Recent trends in total hip arthroplasty (THA) have resulted in the use of larger acetabular components to achieve larger femoral head sizes to reduce dislocation, and improve range of motion and stability. Such practices can result in significant acetabular bone loss at the time of index THA, increasing risk of anterior/posterior wall compromise, reducing component coverage, component fixation, ingrowth surface and bone stock for future revision surgery. We report here on the effects of increasing acetabular reaming on component coverage and bone loss in a radiographic CT scan based computer model system. A total of 74 normal cadaveric pelves with nonarthritic hip joints underwent thin slice CT scan followed by upload of these scans into the FDA approved radiographic analysis software. Utilizing this software package, baseline three-dimensional calculations of femoral head size and acetabular size were obtained. The software was used to produce a CT scan based model that would simulate reaming and placement of acetabular components in these pelves that were 125, 133 and 150% the size of the native femoral head. Calculations were made of cross sectional area bone loss from anterior/posterior columns, and loss of component coverage with increasing size.INTRODUCTION:
METHODS:
Previous modalities such as static x-rays, MRI scans, CT scans and fluoroscopy have been used to diagnosis both soft-tissue clinical conditions and bone abnormalities. Each of these diagnostic tools has definite strengths, but each has significant weaknesses. The objective of this study is to introduce two new diagnostic, ultrasound and sound/vibration sensing, techniques that could be utilized by orthopaedic surgeons to diagnose injuries, defects and other clinical conditions that may not be detected using the previous mentioned modalities. A new technique has been developed using ultrasound to create three-dimensional (3D) bones and soft-tissues at the articulating surfaces and ligaments and muscles across the articulating joints (Figure 1). Using an ultrasound scan, radio frequency (RF) data is captured and prepared for processing. A statistical signal model is then used for bone detection and bone echo selection. Noise is then removed from the signal to derive the true signal required for further analysis. This process allows for a contour to be derived for the rigid body of questions, leading to a 3D recovery of the bone. Further signal processing is conducted to recover the cartilage and other soft-tissues surrounding the region of interest. A sound sensor has also been developed that allows for the capture of raw signals separated into vibration and sound (Figure 2). A filtering process is utilized to remove the noise and then further analysis allows for the true signal to be analyzed, correlating vibrational signals and sound to specific clinical conditions.INTRODUCTION:
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Medial unicompartmental knee arthroplasty (UKA) for isolated medial knee arthritis is a highly successful and efficacious procedure. However, UKA is technically more challenging than total knee arthroplasty (TKA). Research has shown that surgical technical errors may lead to high early failure rates. Haptic robotic systems have recently been developed with the goal of improving accuracy, reducing complications, and improving overall outcomes. There is little research comparing robotic-assisted UKA to standard UKA. The goal of this study was to compare clinical and radiographic data for matched cohorts who received robotic-arm assisted UKA or standard instrumentation UKA. We performed a non-randomised, retrospective review of 30 robotic-arm assisted UKA and 32 manual UKA performed by single fellowship-trained joint arthroplasty surgeon (SKK) over 2.5 years. All procedures completed through a medial parapatellar approach. All components were cemented. All tibial components were a metal-backed onlay design. Average follow-up was 10.1 months (range 5–36). A full clinical/hospital chart review of demographic, intra- and post-operative measures was performed. Radiographic analysis of pre- and post-op images evaluating sagital and coronal alignment, and component positioning was performed by single observer (DCH), using OsiriX imaging system (Pixmeo; Geneva, Switzerland). Radiographs were available for analysis in 28 robotic-assisted and 30 manual patients. Statistical analysis was performed using SPSS v. 20. Comparison between group means was performed as well as calculation of variance in component placement within groups. No demographic differences were seen between groups. Operative time was significantly longer in robotic-assisted UKA compared to the manual group. Minimal clinical post-op differences were seen between groups. The robotic group showed some early advantage in ambulation/ROM during inpatient stay. This ROM difference reversed at 2 weeks post-op. Continued medial-sided knee pain was reported more commonly in robotic group. Radiographic results showed no difference between groups in pre-op mechanical alignment. The robotic group was significantly more accurate at recreating femoral axis. Accuracy in recreation of tibial slope/ was similar between groups. Accuracy of the tibial component in the coronal plane was not significantly different between groups. The robotic group did have significantly larger variance in coronal alignment of the tibial component. Medial overhang of tibial component was significantly greater and more variable in the manual group. Non-significant decrease in resection depth found in robotic group. There were minimal clinical and radiographic differences between techniques. Clinically, both cohorts did very well. Radiographically, both groups had quite accurate placement of components, with the most obvious difference being the increased tibial component overhang in the manual group. The increased variance in tibial component alignment in the robotic group is likely due to the ability to more specifically alter the resection to fit the patient's specific anatomy. Overall, our data suggests that the purported benefits of robotic UKA may be obviated in the hands of a surgeon with training and experience in manual UKA implantation.
The low-cost, no-harm conditions associated with vibroarthography, the study of listening to the vibrations and sound patterns of interaction at the human joints, has made this method a promising tool for diagnosing joint pathologies. This current study focuses on the knee joint and aims to synchronize computational models with vibroarthographic signals via a comprehensive graphical user interface (GUI) to find correlations between kinematics, vibration signals, and joint pathologies. This GUI is the first of its kind to synchronize computational models with vibroarthographic signals and gives researchers a new advantage of analyzing kinematics, vibration signals, and pathologies simultaneously in an easy-to-use software environment. The GUI (Figure 1) has the option to view live or previously captured fluoroscopic videos, the corresponding computational model, and/or the pre- or post-processed vibration signals. Having more than one signal axes available allows for comparison of different filtering techniques to the same signal, or comparison of signals coming from different sensor placements (ex: medial vs. lateral femoral condyle). Using computational models derived using fluoroscopic data synchronized with the vibration signals, the areas of contact between articulating surfaces can be mapped for the in vivo signal (figure 2). This new method gives the opportunity to find correlations between the different sensor signals and contact maps with the diagnosis and cartilage degeneration map, provided by a surgeon, during arthroscopy or TKA implantation (figure 3).Introduction
Methods
Anterior knee pain is one of the most frequently reported musculoskeletal complaints in all age groups. However, patient's complaints are often nonspecific, leading to difficulty in properly diagnosing the condition. One of the causes of pain is the degeneration of the articular cartilage. As the cartilage deteriorates, its ability to distribute the joint reaction forces decreases and the stresses may exceed the pain threshold. Unfortunately, the assessment of the cartilage condition is often limited to a detailed interview with the patient, careful physical examination and x-ray imaging. The X-ray screening may reveal bone degeneration, but does not carry sufficient information of the soft tissues' conditions. More advanced imaging tools such as MRI or CT are available, but these are expensive, time consuming and are only suitable for detection of advanced arthritis. Arthroscopic surgery is often the only reliable option, however due to its semi-invasive nature, it cannot be considered as a practical diagnostic tool. However, as the articular cartilage degenerates, the surfaces become rougher, they produce higher vibrations than smooth surfaces due to higher friction during the interaction. Therefore, it was proposed to detect vibrations non-invasively using accelerometers, and evaluate the signals for their potential diagnostic applications. Vibration data was collected for 75 subjects; 23 healthy and 52 subjects suffering from knee arthritis. The study was approved by the IRB and an Informed Consent was obtained prior to data collection. Five accelerometers were attached to skin around the knee joint (at the patella, medial and lateral femoral condyles, tibial tuberosity and medial tibial plateau). Each subject performed 5 activities; (1) flexion-extension, (2) deep knee bend, (3) chair rising, (4) stair climbing and (5) stair descent. The vibration and motion components of the signals were separated by a high pass filter. Next, 33 parameters of the signals were calculated and evaluated for their discrimination effectiveness (Figure 1). Finally the pattern recognition method based on Baysian classification theorem was used for classify each signal to either healthy or arthritic group, assuming equal prior probabilities. The variance and mean of the vibration signals were significantly higher in the arthritic group (p=2.8e-7 and p=3.7e-14, respectively), which confirms the general hypothesis that the vibration magnitudes increase as the cartilage degenerates. Other signal features providing good discrimination included the 99th quantile, the integral of the vibration signal envelope, and the product of the signal envelope and the activity duration. The pattern classification yielded excellent results with the success rate of up to 92.2% using only 2 features, up to 94.8% using 3 (Figure 2), and 96.1% using 4 features. The current study proved that the vibrations can be studied non-invasively using a low-cost technology. The results confirmed the hypothesis that the degeneration of the cartilage increases the vibration of the articulating bones. The classification rate obtained in the study is very encouraging, providing over 96% accuracy. The presented technology has certainly a potential of being used as an additional screening methodology enhancing the assessment of the articular cartilage condition.
In this work, we present the first real-time fully automatic system for reconstruction of patient-specific 3D knee bones models using ultrasound raw RF data. The system was experimented on two cadaveric knees, and reconstruction accuracy of 2 mm was achieved. To use the highest available contrast and spatial resolution in the ultrasound data, the raw RF signals were used directly to automatically extract the bone contours from the ultrasound scans. Figure 1 shows a sample ultrasound B-mode image for cadaver's distal femur, showing some of the scan lines raw RF signals as well as the final extracted contour using our method. An ultrasound machine (SonixRP, Ultrasonix Inc) was used to scan the knee joint and the RF data of the scans are acquired by custom-built (using Visual C++) software running on the ultrasound machine. An optical tracker (Polaris Spectra, Northern Digital Inc) was attached to the ultrasound probe to track its motion while being used in scanning. The scanning of the knee was performed at two flexion angles (full extension, and deep knee bend). At each position, the knee was fixed in order to collect scans that represent a partial surface of the bone (which will be later mutually registered to represent the whole bone's surface). Figure 4 shows fluoroscopy images of a patient's knee, showing the different articulating surfaces of the knee bones visible to the ultrasound at different flexion angles. Figure 5 shows a dissected cadaver's knee showing the articulating surfaces visible to ultrasound at 90 degrees flexion. The custom-built software collects the RF data synchronized with the probe tracking data for each ultrasound frame. Each frame of the RF data is then processed to extract the bone contour. The bone contours are automatically extracted from the RF data frame with frame rate of 25 frames per second. Figure 2 shows a flowchart for the contour extraction process. The extracted bone contours were then used by the our software, along with the ultrasound probe's tracking data, to reconstruct point clouds representing the bones' surfaces. These point clouds were then aligned to the mean model of the bone's atlas using ICP and integrated together to form 3D point cloud of the bone's surface. A 3D model of the bone is then reconstructed by morphing the mean model to match the point cloud. Figure 3 shows a flowchart for the point cloud and 3D model reconstruction process.Introduction
Methods
Great disparity appears in the literature regarding the occurrence of minor and major complications after two-incision total hip arthroplasty (THA). Advocates of twoincision THA contend that this minimally invasive surgical (MIS) technique provides faster rehabilitation with fewer restrictions and financial advantages stemming from shorter hospital stays and quicker returns to work. These advantages, however, cannot be fully realized unless the procedure can be performed within acceptable risk levels. The operative, perioperative, and postoperative complications of a consecutive series of 200 two-incision THAs from a single surgeon were analyzed. Of the 8 femur fractures which occurred in this series, four occurred intraoperatively. All four were nondisplaced and treated with a cerclage cable through the anterior incision. The prosthesis was retained in each case. Of the four postoperative fractures, two were nondisplaced, permitting retention of the prosthesis. These were treated with a trochanteric plate with wiring above and below the lesser trochanter. The other two postoperative fractures were displaced, necessitating revision to a longer, uncemented stem and cerclage wiring. Other complications in this series included two nondisplaced greater trochanter fractures >
2cm, 14 asymptomatic greater trochanter fractures ≤2 cm, one malpositioned cup requiring revision, one loose stem, seven cases of heterotopic ossification ≥Grade 2, four dislocations, one superficial infection, 80 lateral femoral cutaneous nerve neuropraxias (78 of which resolved within six weeks), and four femoral nerve neuropraxias (three of which resolved in 6 to 12 weeks). In this series, two-incision THA was performed with a low incidence of major complications but a high incidence of minor complications. Despite the minor complications, most patients experienced an accelerated recovery and rehabilitation owing to reduced tissue trauma. To help surgeons avoid complications, we recommend periodic retraining sessions where concerns and pitfalls can be addressed and recent enhancements, taught. Superficial nerve complications, such as those encountered in high numbers in this series, can be avoided by moving the anterior incision slightly lateral and splitting the fibers of the tensor fascia lata. The risk of minor trochanteric fractures can be reduced by first lateralizing broach-only stems with a long straight 9mm reamer and/ or by using direct visualization.
Recent fluoroscopic analyses evaluating the kinematic function of TKAs have demonstrated significant variability among patients with identical implant designs, suggesting surgical technique also influences function. To help explain these kinematic variations, we used intraoperative compartment pressure sensors to assess balancing at trial reduction and ROM then correlated these intraoperative findings with patients’ postoperative kinematics, assessed using video fluoroscopy. This study involved 16 patients implanted with a posterior cruciate-sacrificing LCS TKA using a balanced gap technique. After releases in extension, the femur was rotated the appropriate amount to create a rectangular flexion gap relative to the cut tibial surface. As the knee was taken through a ROM from 0–120°, the sensors (placed on the tibial insert trial) dynamically measured the magnitude and location of compartment pressures throughout the ROM. Six to nine months postoperatively, all patients performed successive weight-bearing deep knee bends to maximum flexion under fluoroscopic surveillance. Each patient’s femoro-tibial contact positions and liftoff values were compared to their respective intraoperative compartment pressure findings to establish correlations. Fluoroscopic results correlated closely with intraoperative compartment pressures and balance data. Three of the 16 patients had condylar liftoff: two patients experienced liftoff in flexion and one in extension (medial). The patient who experienced medial liftoff in extension had decreased medial compartment pressure and a slight valgus malalignment (7° of anatomic alignment). Two of the 13 patients without liftoff had abnormal compartment pressures in extension. In both cases, mechanical axis alignment resulted in loading of the lax compartment with weight-bearing. The other 11 patients had normal compartment pressures in extension and no condylar liftoff. One of these patients had slight valgus (7°) and another slight varus malalignment (4°), but both had normal compartment pressures. Despite good compartment balance, average tibiofemoral rotation was inadequate; three of 16 patients experienced opposite axial rotation with flexion. Extensive ligament release did not always result in equal compartment pressure magnitudes and distributions; compartment balance was influenced by the nature of the release. These data suggest that liftoff may require both a compartment pressure imbalance and abnormal alignment that together exacerbate the laxity with physiologic loading. Previous kinematic studies of LCS knees have shown that the balanced gap technique produces wellbalanced compartment pressures, resulting in TKAs with little lift-off and very good translational and rotational characteristics. Therefore, while a given implant design may have inherent kinematic tendencies, surgical technique may significantly impact kinematic performance. To optimize implant kinematics and subsequent TKA function and longevity, it may be important for surgeons to accurately balance the flexion and extension gaps. Characteristic compartment pressure patterns and distributions for various ligament releases may shed some light on less than optimal rotational kinematic performance.
