Benefits and challenges in implementation of artificial intelligence in colonoscopy: World Endoscopy Organization position statement

The number of artificial intelligence (AI) tools for colonoscopy on the market is increasing with supporting clinical evidence. Nevertheless, their implementation is not going smoothly for a variety of reasons, including lack of data on clinical benefits and cost-effectiveness, lack of trustworthy guidelines, uncertain indications, and cost for implementation. To address this issue and better guide practitioners, the World Endoscopy Organization (WEO) has provided its perspective about the status of AI in colonoscopy as the position statement. WEO Position Statement: Statement 1.1: Computer-aided detection (CADe) for colorectal polyps is likely to improve colonoscopy effectiveness by reducing adenoma miss rates and thus increase adenoma detection; Statement 1.2: In the short term, use of CADe is likely to increase health-care costs by detecting more adenomas; Statement 1.3: In the long term, the increased cost by CADe could be balanced by savings in costs related to cancer treatment (surgery, chemotherapy, palliative care) due to CADe-related cancer prevention; Statement 1.4: Health-care delivery systems and authorities should evaluate the cost-effectiveness of CADe to support its use in clinical practice; Statement 2.1: Computer-aided diagnosis (CADx) for diminutive polyps (≤5 mm), when it has sufficient accuracy, is expected to reduce health-care costs by reducing polypectomies, pathological examinations, or both; Statement 2.2: Health-care delivery systems and authorities should evaluate the cost-effectiveness of CADx to support its use in clinical practice; Statement 3: We recommend that a broad range of high-quality cost-effectiveness research should be undertaken to understand whether AI implementation benefits populations and societies in different health-care systems

Radiografers rutiner før administrering av jodholdig kontrastmiddel på CT

Introduksjon: For å oppdage sykdom på CT-bilder er det ofte nødvendig med intravenøst jodholdig kontrastmiddel (JKM). Det finnes flere risikofaktorer som kan føre til milde eller akutte bivirkninger av kontrastmiddelet. ESUR (European Society of Urogenital Radiology) har listet opp 16 risikofaktorer i en sjekkliste. Erfaringer fra praksis har vist at rutinene for å avdekke risikofaktorer, samt hvilke risikofaktorer og pasientgrupper som kontrolleres, er ulik blant sykehusene i Helse Midt-Norge. Målet med oppgaven er å kartlegge rutiner til radiografer før administrering av JKM blant CT-laboratorier i Helse Midt-Norge. I tillegg vil vi undersøke i hvilken grad dagens rutiner samsvarer med ESUR sin sjekkliste som inneholder risikofaktorer for JKM. Metode: Vi gjennomførte en tverrsnittsundersøkelse av dagens rutiner hos radiografer på CT. Det som inngikk i spørsmålene i spørreskjemaet var hvordan radiografene kontrollerer pasienter før administrering av JKM, hvilke pasientgrupper som blir kontrollert og hvilken fremgangsmåte som benyttes. Det ble sendt ut et elektronisk spørreskjema til totalt 185 radiografer fordelt på 15 CT-laboratorier, ved åtte sykehus i Midt-Norge. Resultat: Totalt 65 respondenter deltok i spørreundersøkelsen. Dette ga en svarprosent på 35%. Resultatene fra spørreundersøkelsen fremhevet ulike fremgangsmåter for å avdekke risikofaktorer. 97% av respondentene stilte faste muntlige spørsmål til pasientene og kun 6 av 65 respondenter rapporterte at de brukte fast skriftlig sjekkliste som fremgangsmåte. Flertallet av sykehusene (>90%) kontrollerte nyresykdom og glomerulær filtrasjonsrate (GFR). Ingen sykehus spurte pasientene om aminoglykosider eller interleukin 2. Konklusjon: Resultatene fra spørreundersøkelsen viser at seks risikofaktorer på sjekklisten til ESUR blir prioritert å kontrollere før pasienten kan få administrert JKM. Disse risikofaktorene er tidligere reaksjoner på jodert kontrast, allergi som krever behandling, astma, diabetes mellitus, metformin, og nyresykdom (inklusiv sjekk av GFR). De fleste radiografer som deltok i undersøkelsen bruker faste muntlige spørsmål som fremgangsmåte for å avdekke risikofaktorer før administrering av JKM på CT

Benefits and challenges in implementation of artificial intelligence in colonoscopy: World Endoscopy Organization position statement

The number of artificial intelligence (AI) tools for colonoscopy on the market is increasing with supporting clinical evidence. Nevertheless, their implementation is not going smoothly for a variety of reasons, including lack of data on clinical benefits and cost-effectiveness, lack of trustworthy guidelines, uncertain indications, and cost for implementation. To address this issue and better guide practitioners, the World Endoscopy Organization (WEO) has provided its perspective about the status of AI in colonoscopy as the position statement. WEO position statement: Statement 1.1: Computer-aided detection (CADe) for colorectal polyps is likely to improve colonoscopy effectiveness by reducing adenoma miss rates and thus increase adenoma detection; Statement 1.2: In the short-term, use of CADe is likely to increase healthcare costs by detecting more adenomas; Statement 1.3: In the long-term, the increased cost by CADe could be balanced by savings in costs related to cancer treatment (surgery, chemotherapy, palliative care) due to CADe-related cancer prevention; Statement 1.4: Healthcare delivery systems and authorities should evaluate the cost effectiveness of CADe to support its use in clinical practice; Statement 2.1: Computer-aided diagnosis (CADx) for diminutive polyps (<=5mm), when it has sufficient accuracy, is expected to reduce healthcare costs by reducing polypectomies, pathological examinations, or both; Statement 2.2: Healthcare delivery systems and authorities should evaluate the cost effectiveness of CADx to support its use in clinical practice; Statement 3: We recommend that a broad range of high-quality cost-effectiveness research should be undertaken to understand whether AI-implementation benefits populations and societies in different healthcare systems

Benefits and challenges in implementation of artificial intelligence in colonoscopy: World Endoscopy Organization position statement.

The number of artificial intelligence (AI) tools for colonoscopy on the market is increasing with supporting clinical evidence. Nevertheless, their implementation is not going smoothly for a variety of reasons, including lack of data on clinical benefits and cost-effectiveness, lack of trustworthy guidelines, uncertain indications, and cost for implementation. To address this issue and better guide practitioners, the World Endoscopy Organization (WEO) has provided its perspective about the status of AI in colonoscopy as the position statement. WEO Position Statement: Statement 1.1: Computer-aided detection (CADe) for colorectal polyps is likely to improve colonoscopy effectiveness by reducing adenoma miss rates and thus increase adenoma detection; Statement 1.2: In the short term, use of CADe is likely to increase health-care costs by detecting more adenomas; Statement 1.3: In the long term, the increased cost by CADe could be balanced by savings in costs related to cancer treatment (surgery, chemotherapy, palliative care) due to CADe-related cancer prevention; Statement 1.4: Health-care delivery systems and authorities should evaluate the cost-effectiveness of CADe to support its use in clinical practice; Statement 2.1: Computer-aided diagnosis (CADx) for diminutive polyps (≤5 mm), when it has sufficient accuracy, is expected to reduce health-care costs by reducing polypectomies, pathological examinations, or both; Statement 2.2: Health-care delivery systems and authorities should evaluate the cost-effectiveness of CADx to support its use in clinical practice; Statement 3: We recommend that a broad range of high-quality cost-effectiveness research should be undertaken to understand whether AI implementation benefits populations and societies in different health-care systems

The rate and spectrum of mosaic mutations during embryogenesis revealed by RNA sequencing of 49 tissues

Background: Mosaic mutations acquired during early embryogenesis can lead to severe early-onset genetic disorders and cancer predisposition, but are often undetectable in blood samples. The rate and mutational spectrum of embryonic mosaic mutations (EMMs) have only been studied in few tissues, and their contribution to genetic disorders is unknown. Therefore, we investigated how frequent mosaic mutations occur during embryogenesis across all germ layers and tissues. Methods: Mosaic mutation detection in 49 normal tissues from 570 individuals (Genotype-Tissue Expression (GTEx) cohort) was performed using a newly developed multi-tissue, multi-individual variant calling approach for RNA-seq data. Our method allows for reliable identification of EMMs and the developmental stage during which they appeared. Results: The analysis of EMMs in 570 individuals revealed that newborns on average harbor 0.5-1 EMMs in the exome affecting multiple organs (1.3230 × 10-8 per nucleotide per individual), a similar frequency as reported for germline de novo mutations. Our multi-tissue, multi-individual study design allowed us to distinguish mosaic mutations acquired during different stages of embryogenesis and adult life, as well as to provide insights into the rate and spectrum of mosaic mutations. We observed that EMMs are dominated by a mutational signature associated with spontaneous deamination of methylated cytosines and the number of cell divisions. After birth, cells continue to accumulate somatic mutations, which can lead to the development of cancer. Investigation of the mutational spectrum of the gastrointestinal tract revealed a mutational pattern associated with the food-borne carcinogen aflatoxin, a signature that has so far only been reported in liver cancer. Conclusions: In summary, our multi-tissue, multi-individual study reveals a surprisingly high number of embryonic mosaic mutations in coding regions, implying novel hypotheses and diagnostic procedures for investigating genetic causes of disease and cancer predisposition.This project has received funding from the European Union’s H2020 research and innovation programme under grant agreement no. 635290 (PanCanRisk). We acknowledge support by the Faculty of Medicine of the University of Tübingen, the Spanish Ministry of Economy and Competitiveness, “Centro de Excelencia Severo Ochoa 2013-2017,” SEV-2012-0208, and the CERCA Programme/Generalitat de Catalunya. LZ is supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Research Fellowship scheme (846614)