Imaging of heart disease in women: review and case presentation

Cardiovascular diseases (CVD) remain the leading cause of mortality worldwide. Although major diagnostic and therapeutic advances have significantly improved the prognosis of patients with CVD in the past decades, these advances have less benefited women than age-matched men. Noninvasive cardiac imaging plays a key role in the diagnosis of CVD. Despite shared imaging features and strategies between both sexes, there are critical sex disparities that warrant careful consideration, related to the selection of the most suited imaging techniques, to technical limitations, and to specific diseases that are overrepresented in the female population. Taking these sex disparities into consideration holds promise to improve management and alleviate the burden of CVD in women. In this review, we summarize the specific features of cardiac imaging in four of the most common presentations of CVD in the female population including coronary artery disease, heart failure, pregnancy complications, and heart disease in oncology, thereby highlighting contemporary strengths and limitations. We further propose diagnostic algorithms tailored to women that might help in selecting the most appropriate imaging modality

Towards generalizable machine learning models for computer-aided diagnosis in medicine

Hidden stratification represents a phenomenon in which a training dataset contains unlabeled (hidden) subsets of cases that may affect machine learning model performance. Machine learning models that ignore the hidden stratification phenomenon--despite promising overall performance measured as accuracy and sensitivity--often fail at predicting the low prevalence cases, but those cases remain important. In the medical domain, patients with diseases are often less common than healthy patients, and a misdiagnosis of a patient with a disease can have significant clinical impacts. Therefore, to build a robust and trustworthy CAD system and a reliable treatment effect prediction model, we cannot only pursue machine learning models with high overall accuracy, but we also need to discover any hidden stratification in the data and evaluate the proposing machine learning models with respect to both overall performance and the performance on certain subsets (groups) of the data, such as the ‘worst group’. In this study, I investigated three approaches for data stratification: a novel algorithmic deep learning (DL) approach that learns similarities among cases and two schema completion approaches that utilize domain expert knowledge. I further proposed an innovative way to integrate the discovered latent groups into the loss functions of DL models to allow for better model generalizability under the domain shift scenario caused by the data heterogeneity. My results on lung nodule Computed Tomography (CT) images and breast cancer histopathology images demonstrate that learning homogeneous groups within heterogeneous data significantly improves the performance of the computer-aided diagnosis (CAD) system, particularly for low-prevalence or worst-performing cases. This study emphasizes the importance of discovering and learning the latent stratification within the data, as it is a critical step towards building ML models that are generalizable and reliable. Ultimately, this discovery can have a profound impact on clinical decision-making, particularly for low-prevalence cases

The cancer patient and cardiology

Advances in cancer treatments have improved clinical outcomes, leading to an increasing population of cancer survivors. However, this success is associated with high rates of short- and long-term cardiovascular (CV) toxicities. The number and variety of cancer drugs and CV toxicity types make long-term care a complex undertaking. This requires a multidisciplinary approach that includes expertise in oncology, cardiology and other related specialties, and has led to the development of the cardio-oncology subspecialty. This paper aims to provide an overview of the main adverse events, risk assessment and risk mitigation strategies, early diagnosis, medical and complementary strategies for prevention and management, and long-term follow-up strategies for patients at risk of cancer therapy-related cardiotoxicities. Research to better define strategies for early identification, follow-up and management is highly necessary. Although the academic cardio-oncology community may be the best vehicle to foster awareness and research in this field, additional stakeholders (industry, government agencies and patient organizations) must be involved to facilitate cross-discipline interactions and help in the design and funding of cardio-oncology trials. The overarching goals of cardio-oncology are to assist clinicians in providing optimal care for patients with cancer and cancer survivors, to provide insight into future areas of research and to search for collaborations with industry, funding bodies and patient advocates. However, many unmet needs remain. This document is the product of brainstorming presentations and active discussions held at the Cardiovascular Round Table workshop organized in January 2020 by the European Society of Cardiology.</p

Artificial intelligence in cancer imaging: Clinical challenges and applications

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care

Mammography

In this volume, the topics are constructed from a variety of contents: the bases of mammography systems, optimization of screening mammography with reference to evidence-based research, new technologies of image acquisition and its surrounding systems, and case reports with reference to up-to-date multimodality images of breast cancer. Mammography has been lagged in the transition to digital imaging systems because of the necessity of high resolution for diagnosis. However, in the past ten years, technical improvement has resolved the difficulties and boosted new diagnostic systems. We hope that the reader will learn the essentials of mammography and will be forward-looking for the new technologies. We want to express our sincere gratitude and appreciation?to all the co-authors who have contributed their work to this volume

Addressing gaps in colorectal cancer screening in Canada : multilevel determinants of screening, pathways to screening inequalities, and program evaluation

Contexte : Le cancer colorectal occupe présentement le deuxième rang des cancers les plus diagnostiqués au Canada et le troisième rang des cancers causant le plus grand nombre de décès. Malgré les avantages du dépistage préventif pour l’identification précoce du cancer colorectal, seulement 20% à 30% des adultes canadiens âgés de 50 à 74 ans participent au dépistage de façon régulière. De plus, il existe plusieurs inégalités sociales au niveau de la participation au dépistage. But : Les objectifs généraux de cette thèse sont de développer une meilleure compréhension des déterminants sociaux du dépistage colorectal et d’explorer les voies potentielles d'intervention—à la fois en identifiant des mécanismes qui expliquent les disparités sociales de dépistage et en évaluant si les stratégies actuelles d’intervention au niveau de la population permettent de promouvoir le dépistage et de réduire les inégalités sociales de dépistage. La thèse comprend trois objectifs spécifiques : 1) Examiner l'association entre le revenu du quartier et la participation au dépistage colorectal; 2) Examiner si l'accès à un médecin régulier agit comme médiateur de l’inégalité de dépistage observée entre les nouveaux arrivants au Canada et les personnes nées au Canada; 3) Évaluer les retombées de deux types de programmes de dépistage du cancer colorectal au Canada (soit des programmes « systématiques » qui impliquent l’envoi et la réception de tests de dépistage à tout résident âgé de 50 à 74 ans par courrier; et des programmes « centrés sur la décision du patient » qui renvoient la responsabilité aux patients de demander le test par l’intermédiaire d’une ligne téléphone, d’un site web, ou de leur médecin, et ensuite de retourner le test en personne) sur la participation au dépistage et sur les inégalités sociales de dépistage. Méthodes : Les analyses ont été effectuées à partir des données recueillies auprès des répondants âgés de 50 à 75 ans de l'Enquête sur la santé dans les collectivités canadiennes (ESCC) qui ne présentaient aucun facteur de risque familial ou médical connu de cancer colorectal (personnes à risque moyen). Les données de l'ESCC fournissent l'information sur l'âge, le sexe, l'état matrimonial, le niveau de scolarité, le revenu, le statut immigrant et de minorité visible, l'accès à un médecin de famille, la ruralité du lieu de résidence, la province de résidence, et la participation à vie (au moins une fois) au dépistage du cancer colorectal, et le dépistage récent (soit par test de selles dans les des deux années précédentes ou par un test endoscopique dans les cinq années précédentes). Les données du Recensement canadien de 2006 ont été utilisées pour caractériser le revenu du quartier des répondants. Les analyses effectuées comprennent, entre autres, des équations d'estimation généralisées (objectif 1), des analyses de médiation incluant des analyses de régression et de pondération par la probabilité inverse (objectif 2), et des analyses évaluatives de type « différences entre les différences » (« Difference-in-Differences ») par le biais d’analyses de régression (objectif 3). Résultats : Les résultats indiquent que le dépistage colorectal est déterminé par des facteurs individuels et contextuels. Cette thèse a révélé un gradient dans le dépistage de cancer colorectal selon le revenu du quartier au Canada, indépendamment des caractéristiques sociales et économiques des individus. Cette observation permet d’entrevoir l'influence des contextes sociaux et environnementaux sur le dépistage du cancer colorectal. De plus, les résultats suggèrent que l'accès aux médecins n’est pas un médiateur de l’association entre l’immigration et le dépistage du cancer colorectal. D’autres mécanismes explicatifs doivent être explorés pour mieux comprendre les causes intermédiaires. Enfin, les programmes dits systématiques et patient-dépendants sont tous les deux associés à une augmentation de participation au dépistage. Cependant, ces deux types de programmes ne semblent pas réduire les inégalités sociales de dépistage. En fait, le programme patient-dépendant semble augmenter la disparité de dépistage entre ceux avec et sans un médecin de famille. Il est possible que la réduction des inégalités sociales du dépistage doive nécessiter la mise en place de stratégies d’intervention davantage ciblées. Conclusions : Cette thèse contribue à l’avancement des connaissances sur les déterminants sociaux du dépistage du cancer colorectal au Canada. Les résultats suggèrent que les contextes socioéconomiques méritent d’être explorés dans la surveillance et les recherches futures sur le dépistage colorectal. Parmi les pistes de recherche porteuses, on compte des recherches portant sur les mécanismes explicatifs des inégalités sociales et des études sur les interventions potentielles pour promouvoir le dépistage parmi les plus populations plus vulnérables.Background: Colorectal cancer is the second most diagnosed cancer in Canada and the third most common cause of cancer mortality. Despite the known benefits of early and regular use of preventive screening tests, only 20% to 30% of Canadian adults aged 50 to 74 years participate in regular screening, and social disparities in screening participation exist. Purpose: The overall aims of the proposed thesis are to contribute to a better understanding of the social determinants of colorectal cancer screening in Canada and to explore potential pathways for intervention—both by identifying mechanisms that explain existing social disparities and by evaluating whether or not current population-level intervention strategies affect screening uptake overall and among vulnerable populations. The specific objectives of the thesis are as follows: 1) To assess the association between area-level socioeconomic deprivation and colorectal cancer screening participation; 2) To assess whether or not access to primary care physician mediates differences in screening uptake between recent immigrants and non-immigrants in Canada; 3) To evaluate the impact of two types of colorectal cancer screening programs (“systematic mail-based programs” that deliver and collect screening kits via-mail to all residents aged 50 to 74 years, and “patient-reliant programs” that rely on individuals to access test kits via a designed phone-line, website, or their physician, and return kits in-person) on screening participation, and screening disparities. Methods: Analyses were conducted utilizing data from 50 to 75-year-old respondents from the population-based Canadian Community Health Study (CCHS) who had no known familial or medical risk factors of colorectal cancer (i.e., those at ‘average risk’). CCHS data provided information on respondents’ age, sex, marital status, educational attainment, income, immigration status, visible minority status, access to a primary care physician, area and province of residence, and both lifetime (i.e., ever vs. never) and non-recent colorectal cancer screening (i.e., no stool-based screening in the previous two years or no endoscopic-based screening in the previous five years). Data from the 2006 Canadian Census provided information on respondents’ local area-level income. Different types of analyses were used, including generalized estimating equations (Objective 1), regression- and inverse probability weighting-based mediation analyses (Objective 2), and regression-based difference-in-differences analyses for program evaluation (Objective 3). Results: First, findings suggest that colorectal cancer screening is determined by both individual- and local area-level or region-wide factors. This thesis observed a gradient in lifetime colorectal cancer screening according to local area-income in Canada independent of individual-level social and economic factors. This finding highlights the potential influence of social and environmental contexts on colorectal cancer screening uptake. Second, access to primary care physicians was not found to mediate the association between recent immigration and colorectal cancer screening. This finding suggests that alternative interventions to reduce immigration-based disparities should be explored. Lastly, both systematic and patient-reliant programs were observed to improve overall screening participation. However, both types of programs did not appear to reduce known social and economic screening inequalities. In fact, the patient-reliant program studied was observed to increase the screening disparity between those with and without a primary care physician. These results indicate that reductions in social inequalities related to colorectal cancer screening may require more targeted strategies. Conclusions: This thesis contributes to the literature on the social determinants of colorectal cancer screening in Canada by exploring area-level determinants of screening as well as mechanisms that explain screening inequalities and by evaluating the effectiveness of various colorectal cancer screening programs at improving screening uptake and reducing screening inequalities. Findings support the notion that the role of socioeconomic contexts, above and beyond individual-level factors, merit attention both in future research on and surveillance of colorectal cancer screening. It also indicates that modifiable pathways to known screening disparities require continued exploration, and that future work should assess the acceptability, feasibility, and effectiveness of complimentary targeted interventions to promote screening both overall and among those most vulnerable

Role of Artificial Intelligence in Radiogenomics for Cancers in the Era of Precision Medicine

Radiogenomics, a combination of “Radiomics” and “Genomics,” using Artificial Intelligence (AI) has recently emerged as the state-of-the-art science in precision medicine, especially in oncology care. Radiogenomics syndicates large-scale quantifiable data extracted from radiological medical images enveloped with personalized genomic phenotypes. It fabricates a prediction model through various AI methods to stratify the risk of patients, monitor therapeutic approaches, and assess clinical outcomes. It has recently shown tremendous achievements in prognosis, treatment planning, survival prediction, heterogeneity analysis, reoccurrence, and progression-free survival for human cancer study. Although AI has shown immense performance in oncology care in various clinical aspects, it has several challenges and limitations. The proposed review provides an overview of radiogenomics with the viewpoints on the role of AI in terms of its promises for computa-tional as well as oncological aspects and offers achievements and opportunities in the era of precision medicine. The review also presents various recommendations to diminish these obstacles

Epidemiological study of aromatase inhibitors in women diagnosed with breast cancer: evaluation and management of secondary effects

[eng] Aromatase inhibitors (AI) are one of the main therapies to treat estrogen-receptor positive breast cancer. AI use is associated with several side effects that affects patient’s quality of life and reduces treatment adherence. Hence, it is necessary to make further efforts in elucidating and diminishing the AI-related side effects. In this line, this thesis provided new and additional evidence for this purpose. Starting by the importance of assessing vitamin D levels during AI treatment, especially to those who underwent to chemotherapy. We also studied the bone health evolution at the end and one-year after AI cessation, and the impact of oral bisphosphonates (BP). Moreover, we analyzed the arthralgia (VAS score) and health-related quality of life in osteoporosis (ECOS-16 score) progression during the AI treatment until one- year post-treatment. Then, fracture incidence and risk during AI therapy compared to tamoxifen (TAM) was analyzed, as well as the protective effect of BP. Finally, we studied the cardiovascular and thromboembolic risk, and overall survival benefit of AI compared to TAM. Our research leads us to state that bone health and circulant vitamin D levels monitoring, plus calcium and vitamin D supplementation is key for the clinical management of AI patients. BP treatment is proved to diminish bone loss and fracture risk, but cannot reverse risk levels towards patients at low fracture risk. Furthermore, prior TAM treatment enhances the odds to withdraw during the first year, increases bone loss during AI treatment, and restricts the recovery in lumbar spine location at one-year post-treatment. On the other hand, since there are no differences in cardiovascular and thromboembolic risk between AI and TAM users, but AI users have lower all-cause mortality, AI should be the preferable choice. In summary, it is mandatory to clinical monitoring AI patients, especially those who were previously treated with TAM, including fracture risk and related risk factors assessments. These would reduce early cessation of treatment and improve patients’ quality of life