Automated Analysis of Proliferating Cells Spatial Organisation Predicts Prognosis in Lung Neuroendocrine Neoplasms

SIMPLE SUMMARY: Lung neuroendocrine neoplasms (lung NENs) are categorised by morphology, defining a classification sometimes unable to reflect ultimate clinical outcome, particularly for the intermediate domains of adenocarcinomas and large-cell neuroendocrine carcinomas. Moreover, subjectivity and poor reproducibility characterise diagnosis and prognosis assessment of all NENs. The aim of this study was to design and evaluate an objective and reproducible approach to the grading of lung NENs, potentially extendable to other NENs, by exploring a completely new perspective of interpreting the well-recognised proliferation marker Ki-67. We designed an automated pipeline to harvest quantitative information from the spatial distribution of Ki-67-positive cells, analysing its heterogeneity in the entire extent of tumour tissue—which currently represents the main weakness of Ki-67—and employed machine learning techniques to predict prognosis based on this information. Demonstrating the efficacy of the proposed framework would hint at a possible path for the future of grading and classification of NENs. ABSTRACT: Lung neuroendocrine neoplasms (lung NENs) are categorised by morphology, defining a classification sometimes unable to reflect ultimate clinical outcome. Subjectivity and poor reproducibility characterise diagnosis and prognosis assessment of all NENs. Here, we propose a machine learning framework for tumour prognosis assessment based on a quantitative, automated and repeatable evaluation of the spatial distribution of cells immunohistochemically positive for the proliferation marker Ki-67, performed on the entire extent of high-resolution whole slide images. Combining features from the fields of graph theory, fractality analysis, stochastic geometry and information theory, we describe the topology of replicating cells and predict prognosis in a histology-independent way. We demonstrate how our approach outperforms the well-recognised prognostic role of Ki-67 Labelling Index on a multi-centre dataset comprising the most controversial lung NENs. Moreover, we show that our system identifies arrangement patterns in the cells positive for Ki-67 that appear independently of tumour subtyping. Strikingly, the subset of these features whose presence is also independent of the value of the Labelling Index and the density of Ki-67-positive cells prove to be especially relevant in discerning prognostic classes. These findings disclose a possible path for the future of grading and classification of NENs

New methods to assess the performance of structural joints with microstructures

The reliability of structural joints plays a crucial role in our daily life since the most recent innovations in engineering and structural materials have exponentially increased the usage of advanced products, multi- components, and structures. Hence, it is necessary to introduce new methods to assess the bonding strengths of adhesive joints, especially in complex interfaces, as in the presence of micro-structured or rough surfaces, since the morphology of the interface highly influences the overall performance of a structural joint. The present thesis explores the role of complex interfaces and functional surfaces in the overall performance of multi-components products, intending to understand the mechanical phenomena that may take place at the interface between different materials, simply in contact or joined through an adhesive. Different topics have been analyzed through experimental and numerical analyses. The research deals with rough interface contact simulations proposing a novel multi-scale approach in the context of computational contact mechanics. Furthermore, the surface morphology influence on adhesive joints has been investigated through peeling tests and numerical models. Moreover, a computational framework for microstructured adhesives has been proposed. The final topic regards the failure simulation of bilayer structural joints with rubber-like materials

A coupled approach to predict cone-cracks in spherical indentation tests with smooth or rough indenters

Indentation tests are largely exploited in experiments to characterize the mechanical and fracture properties of the materials from the resulting crack patterns. This work proposes an efficient theoretical and computational framework, whose implementation is detailed for 2D axisymmetric and 3D geometries, to simulate indentation-induced cracking phenomena caused by non-conforming contacts with indenter profiles of arbitrary shape. The formulation hinges on the coupling of the MPJR (eMbedded Profile for Joint Roughness) interface finite elements which embed the indenter profile to solve the contact problem between non-planar bodies efficiently and the phase-field for brittle fracture to simulate crack evolution and nonlocal damage in the substrate. The novel framework is applied to predict cone-crack formation in the case of indentation tests with smooth spherical indenters, with validation against experimental data. Then, the methodology is employed for the very first time in the literature to assess the effect of surface roughness superimposed on the shape of the smooth spherical indenter. In terms of physical insights, numerical predictions quantify the dependencies of the critical load for crack nucleation and the crack radius on the amplitude of roughness in comparison with the behavior of smooth indenters. Again, the consistency with available experimental trends is noticed.Comment: This article has been published on the Journal of the Mechanics and Physics of Solids at https://doi.org/10.1016/j.jmps.2023.10534

Digital twin models of replicative ground stones: insight into simulating usage of Upper Paleolithic tools

This work presents the first attempt to create a physics-based digital twin model for predictive analysis of damage evolution during the use of ground stone tools (GSTs) in transformative tasks, encompassing the processing of raw resources for nutritional and non-alimentary purposes. The proposed methodology introduces a digital twin of the GSTs developed from 3D models generated using a photogrammetric technique based on Structure-from-Motion and Multi-View Stereo reconstruction. These models serve as the foundation for the development of the finite element (FE)-based digital twin model of the GSTs that exploits a contact formulation and the phase-field approach to simulate tool damage during pounding and grinding tasks. Defining the initial relative positions of the stones, their mechanical behaviour, and controlling the movement of the active stone in a way as close as possible to the real one, the digital twin model has been devised to evaluate how the surface damage is affected by perturbations in the loading conditions. The simulated damage is compared with the surface traces observed from experiments. The developed digital twin model aims at demonstrating its potentials for the GSTs investigations, as a supporting tool for experiments and for simulated tests on the archaeological records

A coupled approach to predict cone-cracks in spherical indentation tests with smooth or rough indenters

Indentation tests are largely exploited in experiments to characterize the mechanical and fracture properties of the materials from the resulting crack patterns. This work proposes an efficient theoretical and computational framework, whose implementation is detailed for 2D axisymmetric and for 3D geometries, to simulate indentation-induced cracking phenomena caused by non-conforming contacts with indenter profiles of an arbitrary shape. The formulation hinges on the coupling of the MPJR (eMbedded Profile for Joint Roughness) interface finite elements which embed the indenter profile to efficiently solve the contact problem between non-planar bodies, and the phase-field model for brittle fracture to simulate crack evolution and nonlocal damage in the substrate. The novel framework is applied to predict cone-crack formation in the case of indentation tests with smooth spherical indenters, with validation against experimental data. Then, the methodology is employed for the very first time in the literature to assess the effect of surface roughness superimposed on the shape of the smooth spherical indenter. In terms of physical insights, numerical predictions quantify the dependencies of the critical load for crack nucleation and the crack radius on the amplitude of roughness in comparison with the behavior of smooth indenters. Again, the consistency with available experimental trends is noticed

Pulmonary Sclerosing Pneumocytoma: A Pre and Intraoperative Diagnostic Challenge. Report of Two Cases and Review of the Literature

Pulmonary sclerosing pneumocytoma is a rare benign pulmonary tumor of primitive epithelial origin. Because of the unspecific radiological features mimicking malignancies and its histological heterogeneity, the differential diagnosis with adenocarcinoma and carcinoid tumors is still challenging. We report our experience of two cases of sclerosing pneumocytoma, as well as a review of the literature. Immunohistochemical findings showed intense staining of the cuboidal epithelial cells for cytokeratin-pool and TTF-1, with focal positivity for progesterone receptors. Round and spindle cells expressed positivity for vimentin, TTF-1 and focally for the progesterone receptor. Cytologic diagnosis of pulmonary pneumocytoma requires the identification of its dual cell population, made up of abundant stromal cells and fewer surface cells. Since the pre- and intraoperative diagnosis should guide surgical decision making, obtaining a sufficient specimen size to find representative material in the cell block is of paramount importance