Zhen Wang, Renjie Lu, Fan Wei, Shilun Du, Mengruo Shen, Yong Lei
{"title":"A Cable-Driven Wearable Robot Design for Multi-Needle Positioning and Manipulation.","authors":"Zhen Wang, Renjie Lu, Fan Wei, Shilun Du, Mengruo Shen, Yong Lei","doi":"10.1002/rcs.70171","DOIUrl":"https://doi.org/10.1002/rcs.70171","url":null,"abstract":"<p><strong>Background: </strong>Multi-needle puncture is essential for clinical procedures such as multi-target biopsy. However, existing robotic systems face the challenge of providing simultaneous 6-DoF multi-needle control while maintaining CT/MRI compatibility.</p><p><strong>Methods: </strong>This paper presents a cable-driven wearable robot for the manipulation of multiple needles, which integrates a 4-DoF parallel module for needle positioning, a miniaturized 2-DoF puncture module for individual steering, and a dual-stiffness mounting module for rapid and stable installation. A hybrid cable-driven transmission combined with non-metallic materials ensures CT/MRI compatibility. A prototype was developed for the dual-needle case, and kinematic models were established for accurate closed-loop control.</p><p><strong>Results: </strong>The prototype demonstrated a static positioning accuracy below 0.5 mm, a maximum puncture force of 10.2 N, and a torque of 2.5 N <math> <semantics><mrow><mo>⋅</mo></mrow> <annotation>$cdot $</annotation></semantics> </math> mm.</p><p><strong>Conclusion: </strong>The proposed design is validated by a prototype capable of accurate multi-needle positioning and manipulation while maintaining full MRI/CT compatibility.</p>","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":"22 2","pages":"e70171"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147731030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yusheng Du, Ji Wang, Li Liu, Hongqin Ma, Ying Li, Wenxing Zhao
{"title":"Robotic Spleen-Preserving Distal Pancreatectomy: Perioperative Outcomes and Comparison of Two Energy Devices.","authors":"Yusheng Du, Ji Wang, Li Liu, Hongqin Ma, Ying Li, Wenxing Zhao","doi":"10.1002/rcs.70170","DOIUrl":"https://doi.org/10.1002/rcs.70170","url":null,"abstract":"<p><strong>Background: </strong>We evaluated the perioperative outcomes of robotic spleen-preserving distal pancreatectomy (RSPDP) and compared articulated monopolar curved scissors (R-MCS) with the harmonic scalpel (R-HS) as the primary energy device.</p><p><strong>Methods: </strong>We retrospectively reviewed consecutive single-centre RSPDPs (September 2020-August 2025) and compared baseline characteristics, intraoperative variables, and postoperative outcomes.</p><p><strong>Results: </strong>Sixty-nine patients were included (R-MCS, n = 31; R-HS, n = 38). Overall spleen preservation was 79.7%, with no between-group difference (80.6% vs. 78.9%, p = 0.852). Among spleen-preserved cases, Kimura completion was higher with R-MCS (88.0% vs. 66.7%, p = 0.032). Operative time and blood loss were comparable. Time to first flatus was shorter with R-MCS (3.2 ± 0.9 vs. 3.7 ± 0.7 days, p = 0.014). Overall complications occurred in 18.8%, including clinically relevant postoperative pancreatic fistula in 11.6%; no Clavien-Dindo grade ≥ IIIb complications or perioperative mortality occurred.</p><p><strong>Conclusion: </strong>RSPDP is safe and feasible. R-MCS may improve Kimura completion and modestly shorten the time to first flatus, pending further validation.</p>","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":"22 2","pages":"e70170"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147791260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yi Yang, Ling He, Donghua Zheng, Difu Wang, Yinhong An, Zhijun Yue
{"title":"Multidimensional Sensory Attention Enhancement Method for Lower Limb Rehabilitation Training.","authors":"Yi Yang, Ling He, Donghua Zheng, Difu Wang, Yinhong An, Zhijun Yue","doi":"10.1002/rcs.70168","DOIUrl":"https://doi.org/10.1002/rcs.70168","url":null,"abstract":"<p><strong>Background: </strong>Maintaining attention is essential for effective lower limb rehabilitation, yet repetitive exercises often cause focus loss. Existing methods lack real-time quantitative assessment, limiting adaptive training adjustments.</p><p><strong>Methods: </strong>This study developed an electroencephalogram (EEG)-based attention model integrating auditory, visual, and tactile stimuli. Event-related desynchronisation (ERD) and movement-related cortical potentials (MRCP) were extracted and fused using principal component analysis (PCA) to quantify attention on a 0-5 scale. EEG preprocessing included spatial correction, artefact removal, and band optimisation.</p><p><strong>Results: </strong>The proposed model effectively quantified attention states and identified optimal sensory combinations. Multisensory stimulation, especially red light with 60 dB sound and external force, significantly enhanced cortical engagement. The system achieved 91.7% sensitivity in detecting attention decline under interference conditions.</p><p><strong>Conclusions: </strong>The multidimensional sensory attention enhancement method enables dynamic attention monitoring and adaptive feedback in rehabilitation training, supporting future clinical applications and large-scale validation.</p>","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":"22 2","pages":"e70168"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147719133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ahmed Abdelsamad, Youssef Badie, Mohamed Elfakharany, Mohamed Elatrosh, Mohamed Elgohary, Eslam Elmaghraby, Florian Gebauer, Ralf Mike Langenbach, Khaled Mohamed
{"title":"Does Robotic Adrenalectomy Outperform Laparoscopic Approaches in Obese Patients? A Systematic Review and Subgroup Meta-Analysis of 1,107 Patients.","authors":"Ahmed Abdelsamad, Youssef Badie, Mohamed Elfakharany, Mohamed Elatrosh, Mohamed Elgohary, Eslam Elmaghraby, Florian Gebauer, Ralf Mike Langenbach, Khaled Mohamed","doi":"10.1002/rcs.70169","DOIUrl":"10.1002/rcs.70169","url":null,"abstract":"<p><strong>Background: </strong>Obesity poses technical challenges in adrenalectomy. Robotic adrenalectomy (RA) offers advantages over laparoscopic adrenalectomy (LA), but evidence in obese patients remains limited.</p><p><strong>Methods: </strong>A meta-analysis of comparative studies through 2025 assessed perioperative outcomes of RA versus LA, with subgroup analyses by body habitus (obese vs. non-obese) and surgical approach (lateral transabdominal [LT] vs. posterior retroperitoneal [PR]). Primary outcomes included operative time (OT), blood loss (EBL), hospital stay (LOHS), complications, conversion, and mortality. Study quality was evaluated using the Newcastle-Ottawa Scale, and certainty was assessed using the GRADE approach.</p><p><strong>Results: </strong>Eight studies (1107 patients) were included. RA was associated with reduced EBL (p < 0.001) and shorter LOHS (p < 0.001), with no other significant differences. Subgroup analysis showed shorter LOHS in non-obese LA patients (p = 0.03). PR showed a shorter LOHS (p = 0.001) compared with LT.</p><p><strong>Conclusions: </strong>RA provides perioperative benefits, particularly reduced blood loss and shorter hospital stay, without compromising safety.</p>","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":"22 2","pages":"e70169"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13094886/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147730942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Meng Fansheng, Duan Xingguang, Song Xinya, Fang Fengxinyun, Tian Jiexi, Wang Xujia, Chen Yu, Zhao Yuanli, Li Changsheng
{"title":"EA-Net: Edge Attention Network for Brain Tumour Segmentation in MRI.","authors":"Meng Fansheng, Duan Xingguang, Song Xinya, Fang Fengxinyun, Tian Jiexi, Wang Xujia, Chen Yu, Zhao Yuanli, Li Changsheng","doi":"10.1002/rcs.70163","DOIUrl":"https://doi.org/10.1002/rcs.70163","url":null,"abstract":"<p><strong>Background: </strong>Accurate brain tumour segmentation is crucial for clinical diagnosis and treatment planning, yet remains challenging due to the scale diversity of tumour regions, ambiguous boundary structures, and highly irregular shapes.</p><p><strong>Methods: </strong>We propose a novel Edge Attention Network that integrates two key components: a Multi-Scale Context Fusion Module to dynamically adjust receptive fields and capture multi-scale contextual information, and an Edge Segmentation Module that explicitly extracts tumour boundaries and injects them into the backbone as spatial attention to refine segmentation details, particularly at edges.</p><p><strong>Results: </strong>Experiments show that our model achieves Dice coefficients of 90.37% for Tumour Core (TC) and 88.91% for Whole Tumour (WT) on the BraTS2021 dataset. In cross-dataset generalisation tests on BTM-PVS, it maintains strong performance with 75.20% TC and 74.20% WT.</p><p><strong>Conclusions: </strong>The proposed method demonstrates superior segmentation accuracy and robust generalisation capability, highlighting its clinical potential and offering new insights for medical image segmentation.</p>","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":"22 2","pages":"e70163"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147663422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Explainable Lightweight Model Using Low-Rank and Convolutional Block Attention for Pancreatic Cancer Diagnosis.","authors":"Vishesh Tanwar, Bhisham Sharma, Dhirendra Prasad Yadav, Panos Liatsis","doi":"10.1002/rcs.70164","DOIUrl":"10.1002/rcs.70164","url":null,"abstract":"<p><strong>Background: </strong>Early and accurate pancreatic cancer (PC) detection remains a major clinical challenge.</p><p><strong>Methods: </strong>We introduce a novel hybrid deep learning framework for automated classification of CT images, which requires fewer computational resources while achieving high diagnostic performance. We integrated a lightweight MobileNetV3Small backbone with a convolutional block attention module and Low-rank Attention with Shared Efficient Representations (LASER) to enhance feature representation. Feature maps are projected via a 1 × 1 convolution into token sequences and processed through a transformer encoder to capture long-range dependencies. A parallel global average pooling extracts aggregated features, fused using a cross-type interaction (CTI) module.</p><p><strong>Results: </strong>The model was evaluated on 18,942 CT images and achieved 99.34% accuracy, AUC-ROC of 0.9996, Cohen's Kappa of 0.9897, and MCC of 0.9859, outperforming ResNet50, EfficientNetB0, and ViT variants with only 1.26 million parameters.</p><p><strong>Conclusions: </strong>Explainability analyses using Grad-CAM, Grad-CAM++, and attention visualisation suggest that the model focuses on clinically relevant regions.</p>","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":"22 2","pages":"e70164"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13091572/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147719164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ramazan Rajabi, Mehrnaz Aghanouri, Hamid Moradi, Alireza Mirbagheri
{"title":"Dynamic Modelling of the Surgery Arm in Sina<sub>flex</sub> Robotic Telesurgery System.","authors":"Ramazan Rajabi, Mehrnaz Aghanouri, Hamid Moradi, Alireza Mirbagheri","doi":"10.1002/rcs.70093","DOIUrl":"https://doi.org/10.1002/rcs.70093","url":null,"abstract":"<p><strong>Background: </strong>The use of robotic telesurgery has increased because of its high accuracy, fewer complications, and remote-control capability. To improve the accuracy of robotic arms in these systems, it is essential to have a precise dynamic model.</p><p><strong>Methods: </strong>In this study, we focus on the Sina<sub>flex</sub> robotic telesurgery system and develop a dynamic model for a novel slave robot. Our approach involves deriving and linearising dynamic equations, defining optimal excitation trajectories, and estimating dynamic parameters using least square optimisation. To investigate the parameters' identification accuracy, the joint torques predicted by the model were compared with those actually obtained from the experiments.</p><p><strong>Results: </strong>The results reveal that the method accurately predicts joint torques with the root mean square ( RMS) ranging from 0.58 to 1.48 Nm.</p><p><strong>Conclusions: </strong>Using the proposed method in this paper for identifying the robot dynamic parameters leads to more accurate results for robots with complex mechanisms.</p>","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":"21 4","pages":"e70093"},"PeriodicalIF":0.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144801190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Man-Ling Wang, Bor-Shiuan Shyr, Shih-Chin Chen, Shin-E Wang, Y. Shyr, B. Shyr
{"title":"Comparison of robotic and open central pancreatectomy.","authors":"Man-Ling Wang, Bor-Shiuan Shyr, Shih-Chin Chen, Shin-E Wang, Y. Shyr, B. Shyr","doi":"10.14701/ahbps.2023s1.bp-pp-4-7","DOIUrl":"https://doi.org/10.14701/ahbps.2023s1.bp-pp-4-7","url":null,"abstract":"BACKGROUND\u0000Central pancreatectomy (CP) is an ideal parenchyma-sparing procedure. The experience of r robotic central pancreatectomy (RCP) is very limited.\u0000\u0000\u0000MATERIALS AND METHODS\u0000Patients undergoing CP were included. Comparisons were made between RCP and open central pancreatectomy (OCP) groups.\u0000\u0000\u0000RESULTS\u0000The most common lesion in patients undergoing CP was serous cystadenoma (35.5%). The median operation time was 4.2 h for RCP versus 5.5 h for OCP. The median blood loss was significantly lower in RCP, 20 c.c. versus 170 c.c., p = 0.001. Postoperative pancreatic fistula occurred in 19.4% of all patients, with 22.1% in RCP and 15.4% in OCP. There was no significant difference regarding other surgical complications between the RCP and OCP groups. Only one patient in the OCP group developed de novo diabetes mellitus (DM), and no steatorrhoea/diarrhoea occurred after either RCP or OCP.\u0000\u0000\u0000CONCLUSIONS\u0000RCP is feasible and safe without compromising surgical outcomes and pancreatic functions.","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":"46 1","pages":"e2562"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80577274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Antoniou, A. Georgiou, N. Evripidou, C. Damianou
{"title":"Full coverage path planning algorithm for MRgFUS therapy","authors":"A. Antoniou, A. Georgiou, N. Evripidou, C. Damianou","doi":"10.1002/rcs.2389","DOIUrl":"https://doi.org/10.1002/rcs.2389","url":null,"abstract":"High‐quality methods for Magnetic Resonance guided Focussed Ultrasound (MRgFUS) therapy planning are needed for safe and efficient clinical practices. Herein, an algorithm for full coverage path planning based on preoperative MR images is presented.","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90881617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Erica Padovan, Giorgia Marullo, L. Tanzi, P. Piazzolla, Sandro Moos, F. Porpiglia, E. Vezzetti
{"title":"A deep learning framework for real‐time 3D model registration in robot‐assisted laparoscopic surgery","authors":"Erica Padovan, Giorgia Marullo, L. Tanzi, P. Piazzolla, Sandro Moos, F. Porpiglia, E. Vezzetti","doi":"10.1002/rcs.2387","DOIUrl":"https://doi.org/10.1002/rcs.2387","url":null,"abstract":"The current study presents a deep learning framework to determine, in real‐time, position and rotation of a target organ from an endoscopic video. These inferred data are used to overlay the 3D model of patient's organ over its real counterpart. The resulting augmented video flow is streamed back to the surgeon as a support during laparoscopic robot‐assisted procedures.","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78535961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}