Background: The TNM staging system is far from perfect in predicting the survival of individual cancer patients because only the gross anatomy is considered. The survival rates of the patients who have the same TNM st...Background: The TNM staging system is far from perfect in predicting the survival of individual cancer patients because only the gross anatomy is considered. The survival rates of the patients who have the same TNM stage disease vary across a wide spectrum. This study aimed to develop a nomogram that incorporates other clinicopathologic factors for predicting the overall survival(OS) of non-metastatic nasopharyngeal carcinoma(NPC) patients after curative treatments.Methods: We retrospectively collected the clinical data of 1520 NPC patients who were diagnosed histologically between November 2000 and September 2003. The clinical data of a separate cohort of 464 patients who received intensity-modulated radiation therapy(IMRT) between 2001 and 2010 were also retrieved to examine the extensibility of the model. Cox regression analysis was used to identify the prognostic factors for building the nomogram. The predictive accuracy and discriminative ability were measured using the concordance index(c-index).Results: We identiied and incorporated 12 independent clinical factors into the nomogram. The calibration curves showed that the prediction of OS was in good agreement with the actual observation in the internal validation set and IMRT cohort. The c-index of the nomogram was statistically higher than that of the 7th edition TNM staging system for predicting the survival in both the primary cohort(0.69 vs. 0.62) and the IMRT cohort(0.67 vs. 0.63).Conclusion: We developed and validated a novel nomogram that outperformed the TNM staging system in predicting the OS of non-metastatic NPC patients who underwent curative therapy.展开更多
Neurodegenerative diseases(NDs)have become a significant threat to an aging human society.Numerous studies have been conducted in the past decades to clarify their pathologic mechanisms and search for reliable biomark...Neurodegenerative diseases(NDs)have become a significant threat to an aging human society.Numerous studies have been conducted in the past decades to clarify their pathologic mechanisms and search for reliable biomarkers.Magnetic resonance imaging(MRI)is a powerful tool for investigating structural and functional brain alterations in NDs.With the advantages of being non-invasive and non-radioactive,it has been frequently used in both animal research and large-scale clinical investigations.MRI may serve as a bridge connecting micro-and macro-level analysis and promoting bench-to-bed translational research.Nevertheless,due to the abundance and complexity of MRI techniques,exploiting their potential is not always straightforward.This review aims to briefly introduce research progress in clinical imaging studies and discuss possible strategies for applying MRI in translational ND research.展开更多
Background:Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperpla-sia,the positive rate for malignancy identification during biopsy is low,thus leading to delayed or missed di...Background:Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperpla-sia,the positive rate for malignancy identification during biopsy is low,thus leading to delayed or missed diagnosis for nasopharyngeal malignancies upon initial attempt.Here,we aimed to develop an artificial intelligence tool to detect nasopharyngeal malignancies under endoscopic examination based on deep learning.Methods:An endoscopic images-based nasopharyngeal malignancy detection model(eNPM-DM)consisting of a fully convolutional network based on the inception architecture was developed and fine-tuned using separate training and validation sets for both classification and segmentation.Briefly,a total of 28,966 qualified images were collected.Among these images,27,536 biopsy-proven images from 7951 individuals obtained from January 1st,2008,to December 31st,2016,were split into the training,validation and test sets at a ratio of 7:1:2 using simple randomiza-tion.Additionally,1430 images obtained from January 1st,2017,to March 31st,2017,were used as a prospective test set to compare the performance of the established model against oncologist evaluation.The dice similarity coef-ficient(DSC)was used to evaluate the efficiency of eNPM-DM in automatic segmentation of malignant area from the background of nasopharyngeal endoscopic images,by comparing automatic segmentation with manual segmenta-tion performed by the experts.Results:All images were histopathologically confirmed,and included 5713(19.7%)normal control,19,107(66.0%)nasopharyngeal carcinoma(NPC),335(1.2%)NPC and 3811(13.2%)benign diseases.The eNPM-DM attained an overall accuracy of 88.7%(95%confidence interval(CI)87.8%-89.5%)in detecting malignancies in the test set.In the prospective comparison phase,eNPM-DM outperformed the experts:the overall accuracy was 88.0%(95%CI 86.1%-89.6%)vs.80.5%(95%CI 77.0%-84.0%).The eNPM-DM required less time(40 s vs.110.0±5.8 min)and exhibited encouraging performance in automatic segmentation of nasopharyngeal malignant area from the background,with an average DSC of 0.78±0.24 and 0.75±0.26 in the test and prospective test sets,respectively.Conclusions:The eNPM-DM outperformed oncologist evaluation in diagnostic classification of nasopharyngeal mass into benign versus malignant,and realized automatic segmentation of malignant area from the background of nasopharyngeal endoscopic images.展开更多
The latent expression pattern of Epstein-Barr Virus (EBV)igenes in nasopharyngeal carcinoma (NPC) has been extensively investigated, and the expression of several lytic genes in NPC has been reported. However, com...The latent expression pattern of Epstein-Barr Virus (EBV)igenes in nasopharyngeal carcinoma (NPC) has been extensively investigated, and the expression of several lytic genes in NPC has been reported. However, comprehensive information through EBV transcriptome analysis in NPC is limited. We performed paired-end RNA-seq to systematically and comprehensively characterize the expression of EBV genes in NPC tissue and C666-1 NPC cell line, which consistently carries EBV. In addition to the transcripts restricted to type II latency infection, the type Ⅲ latency EBNA3s genes and a substantial number of lytic genes, such as BZLF1, BRLF1, and BMRF1, were detected through RNA-seq and were further verified in C666-1 cells and NPC tissue through real- time PCR. We also performed clustering analysis to classify NPC patient groups in terms of EBV gene expression, which presented two subtypes of NPC samples. Results revealed interesting patterns of EBV gene expression in NPC patients. This clustering was correlated with many signaling pathways, such as those related to heterotrimeric G-protein signaling, inflammation mediated by chemokine and cytokine signaling, ribosomes, protein metabolism, influenza infection, and ECM-receptor interaction. Our combined findings suggested that the expression of EBV genes in NPC is restricted not only to type II latency genes but also to type Ⅲ latency and lyric genes. This study provided further insights into the potential role of EBV in the development of NPC.展开更多
Background:Individuals with subjective memory complaints(SMC)feature a higher risk of cognitive decline and clinical progression of Alzheimer’s disease(AD).However,the pathological mechanism underlying SMC remains un...Background:Individuals with subjective memory complaints(SMC)feature a higher risk of cognitive decline and clinical progression of Alzheimer’s disease(AD).However,the pathological mechanism underlying SMC remains unclear.We aimed to assess the intrinsic connectivity network and its relationship with AD-related pathologies in SMC individuals.Methods:We included 44 SMC individuals and 40 normal controls who underwent both resting-state functional MRI and positron emission tomography(PET).Based on graph theory approaches,we detected local and global functional connectivity across the whole brain by using degree centrality(DC)and eigenvector centrality(EC)respectively.Additionally,we analyzed amyloid deposition and tauopathy via florbetapir-PET imaging and cerebrospinal fluid(CSF)data.The voxel-wise two-sample T-test analysis was used to examine between-group differences in the intrinsic functional network and cerebral amyloid deposition.Then,we correlated these network metrics with pathological results.Results:The SMC individuals showed higher DC in the bilateral hippocampus(HP)and left fusiform gyrus and lower DC in the inferior parietal region than controls.Across all subjects,the DC of the bilateral HP and left fusiform gyrus was positively associated with total tau and phosphorylated tau181.However,no significant between-group difference existed in EC and cerebral amyloid deposition.Conclusion:We found impaired local,but not global,intrinsic connectivity networks in SMC individuals.Given the relationships between DC value and tau level,we hypothesized that functional changes in SMC individuals might relate to pathological biomarkers.展开更多
Background:Different oscillations of brain networks could carry different dimensions of brain integration.We aimed to investigate oscillation-specific nodal alterations in patients with Parkinson’s disease(PD)across ...Background:Different oscillations of brain networks could carry different dimensions of brain integration.We aimed to investigate oscillation-specific nodal alterations in patients with Parkinson’s disease(PD)across early stage to middle stage by using graph theory-based analysis.Methods:Eighty-eight PD patients including 39 PD patients in the early stage(EPD)and 49 patients in the middle stage(MPD)and 36 controls were recruited in the present study.Graph theory-based network analyses from three oscillation frequencies(slow-5:0.01–0.027 Hz;slow-4:0.027–0.073 Hz;slow-3:0.073–0.198 Hz)were analyzed.Nodal metrics(e.g.nodal degree centrality,betweenness centrality and nodal efficiency)were calculated.Results:Our results showed that(1)a divergent effect of oscillation frequencies on nodal metrics,especially on nodal degree centrality and nodal efficiency,that the anteroventral neocortex and subcortex had high nodal metrics within low oscillation frequencies while the posterolateral neocortex had high values within the relative high oscillation frequency was observed,which visually showed that network was perturbed in PD;(2)PD patients in early stage relatively preserved nodal properties while MPD patients showed widespread abnormalities,which was consistently detected within all three oscillation frequencies;(3)the involvement of basal ganglia could be specifically observed within slow-5 oscillation frequency in MPD patients;(4)logistic regression and receiver operating characteristic curve analyses demonstrated that some of those oscillation-specific nodal alterations had the ability to well discriminate PD patients from controls or MPD from EPD patients at the individual level;(5)occipital disruption within high frequency(slow-3)made a significant influence on motor impairment which was dominated by akinesia and rigidity.Conclusions:Coupling various oscillations could provide potentially useful information for large-scale network and progressive oscillation-specific nodal alterations were observed in PD patients across early to middle stages.展开更多
基金supported by the National High Technology Research and Development Program of China (Grant No.2012AA02A501 and 2012AA02A502)Sun Yat-sen University Clinical Medical Research Project 5010 (Grant No.20130008)
文摘Background: The TNM staging system is far from perfect in predicting the survival of individual cancer patients because only the gross anatomy is considered. The survival rates of the patients who have the same TNM stage disease vary across a wide spectrum. This study aimed to develop a nomogram that incorporates other clinicopathologic factors for predicting the overall survival(OS) of non-metastatic nasopharyngeal carcinoma(NPC) patients after curative treatments.Methods: We retrospectively collected the clinical data of 1520 NPC patients who were diagnosed histologically between November 2000 and September 2003. The clinical data of a separate cohort of 464 patients who received intensity-modulated radiation therapy(IMRT) between 2001 and 2010 were also retrieved to examine the extensibility of the model. Cox regression analysis was used to identify the prognostic factors for building the nomogram. The predictive accuracy and discriminative ability were measured using the concordance index(c-index).Results: We identiied and incorporated 12 independent clinical factors into the nomogram. The calibration curves showed that the prediction of OS was in good agreement with the actual observation in the internal validation set and IMRT cohort. The c-index of the nomogram was statistically higher than that of the 7th edition TNM staging system for predicting the survival in both the primary cohort(0.69 vs. 0.62) and the IMRT cohort(0.67 vs. 0.63).Conclusion: We developed and validated a novel nomogram that outperformed the TNM staging system in predicting the OS of non-metastatic NPC patients who underwent curative therapy.
基金supported by the National Natural Science Foundation of China(81971577 and 81771820)the Natural Science Foundation of Zhejiang Province(LSZ19H180001)the 13th Five-year Plan for National Key Research and Development Program of China(2016YFC1306600).
文摘Neurodegenerative diseases(NDs)have become a significant threat to an aging human society.Numerous studies have been conducted in the past decades to clarify their pathologic mechanisms and search for reliable biomarkers.Magnetic resonance imaging(MRI)is a powerful tool for investigating structural and functional brain alterations in NDs.With the advantages of being non-invasive and non-radioactive,it has been frequently used in both animal research and large-scale clinical investigations.MRI may serve as a bridge connecting micro-and macro-level analysis and promoting bench-to-bed translational research.Nevertheless,due to the abundance and complexity of MRI techniques,exploiting their potential is not always straightforward.This review aims to briefly introduce research progress in clinical imaging studies and discuss possible strategies for applying MRI in translational ND research.
基金supported by the National Natural Science Foundation of China[Grant Nos.81572665,81672680,81472525,81702873]the International Cooperation Project of Science and Technology Plan of Guangdong Province[Grant No.2016A050502011]the Health&Medical Collaborative Innovation Project of Guangzhou City,China(Grant No.201604020003).
文摘Background:Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperpla-sia,the positive rate for malignancy identification during biopsy is low,thus leading to delayed or missed diagnosis for nasopharyngeal malignancies upon initial attempt.Here,we aimed to develop an artificial intelligence tool to detect nasopharyngeal malignancies under endoscopic examination based on deep learning.Methods:An endoscopic images-based nasopharyngeal malignancy detection model(eNPM-DM)consisting of a fully convolutional network based on the inception architecture was developed and fine-tuned using separate training and validation sets for both classification and segmentation.Briefly,a total of 28,966 qualified images were collected.Among these images,27,536 biopsy-proven images from 7951 individuals obtained from January 1st,2008,to December 31st,2016,were split into the training,validation and test sets at a ratio of 7:1:2 using simple randomiza-tion.Additionally,1430 images obtained from January 1st,2017,to March 31st,2017,were used as a prospective test set to compare the performance of the established model against oncologist evaluation.The dice similarity coef-ficient(DSC)was used to evaluate the efficiency of eNPM-DM in automatic segmentation of malignant area from the background of nasopharyngeal endoscopic images,by comparing automatic segmentation with manual segmenta-tion performed by the experts.Results:All images were histopathologically confirmed,and included 5713(19.7%)normal control,19,107(66.0%)nasopharyngeal carcinoma(NPC),335(1.2%)NPC and 3811(13.2%)benign diseases.The eNPM-DM attained an overall accuracy of 88.7%(95%confidence interval(CI)87.8%-89.5%)in detecting malignancies in the test set.In the prospective comparison phase,eNPM-DM outperformed the experts:the overall accuracy was 88.0%(95%CI 86.1%-89.6%)vs.80.5%(95%CI 77.0%-84.0%).The eNPM-DM required less time(40 s vs.110.0±5.8 min)and exhibited encouraging performance in automatic segmentation of nasopharyngeal malignant area from the background,with an average DSC of 0.78±0.24 and 0.75±0.26 in the test and prospective test sets,respectively.Conclusions:The eNPM-DM outperformed oncologist evaluation in diagnostic classification of nasopharyngeal mass into benign versus malignant,and realized automatic segmentation of malignant area from the background of nasopharyngeal endoscopic images.
基金This study was supported by 973 Program and 863 Program from the Ministry of Science and Technology of China (Nos. 2011CB504300 and 2015AA020931), National Natural Science Foundation of China (Nos. 91440106, 91019015, and 81302037), Ph.D. Startup of Guangzhou Medical University (No. 2012C65), Guangzhou Science and Technology Planing Project (No. 2014J4100181), and Young Teacher Training Program ofStm Yat-sen University (No. 13ykpy50).
文摘The latent expression pattern of Epstein-Barr Virus (EBV)igenes in nasopharyngeal carcinoma (NPC) has been extensively investigated, and the expression of several lytic genes in NPC has been reported. However, comprehensive information through EBV transcriptome analysis in NPC is limited. We performed paired-end RNA-seq to systematically and comprehensively characterize the expression of EBV genes in NPC tissue and C666-1 NPC cell line, which consistently carries EBV. In addition to the transcripts restricted to type II latency infection, the type Ⅲ latency EBNA3s genes and a substantial number of lytic genes, such as BZLF1, BRLF1, and BMRF1, were detected through RNA-seq and were further verified in C666-1 cells and NPC tissue through real- time PCR. We also performed clustering analysis to classify NPC patient groups in terms of EBV gene expression, which presented two subtypes of NPC samples. Results revealed interesting patterns of EBV gene expression in NPC patients. This clustering was correlated with many signaling pathways, such as those related to heterotrimeric G-protein signaling, inflammation mediated by chemokine and cytokine signaling, ribosomes, protein metabolism, influenza infection, and ECM-receptor interaction. Our combined findings suggested that the expression of EBV genes in NPC is restricted not only to type II latency genes but also to type Ⅲ latency and lyric genes. This study provided further insights into the potential role of EBV in the development of NPC.
基金Data collection and sharing for this project was funded by the Alzheimer’s Disease Neuroimaging Initiative(ADNI)(National Institutes of Health Grant U01 AG024904)and DOD ADNI(Department of Defense award number W81XWH-12-2-0012)This study was funded by National Key Research and Development Program of China(Grant No.2016YFC1306600)+3 种基金Zhejiang Provincial Natural Science Foundation of China(Grant Nos.LZ14H180001 and Y16H090026)Young ResearchTalents Fund,Chinese Medicine Science,and Technology Project of Zhejiang Province(Grant No.2018ZQ035)the Fundamental Research Funds for the Central Universities(No.2017XZZX001-01)Zhejiang Medicine and Health Science and Technology Program(2018KY418).
文摘Background:Individuals with subjective memory complaints(SMC)feature a higher risk of cognitive decline and clinical progression of Alzheimer’s disease(AD).However,the pathological mechanism underlying SMC remains unclear.We aimed to assess the intrinsic connectivity network and its relationship with AD-related pathologies in SMC individuals.Methods:We included 44 SMC individuals and 40 normal controls who underwent both resting-state functional MRI and positron emission tomography(PET).Based on graph theory approaches,we detected local and global functional connectivity across the whole brain by using degree centrality(DC)and eigenvector centrality(EC)respectively.Additionally,we analyzed amyloid deposition and tauopathy via florbetapir-PET imaging and cerebrospinal fluid(CSF)data.The voxel-wise two-sample T-test analysis was used to examine between-group differences in the intrinsic functional network and cerebral amyloid deposition.Then,we correlated these network metrics with pathological results.Results:The SMC individuals showed higher DC in the bilateral hippocampus(HP)and left fusiform gyrus and lower DC in the inferior parietal region than controls.Across all subjects,the DC of the bilateral HP and left fusiform gyrus was positively associated with total tau and phosphorylated tau181.However,no significant between-group difference existed in EC and cerebral amyloid deposition.Conclusion:We found impaired local,but not global,intrinsic connectivity networks in SMC individuals.Given the relationships between DC value and tau level,we hypothesized that functional changes in SMC individuals might relate to pathological biomarkers.
基金This work was supported by the 13th Five-year Plan for National Key Research and Development Program of China(Grant No.2016YFC1306600)the Fundamental Research Funds for the Central Universities of China(Grant No.2017XZZX001-01)+3 种基金the 12th Five-year Plan for National Science and Technology Supporting Program of China(Grant No.2012BAI10B04)the National Natural Science Foundation of China(Grant Nos.81571654,81371519 and 81701647)the Cooperative Project by Ministry of Health and Provincial Department(Grant No.2016149022)the Projects of Medical and Health Technology Development Program in Zhejiang Province(Grant No.2015KYB174).
文摘Background:Different oscillations of brain networks could carry different dimensions of brain integration.We aimed to investigate oscillation-specific nodal alterations in patients with Parkinson’s disease(PD)across early stage to middle stage by using graph theory-based analysis.Methods:Eighty-eight PD patients including 39 PD patients in the early stage(EPD)and 49 patients in the middle stage(MPD)and 36 controls were recruited in the present study.Graph theory-based network analyses from three oscillation frequencies(slow-5:0.01–0.027 Hz;slow-4:0.027–0.073 Hz;slow-3:0.073–0.198 Hz)were analyzed.Nodal metrics(e.g.nodal degree centrality,betweenness centrality and nodal efficiency)were calculated.Results:Our results showed that(1)a divergent effect of oscillation frequencies on nodal metrics,especially on nodal degree centrality and nodal efficiency,that the anteroventral neocortex and subcortex had high nodal metrics within low oscillation frequencies while the posterolateral neocortex had high values within the relative high oscillation frequency was observed,which visually showed that network was perturbed in PD;(2)PD patients in early stage relatively preserved nodal properties while MPD patients showed widespread abnormalities,which was consistently detected within all three oscillation frequencies;(3)the involvement of basal ganglia could be specifically observed within slow-5 oscillation frequency in MPD patients;(4)logistic regression and receiver operating characteristic curve analyses demonstrated that some of those oscillation-specific nodal alterations had the ability to well discriminate PD patients from controls or MPD from EPD patients at the individual level;(5)occipital disruption within high frequency(slow-3)made a significant influence on motor impairment which was dominated by akinesia and rigidity.Conclusions:Coupling various oscillations could provide potentially useful information for large-scale network and progressive oscillation-specific nodal alterations were observed in PD patients across early to middle stages.