{"id":6361,"date":"2023-10-11T20:13:23","date_gmt":"2023-10-11T20:13:23","guid":{"rendered":"https:\/\/dailyai.com\/?p=6361"},"modified":"2023-10-11T20:21:52","modified_gmt":"2023-10-11T20:21:52","slug":"ai-models-helps-brain-surgeons-detect-and-analyze-tumor-types-on-the-fly","status":"publish","type":"post","link":"https:\/\/dailyai.com\/nl\/2023\/10\/ai-models-helps-brain-surgeons-detect-and-analyze-tumor-types-on-the-fly\/","title":{"rendered":"Nieuw AI-model helpt hersenchirurgen tumoren on the fly te analyseren"},"content":{"rendered":"

Hersenchirurgen worstelen vaak met kritieke beslissingen tijdens het tumorverwijderingsproces.\u00a0<\/b><\/p>\n

Nu hebben Nederlandse wetenschappers een AI-tool ge\u00efntroduceerd om te helpen bij het intrachirurgische besluitvormingsproces, waarmee chirurgen supersnel inzicht krijgen in tumortypen en subtypen.<\/p>\n

Volgens een recente <\/span>studie gepubliceerd in Nature<\/span><\/a>De AI onderzoekt specifieke segmenten van het DNA van een tumor en identificeert daarbij verschillende chemische structuren. <\/span><\/p>\n

Deze analyse geeft inzicht in het type tumor en mogelijk het subtype. Zulke tijdige informatie kan chirurgen helpen bij hun aanpak van de chirurgische ingreep.<\/span><\/p>\n

\"Het is noodzakelijk dat het tumorsubtype bekend is op het moment van de operatie\", zegt Jeroen de Ridder, universitair hoofddocent in het UMC Utrecht. \"Wat we nu op unieke wijze mogelijk hebben gemaakt, is dat deze zeer fijnmazige, robuuste, gedetailleerde diagnose al tijdens de operatie kan worden uitgevoerd.\"<\/span><\/p>\n

Hun deep learning-systeem, Sturgeon genaamd, werd onderworpen aan strenge tests. In bepaalde initi\u00eble tests weigerde de AI een diagnose te stellen vanwege dubbelzinnige gegevens.<\/span><\/p>\n

Over het geheel genomen toonden de onderzoekers de real-time effectiviteit van het model aan bij 25 operaties, waarbij een snelle diagnostische doorlooptijd van minder dan 90 minuten werd bereikt, veel sneller dan bij traditionele methoden. 72% van de diagnoses waren correct, maar zeven haalden de vereiste betrouwbaarheidsdrempel niet.<\/p>\n

Terwijl het standaard diagnostische proces bestaat uit microscopisch onderzoek van hersentumormonsters, biedt uitgebreide genetische sequencing diepere inzichten. Echter, zoals Dr. Alan Cohen van Johns Hopkins benadrukte: \"We moeten een behandeling starten zonder te weten wat we behandelen.\"<\/span><\/p>\n

Dr. de Ridder legde verder uit waartoe de AI in staat is: \"Het kan zelf uitzoeken waar het naar kijkt en een robuuste classificatie maken.\"<\/span><\/p>\n

Toch blijven er uitdagingen bestaan. Variabiliteit binnen de tumor, steekproefgrootte en bepaalde ongrijpbare tumoren kunnen problemen opleveren. Marc Pag\u00e8s-Gallego, co-auteur van het onderzoek, gaf wat context over hoe ze deze problemen hebben aangepakt.<\/span><\/p>\n

Dr. Sebastian Brandner van het University College London gaf commentaar op de praktische aspecten en stelde: \"De implementatie zelf is minder eenvoudig dan vaak wordt gesuggereerd.\"<\/span><\/p>\n

Hoewel de tool een belangrijke stap voorwaarts betekent, heeft hij ook zijn beperkingen.\u00a0<\/span><\/p>\n

A<\/span>Dr. Cohen gaf toe: \"We hebben wat winst geboekt, maar niet zoveel in de behandeling als in het begrijpen van het moleculaire profiel van de tumoren.\"<\/span><\/p>\n

Meer over het onderzoek<\/span><\/h2>\n

De innovatieve tool 'Sturgeon' maakt gebruik van deep learning om de intraoperatieve classificatie van hersentumoren te verbeteren, waardoor betere chirurgische beslissingen kunnen worden genomen.\u00a0<\/span><\/p>\n

Het model is ontworpen om 'ultrasnel' tumortypes en subtypes te classificeren.<\/span><\/p>\n

    \n
  • Uitdagingen:<\/b> Het classificeren van tumoren tijdens een operatie is moeilijk vanwege de beperkte sequentietijd en onzekere gegevensdekking.\u00a0<\/span><\/li>\n
  • De oplossing van Sturgeon:<\/b> Dit deep learning-systeem gebruikt gegevens die zijn afgeleid van algemeen beschikbare methyleringsarraygegevens, die worden gebruikt om hersentumoren te profileren. Sturgeon besteedt intensieve computertaken uit om de rekenkracht tijdens de operatie te minimaliseren.<\/span><\/li>\n
  • Prestaties:<\/b> Het model heeft consistente resultaten laten zien, maar houdt vaak geen rekening met intratumor diversiteit. Het leverde de juiste diagnose op in 72% van de chirurgische tests.\u00a0<\/span><\/li>\n
  • Toekomstige ontwikkeling:<\/b> Naarmate er meer gegevens worden verzameld, zullen de gegevens van Sturgeon worden uitgebreid, hoewel beperkingen op het delen van gegevens vanwege privacyoverwegingen het moeilijk maken om te leren van andere instellingen.\u00a0<\/span><\/li>\n
  • Beperkingen:<\/b> Een mogelijke beperking is de benodigde hoeveelheid weefsel. Het model vereist een monstergrootte van ongeveer 5 x 5 x 5 mm voor de beste resultaten, maar er is met succes voldoende DNA ge\u00ebxtraheerd uit kleinere monsters.<\/span><\/li>\n<\/ul>\n

    Cruciaal is dat de resultaten van tumordiagnostiek met Sturgeon binnen 90 minuten kunnen worden bereikt, wat in lijn is met de chirurgische tijdlijnen. Dit geeft chirurgen real-time inzichten, waardoor ze betere beslissingen kunnen nemen tijdens de operatie.\u00a0<\/span><\/p>\n

    Hoewel de gegevens van Sturgeon nuttig zijn, zouden ze volgens het onderzoek idealiter worden gebruikt naast de beoordeling van een getrainde patholoog.\u00a0<\/span><\/p>\n

    Sturgeon voegt zich bij de vele geavanceerde medisch geori\u00ebnteerde AI-modellen die dit jaar zijn gemaakt en illustreren het vermogen van de technologie om de resultaten in de gezondheidszorg te transformeren.<\/p>","protected":false},"excerpt":{"rendered":"

    Hersenchirurgen worstelen vaak met kritieke beslissingen tijdens het tumorverwijderingsproces. Nederlandse wetenschappers hebben nu een AI-tool ge\u00efntroduceerd om te helpen bij het intrachirurgische besluitvormingsproces, door chirurgen ultrasnel inzicht te geven in tumortypes en subtypes. Volgens een recent onderzoek, gepubliceerd in Nature, onderzoekt de AI specifieke segmenten van het DNA van een tumor en identificeert daarbij verschillende chemische structuren. Deze analyse geeft inzicht in het type tumor en mogelijk het subtype. Zulke tijdige informatie kan chirurgen helpen bij hun aanpak van de chirurgische ingreep. \"Het is van groot belang dat het subtype van de tumor bekend is op het moment van de operatie\", zegt Jeroen de Ridder, an<\/p>","protected":false},"author":2,"featured_media":6362,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[203,204,101],"class_list":["post-6361","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-biotech","tag-healthcare","tag-medtech"],"yoast_head":"\nNew AI model helps brain surgeons analyze tumors on the fly | DailyAI<\/title>\n<meta name=\"description\" content=\"Brain surgeons often grapple with critical decisions when addressing the boundaries of tumors.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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