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| 1 | Individualized prediction of perineural invasion in colorectal cancer: development and validation of a radiomics prediction model显示文摘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. | Yanqi Huang Lan He Di Dong Caiyun Yang Cuishan Liang Xin Chen Zelan Ma Xiaomei Huang Su Yao Changhong Liang Jie Tian Zaiyi Liu | 2018 | Chinese Journal of Cancer Research2018，30，1： | 23 |
| 2 | Computed tomography-based radiomics for prediction of neoadjuvant chemotherapy outcomes in locally advanced gastric cancer: A pilot study显示文摘Objective: The standard treatment for patients with locally advanced gastric cancer has relied on perioperative radio-chemotherapy or chemotherapy and surgery. The aim of this study was to investigate the wealth of radiomics for pre-treatment computed tomography(CT) in the prediction of the pathological response of locally advanced gastric cancer with preoperative chemotherapy.Methods: Thirty consecutive patients with CT-staged II/III gastric cancer receiving neoadjuvant chemotherapy were enrolled in this study between December 2014 and March 2017. All patients underwent upper abdominal CT during the unenhanced, late arterial phase(AP) and portal venous phase(PP) before the administration of neoadjuvant chemotherapy. In total, 19,985 radiomics features were extracted in the AP and PP for each patient.Four methods were adopted during feature selection and eight methods were used in the process of building the classifier model. Thirty-two combinations of feature selection and classification methods were examined. Receiver operating characteristic(ROC) curves were used to evaluate the capability of each combination of feature selection and classification method to predict a non-good response(non-GR) based on tumor regression grade(TRG).Results: The mean area under the curve(AUC) ranged from 0.194 to 0.621 in the AP, and from 0.455 to 0.722 in the PP, according to different combinations of feature selection and the classification methods. There was only one cross-combination machine-learning method indicating a relatively higher AUC(>0.600) in the AP, while 12 cross-combination machine-learning methods presented relatively higher AUCs(all >0.600) in the PP. The feature selection method adopted by a filter based on linear discriminant analysis + classifier of random forest achieved a significantly prognostic performance in the PP(AUC, 0.722±0.108; accuracy, 0.793; sensitivity, 0.636; specificity,0.889; Z=2.039; P=0.041).Conclusions: It is possible to predict non-GR after neoadjuvant chemotherapy in locally advanced gastric cancers based on the radiomics of CT. | Zhenhui Li Dafu Zhang Youguo Dai Jian Dong Lin Wu Yajun Li Zixuan Cheng Yingying Ding Zaiyi Liu | 2018 | Chinese Journal of Cancer Research2018，30，4： | 18 |
| 3 | Radiomics approach for preoperative identification of stages Ⅰ-Ⅱand Ⅲ-Ⅳ of esophageal cancer显示文摘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=114; validation cohort: n=40) with pathologically confirmed ESCC. All patients underwent a preoperative CT scan from the neck to abdomen. High throughput and quantitative radiomics features were extracted from the CT images for each patient. A radiomics signature was constructed using the least absolute shrinkage and selection operator(Lasso). Associations between radiomics signature, tumor volume and ESCC staging were explored. Diagnostic performance of radiomics approach and tumor volume for discriminating between stages Ⅰ-Ⅱ and Ⅲ-Ⅳ was evaluated and compared using the 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 radiomics signature after feature dimension reduction. The radiomics signature was significantly associated with ESCC staging(P<0.001), and yielded a better performance for discrimination of early and advanced stage ESCC compared to 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-Ⅱ and Ⅲ-Ⅳ ESCC before treatment. | Lei WU Cong Wang Xianzheng Tan Zixuan Cheng Ke Zhao Lifen Yan Yanli Liang Zaiyi Liu Changhong Liang | 2018 | Chinese Journal of Cancer Research2018，30，4： | 14 |
| 4 | 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显示文摘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. | Lan He Yanqi Huang Lixu Yan Junhui Zheng Changhong Liang Zaiyi Liu | 2019 | Chinese Journal of Cancer Research2019，31，4： | 7 |
| 5 | Evaluation of human epidermal growth factor receptor 2 status of breast cancer using preoperative multidetector computed tomography with deep learning and handcrafted radiomics features显示文摘Objective:To evaluate the human epidermal growth factor receptor 2(HER2)status in patients with breast cancer using multidetector computed tomography(MDCT)-based handcrafted and deep radiomics features.Methods:This retrospective study enrolled 339 female patients(primary cohort,n=177;validation cohort,n=162)with pathologically confirmed invasive breast cancer.Handcrafted and deep radiomics features were extracted from the MDCT images during the arterial phase.After the feature selection procedures,handcrafted and deep radiomics signatures and the combined model were built using multivariate logistic regression analysis.Performance was assessed by measures of discrimination,calibration,and clinical usefulness in the primary cohort and validated in the validation cohort.Results:The handcrafted radiomics signature had a discriminative ability with a C-index of 0.739[95%confidence interval(95%CI):0.661-0.818]in the primary cohort and 0.695(95%CI:0.609-0.781)in the validation cohort.The deep radiomics signature also had a discriminative ability with a C-index of 0.760(95%CI:0.690-0.831)in the primary cohort and 0.777(95%CI:0.696-0.857)in the validation cohort.The combined model,which incorporated both the handcrafted and deep radiomics signatures,showed good discriminative ability with a C-index of 0.829(95%CI:0.767-0.890)in the primary cohort and 0.809(95%CI:0.740-0.879)in the validation cohort.Conclusions:Handcrafted and deep radiomics features from MDCT images were associated with HER2 status in patients with breast cancer.Thus,these features could provide complementary aid for the radiological evaluation of HER2 status in breast cancer. | Xiaojun Yang Lei Wu Ke Zhao Weitao Ye Weixiao Liu Yingyi Wang Jiao Li Hanxiao Li Xiaomei Huang Wen Zhang Yanqi Huang Xin Chen Su Yao Zaiyi Liu Changhong Liang | 2020 | Chinese Journal of Cancer Research2020，32，2： | 4 |
| 6 | Integrating pathomics with radiomics and genomics for cancer prognosis:A brief review显示文摘In the last decade,the focus of computational pathology research community has shifted from replicating the pathological examination for diagnosis done by pathologists to unlocking and discovering'sub-visual'prognostic image cues from the histopathological image.While we are getting more knowledge and experience in digital pathology,the emerging goal is to integrate other-omics or modalities that will contribute for building a better prognostic assay.In this paper,we provide a brief review of representative works that focus on integrating pathomics with radiomics and genomics for cancer prognosis.It includes:correlation of pathomics and genomics;fusion of pathomics and genomics;fusion of pathomics and radiomics.We also present challenges,potential opportunities,and avenues for future work. | Cheng Lu Rakesh Shiradkar Zaiyi Liu | 2021 | Chinese Journal of Cancer Research2021，33，5： | 4 |
| 7 | Development and validation of a CT-based radiomics nomogram for preoperative prediction of tumor histologic grade in gastric adenocarcinoma显示文摘Objectives:To develop and validate a radiomics nomogram for preoperative prediction of tumor histologic grade in gastric adenocarcinoma(GA).Methods:This retrospective study enrolled 592 patients with clinicopathologically confirmed GA(low-grade:n=154;high-grade:n=438)from January 2008 to March 2018 who were divided into training(n=450)and validation(n=142)sets according to the time of computed tomography(CT)examination.Radiomic features were extracted from the portal venous phase CT images.The Mann-Whitney U test and the least absolute shrinkage and selection operator(LASSO)regression model were used for feature selection,data dimension reduction and radiomics signature construction.Multivariable logistic regression analysis was applied to develop the prediction model.The radiomics signature and independent clinicopathologic risk factors were incorporated and presented as a radiomics nomogram.The performance of the nomogram was assessed with respect to its calibration and discrimination.Results:A radiomics signature containing 12 selected features was significantly associated with the histologic grade of GA(P<0.001 for both training and validation sets).A nomogram including the radiomics signature and tumor location as predictors was developed.The model showed both good calibration and good discrimination,in which C-index in the training set,0.752[95%confidence interval(95%CI):0.701-0.803];C-index in the validation set,0.793(95%CI:0.711-0.874).Conclusions:This study developed a radiomics nomogram that incorporates tumor location and radiomics signatures,which can be useful in facilitating preoperative individualized prediction of histologic grade of GA. | Jia Huang Huasheng Yao Yexing Li Mengyi Dong Chu Han Lan He Xiaomei Huang Ting Xia Zongjian Yi Huihui Wang Yuan Zhang Jian He Changhong Liang Zaiyi Liu | 2021 | Chinese Journal of Cancer Research2021，33，1： | 3 |
| 8 | A radiomics prognostic scoring system for predicting progression-free survival in patients with stageⅣnon-small cell lung cancer treated with platinum-based chemotherapy显示文摘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 stageⅣNSCLC. | Lan He Zhenhui Li Xin Chen Yanqi Huang Lixu Yan Changhong Liang Zaiyi Liu | 2021 | Chinese Journal of Cancer Research2021，33，5： | 3 |
| 9 | Coupling radiomics analysis of CT image with diversification of tumor ecosystem: A new insight to overall survival in stage Ⅰ-Ⅲ colorectal cancer显示文摘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 risk stratification among stage Ⅰ-Ⅲ CRC patients. | Yanqi Huang Lan He Zhenhui Li Xin Chen Chu Han Ke Zhao Yuan Zhang Jinrong Qu Yun Mao Changhong Liang Zaiyi Liu | 2022 | Chinese Journal of Cancer Research2022，34，1： | 2 |
| 10 | Probe into the method of regional ecological risk assessment—a case study of wetland in the Yellow River Delta in China显示文摘 | Xuegong Xu Huiping Lin Zaiyi Fu | 2003 | Journal of Environmental Management2003，，3： | 1 |
| 11 | Migration of a red blood cell in a permeable microvessel显示文摘One of the important features of the microvessels is with permeable vessels.The hyperpermeablility is especially prounounced due to the fast grow of the microvessel in the tumor tissues.Flow field induced by leakage often presents a different figure compared to that of the health vessel.Non-uniform velocity and pressure distribution are found in the simulation by using Lattice Boltzmann Method combined with Starling law.This non-uniform flow field has significant influence on the mass transport in permeable mocrovessel,such as the motion of red blood cell.Using 2D spring network model to express the red blood cell and immersed boundary method to implement the coupling of fluid and structure,numerical simulations were carried out to study the migration of a red blood cell in a straight permeable channel.The results show that the staying time of red blood cell in the leakage region increases with the intensity of leakage.We also found that the leakage can weaken the lateral migration of the red blood cell from the wall to the channel center,and even tune the migration towards the wall when the leakage is reasonably strong. | Zaiyi Shen Ying He | 2019 | Medicine in Novel Technology and Devices2019，，3： | 1 |
| 12 | 人工干扰下城市水系与建成区空间过渡关系研究——以加拿大多伦多为例显示文摘当前我国城市建设整体上处于一个快速上升期,城市水系保护及城市建成区对水系高强度甚至是超强度干扰的问题比较突出,因此,有必要借鉴国外相关好的做法,促进城市与自然的协调发展。以人类活动对水系产生的影响——人工干扰强度为测度,对加拿大多伦多地区的城市水系与城市建成区的空间过渡和衔接形式进行了调研和分析。结果显示,多伦多地区的人工干扰有3种类型,即自然环境主导型、人工环境主导型和自然人工环境共存型;多伦多城市发展成熟,很好地实现了在不同人工干扰强度下城市水系保护与利用的平衡,积累了指导城市水系与建成区过渡空间开发的理论方法和实践经验。借鉴多伦多市的成功经验,对我国城市化建设过程中人与自然的协调问题提出了相关建议。 | 陈林 李双双 LIAO Zaiyi | 2016 | 人民长江2016，47，8： | 1 |
| 13 | Angiomyolipoma with Minimal Fat显示文摘 | Lifen Yan Zaiyi Liu Guangyi Wang Yanqi Huang Yubao Liu Yuanxin Yu Changhong Liang | 2015 | Academic Radiology2015，，： | 1 |
| 14 | Synergism of INS and PDR in self-contained pedestrian tracking with a miniature sensor module 显示文摘 | Huang Chengliang Liao Zaiyi Zhao Lian | 2010 | IEEE Sensors Journal2010，10，8： | 1 |
| 15 | Leptin promotes fatty acid oxidation and OXPHOS via the c-Myc/PGC-1 pathway in cancer cells显示文摘Alteration in cellular energy metabolism plays a critical role in the development and progression of cancer. Leptin is a hormone secreted by adipose tissue. Recent reports have shown that leptin can induce cancer cell proliferation and regulate cell energy metabolism, but the regulatory mechanism is still unclear. Here, we showed that leptin could promote cell proliferation and maintain high adenosine triphosphate levels in HCT116 and MCF-7 cells. The expression levels of carnitine palmitoyl transferase 1A (CPT1A), pyruvate dehydrogenase, succinate dehydrogenase subunit A and mitochondrial respiratory chain-associated proteins NADH dehydrogenase 1 (ND1), NADH:ubiquinone oxidoreductase subunit B8, and mitochondrial transcription factor A (TFAM) were distinctly increased in leptin-treated HCT116 and MCF-7 cells, while fatty acid synthase and lactate dehydrogenase expression were downregulated. Simultaneously, we found that c-Myc and peroxisome proliferator-activated receptor gamma co-activator 1 (PGC-1) protein expression levels were significantly increased. These results indicated that leptin boosted fatty acid β-oxidation and the tricarboxylic acid cycle, enhanced oxidative phosphorylation (OXPHOS) activity, and inhibited fatty acid synthesis and glycolysis in tumor cells. Gene transfection experiments revealed that leptin could induce the expression of c-Myc. Moreover, the expressions of PGC-1, CPT1A, and TFAM proteins were downregulated in HCT116 cells with low expression of c-Myc, and the expression levels of these proteins were increased in HCT116 cells overexpressing c-Myc. These findings suggest that leptin plays an important role in the regulation of energy metabolism in tumor cells. It may regulate fatty acid oxidation and OXPHOS of tumor cells by regulating the c-Myc/PGC-1 pathway. Targeting metabolic pathways for cancer treatment has been investigated as potential preventive or therapeutic methods. This study has important implications for the clinical therapy of tumor cell metabolism through hormone regulation. | Qianqian Liu Yang Sun Zaiyi Fei Zhibin Yang Ke Duan Jiaji Zi Qinghua Cui Min Yu Wei Xiong | 2019 | Acta Biochimica et Biophysica Sinica2019，51，7： | 1 |
| 16 | Probe into the method of regional ecological risk assessment-a case study of wetland in the Yellow River Delta in China显示文摘 | Xu Xuegong Lin Huiping Fu Zaiyi | 2004 | Journal of Environmental Management2004，，70： | 1 |
| 17 | MRI quantification of non‐Gaussian water diffusion in normal human kidney: a diffusional kurtosis imaging study显示文摘 | Yanqi Huang Xin Chen Zhongping Zhang Lifen Yan Dan Pan Changhong Liang Zaiyi Liu | 2015 | NMR Biomed2015，，： | 1 |
| 18 | Energy-balanced parameteradaptable protocol design in cooperative wireless sensor net-works 显示文摘 | Lu Bai Lian Zhao Liao Zaiyi | 2009 | International Journal of Multimedia and Ubiquitous Engineering2009，4，1： | 1 |
| 19 | Probe into the method of regional ecological risk assessment-a case study of wetland in the Yellow River Delta in China显示文摘 | Xuegong Xu Huiping Lin Zaiyi Fu | 2004 | Journal of Environmental Management2004，70，3： | 1 |
| 20 | Probe into the method of regional ecological risk assessment: A case study of wetland in the Yellow River Delta in China显示文摘 | Xu Xuegong Lin Huiping Fu Zaiyi | 2004 | Journal of Environmental Management2004，70，3： | 1 |
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