Computer-assisted Surgery Applications Research Articles

Computer-Assisted Surgery in Mandible Reconstruction

AbstractComputer-assisted surgery is the most significant recent advancement in osseous head and neck reconstruction. Computer-aided design (CAD) software allows computerized planning of resection and reconstruction. Computer-aided manufacturing (CAM) can be used to create models, cutting guides, and patient-specific plates. Several studies have shown that these techniques are more accurate and result in decreased flap ischemia times compared with conventional techniques. CAD also facilitates the immediate placement of dental implants. The most useful application of computer-assisted surgery is delayed reconstruction, in which soft tissue contraction and the absence of a specimen as a reference make accurate estimation of the defect challenging. The drawbacks of CAD/CAM are lack of intraoperative flexibility and cost. Some centers have created in-house CAD/CAM processes using open-source software and commercially available three-dimensional printers.

A quantitative comparison of bone resection margin distances in virtual surgical planning versus histopathology: a prospective study.

Positive bone margins have been shown to be associated with worse locoregional control and survival performance in oral oncology patients. With the application of computer-assisted surgery and patient-specific surgical guides, the authors can accurately execute the preoperative osteotomy plan. However, how well the authors can predict the margin distance in the final histopathology with a preoperative computed tomography (CT) scan, the factors associated with it, and how much leeway CT should spare when designing the osteotomy planes during virtual surgical planning (VSP) remain to be investigated. Patients from January 2021 to December 2022 with benign or malignant jaw tumors and with signs of bone marrow involvement in the preoperative CT scan in our center were prospectively recruited to the study. VSP and measurement of the closest margin distance in the CT scan were performed by the single team of surgeons. The resection specimen was processed, and the margin distances were measured by a dedicated senior pathologist with the knowledge of orientation of the osteotomy planes. A total of 35 patients were recruited, with 21 malignant and 14 benign cases. Sixty-eight bone margins were quantitatively analyzed. No significant difference in margin distances measured from the CT scan and final histopathology was detected ( P =0.19), and there was a strong correlation between the two (r s =0.74, P <0.01). A considerable amount of variance was detected in the level of discrepancy between margin distances measured in the CT scan and final histopathology (overall SD=6.26 mm, malignancy SD=7.44 mm, benign SD=4.40 mm). No significant correlation existed between the two margin distances when only maxilla tumor margins were assessed ( P =0.16). The bone margin distance in VSP is reliably correlated to the final pathological margin distance. A leeway distance of 15mm and 9mm should be considered when designing the osteotomy planes for malignancy and benign cases, respectively. Extra attention should be paid to maxilla cases when predetermining the osteotomy planes during VSP.

Disparity refinement framework for learning-based stereo matching methods in cross-domain setting for laparoscopic images.

Stereo matching methods that enable depth estimation are crucial for visualization enhancement applications in computer-assisted surgery. Learning-based stereo matching methods have shown great promise in making accurate predictions on laparoscopic images. However, they require a large amount of training data, and their performance may be degraded due to domain shifts. Maintaining robustness and improving the accuracy of learning-based methods are still open problems. To overcome the limitations of learning-based methods, we propose a disparity refinement framework consisting of a local disparity refinement method and a global disparity refinement method to improve the results of learning-based stereo matching methods in a cross-domain setting. Those learning-based stereo matching methods are pre-trained on a large public dataset of natural images and are tested on two datasets of laparoscopic images. Qualitative and quantitative results suggest that our proposed disparity framework can effectively refine disparity maps when they are noise-corrupted on an unseen dataset, without compromising prediction accuracy when the network can generalize well on an unseen dataset. Our proposed disparity refinement framework could work with learning-based methods to achieve robust and accurate disparity prediction. Yet, as a large laparoscopic dataset for training learning-based methods does not exist and the generalization ability of networks remains to be improved, the incorporation of the proposed disparity refinement framework into existing networks will contribute to improving their overall accuracy and robustness associated with depth estimation.

Computer-assisted planning for revision shoulder arthroplasty

Preoperative planning software has emerged as one of the most useful applications of computer-assisted surgery to the field of shoulder arthroplasty. As the burden of revision shoulder arthroplasty has continued to increase, and the value of preoperative planning software has been widely recognized for primary arthroplasty, preoperative planning in revision cases is desired by any surgeons. The development of revision planning software faces certain challenges, including segmentation of implants, artefact reduction, regulatory constraints, and other. Currently, certain planning software packages are available only when custom-made implants are being ordered, whereas a couple of products allow planning essentially every case. Finally, certain healthcare institutions have developed programs for point-of-care planning and 3D-printing. This article reviews the state of the art of preoperative planning software in revision shoulder arthroplasty and provides directions for additional future developments.

A Disparity Refinement Framework for Learning-based Stereo Matching Methods in Cross-domain Setting for Laparoscopic Images.

Stereo matching methods that enable depth estimation are crucial for visualization enhancement applications in computer-assisted surgery (CAS). Learning-based stereo matching methods are promising to predict accurate results for applications involving video images. However, they require a large amount of training data, and their performance may be degraded due to domain shifts. Maintaining robustness and improving performance of learning-based methods are still open problems. To overcome the limitations of learning-based methods, we propose a disparity refinement framework consisting of a local disparity refinement method and a global disparity refinement method to improve the results of learning-based stereo matching methods in a cross-domain setting. Those learning-based stereo matching methods are pre-trained on a large public dataset of natural images and are tested on a dataset of laparoscopic images. Results from the SERV-CT dataset showed that our proposed framework can effectively refine disparity maps on an unseen dataset even when they are corrupted by noise, and without compromising correct prediction, provided the network can generalize well on unseen datasets. As such, our proposed disparity refinement framework has the potential to work with learning-based methods to achieve robust and accurate disparity prediction. Yet, as a large laparoscopic dataset for training learning-based methods does not exist and the generalization ability of networks remains to be improved, it will be beneficial to incorporate the proposed disparity refinement framework into existing networks for more accurate and robust depth estimation.

Patient-Specific Orthognathic Solutions (PSOS) Survey: Global Trends in Orthognathic Surgery

Over the last decade, computer-assisted surgery (CAS) and patient-specific plates (PSP) have changed the way orthognathic surgery is performed. These technologies are now used globally but, to date, there have been no international surveys to assess the application and current trends of CAS and PSP in orthognathic surgery. This study analyzed the current trends and reasons of CAS and PSP use in orthognathic surgery. Previous studies have demonstrated that CAS and PSP in orthognathic surgery resulted in improved accuracy1 and comparable costs2 when compared with traditional techniques.

Application of Computer-assisted Surgery in Urology

The purpose of this scientific article is to show the possibility of using the HoloDoctor software and hardware complex, which includes the following modules: the anatomical atlas module, the data analysis module and the surgical intervention simulation module. HoloDoctor allows us to perform surgical operations in real time. The time of operations using the HoloDoctor is reduced by 20-30% compared to traditional methods. The developed complex provides diagnostics of treatment planning, correction of the treatment plan, minimizing the risk of medical error. The developed product can be used in educational practice by introducing it into educational programs of medical specialties.

ClipAssistNet: bringing real-time safety feedback to operating rooms

PurposeCholecystectomy is one of the most common laparoscopic procedures. A critical phase of laparoscopic cholecystectomy consists in clipping the cystic duct and artery before cutting them. Surgeons can improve the clipping safety by ensuring full visibility of the clipper, while enclosing the artery or the duct with the clip applier jaws. This can prevent unintentional interaction with neighboring tissues or clip misplacement. In this article, we present a novel real-time feedback to ensure safe visibility of the instrument during this critical phase. This feedback incites surgeons to keep the tip of their clip applier visible while operating.MethodsWe present a new dataset of 300 laparoscopic cholecystectomy videos with frame-wise annotation of clipper tip visibility. We further present ClipAssistNet, a neural network-based image classifier which detects the clipper tip visibility in single frames. ClipAssistNet ensembles predictions from 5 neural networks trained on different subsets of the dataset.ResultsOur model learns to classify the clipper tip visibility by detecting its presence in the image. Measured on a separate test set, ClipAssistNet classifies the clipper tip visibility with an AUROC of 0.9107, and 66.15% specificity at 95% sensitivity. Additionally, it can perform real-time inference (16 FPS) on an embedded computing board; this enables its deployment in operating room settings.ConclusionThis work presents a new application of computer-assisted surgery for laparoscopic cholecystectomy, namely real-time feedback on adequate visibility of the clip applier. We believe this feedback can increase surgeons’ attentiveness when departing from safe visibility during the critical clipping of the cystic duct and artery.

Use of computer-assisted surgery in the orbit

ABSTRACT Purpose To present the application of computer-assisted surgery (CAS) in pre-operative planning, intra-operative navigation, and post-operative assessment as an adjunct tool in orbital surgery. Methods An IRB-approved, retrospective review was performed to identify patients who had undergone orbital surgery by a single surgeon from July 2013 to December 2019 with attention to pre-operative virtual surgical planning, intra-operative navigation, and post-operative assessment. The reasons and methods of CAS use were classified. Results The use of computer-assisted technologies was identified in 91 cases out of 464 orbital surgeries (19.6%). This included 23 (25.3%) orbital decompression surgeries, 39 (42.9%) fracture repairs, and 25 (27.5%) orbital tumors. In all cases, pre-, intra-, and post-operative CAS allowed for increased operative efficiency and safety with good outcomes. Conclusions Use of CAS in orbital surgery can allow for complex radiographic analysis and in select cases is a great tool to add to the orbital surgeon’s armamentarium.

Progress on femorotibial mechanical axis of total knee arthroplasty

Femorotibial mechanical axis (FTMA) is one of important factors influencing clinical effect after total knee arthroplasty (TKA). It is generally believed that the range of lower limb alignment after TKA is controlled within neutral FTMA ± 3 °, which has more advantages in improving joint function, prolonging prosthesis survival rate and reducing revision rate, and obtain better clinical results. Therefore, neutral FTMA is also considered to be the gold standard for TKA. However, with the application of computer-assisted surgery and other technologies, the alignment of FTMA is more accurate than before, but the clinical effect after surgery has not significantly improved. Some scholars have begun to question the necessity of neutral alignment of FTMA, and proposed alignment methods such as kinematics and retained residual deformity, which could achieve better clinical effects. In recent years, it has been reported that FTMA might not be the most important factor influencing postoperative clinical effects, and it is suggested that the arrangement and measurement of lower limbs and the effects on adjacent joint functions could affect clinical effect after TKA. The paper reviews neutral FTMA alignment is still an important factor for success of TKA. After a thorough evaluation according to the patient's condition, it should be appropriately applied in the case of neutral FTMA alignment; the operator should explore other factors which affect clinical outcome after TKA, and improve it to achieve the best therapeutic effect.

Light modelling and calibration in laparoscopy

A better understanding of photometry in laparoscopic images can increase the reliability of computer-assisted surgery applications. Photometry requires modelling illumination, tissue reflectance and camera response. There exists a large variety of light models, but no systematic and reproducible evaluation. We present a review of light models in laparoscopic surgery, a unified calibration approach, an evaluation methodology, and a practical use of photometry. We use images of a calibration checkerboard to calibrate the light models. We then use these models in a proposed dense stereo algorithm exploiting the shading and simultaneously extracting the tissue albedo, which we call dense shading stereo. The approach works with a broad range of light models, giving us a way to test their respective merits. We show that overly complex light models are usually not needed and that the light source position must be calibrated. We also show that dense shading stereo outperforms existing methods, in terms of both geometric and photometric errors, and achieves sub-millimeter accuracy. This work demonstrates the importance of careful light modelling and calibration for computer-assisted surgical applications. It gives guidelines on choosing the best performing light model.

A Novel Design of N-Fiducial Phantom for Automatic Ultrasound Calibration.

Background:Freehand ultrasound (US) is a technique used to acquire three-dimensional (3D) US images using a tracked 2D US probe. Calibrating the probe with a proper calibration phantom improves the precision of the technique and allows several applications in computer-assisted surgery. N-fiducial phantom is widely used due to the robustness of precise fabrication and convenience of use. In principle, the design supports single-frame calibration by providing at least three noncollinear points in 3D space at once. Due to this requirement, most designs contain multiple N-fiducials in unpatterned and noncollinear arrangements. The unpatterned multiple N-fiducials appearing as scattered dots in the US image are difficult to extract, and the extracted data are usually contaminated with noise. In practice, the extraction mostly relied on manual interventions, and calibration with N-fiducial phantom has not yet achieved high accuracy with single or few frame calibrations due to noise contamination.Aims:In this article, we propose a novel design of the N-fiducial US calibration phantom to enable automatic feature extraction with comparable accuracy to multiple frame calibration.Materials and Methods:Along with the design, the Random Sample Consensus (RANSAC) algorithm was used for feature extraction with both 2D and 3D models estimation. The RANSAC feature extraction algorithm was equipped with a closed-form calibration method to achieve automatic calibration.Results:The accuracy, precision, and shape reconstruction errors of the calibration acquired from the experiment were significantly matched with the previous literature reports.Conclusions:The results showed that our proposed method has a high efficiency to perform automatic feature extraction compared to conventional extraction performed by humans.

Computer-assisted Surgery for Scaphoid Fracture.

The computer-assisted surgery (CAS) has significantly improved the accuracy, reliability and outcomes of traumatic, spinal, nerve surgery and many other operations with a less invasive way. The application of CAS for scaphoid fractures remains experimental. The related studies are scanty and most of them are cadaver researches. Some intrinsic defects from the registration procedure, scan and immobilization of limbs may inevitably result in deviations. Some deviations become more obvious with operations of small bones (such as scaphoid) although they are acceptable for spine and other orthopedic surgeries. We reviewed the current literatures on the applications of CAS for scaphoid operation and summarized technical principles, scan and registration methods, immobilization of limbs and their outcomes. On the basis of the data, we analyzed the limitations of this technique and envisioned its future development.

EndoAbS dataset: Endoscopic abdominal stereo image dataset for benchmarking 3D stereo reconstruction algorithms.

3D reconstruction algorithms are of fundamental importance for augmented reality applications in computer-assisted surgery. However, few datasets of endoscopic stereo images with associated 3D surface references are currently openly available, preventing the proper validation of such algorithms. This work presents a new and rich dataset of endoscopic stereo images (EndoAbS dataset). The dataset includes (i) endoscopic stereo images of phantom abdominal organs, (ii) a 3D organ surface reference (RF) generated with a laser scanner and (iii) camera calibration parameters. A detailed description of the generation of the phantom and the camera-laser calibration method is also provided. An estimation of the overall error in creation of the dataset is reported (camera-laser calibration error 0.43mm) and the performance of a 3D reconstruction algorithm is evaluated using EndoAbS, resulting in an accuracy error in accordance with state-of-the-art results (<2mm). The EndoAbS dataset contributes to an increase the number and variety of openly available datasets of surgical stereo images, including a highly accurate RF and different surgical conditions.

Computer-assisted Orthopaedic Surgery.

Nowadays, operating rooms can be inefficient and overcrowded. Patient data and images are at times not well integrated and displayed in a timely fashion. This lack of coordination may cause further reductions in efficiency, jeopardize patient safety, and increase costs. Fortunately, technology has much to offer the surgical disciplines and the ongoing and recent operating room innovations have advanced preoperative planning and surgical procedures by providing visual, navigational, and mechanical computerized assistance. The field of computer-assisted surgery (CAS) broadly refers to surgical interface between surgeons and machines. It is also part of the ongoing initiatives to move away from invasive to less invasive or even noninvasive procedures. CAS can be applied preoperatively, intraoperatively, and/or postoperatively to improve the outcome of orthopaedic surgical procedures as it has the potential for greater precision, control, and flexibility in carrying out surgical tasks, and enables much better visualization of the operating field than conventional methods have afforded. CAS is an active research discipline, which brings together orthopaedic practitioners with traditional technical disciplines such as engineering, computer science, and robotics. However, to achieve the best outcomes, teamwork, open communication, and willingness to adapt and adopt new skills and processes are critical. Because of the relatively short time period over which CAS has developed, long-term follow-up studies have not yet been possible. Consequently, this review aims to outline current CAS applications, limitations, and promising future developments that will continue to impact the operating room (OR) environment and the OR in the future, particularly within orthopedic and spine surgery.

THE INFLUENCE OF COMPUTER-ASSISTED SURGERY ON CLINICAL AND RADIOGRAPHIC OUTCOMES OF PERIАRTICULAR FEMUR AND TIBIA OSTEOTOMIES IN OSTEOARTHRITIC PATIENTS (REVIEW)

Nowadays the clinical application of digital technologies became a growing trend at every stage of orthopedic patient treatment: from diagnostic procedures and pre-operative planning to intra-operative control of surgical manipulations and evaluation of final results later. The aim of thi sresearch was to analyze the studies dedicated to application of computer-assisted surgery (CAS) for femur and tibial osteotomies in patients with gonarthrosis. The hypothesis was that CAS improves the precision of leg alignment correction in frontal and sagittal planes that positively influencing both functional result of treatment and longevity of clinical effect. The PubMed, PubMedCentral, GoogleScholar and eLIBRARY searched for relevant studies using following key words: knee, osteoarthritis, gonarthrosis, osteotomy, CAS, navigation and its russian analogs. The majority of publications favored CAS in comparison to traditional osteotomy techniques both for leg alignment and tibial slope control. Despite generally researchers paid less attention to functional results after CASosteotomies than to precision of surgical manipulations it is possible of confirm that there is strong tendency to better knee scores after navigation while the difference is not always statistically significant. Rare publications dedicated to long term results favor CAS: 10 years survival rate is 97% that correspond to outcomes of modern total knee arthroplasty. Hence, the current literature confirms the hypothesis of our study and don’t reveal increase of complications rate associated with CAS.

Soft tissue motion tracking with application to tablet-based incision planning in laser surgery.

Recent research has revealed that incision planning in laser surgery deploying stylus and tablet outperforms micromanipulator control. However, vision-based adaption to dynamic surgical scenes has not been addressed so far. In this study, scene motion compensation for tablet-based planning by means of tissue deformation tracking is discussed. A stereo-based method for motion tracking with piecewise affine deformation modeling is presented. Proposed parametrization relies on the epipolar constraint to enforce left-right consistency in the energy minimization problem. Furthermore, the method implements illumination-invariant tracking and appearance-based occlusion detection. Performance is assessed on laparoscopic and laryngeal in vivo data. In particular, tracking accuracy is measured under various conditions such as occlusions and simulated laser cuttings. Experimental validation is extended to a user study conducted on a tablet-based interface that integrates the tracking for image stabilization. Tracking accuracy measurement reveals a root-mean-square error of 2.45mm for the laparoscopic and 0.41mm for the laryngeal dataset. Results successfully demonstrate stereoscopic tracking under changes in illumination, translation, rotation and scale. In particular, proposed occlusion detection scheme can increase robustness against tracking failure. Moreover, assessed user performance indicates significantly increased path tracing accuracy and usability if proposed tracking is deployed to stabilize the view during free-hand path definition. The presented algorithm successfully extends piecewise affine deformation tracking to stereo vision taking the epipolar constraint into account. Improved surgical performance as demonstrated for laser incision planning highlights the potential of presented method regarding further applications in computer-assisted surgery.

12years of Computer-Aided Surgery around the Head : Developments in surgical planning and simulation from a Bern perspective

Over the past years, the multidisciplinary character of the international Computer-Aided Surgery around the Head (CAS-H) symposium has advanced many medical technologies, which were often adopted by industry. In Bern, the synergetic effects of the CAS-H symposium have enabled many experiences and developments in the area of computer-aided surgery. Planning and simulation methods in the areas of craniomaxillofacial surgery and otorhinolaryngology were developed and tested in clinical settings. In the future, further CAS-H symposia should follow, in order to promote the possibilities and applications of computer-assisted surgery around the head.

(ii) Computer assisted surgery in trauma and osteotomy

Computer assisted surgery (CAS) has been applied more often within the last years. Multiple aspects of CAS have been important in orthopaedic and trauma surgery such as pre-operative planning, intraoperative imaging and navigation. In total four different methods of navigation within CAS exist. While imageless navigation is used more regularly in osteotomy, 3D-based navigation is applied in trauma surgery more commonly. CAS uses infrared signals sent from markers attached to the patient and the instruments which are detected by a camera and processed by a connected computer. The aim of CAS is a visual support during complex surgical procedures leading to an improvement of the operational result. The enhancement of the visualization permits surgical procedures with low soft tissue impairment especially in crucial anatomical regions. Hence CAS together with minimal invasive procedures and an improvement of digital imaging has the option to optimize surgical procedures. However there exist limitations to the application of CAS in trauma care which have to be considered.

Computer-assisted surgery in orthopedic oncology

Background and purpose — In orthopedic oncology, computer-assisted surgery (CAS) can be considered an alternative to fluoroscopy and direct measurement for orientation, planning, and margin control. However, only small case series reporting specific applications have been published. We therefore describe possible applications of CAS and report preliminary results in 130 procedures.Patients and methods — We conducted a retrospective cohort study of all oncological CAS procedures in a single institution from November 2006 to March 2013. Mean follow-up time was 32 months. We categorized and analyzed 130 procedures for clinical parameters. The categories were image-based intralesional treatment, image-based resection, image-based resection and reconstruction, and imageless resection and reconstruction.Results — Application to intralesional treatment showed 1 inadequate curettage and 1 (other) recurrence in 63 cases. Image-based resections in 42 cases showed 40 R0 margins; 16 in 17 pelvic resections. Image-based reconstruction facilitated graft creation with a mean reconstruction accuracy of 0.9 mm in one case. Imageless CAS was helpful in resection planning and length- and joint line reconstruction for tumor prostheses.Interpretation — CAS is a promising new development. Preliminary results show a high number of R0 resections and low short-term recurrence rates for curettage.