Discrimination of benign common nevi from malignant melanoma lesions by use of features based on spectral properties of the wavelet transform

OBJECTIVE: To evaluate the possibilities of describing and discriminating common nevi and malignant melanoma tissue with features based on spectral properties of the Daubechies 4 wavelet transform. STUDY DESIGN: Images of common nevi and malignant melanoma were dissected in square elements. The wavelet coefficients were calculated inside the square elements. The diagonal coefficients and related power spectra were used for further analysis. The analysis results served as guide for the selection of features, including standard deviations of wavelet coefficients inside the frequency bands and the energy of the frequency bands. These features describe properties of the frequency bands, representing information on different scales. To test the usefulness of the features for discrimination, a study set of 80 cases was classified by classification and regression trees analysis. The set was divided into a training set and a test set. RESULTS: In the case of benign common nevi, the energies of the lower frequency bands and higher, whereas malignant melanoma tissue shows more variability of the coefficients in higher-frequency bands. The influence on the detail properties of the images was studied by suppression of coefficients with low values, which are concentrated mainly in higher-frequency bands. In the case of benign common nevi the main information is contained in 15% of the coefficients and in the case of malignant melanoma, in 39%. The results of classification show a clear-cut difference between the cases. The classification correctly classified 95.78% of nevi elements and 94.22% of melanoma elements in the training set and 100% of cases of benign nevi and 80% of cases of malignant melanoma in the test set. CONCLUSION: Features based on the wavelet power spectrum contain sufficient information for differentiation between common nevi and malignant melanomas.     

Diagnostic assessment of cutaneous melanoma and common nevi using tissue counter analysis

OBJECTIVE: To test the applicability of tissue counter analysis to the diagnostic discrimination of cutaneous malignant melanoma and benign common melanocytic nevi. STUDY DESIGN: Forty cases each of melanoma and nevi were consecutively sampled. After creation of a learning set based on 20 cases each, discriminant analysis of background versus tissue elements, tumor versus other tissue elements and benign versus malignant tumor elements was performed. The discriminant functions were used to assess the amount of benign and malignant tumor elements in each case. RESULTS: In the learning set, discriminant analysis facilitated recognition of 99.6% of tissue versus background, 90.7% of tumor versus other tissue components and 85.6% of malignant versus benign tumor elements. In the whole set, the percentage of malignant tumor elements was 8.7 +/- 7.7 (range, 0.1-29.6) for benign nevi and 77.4 +/- 16.2 (43.6-99.4) for malignant melanoma. Based on these measurements, the correct diagnosis could be established in all cases (chi 2 > .0001). CONCLUSION: Tissue counter analysis may be a useful method for diagnostic purposes in histopathology.     

DNA ploidy and nuclear morphometry for the classification of dysplastic nevi

OBJECTIVE: To examine the diagnostic value of DNA ploidy and nuclear morphometric features in sporadic dysplastic nevi as compared to those in compound nevi and melanoma. STUDY DESIGN: DNA ploidy profiles plus seven direct and three derived nuclear features were obtained in a series of 120 melanocytic skin neoplasms (30 dysplastic nevi [DN], 30 melanomas [MM], 60 compound nevi [CN]) and the results compared. RESULTS: DNA ploidy separated melanomas from benign melanocytic skin neoplasms with 96.5% accuracy in classifying the grouped cases. The derived nuclear shape factor Form PE and nuclear axis ratio were the most successful discriminants separating DN from MM but allowed only 73.3% correct classification of cases. Separation of DN from CN was best achieved using Form PE and mean nuclear area (74.4% correctly classified). Results from compound nevi in subjects < 25 years of age fell between those for DN and MM. CONCLUSION: Quantitative nuclear cytologic characteristics in sporadic dysplastic nevi span a range seen in common nevi through to those in thin melanomas. Cytologic changes in sporadic dysplastic nevi overlap those seen in other melanocytic skin neoplasms. Therefore, other reproducible morphometric features need to be assessed in order to further refine the histopathologic diagnosis of this entity.     

Automated detection of connective tissue by tissue counter analysis and classification and regression trees.

OBJECTIVE: To evaluate the feasibility of the CART (Classification and Regression Tree) procedure for the recognition of microscopic structures in tissue counter analysis. METHODS: Digital microscopic images of H & E; stained slides of normal human skin and of primary malignant melanoma were overlayed with regularly distributed square measuring masks (elements) and grey value, texture and colour features within each mask were recorded. In the learning set, elements were interactively labeled as representing either connective tissue of the reticular dermis, other tissue components or background. Subsequently, CART models were based on these data sets. RESULTS: Implementation of the CART classification rules into the image analysis program showed that in an independent test set 94.1% of elements classified as connective tissue of the reticular dermis were correctly labeled. Automated measurements of the total amount of tissue and of the amount of connective tissue within a slide showed high reproducibility (r=0.97 and r=0.94, respectively; p<0.001). CONCLUSIONS: CART procedure in tissue counter analysis yields simple and reproducible classification rules for tissue elements.     

Small bowel image classification using cross-co-occurrence matrices on wavelet domain

This paper presents a novel system to compute the automated classification of wireless capsule endoscope images. Classification is achieved by a classical statistical approach, but novel features are extracted from the wavelet domain and they contain both color and texture information. First, a shift-invariant discrete wavelet transform (SIDWT) is computed to ensure that the multiresolution feature extraction scheme is robust to shifts. The SIDWT expands the signal (in a shift-invariant way) over the basis functions which maximize information. Then cross-co-occurrence matrices of wavelet subbands are calculated and used to extract both texture and color information. Canonical discriminant analysis is utilized to reduce the feature space and then a simple 1D classifier with the leave one out method is used to automatically classify normal and abnormal small bowel images. A classification rate of 94.7% is achieved with a database of 75 images (41 normal and 34 abnormal cases). The high success rate could be attributed to the robust feature set which combines multiresolutional color and texture features, with shift, scale and semi-rotational invariance. This result is very promising and the method could be used in a computer-aided diagnosis system or a content-based image retrieval scheme.     

Tissue counter analysis of histologic sections of melanoma: influence of mask size and shape, feature selection, statistical methods and tissue preparation.

BACKGROUND: Tissue counter analysis is an image analysis tool designed for the detection of structures in complex images at the macroscopic or microscopic scale. As a basic principle, small square or circular measuring masks are randomly placed across the image and image analysis parameters are obtained for each mask. Based on learning sets, statistical classification procedures are generated which facilitate an automated classification of new data sets. OBJECTIVE: To evaluate the influence of the size and shape of the measuring masks as well as the importance of feature selection, statistical procedures and technical preparation of slides on the performance of tissue counter analysis in microscopic images. As main quality measure of the final classification procedure, the percentage of elements that were correctly classified was used. STUDY DESIGN: HE-stained slides of 25 primary cutaneous melanomas were evaluated by tissue counter analysis for the recognition of melanoma elements (section area occupied by tumour cells) in contrast to other tissue elements and background elements. Circular and square measuring masks, various subsets of image analysis features and classification and regression trees compared with linear discriminant analysis as statistical alternatives were used. The percentage of elements that were correctly classified by the various classification procedures was assessed. In order to evaluate the applicability to slides obtained from different laboratories, the best procedure was automatically applied in a test set of another 50 cases of primary melanoma derived from the same laboratory as the learning set and two test sets of 20 cases each derived from two different laboratories, and the measurements of melanoma area in these cases were compared with conventional assessment of vertical tumour thickness. RESULTS: Square measuring masks were slightly superior to circular masks, and larger masks (64 or 128 pixels in diameter) were superior to smaller masks (8 to 32 pixels in diameter). As far as the subsets of image analysis features were concerned, colour features were superior to densitometric and Haralick texture features. Statistical moments of the grey level distribution were of least significance. CART (classification and regression tree) analysis turned out to be superior to linear discriminant analysis. In the best setting, 95% of melanoma tissue elements were correctly recognized. Automated measurement of melanoma area in the independent test sets yielded a correlation of r=0.846 with vertical tumour thickness (p<0.001), similar to the relationship reported for manual measurements. The test sets obtained from different laboratories yielded comparable results. CONCLUSIONS: Large, square measuring masks, colour features and CART analysis provide a useful setting for the automated measurement of melanoma tissue in tissue counter analysis, which can also be used for slides derived from different laboratories.     

Discriminant analysis of image karyometric variables in benign and malignant melanocytic skin lesions

OBJECTIVE: To perform a quantitative analysis to identify which of 7 nuclear morphometry-related variables are of diagnostic value in distinguishing benign from malignant melanocytic skin lesions. STUDY DESIGN: At the Institute of Pathology, University of Nis, formalin-fixed, paraffin-embedded skin biopsies from 23 cases of benign nevi (18 intradermal and 5 junctional) and 25 cases of primary nodular malignant melanomas were retrieved. Specimens were routinely stained with hematoxylin and eosin and analyzed using a computer-assisted interactive image analysis system. Nuclear area, equivalent diameter, volume of equivalent sphere, perimeter, mean chord, circularity and integrated optical density were estimated after manual editing of binary images. RESULTS: In univariate analysis, 6 features were found to be significantly different between the benign and malignant groups (P < .0001); all measured nuclear variables (except circularity) were higher in malignant melanomas. No significant differences were found among lesions with respect to nuclear shape. Using discriminant function analysis, a correct diagnosis was achieved in 95.8% of benign nevi cases and 84.0% of malignant melanoma cases. The best discriminant variable was nuclear area. CONCLUSION: Image analysis is diagnostically relevant to the evaluation of melanocytic lesions of the skin. The area of the nucleus appeared to have potential for differentiating benign from malignant tumors and can be estimated in the course of routine histology.     

Hepatitis C Related Chronic Liver Cirrhosis: Feasibility of Texture Analysis of MR Images for Classification of Fibrosis Stage and Necroinflammatory Activity Grade

Purpose

To assess the feasibility of texture analysis for classifying fibrosis stage and necroinflammatory activity grade in patients with chronic hepatitis C on T2-weighted (T2W), T1-weighted (T1W) and Gd-EOB-DTPA-enhanced hepatocyte-phase (EOB-HP) imaging.

Materials and methods

From April 2008 to June 2012, MR images from 123 patients with pathologically proven chronic hepatitis C were retrospectively analyzed. Texture parameters derived from histogram, gradient, run-length matrix, co-occurrence matrix, autoregressive model and wavelet transform methods were estimated with imaging software. Fisher, probability of classification error and average correlation, and mutual information coefficients were used to extract subsets of optimized texture features. Linear discriminant analysis in combination with 1-nearest neighbor classifier (LDA/1-NN) was used for lesion classification. In compliance with the software requirement, classification was performed based on datasets from all patients, the patient group with necroinflammatory activity grade 1, and that with fibrosis stage 4, respectively.

Results

Based on all patient dataset, LDA/1-NN produced misclassification rates of 28.46%, 35.77% and 20.33% for fibrosis staging and 34.15%, 25.20% and 28.46% for necroinflammatory activity grading in T2W, T1W and EOB-HP images. In the patient group with necroinflammatory activity grade 1, LDA/1-NN yielded misclassification rates of 5.00%, 0% and 12.50% for fibrosis staging in T2W, T1W and EOB-HP images respectively. In the patient group with fibrosis stage 4, LDA/1-NN yielded misclassification rates of 5.88%, 12.94% and 11.76% for necroinflammatory activity grading in T2W, T1W and EOB-HP images respectively.

Conclusion

Texture quantitative parameters of MR images facilitate classification of the fibrosis stage as well as necroinflammatory activity grade in chronic hepatitis C, especially after categorizing the input dataset according to the activity or fibrosis degree in order to remove the interference between the fibrosis stage and necroinflammatory activity grade on texture features.     

Novel Multiple Markers to Distinguish Melanoma from Dysplastic Nevi

Background

Distinguishing melanoma from dysplastic nevi can be challenging.

Objective

To assess which putative molecular biomarkers can be optimally combined to aid in the clinical diagnosis of melanoma from dysplastic nevi.

Methods

Immunohistochemical expressions of 12 promising biomarkers (pAkt, Bim, BRG1, BRMS1, CTHRC1, Cul1, ING4, MCL1, NQO1, SKP2, SNF5 and SOX4) were studied in 122 melanomas and 33 dysplastic nevi on tissue microarrays. The expression difference between melanoma and dysplastic nevi was performed by univariate and multiple logistic regression analysis, diagnostic accuracy of single marker and optimal combinations were performed by receiver operating characteristic (ROC) curve and artificial neural network (ANN) analysis. Classification and regression tree (CART) was used to examine markers simultaneous optimizing the accuracy of melanoma. Ten-fold cross-validation was analyzed for estimating generalization error for classification.

Results

Four (Bim, BRG1, Cul1 and ING4) of 12 markers were significantly differentially expressed in melanoma compared with dysplastic nevi by both univariate and multiple logistic regression analysis (p < 0.01). These four combined markers achieved 94.3% sensitivity, 81.8% specificity and attained 84.3% area under the ROC curve (AUC) and the ANN classified accuracy with training of 83.2% and testing of 81.2% for distinguishing melanoma from dysplastic nevi. The classification trees identified ING4, Cul1 and BRG1 were the most important classification parameters in ranking top-performing biomarkers with cross-validation error of 0.03.

Conclusions

The multiple biomarkers ING4, Cul1, BRG1 and Bim described here can aid in the discrimination of melanoma from dysplastic nevi and provide a new insight to help clinicians recognize melanoma.     

High-resolution and contextual analysis for the diagnosis of fine needle aspirates of breast.

A study was undertaken to confirm earlier work on a smaller number of patients that had suggested that medium-resolution contextual analysis complements high-resolution individual cell analysis for cytomorphometric classification of fine needle aspirate smears of breast. The objectives of this study were to improve and verify the method. Sixty-one biopsy-confirmed hematoxylin and eosin-stained aspirate smears of breast were restained using the Feulgen technique. Individual nuclei were digitized at a resolution of 0.25 micron. Features describing size, shape, density and texture were extracted from the images. Individual cell analysis correctly classified 84% of cases, contextual analysis correctly classified 70% of cases, and the combined use of both techniques resulted in 87% classification accuracy. However, if fibroadenoma cases are excluded, the combined correct classification rate is 93%. Geometric and densitometric features contributed most to correct classification in individual cell analysis, while the most important contextual feature was the number of clusters per scene. We conclude that the addition of quantitative measures of smear patterns, termed "contextual analysis," improves automated classification schemes.     

Genetic and Epidemiologic Evaluation of Dysplastic Nevi

Dysplastic Nevus Syndrome (DNS) has been defined as that trait characterized by the presence of at least one dysplastic melanocytic nevus. DNS was originally described in kindreds having multiple members with melanoma. Various types DNS have been described in other situations to include individuals with apparently sporadic cases, familial DNS without melanoma and individuals with apparently sporadic DNS with melanoma. These categories are based on historical information in general, and not on examination of family members. In all cases, the presence of dysplastic nevi appear to confer some increased risk of melanoma, which varies between the groups. Similarly cutaneous melanoma is thought to occur in several distinct populations-random individuals without DNS, individuals with sporadic DNS, and those with familial DNS. Genetic analysis of DNS has been largely confined to the classically ascertained kindreds associated with melanoma. These studies have usually used diagnostic criteria based on pathology of clinically selected material, and that evidence suggests that DNS is inherited as an autosomal dominant trait in these families. Surveys of the general population have detected rates of dysplastic nevi of 5% 20%. In our Utah-based studies, we have evaluated probands and family members from three groups. These included kindreds with multiple occurrences of melanoma, random individuals with at least one dysplastic nevus, and cases of melanoma with unknown family history. Controls were spouses of study subjects. We sought to determine the percentage of each group associated with dysplastic nevi and/or genetic DNS. The range of phenotype of patients with dysplastic nevi was large with some individuals having few nevi, none of which were clinically atypical, and others having greater than 100 nevi. The prevalence of dysplastic nevi in at least one of two biopsies in Utah population controls is presently Wtimated at 62%. Some probands with melanoma as well as some of their relatives had elevated numbers of nevi, suggesting that this predisposition to melanoma may be inherited.     

Primary cilium depletion typifies cutaneous melanoma in situ and malignant melanoma

Cutaneous melanoma is a lethal malignancy that arises spontaneously or via in situ precursor neoplasms. While melanoma in situ and locally invasive malignant melanoma can be cured surgically, these lesions can sometimes be difficult to distinguish from melanocytic nevi. Thus, the identification of histolopathologic or molecular features that distinguish these biologically distinct lesions would represent an important advance. To this end, we determined the abundance of melanocytic primary cilia in a series of 62 cases composed of typical cutaneous melanocytic nevi, melanoma in situ, invasive melanoma, and metastatic melanoma. Primary cilia are sensory organelles that modulate developmental and adaptive signaling and notably, are substantially depleted from the neoplastic epithelium of pancreatic carcinoma at a stage equivalent to melanoma in situ. In this series, we find that while nearly all melanocytes in 22 melanocytic nevi possessed a primary cilium, a near-complete loss of this organelle was observed in 16 cases of melanoma in situ, in 16 unequivocal primary invasive melanomas, and in 8 metastatic tumors, each associated with a cutaneous primary lesion. These findings suggest that the primary cilium may be used to segregate cutaneous invasive melanoma and melanoma in situ from melanocytic nevi. Moreover, they place the loss of an organelle known to regulate oncogenic signaling at an early stage of melanoma development.     

NRAS and BRAF Mutations in Melanoma-Associated Nevi and Uninvolved Nevi

According to the prevailing multistep model of melanoma development, oncogenic BRAF or NRAS mutations are crucial initial events in melanoma development. It is not known whether melanocytic nevi that are found in association with a melanoma are more likely to carry BRAF or NRAS mutations than uninvolved nevi. By laser microdissection we were able to selectively dissect and genotype cells either from the nevus or from the melanoma part of 46 melanomas that developed in association with a nevus. In 25 cases we also genotyped a control nevus of the same patients. Available tissue was also immunostained using the BRAF^V600E-mutation specific antibody VE1. The BRAF^V600E mutation was found in 63.0% of melanomas, 65.2% of associated nevi and 50.0% of control nevi. No significant differences in the distribution of BRAF or NRAS mutations could be found between melanoma and associated nevi or between melanoma associated nevi and control nevi. In concordant cases immunohistochemistry showed a higher expression (intensity of immunohistochemistry) of the mutated BRAF^V600E-protein in melanomas compared to their associated nevi. In this series the presence of a BRAF- or NRAS mutation in a nevus was not associated with the risk of malignant transformation. Our findings do not support the current traditional model of stepwise tumor progression.     

Dermatoscopy and High Frequency Sonography: Two Useful Non-Invasive Methods to Increase Preoperative Diagnostic Accuracy in Pigmented Skin Lesions

Dermatoscopy and high frequency sonography have recently been combined to increase diagnostic preoperative accuracy in the treatment of pigmented skin lesions. In this monocentric study 80 patients with pigmented skin lesions were evaluated clinically, by dermatoscopy, and 20 MHz-sonography followed by dermatohistopathological evaluation; 39 malignant melanomas, 37 common nevi, 3 dysplastic nevi, and 1 nevus Spitz were diagnosed histologically. In 72 of the 80 cases (91.3%) dermatoscopical diagnoses were confirmed by histopathology, compared to only 79% correct clinical diagnoses. For the mere clinical diagnosis of melanoma sensitivity was 79%, specificity was 78% and diagnostic accuracy was 65%. All diagnostic values increased by dermatoscopy: sensitivity reached 90%, specificity was 93%, and diagnostic accuracy was 83%. In order to determine tumor thickness preoperatively tumor thickness was measured by 20 MHz sonography. The correlation of tumor thickness between histometric and sonographic results was determined for nevi (r = 0.93) and melanoma (r = 0.95); 74.3% of melanomas were diagnosed correctly within an 0.2 mm range. Regarding the clinical important limit of 1 mm tumor thickness, 87.2% were diagnosed in accordance with histometric evaluation. An increase of 18% in diagnostic accuracy by dermatoscopy and 87.2% of correctly diagnosed cases of tumor thickness of malignant melanoma by high frequency sonography clearly demonstrate that these methods should be considered standard procedures in the diagnosis of pigmented skin lesions and will facilitate the decision on necessary surgical treatment.     

An Endogenous Electron Spin Resonance (ESR) Signal Discriminates Nevi from Melanomas in Human Specimens: A Step Forward in Its Diagnostic Application

Given the specific melanin-associated paramagnetic features, the Electron Spin Resonance (ESR, called also Electron Paramagnetic Resonance, EPR) analysis has been proposed as a potential tool for non-invasive melanoma diagnosis. However, studies comparing human melanoma tissues to the most appropriate physiological counterpart (nevi) have not been performed, and ESR direct correlation with melanoma clinical features has never been investigated. ESR spectrum was obtained from melanoma and non-melanoma cell-cultures as well as mouse melanoma and non-melanoma tissues and an endogenous ESR signal (g = 2.005) was found in human melanoma cells and in primary melanoma tissues explanted from mice, while it was always absent in non-melanoma samples. These characteristics of the measured ESR signal strongly suggested its connection with melanin. Quantitative analyses were then performed on paraffin-embedded human melanoma and nevus sections, and validated on an independent larger validation set, for a total of 112 sections (52 melanomas, 60 nevi). The ESR signal was significantly higher in melanomas (p = 0.0002) and was significantly different between “Low Breslow’s and “High Breslow’s” depth melanomas (p<0.0001). A direct correlation between ESR signal and Breslow’s depth, expressed in millimetres, was found (R = 0.57; p<0.0001). The eu/pheomelanin ratio was found to be significantly different in melanomas “Low Breslow’s” vs melanomas “High Breslow’s” depth and in nevi vs melanomas “High Breslow’s depth”. Finally, ROC analysis using ESR data discriminated melanomas sections from nevi sections with up to 90% accuracy and p<0.0002. In the present study we report for the first time that ESR signal in human paraffin-embedded nevi is significantly lower than signal in human melanomas suggesting that spectrum variations may be related to qualitative melanin differences specifically occurring in melanoma cells. We therefore conclude that this ESR signal may represent a reliable marker for melanoma diagnosis in human histological sections.     

On the Interplay of Telomeres,Nevi and the Risk of Melanoma

The relationship between telomeres, nevi and melanoma is complex. Shorter telomeres have been found to be associated with many cancers and with number of nevi, a known risk factor for melanoma. However, shorter telomeres have also been found to decrease melanoma risk. We performed a systematic analysis of telomere-related genes and tagSNPs within these genes, in relation to the risk of melanoma, dysplastic nevi, and nevus count combining data from four studies conducted in Italy. In addition, we examined whether telomere length measured in peripheral blood leukocytes is related to the risk of melanoma, dysplastic nevi, number of nevi, or telomere-related SNPs. A total of 796 cases and 770 controls were genotyped for 517 SNPs in 39 telomere-related genes genotyped with a custom-made array. Replication of the top SNPs was conducted in two American populations consisting of 488 subjects from 53 melanoma-prone families and 1,086 cases and 1,024 controls from a case-control study. We estimated odds ratios for associations with SNPs and combined SNP P-values to compute gene region-specific, functional group-specific, and overall P-value using an adaptive rank-truncated product algorithm. In the Mediterranean population, we found suggestive evidence that RECQL4, a gene involved in genome stability, RTEL1, a gene regulating telomere elongation, and TERF2, a gene implicated in the protection of telomeres, were associated with melanoma, the presence of dysplastic nevi and number of nevi, respectively. However, these associations were not found in the American samples, suggesting variable melanoma susceptibility for these genes across populations or chance findings in our discovery sample. Larger studies across different populations are necessary to clarify these associations.