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Excerpt: The conclusions by Zhang et al. (2015) were notable, but the support for the conclusions was not particularly strong because of two issues. The first weakness is that although some studies have found correlations between self-efficacy and pain, the study did not consider the possibility that it is symptom distress that affects self-efficacy in colorectal cancer patients. Rather, it was assumed only that self-efficacy caused reduced symptom effects instead of a reverse or mutual relationship. The study did not consider the possibility that low self-efficacy in those with high symptom distress was actually caused by the distress itself, which is a plausible explanation. In fact, Chiarotto et al. (2014) found that cancer patients on pain medication have higher rates of self-efficacy, which would appear to show that distress reduces self-efficacy, rather than the other way around, as assumed in the above study.

In 2019, cancer was the second leading cause of death in the United States. Colorectal cancer is the second most common cancer affecting both men and women. Colorectal screenings are an important preventive health service, with approximately half of cases detected through screening, improving life expectancy among those diagnosed. Previous research has noted differences in screening rates between racial or ethnic groups, with whites being screened at a higher rate than other racial and ethnic groups. Additionally, the prevalence of colorectal cancer is becoming more common among persons younger than 50 years old, prompting testing guidelines to be revised in 2018 that call for testing to begin at 45 instead of age 50. The purpose of this analysis is to investigate this issue further by examining differences in colorectal screening among various racial and ethnic groups. A cross-sectional study using the 2021 Behavioral Risk Factor Surveillance System for respondents from West Virginia and Oregon (combined) was used to examine colon cancer screening by various racial and ethnic populations. Individuals responding receipt of a colonoscopy or sigmoidoscopy were the primary outcome of interest. Racial and ethnic groups include whites-only, blacks-only, other races, multi-racial and those of Hispanic ethnicity. Additional covariates of interest were included in the analysis based on Andersen’s behavior model for health service utilization and includes predisposing (gender, age, education, marital status) enabling (insurance, employment status) need (body mass index, other types of cancers) factors. Bivariate and multivariate logistic regression analysis was used to examine these relationships. The study population included 2,831 adults who self-reported being screened for colon cancer. Overall 61% of white populations reported receipt of colon cancer screening compared to 54% of Black, 52% of Other, and 43% of Hispanic populations (p<0.00). Adjusting for additional covariates of interest, there were no significant differences between colon cancer screening among black populations compared to their white counterparts (aOR=.81; 95% CI=0.40-1.64). Age and education independently predicted being screened for colon cancer. Graduating from college increased an individual’s odds of being screened for colon cancer (OR= 2.1, 95% CI: 1.1-4.0). The odds also increased for individuals between the age of 55 to 64 (OR=4.2, 95% CI: 3.2-5.3) and ages 65 to 74 (OR=10.0, 95% CI: 6.8-14.8). Our study did not find significant differences in colon cancer screening by race/ethnicity in these two states. It is possible the racial and ethnic composition of the states contributed to the observed findings. West Virginia and Oregon are predominantly white. Smaller subpopulation groups within the national BRFSS dataset may not be sufficient to detect important differences in screenings. Furthermore, it is possible that several factors associated with screening (age, education) may be associated with race/ethnicity but are stronger predictors than race/ethnicity itself. Regular screening for colorectal cancer can help with detecting and treating colon cancer. Additional efforts to increase the general knowledge of colorectal cancer risks should be encouraged for individuals who did not graduate from college and are between 45 to 55 years old.

Kolorektal cancer är en sjukdom som drabbar individer över 60 års ålder och är den tredje vanligaste cancerformen i Sverige. Syftet med denna litteraturstudie var att redogöra hur individerna upplever livskvalitet efter kolorektal kirurgiskt ingrepp. Litteraturstudien gjordes utifrån ett systematiskt tillvägagångssätt. Litteratursökningen utfördes i databaserna Cinahl, Medline, PsychInfo, PubMed, Samsök samt The Cochrane Library. Kvantitativa studier inkluderades vilka kvalitetsgranskades av båda författarna oberoende av varandra med hjälp av ett modifierat granskningsprotokoll. Resultatet visade en sexuell dysfunktion, förändrad fysisk - social funktion, magtarm - urinblåse dysfunktion, psykiska - emotionella förändringar, förändrad kroppsuppfattning och framtidsperspektiv hos patienter som hade genomgått ett kirurgiskt ingrepp. Fler studier behövs för att slutsatser med hög evidensgrad skall kunna dras. / Colorectal cancer is a disease that affects individuals over age 60 and is the third most common cancer form in Sweden. The aim of this study was to report on how individuals experienced their quality of life after colorectal surgery. The literature review was made in accordance to a systematic procedure. The literature searching was made in the databases CINAHL, Medline, PsychInfo, PubMed, Search, and The Cochrane Library. Quantitative studies were included and the quality was assessed by both authors independently of each other using a modified audit protocol. The results showed a sexual dysfunction, changed physical-social function, gastrointestinal- bladder dysfunction, mental- emotional changes, and changes in body image and future perspectives in patients who had undergone a surgical procedure. Further studies needs to make conclusion with high evidence.

Colorectal cancer is the third most common cancer in the United States with a 5-year late-stage survival rate of only 14%. Due to the lack of translation between animal models and clinical trials as well as the inefficacy of many chemotherapeutics in initial clinical trials, researchers are turning to in vitro drug screening models in an effort to mimic the conditions in vivo. This research project aimed to validate an in vitro tumor culture model within a microfluidic device using a clinically relevant chemotherapy drug. The first experiment consisted of a cell density and drug concentration study to determine the correct cell density and oxaliplatin concentration combinations that would result in a spectrum of quantifiable effects on the tumor cells. This experiment was then converted from a monolayer cell culture on glass into a 2D culture on top of a fibrin extracellular matrix (ECM) to ensure that the cells would respond in a similar way to the drug in the presence of an ECM as they did in the first experiment. The third experiment involved SW620 cells cultured within the fibrin hydrogel to create a 3D tumor model that better mimics the growing conditions in vivo. The goal of this experiment was again to ensure that the cells would respond in the same way to the oxaliplatin treatments as the previous experiments when adding complexity to the model. The final experiment was then to convert this 3D experiment performed in chamber slides into a 3D culture within a microfluidic device with media and oxaliplatin treatments perfused through the chamber using a syringe pump. The purpose of this experiment was to assess whether tumor cells could grow and survive within a microfluidic device with interstitial flow as well as determining if they responded as expected to the oxaliplatin treatment. The first three experiments performed within chamber slides showed that tumor count and average tumor size decreased with increasing oxaliplatin concentrations as expected, which is comparable to the in vivo tumor response to the drug. The fourth experiment demonstrated that, although cells are able to grow within the microfluidic device, this model did not accurately replicate the in vivo condition and future work needs to be aimed at improving the design of the device as well as optimizing parameters within the experiment.

<p>Colorectal cancer (CRC) is the third most prevalent cancer in the United States and estimated to affect 151,030 people and kill 52,580 people in 2022. Although some populations are more susceptible for CRC due to inherited cancer-causing mutations or having family history of CRC, most CRC cases occur sporadically with accumulation of a series of somatic mutation in tumor suppressor genes, oncogenes, and DNA repair system in the colon. Mutations in the adenomatous polyposis coli <em>(APC)</em> and the Kirsten rat sarcoma viral oncogene homologue <em>(KRAS)</em> are known as cancer driving mutations which are most frequently identified genetic lesions at early stages of sporadic CRC development. To evaluate effective drugs for prevention and treatment, preclinical models of CRC that resemble key features of human CRCs are crucial. Genetically modified mouse models (GEMM) of CRC bearing loss of <em>Apc</em> with or without other mutations, such as oncogenic <em>Kras</em> have been valuable tools to study pathobiology, treatment, and prevention of CRC. However, a major limitation of most <em>Apc</em>-mutant GEMMs is the predominant distribution of tumors in the small intestine rather than in the colon. Previously, a murine model bearing colon-specific mutations in <em>Apc</em> and <em>Kras</em> has been reported to develop colon-specific tumorigenesis in the colon, utilizing the <em>carbonic anhydrase 1 promoter/enhancer-Cre recombinase (CAC)</em> in Cre-LoxP system to restrict <em>Apc</em> knockout and a latent expression of oncogenic <em>Kras</em> in the colon tissue. However, only limited features of this model, so called AKC mouse, have been characterized so far. The lack of in depth understanding of this model could potentially hamper its utility for cancer research. Therefore, in Chapter 2 of this dissertation, I first characterized key aspects of disease-related phenotypes including clinical and histopathological features, tumor-elicited inflammation, the transcriptomic profiles, the gut microbial profiles in the AKC mice. Further, comparative analysis has been made on the transcriptomic profiles between AKC mice and human colon cancers with mutations in <em>APC</em> and <em>KRAS</em> at cancer stage II or below to evaluate the utility of the mouse model for studying human CRCs.</p> <p>Chemoprevention is the use of drugs or natural substances to inhibit initiation and delay of the progression of tumorigenesis, which could be a promising approach to reduce the incidence, mortality, and morbidity of CRC. Delta-tocotrienol (𝛿TE) is a natural analogue of vitamin E which has been shown to have antioxidant, anti-inflammatory and anticancer activities. Although its anticancer effects have been studied in different models of CRCs, including carcinogen-induced models, carcinogen-induced colitis-associated models, and colon cancer xenograft models, it has not been tested in a genetic model of sporadic CRC harboring <em>Apc</em> and <em>Kras</em> mutations. Therefore, in Chapter 3, the antitumor effects of 𝛿TE-rich tocotrienols (𝛿TE/gTE) and the potential mechanisms were investigated in AKC mice. 𝛿TE/𝛾TE-supplementation significantly improved the survival of AKC mice and suppressed tumorigenesis in association with inhibition of cell proliferation in the tumors. Further, the anti-tumor effects were correlated with reduction of pro-inflammatory and pro-tumorigenic cytokines, such as interleukin-1b and granulocyte-macrophage colony stimulating factor (GM-CSF), transcriptional enrichment of pathways involved in fatty acid metabolism, and reduction of diacylglycerol (DG) level in the colon tissue.</p> <p>Finally, AKC mice were used for screening the efficacies of other potential chemoprevention candidates, including aspirin, sulindac, and resveratrol in Chapter 4. Aspirin and sulindac are nonsteroidal anti-inflammatory drugs (NSAIDs) and they are among the most studied chemoprevention agents for CRC. However, the long-term regular use of NSAIDs may cause bleedings in the gastrointestinal organ system or hemorrhagic stroke. For aspirin, although extensive studies have shown its beneficial role in the prevention of primary CRC, there are mixed results for its benefit and harms, which may require further identification of populations who will benefit from the regular use of aspirin for prevention of CRC. Resveratrol is a naturally derived polyphenol, which is known for its antioxidant, anti-inflammatory, and antimicrobial activities with generally good safety profile. In our study, when the dietary supplementation of three compounds alone or in combination with 𝛿TE/gTE were examined for its antineoplastic effects in the AKC mice, only aspirin significantly suppressed tumorigenesis with decreased pro-inflammatory and pro-tumorigenic cytokines in the colon without overt toxicity. We found that sulindac induced serious gastric lesions and potential liver toxicity with some animals died earlier than the rest over the study period. Additionally, in this model, resveratrol was not effective in reducing tumorigenesis, in contrast to a previous study where the workgroup used similar genetic model of CRC but different modality to induce the mutations. Our findings add lines of evidence that depending on the use of different models the test compounds, aspirin, sulindac, and resveratrol may exhibit varying cancer prevention effects. Further research is warranted to identify underlying mechanisms that could explain the heterogenous responses to the test compounds and to optimize the interventions. </p>

Colorectal cancer (CRC) is one of the leading causes of cancer death worldwide, accounting for over 600,000 deaths annually. The mortality rate of CRC can be significantly reduced if it is detected early, suggesting the importance of cancer screening in CRC management. Currently, colonoscopy is the gold standard for CRC diagnosis as it is accurate and reliable. However, it is an invasive procedure that is associated with risks of complications, which contributes to the lack of patient compliance in colonoscopy screening. Other noninvasive detection methods suffer from poor sensitivity and specificity. Thus, there remains a great demand for the development of a noninvasive and accurate test for CRC diagnosis. Recently, studies using next-generation sequencing techniques have revealed compositional changes in the intestinal microbiome associated with CRC, implicating the possibility of using fecal microbiome as potential diagnostic markers. Specifically, the level of the gram-negative bacterium, Fusobacterium nucleatum, has been shown to be elevated in CRC patients compared to healthy controls. The work described in this thesis aims to develop unique RNA-cleaving DNAzymes that can distinguish between healthy and CRC stool microbiomes. RNA-cleaving DNAzymes are single stranded DNA molecules that are extensively used as analytical tools for metal ion sensing and bacterial detection. We conducted an in vitro selection experiment and isolated a F. nucleatum-responsive RNA-cleaving DNAzyme sensor, named RFD-FN1, that is activated by a heat stable protein marker by this bacterium. RFD-FN1 is highly specific for F. nucleatum and it has a limit of detection of 107 CFU/mL without culture and a single cell when cultured for 36 hours. The discovery of this novel molecular probe for F. nucleatum presents an important step forward towards the development of a novel DNAzyme-based detection method for colorectal cancer. / Thesis / Master of Science (MSc)

Background and Purpose: Colorectal cancer (CRC) is the third most common cancer, the second leading cause of cancer death, with lower survival rates at later stages. Adherence to CRC screening can prevent the development of cancerous polyps and reduce incidence. Area-level characteristics, such as access to healthcare and deprivation, can create barriers to timely screening, increasing the risk of developing CRC. The degree to which area-level characteristics versus individual-level characteristics are responsible for CRC outcomes, including incidence and stage at diagnosis, are not well-understood. Specifically, deficits in the use of spatial statistical techniques has led to a lack of clarity in the current literature. This study aimed to overcome these deficiencies by identifying and utilizing the optimal measurement for area-level access to healthcare and deprivation, employing robust spatiotemporal and multilevel analytic methods to assess their effects on CRC incidence and late-stage diagnosis in Pennsylvania (PA) at the block group-level from 2008 to 2017. The results of this research will more accurately map areas of high predicted CRC relative risk for targeted public health interventions to reduce the burden of CRC over time. The following three study aims were used to address the research problem: Aim 1: Identify the best predictive measure of access to healthcare for estimating CRC incidence risk at the block group-level in PA from 2008 to 2017. Q1: What is the best measure of access to care for estimating risk of CRC incidence? H1.1: The most comprehensive measurement, Multi-Modal 2SFCA, is optimal for predicting CRC incidence compared to unidimensional distance, availability, and other 2SFCA measures. H1.2: Weighting access to healthcare measures for individual insurance coverage improves predictive performance of CRC incidence. Aim 2: Ascertain the relative risk from area-level deprivation on CRC incidence at the block group-level in PA from 2008 to 2017.Q2: How does area-level deprivation affect CRC incidence? H2.1: WQS will demonstrate the relative importance of an extensive array of SES variables for CRC incidence. H2.2: Higher deprivation will be positively associated with risk of CRC incidence. Aim 3: Determine the individual-level likelihood of being diagnosed with late-stage CRC based on place of residence across PA from 2008 to 2017.Q3: How does place of residence affect the likelihood of developing late-stage CRC incidence after adjusting for individual-level characteristics and covariates? H3.1: PA residents living in areas of worse deprivation and low access to care have a higher likelihood of being diagnosed with late-stage CRC. H3.2: The likelihood of late-stage CRC varies significantly by individual characteristics. Methods: This research used ecologic and cross-sectional study designs to perform secondary data analysis of the cancer registry and publicly available data. The geographic units were block groups in PA (N = 9,740), accessed from the US Census Bureau. The sample included screening age-eligible PA residents, 45-75 years, diagnosed with a primary incident case of CRC from 2008 to 2017 (N=34,250), identified via the PA Cancer Registry. Out-of-state residents at diagnosis and high-risk individuals were excluded. Nine block groups were uninhabitable with no population and thus excluded. Primary exposure variables (i.e., area-level access to healthcare and deprivation) were calculated using the PA Cancer Registry, a provider database, the US Census Bureau’s polygon and network shapefiles, and American Community Survey. Ecologic covariates (see below) were derived from the American Community Survey, the Behavioral Risk Factor Surveillance System, and the USDA’s Rural-Urban Commuting Areas. The PA Cancer Registry provided individual data for patient demographics, tumor characteristics, and insurance coverage. Exploratory spatial, temporal, and spatiotemporal analyses of the CRC data were performed before Aims 1 to 3. Aim 1: CRC cases were aggregated by block group to represent a count of CRC incidence. Area-level access to healthcare measures was calculated using providers’ addresses, population-weighted block group centroids, and road/rail networks (i.e., driving, walking, and public transit). Measures included great-circle distance, driving distance to the nearest provider by miles/time, physician-to-population ratio, enhanced two-step floating catchment area (2SFCA), variable 2SFCA, and multi-modal 2SFCA. Four 15-minute catchment sizes were tested (range = 15-60-minutes). A weighted version of each 2SFCA measure for insurance coverage was calculated. Predictive performance was assessed with model fit statistics from 29 hierarchical Bayesian spatiotemporal Poisson regression models. All models included CRC screening adherence, rurality, age, race, education level, unemployment, and poverty level. Aim 2: CRC cases were aggregated by block group to represent a count of CRC incidence. Area-level deprivation indicators (n=39) were calculated from the American Community Survey’s five-year pooled estimates for demographic, social, economic, and housing characteristics and represented at the census tract or block group-level. Weighted Quantile Sum regression generated an area-level deprivation index, weighting each indicator by its relative relationship with CRC incidence. A hierarchical Bayesian spatiotemporal Poisson regression with conditional autoregressive priors and a first-order autoregressive time series process was used to estimate the relative risk of CRC. The ecologic covariates included in the model were area-level access to healthcare from Aim 1, CRC screening adherence, rurality, age, and sex. Aim 3: Three binary outcome variables represented localized vs. regional, distant, and regional and distant CRC at diagnosis. Aim 1 and 2’s area-level access to healthcare and deprivation measurements were used for this study’s primary exposure variables. The data was split into three time periods (2008-2009, 2010-2013, and 2014-2017) to analyze CRCS coverage mandates from the Affordable Care Act for private insurers in 2010 and Medicare in 2014. Using binomial distributed outcomes, three two-level generalized linear mixed models using hierarchical Bayesian methods with conditional autoregressive priors were run for each time period. Results: There were 34,250 eligible incident cases with 0-6 cases per block group (N=9,731) each year and an average of 3.5 cases per block group for the pooled study period. From 2008 to 2017, the pooled CRC incidence rate was 7.45 cases per 1,000 for 45 to 75 year olds in PA. Scan statistics found the highest CRC burden was in Philadelphia (northeast, west, and south), Pittsburgh, and rural areas in southwest PA (e.g., Westmoreland County and Fayette County) and northcentral PA (e.g., Lycoming County, Clinton County, and Centre County). In PA, yearly crude CRC rates decreased slightly over the ten years (0.80 to 0.72, Δ =-.08), though not empirically tested. Aim 1: The best fitting model used the Multi-Modal 2SFCA, which included aggregated physician-to-population ratios within 45-minutes from the provider facility for population-weighted block group centroids via driving, walking, and public transit of the same distance. Access was generally worst in rural areas and best in urban/suburban areas. Block groups with access one standard deviation above the state median had 27% decreased CRC risk. Weighting for insurance coverage improved a measure’s predictive ability for shorter travel times (i.e., 15-minutes and 30-minutes). Aim 2: Of a 39 indicator deprivation index, nine were statistically significant and three were related to SES (i.e., median household income, the percent of the block group without a high school degree, or living in a house without heating). However, the most important significant indicators belonged to geography and income domains, collectively representing 71% of the relative influence of the index. The area-level deprivation index was significant and positively associated with CRC incidence at the block group-level in PA from 2008 to 2017 (RR: 1.33, 95% CI: 1.32–1.34). Aim 3: After accounting for individual age, race, and insurance coverage, the relationship between area-level access to healthcare and deprivation and late-stage CRC became non-significant. While no area-level effects were significant, several individual-level features had consistent significant findings across outcomes and time periods. At the individual-level, having government insurance and being uninsured had significant positive relationships for all outomes and time periods. Age, and race had significant inverse relationships with late-stage CRC diagnosis. Conclusions: In summary, this study addressed the limitations of previous research by employing innovative measurement techniques, such as the Multi-Modal 2SFCA and Weighted Quantile Sum regression, and rigorous spatiotemporal methods to assess the impact of area-level access to healthcare and deprivation on CRC incidence and late-stage diagnosis. The findings highlight the importance of considering walking and public transit access to healthcare in relation to CRC incidence. Additionally, the study demonstrated the effectiveness of the WQS method in calculating an accurate area-level deprivation index, which enhanced the prediction of CRC incidence and identified high-risk areas for targeted interventions. However, individual-level characteristics, particularly insurance coverage, were found to be more influential in predicting the stage at which CRC was diagnosed than area-level effects. Regardless, using inferences and similar methods from this dissertation improves disease mapping and resource allocation for CRCS outreach, supports evidence for policy, and helps guide the development of tailored public health interventions to ultimately reduce the burden of CRC. / Epidemiology

京都大学 / 新制・課程博士 / 博士(医学) / 甲第24804号 / 医博第4996号 / 新制||医||1067(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 武藤 学, 教授 藤田 恭之, 教授 川口 義弥 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Introduction: Le cancer colorectal demeure un grave problème de santé publique au Canada. Les programmes de dépistage pourraient réduire l'incidence du cancer colorectal et la mortalité qui lui est associée. Une coloscopie de haute qualité est considérée comme un moyen rentable de prévenir le cancer en identifiant et en éliminant les lésions précurseurs du cancer. Bien que la coloscopie puisse servir de mesure préventive contre le cancer, la procédure peut imposer un fardeau supplémentaire à la santé publique par l'enlèvement et l'évaluation histologique de polypes colorectaux diminutifs et insignifiants, qui présentent un risque minime d'histologie avancée ou de cancer. La technologie de l'amélioration de l'image permettrait aux médecins de réséquer et de rejeter les polypes diminutifs ou de diagnostiquer et de laisser les polypes rectosigmoïdiens diminutifs sans examen histopathologique. Malgré la disponibilité de systèmes informatiques de caractérisation des polypes, la pratique du diagnostic optique reste limitée en raison de la crainte d'un mauvais diagnostic de cancer, d'une mauvaise surveillance des patients et des problèmes médico-légaux correspondants. Il est donc indispensable d'élaborer des stratégies alternatives de résection et d'élimination non optiques pour améliorer la précision et la sécurité du diagnostic optique et l'adapter à la pratique clinique. Ces stratégies doivent répondre à des critères cliniques simples et ne nécessitent pas de formation supplémentaire ni de dispositifs d'amélioration de l'image. De plus, la pratique sûre du diagnostic optique, la prise de décision appropriée concernant la technique de polypectomie ou l'intervalle de surveillance dépendent de l'estimation précise de la taille des polypes. La variabilité inter-endoscopistes dans la mesure de la taille des polypes exige le développement de méthodes fiables et validées pour augmenter la précision de la mesure de la taille. Une balance virtuelle intégrée à un endoscope haute définition est actuellement disponible pour le calcul automatique de la taille des polypes, mais sa faisabilité clinique n'a pas encore été établie. En dehors des points susmentionnés, une coloscopie de haute qualité nécessite l'examen complet de la muqueuse colique, ainsi que la visualisation de la valve iléocæcale et de l'orifice appendiculaire. À ce jour, aucune solution informatique n'a été capable d'assister les endoscopistes pendant les coloscopies en temps réel en détectant et en différenciant les points de repère cæcaux de façon automatique. Objectifs: Les objectifs de cette thèse sont : 1) d'étudier l'effet de la limitation du diagnostic optique aux polypes de 1 à 3 mm sur la sécurité du diagnostic optique pour le traitement des polypes diminutifs et l'acceptation par les endoscopistes de son utilisation dans les pratiques en temps réel tout en préservant ses potentiels de temps et de rentabilité ; 2) élaborer et examiner des stratégies non optiques de résection et d'élimination qui peuvent remplacer le diagnostic optique tout en offrant les mêmes possibilités d'économie de temps et d'argent ; 3) examiner la précision relative d'un endoscope à échelle virtuelle pour mesurer la taille des polypes ; 4) former, valider et tester un modèle d'intelligence artificielle qui peut prédire la complétude d'une procédure de coloscopie en identifiant les points de repère anatomiques du cæcum (c'est-à-dire la valve iléo-cæcale et l'orifice appendiculaire) et en les différenciant les uns des autres, des polypes et de la muqueuse normale. Méthodes: Pour atteindre le premier objectif de cette thèse, une analyse post-hoc de trois études prospectives a été réalisée pour évaluer la proportion de patients chez lesquels des adénomes avancés ont été découverts et le diagnostic optique a entraîné une surveillance retardée dans trois groupes de taille de polypes : 1–3, 1–5, et 1–10 mm. Pour atteindre le second objectif de cette thèse, deux stratégies non optiques ont été développées et testées dans deux études prospectives: une stratégie de résection et d'élimination basée sur la localisation qui utilise la localisation anatomique des polypes pour classer les polypes du côlon en non-néoplasiques ou néoplasiques à faible risque et une stratégie de résection et d'élimination basée sur les polypes qui attribue des intervalles de surveillance en fonction du nombre et de la taille des polypes. Dans les trois études, la concordance de l'attribution d'intervalles de surveillance basée sur un diagnostic optique à haute confiance ou sur des stratégies non optiques avec les recommandations basées sur la pathologie, ainsi que la proportion d'examens pathologiques évités et la proportion de communications immédiates d'intervalles de surveillance, ont été évaluées. Le troisième objectif de cette thèse a été abordé par le biais d'une étude de faisabilité pilote prospective qui a utilisé la mesure de spécimens de polypes immédiatement après leur prélèvement, suite à une polypectomie par un pied à coulisse Vernier comme référence pour comparer la précision relative des mesures de la taille des polypes entre les endoscopistes et un endoscope à échelle virtuelle. Enfin, le quatrième objectif de cette thèse a été évalué par l'enregistrement et l'annotation prospective de vidéos de coloscopie. Des images non modifiées de polype, de valve iléo-caecale, d'orifice appendiculaire et de muqueuse normale ont été extraites et utilisées pour développer et tester un modèle de réseau neuronal convolutionnel profond pour classer les images pour les points de repère qu'elles contiennent. Résultats: La réduction du seuil du diagnostic optique favoriserait la sécurité du diagnostic optique en diminuant de manière significative le risque d'écarter un polype avec une histologie avancée ou la mauvaise surveillance d'un patient avec de tels polypes. En outre, les stratégies non optiques de résection et d'élimination pourraient dépasser le critère de référence d'au moins 90% de concordance dans l'attribution des intervalles de surveillance post-polypectomie par rapport aux décisions basées sur l'évaluation pathologique. De plus, il a été démontré que l'endoscope à échelle virtuelle est plus précis que l'estimation visuelle de la taille des polypes en temps réel. Enfin, un modèle d'apprentissage profond s'est révélé très efficace pour détecter les repères cæcaux, les polypes et la muqueuse normale, à la fois individuellement et en combinaison. Discussion: La prédiction histologique optique des polypes de 1 à 3 mm est une approche efficace pour améliorer la sécurité et la faisabilité de la stratégie de résection et d'écartement dans la pratique. Les approches non optiques de résection et d'élimination offrent également des alternatives viables au diagnostic optique lorsque les endoscopistes ne sont pas en mesure de répondre aux conditions de mise en œuvre systématique du diagnostic optique, ou lorsque la technologie d'amélioration de l'image n'est pas accessible. Les stratégies de résection et de rejet, qu'elles soient optiques ou non, pourraient réduire les coûts supplémentaires liés aux examens histopathologiques et faciliter la communication du prochain intervalle de surveillance le même jour que la coloscopie de référence. Un endoscope virtuel à échelle réduite faciliterait l'utilisation du diagnostic optique pour la détection des polypes diminutifs et permet une prise de décision appropriée pendant et après la coloscopie. Enfin, le modèle d'apprentissage profond peut être utile pour promouvoir et contrôler la qualité des coloscopies par la prédiction d'une coloscopie complète. Cette technologie peut être intégrée dans le cadre d'une plateforme de vérification et de génération de rapports qui élimine le besoin d'intervention humaine. Conclusion: Les résultats présentés dans cette thèse contribueront à l'état actuel des connaissances dans la pratique de la coloscopie concernant les stratégies pour améliorer l'efficacité de la coloscopie dans la prévention du cancer colorectal. Cette étude fournira des indications précieuses pour les futurs chercheurs intéressés par le développement de méthodes efficaces de traitement des polypes colorectaux diminutifs. Le diagnostic optique nécessite une formation complémentaire et une mise en œuvre à l'aide de modules de caractérisation informatisés. En outre, malgré la lenteur de l'adoption des solutions informatiques dans la pratique clinique, la coloscopie assistée par l'IA ouvrira la voie à la détection automatique, à la caractérisation et à la rédaction semi-automatique des rapports de procédure. / Introduction: Colorectal cancer remains a critical public health concern in Canada. Screening programs could reduce the incidence of colorectal cancer and its associated mortality. A high-quality colonoscopy is appraised to be a cost-effective means of cancer prevention through identifying and removing cancer precursor lesions. Although colonoscopy can serve as a preventative measure against cancer, the procedure can impose an additional burden on the public health by removing and histologically evaluating insignificant diminutive colorectal polyps, which pose a minimal risk of advanced histology or cancer. The image-enhance technology would enable physicians to resect and discard diminutive polyps or diagnose and leave diminutive rectosigmoid polyps without histopathology examination. Despite the availability of computer-based polyp characterization systems, the practice of optical diagnosis remains limited due to the fear of cancer misdiagnosis, patient mismanagement, and the related medicolegal issues. Thus, alternative non-optical resection and discard strategies are imperative for improving the accuracy and safety of optical diagnosis for adaptation to clinical practice. These strategies should follow simple clinical criteria and do not require additional education or image enhanced devices. Furthermore, the safe practice of optical diagnosis, adequate decision-making regarding polypectomy technique, or surveillance interval depends on accurate polyp size estimation. The inter-endoscopist variability in polyp sizing necessitates the development of reliable and validated methods to enhance the accuracy of size measurement. A virtual scale integrated into a high-definition endoscope is currently available for automated polyp sizing, but its clinical feasibility has not yet been demonstrated. In addition to the points mentioned above, a high-quality colonoscopy requires the complete examination of the entire colonic mucosa, as well as the visualization of the ileocecal valve and appendiceal orifice. To date, no computer-based solution has been able to support endoscopists during live colonoscopies by automatically detecting and differentiating cecal landmarks. Aims: The aims of this thesis are: 1) to investigate the effect of limiting optical diagnosis to polyps 1–3mm on the safety of optical diagnosis for the management of diminutive polyps and the acceptance of endoscopists for its use in real-time practices while preserving its time- and cost-effectiveness potentials; 2) to develop and examine non-optical resect and discard strategies that can replace optical diagnosis while offering the same time- and cost-saving potentials; 3) to examine the relative accuracy of a virtual scale endoscope for measuring polyp size; 4) to train, validate, and test an artificial intelligence-empower model that can predict the completeness of a colonoscopy procedure by identifying cecal anatomical landmarks (i.e., ileocecal valve and appendiceal orifice) and differentiating them from one another, polyps, and normal mucosa. Methods: To achieve the first aim of this thesis, a post-hoc analysis of three prospective studies was performed to evaluate the proportion of patients in which advanced adenomas were found and optical diagnosis resulted in delayed surveillance in three polyp size groups: 1‒3, 1‒5, and 1‒10 mm. To achieve the second aim of this thesis, two non-optical strategies were developed and tested in two prospective studies: a location-based resect and discard strategy that uses anatomical polyp location to classify colon polyps into non-neoplastic or low-risk neoplastic and a polyp-based resect and discard strategy that assigns surveillance intervals based on polyp number and size. In all three studies, the agreement of assigning surveillance intervals based on high-confidence optical diagnosis or non-optical strategies with pathology-based recommendations, as well as the proportion of avoided pathology examinations and the proportion of immediate surveillance interval communications, was evaluated. The third aim of this thesis was addressed through a prospective pilot feasibility study that used the measurement of polyp specimens immediately after retrieving, following a polypectomy by a Vernier caliper as a reference to compare the relative accuracy of polyp size measurements between endoscopists and a virtual scale endoscope. Finally, the fourth aim of this thesis was assessed through prospective recording and annotation of colonoscopy videos. Unaltered images of polyp, ileocecal valve, appendiceal orifice and normal mucosa were extracted and used to develop and test a deep convolutional neural network model for classifying images for the containing landmarks. Results: Reducing the threshold of optical diagnosis would promote the safety of optical diagnosis by significantly decreasing the risk of discarding a polyp with advanced histology or the mismanagement of a patient with such polyps. Additionally, the non-optical resect and discard strategies could surpass the benchmark of at least 90% agreement in the assignment of post-polypectomy surveillance intervals compared with decisions based on pathologic assessment. Moreover, the virtual scale endoscope was demonstrated to be more accurate than visual estimation of polyp size in real-time. Finally, a deep learning model proved to be highly effective in detecting cecal landmarks, polyps, and normal mucosa, both individually and in combination. Discussion: Optical histology prediction of polyps 1‒3 mm in size is an effective approach to enhance the safety and feasibility of resect and discard strategy in practice. Non-optical resect and discard approaches also offer feasible alternatives to optical diagnosis when endoscopists are unable to meet the conditions for routine implementation of optical diagnosis, or when image-enhanced technology is not accessible. Both optical and non-optical resect and discard strategies could reduce additional costs related to histopathology examinations and facilitate the communication of the next surveillance interval in the same day as the index colonoscopy. A virtual scale endoscope would facilitate the use of optical diagnosis for the detection of diminutive polyps and allows for appropriate decision-making during and after colonoscopy. Additionally, the deep learning model may be useful in promoting and monitoring the quality of colonoscopies through the prediction of a complete colonoscopy. This technology may be incorporated as part of a platform for auditing and report generation that eliminates the need for human intervention. Conclusion: The results presented in this thesis will contribute to the current state of knowledge in colonoscopy practice regarding strategies for improving the efficacy of colonoscopy in the prevention of colorectal cancer. This study will provide valuable insights for future researchers interested in developing effective methods for treating diminutive colorectal polyps. Optical diagnosis requires further training and implementation using computer-based characterization modules. Furthermore, despite the slow adoption of computer-based solutions in clinical practice, AI-empowered colonoscopy will eventually pave the way for automatic detection, characterization, and semi-automated completion of procedure reports in the future.