1.Advances in perioperative nutritional management for patients with esophageal cancer
Zuyu ZHANG ; Bo YANG ; Rong NIU ; Jijun XUE ; Jian CHEN ; Dong LI ; Wentao ZHAO ; Wenfeng HAN ; Yue BAI
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2026;33(01):157-162
Esophageal cancer is a prevalent malignant tumor of the digestive tract in China, and radical surgery remains the cornerstone of its comprehensive treatment. However, multifactorial challenges such as postoperative gastrointestinal tract reconstruction, traumatic stress, and tumor-related metabolic disturbances render esophageal cancer patients highly susceptible to malnutrition. Perioperative nutritional support therapy plays a crucial role in enhancing surgical safety, improving clinical outcomes, and elevating patients' quality of life by regulating metabolic homeostasis, preserving organ function, and optimizing the immune microenvironment. This article reviews the mechanisms underlying malnutrition in esophageal cancer, methods for nutritional status assessment, and precision intervention pathways based on multi-omics evaluations. The aim is to strengthen clinicians' awareness of standardized perioperative nutritional management for esophageal cancer patients and promote its clinical implementation, thereby facilitating postoperative recovery and improving long-term quality of life.
2.Expert consensus on the application of artificial intelligence in lung cancer screening, diagnosis, and treatment (2026 edition)
Wenzhao ZHONG ; Haibo WANG ; Yi HU ; Hao ZHANG ; Jigang DAI ; Junqiang FAN ; Guibin QIAO ; Fan YANG ; Jian HU ; Fengwei TAN ; Xuening YANG ; Qiang PU ; Zihao CHEN ; Hongxia TIAN ; Lunxu LIU ; Hecheng LI ; Xiaolong YAN ; Zongyang YU ; Zhenbin QIU ; Yihua SUN ; Jing HU ; Yuhang SHI ; Zhifei GUO ; Peng ZHANG ; Kezhong CHEN ; Shugeng GAO ; Yilong WU
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2026;33(06):848-856
With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung 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.Effects of estrogen signaling on T cell recruitment and polarization in inflamed skeletal muscle with acute myoinjury
Zi-Wei ZHAO ; Xiao-Ting JIAN ; Jun-Yi XIE ; Jing-Wen HUANG ; Yang-Yang LI ; Qi-Sen WANG ; Zhao-Hong LIAO ; Hua LIAO
Acta Anatomica Sinica 2025;56(6):688-696
Objective To investigate the effects of estrogen signaling on T-cell recruitment and polarization in acutely injured skeletal muscle.Methods One hundred C57BL/6 male mice,one hundred and eighty C57BL/6 female mice were selected.Twenty-five female mice were ovariectomized(OVX)and 10 male mice were taken as the sham-operated(sham).Then,cardiotoxin(CTX)induced tibialis anterior(TA)injury for preparing mice myoinjury model.Subcutaneous injection of 17β-estradiol(E2)or estrogen receptor antagonist 4-hydroxytamoxifen(4-OHT)was performed.A total of 140 mice(70 males and 70 females)were divided into four group including:PBS-male,CTX-male,PBS-female,and CTX-female.Serum estradiol(E2)levels were measured by ELISA,and muscle injury models were validated via HE staining.Subsequently,20 male and 20 female mice were selected for immunofluorescence(IF)and Real-time PCR to assess estrogen receptors(ER)expression in injured muscle tissue.Further,10 male and 40 female mice were allocated into five experimental groups,including CTX,CTX+E2,CTX+4-OHT,CTX+OVX,CTX+sham.HE staining and IF were performed to evaluate inflammatory infiltration in the injured muscle.Additionally,50 female mice were divided into CTX and CTX+OVX groups,and IF combined with flow cytometry were used to analyze T-cell phenotypes and muscle fiber regeneration in the injured muscle.Results In vivo,serum E2 and myofiber ERβ increased post-injury in mice of both sexes,significantly higher in females.Compared to the control group,E2 alleviated inflammation,OVX exacerbated inflammation,increased CD4+T-cell infiltration,elevated T helper 1 cell(Th1)response,decreased regulatory T cells(Tregs),impaired regeneration.In vitro,IFN-γ/LPS significantly upregulated ERβ in myotubes.Conclusion Estrogen signaling critically regulates muscle inflammation.Estrogen deficiency(OVX)delays repair of skeletal muscle by promoting Th1 response and suppressing Tregs function.
7.Expert consensus on apical microsurgery.
Hanguo WANG ; Xin XU ; Zhuan BIAN ; Jingping LIANG ; Zhi CHEN ; Benxiang HOU ; Lihong QIU ; Wenxia CHEN ; Xi WEI ; Kaijin HU ; Qintao WANG ; Zuhua WANG ; Jiyao LI ; Dingming HUANG ; Xiaoyan WANG ; Zhengwei HUANG ; Liuyan MENG ; Chen ZHANG ; Fangfang XIE ; Di YANG ; Jinhua YU ; Jin ZHAO ; Yihuai PAN ; Shuang PAN ; Deqin YANG ; Weidong NIU ; Qi ZHANG ; Shuli DENG ; Jingzhi MA ; Xiuping MENG ; Jian YANG ; Jiayuan WU ; Yi DU ; Junqi LING ; Lin YUE ; Xuedong ZHOU ; Qing YU
International Journal of Oral Science 2025;17(1):2-2
Apical microsurgery is accurate and minimally invasive, produces few complications, and has a success rate of more than 90%. However, due to the lack of awareness and understanding of apical microsurgery by dental general practitioners and even endodontists, many clinical problems remain to be overcome. The consensus has gathered well-known domestic experts to hold a series of special discussions and reached the consensus. This document specifies the indications, contraindications, preoperative preparations, operational procedures, complication prevention measures, and efficacy evaluation of apical microsurgery and is applicable to dentists who perform apical microsurgery after systematic training.
Microsurgery/standards*
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Humans
;
Apicoectomy
;
Contraindications, Procedure
;
Tooth Apex/diagnostic imaging*
;
Postoperative Complications/prevention & control*
;
Consensus
;
Treatment Outcome
8.Expert consensus on pulpotomy in the management of mature permanent teeth with pulpitis.
Lu ZHANG ; Chen LIN ; Zhuo CHEN ; Lin YUE ; Qing YU ; Benxiang HOU ; Junqi LING ; Jingping LIANG ; Xi WEI ; Wenxia CHEN ; Lihong QIU ; Jiyao LI ; Yumei NIU ; Zhengmei LIN ; Lei CHENG ; Wenxi HE ; Xiaoyan WANG ; Dingming HUANG ; Zhengwei HUANG ; Weidong NIU ; Qi ZHANG ; Chen ZHANG ; Deqin YANG ; Jinhua YU ; Jin ZHAO ; Yihuai PAN ; Jingzhi MA ; Shuli DENG ; Xiaoli XIE ; Xiuping MENG ; Jian YANG ; Xuedong ZHOU ; Zhi CHEN
International Journal of Oral Science 2025;17(1):4-4
Pulpotomy, which belongs to vital pulp therapy, has become a strategy for managing pulpitis in recent decades. This minimally invasive treatment reflects the recognition of preserving healthy dental pulp and optimizing long-term patient-centered outcomes. Pulpotomy is categorized into partial pulpotomy (PP), the removal of a partial segment of the coronal pulp tissue, and full pulpotomy (FP), the removal of whole coronal pulp, which is followed by applying the biomaterials onto the remaining pulp tissue and ultimately restoring the tooth. Procedural decisions for the amount of pulp tissue removal or retention depend on the diagnostic of pulp vitality, the overall treatment plan, the patient's general health status, and pulp inflammation reassessment during operation. This statement represents the consensus of an expert committee convened by the Society of Cariology and Endodontics, Chinese Stomatological Association. It addresses the current evidence to support the application of pulpotomy as a potential alternative to root canal treatment (RCT) on mature permanent teeth with pulpitis from a biological basis, the development of capping biomaterial, and the diagnostic considerations to evidence-based medicine. This expert statement intends to provide a clinical protocol of pulpotomy, which facilitates practitioners in choosing the optimal procedure and increasing their confidence in this rapidly evolving field.
Humans
;
Calcium Compounds/therapeutic use*
;
Consensus
;
Dental Pulp
;
Dentition, Permanent
;
Oxides/therapeutic use*
;
Pulpitis/therapy*
;
Pulpotomy/standards*
9.Expert consensus on intentional tooth replantation.
Zhengmei LIN ; Dingming HUANG ; Shuheng HUANG ; Zhi CHEN ; Qing YU ; Benxiang HOU ; Lihong QIU ; Wenxia CHEN ; Jiyao LI ; Xiaoyan WANG ; Zhengwei HUANG ; Jinhua YU ; Jin ZHAO ; Yihuai PAN ; Shuang PAN ; Deqin YANG ; Weidong NIU ; Qi ZHANG ; Shuli DENG ; Jingzhi MA ; Xiuping MENG ; Jian YANG ; Jiayuan WU ; Lan ZHANG ; Jin ZHANG ; Xiaoli XIE ; Jinpu CHU ; Kehua QUE ; Xuejun GE ; Xiaojing HUANG ; Zhe MA ; Lin YUE ; Xuedong ZHOU ; Junqi LING
International Journal of Oral Science 2025;17(1):16-16
Intentional tooth replantation (ITR) is an advanced treatment modality and the procedure of last resort for preserving teeth with inaccessible endodontic or resorptive lesions. ITR is defined as the deliberate extraction of a tooth; evaluation of the root surface, endodontic manipulation, and repair; and placement of the tooth back into its original socket. Case reports, case series, cohort studies, and randomized controlled trials have demonstrated the efficacy of ITR in the retention of natural teeth that are untreatable or difficult to manage with root canal treatment or endodontic microsurgery. However, variations in clinical protocols for ITR exist due to the empirical nature of the original protocols and rapid advancements in the field of oral biology and dental materials. This heterogeneity in protocols may cause confusion among dental practitioners; therefore, guidelines and considerations for ITR should be explicated. This expert consensus discusses the biological foundation of ITR, the available clinical protocols and current status of ITR in treating teeth with refractory apical periodontitis or anatomical aberration, and the main complications of this treatment, aiming to refine the clinical management of ITR in accordance with the progress of basic research and clinical studies; the findings suggest that ITR may become a more consistent evidence-based option in dental treatment.
Humans
;
Tooth Replantation/methods*
;
Consensus
;
Periapical Periodontitis/surgery*
10.Expert consensus on peri-implant keratinized mucosa augmentation at second-stage surgery.
Shiwen ZHANG ; Rui SHENG ; Zhen FAN ; Fang WANG ; Ping DI ; Junyu SHI ; Duohong ZOU ; Dehua LI ; Yufeng ZHANG ; Zhuofan CHEN ; Guoli YANG ; Wei GENG ; Lin WANG ; Jian ZHANG ; Yuanding HUANG ; Baohong ZHAO ; Chunbo TANG ; Dong WU ; Shulan XU ; Cheng YANG ; Yongbin MOU ; Jiacai HE ; Xingmei YANG ; Zhen TAN ; Xiaoxiao CAI ; Jiang CHEN ; Hongchang LAI ; Zuolin WANG ; Quan YUAN
International Journal of Oral Science 2025;17(1):51-51
Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans
;
Consensus
;
Dental Implants
;
Mouth Mucosa/surgery*
;
Keratins

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