Bowen Xiang, Jon S Heiselman, Winona L Richey, Michael I D'Angelica, Alice Wei, T Peter Kingham, Frankangel Servin, Kyvia Pereira, Sunil K Geevarghese, William R Jarnagin, Michael I Miga
{"title":"术中表面采集方法对软组织手术导航注册准确性的比较研究。","authors":"Bowen Xiang, Jon S Heiselman, Winona L Richey, Michael I D'Angelica, Alice Wei, T Peter Kingham, Frankangel Servin, Kyvia Pereira, Sunil K Geevarghese, William R Jarnagin, Michael I Miga","doi":"10.1117/1.JMI.11.2.025001","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>To study the difference between rigid registration and nonrigid registration using two forms of digitization (contact and noncontact) in human <i>in vivo</i> liver surgery.</p><p><strong>Approach: </strong>A Conoprobe device attachment and sterilization process was developed to enable prospective noncontact intraoperative acquisition of organ surface data in the operating room (OR). The noncontact Conoprobe digitization method was compared against stylus-based acquisition in the context of image-to-physical registration for image-guided surgical navigation. Data from <math><mrow><mi>n</mi><mo>=</mo><mn>10</mn></mrow></math> patients undergoing liver resection were analyzed under an Institutional Review Board-approved study at Memorial Sloan Kettering Cancer Center. Organ surface coverage of each surface acquisition method was compared. Registration accuracies resulting from the acquisition techniques were compared for (1) rigid registration method (RRM), (2) model-based nonrigid registration method (NRM) using surface data only, and (3) NRM with one subsurface feature (vena cava) from tracked intraoperative ultrasound (NRM-VC). Novel vessel centerline and tumor targets were segmented and compared to their registered preoperative counterparts for accuracy validation.</p><p><strong>Results: </strong>Surface data coverage collected by stylus and Conoprobe were <math><mrow><mn>24.6</mn><mo>%</mo><mo>±</mo><mn>6.4</mn><mo>%</mo></mrow></math> and <math><mrow><mn>19.6</mn><mo>%</mo><mo>±</mo><mn>5.0</mn><mo>%</mo></mrow></math>, respectively. The average difference between stylus data and Conoprobe data using NRM was <math><mrow><mo>-</mo><mn>1.05</mn><mtext> </mtext><mi>mm</mi></mrow></math> and using NRM-VC was <math><mrow><mo>-</mo><mn>1.42</mn><mtext> </mtext><mi>mm</mi></mrow></math>, indicating the registrations to Conoprobe data performed worse than to stylus data with both NRM approaches. However, using the stylus and Conoprobe acquisition methods led to significant improvement of NRM-VC over RRM by average differences of 4.48 and 3.66 mm, respectively.</p><p><strong>Conclusion: </strong>The first use of a sterile-field amenable Conoprobe surface acquisition strategy in the OR is reported for open liver surgery. Under clinical conditions, the nonrigid registration significantly outperformed standard-of-care rigid registration, and acquisition by contact-based stylus and noncontact-based Conoprobe produced similar registration results. The accuracy benefits of noncontact surface acquisition with a Conoprobe are likely obscured by inferior data coverage and intrinsic noise within acquisition systems.</p>","PeriodicalId":47707,"journal":{"name":"Journal of Medical Imaging","volume":"11 2","pages":"025001"},"PeriodicalIF":1.9000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10911768/pdf/","citationCount":"0","resultStr":"{\"title\":\"Comparison study of intraoperative surface acquisition methods on registration accuracy for soft-tissue surgical navigation.\",\"authors\":\"Bowen Xiang, Jon S Heiselman, Winona L Richey, Michael I D'Angelica, Alice Wei, T Peter Kingham, Frankangel Servin, Kyvia Pereira, Sunil K Geevarghese, William R Jarnagin, Michael I Miga\",\"doi\":\"10.1117/1.JMI.11.2.025001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>To study the difference between rigid registration and nonrigid registration using two forms of digitization (contact and noncontact) in human <i>in vivo</i> liver surgery.</p><p><strong>Approach: </strong>A Conoprobe device attachment and sterilization process was developed to enable prospective noncontact intraoperative acquisition of organ surface data in the operating room (OR). The noncontact Conoprobe digitization method was compared against stylus-based acquisition in the context of image-to-physical registration for image-guided surgical navigation. Data from <math><mrow><mi>n</mi><mo>=</mo><mn>10</mn></mrow></math> patients undergoing liver resection were analyzed under an Institutional Review Board-approved study at Memorial Sloan Kettering Cancer Center. Organ surface coverage of each surface acquisition method was compared. Registration accuracies resulting from the acquisition techniques were compared for (1) rigid registration method (RRM), (2) model-based nonrigid registration method (NRM) using surface data only, and (3) NRM with one subsurface feature (vena cava) from tracked intraoperative ultrasound (NRM-VC). Novel vessel centerline and tumor targets were segmented and compared to their registered preoperative counterparts for accuracy validation.</p><p><strong>Results: </strong>Surface data coverage collected by stylus and Conoprobe were <math><mrow><mn>24.6</mn><mo>%</mo><mo>±</mo><mn>6.4</mn><mo>%</mo></mrow></math> and <math><mrow><mn>19.6</mn><mo>%</mo><mo>±</mo><mn>5.0</mn><mo>%</mo></mrow></math>, respectively. The average difference between stylus data and Conoprobe data using NRM was <math><mrow><mo>-</mo><mn>1.05</mn><mtext> </mtext><mi>mm</mi></mrow></math> and using NRM-VC was <math><mrow><mo>-</mo><mn>1.42</mn><mtext> </mtext><mi>mm</mi></mrow></math>, indicating the registrations to Conoprobe data performed worse than to stylus data with both NRM approaches. However, using the stylus and Conoprobe acquisition methods led to significant improvement of NRM-VC over RRM by average differences of 4.48 and 3.66 mm, respectively.</p><p><strong>Conclusion: </strong>The first use of a sterile-field amenable Conoprobe surface acquisition strategy in the OR is reported for open liver surgery. Under clinical conditions, the nonrigid registration significantly outperformed standard-of-care rigid registration, and acquisition by contact-based stylus and noncontact-based Conoprobe produced similar registration results. The accuracy benefits of noncontact surface acquisition with a Conoprobe are likely obscured by inferior data coverage and intrinsic noise within acquisition systems.</p>\",\"PeriodicalId\":47707,\"journal\":{\"name\":\"Journal of Medical Imaging\",\"volume\":\"11 2\",\"pages\":\"025001\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10911768/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Medical Imaging\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1117/1.JMI.11.2.025001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/3/4 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Medical Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1117/1.JMI.11.2.025001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/3/4 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Comparison study of intraoperative surface acquisition methods on registration accuracy for soft-tissue surgical navigation.
Purpose: To study the difference between rigid registration and nonrigid registration using two forms of digitization (contact and noncontact) in human in vivo liver surgery.
Approach: A Conoprobe device attachment and sterilization process was developed to enable prospective noncontact intraoperative acquisition of organ surface data in the operating room (OR). The noncontact Conoprobe digitization method was compared against stylus-based acquisition in the context of image-to-physical registration for image-guided surgical navigation. Data from patients undergoing liver resection were analyzed under an Institutional Review Board-approved study at Memorial Sloan Kettering Cancer Center. Organ surface coverage of each surface acquisition method was compared. Registration accuracies resulting from the acquisition techniques were compared for (1) rigid registration method (RRM), (2) model-based nonrigid registration method (NRM) using surface data only, and (3) NRM with one subsurface feature (vena cava) from tracked intraoperative ultrasound (NRM-VC). Novel vessel centerline and tumor targets were segmented and compared to their registered preoperative counterparts for accuracy validation.
Results: Surface data coverage collected by stylus and Conoprobe were and , respectively. The average difference between stylus data and Conoprobe data using NRM was and using NRM-VC was , indicating the registrations to Conoprobe data performed worse than to stylus data with both NRM approaches. However, using the stylus and Conoprobe acquisition methods led to significant improvement of NRM-VC over RRM by average differences of 4.48 and 3.66 mm, respectively.
Conclusion: The first use of a sterile-field amenable Conoprobe surface acquisition strategy in the OR is reported for open liver surgery. Under clinical conditions, the nonrigid registration significantly outperformed standard-of-care rigid registration, and acquisition by contact-based stylus and noncontact-based Conoprobe produced similar registration results. The accuracy benefits of noncontact surface acquisition with a Conoprobe are likely obscured by inferior data coverage and intrinsic noise within acquisition systems.
期刊介绍:
JMI covers fundamental and translational research, as well as applications, focused on medical imaging, which continue to yield physical and biomedical advancements in the early detection, diagnostics, and therapy of disease as well as in the understanding of normal. The scope of JMI includes: Imaging physics, Tomographic reconstruction algorithms (such as those in CT and MRI), Image processing and deep learning, Computer-aided diagnosis and quantitative image analysis, Visualization and modeling, Picture archiving and communications systems (PACS), Image perception and observer performance, Technology assessment, Ultrasonic imaging, Image-guided procedures, Digital pathology, Biomedical applications of biomedical imaging. JMI allows for the peer-reviewed communication and archiving of scientific developments, translational and clinical applications, reviews, and recommendations for the field.