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Coupling radiomics analysis of CT image with diversification of tumor ecosystem: A new insight to overall survival in stage Ⅰ-Ⅲ colorectal cancer

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Chinese Journal of Cancer Research 2022年第1期34卷 40-52页

作者： Yanqi Huang Lan He Zhenhui Li Xin Chen Chu Han Ke Zhao Yuan Zhang Jinrong Qu Yun Mao changhong liang Zaiyi Liu The Second School of Clinical Medicine Southern Medical UniversityGuangzhou 510515China Department of Radiology Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhou 510080China Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhou 510080China Department of Radiology the Third Affiliated Hospital of Kunming Medical UniversityYunnan Cancer HospitalYunnan Cancer CenterKunming 650118China Department of Radiology Guangzhou First People’s HospitalSchool of MedicineSouth China University of TechnologyGuangzhou 510180China Department of Radiology the Affiliated Cancer Hospital of Zhengzhou University&Henan Cancer HospitalZhengzhou 450003China Department of Radiology the First Affiliated Hospital of Chongqing Medical UniversityChongqing 400042China

Objective: This study aimed to establish a method to predict the overall survival(OS) of patients with stage Ⅰ-Ⅲ colorectal cancer(CRC) through coupling radiomics analysis of CT images with the measurement of tumor ecosystem diversification.Methods: We retrospectively identified 161 consecutive patients with stage Ⅰ-Ⅲ CRC who had underwent radical resection as a training cohort. A total of 248 patients were recruited for temporary independent validation as external validation cohort 1, with 103 patients from an external institute as the external validation cohort 2. CT image features to describe tumor spatial heterogeneity leveraging the measurement of diversification of tumor ecosystem, were extracted to build a marker, termed the EcoRad signature. Multivariate Cox regression was used to assess the EcoRad signature, with a prediction model constructed to demonstrate its incremental value to the traditional staging system for OS prediction.Results: The EcoRad signature was significantly associated with OS in the training cohort [hazard ratio(HR)=6.670;95% confidence interval(95% CI): 3.433-12.956;P<0.001), external validation cohort 1(HR=2.866;95% CI: 1.646-4.990;P<0.001) and external validation cohort 2(HR=3.342;95% CI: 1.289-8.663;P=0.002).Incorporating the EcoRad signature into the prediction model presented a higher prediction ability(P<0.001) with respect to the C-index(0.813, 95% CI: 0.804-0.822 in the training cohort;0.758, 95% CI: 0.751-0.765 in the external validation cohort 1;and 0.746, 95% CI: 0.722-0.770 in external validation cohort 2), compared with the reference model that only incorporated tumor, node, metastasis(TNM) system, as well as a better calibration,improved reclassification and superior clinical usefulness.Conclusions: This study establishes a method to measure the spatial heterogeneity of CRC through coupling radiomics analysis with measurement of diversification of the tumor ecosystem, and suggests that this approach could effectively predict OS and could be used as a supplement for ris

关键词： Radiomics tumor ecosystem spatial heterogeneity survival prediction colorectal cancer

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基于数控工艺信息挖掘的型腔特征粗加工刀具序列优化决策方法

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计算机集成制造系统 2024年第3期30卷 1060-1071页

作者：徐昌鸿张树生梁嘉宸南京工程学院工业中心江苏南京211167 西北工业大学机电学院陕西西安710072

为有效提升数控加工过程中粗加工刀具的使用效率,提出一种基于数控工艺信息挖掘的型腔特征粗加工刀具序列优化决策方法。首先计算型腔特征的中轴变换表征数控加工的刀具轨迹,探究中轴变换与数控加工的映射机理;然后基于加工规则和中轴... 详细信息

为有效提升数控加工过程中粗加工刀具的使用效率,提出一种基于数控工艺信息挖掘的型腔特征粗加工刀具序列优化决策方法。首先计算型腔特征的中轴变换表征数控加工的刀具轨迹,探究中轴变换与数控加工的映射机理;然后基于加工规则和中轴变换参数,挖掘隐含在型腔特征中的深层次数控工艺信息;最后综合考虑材料去除量和加工连续性,建立刀具序列决策的多目标优化模型,采用混合蚁群/模拟退火算法进行优化求解。实验结果表明,该方法能够高效、自动生成型腔特征最优粗加工刀具序列,提升企业数控工艺设计智能化水平。

关键词：信息挖掘型腔特征粗加工刀具序列优化决策数控加工

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Generalized principle of least action in electromagnetism and its applications

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Chinese Science Bulletin 1998年第9期43卷 732-734页

作者： Yongjun Xie changhong liang Xidian Univ Dept Microwave Telecommun Engn Xian 710071 Peoples R China

The generalized principle of least action in electromagnetism is presented, which is effective even though in lossy and nonreciprocal media. It is pointed out that the Maxwell’s equations can be derived from this principle. At last for example of its applications, some useful variational expressions for electromagnetic fields are derived systematically from the principle.

关键词： the generalized principle of least action lossy and nonreciprocal media Maxwell’s equations variational expressions.

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Radiomics-based predictive risk score: A scoring system for preoperatively predicting risk of lymph node metastasis in patients with resectable non-small cell lung cancer

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Chinese Journal of Cancer Research 2019年第4期31卷 641-652页

作者： Lan He Yanqi Huang Lixu Yan Junhui Zheng changhong liang Zaiyi Liu Department of Radiology Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhou 510080China Department of Pathology Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhou 510080China

Objective: To develop and validate a radiomics-based predictive risk score(RPRS) for preoperative prediction of lymph node(LN) metastasis in patients with resectable non-small cell lung cancer(NSCLC).Methods: We retrospectively analyzed 717 who underwent surgical resection for primary NSCLC with systematic mediastinal lymphadenectomy from October 2007 to July 2016. By using the method of radiomics analysis, 591 computed tomography(CT)-based radiomics features were extracted, and the radiomics-based classifier was constructed. Then, using multivariable logistic regression analysis, a weighted score RPRS was derived to identify LN metastasis. Apparent prediction performance of RPRS was assessed with its calibration,discrimination, and clinical usefulness.Results: The radiomics-based classifier was constructed, which consisted of 13 selected radiomics features.Multivariate models demonstrated that radiomics-based classifier, age group, tumor diameter, tumor location, and CT-based LN status were independent predictors. When we assigned the corresponding score to each variable,patients with RPRSs of 0-3, 4-5, 6, 7-8, and 9 had distinctly very low(0%-20%), low(21%-40%), intermediate(41%-60%), high(61%-80%), and very high(81%-100%) risks of LN involvement, respectively. The developed RPRS showed good discrimination and satisfactory calibration (C-index: 0.785, 95% confidence interval(95% CI):0.780-0.790)Additionally, RPRS outperformed the clinicopathologic-based characteristics model with net reclassification index(NRI) of 0.711(95% CI: 0.555-0.867).Conclusions: The novel clinical scoring system developed as RPRS can serve as an easy-to-use tool to facilitate the preoperatively individualized prediction of LN metastasis in patients with resectable NSCLC. This stratification of patients according to their LN status may provide a basis for individualized treatment.

关键词： Lymph node radiomics risk score CT non-small cell lung cancer

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A radiomics prognostic scoring system for predicting progression-free survival in patients with stageⅣnon-small cell lung cancer treated with platinum-based chemotherapy

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Chinese Journal of Cancer Research 2021年第5期33卷 592-605页

作者： Lan He Zhenhui Li Xin Chen Yanqi Huang Lixu Yan changhong liang Zaiyi Liu Department of Radiology Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhou 510080China Department of Radiology the Third Affiliated Hospital of Kunming Medical UniversityYunnan Cancer HospitalYunnan Cancer CenterKunming 650118China Department of Radiology Guangzhou First People’s HospitalSchool of MedicineSouth China University of TechnologyGuangzhou 510120China The Second School of Clinical Medicine Southern Medical UniversityGuangzhou 510515China Department of Pathology Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhou 510080China

Objective:To develop and validate a radiomics prognostic scoring system(RPSS)for prediction of progressionfree survival(PFS)in patients with stageⅣnon-small cell lung cancer(NSCLC)treated with platinum-based chemotherapy.Methods:In this retrospective study,four independent cohorts of stageⅣNSCLC patients treated with platinum-based chemotherapy were included for model construction and validation(Discovery:n=159;Internal validation:n=156;External validation:n=81,Mutation validation:n=64).First,a total of 1,182 three-dimensional radiomics features were extracted from pre-treatment computed tomography(CT)images of each patient.Then,a radiomics signature was constructed using the least absolute shrinkage and selection operator method(LASSO)penalized Cox regression analysis.Finally,an individualized prognostic scoring system incorporating radiomics signature and clinicopathologic risk factors was proposed for PFS prediction.Results:The established radiomics signature consisting of 16 features showed good discrimination for classifying patients with high-risk and low-risk progression to chemotherapy in all cohorts(All P<0.05).On the multivariable analysis,independent factors for PFS were radiomics signature,performance status(PS),and N stage,which were all selected into construction of RPSS.The RPSS showed significant prognostic performance for predicting PFS in discovery[C-index:0.772,95%confidence interval(95%CI):0.765-0.779],internal validation(C-index:0.738,95%CI:0.730-0.746),external validation(C-index:0.750,95%CI:0.734-0.765),and mutation validation(Cindex:0.739,95%CI:0.720-0.758).Decision curve analysis revealed that RPSS significantly outperformed the clinicopathologic-based model in terms of clinical usefulness(All P<0.05).Conclusions:This study established a radiomics prognostic scoring system as RPSS that can be conveniently used to achieve individualized prediction of PFS probability for stageⅣNSCLC patients treated with platinumbased chemotherapy,which holds promise for guiding personalized pre-therapy of

关键词： Non-small cell lung cancer radiomics prognostic scoring system progression-free survival platinum-based chemotherapy

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Radiomics approach for preoperative identification of stages Ⅰ-Ⅱand Ⅲ-Ⅳ of esophageal cancer

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Chinese Journal of Cancer Research 2018年第4期30卷 396-405页

作者： Lei WU Cong Wang Xianzheng Tan Zixuan Cheng Ke Zhao Lifen Yan Yanli liang Zaiyi Liu changhong liang School of Medicine South China University of Technology Guangzhou 510006 China Department of Radiology Guangdong General HospitalGuangdong Academy of Medical Sciences Guangzhou 510080 China School of Automation Science and Engineering South China University of Technology Guangzhou 510641 China

Objective： To predict preoperative staging using a radiomics approach based on computed tomography （CT）images of patients with esophageal squamous cell carcinoma （ESCC）.Methods： This retrospective study included 154 patients （primary cohort： n： t 14; validation cohort： n：40） withpathologically confirmed ESCC. All patients underwent a preoperative CT scan from the neck to abdomen. Highthroughput and quantitative radiomics features were extracted from the CT images for each patient. A radiomicssignature was constructed using the least absolute shrinkage and selection operator （Lasso）. Associations betweenradiomics signature, tumor volume and ESCC staging were explored. Diagnostic performance of radiomicsapproach and tumor volume for discriminating between stages Ⅰ-Ⅱand Ⅲ-Ⅳ was evaluated and compared usingthe receiver operating characteristics （ROC） curves and net reclassification improvement （NRI）.Results= A total of 9,790 radiomics features were extracted. Ten features were selected to build a radiomicssignature after feature dimension reduction. The radiomics signature was significantly associated with ESCCstaging （P〈0.001）, and yielded a better performance for discrimination of early and advanced stage ESCC comparedto tumor volume in both the primary [area under the receiver operating characteristic curve （AUC）： 0.795 vs. 0.694,P=0.003; NRI=0.424）] and validation cohorts （AUC： 0.762 vs. 0.624, P=0.035; NRI=0.834）.Conclusions： The quantitative approach has the potential to identify stage Ⅰ-Ⅱand Ⅲ-Ⅳ ESCC beforetreatment.

关键词： Esophageal cancer tumor staging diagnostic imaging tumor volume

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Individualized prediction of perineural invasion in colorectal cancer: development and validation of a radiomics prediction model

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Chinese Journal of Cancer Research 2018年第1期30卷 40-50页

作者： Yanqi Huang Lan He Di Dong Caiyun Yang Cuishan liang Xin Chen Zelan Ma Xiaomei Huang Su Yao changhong liang Jie Tian Zaiyi Liu Department of Radiology Guangdong General Hospital Guangdong Academy of Medical Sciences School of Medicine South China University of Technology Key Laboratory of Molecular Imaging Chinese Academy of Sciences Department of Radiology the Affiliated Guangzhou First People's Hospital Guangzhou Medical University Department of Pathology Guangdong General Hospital Guangdong Academy of Medical Sciences

Objective： To develop and validate a radiomics prediction model for individualized prediction of perineural invasion（PNI） in colorectal cancer（CRC）.Methods： After computed tomography（CT） radiomics features extraction, a radiomics signature was constructed in derivation cohort（346 CRC patients）. A prediction model was developed to integrate the radiomics signature and clinical candidate predictors [age, sex, tumor location, and carcinoembryonic antigen（CEA） level]. Apparent prediction performance was assessed. After internal validation, independent temporal validation（separate from the cohort used to build the model） was then conducted in 217 CRC patients. The final model was converted to an easy-to-use nomogram.Results： The developed radiomics nomogram that integrated the radiomics signature and CEA level showed good calibration and discrimination performance [Harrell＇s concordance index（c-index）： 0.817; 95% confidence interval（95% CI）： 0.811–0.823]. Application of the nomogram in validation cohort gave a comparable calibration and discrimination（c-index： 0.803; 95% CI： 0.794–0.812）.Conclusions： Integrating the radiomics signature and CEA level into a radiomics prediction model enables easy and effective risk assessment of PNI in CRC. This stratification of patients according to their PNI status may provide a basis for individualized auxiliary treatment.

关键词： Colorectal cancer perineural invasion prediction model radiomics nomogram

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Expert consensus on organizing the multidisciplinary team(MDT) diagnosis and treatment of hepato-pancreato-biliary diseases in China

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Science China(Life Sciences) 2022年第5期65卷 1036-1039页

作者： Binhao Zhang Jian Zhou Weifen Xie Kaishan Tao Shichun Lu Xianglin Yuan Lianxin Liu Weilin Wang Yilei Mao Ping Bie Jingfeng Liu Xinyu Bi Zhiwei Zhang changhong liang Jianqiang Cai Zhixiang Jian Yi Lv Peng Zhu Wei Zhang Hongqiang Yang Weiping Zhou Bixiang Zhang Xiaoping Chen Tongji Hospital Tongji Medical College of Huazhong University of Science and TechnologyWuhan 430030China Zhongshan Hospital Fudan UniversityShanghai 200032China Shanghai Changzheng Hospital Shanghai 200003China Xijing Hospital of Air Force Medical University Xi’an 710032China Chinese PLA General Hospital Beijing 100048China The First Affiliated Hospital of University of Science and Technology of China Hefei 230001China The Second Affiliated Hospital of Medical College of Zhejiang University Hangzhou 310009China Peking Union Medical College Hospital Beijing 100140China The Third Affiliated Hospital of Chongqing Medical University Chongqing 400016China Fujian Medical University Cancer Hospital Fuzhou 350005China Cancer Hospital Chinese Academy of Medical Sciences Beijing 100021China Guangdong Provincial People’s Hospital Guangzhou 510080China The First Affiliated Hospital of Xi’an Jiaotong University Xi’an 710061China The First Affiliated Hospital of Chengdu Medical College Chengdu 610599China The Eastern Hepatobiliary Surgery Hospital Second Military Medical UniversityShanghai 201805China

Multidisciplinary team(MDT) discussion has been well established in some European countries and widely carried out in various clinical professional fields(Festen et al.,2021;Fleissig et al.,2006).Many studies have reported the benefits of MDT,including improving survival and quality of cancer care(Munro et al.,2015;Nixon et al.,2021;Tsai et al.,2020).

关键词： diagnosis MDT

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基于自然语言生成的制造企业自动化图表分析方法研究

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计算机科学 2024年第4期51卷 174-181页

作者：王旭刘昌宏李生春刘爽赵康廷陈亮西安工程大学计算机科学学院西安710048 重庆中烟工业有限责任公司黔江卷烟厂重庆409000 陕西师范大学数学与统计学院西安710119

随着数字化转型的浪潮席卷全球,制造企业每天都会产生大量的图表数据,传统的图表分析方法很难对图表数据进行高效、准确的分析,自动化图表分析方法成为图表分析的重要手段。为解决自动化图表分析方法在实际应用时很难满足具体需求的问题... 详细信息

随着数字化转型的浪潮席卷全球,制造企业每天都会产生大量的图表数据,传统的图表分析方法很难对图表数据进行高效、准确的分析,自动化图表分析方法成为图表分析的重要手段。为解决自动化图表分析方法在实际应用时很难满足具体需求的问题,提出了一种基于自然语言生成的制造企业自动化图表分析方法。该方法基于LSTM对图表数据进行分析,并针对分析过程中出现的多余数据误导LSTM等问题,在嵌入层之后增加判别器层使LSTM能够根据图表类型进行更有针对性的语义理解和文本预测;针对图表分析过程中生成描述语句质量差等问题,参考集束搜索和随机采样策略,提出随机集束采样策略以提高图表分析质量,并引入知识蒸馏方法对LSTM进行优化,进一步提高描述文本的质量。实验证明,相较于LSTM,该方法文本质量提升了8.9%。为了便于将该方法应用在实际中,设计并开发了制造企业自动化图表分析系统,并将该方法引入作为图表分析工具。实验结果表明,所提方法能够提高制造企业图表分析的质量和效率。

关键词：图表分析自然语言生成 LSTM 知识蒸馏

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Prognostic value of a modified Immunoscore in patients with stage Ⅰ-Ⅲ resectable colon cancer

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Chinese Journal of Cancer Research 2021年第3期33卷 379-390页

作者： Ke Zhao Xiaomei Wu Zhenhui Li Yingyi Wang Zeyan Xu Yajun Li Lin Wu Su Yao Yanqi Huang changhong liang Zaiyi Liu Department of Radiology Guangdong Provincial People's HospitalGuangdong Academy of Medical SciencesGuangzhou 510080China School of Medicine South China University of TechnologyGuangzhou 510006China Department of Radiology the Sixth Affiliated Hospital of Sun Yat-sen UniversityGuangzhou 510655China Department of Radiology the Third Affiliated Hospital of Kunming Medical UniversityYunnan Cancer HospitalYunnan Cancer CenterKunming 650118China Department of Radiology Zhuhai People's HospitalZhuhai Hospital Affiliated with Jinan UniversityZhuhai 519000China Department of Pathology the Third Affiliated Hospital of Kunming Medical UniversityYunnan Cancer HospitalYunnan Cancer CenterKunming 650118China Department of Pathology Guangdong Provincial People's HospitalGuangdong Academy of Medical SciencesGuangzhou 510080China the Second School of Clinical Medicine Southern Medical UniversityGuangzhou 510080China

Objective: The Immunoscore method has proved fruitful for predicting prognosis in patients with colon cancer.However, there is still room for improvement in this scoring method to achieve further advances in its clinical translation. This study aimed to develop and validate a modified Immunoscore(IS-mod) system for predicting overall survival(OS) in patients with stage Ⅰ-Ⅲ colon cancer.Methods: The IS-mod was proposed by counting CD3+ and CD8+ immune cells in regions of the tumor core and its invasive margin by drawing two lines of interest. A discovery cohort(N=212) and validation cohort(N=103)from two centers were used to evaluate the prognostic value of the IS-mod.Results: In the discovery cohort, 5-year survival rates were 88.6% in the high IS-mod group and 60.7% in the low IS-mod group. Multivariate analysis confirmed that the IS-mod was an independent prognostic factor for OS[adjusted hazard ratio(HR)=0.36, 95% confidence interval(95% CI): 0.20-0.63]. With less annotation and computation cost, the IS-mod achieved performance comparable to that of the Immunoscore-like(IS-like) system(C-index, 0.676 vs. 0.661, P=0.231). The 2-category IS-mod using 47.5% as the threshold had a better prognostic value than that using a fixed threshold of 25%(C-index, 0.653 vs. 0.573, P=0.004). Similar results were confirmed in the validation cohort.Conclusions: Our method simplifies the annotation and accelerates the calculation of Immunoscore method,thus making it easier for clinical implementation. The IS-mod achieved comparable prognostic performance when compared to the IS-like system in both cohorts. Besides, we further found that even with a small reference set(N≥120), the IS-mod still demonstrated a stable prognostic value. This finding may inspire other institutions to develop a local reference set of an IS-mod system for more accurate risk stratification of colon cancer.

关键词： Immunoscore colon cancer whole-slide image overall survival digital pathology

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