3D Bioprinting as a Powerful Technique for Recreating the Tumor Microenvironment.

In vitro three-dimensional models aim to reduce and replace animal testing and establish new tools for oncology research and the development and testing of new anticancer therapies. Among the various techniques to produce more complex and realistic cancer models is bioprinting, which allows the realization of spatially controlled hydrogel-based scaffolds, easily incorporating different types of cells in order to recreate the crosstalk between cancer and stromal components. Bioprinting exhibits other advantages, such as the production of large constructs, the repeatability and high resolution of the process, as well as the possibility of vascularization of the models through different approaches. Moreover, bioprinting allows the incorporation of multiple biomaterials and the creation of gradient structures to mimic the heterogeneity of the tumor microenvironment. The aim of this review is to report the main strategies and biomaterials used in cancer bioprinting. Moreover, the review discusses several bioprinted models of the most diffused and/or malignant tumors, highlighting the importance of this technique in establishing reliable biomimetic tissues aimed at improving disease biology understanding and high-throughput drug screening.

A Human Ovarian Tumor & Liver Organ-on-Chip for Simultaneous and More Predictive Toxo-Efficacy Assays.

In oncology, the poor success rate of clinical trials is becoming increasingly evident due to the weak predictability of preclinical assays, which either do not recapitulate the complexity of human tissues (i.e., in vitro tests) or reveal species-specific outcomes (i.e., animal testing). Therefore, the development of novel approaches is fundamental for better evaluating novel anti-cancer treatments. Here, a multicompartmental organ-on-chip (OOC) platform was adopted to fluidically connect 3D ovarian cancer tissues to hepatic cellular models and resemble the systemic cisplatin administration for contemporarily investigating drug efficacy and hepatotoxic effects in a physiological context. Computational fluid dynamics was performed to impose capillary-like blood flows and predict cisplatin diffusion. After a cisplatin concentration screening using 2D/3D tissue models, cytotoxicity assays were conducted in the multicompartmental OOC and compared with static co-cultures and dynamic single-organ models. A linear decay of SKOV-3 ovarian cancer and HepG2 liver cell viability was observed with increasing cisplatin concentration. Furthermore, 3D ovarian cancer models showed higher drug resistance than the 2D model in static conditions. Most importantly, when compared to clinical therapy, the experimental approach combining 3D culture, fluid-dynamic conditions, and multi-organ connection displayed the most predictive toxicity and efficacy results, demonstrating that OOC-based approaches are reliable 3Rs alternatives in preclinic.

A new tool for assessing Pectus Excavatum by a semi-automatic image processing pipeline calculating the classical severity indexes and a new marker: the Volumetric Correction Index.

BACKGROUND: In clinical assessment of Pectus Excavatum (PE), the indication to surgery is based not only on symptoms but also on quantitative markers calculated from Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) scans. According to clinical routine, these indexes are measured manually by radiologists with limited computer support. This process is time consuming and potentially subjected to inaccuracy and individual variability in measurements. Moreover, the existing indexes have limitations, since they are based on linear measurements performed on single slices rather than on volumetric data derived from all the thoracic scans. RESULTS: In this paper we present an image processing pipeline aimed at providing radiologists with a computer-aid tool in support of diagnosis of PE patients developed in MATLAB® and conceived for MRI images. This framework has a dual purpose: (i) to automatize computation of clinical indexes with a view to ease and standardize pre-operative evaluation; (ii) to propose a new marker of pathological severity based on volumetric analysis and overcoming the limitations of existing axial slice-based indexes. Final designed framework is semi-automatic, requiring some user interventions at crucial steps: this is realized through a Graphical User Interface (GUI) that simplifies the interaction between the user and the tools. We tested our pipeline on 50 pediatric patients from Gaslini Children's Hospital and performed manual computation of indexes, comparing the results between the proposed tool and gold-standard clinical practice. Automatic indexes provided by our algorithm have shown good agreement with manual measurements by two independent readers. Moreover, the new proposed Volumetric Correction Index (VCI) has exhibited good correlation with standardized markers of pathological severity, proving to be a potential innovative tool for diagnosis, treatment, and follow-up. CONCLUSIONS: Our pipeline represents an innovative image processing in PE evaluation, based on MRI images (radiation-free) and providing the clinician with a quick and accurate tool for automatically calculating the classical PE severity indexes and a new more comprehensive marker: the Volumetric Correction Index.

High blood flow shear stress values are associated with circulating tumor cells cluster disaggregation in a multi-channel microfluidic device.

Metastasis represents a dynamic succession of events involving tumor cells which disseminate through the organism via the bloodstream. Circulating tumor cells (CTCs) can flow the bloodstream as single cells or as multicellular aggregates (clusters), which present a different potential to metastasize. The effects of the bloodstream-related physical constraints, such as hemodynamic wall shear stress (WSS), on CTC clusters are still unclear. Therefore, we developed, upon theoretical and CFD modeling, a new multichannel microfluidic device able to simultaneously reproduce different WSS characterizing the human circulatory system, where to analyze the correlation between SS and CTC clusters behavior. Three physiological WSS levels (i.e. 2, 5, 20 dyn/cm2) were generated, reproducing values typical of capillaries, veins and arteries. As first validation, triple-negative breast cancer cells (MDA-MB-231) were injected as single CTCs showing that higher values of WSS are correlated with a decreased viability. Next, the SS-mediated disaggregation of CTC clusters was computationally investigated in a vessels-mimicking domain. Finally, CTC clusters were injected within the three different circuits and subjected to the three different WSS, revealing that increasing WSS levels are associated with a raising clusters disaggregation after 6 hours of circulation. These results suggest that our device may represent a valid in vitro tool to carry out systematic studies on the biological significance of blood flow mechanical forces and eventually to promote new strategies for anticancer therapy.

3D Perfusable Hydrogel Recapitulating the Cancer Dynamic Environment to in Vitro Investigate Metastatic Colonization.

Metastasis is a dynamic process involving the dissemination of circulating tumor cells (CTCs) through blood flow to distant tissues within the body. Nevertheless, the development of an in vitro platform that dissects the crucial steps of metastatic cascade still remains a challenge. We here developed an in vitro model of extravasation composed of (i) a single channel-based 3D cell laden hydrogel representative of the metastatic site, (ii) a circulation system recapitulating the bloodstream where CTCs can flow. Two polymers (i.e., fibrin and alginate) were tested and compared in terms of mechanical and biochemical proprieties. Computational fluid-dynamic (CFD) simulations were also performed to predict the fluid dynamics within the polymeric matrix and, consequently, the optimal culture conditions. Next, once the platform was validated through perfusion tests by fluidically connecting the hydrogels with the external circuit, highly metastatic breast cancer cells (MDA-MB-231) were injected and exposed to physiological wall shear stress (WSS) conditions (5 Dyn/cm2) to assess their migration toward the hydrogel. Results indicated that CTCs arrested and colonized the polymeric matrix, showing that this platform can be an effective fluidic system to model the first steps occurring during the metastatic cascade as well as a potential tool to in vitro elucidate the contribution of hemodynamics on cancer dissemination to a secondary site.

A new cell-laden 3D Alginate-Matrigel hydrogel resembles human breast cancer cell malignant morphology, spread and invasion capability observed "in vivo".

Purpose of this study was the development of a 3D material to be used as substrate for breast cancer cell culture. We developed composite gels constituted by different concentrations of Alginate (A) and Matrigel (M) to obtain a structurally stable-in-time and biologically active substrate. Human aggressive breast cancer cells (i.e. MDA-MB-231) were cultured within the gels. Known the link between cell morphology and malignancy, cells were morphologically characterized and their invasiveness correlated through an innovative bioreactor-based invasion assay. A particular type of gel (i.e. 50% Alginate, 50% Matrigel) emerged thanks to a series of significant results: 1. cells exhibited peculiar cytoskeleton shapes and nuclear fragmentation characteristic of their malignancy; 2. cells expressed the formation of the so-called invadopodia, actin-based protrusion of the plasma membrane through which cells anchor to the extracellular matrix; 3. cells were able to migrate through the gels and attach to an engineered membrane mimicking the vascular walls hosted within bioreactor, providing a completely new 3D in vitro model of the very precursor steps of metastasis.

SEEG assistant: a 3DSlicer extension to support epilepsy surgery.

BACKGROUND: In the evaluation of Stereo-Electroencephalography (SEEG) signals, the physicist's workflow involves several operations, including determining the position of individual electrode contacts in terms of both relationship to grey or white matter and location in specific brain regions. These operations are (i) generally carried out manually by experts with limited computer support, (ii) hugely time consuming, and (iii) often inaccurate, incomplete, and prone to errors. RESULTS: In this paper we present SEEG Assistant, a set of tools integrated in a single 3DSlicer extension, which aims to assist neurosurgeons in the analysis of post-implant structural data and hence aid the neurophysiologist in the interpretation of SEEG data. SEEG Assistant consists of (i) a module to localize the electrode contact positions using imaging data from a thresholded post-implant CT, (ii) a module to determine the most probable cerebral location of the recorded activity, and (iii) a module to compute the Grey Matter Proximity Index, i.e. the distance of each contact from the cerebral cortex, in order to discriminate between white and grey matter location of contacts. Finally, exploiting 3DSlicer capabilities, SEEG Assistant offers a Graphical User Interface that simplifies the interaction between the user and the tools. SEEG Assistant has been tested on 40 patients segmenting 555 electrodes, and it has been used to identify the neuroanatomical loci and to compute the distance to the nearest cerebral cortex for 9626 contacts. We also performed manual segmentation and compared the results between the proposed tool and gold-standard clinical practice. As a result, the use of SEEG Assistant decreases the post implant processing time by more than 2 orders of magnitude, improves the quality of results and decreases, if not eliminates, errors in post implant processing. CONCLUSIONS: The SEEG Assistant Framework for the first time supports physicists by providing a set of open-source tools for post-implant processing of SEEG data. Furthermore, SEEG Assistant has been integrated into 3D Slicer, a software platform for the analysis and visualization of medical images, overcoming limitations of command-line tools.

Microenvironment complexity and matrix stiffness regulate breast cancer cell activity in a 3D in vitro model.

Three-dimensional (3D) cell cultures represent fundamental tools for the comprehension of cellular phenomena both in normal and in pathological conditions. In particular, mechanical and chemical stimuli play a relevant role on cell fate, cancer onset and malignant evolution. Here, we use mechanically-tuned alginate hydrogels to study the role of substrate elasticity on breast adenocarcinoma cell activity. The hydrogel elastic modulus (E) was measured via atomic force microscopy (AFM) and a remarkable range (150-4000 kPa) was obtained. A breast cancer cell line, MCF-7, was seeded within the 3D gels, on standard Petri and alginate-coated dishes (2D controls). Cells showed dramatic morphological differences when cultured in 3D versus 2D, exhibiting a flat shape in both 2D conditions, while maintaining a circular, spheroid-organized (cluster) conformation within the gels, similar to those in vivo. Moreover, we observed a strict correlation between cell viability and substrate elasticity; in particular, the number of MCF-7 cells decreased constantly with increasing hydrogel elasticity. Remarkably, the highest cellular proliferation rate, associated with the formation of cell clusters, occurred at two weeks only in the softest hydrogels (E = 150-200 kPa), highlighting the need to adopt more realistic and a priori defined models for in vitro cancer studies.

Automatic segmentation of deep intracerebral electrodes in computed tomography scans.

BACKGROUND: Invasive monitoring of brain activity by means of intracerebral electrodes is widely practiced to improve pre-surgical seizure onset zone localization in patients with medically refractory seizures. Stereo-Electroencephalography (SEEG) is mainly used to localize the epileptogenic zone and a precise knowledge of the location of the electrodes is expected to facilitate the recordings interpretation and the planning of resective surgery. However, the localization of intracerebral electrodes on post-implant acquisitions is usually time-consuming (i.e., manual segmentation), it requires advanced 3D visualization tools, and it needs the supervision of trained medical doctors in order to minimize the errors. In this paper we propose an automated segmentation algorithm specifically designed to segment SEEG contacts from a thresholded post-implant Cone-Beam CT volume (0.4 mm, 0.4 mm, 0.8 mm). The algorithm relies on the planned position of target and entry points for each electrode as a first estimation of electrode axis. We implemented the proposed algorithm into DEETO, an open source C++ prototype based on ITK library. RESULTS: We tested our implementation on a cohort of 28 subjects in total. The experimental analysis, carried out over a subset of 12 subjects (35 multilead electrodes; 200 contacts) manually segmented by experts, show that the algorithm: (i) is faster than manual segmentation (i.e., less than 1s/subject versus a few hours) (ii) is reliable, with an error of 0.5 mm ± 0.06 mm, and (iii) it accurately maps SEEG implants to their anatomical regions improving the interpretability of electrophysiological traces for both clinical and research studies. Moreover, using the 28-subject cohort we show here that the algorithm is also robust (error < 0.005 mm) against deep-brain displacements (< 12 mm) of the implanted electrode shaft from those planned before surgery. CONCLUSIONS: Our method represents, to the best of our knowledge, the first automatic algorithm for the segmentation of SEEG electrodes. The method can be used to accurately identify the neuroanatomical loci of SEEG electrode contacts by a non-expert in a fast and reliable manner.

Survival Online: a web-based service for the analysis of correlations between gene expression and clinical and follow-up data.

BACKGROUND: Complex microarray gene expression datasets can be used for many independent analyses and are particularly interesting for the validation of potential biomarkers and multi-gene classifiers. This article presents a novel method to perform correlations between microarray gene expression data and clinico-pathological data through a combination of available and newly developed processing tools. RESULTS: We developed Survival Online (available at http://ada.dist.unige.it:8080/enginframe/bioinf/bioinf.xml), a Web-based system that allows for the analysis of Affymetrix GeneChip microarrays by using a parallel version of dChip. The user is first enabled to select pre-loaded datasets or single samples thereof, as well as single genes or lists of genes. Expression values of selected genes are then correlated with sample annotation data by uni- or multi-variate Cox regression and survival analyses. The system was tested using publicly available breast cancer datasets and GO (Gene Ontology) derived gene lists or single genes for survival analyses. CONCLUSION: The system can be used by bio-medical researchers without specific computation skills to validate potential biomarkers or multi-gene classifiers. The design of the service, the parallelization of pre-processing tasks and the implementation on an HPC (High Performance Computing) environment make this system a useful tool for validation on several independent datasets.

A model to prioritize access to elective surgery on the basis of clinical urgency and waiting time.

BACKGROUND: Prioritization of waiting lists for elective surgery represents a major issue in public systems in view of the fact that patients often suffer from consequences of long waiting times. In addition, administrative and standardized data on waiting lists are generally lacking in Italy, where no detailed national reports are available. This is true although since 2002 the National Government has defined implicit Urgency-Related Groups (URGs) associated with Maximum Time Before Treatment (MTBT), similar to the Australian classification. The aim of this paper is to propose a model to manage waiting lists and prioritize admissions to elective surgery. METHODS: In 2001, the Italian Ministry of Health funded the Surgical Waiting List Info System (SWALIS) project, with the aim of experimenting solutions for managing elective surgery waiting lists. The project was split into two phases. In the first project phase, ten surgical units in the largest hospital of the Liguria Region were involved in the design of a pre-admission process model. The model was embedded in a Web based software, adopting Italian URGs with minor modifications. The SWALIS pre-admission process was based on the following steps: 1) urgency assessment into URGs; 2) correspondent assignment of a pre-set MTBT; 3) real time prioritization of every referral on the list, according to urgency and waiting time. In the second project phase a prospective descriptive study was performed, when a single general surgery unit was selected as the deployment and test bed, managing all registrations from March 2004 to March 2007 (1809 ordinary and 597 day cases). From August 2005, once the SWALIS model had been modified, waiting lists were monitored and analyzed, measuring the impact of the model by a set of performance indexes (average waiting time, length of the waiting list) and Appropriate Performance Index (API). RESULTS: The SWALIS pre-admission model was used for all registrations in the test period, fully covering the case mix of the patients referred to surgery. The software produced real time data and advanced parameters, providing patients and users useful tools to manage waiting lists and to schedule hospital admissions with ease and efficiency. The model protected patients from horizontal and vertical inequities, while positive changes in API were observed in the latest period, meaning that more patients were treated within their MTBT. CONCLUSION: The SWALIS model achieves the purpose of providing useful data to monitor waiting lists appropriately. It allows homogeneous and standardized prioritization, enhancing transparency, efficiency and equity. Due to its applicability, it might represent a pragmatic approach towards surgical waiting lists, useful in both clinical practice and strategic resource management.

Hydroxyapatite-coated polycaprolacton wide mesh as a model of open structure for bone regeneration.

In principle, three-dimensional (3D) osteoconductive grafts with a proper chemical composition, high total porosity, and fully interconnected pores are suitable carriers to provide a proper substrate for in vivo neobone tissue ingrowth. However, most porous materials carry some intrinsic limits because of their internal structure (i.e., limited macroporosity and small pore interconnection size), representing a physical constraint for a massive blood afflux and bone ingrowth and therefore for generating effective osteopermissive grafts. We therefore hypothesized that an unconventional scaffold, based on an "open-structure" concept, should not pose any limit to vascularization of grafts and consequently to the amount of bone growth. Starting from this hypothesis, we have designed and developed a 3D osteoconductive polymeric-based wide-net mesh. Polymer fibers, joining hydroxyapatite beads, were coated with a thin layer of calcium phosphate (Ca-P), coupling the osteoconductivity properties of Ca-P with the handness and bulk properties of polymers. This completely open 3D scaffold prototype was tested both in vitro and in vivo, displaying a promising in vivo blood vessel invasion and bone-forming efficiency.

A Web-based and Grid-enabled dChip version for the analysis of large sets of gene expression data.

BACKGROUND: Microarray techniques are one of the main methods used to investigate thousands of gene expression profiles for enlightening complex biological processes responsible for serious diseases, with a great scientific impact and a wide application area. Several standalone applications had been developed in order to analyze microarray data. Two of the most known free analysis software packages are the R-based Bioconductor and dChip. The part of dChip software concerning the calculation and the analysis of gene expression has been modified to permit its execution on both cluster environments (supercomputers) and Grid infrastructures (distributed computing).This work is not aimed at replacing existing tools, but it provides researchers with a method to analyze large datasets without any hardware or software constraints. RESULTS: An application able to perform the computation and the analysis of gene expression on large datasets has been developed using algorithms provided by dChip. Different tests have been carried out in order to validate the results and to compare the performances obtained on different infrastructures. Validation tests have been performed using a small dataset related to the comparison of HUVEC (Human Umbilical Vein Endothelial Cells) and Fibroblasts, derived from same donors, treated with IFN-alpha.Moreover performance tests have been executed just to compare performances on different environments using a large dataset including about 1000 samples related to Breast Cancer patients. CONCLUSION: A Grid-enabled software application for the analysis of large Microarray datasets has been proposed. DChip software has been ported on Linux platform and modified, using appropriate parallelization strategies, to permit its execution on both cluster environments and Grid infrastructures. The added value provided by the use of Grid technologies is the possibility to exploit both computational and data Grid infrastructures to analyze large datasets of distributed data. The software has been validated and performances on cluster and Grid environments have been compared obtaining quite good scalability results.

Gamma-aminobutyric acid and related molecules in the sea fan Eunicella cavolini (Cnidaria: Octocorallia): a biochemical and immunohistochemical approach.

The aim of this study has been the biochemical demonstration of the presence of gamma-aminobutyric acid (GABA) in the Mediterranean sea fan Eunicella cavolini by means of high-performance liquid chromatography, and the description of the distribution pattern of GABA and its related molecules, glutamic acid decarboxylase (GAD), vesicular GABA transporter (VGAT) and one of the GABA receptors (GABA(B) R) by immunohistochemical methods. The interrelationships of GABA, GAD and GABA receptor immunoreactivity have been established by using double-immunohistochemical methods and confocal microscopy. The immunodetection of monoclonal and/or polyclonal antibodies has revealed GABA immunoreactivity throughout the polyp tissue, both in neuronal and non-neuronal elements. GAD immunoreactivity has been mostly localized in the neuronal compartment, contacting epithelial and muscular elements. GABA(B) R immunoreactivity appears particularly intense in the nematocytes and in the oocyte envelope; its presence in GAD-immunoreactive neurons in the tentacles suggests an autocrine type of regulation. Western blot analysis has confirmed that a GABA(B) R, with a molecular weight of 142 kDa, similar to that of rat brain, is present in E. cavolini polyp tissue. The identification of the sites of the synthesis, vesicular transport, storage and reception of GABA strongly suggests the presence of an almost complete set of GABA-related molecules for the functioning of the GABAergic system in this simple nervous system. The distribution of these different immunoreactivities has allowed us to hypothesize GABA involvement in nematocyst discharge, in body wall and enteric muscular contraction, in neuronal integration and in male gametocyte differentiation.

Simulation of the biomechanical behavior of the skin in virtual surgical applications by finite element method.

The objective of this study was to develop a software application that is able to support plastic surgeons interested in applying simulations and soft tissue modeling during presurgical planning activities. By using our user-friendly interface and force-displacement graphs, users can analyze scalp skin behaviors when subjected to stress. Users can 1) determine the dynamic of a general point of scalp skin after the application of a specific force, 2) predict the force needed for displacement of a point, and 3) study the deformation of all the points of the entire scalp based on the force applied. Results showed how users are able to manipulate and analyze mechanical behaviors on a mechanical model rather than on a pure geometric qualitative physiological model. The entire application was developed on a Silicon Graphics workstation.

An integrated environment for plastic surgery support: building virtual patients, simulating interventions, and supporting intraoperative decisions.

In the last decade a number of environments for Computer Supported Plastic Surgery have been presented. Nevertheless, an overall approach for training and intraoperative support is still missing or has not been widely exploited yet. We developed a fully integrated system which allows surgical simulation, planning, and support for computer-guided plastic surgery procedures starting from image acquisition to final intraoperative assistance. The system also provides the user with a radiological workstation able to analyse patient medical images and case studies, with advanced bidimensional and three dimensional image processing functionalities. We intend to demonstrate that such a platform can be built at an affordable cost. The radiological workstation is capable of supporting radiologists and surgeons in real patient case studies and the simulation workstation may be adopted by plastic surgeons in teaching and training of complex surgical planning. Moreover, results of simulation can be used in the operating room with a relatively high benefit in terms of improved accuracy, reduction of surgical risks, and decrease in training costs.