机器学习在鼻咽癌影像分析中的研究进展

鼻咽癌的诊疗高度依赖临床医生对临床影像数据的分析处理,但人工分析处理影像主观、耗时。而机器学习用于鼻咽癌影像分析能够较好地实现肿瘤病灶自动或半自动分割、分类,有利于提高临床医生的诊疗效率和准确度。就机器学习在鼻咽癌的MRI、CT、鼻内镜影像分割中的应用及其在影像分类中的研究进展予以综述。     

电子计算机在肿瘤放疗中的应用

一、简况:随着高能电子直线和电子感应加迅器的普遍使用,以及临床肿瘤学、肿瘤的放射生物学、临床放射剂量学和照射技术的进展,使得放射治疗在治疗的质和量的方面均有很大的提高。特别是电子计算机在放射治疗中的应用,标志着放射治疗技术的现代化。     

加强机器学习在医学影像中的研究和应用

在临床工作中,医学影像为临床决策提供重要的辅助信息。但传统的影像诊断主要基于放射科医生的主观判断,已不能满足精准医学发展的要求。近年来,以深度学习为代表技术的机器学习方法,为拓展医学影像的临床应用范围提供了巨大的机遇。对机器学习在医学影像中的研究和应用、基本概念、研究现状作简要介绍,以期推动相关研究的开展。     

2016年度福建省放射治疗应用基本情况调查分析

目的 掌握2016年度福建省放射治疗应用基本情况。方法 采用统一设计的调查表,通过普查的方法搜集全省放射治疗单位的放射治疗及其配套设备的种类与数量、放射治疗工作人员数以及放射治疗质量控制工作开展情况,统计26家医院的放射治疗患者和门诊量等数据。通过相关性和多重线性回归分析建立模型来估算全省的放射治疗患者总数。结果 2016年福建省有32家放射治疗单位,放射治疗设备62台（套）,模拟定位机33台,放射治疗计划系统（TPS）57套,放射治疗工作人员762名,可搜集到的26家医院的放射治疗患者共计15 156人。根据多元线性回归模型得到医用电子加速器的应用频度与门急诊和住院量,放射治疗工作人员数,加速器设备数呈正相关（r=0.311、0.893、0.956,P<0.05）;后装治疗的应用频度与门急诊和住院量、放射治疗工作人员数、后装设备数呈正相关（r=0.307、0.966、0.988,P<0.05）。通过估算得到福建省2016年度放射治疗应用频度为0.54例/千人口。经调查各单位基本都能按照规定开展加速器输出剂量校准,但晨检仪、井型电离室等放射治疗质控设备的配置明显不足。结论 近几年福建省的放射治疗发展较快,规范、加强应用过程中的质量控制和监督应当作为将来放射治疗管理的关注重点。     

MRI扩散加权成像在鼻咽癌调强放疗疗效评价中的应用价值

目的 探讨磁共振扩散加权成像(diffusion weighted imaging,DWI)在鼻咽癌调强放射治疗中的临床应用价值.方法 回顾性分析经病理检查证实的60例初诊鼻咽癌患者,均行调强放射治疗,放射治疗前1周内和放射治疗50Gy时均行MRI及DWI检查,比较放疗前后MRI及DWI-MRI情况.结果 56例放疗后肿瘤病灶缩小,3例变化不明显,1例增大,与放疗前比较差异具有统计学意义(P＜0.05).放疗后弥散加权成像信号减低,表观弥散系数(apparent diffusion coefficient,ADC)值增大,与放疗前比较差异具有统计学意义(P＜0.05).52例颈部转移性淋巴结缩小.结论 MRI扩散加权成像可快速,灵敏显示鼻咽癌放疗前后的变化,对IMRT的疗效评价具有很好的临床应用价值.     

通过有规则的布置子野解决全中枢放疗射野衔接和剂量冷热点

目的 掌握2016年度福建省放射治疗应用基本情况。方法 采用统一设计的调查表，通过普查的方法搜集全省放射治疗单位的放射治疗及其配套设备的种类与数量、放射治疗工作人员数以及放射治疗质量控制工作开展情况，统计26家医院的放射治疗患者和门诊量等数据；通过相关性和多重线性回归分析建立模型来估算全省的放射治疗患者总数。结果 2016年福建省有32家放射治疗单位，放射治疗设备62台套，模拟定位机33台，放射治疗计划系统（TPS）57套，放射治疗工作人员762名，可搜集到的26家医院的放射治疗患者共计15156人。根据多元线性回归模型得到医用电子加速器的应用频度与门急诊和住院量，放射治疗工作人员数，加速器设备数呈正相关（r=0.311、0.893、0.956，P<0.05）；后装治疗的应用频度与门急诊和住院量、放射治疗工作人员数、后装设备数呈正相关（r=0.307、0.966、0.988，P<0.05）。通过估算得到福建省2016年度放射治疗应用频度为0.54例/千人口。经调查各单位基本都能按照规定开展加速器输出剂量校准，但晨检仪、井型电离室等放射治疗质控设备的配置明显不足。结论 近几年我省的放射治疗发展较快，规范、加强应用过程中的质量控制和监督应当作为将来我省放射治疗管理的关注重点。     

放射外科在MD安德森肿瘤中心的实践及进展

非小细胞肺癌（NSCLC）是我国最常见的恶性肿瘤之一。立体放射外科（SABR）,也称立体定向放疗（SBRT）,是一种无创性治疗,在现代精确的影像引导技术下给予局部肿瘤以高剂量、低分割的放射治疗,可获得超过90%的肿瘤局部控制率,已成为不可切除早期NSCLC的标准治疗,也是可手术早期NSCLC的治疗选择之一。美国德州大学MD安德森肿瘤中心（MDACC）作为全美肿瘤治疗排名第一的机构,对NSCLC的放射治疗进行了一系列颇具影响力的SABR临床试验和研究,促进了SABR在早期和晚期NSCLC中的应用。本文将MDACC对SABR的临床应用、研究结果和进展做一总结。     

影像组学在心脏CT成像中的研究进展

心脏CT成像已被广泛用于冠状动脉及心脏结构性疾病的诊断。传统心脏CT影像主要依靠医生通过视觉进行评估。影像组学可以从医学影像中挖掘大量人眼看不见的定量特征,并与机器学习等数据分析方法相结合,构建模型预测疾病状态以及病人的临床结局。就影像组学方法在心脏CT成像领域（包括冠状动脉斑块、冠状动脉周围脂肪、心肌组织及心脏占位）的应用现状予以综述,并探讨面临的挑战及发展方向。     

89Sr及联合治疗转移性骨肿瘤的临床应用

放射性核素治疗在临床上主要以一种单一的方法在使用,很少作为治疗规范有效地与化学治疗、免疫治疗或者放射治疗联合应用。转移性骨肿瘤的疼痛缓解是近来放射性核素治疗的重要领域,89Sr是常用的治疗这种疾病的放射性核素,它与阿霉素、吉西他滨和顺铂等化疗药物或者放射治疗联合应用后可以增强放射性核素的治疗作用,延长疼痛缓解的时间。这种联合治疗的方法也被用来治疗淋巴瘤、神经母细胞瘤和脑胶质瘤等其他恶性肿瘤,显示出良好的应用前景。     

宫颈癌基因治疗联合放射治疗的研究进展

目前宫颈癌基因治疗尚存在许多问题,距临床应用还有相当的距离,但是在传统的放疗、化疗和手术治疗的基础上,放射治疗与基因治疗的有机结合在宫颈癌治疗中却显示出可喜的前景。本文探讨了宫颈癌基因治疗联合放射治疗的应用前景。     

Current Status and New Developments in Ion Therapy

BACKGROUND: Worldwide, encouraging clinical results of ion radiotherapy led to planning and construction of several new treatment facilities. MATERIAL AND METHODS: The main technical and biological aspects of ion therapy are reviewed. The current status and future developments are discussed. RESULTS: The use of ions in radiotherapy results in highly conformal dose distributions. The degree of conformality is higher for active than for passive beam delivery techniques. Applying ion therapy, uncertainties in the range and the biologically effective dose have to be considered. For heavy ions, the clinical value of the increased biological efficiency has to be investigated. CONCLUSION: Although the principal methods for clinical application of ion therapy are available, the development must be continued to explore its full potential.     

Using Artificial Intelligence to Improve the Quality and Safety of Radiation Therapy

Within artificial intelligence, machine learning (ML) efforts in radiation oncology have augmented the transition from generalized to personalized treatment delivery. Although their impact on quality and safety of radiation therapy has been limited, they are increasingly being used throughout radiation therapy workflows. Various data-driven approaches have been used for outcome prediction, CT simulation, clinical decision support, knowledge-based planning, adaptive radiation therapy, plan validation, machine quality assurance, and process quality assurance; however, there are many challenges that need to be addressed with the creation and usage of ML algorithms as well as the interpretation and dissemination of findings. In this review, the authors present current applications of ML in radiation oncology quality and safety initiatives, discuss challenges faced by the radiation oncology community, and suggest future directions.     

Erfassung m?glicher Verbesserungen im Ablauf der Strahlentherapie �� eine Patientenbefragung

Introduction and Background

In the context of quality assurance, increasing demands are placed on the whole radiotherapy treatment process. The patients directly concerned generally do not realize most aspects of the quality assurance program (e.g., additional safety checks) during their daily therapy. It was the aim of this study to systematically ask patients about potential improvements during the course of radiotherapy treatment from their own perspective.

Patients and Methods

In the defined time span (1 month), 624 radiotherapy patients (600 questionnaires were returned, 96.2%) were interviewed using a questionnaire newly developed to inquire about several aspects of their treatment. Furthermore, they were asked for their specific needs and suggestions for improvements that could be made during the course of radiotherapy treatment.

Results

Overall, the patients were satisfied with the course of their radiotherapy treatment and with patient care. As an example, about 90% agreed with the statement: ??My first contact with the radiation oncology unit proceeded with kindness and competence so that I was given the impression that I will be well cared for in this clinic.?? Considering the organization of the course of radiotherapy, a large majority of patients attached great value to set appointments for the therapy fractions. A main point of criticism was waiting times or delays caused by servicing or machine failures. Small, low cost improvements as music in the therapy room were considered as important as expensive measures (e.g., daylight in the therapy room). The patients emphasized the importance of staff friendliness.

Conclusion

The situation of radiotherapy patients was, in general, satisfactory. Future improvements can be mainly expected from smooth organisation of both planning and treatment which can be achieved by electronic scheduling systems. Many results of the survey could be easily implemented in daily practice. In matters of organization radiation oncology with its complex procedures can be used as a model for other clinical departments.     

质子重离子治疗肿瘤的进展

对于恶性肿瘤而言,传统的治疗手段主要包括手术、化疗、常规放疗等。尽管这些治疗手段在肿瘤治疗方面发挥了重要作用,但也存在很大的不足,有的治疗效果不佳,有的存在严重的并发症。为了解决上述治疗手段在肿瘤治疗方面存在的问题,国内外研究者成功研发出新的治疗手段——质子重离子放疗。笔者对此种治疗手段的基本原理和临床应用效果进行详细的介绍,以便为肿瘤科医师和患者在治疗过程中提供更多的信息和决策支持。     

Artificial intelligence in brachytherapy: a summary of recent developments

Artificial intelligence (AI) applications, in the form of machine learning and deep learning, are being incorporated into practice in various aspects of medicine, including radiation oncology. Ample evidence from recent publications explores its utility and future use in external beam radiotherapy. However, the discussion on its role in brachytherapy is sparse. This article summarizes available current literature and discusses potential uses of AI in brachytherapy, including future directions. AI has been applied for brachytherapy procedures during almost all steps, starting from decision-making till treatment completion. AI use has led to improvement in efficiency and accuracy by reducing the human errors and saving time in certain aspects. Apart from direct use in brachytherapy, AI also contributes to contemporary advancements in radiology and associated sciences that can affect brachytherapy decisions and treatment. There is a renewal of interest in brachytherapy as a technique in recent years, contributed largely by the understanding that contemporary advances such as intensity modulated radiotherapy and stereotactic external beam radiotherapy cannot match the geometric gains and conformality of brachytherapy, and the integrated efforts of international brachytherapy societies to promote brachytherapy training and awareness. Use of AI technologies may consolidate it further by reducing human effort and time. Prospective validation over larger studies and incorporation of AI technologies for a larger patient population would help improve the efficiency and acceptance of brachytherapy. The enthusiasm favoring AI needs to be balanced against the short duration and quantum of experience with AI in limited patient subsets, need for constant learning and re-learning to train the AI algorithms, and the inevitability of humans having to take responsibility for the correctness and safety of treatments.     

Monte Carlo simulation for MLC-based intensity-modulated radiotherapy.

This article describes photon beam Monte Carlo simulation for multi leaf collimator (MLC)-based intensity-modulated radiotherapy (IMRT). We present the general aspects of the Monte Carlo method for the non-Monte Carloist with an emphasis given to patient-specific radiotherapy application. Patient-specific application of the Monte Carlo method can be used for IMRT dose verification, inverse planning, and forward planning in conventional conformal radiotherapy. Because it is difficult to measure IMRT dose distributions in heterogeneous phantoms that approximate a patient, Monte Carlo methods can be used to verify IMRT dose distributions that are calculated using conventional methods. Furthermore, using Monte Carlo as the dose calculation method for inverse planning results in better-optimized treatment plans. We describe both aspects and present our recent results to illustrate the discussion. Finally, we present current issues related to clinical implementation of Monte Carlo dose calculation. Monte Carlo is the most recent, and most accurate, method of radiotherapy dose calculation. It is currently in the process of being implemented by various treatment planning vendors and will be available for clinical use in the immediate future.     

3D打印技术在放疗中的应用与进展

随着3D打印技术的发展和成熟,其在医学领域被广泛应用,尤其在骨科、口腔颌面外科等方面取得了突破性进展。而在肿瘤的放疗领域,创新性地将3D打印技术与放疗技术相结合并应用于临床,可大大提高放疗的精确度和临床疗效,为肿瘤的精确放疗提供有力保障。     

原发性肝细胞肝癌手术联合放疗的进展

肝癌是一种严重危害人类健康的常见恶性肿瘤,手术切除是早中期肝细胞肝癌（hepatocellular carcinoma,HCC）的主要根治手段,而术后复发率高是影响其疗效的主要因素。然而,目前尚无普遍接受的可降低HCC术后较高复发率的辅助治疗方式。精准放疗技术的应用,使肿瘤局部可准确地获得更高的放疗剂量,也越来越多地应用于HCC的治疗。鉴于精准放疗在中晚期肝癌的治疗地位越来越明确,而是否能作为HCC的辅助治疗尚有争议,本文将综述放疗作为手术的辅助治疗在HCC的研究进展,以期为HCC的临床辅助治疗的应用提供参考依据。     

The challenges of precision radiotherapy technology to the traditional theory of radiobiology

With the development of modern computing technology and medical physics, radiotherapy has made great progress. The theoretical basis of radiobiology seems to lag behind the clinical application of radiotherapy, which hampers the further improvement of treatment efficacy and the optimization of treatment modality. In this paper, some emerging challenges of precision radiotherapy technology to the traditional theory of radiobiology, such as radiosensitivity, dose-response curve and survival curve, linear-quadratic model, 4Rs theory, as well as the interaction between cancer and microenvironment, radiation-induced second primary cancers (RISPC), will be discussed. The interplay between precision radiotherapy and traditional radiobiology theories will be addressed with the aim to potentially solve some of the challenging problems.     

机器学习在预测放疗疗效及并发症中的应用

近年来,机器学习发展迅速,利用机器学习对放疗后疗效及并发症进行预测,可以更加准确地评估患者病情,及早采取相应治疗措施。将放疗过程中产生的非剂量相关和剂量相关特征值经筛选后输入算法模型,可以得到相应的预测结果。目前,已有多种算法模型可以对放疗后患者生存率、肿瘤控制率及各种放疗后并发症进行预测,预测结果较为准确。但算法模型也存在各种问题,需要不断探索改进。