Calcium identification and scoring based on echocardiography imaging

Currently, an echocardiography expert is needed to identify calcium in the aortic valve, and a cardiac CT-Scan image is needed for calcium quantification. When performing a CT-scan, the patient is subject to radiation, and therefore the number of CT-scans that can be performed should be limited, restricting the patient's monitoring. Computer Vision (CV) has opened new opportunities for improved efficiency when extracting knowledge from an image. Applying CV techniques on echocardiography imaging may reduce the medical workload for identifying the calcium and quantifying it, helping doctors to maintain a better tracking of their patients. In our approach, we developed a simple technique to identify and extract the calcium pixel count from echocardiography imaging, by using CV. Based on anonymized real patient echocardiographic images, this approach enables semi-automatic calcium identification. As the brightness of echocardiography images (with the highest intensity corresponding to calcium) vary depending on the acquisition settings, we performed echocardiographic adaptive image binarization. Given that blood maintains the same intensity on echocardiographic images – being always the darker region – we used blood structures in the image to create an adaptive threshold for binarization. After binarization, the region of interest (ROI) with calcium, was interactively selected by an echocardiography expert and extracted, allowing us to compute a calcium pixel count, corresponding to the spatial amount of calcium. The results obtained from our experiments are encouraging. With our technique, from echocardiographic images collected for the same patient with different acquisition settings and different brightness, we were able to obtain a calcium pixel count, where pixels values show an absolute pixel value margin of error of 3 (on a scale from 0 to 255), that correlated well with human expert assessment of calcium area for the same images.Atualmente, é necessário um perito em ecocardiografia para identificar o cálcio na válvula aórtica, e é necessária uma imagem Tomográfica Computorizada (TAC) cardíaca para a quantificação do cálcio. Ao realizar uma TAC, o paciente é sujeito a radiação, pelo que o número de TACs que podem ser realizadas deve ser limitado, restringindo a monitorização do paciente. A Visão por Computador (VC) abriu novas oportunidades para uma maior eficiência na extração de conhecimentos de uma imagem. A aplicação de técnicas de VC na ecocardiografia pode reduzir a carga de trabalho médico para identificar o cálcio e quantificálo, ajudando os médicos a manter um melhor acompanhamento dos seus pacientes. Na nossa abordagem, desenvolvemos uma técnica simples para identificar e extrair o número de pixéis de cálcio da ecocardiografia, através da utilização de VC. Com base em ecocardiografias anónimas de doentes reais, esta abordagem permite a identificação semiautomática do cálcio. Como o brilho das imagens de ecocardiografia (com a intensidade mais elevada corresponde ao cálcio) varia consoante os parâmetros de aquisição, realizámos a binarização das ecocardiografias de forma adaptativa. Dado que o sangue mantém a mesma intensidade nas ecocardiografias - sendo sempre a região mais escura - utilizámos estruturas sanguíneas na imagem para criar um limiar adaptativo para a binarização. Após a binarização, a região de interesse (ROI) com cálcio, foi selecionada interactivamente por um especialista em ecocardiografia e extraída, permitindo-nos calcular o número de pixéis de cálcio, correspondente à quantidade espacial de cálcio. Os resultados obtidos com as nossas experiências são encorajadores. Com a nossa técnica, a partir de ecocardiografias recolhidas para o mesmo paciente com diferentes configurações de aquisição e diferentes brilhos, conseguimos obter uma contagem de pixéis de cálcio, onde os valores de pixéis mostram uma margem de erro absoluta de 3 (numa escala de 0 a 255), que se correlacionou bem com a avaliação humana perita da área de cálcio para as mesmas imagens

Systematic Review

Funding Information: MP received support from the Portuguese National Funds through FITEC – Programa Interface, with reference CIT INOV – INESC INOVAÇÃO. Funding was also provided from the PhD program in Industrial Management, NOVA Science and Technology Faculty. Funding Information: MP and LVL acknowledge Fundação para a Ciência e a Tecnologia (FCT-MCTES) for its financial support via the project UIDB/00667/2020 (UNIDEMI).Background: The digital age, with digital sensors, the Internet of Things (IoT), and big data tools, has opened new opportunities for improving the delivery of health care services, with remote monitoring systems playing a crucial role and improving access to patients. The versatility of these systems has been demonstrated during the current COVID-19 pandemic. Health remote monitoring systems (HRMS) present various advantages such as the reduction in patient load at hospitals and health centers. Patients that would most benefit from HRMS are those with chronic diseases, older adults, and patients that experience less severe symptoms recovering from SARS-CoV-2 viral infection. Objective: This paper aimed to perform a systematic review of the literature of HRMS in primary health care (PHC) settings, identifying the current status of the digitalization of health processes, remote data acquisition, and interactions between health care personnel and patients. Methods: A systematic literature review was conducted using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines to identify articles that explored interventions with HRMS in patients with chronic diseases in the PHC setting. Results: The literature review yielded 123 publications, 18 of which met the predefined inclusion criteria. The selected articles highlighted that sensors and wearables are already being used in multiple scenarios related to chronic disease management at the PHC level. The studies focused mostly on patients with diabetes (9/26, 35%) and cardiovascular diseases (7/26, 27%). During the evaluation of the implementation of these interventions, the major difficulty that stood out was the integration of information into already existing systems in the PHC infrastructure and in changing working processes of PHC professionals (83%). Conclusions: The PHC context integrates multidisciplinary teams and patients with often complex, chronic pathologies. Despite the theoretical framework, objective identification of problems, and involvement of stakeholders in the design and implementation processes, these interventions mostly fail to scale up. Despite the inherent limitations of conducting a systematic literature review, the small number of studies in the PHC context is a relevant limitation. This study aimed to demonstrate the importance of matching technological development to the working PHC processes in interventions regarding the use of sensors and wearables for remote monitoring as a source of information for chronic disease management, so that information with clinical value is not lost along the way.publishersversionpublishe

The Effect of Oral Simethicone in a Bowel Preparation in a Colorectal Cancer Screening Colonoscopy Setting: A Randomized Controlled Trial

Introduction: Current guidelines suggest adding oral simethicone to bowel preparation for colonoscopy. However, its effect on key quality indicators for screening colonoscopy remains unclear. The primary aim was to assess the rate of adequate bowel preparation in split-dose high-volume polyethylene glycol (PEG), with or without simethicone. Methods: This is an endoscopist-blinded, randomized controlled trial, including patients scheduled for colonoscopy after a positive faecal immunochemical test. Patients were randomly assigned to 4 L of PEG split dose (PEG) or 4 L of PEG split dose plus 500 mg oral simethicone (PEG + simethicone). The Boston Bowel Preparation Scale (BBPS) score, the preparation quality regarding bubbles using the Colon Endoscopic Bubble Scale (CEBuS), ADR, CIR, and the intraprocedural use of simethicone were recorded. Results: We included 191 and 197 patients in the PEG + simethicone group and the PEG group, respectively. When comparing the PEG + simethicone group versus the PEG group, no significant differences in adequate bowel preparation rates (97% vs. 93%; p = 0.11) were found. However, the bubble scale score was significantly lower in the PEG + simethicone group (0 [0] versus 2 [5], p < 0.01), as well as intraprocedural use of simethicone (7% vs. 37%; p < 0.01). ADR (62% vs. 61%; p = 0.86) and CIR (98% vs. 96%, p = 0.14) did not differ between both groups. Conclusion: Adding oral simethicone to a split-bowel preparation resulted in a lower incidence of bubbles and a lower intraprocedural use of simethicone but no further improvement on the preparation quality or ADR