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© The Author(s) 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons. org/licenses/by/4.0/., Introduction: We previously developed an artificial intelligence (AI) model for automatic coronary angiography (CAG) segmentation, using deep learning. To validate this approach, the model was applied to a new dataset and results are reported. Methods: Retrospective selection of patients undergoing CAG and percutaneous coronary intervention or invasive physiology assessment over a one month period from four centers. A single frame was selected from images containing a lesion with a 50-99% stenosis (visual estimation). Automatic Quantitative Coronary Analysis (QCA) was performed with a validated software. Images were then segmented by the AI model. Lesion diameters, area overlap [based on true positive (TP) and true negative (TN) pixels] and a global segmentation score (GSS - 0 -100 points) - previously developed and published - were measured. Results: 123 regions of interest from 117 images across 90 patients were included. There were no significant differences between lesion diameter, percentage diameter stenosis and distal border diameter between the original/segmented images. There was a statistically significant albeit minor difference [0,19 mm (0,09-0,28)] regarding proximal border diameter. Overlap accuracy ((TP + TN)/(TP + TN + FP + FN)), sensitivity (TP / (TP + FN)) and Dice Score (2TP / (2TP + FN + FP)) between original/segmented images was 99,9%, 95,1% and 94,8%, respectively. The GSS was 92 (87-96), similar to the previously obtained value in the training dataset. Conclusion: the AI model was capable of accurate CAG segmentation across multiple performance metrics, when applied to a multicentric validation dataset. This paves the way for future research on its clinical uses., Open access funding provided by FCT|FCCN (b-on). Cardiovascular Center of the University of Lisbon, INESC-ID / Instituto Superior Técnico, University of Lisbon.

Dissertação de Mestrado Integrado em Arquitetura, com a especialização em Arquitetura apresentada na Faculdade de Arquitetura da Universidade de Lisboa para obtenção do grau de Mestre. A revitalização é actualmente um dos temas centrais no trabalho de arquitectura e planeamento urbano nas cidades do mundo ocidental. Servindo-se de uma área específica como objecto de estudo, o trabalho “Revitalizar em Cenários de Abandono” procura entender os fenómenos de encolhimento urbano, e fazer uma reflexão crítica sobre diferentes formas de revitalizar as áreas afectadas. No município de Lisboa, o período da desindustrialização e dinâmicas acentuadas de suburbanização deixaram para trás inúmeras áreas abandonadas, distribuídas segundo um padrão irregular. Partes do centro histórico e antigas áreas industriais ficaram suspensas durante décadas. Muitas encontram-se ainda hoje à espera de novos usos; à espera de uma nova vida. Este trabalho procura compreender a área de Xabregas, incluída no Vale de Chelas, em Lisboa, como cenário de abandono. É apresentada uma revisão bibliográfica sobre o tema do encolhimento urbano, com especial enfoque nas consequências espaciais e no problema dos vazios urbanos. Numa aproximação à componente prática, apresentam-se vários tipos de resposta para o problema dos vazios urbanos. Por fim, no âmbito do projecto, pretende-se explorar as vantagens dos usos temporários, como estratégia para uma rápida revitalização de áreas expectantes. O projecto desenvolvido toma o edifício da antiga Fábrica de Fiação e Tecidos de Xabregas, abandonado há mais de sessenta anos, como oportunidade para iniciar uma dinâmica eficaz de revitalização, tendo como ponto de partida a introdução de um uso temporário. ABSTRACT: Urban Revitalization is currently one of the most important topics for architects and urban planners working in western civilization. By focusing on a specific site, the work “Revitalization in Abandoned Scenarios” tries to understand urban shrinkage as a complex phenomenon, and brings up a critical reflection on different ways of revitalizing affected areas. In the municipality of Lisbon, the deindustrialization period and strong suburbanization dynamics left behind a number of abandoned areas, distributed in an irregular pattern. Parts of the historic center and old industrial areas were kept in standby for decades. Many of those are still waiting for new uses; for a new life. This work aims to understand the areas of Xabregas and Chelas Valley, in Lisbon, as abandoned scenarios. A literature review on urban shrinkage is presented with a special focus on spatial consequences as the problem of urban voids. Several solutions for the problem of urban voids are presented as approaching a practical component in this work. Finally, in a project mindset, the work intends to take advantage of temporary uses and meanwhile spaces, as strategies for a fast revitalization process. The project takes the building of the former Cotton Spinning Factory of Xabregas, abandoned since more than sixty years, as an opportunity to start effective revitalization dynamics, initiated by the introduction of temporary uses. N/A

Dissertação de Mestrado Integrado em Arquitetura, com a especialização em Arquitetura apresentada na Faculdade de Arquitetura da Universidade de Lisboa para obtenção do grau de Mestre. Submitted by Inês Monteiro (inesmonteiro@fa.ulisboa.pt) on 2019-09-09T09:54:02Z No. of bitstreams: 1 TFM_Manuel Santos_documento definitivo.pdf: 30530376 bytes, checksum: b87e8bcc34f4231f551da7646e862aa2 (MD5) Made available in DSpace on 2019-09-09T09:54:15Z (GMT). No. of bitstreams: 1 TFM_Manuel Santos_documento definitivo.pdf: 30530376 bytes, checksum: b87e8bcc34f4231f551da7646e862aa2 (MD5) Previous issue date: 2019-03-21 N/A

Trabalho Final do Mestrado Integrado em Medicina apresentado à Faculdade de Medicina Aims: We aimed to investigate CAV incidence and predictors in a large cohort of OHT patients.Methods: We conducted a retrospective analysis on a prospective cohort of 233 patients who underwent OHT at our institution from November 2003 to May 2014. OHT recipients younger than 18 years (n=3) and those who died less than a year after OHT were excluded (n=28). Baseline data was extracted from a main database; we analysed all invasive coronary angiograms (ICA) (n=712) performed as part of the structured follow up program of these patients. CAV was defined by at least one ICA with visible coronary lesions. Results: We included 157 male and 45 female recipients. Median age was 66 years and median BMI was 24.7 kg.m-2. Regarding risk factors for atherosclerosis, 17.3% were smokers, 36.8% had hypertension and 46.8% were dyslipidemic. A third of patients had established vascular disease before OHT, either an abnormal carotid doppler (39.6%), peripheral vascular disease (30.3%) or ischemic heart disease (IHD) (35.6%). Acute rejection occurred in 42 patients (21.3%) during the first year. The donor group was composed by 154 males and 48 females. Median age was 35 years and median BMI 24.1 kg.m-2. Over a median follow-up of 2920 (1825-3650) days after HT, 37 patients (18.3%) were diagnosed with CAV. Incidence rate of CAV in our overall population was 2.91 cases per 100 person-year. Regarding lesion type, 14 had CAV 1 (38%), 12 had CAV 2 (35%) and 9 had CAV 3 (24%). PCI was performed in 15 (41%) patients. There was no significant difference among baseline variables when comparing patients with normal (n=165) and abnormal ICA. When considering CAV (+) group, abnormal carotid doppler [hazard ratio (HR) 2.44 95% confidence Interval (CI) 1.27–4.71, P