Reproducibility and repeatability of a semi-automated pipeline to quantify trapeziometacarpal joint angles using dynamic computed tomography

Background

The trapeziometacarpal (TMC) joint is a mechanically complex joint and is commonly affected by musculoskeletal diseases such as osteoarthritis. Quantifying in vivo TMC joint biomechanics, such as joint angles, with traditional reflective marker-based methods can be difficult due to the joint’s location in the hand. Dynamic computed tomography (CT) can facilitate the quantification of TMC joint motion by continuously capturing three-dimensional volumes over time. However, post-processing of dynamic CT datasets can be time intensive and automated methods are needed to reduce processing times to allow for application to larger clinical studies. The purpose of this work is to introduce a fast, semi-automated pipeline to quantify joint angles from dynamic CT scans of the TMC joint and evaluate the associated error in joint angle and translation computation by means of a reproducibility and repeatability study.

Methods

Ten cadaveric hands were scanned with dynamic CT using a passive motion device to move thumbs in a radial abduction–adduction motion. Static CT scans and high-resolution peripheral quantitative CT scans were also acquired to generate high-resolution bone meshes. Abduction–adduction, flexion–extension, and axial rotation angles were computed using a joint coordinate system. Reproducibility and repeatability were assessed using intraclass correlation coefficients, Bland–Altman analysis, and root mean square errors. Target registration errors were computed to evaluate errors associated with image registration.

Results

We found good repeatability for flexion–extension, abduction–adduction, and axial rotation angles. Reproducibility was moderate for all three angles. Joint translations exhibited greater repeatability than reproducibility. Specimens with greater joint degeneration had lower repeatability and reproducibility. We found that the difference in resulting joint angles and translations were likely due to differences in segment coordinate system definition between multiple raters, rather than due to registration errors.

Conclusions

The proposed semi-automatic processing pipeline was fast, repeatable, and moderately reproducible when quantifying TMC joint angles and translations. This work provides a range of errors for TMC joint angles from dynamic CT scans using manually selected anatomical landmarks.

Frameless Stereotactic Biopsy with Intraoperative Computed Tomography "Assessment of Efficacy and Real Target Registration Error"

Frameless stereotactic brain biopsy (FSB) with navigation system has been widely used. We reported preliminary experience of FSB with intraoperative computed tomography (iCT) and examined the usefulness of this novel adjuvant technique and real target registration error (rTRE) of FSB. The FSB with 5-aminolevulinic acid (5-ALA) and iCT was performed on 10 patients. The gadolinium-enhanced lesions on magnetic resonance image were defined as the biopsy target. In the procedure, iCTs were scanned twice, for autoregistration of the navigation system and for confirmation of the position of the actual inserted biopsy needle. The red fluorescence of the samples was observed under excitation with violet-blue light through a low-cut filter of neurosurgical microscope. The distance between the planned target and the tip of the biopsy needle in the image of iCT was calculated in a workstation for the assessment of rTRE. The median volume of the target was 12.13 mL (0.06-39.15 mL). We performed the surgical procedure in a prone position in four patients. None to faint 5-ALA-induced fluorescence was observed in six samples. There existed no sampling errors. The mean target distance between the planned and real targets of the mean rTRE of FSB was 2.7 ± 0.56 mm.The real TRE of FSB was first reported and was larger than the reported rTRE exactly calculated from the fiducial registration error. iCT guarantees accurate tumor sampling with autoregistration regardless of the surgical position and prevents inaccurate biopsy to occur even with ALA fluorescence assistance.

Fluoroscopy-guided robotic biopsy intervention system

Fluoroscopy-guided percutaneous biopsy interventions are mostly performed with traditional free-hand technique. The practical experience of the surgeon influences the duration of the intervention and the radiation exposure for patients and him-/herself. Especially when the placement of heavy and long instruments in double oblique angles is required, manual techniques reach their technical limitations very fast. The system presented herein automatizes the needle positioning using only two 2D scans while the robotic platform guides the intervention. These two images were used to plan the needle pathway and to estimate the pose of the robot using a custom-made end-effector with embedded registration fiducials. The estimated pose was subsequently used to transfer the planed needle path to the robot’s coordinate system and finally to compute the movement parameters in order to align the robot with this plan. To evaluate the system, two phantoms with 11 different targets on it were developed. The targets were punctured, and the application accuracy was measured quantitatively. The solution achieved sub-millimetric accuracy for needle placement (min. 0.23, max. 1.04 in mm). Our approach combines the advantages of fluoroscopic imaging and ensures automatic needle alignment with highly reduced X-ray radiation. The proposed system shows promising potential to be a guidance platform that is easy to combine with available fluoroscopic imaging systems and provides valuable help to the physician in more difficult interventions.

Multivariate analysis for the estimation of target localization errors in fiducial marker-based radiotherapy

PURPOSE

To assess the target localization error (TLE) in terms of the distance between the target and the localization point estimated from the surrogates (|TMD|), the average of respiratory motion for the surrogates and the target (|aRM|), and the number of fiducial markers used for estimating the target (n).

METHODS

This study enrolled 17 lung cancer patients who subsequently underwent four fractions of real-time tumor tracking irradiation. Four or five fiducial markers were implanted around the lung tumor. The three-dimensional (3D) distance between the tumor and markers was at maximum 58.7 mm. One of the markers was used as the target (Pt), and those markers with a 3D |TMDn| ≤ 58.7 mm at end-exhalation were then selected. The estimated target position (Pe) was calculated from a localization point consisting of one to three markers except Pt. Respiratory motion for Pt and Pe was defined as the root mean square of each displacement, and |aRM| was calculated from the mean value. TLE was defined as the root mean square of each difference between Pt and Pe during the monitoring of each fraction. These procedures were performed repeatedly using the remaining markers. To provide the best guidance on the answer with n and |TMD|, fiducial markers with a 3D |aRM ≥ 10 mm were selected. Finally, a total of 205, 282, and 76 TLEs that fulfilled the 3D |TMD| and 3D |aRM| criteria were obtained for n = 1, 2, and 3, respectively. Multiple regression analysis (MRA) was used to evaluate TLE as a function of |TMD| and |aRM| in each n.

RESULTS

|TMD| for n = 1 was larger than that for n = 3. Moreover, |aRM| was almost constant for all n, indicating a similar scale for the marker's motion near the lung tumor. MRA showed that |aRM| in the left-right direction was the major cause of TLE; however, the contribution made little difference to the 3D TLE because of the small amount of motion in the left-right direction. The TLE calculated from the MRA ((MRA)TLE) increased as |TMD| and |aRM| increased and adversely decreased with each increment of n. The median 3D (MRA)TLE was 2.0 mm (range, 0.6-4.3 mm) for n = 1, 1.8 mm (range, 0.4-4.0 mm) for n = 2, and 1.6 mm (range, 0.3-3.7 mm) for n = 3. Although statistical significance between n = 1 and n = 3 was observed in all directions, the absolute average difference and the standard deviation of the (MRA)TLE between n = 1 and n = 3 were 0.5 and 0.2 mm, respectively.

CONCLUSIONS

A large |TMD| and |aRM| increased the differences in TLE between each n; however, the difference in 3D (MRA)TLEs was, at most, 0.6 mm. Thus, the authors conclude that it is acceptable to continue fiducial marker-based radiotherapy as long as |TMD| is maintained at ≤58.7 mm for a 3D |aRM|  ≥  10 mm.

Introduction: Intraoperative spinal imaging and navigation

Image-guided surgery (IGS) has been evolving since the early 1990s and is now used on a daily basis in the operating theater for spine surgery at many institutions. In the last 5 years, spinal IGS has greatly benefitted from important enhancements including portable intraoperative CT (iCT) coupled with high-speed computerized stereotactic navigation systems and optical-based camera tracking technology.

An on-board surgical tracking and video augmentation system for C-arm image guidance

PURPOSE

Conventional tracker configurations for surgical navigation carry a variety of limitations, including limited geometric accuracy, line-of-sight obstruction, and mismatch of the view angle with the surgeon's-eye view. This paper presents the development and characterization of a novel tracker configuration (referred to as "Tracker-on-C") intended to address such limitations by incorporating the tracker directly on the gantry of a mobile C-arm for fluoroscopy and cone-beam CT (CBCT).

METHODS

A video-based tracker (MicronTracker, Claron Technology Inc., Toronto, ON, Canada) was mounted on the gantry of a prototype mobile isocentric C-arm next to the flat-panel detector. To maintain registration within a dynamically moving reference frame (due to rotation of the C-arm), a reference marker consisting of 6 faces (referred to as a "hex-face marker") was developed to give visibility across the full range of C-arm rotation. Three primary functionalities were investigated: surgical tracking, generation of digitally reconstructed radiographs (DRRs) from the perspective of a tracked tool or the current C-arm angle, and augmentation of the tracker video scene with image, DRR, and planning data. Target registration error (TRE) was measured in comparison with the same tracker implemented in a conventional in-room configuration. Graphics processing unit (GPU)-accelerated DRRs were generated in real time as an assistant to C-arm positioning (i.e., positioning the C-arm such that target anatomy is in the field-of-view (FOV)), radiographic search (i.e., a virtual X-ray projection preview of target anatomy without X-ray exposure), and localization (i.e., visualizing the location of the surgical target or planning data). Video augmentation included superimposing tracker data, the X-ray FOV, DRRs, planning data, preoperative images, and/or intraoperative CBCT onto the video scene. Geometric accuracy was quantitatively evaluated in each case, and qualitative assessment of clinical feasibility was analyzed by an experienced and fellowship-trained orthopedic spine surgeon within a clinically realistic surgical setup of the Tracker-on-C.

RESULTS

The Tracker-on-C configuration demonstrated improved TRE (0.87 ± 0.25) mm in comparison with a conventional in-room tracker setup (1.92 ± 0.71) mm (p < 0.0001) attributed primarily to improved depth resolution of the stereoscopic camera placed closer to the surgical field. The hex-face reference marker maintained registration across the 180° C-arm orbit (TRE = 0.70 ± 0.32 mm). DRRs generated from the perspective of the C-arm X-ray detector demonstrated sub- mm accuracy (0.37 ± 0.20 mm) in correspondence with the real X-ray image. Planning data and DRRs overlaid on the video scene exhibited accuracy of (0.59 ± 0.38) pixels and (0.66 ± 0.36) pixels, respectively. Preclinical assessment suggested potential utility of the Tracker-on-C in a spectrum of interventions, including improved line of sight, an assistant to C-arm positioning, and faster target localization, while reducing X-ray exposure time.

CONCLUSIONS

The proposed tracker configuration demonstrated sub- mm TRE from the dynamic reference frame of a rotational C-arm through the use of the multi-face reference marker. Real-time DRRs and video augmentation from a natural perspective over the operating table assisted C-arm setup, simplified radiographic search and localization, and reduced fluoroscopy time. Incorporation of the proposed tracker configuration with C-arm CBCT guidance has the potential to simplify intraoperative registration, improve geometric accuracy, enhance visualization, and reduce radiation exposure.

Surface-based facial scan registration in neuronavigation procedures: a clinical study

OBJECT

Surface-based registration (SBR) with facial surface scans has been proposed as an alternative for the commonly used fiducial-based registration in image-guided neurosurgery. Recent studies comparing the accuracy of SBR and fiducial-based registration have been based on a few targets located on the head surface rather than inside the brain and have yielded contradictory conclusions. Moreover, no visual feedback is provided with either method to inform the surgeon about the estimated target registration error (TRE) at various target locations. The goals in the present study were: 1) to quantify the SBR error in a clinical setup, 2) to estimate the targeting error for many target locations inside the brain, and 3) to create a map of the estimated TRE values superimposed on a patient's head image.

METHODS

The authors randomly selected 12 patients (8 supine and 4 in a lateral position) who underwent neurosurgery with a commercial navigation system. Intraoperatively, scans of the patients' faces were acquired using a fast 3D surface scanner and aligned with their preoperative MR or CT head image. In the laboratory, the SBR accuracy was measured on the facial zone and estimated at various intracranial target locations. Contours related to different TREs were superimposed on the patient's head image and informed the surgeon about the expected anisotropic error distribution.

RESULTS

The mean surface registration error in the face zone was 0.9 +/- 0.35 mm. The mean estimated TREs for targets located 60, 105, and 150 mm from the facial surface were 2.0, 3.2, and 4.5 mm, respectively. There was no difference in the estimated TRE between the lateral and supine positions. The entire registration procedure, including positioning of the scanner, surface data acquisition, and the registration computation usually required < 5 minutes.

CONCLUSIONS

Surface-based registration accuracy is better in the face and frontal zones, and error increases as the target location lies further from the face. Visualization of the anisotropic TRE distribution may help the surgeon to make clinical decisions. The observed and estimated accuracies and the intraoperative registration time show that SBR using the fast surface scanner is practical and feasible in a clinical setup.

Application accuracy in frameless image-guided neurosurgery: a comparison study of three patient-to-image registration methods

Object

The aim of this study was to compare three patient-to-image registration methods in frameless stereotaxy in terms of their application accuracy (the accuracy with which the position of a target can be determined intraoperatively). In frameless stereotaxy, imaging information is transposed to the surgical field to show the spatial position of a localizer or surgical instrument. The mathematical relationship between the image volume and the surgical working space is calculated using a rigid body transformation algorithm, based on point-pair matching or surface matching.

Methods

Fifty patients who were scheduled to undergo a frameless image-guided neurosurgical procedure were included in the study. Prior to surgery, the patients underwent either computerized tomography (CT) scanning or magnetic resonance (MR) imaging with widely distributed adhesive fiducial markers on the scalp. An extra fiducial marker was placed on the head as a target, as near as possible to the intracranial lesion. Prior to each surgical procedure, an optical tracking system was used to perform three separate patient-to-image registration procedures, using anatomical landmarks, adhesive markers, or surface matching. Subsequent to each registration, the target registration error (TRE), defined as the Euclidean distance between the image space coordinates and world space coordinates of the target marker, was determined.

Independent of target location or imaging modality, mean application accuracy (± standard deviation) was 2.49 ± 1.07 mm when using adhesive markers. Using the other two registration strategies, mean TREs were significantly larger (surface matching, 5.03 ± 2.30 mm; anatomical landmarks, 4.97 ± 2.29 mm; p < 0.001 for both).

Conclusions

The results of this study show that skin adhesive fiducial marker registration is the most accurate noninvasive registration method. When images from an earlier study are to be used and accuracy may be slightly compromised, anatomical landmarks and surface matching are equally accurate alternatives.

Image-guided surgery and medical robotics in the cranial area

Surgery in the cranial area includes complex anatomic situations with high-risk structures and high demands for functional and aesthetic results. Conventional surgery requires that the surgeon transfers complex anatomic and surgical planning information, using spatial sense and experience. The surgical procedure depends entirely on the manual skills of the operator. The development of image-guided surgery provides new revolutionary opportunities by integrating presurgical 3D imaging and intraoperative manipulation. Augmented reality, mechatronic surgical tools, and medical robotics may continue to progress in surgical instrumentation, and ultimately, surgical care. The aim of this article is to review and discuss state-of-the-art surgical navigation and medical robotics, image-to-patient registration, aspects of accuracy, and clinical applications for surgery in the cranial area.

In vivo accuracy of image guidance performed using optical tracking and optimized registration

Object

Image guidance systems involving the use of frameless referencing of surgical space to compile volumetric imaging data sets recently have come into widespread use. Few studies have addressed the true intraoperative surgical accuracy (that is, the application accuracy) of these systems except in a subjective manner. Calculated accuracies given by the systems do not necessarily reflect true intraoperative accuracy.

Methods

To objectively assess the stereotactic accuracy of a frameless image guidance system using optical spatial referencing, the author analyzed postoperative magnetic resonance (MR) images after placement of depth electrodes for the investigation of epilepsy. Preoperative planning for the treatment of seven patients included implanting skull fiducial screws and obtaining computed tomography/MR fusion images by using ImMerge image fusion software on the StealthStation (Medtronic, Inc.). A total of 42 electrodes were placed. Postoperative volumetric MR images were fused with preoperative study images. The difference between the planned electrode trajectories and targets and the visualized electrodes was measured in stereotactic space.

Conclusions

The mean distance between the distal electrode contact and the distal end of the planned trajectory for the 42 targets was 3 ± 1.5 mm. The most common error was in depth. The author’s technique did not involve rigid skull fixation of electrodes because they were subsequently tunneled subcutaneously and later removed at the bedside of the patient. Errors in depth were known to be due to traction at the time of tunneling and not due to stereotactic factors. Correcting for depth along the electrode trajectory, the mean accuracy was found to be 2.4 ± 1 mm.

Evaluation of registration techniques for spinal image guidance

Object

Paired point matching alone and paired point matching combined with surface matching are the two techniques used for the registration step in preoperative computerized tomography–based spinal image guidance. In the present study the authors sought to compare paired point–matching registration alone with paired point matching supplemented with surface matching to determine if the addition of surface matching improves navigational accuracy.

Methods

Pedicle screws were placed in three embalmed human cervicothoracic spinal specimens during image guidance to serve as a reference points. The specimens were then rescanned, and each level was registered using paired point matching alone and then by paired point supplemented with surface matching. Navigational accuracy was assessed by placing the stereotactic probe in the center of the screw head, and measuring the apparent distance between the screw head and probe on the computer monitor. Statistical analysis was used to compare the registration error and navigational error between the two techniques.

Seventy-five screws were placed at 46 vertebral levels. The mean registration error for the paired point matching/surface matching technique (0.5 mm) was significantly lower (p < 0.001) than that of the paired point matching alone technique (1.2 mm); however, the intertechnique difference in navigational error was nearly equivalent (1.3 mm compared with 1.4 mm) and statistically insignificant (p > 0.05).

Conclusions

Although the addition of surface matching to paired point registration significantly decreased the mean registration error, the actual navigational accuracy between the two techniques was equivalent when easily distinguishable points were meticulously selected. The use of paired point matching alone did not compromise the accuracy of navigation and is likely to result in decreased operating time.

Evaluation of a Rigid Registration Method of Lung Perfusion SPECT and Thoracic CT

OBJECTIVE

The objective of our study was to evaluate a rigid registration method in lung perfusion SPECT using thoracic CT as a standard.

MATERIALS AND METHODS

The reproducibility of markers selection and the robustness of the method were assessed on a torso phantom. The accuracy of registration regarding the number and location of markers and the breathing state during CT was evaluated on eight patients using 10 external markers placed around the thorax before SPECT and CT acquisitions. The accuracy of registration was assessed using the mean errors (ME) between 10 markers after registration.

RESULTS

Registration using external markers on a phantom was accurate (ME, < 3 mm) when rotation was less than 40 degrees (p = 0.02). The accuracy of registration improved markedly from four to six markers for phantom (5.5-3.6 mm) and patients (11.2-9.5 mm) and then remained constant up to 10 markers. The ME was less when using markers that well encompassed the thorax for phantom and patients (p = 0.02 and p = 0.05, respectively). The use of four anatomic markers was not accurate (ME, 20 mm).

CONCLUSION

The registration method is reproducible and accurate, and six external markers were required to get an ME of less than 10 mm in patients.

Frameless stereotaxy using bone fiducial markers for deep brain stimulation

OBJECT

Functional neurosurgical interventions such as deep brain stimulation (DBS) are traditionally performed with the aid of a stereotactic frame. Although frameless techniques have been perceived as less accurate, data from a recent phantom study of a modified frameless approach demonstrated a laboratory accuracy exceeding that obtained using a common frame system. The present study was conducted to evaluate the accuracy of a frameless system in routine clinical use.

METHODS

Deep brain stimulation leads were implanted in 38 patients by using a skull-mounted trajectory guide and an image-guided workstation. Registration was accomplished with bone fiducial markers. Final lead positions were measured on postoperative computerized tomography scans and compared with the planned lead positions. The accuracy of the Leksell frame within the clinical situation has been reported on in a recent study; these raw data served as a comparison data set. The difference between expected and actual lead locations in the x plane was 1.4 mm in the frame-based procedure and 1.6 mm in the frameless procedure. Similarly, the difference in the y plane was 1.6 mm in the frame-based system and 1.3 mm in the frameless one. The error was greatest in the z plane, that is, 1.7 mm in the frame-based method and 2 mm in the frameless system. Multivariate analysis of variance demonstrated no statistically significant difference in the accuracy of the two methods.

CONCLUSIONS

The accuracy of the frame-based and frameless systems was not statistically significantly different (p = 0.22). Note, however, that frameless techniques offer advantages in patient comfort, separation of imaging from surgery, and decreased operating time.