Reducing the annotation burden is an active and meaningful area of artificial intelligence (AI) research.
Methods
Multiple datasets for the segmentation of two landmarks were constructed based on 41 257 labelled images and 6 different microsurgical scenarios. These datasets were trained using the multi-stage transfer learning (TL) methodology.
Results
The multi-stage TL enhanced segmentation performance over baseline (mIOU 0.6892 vs. 0.8869). Besides, Convolutional Neural Networks (CNNs) achieved a robust performance (mIOU 0.8917 vs. 0.8603) even when the training dataset size was reduced from 90% (30 078 images) to 10% (3342 images). When directly applying the weight from one certain surgical scenario to recognise the same target in images of other scenarios without training, CNNs still obtained an optimal mIOU of 0.6190 ± 0.0789.
Conclusions
Model performance can be improved with TL in datasets with reduced size and increased complexity. It is feasible for data-based domain adaptation among different microsurgical fields.
{"title":"Transfer learning for anatomical structure segmentation in otorhinolaryngology microsurgery","authors":"Xin Ding, Yu Huang, Yang Zhao, Xu Tian, Guodong Feng, Zhiqiang Gao","doi":"10.1002/rcs.2634","DOIUrl":"10.1002/rcs.2634","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Reducing the annotation burden is an active and meaningful area of artificial intelligence (AI) research.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Multiple datasets for the segmentation of two landmarks were constructed based on 41 257 labelled images and 6 different microsurgical scenarios. These datasets were trained using the multi-stage transfer learning (TL) methodology.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The multi-stage TL enhanced segmentation performance over baseline (mIOU 0.6892 vs. 0.8869). Besides, Convolutional Neural Networks (CNNs) achieved a robust performance (mIOU 0.8917 vs. 0.8603) even when the training dataset size was reduced from 90% (30 078 images) to 10% (3342 images). When directly applying the weight from one certain surgical scenario to recognise the same target in images of other scenarios without training, CNNs still obtained an optimal mIOU of 0.6190 ± 0.0789.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Model performance can be improved with TL in datasets with reduced size and increased complexity. It is feasible for data-based domain adaptation among different microsurgical fields.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50311,"journal":{"name":"International Journal of Medical Robotics and Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141066207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Luis E. Delgadillo Chabolla, Linda A. Alpuing Radilla, Tamisa Koythong, Sowmya Sunkara, Yamely Mendez, Qianqing Wang, Xiaoming Guan
Background
To assess the feasibility of use of indocyanine green (ICG) in identifying and minimising urinary tract injury during surgical resection of endometriosis through robotic transvaginal natural orifice transluminal endoscopy surgery (RvNOTES).
Methods
We conducted a retrospective case series in two academic tertiary care hospitals. We examined 53 patients who underwent RvNOTES hysterectomy with planned endometriosis resection.
Results
The study involved 53 patients undergoing RvNOTES with ICG fluorescence for endometriosis resection. Mean patient age was 37.98 ± 6.65 years. Operative time averaged 181.32 ± 53.94 min, with estimated blood loss at 45.57 ± 33.62 mL. Postoperative stay averaged 0.23 ± 0.47 days. No ICG-related complications occurred.
Conclusion
No complications occurred with ICG fluorescence in RvNOTES. It appears to be a safe option for ureteral localisation and preservation. ICG fluorescence is widely used in diverse medical specialities for identifying ureters during complex surgeries. Larger studies are needed to firmly establish its advantages in intraoperative ureteral visualisation during RvNOTES for deep infiltrative endometriosis.
{"title":"Exploring the feasibility of indocyanine green fluorescence for intraoperative ureteral visualisation in robotic transvaginal natural orifice transluminal endoscopy surgery during endometriosis resection","authors":"Luis E. Delgadillo Chabolla, Linda A. Alpuing Radilla, Tamisa Koythong, Sowmya Sunkara, Yamely Mendez, Qianqing Wang, Xiaoming Guan","doi":"10.1002/rcs.2636","DOIUrl":"https://doi.org/10.1002/rcs.2636","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>To assess the feasibility of use of indocyanine green (ICG) in identifying and minimising urinary tract injury during surgical resection of endometriosis through robotic transvaginal natural orifice transluminal endoscopy surgery (RvNOTES).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We conducted a retrospective case series in two academic tertiary care hospitals. We examined 53 patients who underwent RvNOTES hysterectomy with planned endometriosis resection.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The study involved 53 patients undergoing RvNOTES with ICG fluorescence for endometriosis resection. Mean patient age was 37.98 ± 6.65 years. Operative time averaged 181.32 ± 53.94 min, with estimated blood loss at 45.57 ± 33.62 mL. Postoperative stay averaged 0.23 ± 0.47 days. No ICG-related complications occurred.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>No complications occurred with ICG fluorescence in RvNOTES. It appears to be a safe option for ureteral localisation and preservation. ICG fluorescence is widely used in diverse medical specialities for identifying ureters during complex surgeries. Larger studies are needed to firmly establish its advantages in intraoperative ureteral visualisation during RvNOTES for deep infiltrative endometriosis.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50311,"journal":{"name":"International Journal of Medical Robotics and Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140952999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Peng Yan, Xudong Duan, Yutian Lei, Fangze Xing, Ruomu Cao, Sen Luo, Yang Chen, Zeyu Liu, Kunzheng Wang, Pei Yang, Run Tian
Background
Rotational alignment in total knee arthroplasty (TKA) is a crucial technical point that needs attention. We conducted a retrospective study to investigate whether a new robot-assisted TKA (RA-TKA) could improve the accuracy of rotational alignment and whether rotational alignment affects postoperative pain and functional evaluation of the knee.
Methods
A total of 136 consecutive patients who underwent TKA were included in this study. Half of the patients underwent RA-TKA and the other half underwent conventional TKA (CON-TKA) by the same group of surgeons. Collect the relevant parameters.
Results
The postoperative femoral rotation angle (FRA) was −0.72 ± 2.59° in the robot-assisted group and 1.13 ± 2.73° in the conventional group, and were statistically significantly different (p < 0.001).
Conclusion
This study provides preliminary evidence that the RA-TKA provides more precise control of FRA than CON-TKA, and verifies that tibial rotation angle and combined rotation angle affect postoperative knee pain and functional evaluation.
{"title":"Robot-assisted total knee arthroplasty system provides more precise control of the femoral rotation angle: A retrospective study","authors":"Peng Yan, Xudong Duan, Yutian Lei, Fangze Xing, Ruomu Cao, Sen Luo, Yang Chen, Zeyu Liu, Kunzheng Wang, Pei Yang, Run Tian","doi":"10.1002/rcs.2635","DOIUrl":"10.1002/rcs.2635","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Rotational alignment in total knee arthroplasty (TKA) is a crucial technical point that needs attention. We conducted a retrospective study to investigate whether a new robot-assisted TKA (RA-TKA) could improve the accuracy of rotational alignment and whether rotational alignment affects postoperative pain and functional evaluation of the knee.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A total of 136 consecutive patients who underwent TKA were included in this study. Half of the patients underwent RA-TKA and the other half underwent conventional TKA (CON-TKA) by the same group of surgeons. Collect the relevant parameters.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The postoperative femoral rotation angle (FRA) was −0.72 ± 2.59° in the robot-assisted group and 1.13 ± 2.73° in the conventional group, and were statistically significantly different (<i>p</i> < 0.001).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>This study provides preliminary evidence that the RA-TKA provides more precise control of FRA than CON-TKA, and verifies that tibial rotation angle and combined rotation angle affect postoperative knee pain and functional evaluation.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50311,"journal":{"name":"International Journal of Medical Robotics and Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140909695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Allergic rhinitis constitutes a widespread health concern, with traditional treatments often proving to be painful and ineffective. Acupuncture targeting the pterygopalatine fossa proves effective but is complicated due to the intricate nearby anatomy.
Methods
To enhance the safety and precision in targeting the pterygopalatine fossa, we introduce a deep learning-based model to refine the segmentation of the pterygopalatine fossa. Our model expands the U-Net framework with DenseASPP and integrates an attention mechanism for enhanced precision in the localisation and segmentation of the pterygopalatine fossa.
Results
The model achieves Dice Similarity Coefficient of 93.89% and 95% Hausdorff Distance of 2.53 mm with significant precision. Remarkably, it only uses 1.98 M parameters.
Conclusions
Our deep learning approach yields significant advancements in localising and segmenting the pterygopalatine fossa, providing a reliable basis for guiding pterygopalatine fossa-assisted punctures.
{"title":"Automatic pterygopalatine fossa segmentation and localisation based on DenseASPP","authors":"Bing Wang, Weili Shi","doi":"10.1002/rcs.2633","DOIUrl":"https://doi.org/10.1002/rcs.2633","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Allergic rhinitis constitutes a widespread health concern, with traditional treatments often proving to be painful and ineffective. Acupuncture targeting the pterygopalatine fossa proves effective but is complicated due to the intricate nearby anatomy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>To enhance the safety and precision in targeting the pterygopalatine fossa, we introduce a deep learning-based model to refine the segmentation of the pterygopalatine fossa. Our model expands the U-Net framework with DenseASPP and integrates an attention mechanism for enhanced precision in the localisation and segmentation of the pterygopalatine fossa.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The model achieves Dice Similarity Coefficient of 93.89% and 95% Hausdorff Distance of 2.53 mm with significant precision. Remarkably, it only uses 1.98 M parameters.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our deep learning approach yields significant advancements in localising and segmenting the pterygopalatine fossa, providing a reliable basis for guiding pterygopalatine fossa-assisted punctures.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50311,"journal":{"name":"International Journal of Medical Robotics and Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140639573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anjelica Alfonso, Kimberly N. McFarland, Kush Savsani, Seung Lee, Daisuke Imai, Aamir Khan, Amit Sharma, Muhammad Saeed, Vinay Kumaran, Adrian Cotterell, David Bruno, Marlon Levy
Background
Cholecystoduodenal fistula (CDF) arises from persistent biliary tree disorders, causing fusion between the gallbladder and duodenum. Initially, open resection was common until laparoscopic fistula closure gained popularity. However, complexities within the gallbladder fossa yielded inconsistent outcomes. Advanced imaging and robotic surgery now enhance precision and detection.
Method
A 62-year-old woman with chronic cholangitis attributed to cholecystoduodenal fistula underwent successful robotic cholecystectomy and fistula closure.
Results
Postoperatively, the symptoms subsided with no complications during the robotic procedure. Existing studies report favourable outcomes for robotic cholecystectomy and fistula closure.
Conclusions
Our case report showcases a rare instance of successful robotic cholecystectomy with CDF closure. This case, along with a review of previous cases, suggests the potential of robotic surgery as the preferred approach, especially for patients anticipated to face significant laparoscopic morbidity.
{"title":"Robotic management of primary cholecystoduodenal fistula: A case report and brief literature review","authors":"Anjelica Alfonso, Kimberly N. McFarland, Kush Savsani, Seung Lee, Daisuke Imai, Aamir Khan, Amit Sharma, Muhammad Saeed, Vinay Kumaran, Adrian Cotterell, David Bruno, Marlon Levy","doi":"10.1002/rcs.2629","DOIUrl":"https://doi.org/10.1002/rcs.2629","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Cholecystoduodenal fistula (CDF) arises from persistent biliary tree disorders, causing fusion between the gallbladder and duodenum. Initially, open resection was common until laparoscopic fistula closure gained popularity. However, complexities within the gallbladder fossa yielded inconsistent outcomes. Advanced imaging and robotic surgery now enhance precision and detection.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method</h3>\u0000 \u0000 <p>A 62-year-old woman with chronic cholangitis attributed to cholecystoduodenal fistula underwent successful robotic cholecystectomy and fistula closure.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Postoperatively, the symptoms subsided with no complications during the robotic procedure. Existing studies report favourable outcomes for robotic cholecystectomy and fistula closure.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our case report showcases a rare instance of successful robotic cholecystectomy with CDF closure. This case, along with a review of previous cases, suggests the potential of robotic surgery as the preferred approach, especially for patients anticipated to face significant laparoscopic morbidity.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50311,"journal":{"name":"International Journal of Medical Robotics and Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rcs.2629","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140622647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yuzuru Sambommatsu, Seung Duk Lee, Daisuke Imai, Kush Savsani, Aamir A. Khan, Amit Sharma, Muhammad Saeed, Adrian H. Cotterell, Vinay Kumaran, Marlon F. Levy, David A. Bruno
Background
Liver parenchymal transection during robotic liver resection (RLR) remains a significant challenge due to the limited range of specialised instruments. This study introduces our ‘Burn and Push’ technique as a novel approach to address these challenges.
Methods
A retrospective analysis was conducted on 20 patients who underwent RLR using the ‘Burn and Push’ technique at Virginia Commonwealth University Health System from November 2021 to August 2023. The study evaluated peri- and post-operative outcomes.
Results
The median operation time was 241.5 min (range, 90–620 min), and the median blood loss was 100 mL (range, 10–600 mL). Major complications occurred in one case, with no instances of postoperative bleeding, bile leak, or liver failure.
Conclusions
The ‘Burn and Push’ technique is a viable and efficient alternative for liver parenchymal transection in RLR. Further research with larger sample sizes and consideration of the learning curve is necessary to validate these findings.
{"title":"‘Burn and Push’ technique: A novel robotic liver parenchymal transection technique","authors":"Yuzuru Sambommatsu, Seung Duk Lee, Daisuke Imai, Kush Savsani, Aamir A. Khan, Amit Sharma, Muhammad Saeed, Adrian H. Cotterell, Vinay Kumaran, Marlon F. Levy, David A. Bruno","doi":"10.1002/rcs.2631","DOIUrl":"https://doi.org/10.1002/rcs.2631","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Liver parenchymal transection during robotic liver resection (RLR) remains a significant challenge due to the limited range of specialised instruments. This study introduces our ‘Burn and Push’ technique as a novel approach to address these challenges.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A retrospective analysis was conducted on 20 patients who underwent RLR using the ‘Burn and Push’ technique at Virginia Commonwealth University Health System from November 2021 to August 2023. The study evaluated peri- and post-operative outcomes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The median operation time was 241.5 min (range, 90–620 min), and the median blood loss was 100 mL (range, 10–600 mL). Major complications occurred in one case, with no instances of postoperative bleeding, bile leak, or liver failure.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The ‘Burn and Push’ technique is a viable and efficient alternative for liver parenchymal transection in RLR. Further research with larger sample sizes and consideration of the learning curve is necessary to validate these findings.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50311,"journal":{"name":"International Journal of Medical Robotics and Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rcs.2631","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140622678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Constantinos Loukas, Ioannis Seimenis, Konstantina Prevezanou, Dimitrios Schizas
Background
Real-time prediction of the remaining surgery duration (RSD) is important for optimal scheduling of resources in the operating room.
Methods
We focus on the intraoperative prediction of RSD from laparoscopic video. An extensive evaluation of seven common deep learning models, a proposed one based on the Transformer architecture (TransLocal) and four baseline approaches, is presented. The proposed pipeline includes a CNN-LSTM for feature extraction from salient regions within short video segments and a Transformer with local attention mechanisms.
Results
Using the Cholec80 dataset, TransLocal yielded the best performance (mean absolute error (MAE) = 7.1 min). For long and short surgeries, the MAE was 10.6 and 4.4 min, respectively. Thirty minutes before the end of surgery MAE = 6.2 min, 7.2 and 5.5 min for all long and short surgeries, respectively.
Conclusions
The proposed technique achieves state-of-the-art results. In the future, we aim to incorporate intraoperative indicators and pre-operative data.
{"title":"Prediction of remaining surgery duration in laparoscopic videos based on visual saliency and the transformer network","authors":"Constantinos Loukas, Ioannis Seimenis, Konstantina Prevezanou, Dimitrios Schizas","doi":"10.1002/rcs.2632","DOIUrl":"https://doi.org/10.1002/rcs.2632","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Real-time prediction of the remaining surgery duration (RSD) is important for optimal scheduling of resources in the operating room.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We focus on the intraoperative prediction of RSD from laparoscopic video. An extensive evaluation of seven common deep learning models, a proposed one based on the Transformer architecture (TransLocal) and four baseline approaches, is presented. The proposed pipeline includes a CNN-LSTM for feature extraction from salient regions within short video segments and a Transformer with local attention mechanisms.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Using the Cholec80 dataset, TransLocal yielded the best performance (mean absolute error (MAE) = 7.1 min). For long and short surgeries, the MAE was 10.6 and 4.4 min, respectively. Thirty minutes before the end of surgery MAE = 6.2 min, 7.2 and 5.5 min for all long and short surgeries, respectively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The proposed technique achieves state-of-the-art results. In the future, we aim to incorporate intraoperative indicators and pre-operative data.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50311,"journal":{"name":"International Journal of Medical Robotics and Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rcs.2632","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140606365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We investigated the rates of acute kidney injury (AKI) post robot-assisted laparoscopic prostatectomy (RALP).
Methods
A comprehensive search was conducted to identify studies that reported the rates of AKI post-RALP. A random effects model was used, and the pooled rates of AKI were calculated.
Results
We identified 10 studies with 60,937 patients to be included. The mean age was 65.1 years. The mean anaesthesia time was 234.3 min (95% CI: 177.8–290.9). The mean operation time was 212.2 min (95% CI: 188.7–235.6). The mean estimated blood loss was 314.1 mL (95% CI: 153–475.3). The mean intraoperative IV fluids administered were 1985 mL (95% CI: 1516.3–2453.7). The pooled rate of AKI post RALP was 7.2% (95% CI 19–23.9).
Conclusions
The rates of AKI after RALP are significant. Further studies are needed to detect the risk factors for AKI and to determine the rates of chronic kidney disease post-RALP.
背景 我们调查了机器人辅助腹腔镜前列腺切除术（RALP）术后急性肾损伤（AKI）的发生率。 方法 对报告 RALP 术后 AKI 发生率的研究进行了全面检索。采用随机效应模型，并计算出AKI的汇总率。 结果 我们确定了 10 项研究，共纳入 60,937 名患者。平均年龄为 65.1 岁。平均麻醉时间为 234.3 分钟（95% CI：177.8-290.9）。平均手术时间为 212.2 分钟（95% CI：188.7-235.6 分钟）。估计平均失血量为 314.1 毫升（95% CI：153-475.3）。术中平均静脉输液量为 1985 毫升（95% CI：1516.3-2453.7）。RALP 术后的 AKI 总发生率为 7.2% (95% CI 19-23.9)。 结论 RALP 后的 AKI 发生率很高。需要进一步研究来检测 AKI 的风险因素，并确定 RALP 术后慢性肾病的发病率。
{"title":"Acute kidney injury after robot-assisted laparoscopic prostatectomy: A meta-analysis","authors":"Deepak Chandramohan, Raghunandan Konda, Ashwini Pujari, Sreekant Avula, Sujith Kumar Palleti, Nihar Jena, Roopa Naik, Atul Bali","doi":"10.1002/rcs.2630","DOIUrl":"https://doi.org/10.1002/rcs.2630","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>We investigated the rates of acute kidney injury (AKI) post robot-assisted laparoscopic prostatectomy (RALP).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A comprehensive search was conducted to identify studies that reported the rates of AKI post-RALP. A random effects model was used, and the pooled rates of AKI were calculated.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We identified 10 studies with 60,937 patients to be included. The mean age was 65.1 years. The mean anaesthesia time was 234.3 min (95% CI: 177.8–290.9). The mean operation time was 212.2 min (95% CI: 188.7–235.6). The mean estimated blood loss was 314.1 mL (95% CI: 153–475.3). The mean intraoperative IV fluids administered were 1985 mL (95% CI: 1516.3–2453.7). The pooled rate of AKI post RALP was 7.2% (95% CI 19–23.9).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The rates of AKI after RALP are significant. Further studies are needed to detect the risk factors for AKI and to determine the rates of chronic kidney disease post-RALP.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50311,"journal":{"name":"International Journal of Medical Robotics and Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rcs.2630","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140343089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Moamen Mohsen Sarhan, Eman Assem Ibrahim, Salah Ezzelarab, Mona K. Marei
Background
The aim of this scoping review was to understand the development of robotics and its accuracy in placing dental implants when compared to other forms of guided surgery.
Methods
An electronic search was conducted on the electronic databases of PubMed, Cochrane, and Science direct with the following queries: ((robotics) AND (dental implant)) AND (accuracy). The search timeline was between 2017 and 2022.
Results
A total of 54 articles were screened for title and abstract, of which 16 were deemed eligible for inclusion. Thirty-one articles were excluded mainly because they were out of topic (not relevant) or not in English. In total, 16 articles were included for analysis.
Conclusions
This review thoroughly analyses 5 years of literature concerning the evolution of robotics in dental implant surgery, underscoring the necessity for additional research on nascent technologies reported and a comparative study with static and dynamic systems for clinical efficacy evaluation.
{"title":"Navigating the future of guided dental implantology: A scoping review","authors":"Moamen Mohsen Sarhan, Eman Assem Ibrahim, Salah Ezzelarab, Mona K. Marei","doi":"10.1002/rcs.2627","DOIUrl":"10.1002/rcs.2627","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The aim of this scoping review was to understand the development of robotics and its accuracy in placing dental implants when compared to other forms of guided surgery.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>An electronic search was conducted on the electronic databases of PubMed, Cochrane, and Science direct with the following queries: ((robotics) AND (dental implant)) AND (accuracy). The search timeline was between 2017 and 2022.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A total of 54 articles were screened for title and abstract, of which 16 were deemed eligible for inclusion. Thirty-one articles were excluded mainly because they were out of topic (not relevant) or not in English. In total, 16 articles were included for analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This review thoroughly analyses 5 years of literature concerning the evolution of robotics in dental implant surgery, underscoring the necessity for additional research on nascent technologies reported and a comparative study with static and dynamic systems for clinical efficacy evaluation.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50311,"journal":{"name":"International Journal of Medical Robotics and Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140208397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shurui Wu, Liu Boyuan, Tao Zeng, Ben Ma, Zhaoyi Lin, Minggen Hu
Background
The applicability of robot-assisted resection for huge hepatocellular carcinoma (HCC) of ≥10 cm remains contentious with limited available data.
Methods
This retrospective analysis involved 337 patients who underwent robotic liver resection for HCC by a single surgeon. Propensity score matching (PSM) was employed to compare perioperative indicators between patients with regular and huge HCC.
Results
The regular HCC group exhibited a shorter median operative duration than the huge HCC group. The IWATE criteria revealed higher scores in the huge HCC group than in the regular HCC group. No significant differences were observed between the two groups in Pringle time, drainage tube removal, duration of hospital stays, blood loss volume, blood product transfusion, margin status, conversion rate to open surgery, bile leakage, in-hospital mortality, and reoperation rate.
Conclusion
Robotic liver resection is feasible for huge HCC, with effective perioperative risk management potentially improving outcomes for subsequent minimally invasive surgeries.
{"title":"Feasibility and safety of robotic liver resection for huge (≥10 cm) hepatocellular carcinoma in a single centre: A propensity score-matched single-surgeon study","authors":"Shurui Wu, Liu Boyuan, Tao Zeng, Ben Ma, Zhaoyi Lin, Minggen Hu","doi":"10.1002/rcs.2628","DOIUrl":"10.1002/rcs.2628","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The applicability of robot-assisted resection for huge hepatocellular carcinoma (HCC) of ≥10 cm remains contentious with limited available data.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This retrospective analysis involved 337 patients who underwent robotic liver resection for HCC by a single surgeon. Propensity score matching (PSM) was employed to compare perioperative indicators between patients with regular and huge HCC.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The regular HCC group exhibited a shorter median operative duration than the huge HCC group. The IWATE criteria revealed higher scores in the huge HCC group than in the regular HCC group. No significant differences were observed between the two groups in Pringle time, drainage tube removal, duration of hospital stays, blood loss volume, blood product transfusion, margin status, conversion rate to open surgery, bile leakage, in-hospital mortality, and reoperation rate.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Robotic liver resection is feasible for huge HCC, with effective perioperative risk management potentially improving outcomes for subsequent minimally invasive surgeries.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50311,"journal":{"name":"International Journal of Medical Robotics and Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140190480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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