Motivation Medical imaging and its application in interventional guidance has revolutionized the development of minimally invasive surgical procedures leading to reduced patient trauma, fewer risks, and shorter recovery times. However, a frequently posed question with regards to an image guidance system is “how accurate is it?” On one hand, the accuracy challenge can be posed in terms of the tolerable clinical error associated with the procedure; on the other hand, accuracy is bound by the limitations of the system’s components, including modeling, patient registration, and surgical instrument tracking, all of which ultimately impact the overall targeting capabilities of the system. Methods While these processes are not unique to any interventional specialty, this paper discusses them in the context of two different cardiac image-guidance platforms: a model-enhanced ultrasound platform for intracardiac interventions and a prototype system for advanced visualization in image-guided cardiac ablation therapy. Results Pre-operative modeling techniques involving manual, semi-automatic and registration-based segmentation are discussed. The performance and limitations of clinically feasible approaches for patient registration evaluated both in the laboratory and operating room are presented. Our experience with two different magnetic tracking systems for instrument and ultrasound transducer localization is reported. Ultimately, the overall accuracy of the systems is discussed based on both in vitro and preliminary in vivo experience. Conclusion While clinical accuracy is specific to a particular patient and procedure and vastly dependent on the surgeon’s experience, the system’s engineering limitations are critical to determine whether the clinical requirements can be met.

No abstract

Abstract. Prior to performing a robot-assisted coronary artery bypass grafting procedure, a pre-operative computed tomography scan is used to assess patient candidacy and to identify the location of the target vessel. The surgeon then determines the optimal port locations to ensure proper reach to the target with the robotic instruments, while assuming that the heart does not undergo any significant changes between the preand intra-operative stages. However, the peri-operative workflow itself leads to changes in heart position and consequently the intra-operative target vessel location. As such, the pre-operative plan must be adequately updated to adjust the target vessel location to better suit the intraoperative condition. Here we propose a technique to predict the position of the peri-operative target vessel location with ∼ 3.5 mm RMS accuracy. We believe this technique will potentially reduce the rate of conversion of robot-assisted procedures to traditional open-chest surgery due to poor planning.

Although robot-assisted coronary artery bypass grafting (RA-CABG) has gained more acceptance worldwide, its success still depends on the surgeon's experience and expertise, and the conversion rate to full sternotomy is in the order of 15%-25%. One of the reasons for conversion is poor preoperative planning, which is based solely on pre-operative computed tomography (CT) images. In this paper, the authors propose a technique to estimate the global peri-operative displacement of the heart and to predict the intra-operative target vessel location, validated via both an in vitro and a clinical study. Methods: As the peri-operative heart migration during RA-CABG has never been reported in the literatures, a simple in vitro validation study was conducted using a heart phantom. To mimic the clinical workflow, a pre-operative CT as well as peri-operative ultrasound images at three different stages in the procedure (Stage 0-following intubation; Stage 1-following lung deflation; and Stage 2-following thoracic insufflation) were acquired during the experiment. Following image acquisition, a rigid-body registration using iterative closest point algorithm with the robust estimator was employed to map the pre-operative stage to each of the peri-operative ones, to estimate the heart migration and predict the peri-operative target vessel location. Moreover, a clinical validation of this technique was conducted using offline patient data, where a Monte Carlo simulation was used to overcome the limitations arising due to the invisibility of the target vessel in the peri-operative ultrasound images. Results: For the in vitro study, the computed target registration error (TRE) at Stage 0 , Stage 1 , and Stage 2 was 2.1, 3.3, and 2.6 mm, respectively. According to the offline clinical validation study, the maximum TRE at the left anterior descending (LAD) coronary artery was 4.1 mm at Stage 0 , 5.1 mm at Stage 1 , and 3.4 mm at Stage 2. Conclusions: The authors proposed a method to measure and validate peri-operative shifts of the heart during RA-CABG. In vitro and clinical validation studies were conducted and yielded a TRE in the order of 5 mm for all cases. As the desired clinical accuracy imposed by this procedure is on the order of one intercostal space (10-15 mm), our technique suits the clinical requirements. The authors therefore believe this technique has the potential to improve the pre-operative planning by updating peri-operative migration patterns of the heart and, consequently, will lead to reduced conversion to conventional open thoracic procedures. V

Objective For robot-assisted coronary artery bypass graft interventions, surgeons typically use a preoperative thoracic computed tomography scan of the patient to plan the procedure. However, the cardiac anatomy is prone to changes induced perioperatively in the effort to access the heart and surgical targets, which, in turn, may invalidate the initial plan. This article presents a method to estimate the perioperative heart migration, information which can be further exploited to refine the preoperative surgical plan. Methods Tracked transesophageal ultrasound images of four patients’ hearts were acquired at each stage in the procedure: before lung deflation, after lung deflation, and after both lung deflation and CO2 thoracic insufflation. Anatomic features of interest—the mitral and aortic valves—were identified from each dataset, and their movement between the different procedure stages was recorded and used to estimate the global heart displacement. Moreover, the local morphology of the features of interest was investigated to provide insight on the extent of the deformation the heart has undergone during the workflow. Results The study suggested that the heart does undergo substantial displacement—on the order of 10 to 15 mm in each direction (axial, coronal, and sagittal) after lung deflation and CO2 thoracic insufflation. However, no significant differences (P > 0.1) were observed in the morphologic characteristics of the features of interest across the multiple workflow stages, suggesting that local deformations occur at a much smaller scale compared with the global migration. Conclusions The quantification of the perioperatively induced changes is critical to track the displacement of the heart and surgical targets. The recorded migration patterns should not be ignored but rather be used to update the surgical plan to better suit the intraoperative environment.