影像组学技术研究进展及其在结直肠癌中的临床应用

医学影像包含着大量人眼无法识别的信息,不仅可以全面表达肿瘤的异质性,还可能反映患者预后等重要信息。近年来,随着图像处理与人工智能技术的发展,应用基于医学影像大数据的分析方法来辅助医生决策或者解决临床实践中的棘手问题成为研究热点,这个新兴的领域被称为“影像组学”。另外,结直肠癌是中国主要发病及致死癌种之一,发病人数和致死人数均逐年上升,在其术前、术中和术后3个不同阶段均有许多热点研究问题。从影像组学的基本原理与技术入手,结合其在结直肠癌临床诊疗中的应用研究,针对术前新辅助放化疗的疗效评估、术中手术方案的决策和术后生存分析这3个不同阶段的不同问题,分别介绍影像学组如何发挥其价值。     

Policy Interoperability in Stem Cell Research: Demystifying Harmonization

Scientific developments in the field of stem cell research continue to emerge at incredible speed and so too has the contentious debate surrounding their broad implications. Though economic, socio-ethical and legal concerns remain, at both national and international forums; we are witnessing a departure from an “embryo-centric” approach, to one that is focused on the globalization of research and to the ensuing need for policy interoperability. The common response to the challenges associated with the meaning, scope, and ethical significance of variance in national policies, is a call for the creation of uniform legal and ethical standards. However, this call towards policy convergence on the fundamental ethical and governance principles underpinning policies choices has led to confusion and to the mystification of the notion of harmonization. In this article we aim demystify the notion of policy harmonization in the context of stem cell research. We will do so by surveying the diverse elements to be harmonized. We will then present the problems of policy interoperability in the context of the globalization of SC research, in order to propose that the goal of harmonization in this field lies in the identification of prospective strategies to foster seamless cross-jurisdictional collaboration. Finally, policy interoperability will be analyzed through the lens of a range of policy approaches addressing the cross-jurisdictional transfer of hESC lines with the aim of demonstrating that the apparent ethical-political-legal divide in some contexts largely vanishes once we grasp the notion of harmonization and identify points of convergence.

Radiologist Use of and Perceived Need for Patient Data Access

Given the increasing volume of radiological exams, the decreasing frequency of direct communication with the referring provider, and the distribution of patient data over many clinical systems, radiologists often do not have adequate clinical information at the time of interpretation. We have performed a survey of radiologists to determine the need and actual utilization of patient data at the time of image interpretation. Our findings demonstrate that most radiologists want more clinical information when interpreting images and that this information would impact their report, but they are discouraged by the time it takes to access this information. In addition, current mechanisms for monitoring necessary patient follow-up are inadequate.     

医疗数据整合模式的研究

HL7是涉及到许多不同领域的医疗数据交换标准。通过对该标准的分析,本研究从最底层的结构入手,提出一种进行HL7完整构造的通用方法,并通过软件算法完全实现了此方法。本方法将XML对象树与数据表结合;它不同于其它文献所提的只针对HL7某一特定点或层次的方法,它不仅包含HL7的横向全部消息也深入了HL7的纵向所有层次。另外在此基础上,还提出了一个包含HL7适配器和HL7网关的,适合于不同医疗系统的信息整合模型。     

Design and Development of a Medical Image Databank for Assisting Studies in Radiomics

Journal of Digital Imaging - CompreHensive Digital ArchiVe of Cancer Imaging - Radiation Oncology (CHAVI-RO) is a multi-tier WEB-based medical image databank. It supports archiving de-identified...     

A Marginal Likelihood Model for Family-Based Data

This paper presents a marginal likelihood model for family‐based data based upon the transmission of marker alleles from each heterozygous parent to his/her affected children. The proposed model, extending the maximum‐likelihood‐binomial (MLB) method and the disequilibrium maximum‐likelihood‐binomial (DMLB) method ( Abel et al. 1998 ; Abel & Müller‐Myhsok, 1998 ; Huang & Jiang, 1999 ), is adaptive to linkage disequilibrium (LD) and linkage heterogeneity. Compared with other procedures, the likelihood ratio test (LRT) derived from the proposed model enjoys superior qualities. First, simulations indicate that the power of the LRT is greater than that of the TDT or DMLB in all of our studied scenarios. Second, when we applied the LRT and other tests to a Tourette Syndrome data, the result was data favorable to the use of the LRT. Therefore, we recommend the use of the LRT as an additional linkage test wherever applicable, especially when the amount of LD is uncertain.     

PhenoTips: Patient Phenotyping Software for Clinical and Research Use

We have developed PhenoTips: open source software for collecting and analyzing phenotypic information for patients with genetic disorders. Our software combines an easy‐to‐use interface, compatible with any device that runs a Web browser, with a standardized database back end. The PhenoTips’ user interface closely mirrors clinician workflows so as to facilitate the recording of observations made during the patient encounter. Collected data include demographics, medical history, family history, physical and laboratory measurements, physical findings, and additional notes. Phenotypic information is represented using the Human Phenotype Ontology; however, the complexity of the ontology is hidden behind a user interface, which combines simple selection of common phenotypes with error‐tolerant, predictive search of the entire ontology. PhenoTips supports accurate diagnosis by analyzing the entered data, then suggesting additional clinical investigations and providing Online Mendelian Inheritance in Man (OMIM) links to likely disorders. By collecting, classifying, and analyzing phenotypic information during the patient encounter, PhenoTips allows for streamlining of clinic workflow, efficient data entry, improved diagnosis, standardization of collected patient phenotypes, and sharing of anonymized patient phenotype data for the study of rare disorders. Our source code and a demo version of PhenoTips are available at http://phenotips.org .     

Development and Validation of CT-Based Radiomics Signature for Overall Survival Prediction in Multi-organ Cancer

Journal of Digital Imaging - The malignant tumors in nature share some common morphological characteristics. Radiomics is not only images but also data; we think that a probability exists in a set...     

精神分裂症患者暴力行为临床特征研究

目的 探讨精神分裂症患者的暴力行为特点及相关影响因素,为制定干预措施提供依据.方法 对176例具有暴力行为的精神分裂症患者的相关文化背景、职业、、精神症状等进行回顾性研究.并提出干预对策.结果 男性暴力行为发生率高于女性(3:1);工人农民居多,占68.75%.初中以下文化程度占76.15%.结论 暴力行为多发生于男性,且与患者的文化背景、职业等特征有关,早期预测和干预有重要意义.     

The Impact of Internet Health Information on Patient Compliance: A Research Model and an Empirical Study

Background

Patients have been increasingly seeking and using Internet health information to become more active in managing their own health in a partnership with their physicians. This trend has both positive and negative effects on the interactions between patients and their physicians. Therefore, it is important to understand the impact that the increasing use of Internet health information has on the patient-physician relationship and patients’ compliance with their treatment regimens.

Objective

This study examines the impact of patients’ use of Internet health information on various elements that characterize the interactions between a patient and her/his physician through a theoretical model based on principal-agent theory and the information asymmetry perspective.

Methods

A survey-based study consisting of 225 participants was used to validate a model through various statistical techniques. A full assessment of the measurement model and structural model was completed in addition to relevant post hoc analyses.

Results

This research revealed that both patient-physician concordance and perceived information asymmetry have significant effects on patient compliance, with patient-physician concordance exhibiting a considerably stronger relationship. Additionally, both physician quality and Internet health information quality have significant effects on patient-physician concordance, with physician quality exhibiting a much stronger relationship. Finally, only physician quality was found to have a significant impact on perceived information asymmetry, whereas Internet health information quality had no impact on perceived information asymmetry.

Conclusions

Overall, this study found that physicians can relax regarding their fears concerning patient use of Internet health information because physician quality has the greatest impact on patients and their physician coming to an agreement on their medical situation and recommended treatment regimen as well as patient’s compliance with their physician’s advice when compared to the impact that Internet health information quality has on these same variables. The findings also indicate that agreement between the patient and physician on the medical situation and treatment is much more important to compliance than the perceived information gap between the patient and physician (ie, the physician having a higher level of information in comparison to the patient). In addition, the level of agreement between a patient and their physician regarding the medical situation is more reliant on the perceived quality of their physician than on the perceived quality of Internet health information used. This research found that only the perceived quality of the physician has a significant relationship with the perceived information gap between the patient and their physician and the quality of the Internet health information has no relationship with this perceived information gap.     

Challenges for Data Storage in Medical Imaging Research

Researchers in medical imaging have multiple challenges for storing, indexing, maintaining viability, and sharing their data. Addressing all these concerns requires a constellation of tools, but not all of them need to be local to the site. In particular, the data storage challenges faced by researchers can begin to require professional information technology skills. With limited human resources and funds, the medical imaging researcher may be better served with an outsourcing strategy for some management aspects. This paper outlines an approach to manage the main objectives faced by medical imaging scientists whose work includes processing and data mining on non-standard file formats, and relating those files to the their DICOM standard descendents. The capacity of the approach scales as the researcher’s need grows by leveraging the on-demand provisioning ability of cloud computing.     

以病人为中心的多媒体电子病案的开发和研究

HIS（hospital information system)在中国得到了蓬勃的发展,但目前大多数系统只局限于物流管理层次,尚未进一步向临床医疗信息的管理层次转变,我们使用面向对象方法设计和实现了一个以“病人为中心”的多媒体电子病案,该系统由三个子系统构成,包括数据采集、多媒体数据库、数据处理与输出系统,通过对病人的各种医疗信息（影像、声音、生理信号）进行采集、保存、查询和分析。满足医院无纸病案的要求,实现医疗信息的资源共享。     

Radiomics analysis of amide proton transfer-weighted and structural MR images for treatment response assessment in malignant gliomas

The purpose of this study was to evaluate the value of amide proton transfer-weighted (APTw) MRI radiomic features for the differentiation of tumor recurrence from treatment effect in malignant gliomas. Eighty-six patients who had suspected tumor recurrence after completion of chemoradiation or radiotherapy, and who had APTw-MRI data acquired at 3 T, were retrospectively analyzed. Using a fluid-attenuated inversion recovery (FLAIR) image-based mask, radiomics analysis was applied to the processed APTw and structural MR images. A chi-square automatic interaction detector decision tree was used for classification analysis. Models with and without APTw features were built using the same strategy. Tenfold cross-validation was applied to obtain the overall classification performance of each model. Sixty patients were confirmed as having tumor recurrence, and the remainder were confirmed as having treatment effect, at median time points of 190 and 171 days after therapy, respectively. There were 525 radiomic features extracted from each of the processed APTw and structural MR images. Based on these, the APTw-based model yielded the highest accuracy (86.0%) for the differentiation of tumor recurrence from treatment effect, compared with 74.4%, 76.7%, 83.7%, and 76.7% for T₁w, T₂w, FLAIR, and Gd-T₁w, respectively. Model classification accuracy was 82.6% when using the combined structural MR images (T₁w, T₂w, FLAIR, Gd-T₁w), and increased to 89.5% when using these structural plus APTw images. The corresponding sensitivity and specificity were 85.0% and 76.9% for the combination of structural MR images, and 85.0% and 100% after adding APTw image features. Adding APTw-based radiomic features increased MRI accuracy in the assessment of the treatment response in post-treatment malignant gliomas.     

结直肠癌肝转移预测及预后的影像组学综述

结直肠癌在国内外都是高发病率和高死亡率的肿瘤疾病,肝脏是结直肠癌血行转移最主要的靶器官,尽早准确地预测结直肠癌肝转移的发生以及监测患者治疗的预后反应,对患者的诊断和治疗尤为关键。新兴的影像组学为精准预测结直肠癌肝转移以及评估预后提供新的可能。对现有的结直肠癌肝转移影像组学研究进行综述,首先介绍结直肠癌肝转移研究的临床意义以及现有研究存在的缺陷,然后阐述结直肠癌肝转移影像组学的分析流程,接着对结直肠癌肝转移影像组学的4个研究方向展开综述,包括肝转移病理生长模式预测、隐匿性肝转移预测、肝转移疗效预后评估、肝转移患者生存期预后评估;阐明各个方向的最新研究进展及存在的缺陷性;最后对结直肠癌肝转移影像组学的未来发展趋势进行展望。     

Radiomics Signature: A potential biomarker for the prediction of survival in Advanced Hepatocellular Carcinoma

Objectives: To develop and validate radiomics nomograms for the pretreatment predictions of overall survival (OS) and time to progression (TTP) in the patients with advanced hepatocellular carcinoma (HCC) treated with apatinib plus transarterial chemoembolization (TACE), and to assess the incremental value of the clinical-radiomics nomograms for estimating individual OS and TTP.Methods: A total of 60 patients with advanced HCC (BCLC stage C) treated with apatinib plus TACE were divided into a training set (n=48) and a validation set (n=12). The predictors identified from the clinical variables and the radiomics signature constructed from the computed tomography images, such as ɑ-fetoprotein level (AFP), formfactor, the grey level co-occurrence matrix, the gray level size zone matrix, and the gray level run-length matrix, were used to build the clinical-radiomics nomograms and the radiomics nomograms for the prediction of OS and TTP.Results: Apatinib plus TACE benefited the patients with advanced HCC, with a 579-day median OS and a 270-day median TTP. The nomograms were built with the radiomics signature and AFP, and achieved favorable prediction efficacy with acceptable calibration curves. Decision curve analyses demonstrated that the clinical-radiomics nomograms outperformed the radiomics nomograms for the predictions of OS and TTP.Conclusions: Apatinib plus TACE may improve OS and prolonged TTP in the patients with advanced HCC. The clinical-radiomics nomograms, a noninvasive pretreatment prediction tool that incorporate radiomics signature and AFP, demonstrated good prediction accuracy for OS and TTP in these patients. These results indicate that the clinical-radiomics nomograms may provide novel insight for precise personalized medicine approaches in the patients with advanced HCC.     

Multiclassifier Radiomics Analysis of Ultrasound for Prediction of Extrathyroidal Extension in Papillary Thyroid Carcinoma in Children

Objective: To explore extrathyroidal extension (ETE) in children and adolescents with papillary thyroid carcinoma using a multiclassifier ultrasound radiomic model.Methods: In this study, data from 164 pediatric patients with papillary thyroid cancer (PTC) were retrospectively analyzed and patients were randomly divided into a training cohort (115) and a validation cohort (49) in a 7:3 ratio. To extract radiomics features from ultrasound images of the thyroid, areas of interest (ROIs) were delineated layer by layer along the edge of the tumor contour. The feature dimension was then reduced using the correlation coefficient screening method, and 16 features with a nonzero coefficient were chosen using Lasso. Then, in the training cohort, four supervised machine learning radiomics models (k-nearest neighbor, random forest, support vector machine [SVM], and LightGBM) were developed. ROC and decision-making curves were utilized to compare model performance, which was validated using validation cohorts. In addition, the SHapley Additive exPlanations (SHAP) framework was applied to explain the optimal model.Results: In the training cohort, the average area under the curve (AUC) was 0.880 (0.835-0.927), 0.873 (0.829-0.916), 0.999 (0.999-1.000), and 0.926 (0.892-0.926) for the SVM, KNN, random forest, and LightGBM, respectively. In the validation cohort, the AUC for the SVM was 0.784 (0.680-0.889), for the KNN, it was 0.720 (0.615-0.825), for the random forest, it was 0.728 (0.622-0.834), and for the LightGBM, it was 0.832 (0.742-0.921). Generally, the LightGBM model performed well in both the training and validation cohorts. From the SHAP results, original_shape_MinorAxisLength,original_shape_Maximum2DDiameterColumn, and wavelet-HHH_glszm_SmallAreaLowGrayLevelEmphasis have the most significant effect on the model.Conclusions: Our combined model based on machine learning and ultrasonic radiomics demonstrate the excellent predictive ability for extrathyroidal extension (ETE) in pediatric PTC.     

Pseudonymization of Radiology Data for Research Purposes

Medical image processing methods and algorithms, developed by researchers, need to be validated and tested. Test data would ideally be real clinical data especially that clinical data is varied and exists in large volumes. Nowadays, clinical data is accessible electronically and has important value for researchers. However, the usage of clinical data for research purposes should respect data confidentiality, patient right to privacy, and patient consent. In fact, clinical data is nominative given that it contains information about the patient such as name, age, and identification number. Evidently, clinical data needs to be de-identified to be exported to research databases. However, the same patient is usually followed during a long period of time. The disease progression and the diagnostic evolution represent extremely valuable information for researchers as well. Our objective is to build a research database from de-identified clinical data while enabling the data set to be easily incremented by exporting new pseudonymous data, acquired over a long period of time. Pseudonymization is data de-identification, such that data belonging to an individual in the clinical environment still belong to the same individual in the de-identified research version. In this paper, we explore various software architectures to enable the implementation of an imaging research database that can be incremented in time. We also evaluate their security and discuss their security pitfalls. As most imaging data accessible electronically is available with the digital imaging and communication in medicine (DICOM) standard, we propose a de-identification scheme that closely follows DICOM recommendations. Our work can be used to enable electronic health record (EHR) secondary usage such as public surveillance and research, while maintaining patient confidentiality.     

基于双目视觉的医疗器械3D数据模型获取方法研究

目的：为了高效率、低创伤地完成外科手术．计算机辅助外科手术得到了广泛应用。医疗器械3D数据模型可有效地结合病人的影像数据,指导外科医生完成顺利外科手术,从而降低手术的风险,减少对病人的伤害。方法：基于双目视觉基本原理,首先对双目摄像机进行立体标定,利用标定后获得的摄像机参数对双目立体图像进行畸变矫正和立体校正,然后为了提高后续匹配精度,对医疗器械目标进行分割后再进行立体匹配,最后将获取的匹配视差信息重投影到3D空间。获得医疗机械的3D数据。结果：采用交互式分割方法对医疗器械目标进行先分割再立体匹配,能避免遮挡造成的误匹配。大大提高匹配精度。通过实验,将基于双目视觉获取的医疗器械3D数据与实际测量获得的数据进行比较后发现,本文方法获取的医疗器械3D数据精确度较高。结论：基于双目视觉理论可以高效率、高精度地进行医疗器械3D模型还原．其模型可用于模拟手术、手术导航等实际应用。