Lacunarity analysis: a promising method for the automated assessment of melanocytic naevi and melanoma

Computer-aided clinical image analysis as a predictor of sentinel lymph node positivity in cutaneous melanoma

BACKGROUND

Delays in sentinel lymph node (SLN) biopsy may affect the positivity of non-SLNs. For these reasons, effort is being directed at obtaining reliable information regarding SLN positivity prior to surgical excision. However, the existing tools, e.g., dermoscopy, do not recognize statistically significant predictive criteria for SLN positivity in melanomas.

AIM

To investigate the possible association of computer-assisted objectively obtained color, color texture, sharpness and geometry variables with SLN positivity.

METHODS

We retrospectively reviewed and analyzed the computerized medical records of all patients diagnosed with cutaneous melanoma in a tertiary hospital in Germany during a 3-year period. The study included patients with histologically confirmed melanomas with Breslow > 0.75 mm who underwent lesion excision and SLN biopsy during the study period and who had clinical images shot with a digital camera and a handheld ruler aligned beside the lesion.

RESULTS

Ninety-nine patients with an equal number of lesions met the inclusion criteria and were included in the analysis. Overall mean (± standard deviation) age was 66 (15) years. The study group consisted of 20 patients with tumor-positive SLN (SLN+) biopsy, who were compared to 79 patients with tumor-negative SLN biopsy specimen (control group). The two groups differed significantly in terms of age (61 years vs 68 years) and histological subtype, with the SLN+ patients being younger and presenting more often with nodular or secondary nodular tumors (P < 0.05). The study group patients showed significantly higher eccentricity (i.e. distance between color and geometrical midpoint) as well as higher sharpness (i.e. these lesions were more discrete from the surrounding normal skin, P < 0.05). Regarding color variables, SLN+ patients demonstrated higher range in all four color intensities (gray, red, green, blue) and significantly higher skewness in three color intensities (gray, red, blue), P < 0.05. Color texture variables, i.e. lacunarity, were comparable in both groups.

CONCLUSION

SLN+ patients demonstrated significantly higher eccentricity, higher sharpness, higher range in all four color intensities (gray, red, green, blue) and significantly higher skewness in three color intensities (gray, red, blue). Further prospective studies are needed to better understand the effectiveness of clinical image processing in SLN+ melanoma patients.

The fractal and textural analysis of glomeruli in obese and non-obese patients

Background

Fractal dimension is an indirect indicator of signal complexity. The aim was to evaluate the fractal and textural analysis parameters of glomeruli in obese and non-obese patients with glomerular diseases and association of these parameters with clinical features.

Methods

The study included 125 patients mean age 46 ± 15.2 years: obese (BMI ≥ 27 kg/m²—63 patients) and non-obese (BMI < 27 kg/m²—62 patients). Serum concentration of creatinine, protein, albumin, cholesterol, trygliceride, and daily proteinuria were measured. Formula Chronic Kidney Disease Epidemiology Colaboration (CKD-EPI) equation was calculated. Fractal (fractal dimension, lacunarity) and textural (angular second moment (ASM), textural correlation (COR), inverse difference moment (IDM), textural contrast (CON), variance) analysis parameters were compared between two groups.

Results

Obese patients had higher mean value of variance (t = 1.867), ASM (t = 1.532) and CON (t = 0.394) but without significant difference (P > 0.05) compared to non-obese. Mean value of COR (t = 0.108) and IDM (t = 0.185) were almost the same in two patient groups. Obese patients had higher value of lacunarity (t = 0.499) in comparison with non-obese, the mean value of fractal dimension (t = 0.225) was almost the same in two groups. Significantly positive association between variance and creatinine concentration (r = 0.499, P < 0.01), significantly negative association between variance and CKD-EPI (r = -0.448, P < 0.01), variance and sex (r = -0.339, P < 0.05) were found.

Conclusions

Variance showed significant correlation with serum creatinine concentration, CKD-EPI and sex. CON and IDM were significantly related to sex. Fractal and textural analysis parameters of glomeruli could become a supplement to histopathologic analysis of kidney tissue.

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Variance showed significant correlation with eGFR calculated by CKD- EPI formula.

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Significant correlation between variance and serum creatinine was found.

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Textural contrast and inverse difference moment were significantly related to sex.

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Fractal analysis of glomeruli could become supplement to histopathologic analysis.

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Textural analyses of kidney tissue should become useful to histopathologic analysis.

Reproductive Homeostasis and Senescence in Drosophila melanogaster

The homeostatic properties of reproduction in aging female Drosophila melanogaster are investigated. Classic studies based on cohort analysis suggest that homeostatic capacity declines gradually as daily oviposition rates decline in aging flies. Analysis at the level of individuals gives a very different picture: reproductive homeostasis remains relatively constant for most of adult life until a critical point when oviposition either ceases entirely or continues in dysregulated fashion. The collapse of homeostatic capacity is abrupt. Enhanced homeostasis is associated with increased lifetime fecundity and improved prospects for survival. The fractal concept of lacunarity can be used to parameterize the "roughness" of individual fecundity trajectories and is inversely related to homeostatic capacity.

Laminin-driven Epac/Rap1 regulation of epithelial barriers on decellularized matrix

Decellularized tissues offer a unique tool for developing regenerative biomaterials or in vitro platforms for the study of cell-extracellular matrix (ECM) interactions. One main challenge associated with decellularized lung tissue is that ECM components can be stripped away or altered by the detergents used to remove cellular debris. Without characterizing the composition of lung decellularized ECM (dECM) and the cellular response caused by the altered composition, it is difficult to utilize dECM for regeneration and specifically, engineering the complexities of the alveolar-capillary barrier. This study takes steps towards uncovering if dECM must be enhanced with lost ECM proteins to achieve proper epithelial barrier formation. To achieve this, the epithelial barrier function was assessed on dECM coatings with and without the systematic addition of several key basement membrane proteins. After comparing barrier function on collagen I, fibronectin, laminin, and dECM in varying combinations as an in vitro coating, the alveolar epithelium exhibited superior barrier function when dECM was supplemented with laminin as evidenced by trans-epithelial electrical resistance (TEER) and permeability assays. Increased barrier resistance with laminin addition was associated with upregulation of Claudin-18, E-cadherin, and junction adhesion molecule (JAM)-A, and stabilization of zonula occludens (ZO)-1 at junction complexes. The Epac/Rap1 pathway was observed to play a role in the ECM-mediated barrier function determined by protein expression and Epac inhibition. These findings revealed potential ECM coatings and molecular therapeutic targets for improved regeneration with decellularized scaffolds. STATEMENT OF SIGNIFICANCE: Efforts to produce a transplantable organ-scale biomaterial for lung regeneration has not been entirely successful to date, due to incomplete cell-cell junction formation, ultimately leading to severe edema in vivo. To fully understand the process of alveolar junction formation on ECM-derived biomaterials, this research has characterized and tailored decellularized ECM (dECM) to mitigate reductions in barrier strength or cell attachment caused by abnormal ECM compositions or detergent damage to dECM. These results indicate that laminin-driven Epac signaling plays a vital role in the stabilization of the alveolar barrier. Addition of laminin or Epac agonists during alveolar regeneration can reduce epithelial permeability within bioengineered lungs.

Visual inspection and dermoscopy, alone or in combination, for diagnosing keratinocyte skin cancers in adults

BACKGROUND

Early accurate detection of all skin cancer types is important to guide appropriate management, to reduce morbidity and to improve survival. Basal cell carcinoma (BCC) is almost always a localised skin cancer with potential to infiltrate and damage surrounding tissue, whereas a minority of cutaneous squamous cell carcinomas (cSCCs) and invasive melanomas are higher-risk skin cancers with the potential to metastasise and cause death. Dermoscopy has become an important tool to assist specialist clinicians in the diagnosis of melanoma, and is increasingly used in primary-care settings. Dermoscopy is a precision-built handheld illuminated magnifier that allows more detailed examination of the skin down to the level of the superficial dermis. Establishing the value of dermoscopy over and above visual inspection for the diagnosis of BCC or cSCC in primary- and secondary-care settings is critical to understanding its potential contribution to appropriate skin cancer triage, including referral of higher-risk cancers to secondary care, the identification of low-risk skin cancers that might be treated in primary care and to provide reassurance to those with benign skin lesions who can be safely discharged.

OBJECTIVES

To determine the diagnostic accuracy of visual inspection and dermoscopy, alone or in combination, for the detection of (a) BCC and (b) cSCC, in adults. We separated studies according to whether the diagnosis was recorded face-to-face (in person) or based on remote (image-based) assessment.

SEARCH METHODS

We undertook a comprehensive search of the following databases from inception up to August 2016: Cochrane Central Register of Controlled Trials; MEDLINE; Embase; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform. We studied reference lists and published systematic review articles.

SELECTION CRITERIA

Studies of any design that evaluated visual inspection or dermoscopy or both in adults with lesions suspicious for skin cancer, compared with a reference standard of either histological confirmation or clinical follow-up.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted all data using a standardised data extraction and quality assessment form (based on QUADAS-2). We contacted authors of included studies where information related to the target condition or diagnostic thresholds were missing. We estimated accuracy using hierarchical summary ROC methods. We undertook analysis of studies allowing direct comparison between tests. To facilitate interpretation of results, we computed values of sensitivity at the point on the SROC curve with 80% fixed specificity and values of specificity with 80% fixed sensitivity. We investigated the impact of in-person test interpretation; use of a purposely-developed algorithm to assist diagnosis; and observer expertise.

MAIN RESULTS

We included 24 publications reporting on 24 study cohorts, providing 27 visual inspection datasets (8805 lesions; 2579 malignancies) and 33 dermoscopy datasets (6855 lesions; 1444 malignancies). The risk of bias was mainly low for the index test (for dermoscopy evaluations) and reference standard domains, particularly for in-person evaluations, and high or unclear for participant selection, application of the index test for visual inspection and for participant flow and timing. We scored concerns about the applicability of study findings as of 'high' or 'unclear' concern for almost all studies across all domains assessed. Selective participant recruitment, lack of reproducibility of diagnostic thresholds and lack of detail on observer expertise were particularly problematic.The detection of BCC was reported in 28 datasets; 15 on an in-person basis and 13 image-based. Analysis of studies by prior testing of participants and according to observer expertise was not possible due to lack of data. Studies were primarily conducted in participants referred for specialist assessment of lesions with available histological classification. We found no clear differences in accuracy between dermoscopy studies undertaken in person and those which evaluated images. The lack of effect observed may be due to other sources of heterogeneity, including variations in the types of skin lesion studied, in dermatoscopes used, or in the use of algorithms and varying thresholds for deciding on a positive test result.Meta-analysis found in-person evaluations of dermoscopy (7 evaluations; 4683 lesions and 363 BCCs) to be more accurate than visual inspection alone for the detection of BCC (8 evaluations; 7017 lesions and 1586 BCCs), with a relative diagnostic odds ratio (RDOR) of 8.2 (95% confidence interval (CI) 3.5 to 19.3; P < 0.001). This corresponds to predicted differences in sensitivity of 14% (93% versus 79%) at a fixed specificity of 80% and predicted differences in specificity of 22% (99% versus 77%) at a fixed sensitivity of 80%. We observed very similar results for the image-based evaluations.When applied to a hypothetical population of 1000 lesions, of which 170 are BCC (based on median BCC prevalence across studies), an increased sensitivity of 14% from dermoscopy would lead to 24 fewer BCCs missed, assuming 166 false positive results from both tests. A 22% increase in specificity from dermoscopy with sensitivity fixed at 80% would result in 183 fewer unnecessary excisions, assuming 34 BCCs missed for both tests. There was not enough evidence to assess the use of algorithms or structured checklists for either visual inspection or dermoscopy.Insufficient data were available to draw conclusions on the accuracy of either test for the detection of cSCCs.

AUTHORS' CONCLUSIONS

Dermoscopy may be a valuable tool for the diagnosis of BCC as an adjunct to visual inspection of a suspicious skin lesion following a thorough history-taking including assessment of risk factors for keratinocyte cancer. The evidence primarily comes from secondary-care (referred) populations and populations with pigmented lesions or mixed lesion types. There is no clear evidence supporting the use of currently-available formal algorithms to assist dermoscopy diagnosis.

Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults

BACKGROUND

Melanoma has one of the fastest rising incidence rates of any cancer. It accounts for a small percentage of skin cancer cases but is responsible for the majority of skin cancer deaths. Although history-taking and visual inspection of a suspicious lesion by a clinician are usually the first in a series of 'tests' to diagnose skin cancer, dermoscopy has become an important tool to assist diagnosis by specialist clinicians and is increasingly used in primary care settings. Dermoscopy is a magnification technique using visible light that allows more detailed examination of the skin compared to examination by the naked eye alone. Establishing the additive value of dermoscopy over and above visual inspection alone across a range of observers and settings is critical to understanding its contribution for the diagnosis of melanoma and to future understanding of the potential role of the growing number of other high-resolution image analysis techniques.

OBJECTIVES

To determine the diagnostic accuracy of dermoscopy alone, or when added to visual inspection of a skin lesion, for the detection of cutaneous invasive melanoma and atypical intraepidermal melanocytic variants in adults. We separated studies according to whether the diagnosis was recorded face-to-face (in-person), or based on remote (image-based), assessment.

SEARCH METHODS

We undertook a comprehensive search of the following databases from inception up to August 2016: CENTRAL; MEDLINE; Embase; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform. We studied reference lists and published systematic review articles.

SELECTION CRITERIA

Studies of any design that evaluated dermoscopy in adults with lesions suspicious for melanoma, compared with a reference standard of either histological confirmation or clinical follow-up. Data on the accuracy of visual inspection, to allow comparisons of tests, was included only if reported in the included studies of dermoscopy.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted all data using a standardised data extraction and quality assessment form (based on QUADAS-2). We contacted authors of included studies where information related to the target condition or diagnostic threshold were missing. We estimated accuracy using hierarchical summary receiver operating characteristic (SROC),methods. Analysis of studies allowing direct comparison between tests was undertaken. To facilitate interpretation of results, we computed values of sensitivity at the point on the SROC curve with 80% fixed specificity and values of specificity with 80% fixed sensitivity. We investigated the impact of in-person test interpretation; use of a purposely developed algorithm to assist diagnosis; observer expertise; and dermoscopy training.

MAIN RESULTS

We included a total of 104 study publications reporting on 103 study cohorts with 42,788 lesions (including 5700 cases), providing 354 datasets for dermoscopy. The risk of bias was mainly low for the index test and reference standard domains and mainly high or unclear for participant selection and participant flow. Concerns regarding the applicability of study findings were largely scored as 'high' concern in three of four domains assessed. Selective participant recruitment, lack of reproducibility of diagnostic thresholds and lack of detail on observer expertise were particularly problematic.The accuracy of dermoscopy for the detection of invasive melanoma or atypical intraepidermal melanocytic variants was reported in 86 datasets; 26 for evaluations conducted in person (dermoscopy added to visual inspection), and 60 for image-based evaluations (diagnosis based on interpretation of dermoscopic images). Analyses of studies by prior testing revealed no obvious effect on accuracy; analyses were hampered by the lack of studies in primary care, lack of relevant information and the restricted inclusion of lesions selected for biopsy or excision. Accuracy was higher for in-person diagnosis compared to image-based evaluations (relative diagnostic odds ratio (RDOR) 4.6, 95% confidence interval (CI) 2.4 to 9.0; P < 0.001).We compared accuracy for (a), in-person evaluations of dermoscopy (26 evaluations; 23,169 lesions and 1664 melanomas),versus visual inspection alone (13 evaluations; 6740 lesions and 459 melanomas), and for (b), image-based evaluations of dermoscopy (60 evaluations; 13,475 lesions and 2851 melanomas),versus image-based visual inspection (11 evaluations; 1740 lesions and 305 melanomas). For both comparisons, meta-analysis found dermoscopy to be more accurate than visual inspection alone, with RDORs of (a), 4.7 (95% CI 3.0 to 7.5; P < 0.001), and (b), 5.6 (95% CI 3.7 to 8.5; P < 0.001). For a), the predicted difference in sensitivity at a fixed specificity of 80% was 16% (95% CI 8% to 23%; 92% for dermoscopy + visual inspection versus 76% for visual inspection), and predicted difference in specificity at a fixed sensitivity of 80% was 20% (95% CI 7% to 33%; 95% for dermoscopy + visual inspection versus 75% for visual inspection). For b) the predicted differences in sensitivity was 34% (95% CI 24% to 46%; 81% for dermoscopy versus 47% for visual inspection), at a fixed specificity of 80%, and predicted difference in specificity was 40% (95% CI 27% to 57%; 82% for dermoscopy versus 42% for visual inspection), at a fixed sensitivity of 80%.Using the median prevalence of disease in each set of studies ((a), 12% for in-person and (b), 24% for image-based), for a hypothetical population of 1000 lesions, an increase in sensitivity of (a), 16% (in-person), and (b), 34% (image-based), from using dermoscopy at a fixed specificity of 80% equates to a reduction in the number of melanomas missed of (a), 19 and (b), 81 with (a), 176 and (b), 152 false positive results. An increase in specificity of (a), 20% (in-person), and (b), 40% (image-based), at a fixed sensitivity of 80% equates to a reduction in the number of unnecessary excisions from using dermoscopy of (a), 176 and (b), 304 with (a), 24 and (b), 48 melanomas missed.The use of a named or published algorithm to assist dermoscopy interpretation (as opposed to no reported algorithm or reported use of pattern analysis), had no significant impact on accuracy either for in-person (RDOR 1.4, 95% CI 0.34 to 5.6; P = 0.17), or image-based (RDOR 1.4, 95% CI 0.60 to 3.3; P = 0.22), evaluations. This result was supported by subgroup analysis according to algorithm used. We observed higher accuracy for observers reported as having high experience and for those classed as 'expert consultants' in comparison to those considered to have less experience in dermoscopy, particularly for image-based evaluations. Evidence for the effect of dermoscopy training on test accuracy was very limited but suggested associated improvements in sensitivity.

AUTHORS' CONCLUSIONS

Despite the observed limitations in the evidence base, dermoscopy is a valuable tool to support the visual inspection of a suspicious skin lesion for the detection of melanoma and atypical intraepidermal melanocytic variants, particularly in referred populations and in the hands of experienced users. Data to support its use in primary care are limited, however, it may assist in triaging suspicious lesions for urgent referral when employed by suitably trained clinicians. Formal algorithms may be of most use for dermoscopy training purposes and for less expert observers, however reliable data comparing approaches using dermoscopy in person are lacking.

Automated decision support in melanocytic lesion management

An automated melanocytic lesion image-analysis algorithm is described that aims to reproduce the decision-making of a dermatologist. The utility of the algorithm lies in its ability to identify lesions requiring excision from lesions not requiring excision. Using only wavelet coefficients as features, and testing three different machine learning algorithms, a cohort of 250 images of pigmented lesions is classified based on expert dermatologists’ recommendations of either excision (165 images) or no excision (85 images). It is shown that the best algorithm utilises the Shannon4 wavelet coupled to the support vector machine, where the latter is used as the classifier. In this case the algorithm, utilising only 22 othogonal features, achieves a 10-fold cross validation sensitivity and specificity of 0.96 and 0.87, resulting in a diagnostic-odds ratio of 261. The advantages of this method over diagnostic algorithms–which make a melanoma/no melanoma decision–are twofold: first, by reproducing the decision-making of a dermatologist, the average number of lesions excised per melanoma among practioners in general can be reduced without compromising the detection of melanoma; and second, the intractable problem of clinically differentiating between many atypical dysplastic naevi and melanoma is avoided. Since many atypical naevi that require excision on clinical grounds will not be melanoma, the algorithm–in contrast to diagnostic algorithms–can aim for perfect specificities without clinical concerns, thus lowering the excision rate of non-melanoma. Finally, the algorithm has been implemented as a smart phone application to investigate its utility in clinical practice and to streamline the assimilation of hitherto unseen tested images into the training set.

Pattern formation of stains from dried drops to identify spermatozoa motility

We study how cell motility affects the stains left by the evaporation of droplets of a biofluid suspension containing mouse spermatozoa. The suspension, which contains also a high concentration of salts usually needed by motile cells, forms, upon drying, a crystallized pattern. We examine the structural characteristics of such patterns by optical microscopy. The analysis reveals that cell motility affects the formation of elongated crystals with lateral tips, as well as the creation of interlocked aggregates. We prove that a lacunarity algorithm based on polar symmetry, distinguishes among deposits generated by motile and non-motile cells with an accuracy greater than 95%.

Iron oxide nanoparticles decrease nuclear fractal dimension of buccal epithelial cells in a time-dependent manner

In this paper, we present results that iron oxide nanoparticles (IONPs) induce time-dependent structural changes in nuclei of buccal epithelial cells. The cells were treated with magnetite, Fe₃ O₄ nanoparticles (spherical shape, diameter 80-100 nanometres). The digital micrographs of the nuclei were made in 3 different time points: 15, 30 and 60 min after the treatment with IONPs, as well as in the control cells. A total of 120 nuclear structures (30 per sample) were analysed. Fractal analysis of nuclei was done in ImageJ software of the National Institutes of Health, (Bethesda, MD, USA). For each nuclear structure, the values of fractal dimension and lacunarity were calculated. There was a time-dependent reduction of nuclear fractal dimension in buccal epithelial cells after exposure to magnetite iron oxide nanoparticles. Negative trend was observed (p < 0.01). Nuclear lacunarity, as another fractal parameter was shown to increase, also in a time-dependent manner, after the treatment with IONPs. To our knowledge, this is the first study to investigate effects of magnetite nanomaterial on nuclear fractal complexity, and also the first to apply fractal analysis method in testing of the interaction between nanoparticles and cell nucleus in this experimental setting.

A mathematical analysis of the ABCD criteria for diagnosing malignant melanoma

The medical community currently employs the ABCD (asymmetry, border irregularity, color variegation, and diameter of the lesion) criteria in the early diagnosis of a malignant melanoma. Although many image segmentation and classification methods are used to analyze the ABCD criteria, it is rare to see a study containing mathematical justification of the parameters that are used to quantify the ABCD criteria. In this paper, we suggest new parameters to assess asymmetry, border irregularity, and color variegation, and explain the mathematical meaning of the parameters. The suggested parameters are then tested with 24 skin samples. The parameters suggested for the 24 skin samples are displayed in three-dimensional coordinates and are compared to those presented in other studies (Ercal et al 1994 IEEE Trans. Biomed. Eng. 41 837-45, Cheerla and Frazier 2014 Int. J. Innovative Res. Sci., Eng. Technol. 3 9164-83) in terms of Pearson correlation coefficient and classification accuracy in determining the malignancy of the lesions.

Spatial intratumoral heterogeneity of proliferation in immunohistochemical images of solid tumors

PURPOSE

The interactions of neoplastic cells with each other and the microenvironment are complex. To understand intratumoral heterogeneity, subtle differences should be quantified. Main factors contributing to heterogeneity include the gradient ischemic level within neoplasms, action of microenvironment, mechanisms of intercellular transfer of genetic information, and differential mechanisms of modifications of genetic material/proteins. This may reflect on the expression of biomarkers in the context of prognosis/stratification. Hence, a rigorous approach for assessing the spatial intratumoral heterogeneity of histological biomarker expression with accuracy and reproducibility is required, since patterns in immunohistochemical images can be challenging to identify and describe.

METHODS

A quantitative method that is useful for characterizing complex irregular structures is lacunarity; it is a multiscale technique that exhaustively samples the image, while the decay of its index as a function of window size follows characteristic patterns for different spatial arrangements. In histological images, lacunarity provides a useful measure for the spatial organization of a biomarker when a sampling scheme is employed and relevant features are computed. The proposed approach quantifies the segmented proliferative cells and not the textural content of the histological slide, thus providing a more realistic measure of heterogeneity within the sample space of the tumor region. The aim is to investigate in whole sections of primary pancreatic neuroendocrine neoplasms (pNENs), using whole-slide imaging and image analysis, the spatial intratumoral heterogeneity of Ki-67 immunostains. Unsupervised learning is employed to verify that the approach can partition the tissue sections according to distributional heterogeneity.

RESULTS

The architectural complexity of histological images has shown that single measurements are often insufficient. Inhomogeneity of distribution depends not only on percentage content of proliferation phase but also on how the phase fills the space. Lacunarity curves demonstrate variations in the sampled image sections. Since the spatial distribution of proliferation in each case is different, the width of the curves changes too. Image sections that have smaller numerical variations in the computed features correspond to neoplasms with spatially homogeneous proliferation, while larger variations correspond to cases where proliferation shows various degrees of clumping. Grade 1 (uniform/nonuniform: 74%/26%) and grade 3 (uniform: 100%) pNENs demonstrate a more homogeneous proliferation with grade 1 neoplasms being more variant, while grade 2 tumor regions render a more diverse landscape (50%/50%). Hence, some cases show an increased degree of spatial heterogeneity comparing to others with similar grade. Whether this is a sign of different tumor biology and an association with a more benign/malignant clinical course needs to be investigated further. The extent and range of spatial heterogeneity has the potential to be evaluated as a prognostic marker.

CONCLUSIONS

The association with tumor grade as well as the rationale that the methodology reflects true tumor architecture supports the technical soundness of the method. This reflects a general approach which is relevant to other solid tumors and biomarkers. Drawing upon the merits of computational biomedicine, the approach uncovers salient features for use in future studies of clinical relevance.

Villus packing density and lacunarity: Markers of placental efficiency?

We evaluate, in routine H&E histology slides, villus quantity in a given area (villous packing density, VPD) and the pattern or "gappiness" of villous distribution (lacunarity), and test for correlations with a proxy for fetoplacental metabolic rate, β calculated as (ln (placental weight)/ln (birthweight)) from Kleiber's law [1]. Three ∼4.3 mm² images each were obtained from 88 term placentas. Ranges of VPD and lacunarity were each correlated with β (r = 0.31, p = 0.003, r = 0.23, p = 0.03 and respectively). The relationship between β and within-placenta variation in VPD and lacunarity highlights the need to study not merely the mean but the variance of villous geometries and spatial distributions.

Tug-of-war lacunarity-A novel approach for estimating lacunarity

Modern instrumentation provides us with massive repositories of digital images that will likely only increase in the future. Therefore, it has become increasingly important to automatize the analysis of digital images, e.g., with methods from pattern recognition. These methods aim to quantify the visual appearance of captured textures with quantitative measures. As such, lacunarity is a useful multi-scale measure of texture's heterogeneity but demands high computational efforts. Here we investigate a novel approach based on the tug-of-war algorithm, which estimates lacunarity in a single pass over the image. We computed lacunarity for theoretical and real world sample images, and found that the investigated approach is able to estimate lacunarity with low uncertainties. We conclude that the proposed method combines low computational efforts with high accuracy, and that its application may have utility in the analysis of high-resolution images.

Lacunarity analysis of atomic configurations: application to ethanol-water mixtures

Lacunarity analysis is a scale-dependent method quantifying the translational invariance in patterns. In this work it is used to characterize the distribution of several subsets of atoms in molecular systems. Binary clusters and one-component (ethanol or water) hydrogen-bonded clusters of ethanol-water mixtures with 0-100mol% ethanol content were analyzed. Molecular dynamics simulations created the configurations, and all were in good agreement with the respective experimental x-ray diffraction data. Lacunarity analysis revealed that the placement of the one-component clusters at low concentration can be described by a multifractal distribution, especially in the case of ethanol. Most of the cases these clusters are not isolated entities, but form islands in binary clusters.

Application of fractal and grey level co-occurrence matrix analysis in evaluation of brain corpus callosum and cingulum architecture

This aim of this study was to assess the discriminatory value of fractal and grey level co-occurrence matrix (GLCM) analysis methods in standard microscopy analysis of two histologically similar brain white mass regions that have different nerve fiber orientation. A total of 160 digital micrographs of thionine-stained rat brain white mass were acquired using a Pro-MicroScan DEM-200 instrument. Eighty micrographs from the anterior corpus callosum and eighty from the anterior cingulum areas of the brain were analyzed. The micrographs were evaluated using the National Institutes of Health ImageJ software and its plugins. For each micrograph, seven parameters were calculated: angular second moment, inverse difference moment, GLCM contrast, GLCM correlation, GLCM variance, fractal dimension, and lacunarity. Using the Receiver operating characteristic analysis, the highest discriminatory value was determined for inverse difference moment (IDM) (area under the receiver operating characteristic (ROC) curve equaled 0.925, and for the criterion IDM≤0.610 the sensitivity and specificity were 82.5 and 87.5%, respectively). Most of the other parameters also showed good sensitivity and specificity. The results indicate that GLCM and fractal analysis methods, when applied together in brain histology analysis, are highly capable of discriminating white mass structures that have different axonal orientation.

Computer aided diagnostic support system for skin cancer: a review of techniques and algorithms

Image-based computer aided diagnosis systems have significant potential for screening and early detection of malignant melanoma. We review the state of the art in these systems and examine current practices, problems, and prospects of image acquisition, pre-processing, segmentation, feature extraction and selection, and classification of dermoscopic images. This paper reports statistics and results from the most important implementations reported to date. We compared the performance of several classifiers specifically developed for skin lesion diagnosis and discussed the corresponding findings. Whenever available, indication of various conditions that affect the technique's performance is reported. We suggest a framework for comparative assessment of skin cancer diagnostic models and review the results based on these models. The deficiencies in some of the existing studies are highlighted and suggestions for future research are provided.

Age-related reduction of structural complexity in spleen hematopoietic tissue architecture in mice

The effects of aging on structural complexity in hematopoietic tissue are unknown. In this work, in a mouse experimental model, we report the age-related reduction of spleen hematopoietic tissue (SHT) complexity. Spleen tissue was obtained from the total of 64 male Swiss albino mice divided into 8 age groups: newborns (0 days old), 10 days, 20 days, 30 days, 120 days, 210 days, 300 and 390 days old. SHT was stained using conventional hematoxylin/eosin, and DNA-binding toluidine blue dyes. Fractal dimension as an indicator of cellular complexity, and lacunarity as indicator of tissue heterogeneity were determined based on the binarized SHT micrographs. Results indicate that fractal dimension of mice spleen hematopoietic tissue decreases with age, while lacunarity increases. These changes/trends have been detected in SHT stained both with toluidine blue and conventional hematoxylin/eosin. Fractal dimension was negatively correlated with lacunarity. The detected reduction in complexity suggests that age-related structural changes are present in mouse SHT both in general tissue architecture and progenitor cell DNA.

On the fractal geometry of DNA by the binary image analysis

The multifractal analysis of binary images of DNA is studied in order to define a methodological approach to the classification of DNA sequences. This method is based on the computation of some multifractality parameters on a suitable binary image of DNA, which takes into account the nucleotide distribution. The binary image of DNA is obtained by a dot-plot (recurrence plot) of the indicator matrix. The fractal geometry of these images is characterized by fractal dimension (FD), lacunarity, and succolarity. These parameters are compared with some other coefficients such as complexity and Shannon information entropy. It will be shown that the complexity parameters are more or less equivalent to FD, while the parameters of multifractality have different values in the sense that sequences with higher FD might have lower lacunarity and/or succolarity. In particular, the genome of Drosophila melanogaster has been considered by focusing on the chromosome 3r, which shows the highest fractality with a corresponding higher level of complexity. We will single out some results on the nucleotide distribution in 3r with respect to complexity and fractality. In particular, we will show that sequences with higher FD also have a higher frequency distribution of guanine, while low FD is characterized by the higher presence of adenine.

Effects of ghrelin on the structural complexity of exocrine pancreas tissue architecture

Recent studies have shown that ghrelin increases pancreatic exocrine secretion. However, the potential effects of ghrelin on the morphology of exocrine pancreas (EP) remain unknown. In this work, using fractal analysis, we demonstrate that centrally administered ghrelin increases structural complexity and tissue disorder in rat EP. The study was carried out on a total of 40 male Wistar rats divided into four groups (n = 10): ghrelin-treated animals (average age, 1.5 months), ghrelin-treated animals (8.5 months), and controls (1.5 and 8.5 months). The pancreas tissue sections were stained with hematoxylin/eosin and visualized by light microscopy. For each animal, the average values of tissue fractal dimension, lacunarity, as well as parameters of co-occurrence matrix texture, were determined using tissue digital micrographs. The results indicate that ghrelin administration increases EP fractal dimension and textural entropy, and decreases lacunarity, regardless of the age. To our knowledge, this is the first study to investigate the effects of ghrelin on the morphological properties of pancreatic tissue, and also the first to apply fractal and textural analysis methods in quantification of EP tissue architecture.

Biomaterial porosity determined by fractal dimensions, succolarity and lacunarity on microcomputed tomographic images

Porous structures are becoming more and more important in biology and material science because they help in reducing the density of the grafted material. For biomaterials, porosity also increases the accessibility of cells and vessels inside the grafted area. However, descriptors of porosity are scanty. We have used a series of biomaterials with different types of porosity (created by various porogens: fibers, beads …). Blocks were studied by microcomputed tomography for the measurement of 3D porosity. 2D sections were re-sliced to analyze the microarchitecture of the pores and were transferred to image analysis programs: star volumes, interconnectivity index, Minkowski-Bouligand and Kolmogorov fractal dimensions were determined. Lacunarity and succolarity, two recently described fractal dimensions, were also computed. These parameters provided a precise description of porosity and pores' characteristics. Non-linear relationships were found between several descriptors e.g. succolarity and star volume of the material. A linear correlation was found between lacunarity and succolarity. These techniques appear suitable in the study of biomaterials usable as bone substitutes.

Pattern analysis accounts for heterogeneity observed in MRI studies of tumor angiogenesis

MRI is a method of choice for assessing anatomical structures or angiogenesis-related parameters noninvasively during tumor progression. Typically, tumor tissue displays a high degree of heterogeneity that can be evaluated using pattern analysis (PA), which comprises shape and texture analysis. This work aims at implementing PA methods to study angiogenesis in a murine tumor model and testing its sensitivity with regard to detecting changes elicited by administration of a drug. Twelve balb/c-nude mice were injected subcutaneously with 10(6) C51 cells (colon carcinoma). A first group (N = 6) of animals was treated with dimethyloxalylglycine, a drug known to stabilize hypoxia-inducible-factor-α, which among other functions, is involved in angiogenesis. The second group (N = 6) was treated with saline. MRI experiments assessing tumor blood volume and permeability-maps (K(trans) ) were performed immediately before and 6 days after drug treatment. Data have been analyzed using standard histogram analysis and PA. Standard histogram analysis did not reveal any difference between the two groups, neither before nor after the treatment. In contrast, PA revealed significant differences between drug and placebo treated mice in the texture of the TBV and K(trans) maps after drug treatment, but not with regard to tumors shapes. The results indicated that in view of the heterogeneity of tumor tissue, standard histogram analysis appears insensitive in picking-up differences in response to treatment, while PA appears to be particularly sensitive to changes in texture.