1.Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI
Xue-han WU ; Yu-tao QUE ; Xin-yue YANG ; Zi-qiang WEN ; Yu-ru MA ; Zhi-wen ZHANG ; Quan-meng LIU ; Wen-jie FAN ; Li DING ; Yue-jiao LANG ; Yun-zhu WU ; Jian-peng YUAN ; Shen-ping YU ; Yi-yan LIU ; Yan CHEN
Korean Journal of Radiology 2025;26(5):400-410
Objective:
To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer.
Materials and Methods:
A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs.
Results:
All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027).
Conclusion
The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.
2.Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI
Xue-han WU ; Yu-tao QUE ; Xin-yue YANG ; Zi-qiang WEN ; Yu-ru MA ; Zhi-wen ZHANG ; Quan-meng LIU ; Wen-jie FAN ; Li DING ; Yue-jiao LANG ; Yun-zhu WU ; Jian-peng YUAN ; Shen-ping YU ; Yi-yan LIU ; Yan CHEN
Korean Journal of Radiology 2025;26(5):400-410
Objective:
To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer.
Materials and Methods:
A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs.
Results:
All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027).
Conclusion
The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.
3.Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI
Xue-han WU ; Yu-tao QUE ; Xin-yue YANG ; Zi-qiang WEN ; Yu-ru MA ; Zhi-wen ZHANG ; Quan-meng LIU ; Wen-jie FAN ; Li DING ; Yue-jiao LANG ; Yun-zhu WU ; Jian-peng YUAN ; Shen-ping YU ; Yi-yan LIU ; Yan CHEN
Korean Journal of Radiology 2025;26(5):400-410
Objective:
To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer.
Materials and Methods:
A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs.
Results:
All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027).
Conclusion
The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.
4.Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI
Xue-han WU ; Yu-tao QUE ; Xin-yue YANG ; Zi-qiang WEN ; Yu-ru MA ; Zhi-wen ZHANG ; Quan-meng LIU ; Wen-jie FAN ; Li DING ; Yue-jiao LANG ; Yun-zhu WU ; Jian-peng YUAN ; Shen-ping YU ; Yi-yan LIU ; Yan CHEN
Korean Journal of Radiology 2025;26(5):400-410
Objective:
To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer.
Materials and Methods:
A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs.
Results:
All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027).
Conclusion
The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.
5.Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI
Xue-han WU ; Yu-tao QUE ; Xin-yue YANG ; Zi-qiang WEN ; Yu-ru MA ; Zhi-wen ZHANG ; Quan-meng LIU ; Wen-jie FAN ; Li DING ; Yue-jiao LANG ; Yun-zhu WU ; Jian-peng YUAN ; Shen-ping YU ; Yi-yan LIU ; Yan CHEN
Korean Journal of Radiology 2025;26(5):400-410
Objective:
To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer.
Materials and Methods:
A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs.
Results:
All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027).
Conclusion
The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.
6.Artificial intelligence in prostate cancer.
Wei LI ; Ruoyu HU ; Quan ZHANG ; Zhangsheng YU ; Longxin DENG ; Xinhao ZHU ; Yujia XIA ; Zijian SONG ; Alessia CIMADAMORE ; Fei CHEN ; Antonio LOPEZ-BELTRAN ; Rodolfo MONTIRONI ; Liang CHENG ; Rui CHEN
Chinese Medical Journal 2025;138(15):1769-1782
Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients' survival rates. The advancement of artificial intelligence (AI), particularly the utilization of deep learning (DL) algorithms, has brought about substantial progress in assisting the diagnosis, treatment, and prognosis prediction of PCa. The introduction of the foundation model has revolutionized the application of AI in medical treatment and facilitated its integration into clinical practice. This review emphasizes the clinical application of AI in PCa by discussing recent advancements from both pathological and imaging perspectives. Furthermore, it explores the current challenges faced by AI in clinical applications while also considering future developments, aiming to provide a valuable point of reference for the integration of AI and clinical applications.
Humans
;
Prostatic Neoplasms/diagnosis*
;
Male
;
Artificial Intelligence
;
Deep Learning
;
Prognosis
7.Burden and risk factors of stroke worldwide and in China: An analysis from the Global Burden of Disease Study 2021.
Zhengbao ZHU ; Mengyao SHI ; Quan YU ; Jiawen FEI ; Beiping SONG ; Xiaoli QIN ; Lulu SUN ; Yonghong ZHANG
Chinese Medical Journal 2025;138(20):2588-2595
BACKGROUND:
Stroke is the leading cause of death and long-term disability worldwide, including China. This study aimed to provide timely updates on stroke burden and stroke-related risk factors to help improve population-based prevention and control strategies.
METHODS:
Based on the Global Burden of Disease study 2021, incidence rate, prevalence rate, mortality rate, and disability-adjusted life-year (DALY) rate were used to estimate stroke burden trend from 1990 to 2021.
RESULTS:
In 2021, China had 4.1 million incident stroke cases, 26.3 million prevalent stroke cases, 2.6 million stroke related deaths, and 53.2 million stroke related DALYs, compared to 11.9 million incident stroke cases, 93.8 million prevalent stroke cases, 7.3 million stroke related deaths, and 160.5 million stroke-related DALYs worldwide. In 2021, the top six risk factors contributing to stroke burden were high blood pressure, air pollution, tobacco consumption, dietary risk factors, high low-density lipoprotein cholesterol, and high fasting plasma glucose, both in China and worldwide. From 1990 to 2021, China had significant increases of incidence rate, prevalence rate, mortality rate, and DALY rate for stroke, with estimates of 100.6 (95% uncertainty intervals [UI]: 87.2, 114.1)%, 102.9 (95% UI: 95.5, 110.9)%, 40.0 (95% UI: 14.9, 72.3)% and 15.7 (95% UI: -4.6, 41.2)%, respectively, while global incidence rate, prevalence rate, mortality rate and DALY rate for total stroke showed relatively moderate increases or even decreases, with estimates of 15.0 (95% UI: 12.1,18.0)%, 25.8 (95% UI: 23.7, 28.0)%, -2.6 (95% UI: -10.6, 5.5)%, and -10.7 (95% UI: -17.7, -3.6)%, respectively.
CONCLUSION
Stroke remains a huge disease burden worldwide and in China, and compared to the worldwide China has a significantly higher burden of stroke.
Humans
;
Stroke/etiology*
;
China/epidemiology*
;
Risk Factors
;
Global Burden of Disease
;
Disability-Adjusted Life Years
;
Prevalence
;
Incidence
;
Female
;
Quality-Adjusted Life Years
;
Male
8.Expression and function of CDYL-interacting protein MYH9 in mouse testis.
Huan-Tong GONG ; Yan-Mei QUAN ; Yun-Xia ZHANG ; Han-Fei ZHU ; Xiao-Yu XIA
National Journal of Andrology 2025;31(9):771-779
OBJECTIVE:
To identify the CDYL-interacting proteins in murine testis and investigate the mechanism of CDYL involved in spermatogenesis.
METHODS:
CDYL-interacting partners in testis were identified using co-immunoprecipitation coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Expression pattern of CDYL-interacting protein MYH9 was analyzed through immunohistochemistry (IHC), confocal immunofluorescence (IF) and Western blot (WB) in mouse testicular cells. The effect of the Cdyl conditional knockout (CdylcKO) in spermatogenic cell on Myh9 expression was quantified via RT-qPCR, WB and IF imaging in both spermatids and spermatozoa from cauda epididymides.
RESULTS:
Direct interaction between MYH9 and CDYL was confirmed in murine testis. During spermiogenesis, MYH9 exhibited co-localization with CDYL at the manchette structure, and binding to F-ACTIN, the component of manchette. In cauda epididymal spermatozoa, MYH9 signal concentrated on acrosomal region and continuously distributed along the tail length. Conditional deletion of Cdyl in spermatogenic cell resulted in the transcriptional downregulation of Myh9. In spermatids, CdylcKO led to reduced but retained MYH9 localization to the disorganized manchette structure. In spermatozoa from CdylcKO mice, abnormalities of MYH9 localization were observed, including attenuation of acrosomal signal and/or partial vanishment/enhancement of tail signal.
CONCLUSION
In murine spermatids, MYH9 protein is localized to the manchette structure, with its expression and subcellular distribution is affected by CDYL protein. CDYL-MYH9 interaction is essential for the spermiogenesis.
Animals
;
Male
;
Mice
;
Testis/metabolism*
;
Myosin Heavy Chains/metabolism*
;
Spermatogenesis
;
Mice, Knockout
9.Glucocorticoid Discontinuation in Patients with Rheumatoid Arthritis under Background of Chinese Medicine: Challenges and Potentials Coexist.
Chuan-Hui YAO ; Chi ZHANG ; Meng-Ge SONG ; Cong-Min XIA ; Tian CHANG ; Xie-Li MA ; Wei-Xiang LIU ; Zi-Xia LIU ; Jia-Meng LIU ; Xiao-Po TANG ; Ying LIU ; Jian LIU ; Jiang-Yun PENG ; Dong-Yi HE ; Qing-Chun HUANG ; Ming-Li GAO ; Jian-Ping YU ; Wei LIU ; Jian-Yong ZHANG ; Yue-Lan ZHU ; Xiu-Juan HOU ; Hai-Dong WANG ; Yong-Fei FANG ; Yue WANG ; Yin SU ; Xin-Ping TIAN ; Ai-Ping LYU ; Xun GONG ; Quan JIANG
Chinese journal of integrative medicine 2025;31(7):581-589
OBJECTIVE:
To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM).
METHODS:
This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis.
RESULTS:
Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings.
CONCLUSIONS
RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult
;
Aged
;
Female
;
Humans
;
Male
;
Middle Aged
;
Arthritis, Rheumatoid/drug therapy*
;
Glucocorticoids/therapeutic use*
;
Medicine, Chinese Traditional
;
Retrospective Studies
10.Autophagy in Oligodendrocyte Lineage Cells Controls Oligodendrocyte Numbers and Myelin Integrity in an Age-dependent Manner.
Hong CHEN ; Gang YANG ; De-En XU ; Yu-Tong DU ; Chao ZHU ; Hua HU ; Li LUO ; Lei FENG ; Wenhui HUANG ; Yan-Yun SUN ; Quan-Hong MA
Neuroscience Bulletin 2025;41(3):374-390
Oligodendrocyte lineage cells, including oligodendrocyte precursor cells (OPCs) and oligodendrocytes (OLs), are essential in establishing and maintaining brain circuits. Autophagy is a conserved process that keeps the quality of organelles and proteostasis. The role of autophagy in oligodendrocyte lineage cells remains unclear. The present study shows that autophagy is required to maintain the number of OPCs/OLs and myelin integrity during brain aging. Inactivation of autophagy in oligodendrocyte lineage cells increases the number of OPCs/OLs in the developing brain while exaggerating the loss of OPCs/OLs with brain aging. Inactivation of autophagy in oligodendrocyte lineage cells impairs the turnover of myelin basic protein (MBP). It causes MBP to accumulate in the cytoplasm as multimeric aggregates and fails to be incorporated into integral myelin, which is associated with attenuated endocytic recycling. Inactivation of autophagy in oligodendrocyte lineage cells impairs myelin integrity and causes demyelination. Thus, this study shows autophagy is required to maintain myelin quality during aging by controlling the turnover of myelin components.
Animals
;
Autophagy/physiology*
;
Oligodendroglia/metabolism*
;
Myelin Sheath/physiology*
;
Aging/pathology*
;
Myelin Basic Protein/metabolism*
;
Cell Lineage/physiology*
;
Mice
;
Oligodendrocyte Precursor Cells
;
Mice, Inbred C57BL
;
Brain/cytology*
;
Cells, Cultured
;
Cell Count

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