人工智能技术在乳腺癌磁共振影像评估中的应用研究进展

磁共振成像（magnetic resonance imaging,MRI）作为乳腺癌主要的影像学检查手段在其肿瘤诊治过程中发挥重要作用,近年来人工智能（artificial intelligence,AI）技术在医学影像领域发展迅速,在AI技术协助下MRI对乳腺癌的诊断效能进一步提高,在病灶检出、分割、诊断、病理及分子分型、病情预测、疗效评估等临床需求方面均有显著进展,本文就AI在乳腺癌MRI方面的应用研究进展进行综述。     

人工智能在肺部肿瘤影像诊断中的研究进展

肺癌的早期发现、精确诊断对于患者的预后至关重要。影像学能够无创、全面地反映肿瘤的异质性,在肺癌诊断中发挥重要作用。海量影像数据的深入挖掘是影像医师面临的巨大挑战。人工智能(artificial intelligence,AI)擅长处理大批量、高维度的信息,用算法解析数据,既可以自动提取定量特征,也可以自动学习现有数据,从而对新数据进行预测。AI在影像处理领域得到快速发展,在肺结节检出、肺癌诊断等方面显示出较大的优势和应用前景。将AI与临床工作相结合有助于精准医疗的实施。本文对近年来AI在肺部肿瘤影像诊断领域的研究现状和进展予以概述。     

光学功能成像技术在乳腺癌早期诊断中的应用

乳腺癌的发病率逐年上升,已经成为危害女性健康的第一大疾病,因而乳腺癌的早期发现和诊断对及时治疗和保证生活质量具有关键的意义。光学功能成像技术是乳腺肿瘤常用的检查手段之一,对肿瘤的良恶性能做出较准确的诊断。在过去的几十年中,光纤、光源、探测器、影像及计算机控制仪器的发展,对光学定量技术在临床诊断和治疗中的应用起到了史无前例的促进作用。在乳腺疾病的检测、诊断和监测上,     

《中国肿瘤临床》文章推荐:人工智能在肺部肿瘤影像诊断中的研究进展

肺癌的早期发现、精确诊断对于患者的预后至关重要。影像学能够无创、全面地反映肿瘤的异质性,在肺癌诊断中发挥重要作用。海量影像数据的深入挖掘是影像医师面临的巨大挑战。人工智能(artificial intelli gence,AI)擅长处理大批量、高维度的信息,用算法解析数据,既可以自动提取定量特征,也可以自动学习现有数据,从而对新数据进行预测。AI在影像处理领域得到快速发展,在肺结节检出、肺癌诊断等方面显示出较大的优势和应用前景。将AI与临床工作相结合有助于精准医疗的实施。为此,2020年第2期《中国肿瘤临床》专家论坛栏目刊发了天津医科大学肿瘤医院放射治疗科主任叶兆祥教授撰写的《人工智能在肺部肿瘤影像诊断中的研究进展》一文,该文对近年来AI在肺部肿瘤影像诊断领域的研究现状和进展予以概述,以飨读者。     

国内首台乳腺癌早期临床检测设备研制成功

<正>据中国科学报6月30日消息报道,由中国科学院自动化研究所成功研制的国内首台乳腺癌早期临床检测设备——光学分子影像手术导航系统在中国人民解放军总医院等多家医院开展临床应用,目前已成功诊治百余例乳腺癌患者,实现了光学分子影像技术在临床应用的重大突破。该方法突破现有解剖结构影像的局限,独创性地将分子影像方法应用于临床手术中,对于乳腺癌及其他肿瘤的早期诊断、     

乳腺影像诊断：现状与进展

随着乳腺癌的逐年高发,乳腺影像技术和诊断观念也发生了很大的变化,无论是影像诊断的规范化,还是各种影像技术在乳腺癌早期诊断、局部进展期乳腺癌治疗的评估、保留乳房手术病例术前筛选、术后随访方面都有了很大的发展。同时一些常规的影像技术也因为新技术的研发应用而克服了以往的局限。可以说现代乳腺癌治疗模式的改变得益于乳腺影像技术的发展、诊断的规范化和影像评估的日益准确,同时也反过来促进了影像技术和诊断的发展。     

早期乳腺癌的影像学筛查现状与进展

乳腺癌是女性最常见、最多发的恶性肿瘤,严重威胁着女性的身心健康和生活质量。当前,随着各种影像技术的发展,超声检查和乳腺X线摄影已成为早期乳腺癌的基本筛查手段,另有MRI、CT以及乳腺热层析扫描,均有效提高了乳腺癌的早期诊断率。目前,这些手段都已应用于乳腺癌的筛查、诊断、治疗和随访。因此,综合应用以上各种影像学检查方法必将成为乳腺癌早期筛查的主要发展趋势。笔者将系统分析以上各种筛查方法的应用现状与进展,为早期乳腺癌的甄辨提供合理的个体化筛查方案。     

乳腺癌外科治疗中一些争议问题的探讨

乳腺癌的外科治疗经历了经典根治术、扩大根治术、改良根治术、保乳手术和保乳手术＋前哨淋巴结活检及乳房重建的一个发展过程。由于影像诊断技术的进步如全数字钼靶X线检查及超声检查的普遍使用,以及女性对乳房健康关注度的提高,使得临床中早期乳腺癌比例逐渐增高,这促使临床医师在重视外科根治性的同时兼顾患者的生活质量。     

人工智能在鼻咽癌影像中的研究进展

人工智能（artificial intelligence,AI）与医学多学科、多专业深度融合,其中医学影像也是AI在医学领域的重要应用方向之一。目前临床对鼻咽癌（nasopharyngeal carcinoma,NPC）的诊断主要依靠影像学检查,数量庞大的影像数据和放射科医师的主观性让检查结果、疗效评估和预后的准确性有所降低。AI具有强大的运算和数据处理性能,应用于鼻咽癌影像诊断可提高影像诊断效率和准确性,尤其是医学影像与AI融合的影像组学有望为NPC患者提供更加精准的医疗服务。本文就AI在NPC影像中的应用予以综述。     

蛋白质组学技术在乳腺癌研究中的应用

乳腺癌是最常见的女性恶性肿瘤,尽管筛查、诊断、治疗方面有巨大的进展,但发病机制仍不清楚。蛋白质组学是一个迅速发展的领域,可以探索乳腺癌的异质性并同时从基因组中提供大量的信息。蛋白质组学为寻找与乳腺癌诊断和预后密切相关的特异性生物学标志物、探讨乳腺癌的发生机制及早期临床治疗提供了研究平台。     

Development of artificial intelligence technology in diagnosis,treatment, and prognosis of colorectal cancer

Artificial intelligence (AI) technology has made leaps and bounds since its invention. AI technology can be subdivided into many technologies such as machine learning and deep learning. The application scope and prospect of different technologies are also totally different. Currently, AI technologies play a pivotal role in the highly complex and wide-ranging medical field, such as medical image recognition, biotechnology, auxiliary diagnosis, drug research and development, and nutrition. Colorectal cancer (CRC) is a common gastrointestinal cancer that has a high mortality, posing a serious threat to human health. Many CRCs are caused by the malignant transformation of colorectal polyps. Therefore, early diagnosis and treatment are crucial to CRC prognosis. The methods of diagnosing CRC are divided into imaging diagnosis, endoscopy, and pathology diagnosis. Treatment methods are divided into endoscopic treatment, surgical treatment, and drug treatment. AI technology is in the weak era and does not have communication capabilities. Therefore, the current AI technology is mainly used for image recognition and auxiliary analysis without in-depth communication with patients. This article reviews the application of AI in the diagnosis, treatment, and prognosis of CRC and provides the prospects for the broader application of AI in CRC.     

多模态超声技术在乳腺癌新辅助化疗疗效评估中的应用

随着诊疗技术的发展，乳腺癌进入多种模式相结合的综合治疗时代，新辅助化疗因具有使乳腺癌降期、提高保乳率等优势，应用日渐广泛。早期准确评估疗效对乳腺癌个体化治疗和预后至关重要。目前常见的超声诊断方式包括常规超声、彩色多普勒超声、超声造影、超声弹性成像、自动乳腺全容积成像等技术，因安全无创、操作简单及重复性强等众多优势，被广泛用于乳腺癌治疗前后的疗效评估。本文主要针对多模态超声成像技术在乳腺癌新辅助化疗疗效评估中的应用进行综述。     

Brustkrebs-Früherkennung in Deutschland

The guideline Early Detection of Breast Cancer in Germany aims to assist physicians, healthy women, and patients in decision making with recommendations based on evidence and formal consensus regarding the diagnostic chain of health care for early detection of breast cancer. This guideline updates the previous version of 2003. The guideline is a precondition to establishing an effective and efficient national early breast cancer detection program in accordance with the requirements of the European Council and the World Health Organization for cancer control programs. The core imaging technique of an early detection program is mammography, whether used for screening or diagnosis. Breast health care outcomes can be improved by embedding this imaging technology in a quality-assured diagnostic chain. The guideline comprises areas of present scientific and medical knowledge, based on evidence and consensus and covering all multidisciplinary aspects of the diagnostic chain, including clinical history taking, risk consultation and communication, breast health awareness, physical breast examination, breast imaging, interventional guided biopsy, excision biopsy, and breast pathology. The guideline provides formal measures as quality indicators to ensure resource availability, process quality, and outcome of the diagnostic chain. Early detection of breast cancer is presently the most promising chance for optimizing diagnosis and treatment of breast cancer in order to reduce mortality and morbidity while improving survivors’ quality of life. The aim is to detect breast cancer as a noninvasive disease or an invasive disease at an early stage, with a 5-year survival rate of more than 90% with adequate treatment. Detecting more noninvasive breast cancer might even help reduce the incidence. Within the scope of secondary prevention, early detection offers the chance of cure at an early disease stage by less intensive treatment.     

副乳腺癌诊治研究

目的：探讨副乳腺癌的临床特点及诊治方法。方法：应用PubMed及CNKI期刊全文数据库检索系统,以“副乳腺、副乳腺癌、诊断、治疗”等为关键词,检索1990-2013年相关文献。纳入标准：1）副乳腺癌的临床及病理;2）副乳腺癌的诊断及鉴别;3）副乳腺癌的治疗及预后。根据纳入标准符合分析文献43篇。结果：副乳是一种男女都能够出现的先天性发育异常,女性患者多见。副乳腺癌病变部位异常,临床表现常以腋下肿块为首发症状,易被漏诊和误诊。肿瘤生长迅速,发现较晚且副乳癌区域淋巴结丰富,发生转移早,确诊时患者常处于临床晚期阶段。副乳腺癌的预后比乳腺癌差。诊断时需要与腋窝淋巴结转移性乳腺癌、淋巴结肿大和汗腺癌等疾病鉴别。副乳腺癌在病理及影像学表现方面有其独特性,能够为诊治提供帮助。结论：副乳腺癌临床较为少见,预后较差。诊断主要依据影像学资料和术后病理。治疗应遵循以手术为主的综合治疗,手术方法推荐副乳腺区扩大切除加腋窝淋巴清除。争取早期诊断是改善预后的关键。     

Body mass and stage of breast cancer at diagnosis

Obesity is a well-known risk factor for postmenopausal breast cancer. In contrast, the relationship between obesity and stage of breast cancer at diagnosis is less clear. We hypothesized that increased breast size in obese women may delay discovery of breast tumors. Thus, the purpose of our study was to examine whether there is an association between body mass and stage of breast cancer at diagnosis using hospital medical records. Newly diagnosed breast cancer cases (n = 966) in the Baltimore metropolitan area from 1991 to 1997 were included in our study. Patient information including age, ethnicity, weight, height and pathology data were obtained from hospital medical records. High body mass was significantly associated with late stage of breast cancer at diagnosis. Women who were obese (body mass index [BMI] > or = 27.3) were more likely to be at an advanced stage at diagnosis compared with women with a BMI of < 27.3 (multivariate-adjusted odds ratio [OR] 1.57, 95% confidence interval [CI] 1.15-2.14). The association between body mass and stage at diagnosis was stronger among women younger than 50 years (OR 2.34, 95% CI 1.34-4.08) compared with women 50 years or older (OR 1.30, 95% CI 0.89-1.91). Our study suggests that higher body mass is associated with advanced stage of breast cancer at diagnosis. This finding may be of considerable concern, given the increasing prevalence of obesity in women in the United States and the poor prognosis associated with late-stage tumors.     

人工智能在鼻咽癌诊断与预后领域的研究进展

人工智能（artificial intelligence,AI）的应用可以帮助解决鼻咽癌（nasopharyngeal carcinoma,NPC）诊断中的诸多问题,包括影像学诊断、病理学诊断、内镜筛查等,并可以通过AI对鼻咽癌患者达到预测预后的目的。就目前而言,虽然AI在鼻咽癌领域的应用越来越多,但是AI在实际应用方面仍面临较多挑战。相信随着AI在鼻咽癌领域的应用增加与不断改进的算法,未来AI能作为常用的工具应用于临床。     

In vivo single molecular imaging and sentinel node navigation by nanotechnology for molecular targeting drug-delivery systems and tailor-made medicine

The recent advances in nanotechnology have a great potential to improve the prevention, diagnosis, and treatment of human diseases. Nanomaterials for medical applications are expected to grasp pharmacokinetics and the toxicity for application to medical treatment on the aspect of safety of the nanomaterials and nanodevices. We describe a generation of CdSe nanoparticles [quantum dots (QDs)] conjugated with monoclonal anti-HER2 antibody (Trastuzumab), for single molecular in vivo imaging of breast cancer cells. We established a high-resolution in vivo 3D microscopic system for a novel imaging method at the molecular level. The cancer cells expressing HER2 protein were visualized by the nanoparticles in vivo at subcellular resolution, suggesting future utilization of the system in medical applications to improve drug-delivery systems to target the primary and metastatic tumors for made-to-order treatment. We also describe sentinel node navigation using fluorescent nanoparticles for breast cancer surgery in experimental model, which have shown the potential to be an alternative to existing tracers in the detection of the sentinel node if we select the appropriate particle size and wavelength. Future innovation in cancer imaging by nanotechnology and novel measurement technology will provide great improvement, not only in the clinical field but also in basic medical science for the development of medicine. This article is based on a presentation delivered at the Presidential Symposium 1, “Breast cancer: individualized diagnosis for tailored treatment,” held on 29 June 2007 at the 15th Annual Meeting of the Japanese Breast Cancer Society in Yokohama.     

肿瘤的过诊断和过治疗

长期以来,为减少肿瘤的死亡率一直强调“早期诊断和早期治疗”。但迄今病理学并不能够回答多早期的“癌”性病变一定会不可逆的向前发展,恶性生长、转移,直至夺人性命。很多看似“癌”性的病变可长期稳定,甚至消退,在患者因其它原因死亡前不因“癌”而就诊。医学影像技术的进步和医疗福利的提高,很多人群经常进行体检和肿瘤的筛查,从而查出很多早期癌患。本文以乳腺癌、肺癌、前列腺癌和甲状腺癌为例,就这种筛查导致的多诊断出的“癌”和由其导致的不必要的治疗,做一简要回顾分析。     

Breast cancer and screening in American Indian and Alaska Native women

Data relative to breast cancer among American Indian and Alaska native (AI/AN) women are limited and vary by regions. Despite national decreases in breast cancer incidence and mortality rates, declines in these measures have not yet appeared among AI/AN women. Health disparities in breast cancer persist, manifest by higher stage at diagnosis, and lower screening rates compared to other racial and ethnic groups. Disproportionately more AI/AN are younger at diagnosis. Screening beginning at age 40, improving access, annual rescreening, community education and outreach, and mobile mammography for rural areas are ways to improve these disparities in breast cancer.     

Breast Cancer and Screening in American Indian and Alaska Native Women

Data relative to breast cancer among American Indian and Alaska native (AI/AN) women are limited and vary by regions. Despite national decreases in breast cancer incidence and mortality rates, declines in these measures have not yet appeared among AI/AN women. Health disparities in breast cancer persist, manifest by higher stage at diagnosis, and lower screening rates compared to other racial and ethnic groups. Disproportionately more AI/AN are younger at diagnosis. Screening beginning at age 40, improving access, annual rescreening, community education and outreach, and mobile mammography for rural areas are ways to improve these disparities in breast cancer.