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

Quantitative ADC: An Additional Tool in the Evaluation of Prostate Cancer?

Prostate cancer is one of the most common tumors among the male population. Magnetic resonance imaging (MRI), standardized by the PI-RADS version 2.1 scoring system, has a fundamental role in detecting prostate cancer and evaluating its aggressiveness. Diffusion-weighted imaging sequences and apparent diffusion coefficient values, in particular, are considered fundamental for the detection and characterization of lesions. In 2016 the International Society of Urological Pathology introduced a new anatomopathological 5-grade scoring system for prostate cancer. The aim of this study is to evaluate the correlation between quantitative apparent diffusion coefficient values (ADC) derived from diffusion-weighted imaging (DWI) sequences and the International Society of Urological Pathology (ISUP) and PI-RADS groups. Our retrospective study included 143 patients with 154 suspicious lesions, observed on prostate magnetic resonance imaging and compared with the histological results of the biopsy. We observed that ADC values can aid in discriminating between not clinically significant (ISUP 1) and clinically significant (ISUP 2-5) prostate cancers. In fact, ADC values were lower in ISUP 5 lesions than in negative lesions. We also found a correlation between ADC values and PI-RADS groups; we noted lower ADC values in the PI-RADS 5 and PI-RADS 4 groups than in the PI-RADS 3 group. In conclusion, quantitative apparent diffusion coefficient values can be useful to assess the aggressiveness of prostate cancer

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

Angiomatoid Fibrous Histiocytoma (AFH) of the Right Arm: An Exceptional Case with Pulmonary Metastasis and Confirmatory EWSR1::CREB1 Translocation

Angiomatoid fibrous histiocytoma (AFH) is a rare neoplasm described for the first time by Enzinger in 1979, and classified by World Health Organization 2020 as intermediate malignant potential neoplasm. It mostly occurs in the subcutis and is characterized by varying proportions of epithelioid, ovoid and spindle cells in a nodular and syncytial growth pattern, with some hemorrhagic pseudovascular spaces. In this paper, we report the clinical case of a 62-year-old man who presented with AFH on the right arm, and relapsed three years after first surgical excision. After a further three years, the patient presented with an intramuscular localization of AFH, and 12 months after this, a pulmonary metastasis of AFH was diagnosed. Given the rarity of the spreading of AFH, we performed Fluorescence In Situ Hybridization (FISH) and we detected EWSR1::CREB1 gene fusion