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ISSN: 2957-5443
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Editor-in-Chief: Lize XIONG
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Volume 3, Issue 4
Research progress on the mechanisms of traditional Chinese medicine extracts in improving acute lung injury in sepsis

Review Article |Published on: 31 December 2025

[Perioperative Precision Medicine] 2025; 3 (4): 122-133

DOI: https://doi.org/10.61189/579841iexakc
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Limb nerve block localization using deep learning-driven segmentation: A review

Jiaxun Jiang1, Miao Zhou2, Liangqing Lin3, Haipo Cui1, Long Liu1, Jiaen Wu1, Zhaopeng Zhou1


1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China. 2Jiangsu Cancer Hospital, Nanjing 213164, Jiangsu Province, China. 3Anesthesiology, The First Hospital of Putian, Putian 351100, Fujian Province, China.


Address correspondence to: Haipo Cui, School of Health Science and Engineering, University of Shanghai for Science and Technology, No. 516 Jungong Road, Yangpu District, Shanghai 200093, China. E-mail: h_b_cui@163.com.


DOI: https://doi.org/10.61189/295165xbmhth


Received April 1, 2025; Accepted May 12, 2025; Published December 31, 2025


Highlights

● Deep learning-powered nerve block segmentation significantly contributes to optimized perioperative pain management by enhancing the precision and safety of regional anesthesia. 

● Advanced architectures, particularly U-Net variants, dominate peripheral nerve block segmentation, offering high precision and adaptability to medical imaging challenges. 

● Deep learning enhances clinical workflows by improving segmentation accuracy and efficiency in upper and lower limb nerve blocks, thereby supporting procedural success. 

● Future efforts will focus on improving model robustness and generalizability to address limitations such as data variability and limited adaptability, facilitating broader clinical adoption.

Review Article |Published on: 31 December 2025

[Perioperative Precision Medicine] 2025; 3 (4): 134-151

DOI: https://doi.org/10.61189/295165xbmhth
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A review of multimodal medical image fusion: Developments in traditional, model-based and learning-based approaches

Zhaopeng Zhou1, Jiaen Wu1, Jiaxun Jiang1, Miao Zhou2, Wenhui Guo3, Yongchu Hu4


1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China. 2Jiangsu Cancer Hospital, Nanjing 213164, Jiangsu Province, China. 3The Department of Anesthesiology,  Naval Medical University, Shanghai 200433, China. 4The Department of Anesthesiology, Second Affiliated Hospital of Navy Medical University, Shanghai 200003, China.


Address correspondence to: Yongchu Hu, The Department of Anesthesiology, Second Affiliated Hospital of Navy Medical University, No. 415 Fengyang Road, Shanghai 200003, China. E-mail: liuyang1268@smmu.edu.cn.


DOI: https://doi.org/10.61189/617079irudnn


Received April 10, 2025; Accepted July 11, 2025; Published December 31, 2025


Highlights

● Significant Advantages of Multimodal Fusion: Multimodal medical image fusion enhances diagnostic accuracy and medical value by integrating multi-source data such as CT, MRI, and PET images, outperforming singlemodality technologies. 

● Benefits of Deep Learning: Deep learning technologies significantly advance multimodal medical image fusion, enabling more efficient and accurate fusion results. 

● Perioperative clinical significance: Multimodal image fusion can provide important support for perioperative preoperative planning, intraoperative guidance, and postoperative evaluation, thereby improving surgical accuracy and patient safety. 

● Future Research Directions: Future research should focus on improving model interpretability, enhancing modality alignment, and achieving breakthroughs in practicality, applicability, and efficiency.

Review Article |Published on: 31 December 2025

[Perioperative Precision Medicine] 2025; 3 (4): 152-167

DOI: https://doi.org/10.61189/617079irudnn
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Research progress of bone marrow mesenchymal stem cells in the treatment of acute liver failure

Huan Li1,2, Xiaoyu Tang1,2, Jiameng Liu1,2, Wanning Li1,2, Xin Niu1,2, Xingchen Yue1,2, Shangping Fang1,2


1School of Anesthesiology, Wannan Medical College, Wuhu 241002, Anhui Province, China. 2Anesthesia Laboratory and Training Center, Wannan Medical College, Wuhu 241002, Anhui Province, China.


Address correspondence to: Shangping Fang, Anaesthesiology Experimental Training Center, College of Anesthesiology, Wannan Medical College, No. 22 Wenchang West Road, Yijiang District, Wuhu 241002, Anhui Province, China. Tel: +86-19855362767. E-mail: fangshangping0@163.com.


Acknowledgement: This work was supported by Key Project Research Fund of Wannan Medical College (WK2022Z10); Anhui Province College Student Innovation and Entrepreneurship Training Program Project (S202410368031); Anhui Province College Student Innovation Training Program Project (S202510368032).


DOI: https://doi.org/10.61189/167468gjipte


Received April 15, 2025; Accepted July 25, 2025; Published December 31, 2025


Highlights

● This review focuses on the research of bone marrow mesenchymal stem cells (BM-MSCs) in treating acute liver  failure (ALF). 

● BM-MSCs are a heterogeneous subset of stromal stem cells that can be isolated from various adult tissues. 

● BM-MSCs have the ability to migrate toward damaged tissues and differentiate into hepatocytes. They effectively suppress pro-inflammatory cytokine release and promote hepatocyte proliferation. 

● BM-MSCs are a promising target for clinical treatment of acute liver failure. 

● BM-MSCs provide a new therapeutic direction for patients with acute liver failure during the perioperative period.

Review Article |Published on: 31 December 2025

[Perioperative Precision Medicine] 2025; 3 (4): 168-175

DOI: https://doi.org/10.61189/167468gjipte
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The role and research progress of ferroptosis in myocardial injury in sepsis

Jiayin Wang1,4,5,*, Sixu Chen2,5,*, Weiqi Lin3,4,*, Xinyi Xie1,5, Yutong Sun3,5, Qin Zhang3,5, Qixiang Xu1,4,5, Cuifeng Zhang2,5


1School of Pharmacology, Wannan Medical College, Wuhu, Anhui, China. 2School of Anesthesiology, Wannan  Medical College, Wuhu, Anhui, China. 3School of Clinical Medicine, Wannan Medical College, Wuhu, Anhui, China.  4Anesthesia Laboratory and Training Center, Wannan Medical College, Wuhu, Anhui, China. 5Wuhu Perioperative  Monitoring and Prognostic Technology Research and Development Center, Wannan Medical College, Wuhu, Anhui,  China. 

* The authors contribute equally and co-first authors.


Address correspondence to: Qixiang Xu, School of Pharmacology, Wannan Medical College, No. 22  Wenchang West Road, Yijiang District, Wuhu 241002, Anhui, China. Tel: +86-18355305112. E-mail:  xuqixiang@wnmc.edu.cn. Cuifeng Zhang, School of Anesthesiology, Wannan Medical College, No. 22  Wenchang West Road, Yijiang District, Wuhu 241002, Anhui, China. Tel: +86-15551257181. E-mail:  zhangcuifeng@wnmc.edu.cn.


Acknowledgement: This work was supported by The Foundation of Wannan Medical College (WK2023ZQNZ08), National university innovation and entrepreneurship training program (202310368014, 202310368049, 202410368014), Anhui Province university innovation and entrepreneurship training program (S202310368095, S202310368087, S202410368004, S202410368009).


DOI: https://doi.org/10.61189/691939hefazb


Received March 2, 2025; Accepted June 4, 2025; Published December 31, 2025


Highlights

● A comprehensive review of the role of ferroptosis in sepsis-induced myocardial injury is presented. 

● The mechanisms of ferroptosis and recent advancements in its involvement in sepsis-induced myocardial injury are discussed. 

● Perioperative whole-process risks may induce sepsis, activate ferroptosis and raise myocardial injury risk, while integrating ferroptosis into management can reduce this risk.

Review Article |Published on: 31 December 2025

[Perioperative Precision Medicine] 2025; 3 (4): 176-185

DOI: https://doi.org/10.61189/691939hefazb
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Diagnostic performance of deep learning for brachial plexus ultrasound: A systematic review

Jiaen Wu1, Jiaxun Jiang1, Zhaopeng Zhou1, Miao Zhou2, Liangqing Lin3, Jinjing Wu1, Haipo Cui1


1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China. 2Jiangsu Cancer Hospital, Changzhou 213164, Jiangsu Province, China. 3Department of Anesthesiology, The First Hospital of Putian, Putian 351100, Fujian, China.


Address correspondence to: Haipo Cui, School of Health Science and Engineering, University of Shanghai for Science and Technology, No. 516 Jungong Road, Yangpu District, Shanghai 200093, China. E-mail: h_b_cui@163.com.


DOI: https://doi.org/10.61189/251934gxqfic


Received April 9, 2025; Accepted August 13, 2025; Published December 31, 2025


Highlights

● This study compares deep learning methods for brachial plexus ultrasound segmentation, demonstrating improved segmentation efficiency and reduced learning difficulty, which may enhance perioperative regional anesthesia planning and safety. 

● U-Net is favored for brachial plexus segmentation due to its enhanced ability to capture contextual features through increased channel utilization. 

● Available public brachial plexus datasets are summarized, offering valuable resources for future research and perioperative ultrasound applications.

Review Article |Published on: 31 December 2025

[Perioperative Precision Medicine] 2025; 3 (4): 186-199

DOI: https://doi.org/10.61189/251934gxqfic
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Application of 0.15% ropivacaine in labor analgesia for primiparous women with severe pain

Research Article |Published on: 31 December 2025

[Perioperative Precision Medicine] 2025; 3 (4): 200-206

DOI: https://doi.org/10.61189/924159jtzdps
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Research progress on pharmacological effects and mechanisms of cycloastragenol

Weiqi Lin1,2,3*, Qin Zhang1,3* , Sixu Chen2,4*, Xinyi Xie3,5 , Jiayin Wang3,5, Yutong Sun1,3, Qixiang Xu3,5,  Cuifeng Zhang2,3,4


1School of Clinical Medicine, Wannan Medical College, Wuhu 241002, Anhui, China. 2Anesthesia Laboratory and Training Center, Wannan Medical College, Wuhu 241002, Anhui, China. 3Wuhu Perioperative Monitoring and Prognostic Technology Research and Development Center, Wannan Medical College, Wuhu 241002, Anhui, China. 4School of Anesthesiology, Wannan Medical College, Wuhu 241002, Anhui, China. 5School of Pharmacology, Wannan Medical College, Wuhu 241002, Anhui, China. 


*The authors contribute equally.


Address correspondence to: Qixiang Xu, School of Pharmacology, Wannan Medical College, No.22 Wenchang West Road, Yijiang District, Wuhu 241002, Anhui Province, China. Tel: +86-18355305112. E-mail: xuqixiang@wnmc.edu.cn. Cuifeng Zhang, School of Anesthesiology, Wannan Medical College, No.22 Wenchang West Road, Yijiang District, Wuhu 241002, Anhui Province, China. Tel: +86-15551257181. E-mail: zhangcuifeng@wnmc.edu.cn.


Acknowledgement: This work was supported by the Natural Science Foundation Of The Higher Education Insti tutions Of Anhui Province (2024AH051958), the Foundation Of Wannan Medical College (WK2023ZQNZ08), the National University Innovation And Entrepreneurship Training Program (202310368014, 202310368049, 202410368014), the Anhui Province University Innovation And Entrepreneurship Training Program (S202310368087, S202410368004, S202410368009), the Wannan Medical College Undergraduate Research Fund Project (WK2024XS01).


DOI: https://doi.org/10.61189/313450skrqzv


Received January 21, 2025; Accepted April 24, 2025; Published December 31, 2025


Highlights

● Cycloastragenol exhibits anti-aging, anti-cancer, and anti-fibrosis effects. 

● Although cycloastragenol shows innovative therapeutic potential, further clinical trials are essential to confirm its clinical applicability.  

● Cycloastragenol offers innovative therapeutic avenues for enhancing surgical recovery.

Review Article |Published on: 31 December 2025

[Perioperative Precision Medicine] 2025; 3 (4): 207-215

DOI: https://doi.org/10.61189/313450skrqzv
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Tailoring perioperative analgesia: Selecting ketamine or dexmedetomidine based on patient-specific factors

Edward Sun1, Meikun Wang2, Zongda He3, Mingyue Li4, Jingping Wang5


1University of British Columbia, Vancouver, Canada BC V6T 1Z4. 2Department of Anesthesia, First Hospital, Jilin University, Changchun 130021, Jilin Province, China.3King' s College, London, UK WC2R 2LS. 4Department of Anesthesia, Second Hospital, Jilin University, Changchun 130021, Jilin Province, China. 5Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston 02114, MA,  USA.


Address correspondence to: Jingping Wang, Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, 55 Fruit Street, Boston 02114, MA, USA. Tel: +86-617-643- 2729. E-mail: jwang23@MGH.Harvard.edu.


DOI: https://doi.org/10.61189/577707zkzsmw


Received July 5, 2025; Accepted September 5, 2025; Published December 31, 2025


Highlights

● Ketamine and dexmedetomidine offer effective non-opioid perioperative analgesia, each with distinct cardiovas-cular, hepatic, and neurological profiles. 

● Dexmedetomidine provides stable sedation and potential neuroprotection, making it particularly suitable for pa-tients with hepatic dysfunction and those undergoing neurosurgery. 

● Ketamine helps maintain hemodynamic stability and possesses anti-inflammatory and anti-depressant proper-ties, making it beneficial for high-risk or unstable patients. 

● Agent selection should be tailored to individual comorbidities, with combination therapy offering potential syner-gistic advantages.

Review Article |Published on: 31 December 2025

[Perioperative Precision Medicine] 2025; 3 (4): 216-225.

DOI: https://doi.org/10.61189/577707zkzsmw
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