Euclidean and fractal geometry of microvascular networks in normal and neoplastic pituitary tissue

A Nexus of Biomolecular Complexities in Pituitary Neuroendocrine Tumors: Insights into Key Molecular Drivers

Approximately 90% of the lesions of hypophyseal origins are represented by pituitary neuroendocrine tumors, which further account for up to 22.5% of the intracranial tumors in the adult population. Although the intricacy of this pathology is yet to be fully understood on a biomolecular level, it is well known that these lesions develop within a microenvironment that supports their evolution and existence. The role of the tumoral microenvironment in pituitary lesions is pivotal, mainly due to this gland's distinct anatomical, histological, and physiological structure and function. Each component of the tumoral microenvironment is specifically involved in tumorigenesis, angiogenesis, tumoral growth, progression, and dissemination. By recognizing and understanding how these elements are involved in such processes, targeted treatments can emerge, and better future management of pituitary lesions can be provided. This article aims to summarize the role of each component of the tumoral microenvironment in pituitary lesions while assessing their association with biomolecular mechanisms.

Study of prediction model for high-grade meningioma using fractal geometry combined with radiological features

PURPOSE

To establish a prediction model combining fractal geometry and radiological features, which consider the complexity of tumour morphology advancing beyond the limitations of previous models.

METHODS

A total of 227 patients at the First Affiliated Hospital of Harbin Medical University from July 2021 to November 2023 were included. Fractal geometry was calculated and the radiomics features were extracted from regions of interest (ROIs). Weighted Gene Co-Expression Network Analysis (WGCNA) was employed for preliminary screening to identify those that were significantly associated with high-grade meningioma. In the training cohort, the least absolute shrinkage and selection operator (LASSO) regression was employed for further screening the radiomics features. Area under curve (AUC) was to evaluate models' performance.

RESULTS

In entire patient cohort, low-grade meningiomas had significantly lower fractal dimensions (P = 0.01), while high-grade meningiomas had higher lacunarity (P = 0.049). Fractal dimension (OR 6.8, 95% CI 1.49-36.51, P = 0.017), lacunarity (OR 3.7, 95% CI 1.36-11.75, P = 0.014), and Rscore (OR 2.8, 95% CI 1.55-5.75, P = 0.002) were independent risk factors for high-grade meningiomas. The final results demonstrated that the "fractal geometry + radiological features (semantic features + radiomics features)" model exhibited the most optimal performance in predicting high-grade meningioma, with an AUC of 0.854 in the training cohort and 0.757 in the validation cohort.

CONCLUSION

Significant differences in fractal dimension and lacunarity exist between high-grade and low-grade meningiomas, which can be potential predictive factors. The developed predictive model demonstrated good performance in predicting high-grade meningiomas.

Fractal Analysis in Clinical Neurosciences: An Overview

Over the last years, fractals have entered into the realms of clinical neurosciences. The whole brain and its components (i.e., neurons and astrocytes) have been studied as fractal objects, and even more relevant, the fractal-based quantification of the geometrical complexity of histopathological and neuroradiological images as well as neurophysiopathological time series has suggested the existence of a gradient in the pattern representation of neurological diseases. Computational fractal-based parameters have been suggested as potential diagnostic and prognostic biomarkers in different brain diseases, including brain tumors, neurodegeneration, epilepsy, demyelinating diseases, cerebrovascular malformations, and psychiatric disorders as well. This chapter and the entire third section of this book are focused on practical applications of computational fractal-based analysis into the clinical neurosciences, namely, neurology and neuropsychiatry, neuroradiology and neurosurgery, neuropathology, neuro-oncology and neurorehabilitation, neuro-ophthalmology, and cognitive neurosciences, with special emphasis on the translation of the fractal dimension and other fractal parameters as clinical biomarkers useful from bench to bedside.

Fractals, Pattern Recognition, Memetics, and AI: A Personal Journal in the Computational Neurosurgery

In this chapter, the personal journey of the author in many countries, including Italy, Germany, Austria, the United Kingdom, Switzerland, the United States, Canada, and Australia, is summarized, aimed to merge different translational fields (such as neurosurgery and the clinical neurosciences in general, biomedical engineering, mathematics, computer science, and cognitive sciences) and lay the foundations of a new field defined computational neurosurgery, with fractals, pattern recognition, memetics, and artificial intelligence as the common key words of the journey.

Computational Fractal-Based Analysis of Brain Tumor Microvascular Networks

Brain parenchyma microvasculature is set in disarray in the presence of tumors, and malignant brain tumors are among the most vascularized neoplasms in humans. As microvessels can be easily identified in histologic specimens, quantification of microvascularity can be used alone or in combination with other histological features to increase the understanding of the dynamic behavior, diagnosis, and prognosis of brain tumors. Different brain tumors, and even subtypes of the same tumor, show specific microvascular patterns, as a kind of "microvascular fingerprint," which is particular to each histotype. Reliable morphometric parameters are required for the qualitative and quantitative characterization of the neoplastic angioarchitecture, although the lack of standardization of a technique able to quantify the microvascular patterns in an objective way has limited the "morphometric approach" in neuro-oncology.In this chapter, we focus on the importance of computational-based morphometrics, for the objective description of tumoral microvascular fingerprinting. By also introducing the concept of "angio-space," which is the tumoral space occupied by the microvessels, we here present fractal analysis as the most reliable computational tool able to offer objective parameters for the description of the microvascular networks.The spectrum of different angioarchitectural configurations can be quantified by means of Euclidean and fractal-based parameters in a multiparametric analysis, aimed to offer surrogate biomarkers of cancer. Such parameters are here described from the methodological point of view (i.e., feature extraction) as well as from the clinical perspective (i.e., relation to underlying physiology), in order to offer new computational parameters to the clinicians with the final goal of improving diagnostic and prognostic power of patients affected by brain tumors.

Biomarkers for Liquid Biopsies of Pituitary Neuroendocrine Tumors

Pituitary neuroendocrine tumors (PitNET) do not only belong to the most common intracranial neoplasms but seem to be generally more common than has been thought. Minimally invasive liquid biopsies have the potential to improve their early screening efficiency as well as monitor prognosis by facilitating the diagnostic procedures. This review aims to assess the potential of using liquid biopsies of different kinds of biomarker species that have only been obtained from solid pituitary tissues so far. Numerous molecules have been associated with the development of a PitNET, suggesting that it often develops from the cumulative effects of many smaller genetic or epigenetic changes. These minor changes eventually pile up to switch critical molecules into tumor-promoting states, which may be the key regulatory nodes representing the most potent marker substances for a diagnostic test. Drugs targeting these nodes may be superior for the therapeutic outcome and therefore the identification of such pituitary-specific cellular key nodes will help to accelerate their application in medicine. The ongoing genetic degeneration in pituitary adenomas suggests that repeated tumor profiling via liquid biopsies will be necessary for personalized and effective treatment solutions.

Biofabrication strategies for creating microvascular complexity

Design and fabrication of effective biomimetic vasculatures constitutes a relevant and yet unsolved challenge, lying at the heart of tissue repair and regeneration strategies. Even if cell growth is achieved in 3D tissue scaffolds or advanced implants, tissue viability inevitably requires vascularization, as diffusion can only transport nutrients and eliminate debris within a few hundred microns. This engineered vasculature may need to mimic the intricate branching geometry of native microvasculature, referred to herein as vascular complexity, to efficiently deliver blood and recreate critical interactions between the vascular and perivascular cells as well as parenchymal tissues. This review first describes the importance of vascular complexity in labs- and organs-on-chips, the biomechanical and biochemical signals needed to create and maintain a complex vasculature, and the limitations of current 2D, 2.5D, and 3D culture systems in recreating vascular complexity. We then critically review available strategies for design and biofabrication of complex vasculatures in cell culture platforms, labs- and organs-on-chips, and tissue engineering scaffolds, highlighting their advantages and disadvantages. Finally, challenges and future directions are outlined with the hope of inspiring researchers to create the reliable, efficient and sustainable tools needed for design and biofabrication of complex vasculatures.

Retinal capillary perfusion: Spatial and temporal heterogeneity

The central role of the cardiovascular system is to maintain adequate capillary perfusion. The spatially and temporally heterogeneous nature of capillary perfusion has been reported in some organs. However, such heterogeneous perfusion properties have not been sufficiently explored in the retina. Arguably, spatial and temporal heterogeneity of capillary perfusion could be more predominant in the retina than that in other organs. This is because the retina is one of the highest metabolic demand neural tissues yet it has a limited blood supply due to optical requirements. In addition, the unique heterogeneous distribution of retinal neural cells within different layers and regions, and the significant heterogeneity of intraretinal oxygen distribution and consumption add to the complexity. Retinal blood flow distribution must match consumption of nutrients such as oxygen and glucose within the retina at the cellular level in order to effectively maintain cell survival and function. Sophisticated local blood flow control in the microcirculation is likely required to control the retinal capillary perfusion to supply local retinal tissue and accommodate temporal and spatial variations in metabolic supply and demand. The authors would like to update the knowledge of the retinal microvessel and capillary network and retinal oxidative metabolism from their own studies and the work of others. The coupling between blood supply and energy demands in the retina is particularly interesting. We will mostly describe information regarding the retinal microvessel network and retinal oxidative metabolism relevant to the spatial and temporal heterogeneity of capillary perfusion. We believe that there is significant and necessary spatial and temporal heterogeneity and active regulation of retinal blood flow in the retina, particularly in the macular region. Recently, retinal optical coherence tomography angiography (OCTA) has been widely used in ophthalmology, both experimentally and clinically. OCTA could be a valuable tool for examining retinal microvessel and capillary network structurally and has potential for determining retinal capillary perfusion and its control. We have demonstrated spatial and temporal heterogeneity of capillary perfusion in the retina both experimentally and clinically. We have also found close relationships between the smallest arterioles and capillaries within paired arterioles and venules and determined the distribution of smooth muscle cell contraction proteins in these vessels. Spatial and temporal heterogeneity of retinal capillary perfusion could be a useful parameter to determine retinal microvessel regulatory capability as an early assay for retinal vascular diseases. This topic will be of great interest, not only for the eye but also other organs. The retina could be the best model for such investigations. Unlike cerebral vessels, retinal vessels can be seen even at the capillary level. The purpose of this manuscript is to share our current understanding with the readers and encourage more researchers and clinicians to investigate this field. We begin by reviewing the general principles of microcirculation properties and the spatial and temporal heterogeneity of the capillary perfusion in other organs, before considering the special requirements of the retina. The local heterogeneity of oxygen supply and demand in the retina and the need to have a limited and well-regulated retinal circulation to preserve the transparency of the retina is discussed. We then consider how such a delicate balance of metabolic supply and consumption is achieved. Finally we discuss how new imaging methodologies such as optical coherence tomography angiography may be able to detect the presence of spatial and temporal heterogeneity of capillary perfusion in a clinical setting. We also provide some new information of the control role of very small arterioles in the modulation of retinal capillary perfusion which could be an interesting topic for further investigation.

Early and delayed evaluation of solid tumours with 64Cu-ATSM PET/CT: a pilot study on semiquantitative and computer-aided fractal geometry analysis

OBJECTIVE

The aim of this study was to analyse early and delayed acquisition on copper-64 diacetyl-bisN4-methylthiosemicarbazone (Cu-ATSM) PET/CT in a small cohort of patients by comparing semiquantitative and computer-aided fractal geometry analyses.

PATIENTS AND METHODS

Five cancer patients, including non-small-cell lung cancer and head and neck cancer, were investigated with Cu-ATSM PET/CT. Participants received an intravenous injection of Cu-ATSM according to body size and were imaged 60 min (early) and 16 h (delayed) later on hybrid PET/CT. Reconstructed images were visualized on advanced workstations for the definition of semiquantitative parameters: standardized uptake value (SUV)max, SUVratio-to-muscle, SUVmean, hypoxic volume (HV) and hypoxic burden (HB=HV×SUVmean). DICOM data retrieved from both scans were analysed using an ad-hoc computer program to determine the mean intensity value, SD, relative dispersion, three-dimensional histogram fractal dimension and three-dimensional fractal dimension.

RESULTS

All tumour lesions showed increased uptake of Cu-ATSM at early evaluation, with a median SUVratio-to-muscle of 4.42 (range: 1.58-5.62), a median SUVmax of 5.3 (range: 1.9-7.3), a median SUVmean of 2.8 (range: 1.5-3.9), a median HV of 41.6 cm (range: 2.8-453.7) and a median HB of 161.5 cm (range: 4.4-1112.5). All semiquantitative data obtained at 1 h were consistent with the parameters obtained on delayed imaging (P>0.05). A borderline statistically significant difference was found only for SUVmax of the muscle (P=0.045). Fractal geometry analysis on DICOM images showed that all parameters at early imaging showed no statistically significant difference with late acquisition (P>0.05).

CONCLUSION

Our findings support the consistency of Cu-ATSM PET/CT images obtained at early and delayed acquisition for the assessment of tumour lesions.

Unique fractal evaluation and therapeutic implications of mitochondrial morphology in malignant mesothelioma

Malignant mesothelioma (MM), is an intractable disease with limited therapeutic options and grim survival rates. Altered metabolic and mitochondrial functions are hallmarks of MM and most other cancers. Mitochondria exist as a dynamic network, playing a central role in cellular metabolism. MM cell lines display a spectrum of altered mitochondrial morphologies and function compared to control mesothelial cells. Fractal dimension and lacunarity measurements are a sensitive and objective method to quantify mitochondrial morphology and most importantly are a promising predictor of response to mitochondrial inhibition. Control cells have high fractal dimension and low lacunarity and are relatively insensitive to mitochondrial inhibition. MM cells exhibit a spectrum of sensitivities to mitochondrial inhibitors. Low mitochondrial fractal dimension and high lacunarity correlates with increased sensitivity to the mitochondrial inhibitor metformin. Lacunarity also correlates with sensitivity to Mdivi-1, a mitochondrial fission inhibitor. MM and control cells have similar sensitivities to cisplatin, a chemotherapeutic agent used in the treatment of MM. Neither oxidative phosphorylation nor glycolytic activity, correlated with sensitivity to either metformin or mdivi-1. Our results suggest that mitochondrial inhibition may be an effective and selective therapeutic strategy in mesothelioma, and identifies mitochondrial morphology as a possible predictor of response to targeted mitochondrial inhibition.

Lung cancer-a fractal viewpoint

Fractals are mathematical constructs that show self-similarity over a range of scales and non-integer (fractal) dimensions. Owing to these properties, fractal geometry can be used to efficiently estimate the geometrical complexity, and the irregularity of shapes and patterns observed in lung tumour growth (over space or time), whereas the use of traditional Euclidean geometry in such calculations is more challenging. The application of fractal analysis in biomedical imaging and time series has shown considerable promise for measuring processes as varied as heart and respiratory rates, neuronal cell characterization, and vascular development. Despite the advantages of fractal mathematics and numerous studies demonstrating its applicability to lung cancer research, many researchers and clinicians remain unaware of its potential. Therefore, this Review aims to introduce the fundamental basis of fractals and to illustrate how analysis of fractal dimension (FD) and associated measurements, such as lacunarity (texture) can be performed. We describe the fractal nature of the lung and explain why this organ is particularly suited to fractal analysis. Studies that have used fractal analyses to quantify changes in nuclear and chromatin FD in primary and metastatic tumour cells, and clinical imaging studies that correlated changes in the FD of tumours on CT and/or PET images with tumour growth and treatment responses are reviewed. Moreover, the potential use of these techniques in the diagnosis and therapeutic management of lung cancer are discussed.

Aggressive pituitary adenomas--diagnosis and emerging treatments

The WHO categorizes pituitary tumours as typical adenomas, atypical adenomas and pituitary carcinomas, with typical adenomas constituting the major class. However, the WHO classification does not provide an accurate correlation between histopathological findings and clinical behaviour. Tumours lacking typical histological features are classified as atypical, but not all are clinically atypical or exhibit aggressive behaviour. Pituitary carcinomas, by definition, have craniospinal or systemic metastases, although not all display classical cytological features of malignancy. Aggressive pituitary adenomas, defined from a clinical perspective, have earlier and more frequent recurrences and can be resistant to conventional treatments. Specific biomarkers have not yet been identified that can distinguish between clinically aggressive and nonaggressive pituitary adenomas, although the antigen Ki-67 proliferation index might be of value. This Review highlights the need to develop new biomarkers to facilitate the early detection of clinically aggressive pituitary adenomas and discusses emerging markers that hold promise for their identification. Defining aggressiveness is of crucial importance for improving the management of patients by enhancing prognostic predictions and effectiveness of treatment. New drugs, such as temozolomide, have potential use in the management of these patients; anti-VEGF therapy, mTOR and tyrosine kinase inhibitors are also potentially useful in managing selected patients.

Microvascular morphometrics of the hypophysis and pituitary tumors: from bench to operating theatre

The idea that microvasculature might be a histopathological biomarker in the prognosis and treatment of tumors is garnering even more attention in the scientific community. The roles of neovascularity in tumor progression and metastasis, have become a hot-topic of investigation in cancer research. A number of methods of quantitatively analyzing pituitary adenoma microvasculature have been applied, and fractal analysis is emerging as a potential effective model for this aim. Additionally, new and more specific immunological techniques have been developed for the detection of microvessels. CD105 (Endoglin) has been proposed as a valuable antigen that marks only newly formed vessels, rather than the entire tumor microvascular system. The combination of different types of immunostaining techniques for the detection of microvessels in pituitary adenomas with fractal analysis as an objective and computer-aided technique to quantify and describe morphological aspects of microvessels has potential implications in future clinical and surgical applications. Tumor treatments, such as anti-angiogenic therapy, as well as intraoperative tools, stand to be enhanced by increasing advances in microvascular research. We here review the methods used for the quantitative analysis of microvessels of the pituitary in its physiopathological states, with the aim to show the pituitary adenoma as a model for the study of neoplastic angioarchitecture and the importance of the introduction of new techniques for the study of angiogenesis, with the relative scientific, medical and surgical implications.

Enhanced nestin expression and small blood vessels in human pituitary adenomas

The role of angiogenesis in human pituitary tumor progression is questioned. Our aim was to characterize the morphologic changes that occur in the vasculature of pituitary adenomas, in correlation with the expression of nestin, a protein found in endothelial cells of newly formed vessels of developing organs. We also evaluated the relation of angiogenic markers and nestin with Ki-67 index. Immunohistochemical studies were performed on paraffin embedded samples of 47 pituitary adenomas and six normal pituitaries. We determined microvessel density (number of CD31+ or CD34+ vessels per square millimetre), vascular area (cumulative area occupied by vessels), average vessel size, and further classified vessels as small (< 100 μm2) or large (> 100 μm2). We correlated the above parameters with nestin expression and Ki-67 index. Lower vascular area compared to normal tissue was found in adenomas (p < 0.05). Interestingly, pituitary adenomas had significantly more small vessels than control pituitaries (p < 0.04 for CD31 and CD34). In tumors many capillaries were positive for nestin, while scarce staining was detected in controls, so that nestin positive area was significantly higher in tumors. Furthermore, nestin area correlated positively with the % of small vessels. Ki-67 correlated neither with vascular area nor with nestin expression. In human pituitary tumors there was a predominance of small capillaries in correlation with increased expression of the progenitor marker nestin. We suggest that angiogenesis is an active process in these tumors, in spite of their low total vascular area when compared to normal pituitaries.

Systems toxicology from genes to organs

This unique overview of systems toxicology methods and techniques begins with a brief account of systems thinking in biology over the last century. We discuss how systems biology and toxicology continue to leverage advances in computational modeling, informatics, large-scale computing, and biotechnology. Next, we chart the genesis of systems toxicology from previous work in physiologically based models, models of early development, and more recently, molecular systems biology. For readers interested in further details this background provides useful linkages to the relevant literature. It also lays the foundations for new ideas in systems toxicology that could translate laboratory measurements of molecular responses from xenobiotic perturbations to adverse organ level effects in humans. By providing innovative solutions across disciplinary boundaries and highlighting key scientific gaps, we believe this chapter provides useful information about the current state, and valuable insight about future directions in systems toxicity.

An imaging-based stochastic model for simulation of tumour vasculature

A mathematical model which reconstructs the structure of existing vasculature using patient-specific anatomical, functional and molecular imaging as input was developed. The vessel structure is modelled according to empirical vascular parameters, such as the mean vessel branching angle. The model is calibrated such that the resultant oxygen map modelled from the simulated microvasculature stochastically matches the input oxygen map to a high degree of accuracy (R(2) ≈ 1). The calibrated model was successfully applied to preclinical imaging data. Starting from the anatomical vasculature image (obtained from contrast-enhanced computed tomography), a representative map of the complete vasculature was stochastically simulated as determined by the oxygen map (obtained from hypoxia [(64)Cu]Cu-ATSM positron emission tomography). The simulated microscopic vasculature and the calculated oxygenation map successfully represent the imaged hypoxia distribution (R(2) = 0.94). The model elicits the parameters required to simulate vasculature consistent with imaging and provides a key mathematical relationship relating the vessel volume to the tissue oxygen tension. Apart from providing an excellent framework for visualizing the imaging gap between the microscopic and macroscopic imagings, the model has the potential to be extended as a tool to study the dynamics between the tumour and the vasculature in a patient-specific manner and has an application in the simulation of anti-angiogenic therapies.

Inhibitory effects of antivascular endothelial growth factor strategies in experimental dopamine-resistant prolactinomas

Prolactin-secreting adenomas are the most frequent type among pituitary tumors, and pharmacological therapy with dopamine agonists remains the mainstay of treatment. But some adenomas are resistant, and a decrease in the number or function of dopamine D2 receptors (D2Rs) has been described in these cases. D2R knockout [Drd2(-/-)] mice have chronic hyperprolactinemia and pituitary hyperplasia and provide an experimental model for dopamine agonist-resistant prolactinomas. We described previously that disruption of D2Rs increases vascular endothelial growth factor (VEGF) expression. We therefore designed two strategies of antiangiogenesis using prolactinomas generated in Drd2(-/-) female mice: direct intra-adenoma mVEGF R1 (Flt-1)/Fc chimera (VEGF-TRAP) injection for 3 weeks [into subcutaneously transplanted pituitaries from Drd2(-/-) mice] and systemic VEGF neutralization with the specific monoclonal antibody G6-31. Both strategies resulted in substantial decrease of prolactin content and lactotrope area, and a reduction in tumor size was observed in in situ prolactinomas. There were significant decreases in vascularity, evaluated by cluster of differentiation molecule 31 vessel staining, and proliferation (proliferating cell nuclear antigen staining) in response to both anti-VEGF treatments. These data demonstrate that the antiangiogenic approach was effective in inhibiting the growth of in situ dopamine-resistant prolactinomas as well as in the transplanted adenomas. No differences in VEGF protein expression were observed after either anti-VEGF treatment, and, although serum VEGF was increased in G6-31-treated mice, pituitary activation of the VEGF receptor 2 signaling pathway was reduced. Our results indicate that, even though the role of angiogenesis in pituitary adenomas is contentious, VEGF might contribute to adequate vascular supply and represent a supplementary therapeutic target in dopamine agonist-resistant prolactinomas.

Correlation of microvascular fractal dimension with positron emission tomography [(11)C]-methionine uptake in glioblastoma multiforme: preliminary findings

Neuroradiological and metabolic imaging is a fundamental diagnostic procedure in the assessment of patients with primary and metastatic brain tumors. The correlation between objective parameters capable of quantifying the neoplastic angioarchitecture and imaging data may improve our understanding of the underlying physiopathology and make it possible to evaluate treatment efficacy in brain tumors. Only a few studies have so far correlated the quantitative parameters measuring the neovascularity of brain tumors with the metabolic profiles measured by means of amino acid uptake in positron emission tomography (PET) scans. Fractal geometry offers new mathematical tools for the description and quantification of complex anatomical systems, including microvascularity. In this study, we evaluated the microvascular network complexity of six cases of human glioblastoma multiforme quantifying the surface fractal dimension on CD34 immunostained specimens. The microvascular fractal dimension was estimated by applying the box-counting algorithm. As the fractal dimension depends on the density, size and shape of the vessels, and their distribution pattern, we defined it as an index of the whole complexity of microvascular architecture and compared it with the uptake of (11)C-methionine (MET) assessed by PET. The different fractal dimension values observed showed that the same histological category of brain tumor had different microvascular network architectures. Fractal dimension ranged between 1.19 and 1.77 (mean: 1.415+/-0.225), and the uptake of (11)C-methionine ranged between 1.30 and 5.30. A statistically significant direct correlation between the microvascular fractal dimension and the uptake of (11)C-methionine (p=0.02) was found. Our preliminary findings indicate that that vascularity (estimated on the histologic specimens by means of the fractal dimension) and (11)C-methionine uptake (assessed by PET) closely correlate in glioblastoma multiforme and that microvascular fractal dimension can be a useful parameter to objectively describe and quantify the geometrical complexity of the microangioarchitecture in glioblastoma multiforme.

VEGF and CD31 association in pituitary adenomas

Pituitary tumors are usually less vascularized than the normal pituitary, and the role of angiogenesis in these adenomas is contentious. Appraisal of microvascular density and expression of the potent angiogenic vascular endothelial growth factor (VEGF) by immunohistochemistry has yielded controversial results, as a broad spectrum of immunostaining can be found. We determined the protein expression of VEGF and CD31, an endothelial marker, in a series of 56 surgically removed pituitary adenomas using Western blot assay. Prolactinomas had higher VEGF protein expression compared to nonfunctioning or ACTH- and GH-secreting adenomas, while CD31 was similar in the different adenoma histotypes. VEGF and CD31 were not affected by sex, age, years of adenoma evolution, or proliferation rate (Ki67 and PCNA) for all adenoma types. Only in nonfunctioning adenomas CD31 concentration increased significantly with age. There was a positive correlation between CD31 and VEGF expression when all adenoma histotypes were considered, or when prolactinomas and nonfunctioning adenomas were evaluated separately. The positive association of VEGF and CD31 expression suggests the participation of angiogenesis in adenoma development, while epithelial cell proliferation in pituitary tumors is not directly related to VEGF or CD31 expression, and other factors, such as primary genetic alterations may be involved.

The role of interleukin-6 in the formation of the coronary vasculature

The formation and the patterning of the coronary vasculature are critical to the development and pathology of the heart. Alterations in cytokine signaling and biomechanical load can alter the vascular distribution of the vessels within the heart. Changes in the physical patterning of the vasculature can have significant impacts on the relationships of the pressure-flow network and distribution of critical growth and survival factors to the tissue. Interleukin-6 (IL-6) is a pleiotropic cytokine that regulates several biological processes, including vasculogenesis. Using both immunohistological and cardioangiographic analyses, we tested the hypothesis that IL-6-loss will result in decreased vessel density, along with changes in vascular distribution. Moreover, given the impact of vascular patterning on pressure-flow and distribution mechanics, we utilized non-Euclidean geometrical fractal analysis to quantify the changes in patterning resulting from IL-6-loss. Our analyses revealed that IL-6-loss results in a decreased capillary density and increase in intercapillary distances, but does not alter vessel size or diameter. We also observed that the IL-6-/- coronary vasculature had a marked increase in fractal dimension (D value), indicating that IL-6-loss alters vascular patterning. Characterization of IL-6-loss on coronary vasculature may lend insight into the role of IL-6 in the formation and patterning of the vascular bed.

Fractal analysis of two-dimensional vascularity in primary prostate cancer and surrounding non-tumoral parenchyma

Prostate cancer is the fifth most frequent cancer in the world. However, none of the actual prognostic factors provide a valid index for predicting patient outcome. Here, we evaluate the two-dimensional vascularity in primary prostate tumors and surrounding non-tumoral parenchyma by means of fractal geometry, and assess any correlations between the results and some clinical and pathological parameters of prostate carcinoma. Prostate sections from 27 carcinoma patients were treated with CD34 antibodies. Two >10mm(2) areas of tumoral and surrounding non-tumoral parenchyma were digitized using an image analysis system that automatically quantified the fractal dimension of the vascular surface. Data were correlated with patient's age, PSA level, clinical and pathological stage, Gleason score, tumor volume, vascular invasion, surgical margins, and biochemical relapse. Two groups of patients were distinguished on the basis of whether the fractal dimension of their tumoral vascular surface was higher (group 1) or lower (group 2) than that of the surrounding non-tumoral parenchyma. Statistically significant between-group differences were found in terms of serum PSA levels (p=0.0061), tumor volume (p=0.0017), and biochemical relapse (p=0.031). The patients in group 2 had a poorer outcome. Our findings suggest a group of prostate cancer patients with a poor outcome, and the vascular surface fractal dimension as a helpful geometrical index in clinical practice.