摘要
一位新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-人工智能的新研究是一篇报道的主题。根据NewsRx编辑在爱尔兰都柏林的新闻报道，研究表明：“结直肠癌仍然是世界范围内癌症死亡和发病的主要原因。外科手术是主要的治疗方式，越来越多的是次要的治疗。”这项研究的财政支持来自都柏林大学学院。我们的新闻记者从都柏林大学学院的研究中获得一句话：“然而，随着越来越多的患者被诊断为早期和以大息肉为表现的先兆疾病，从第一次内窥镜检查开始就需要更高的诊断和治疗精度。人工智能领域的快速发展(AI)，结合近红外成像(目前基于Indocya Nine Green(ICG))的广泛可用性，可以实现结肠镜组织分类和显著息肉的预后评估，与当代动态放射灌注成像相似，但其优点是能够在介入手术的时间范围内直接进行。它可以为直接数字化活检提供一种解释的方法，可以指导甚至取代传统的镊子活检，并提供指导边缘（这两个领域在最终切除前的准确率只有大约80%）。我们讨论了AI增强的ICG灌注分析在直肠癌手术中的概念和实践，同时强调了近期和未来的重要进展，包括计算机Visio和时间序列分析的突破性进展，这些进展允许实时定量和分类直肠癌术中荧光灌注信号，在内镜下准确区分正常、良性和恶性组织，目前正在进行国际前瞻性验证(Horizon Europe CLASSICA研究)。下一阶段的进展可能包括基于术中对特定肿瘤内荧光信号模式的详细数字表征。这可能包括T分期和肿瘤内分子过程分析(例如关于血管生成、分化、炎性成分、和肿瘤与基质的比率)，有可能准确预测显微局部对非手术治疗的反应，从而通过决策支持工具实现个性化治疗。这些优点也适用于目前临床试验中出现的下一代荧光团和成像agen。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news reporting out of Dublin, Ireland , by NewsRx editors, research stated, "Colorectal cancer remains a major cause o f cancer death and morbidity worldwide. Surgery is a major treatment modality fo r primary and, increasingly, secondary curative therapy." Financial support for this research came from University College Dublin. Our news journalists obtained a quote from the research from University College Dublin, "However, with more patients being diagnosed with early stage and premal ignant disease manifesting as large polyps, greater accuracy in diagnostic and t herapeutic precision is needed right from the time of first endoscopic encounter . Rapid advancements in the field of artificial intelligence (AI), coupled with widespread availability of near infrared imaging (currently based around indocya nine green (ICG)) can enable colonoscopic tissue classification and prognostic s tratification for significant polyps, in a similar manner to contemporary dynami c radiological perfusion imaging but with the advantage of being able to do so d irectly within interventional procedural time frames. It can provide an explaina ble method for immediate digital biopsies that could guide or even replace tradi tional forceps biopsies and provide guidance re margins (both areas where curren t practice is only approximately 80% accurate prior to definitive excision). Here, we discuss the concept and practice of AI enhanced ICG perfusio n analysis for rectal cancer surgery while highlighting recent and essential nea r-future advancements. These include breakthrough developments in computer visio n and time series analysis that allow for real-time quantification and classific ation of fluorescent perfusion signals of rectal cancer tissue intraoperatively that accurately distinguish between normal, benign, and malignant tissues in sit u endoscopically, which are now undergoing international prospective validation (the Horizon Europe CLASSICA study). Next stage advancements may include detaile d digital characterisation of small rectal malignancy based on intraoperative as sessment of specific intratumoral fluorescent signal pattern. This could include T staging and intratumoral molecular process profiling (e.g. regarding angiogen esis, differentiation, inflammatory component, and tumour to stroma ratio) with the potential to accurately predict the microscopic local response to nonsurgica l treatment enabling personalised therapy via decision support tools. Such advan cements are also applicable to the next generation fluorophores and imaging agen ts currently emerging from clinical trials."
NETL
NSTL