC and EC. We performed comprehensive molecular and DNA copy number analyses of CRCs fulfilling the diagnostic criteria for HNPCC. We studied the role of five pathways (MMR, Wnt, p53, CIN, PI3K/AKT) and divided the tumors into two groups, one with MMR gene germline mutations and the other without. We observed that MMR proficient familial CRC consist of two molecularly distinct groups that differ from MMR deficient tumors. Group A shows paucity of common molecular and chromosomal alterations characteristic of colorectal carcinogenesis. Group B shows molecular features similar to classical microsatellite stable tumors with gross chromosomal alterations. Our finding of a unique tumor profile in group A suggests the involvement of novel predisposing genes and pathways in colorectal cancer cohorts not linked to MMR gene defects. We investigated the genetic background of familial ECs. Among 22 families with clustering of EC, two (9%) were due to MMR gene germline mutations. The remaining familial site-specific ECs are largely comparable with HNPCC associated ECs, the main difference between these groups being MMR proficiency vs. deficiency. We studied the role of PI3K/AKT pathway in familial ECs as well and observed that PIK3CA amplifications are characteristic of familial site-specific EC without MMR gene germline mutations. Most of the high-level amplifications occurred in tumors with stable microsatellites, suggesting that these tumors are more likely associated with chromosomal rather than microsatellite instability and MMR defect. The existence of site-specific endometrial carcinoma as a separate entity remains equivocal until predisposing genes are identified. It is possible that no single highly penetrant gene for this proposed syndrome exists, it may, for example be due to a combination of multiple low penetrance genes. Despite advances in deciphering the molecular genetic background of HNPCC, it is poorly understood why certain organs are more susceptible than others to cancer development. We found that important determinants of the HNPCC tumor spectrum are, in addition to different predisposing germline mutations, organ specific target genes and different instability profiles, loss of heterozygosity at MLH1 locus, and MLH1 promoter methylation. This study provided more precise molecular classification of families with CRC and EC. Our observations on familial CRC and EC are likely to have broader significance that extends to sporadic CRC and EC as well.

Human parvovirus B19: tissue persistence and prevalence of prototypic and new variants

Human parvovirus B19 is a minute ssDNA virus causing a wide variety of diseases, including erythema infectiosum, arthropathy, anemias, and fetal death. After primary infection, genomic DNA of B19 has been shown to persist in solid tissues of not only symptomatic but also of constitutionally healthy, immunocompetent individuals. In this thesis, the viral DNA was shown to persist as an apparently intact molecule of full length, and without persistence-specific mutations. Thus, although the mere presence of B19 DNA in tissue can not be used as a diagnostic criterion, a possible role in the pathogenesis of diseases e.g. through mRNA or protein production can not be excluded. The molecular mechanism, the host-cell type and the possible clinical significance of B19 DNA tissue persistence are yet to be elucidated. In the beginning of this work, the B19 genomic sequence was considered highly conserved. However, new variants were found: V9 was detected in 1998 in France, in serum of a child with aplastic crisis. This variant differed from the prototypic B19 sequences by ~10 %. In 2002 we found, persisting in skin of constitutionally healthy humans, DNA of another novel B19 variant, LaLi. Genetically this variant differed from both the prototypic sequences and the variant V9 also by ~10%. Simultaneously, B19 isolates with DNA sequences similar to LaLi were introduced by two other groups, in the USA and France. Based on phylogeny, a classification scheme based on three genotypes (B19 types 1-3) was proposed. Although the B19 virus is mainly transmitted via the respiratory route, blood and plasma-derived products contaminated with high levels of B19 DNA have also been shown to be infectious. The European Pharmacopoeia stipulates that, in Europe, from the beginning of 2004, plasma pools for manufacture must contain less than 104 IU/ml of B19 DNA. Quantitative PCR screening is therefore a prerequisite for restriction of the B19 DNA load and obtaining of safe plasma products. Due to the DNA sequence variation among the three B19 genotypes, however, B19 PCR methods might fail to detect the new variants. We therefore examined the suitability of the two commercially available quantitative B19 PCR tests, LightCycler-Parvovirus B19 quantification kit (Roche Diagnostics) and RealArt Parvo B19 LC PCR (Artus), for detection, quantification and differentiation of the three B19 types known, including B19 types 2 and 3. The former method was highly sensitive for detection of the B19 prototype but was not suitable for detection of types 2 and 3. The latter method detected and differentiated all three B19 virus types. However, one of the two type-3 strains was detected at a lower sensitivity. Then, we assessed the prevalence of the three B19 virus types among Finnish blood donors, by screening pooled plasma samples derived from >140 000 blood-donor units: none of the pools contained detectable levels of B19 virus types 2 or 3. According to the results of other groups, B19 type 2 was absent also among Danish blood-donors, and extremely rare among symptomatic European patients. B19 type 3 has been encountered endemically in Ghana and (apparently) in Brazil, and sporadical cases have been detected in France and the UK. We next examined the biological characteristics of these virus types. The p6 promoter regions of virus types 1-3 were cloned in front of a reporter gene, the constructs were transfected into different cell lines, and the promoter activities were measured. As a result, we found that the activities of the three p6 promoters, although differing in sequence by >20%, were of equal strength, and most active in B19-permissive cells. Furthermore, the infectivity of the three B19 types was examined in two B19-permissive cell lines. RT-PCR revealed synthesis of spliced B19 mRNAs, and immunofluorescence verified the production of NS1 and VP proteins in the infected cells. These experiments suggested similar host-cell tropism and showed that the three virus types are strains of the same species, i.e. human parvovirus B19. Last but not least, the sera from subjects infected in the past either with B19 type 1 or type 2 (as evidenced by tissue persistence of the respective DNAs), revealed in VP1/2- and VP2-EIAs a 100 % cross-reactivity between virus types 1 and 2. These results, together with similar studies by others, indicate that the three B19 genotypes constitute a single serotype.

Antiendomysial and antihuman recombinant tissue transglutaminase antibodies in the diagnosis of coeliac disease: a biopsy-proven European multicentre study.

OBJECTIVE: To investigate the value of serum antitissue transglutaminase IgA antibodies (IgA-TTG) and IgA antiendomysial antibodies (IgA-EMA) in the diagnosis of coeliac disease in cohorts from different geographical areas in Europe. The setting allowed a further comparison between the antibody results and the conventional small-intestinal histology. METHODS: A total of 144 cases with coeliac disease [median age 19.5 years (range 0.9-81.4)], and 127 disease controls [median age 29.2 years (range 0.5-79.0)], were recruited, on the basis of biopsy, from 13 centres in nine countries. All biopsy specimens were re-evaluated and classified blindly a second time by two investigators. IgA-TTG were determined by ELISA with human recombinant antigen and IgA-EMA by an immunofluorescence test with human umbilical cord as antigen. RESULTS: The quality of the biopsy specimens was not acceptable in 29 (10.7%) of 271 cases and a reliable judgement could not be made, mainly due to poor orientation of the samples. The primary clinical diagnosis and the second classification of the biopsy specimens were divergent in nine cases, and one patient was initially enrolled in the wrong group. Thus, 126 coeliac patients and 106 controls, verified by biopsy, remained for final analysis. The sensitivity of IgA-TTG was 94% and IgA-EMA 89%, the specificity was 99% and 98%, respectively. CONCLUSIONS: Serum IgA-TTG measurement is effective and at least as good as IgA-EMA in the identification of coeliac disease. Due to a high percentage of poor histological specimens, the diagnosis of coeliac disease should not depend only on biopsy, but in addition the clinical picture and serology should be considered.