The number of joint revision surgeries is rising, and the complexity of the cases is increasing. In 58% of the revision cases, the acetabular component has to be revised. For these indications, literature decision schemes [Paprosky 2005] point at custom pre-shaped implants. Any standard device would prove either unfeasible during surgery or inadequate in the short term. Studies show that custom-made triflanged implants can be a durable solution with good clinical results. However, the number of cases reported is few confirming that the device is not in widespread use. Case Report. A patient, female 50 yrs old, diagnosed having a pseudotumor after Resurfacing Arthroplasty for osteo-arthritis of the left hip joint. The revision also failed after 1 y and she developed a pelvic discontinuity. X-ray and Ct scans were taken and sent to a specialized implant manufacturer [Mobelife, Leuven, Belgium]. The novel process of patient-specific implant design comprises three highly automated steps. In the first step, advanced 3D image processing presented the bony structures and implant components. Analysis showed that anterior column was missing, while the posterior column was degraded and fractured. The acetabular defect was diagnosed being Paprosky 3B. The former acetabular component migrated in posterolateral direction resulting in luxation of the joint. The reconstruction proposal showed the missing bone stock and anatomical joint location. In the second step, a triflanged custom acetabular metal backing implant was proposed. The bone defect (35ml) is filled with a patient-specific porous structure which is rigidly connected to a solid patient-specific plate. The proposed implant shape is determined taking into account surgical window and surrounding soft tissues. Cup orientation is anatomically analyzed for inclination and anteversion. A cemented liner fixation was preferred (Biomet Advantage 48mm). Screw positions and lengths are pre-operatively planned depending on bone quality, and transferred into surgery using jig guiding technology (Materialise NV, Leuven, Belgium). In the third step, the implant design was evaluated in a fully patient-specific manner in dedicated engineering (FEA) software. Using the novel automated CT-based methodology, patient-specific bone quality and thickness, as well as individualised muscle attachments and muscle and joint forces were included in the evaluation. Implants and jig were produced with Additive Manufacturing techniques under ISO 13485 certification, using respectively Selective Laser Melting (SLM) techniques [Kruth 2005] in medical grade Ti6Al4V material, and the Selective Laser Sintering technique using medical grade epoxy monomer. The parts were cleaned ultrasonically, and quality control was performed by optical scanning [Atos2 scanning device, GOM Intl. AG, Wilden, Switzerland]. Sterilization is performed in the hospital. CONCLUSION. A unique combination of advanced 3D planning, patient-specific designed and evaluated implants and drill guides is presented. This paper illustrates, by means of a clinical case, the novel tools and devices that are able to turn reconstruction of complex acetabular deficiencies into a reliable procedure

Introduction. Although total knee arthroplasty (TKA) is generally considered successful, 16–30% of patients are dissatisfied. There are multiple reasons for this, but some of the most frequent reasons for revision are instability and joint stiffness. A possible explanation for this is that the implant alignment is not optimized to ensure joint stability in the individual patient. In this work, we used an artificial neural network (ANN) to learn the relation between a given standard cruciate-retaining (CR) implant position and model-predicted post-operative knee kinematics. The final aim was to find a patient-specific implant alignment that will result in the estimated post-operative knee kinematics closest to the native knee. Methods. We developed subject-specific musculoskeletal models (MSM) based on magnetic resonance images (MRI) of four ex vivo left legs. The MSM allowed for the estimation of secondary knee kinematics (e.g. varus-valgus rotation) as a function of contact, ligament, and muscle forces in a native and post-TKA knee. We then used this model to train an ANN with 1800 simulations of knee flexion with random implant position variations in the ±3 mm and ±3° range from mechanical alignment. The trained ANN was used to find the implant alignment that resulted in the smallest mean-square-error (MSE) between native and post-TKA tibiofemoral kinematics, which we term the dynamic alignment. Results. Dynamic alignment average MSE kinematic differences to the native knees were 1.47 mm (± 0.89 mm) for translations and 2.89° (± 2.83°) for rotations. The implant variations required were in the range of ±3 mm and ±3° from the starting mechanical alignment. Discussion. In this study we showed that the developed tool has the potential to find an implant position that will restore native tibiofemoral kinematics in TKA. The proposed method might also be used with other alignment strategies, such as to optimize implant position towards native ligament strains. If native knee kinematics are restored, a more normal gait pattern can be achieved, which might result in improved patient satisfaction. The small changes required to achieve the dynamic alignment do not represent large modifications that might compromise implant survivorship. Conclusion. Patient-specific implant position predicted with MSM and ANN can restore native knee function in a post-TKA knee with a standard CR implant

Introduction:. Despite over 95% long-term survivorship of TKA, 14–39% of patients express dissatisfaction due to anterior knee pain, mid-flexion instability, reduction in range of flexion, and incomplete return of function. Changing demographics with higher expectations are leading to renewed interest in patient-specific designs with the goal of restoring of normal kinematics. Improved imaging and image-processing technology coupled with rapid prototyping allow manufacturing of patient-specific cutting guides with individualized femoral and tibial components with articulating surfaces that maximize bony coverage and more closely approximate the natural anatomy. We hypothesized that restoring the articular surface and maintaining medial and lateral condylar offset of the implanted knee to that of the joint before implantation would restore normal knee kinematics. To test this hypothesis we recorded kinematics of patient-specific prostheses implanted using patient-specific cutting guides. Methods:. Preoperative CT scans were obtained from nine matched pairs of human cadaveric knees. One of each pair was randomly assigned to one of two groups: one group implanted with a standard off-the-shelf posterior cruciate-retaining design using standard cutting guides based on intramedullary alignment; the contralateral knee implanted with patient-specific implants using patient-specific cutting guides, both manufactured from the preoperative CT scans. Each knee was tested preoperatively as an intact, normal knee, by mounting the knee on a dynamic, quadriceps-driven, closed-kinetic-chain Oxford knee rig (OKR), simulating a deep knee bend from 0° to 120° flexion. Following implantation with either the standard or patient-specific implant, knees were mounted on the OKR and retested. Femoral rollback, tibiofemoral rotation, tibial adduction, patellofemoral tilt and shift were recorded using an active infrared tracking system. Results:. To reduce the effect of variability, change in each kinematic measure was quantified as the absolute difference between the normal kinematic measure and the same measure after implantation (10° flexion increments). The cumulative difference from normal kinematics was calculated by summing the area beneath the curve (Fig 2). Cumulative differences in kinematics from normal were statistically lower for the patient-specific group compared to the standard group for all measures except patellar shift (Fig 2, paired t-test). Discussion:. Knee kinematics with the patient-specific design more closely approximated normal femoral rollback and tibial adduction than knees with the standard design. Femoral rollback is significantly closer qualitatively and quantitatively to normal in specimens implanted with patient-specific designs (Figs 1). The tibia rotated internally with flexion; however, the patient-specific group more closely approximated normal rotation. The patient-specific group more closely approximated normal tibial adduction suggesting ligament balance was better restored. Due to substantial differences in articular morphology among genders, races and patients, it is impossible to provide multiple sized implants to address the full range of inter-patient variability. Patient-specific designs that remove this variation, restore normal articular geometry, and maintain alignment are more likely to result in normal kinematics. Our results support the hypothesis that knees with patient-specific implants generate kinematics more closely resembling normal knee kinematics than standard knee designs. Clinical outcome studies are necessary to determine if our results translate into better outcomes

Introduction:. Tibial component fit, specifically significant overhang of tibial plateau or underhang of cortical bone, can lead to pain, loosening and subsidence. The purpose was to utilize morphometric data to compare size, match, and fit between patient specific and incrementally sized standard unicompartmental knee arthroplasty (UKA) implants. Methods:. CT images of 20 medial UKA knees and 10 lateral UKA knees were retrospectively reviewed. Standard and patient-specific implants were modeled in CAD, utilizing sizing templates and patient-specific CAD Designs. Virtual surgery maximized coverage of tibial plateau while minimizing implant overhang. Tibial plateau implant coverage was evaluated for fit and incidence of overhang/undercoverage. RESULTS:. Patient specific implants provided significantly greater cortical rim coverage versus incrementally sized standard implants, 77% v. 43% (range 41–46%) respectively medially (p < 0.0001) and 60% v. 37% (range 29–41%) laterally (p < 0.0001). Patient-specific and standard implants' arc length were evaluated for percent of implant edge on cortical bone, 84% v. 55% (range 48–59%) medially (p < 0.0001) and 79% v. 57% (range 53–60%) laterally (p < 0.0001). Average amount of overhang/undercoverage of cortical rim area differed in patient-specific and standard implants: 0.24 mm v. 0.46 mm maximum overhang, (p = 0.043); 0.87 mm vs. 3.01 mm maximum undercoverage medially (p < 0.0001); 0.14 mm vs. 0.59 mm maximum overhang, (p = 0.05); 1.19 mm vs. 2.26 mm maximum undercoverage laterally (p = 0.017). Anterior overhang yielded 25 −75% and 30–80% of medial and lateral implants respectively in standard implant group; no overhang in patient-specific implant group. Conclusions:. Tibial plateau anatomy variability produces difficulty optimizing coverage and preventing significant implant overhang/undercoverage with standard unicompartmental implants. Using virtual implantation, standard implants were undersized to avoid overhang. However, we encountered significantly more overhang in standard implants versus patient specific cohort. This study removed variability matching tibial tray and femoral standard group implant placement. Patient-specific implants provide superior cortical bone coverage and fit while minimizing issues of overhang and undercoverage seen in standard implants

For a proper functional restoration of the knee following knee arthroplasty, a comprehensive understanding of bony and soft tissue structures and their effects on biomechanics of the individual patient is essential. A systematic description of morphological knee joint parameters and a study of their effects could beneficial for an optimal patient-specific implant design. The goal of this study was the development of a full parametric model for a comprehensive analysis of the distal femoral morphology also enabling a systematic parameter variation in the context of a patient specific multi-parameter optimisation of the knee implant shape. The computational framework was implemented in MATLAB and tested on 20 CT-models which originated from pathological right knees. The femora were segmented semi-automatically and exported in STL-format. First, a 3D surface model was imported, visualised and reference landmarks were defined. Cutting planes were rotated around the transepicondylar axis and ellipses were fitted in the cutting contour using pattern recognition. The portions between the ellipses were approximated by using a piecewise cubic hermite interpolation polynom such that a closed contour was obtained following the characteristics of the real bone model. At this point the user could change the parameters of the ellipses in order to manipulate the approximated contour for e.g. higher-level biomechanical analyses. A 3D surface was generated by using the lofting technique. Finally, the parameter model was exported in STL-format and compared against the original 3D surface model to evaluate the accuracy of the framework. The presented framework could be successfully applied for automatic parameterisation of all 20 distal femur surface data-sets. The mean global accuracy was 0.09±0.62 mm with optimal program settings which is more accurate than the optimal resolution of the CT based data acquisition. A systematic variation of the femoral morphology could be proofed based on several examples such as the manipulation of the medial/lateral curvature in the frontal plane, contact width of the condyles, J-Curve and trochlear groove orientation. In our opinion, this novel approach might offer the opportunity to study the effect of femoral morphology on knee biomechanics in combination with validated biomechanical simulation models or experimental setups. New insights could directly be used for patient-specific implant design and optimisation

Introduction. The ability to create patient-specific implants (PSI) at the point-of-care has become a desire for clinicians wanting to provide affordable and customized treatment. While some hospitals have already adopted extrusion-based 3D printing (fused filament fabrication; FFF) for creating non-implantable instruments, recent innovations have allowed for the printing of high-temperature implantable polymers including polyetheretherketone (PEEK). With interest in FFF PEEK implants growing, it is important to identify methods for printing favorable implant characteristics such as porosity for osseointegration. In this study, we assess the effect of porous geometry on the cell response and mechanical properties for FFF-printed porous PEEK. We also demonstrate the ability to design and print customized porous implants, specifically for a sheep tibial segmental defect model, based on CT images and using the geometry of triply periodic minimal surfaces (TPMS). Methods. Three porous constructs – a rectilinear pattern and gyroid/diamond TPMSs – were designed to mimic trabecular bone morphology and manufactured via PEEK FFF. TPMSs were designed by altering their respective equation approximations to achieve desired porous characteristics, and the meshes were solidified and shaped using a CAD workflow. Printed samples were mCT scanned to determine the resulting pore size and porosity, then seeded with pre-osteoblast cells for 7 and 14 days. Cell proliferation and alkaline phosphatase activity (ALP) were evaluated, and the samples were imaged via SEM. The structures were tested in compression, and stiffness and yield strength values were determined from resulting stress-strain plots. Roughness was determined using optical profilometry. Finally, our process of porous structure design/creation was modified to establish a proof-of-concept workflow for creating PSIs using geometry established from segmented sheep tibia CT images. Results. ALP activity measurements of the porous PEEK samples at 7 and 14 days were significantly greater than for solid controls (p < 0.001 for all three designs, 14 days). No difference between the porous geometries was found. SEM imaging revealed cells with flat, elongated morphology attached to the surface of the PEEK and into the pore openings, with filopodia and lamellipodia extensions apparent. mCT imaging showed average pore size to be 545 ± 43 µm (porosity 70%), 708 ± 64 µm (porosity 68%), and 596 ± 94 µm (porosity 69%) for the rectilinear, gyroid, and diamond structures, respectively. The average error between the theoretical and actual values was −16.3 µm (pore size) and −3.3 % (porosity). Compression testing revealed elastic moduli ranging from 210 to 268 MPa for the porous samples. Yield strengths were 6.6 ± 1.2 MPa for lattice, 14.8 ± 0.7 MPa for gyroid, and 17.1 ± 0.6 for diamond. Average roughness ranged from 0.8 to 3 µm. Finally, we demonstrated the ability to design and print a fully porous implant with the geometry of a sheep tibia segment. Assessments of implant geometrical accuracy and mechanical performance are ongoing. Discussion. We created porous PEEK with TPMS geometries via FFF and demonstrated a positive cellular response and mechanical characteristics similar to trabecular bone. Our work offers an innovative approach for advancing point-of-care 3D printing and PSI creation

Three-dimensional (3D) printing has become more frequently used in surgical specialties in recent years. Orthopaedic surgery is particularly well-suited to 3D printing applications, and thus has seen a variety of uses for this technology. These uses include pre-operative planning, patient-specific instrumentation (PSI), and patient-specific implant production. As with any new technology, it is important to assess the clinical impact, if any, of three-dimensional printing. The purpose of this review was to answer the following questions: . What are the current clinical uses of 3D printing in orthopaedic surgery?. Does the use of 3D printing have an effect on peri-operative outcomes?. Four electronic databases (Embase, MEDLINE, PubMed, Web of Science) were searched for Articles discussing clinical applications of 3D printing in orthopaedics up to November 13, 2018. Titles, abstracts, and full texts were screened in duplicate and data was abstracted. Descriptive analysis was performed for all studies. A meta-analysis was performed among eligible studies to compare estimated blood loss (EBL), operative time, and fluoroscopy use between 3D printing cases and controls. Study quality was assessed using the Methodological Index for Non-Randomized Studies (MINORS) criteria for non-randomized studies and the Cochrane Risk of Bias Tool for randomized controlled trials (RCTs). This review was prospectively registered on PROSPERO (Registration ID: CRD42018099144). One-hundred and eight studies were included, published between 2012 and 2018. A total of 2328 patients were included in these studies, and 1558 patients were treated using 3D printing technology. The mean age of patients, where reported, was 47 years old (range 3 to 90). Three-dimensional printing was most commonly reported in trauma (N = 41) and oncology (N = 22). Pre-operative planning was the most common use of 3D printing (N = 63), followed by final implants (N = 32) and PSI (N = 22). Titanium was the most commonly used 3D printing material (16 studies, 27.1%). A wide range of costs were reported for 3D printing applications, ranging from “less than $10” to $20,000. The mean MINORS score for non-randomized studies was 8.3/16 for non-comparative studies (N = 78), and 17.7/24 for non-randomized comparative studies (N = 19). Among RCTs, the most commonly identified sources of bias were for performance and detection biases. Three-dimensional printing resulted in a statistically significant decrease in mean operative time (−15.6 mins, p < .00001), mean EBL (−35.9 mL, p<.00001), and mean fluoroscopy shots (−3.5 shots, p < .00001) in 3D printing patients compared to controls. The uses of 3D printing in orthopaedic surgery are growing rapidly, with its use being most common in trauma and oncology. Pre-operative planning is the most common use of 3D printing in orthopaedics. The use of 3D printing significantly reduces EBL, operative time, and fluoroscopy use compared to controls. Future research is needed to confirm and clarify the magnitude of these effects

Glenoid bone loss is not an uncommon challenge in both primary shoulder arthroplasty surgery and revision surgery. Walch described the classification of glenoid morphology and this has led to an understanding of the expanded role for bone grafting, patient-specific implants and reverse prostheses. While bone grafting of the glenoid in conventional arthroplasty has been shown to be successful in some patients it is more routinely used in combination with reverse prostheses. More recently, augmented glenoid components have been developed for both conventional and reverse arthroplasty, though follow-up is insufficient to confirm their durability at this time

Introduction. Hemiarthroplasty is a treatment option for comminuted fractures and non-unions of the distal humerus. Unfortunately, the poor anatomical fit of off-the-shelf distal humeral hemiarthroplasty (DHH) implants can cause altered cartilage contact mechanics. The result is reduced contact area and higher cartilage stresses, thus subsequent cartilage erosion a concern. Previous studies have investigated reverse-engineered DHH implants which reproduce the shape of the distal humerus bone or cartilage at the articulation, but still failed to match native contact mechanics. In this study, design optimization was used to determine the optimal DHH implant shape. We hypothesized that patient-specific optimal implants will outperform population-optimized designs, and both will optimize simple reverse-engineered designs. Methods. The boney geometries of six elbow joints were created based on cadaver arm CT data using a semi-automatic threshold technique in 3D Slicer. CT scans were also obtained with the elbows denuded and disarticulated, such that the high contrast between hydrated cartilage and air could be exploited in order to reconstruct cartilage geometry. Using this 3D model data, finite element contact models were created for each elbow, where bones (distal humerus, proximal ulna and radius) were modelled as rigid surfaces covered by non-uniform thickness layers of cartilage. Cartilage was modelled as a Neo-Hookean hyperelastic material (K = 0.31 MPa, G = 0.37 MPa), and frictionless contact was assumed. In order to simulate hemiarthroplasty, the distal humerus cartilage surface was replaced by either a rigid surface in the shape of the subchondral bone (bone reverse engineered or BRE design), or a surface offset from the bone by some distance, which was defined parametrically and modified by an optimization algorithm. Simple flexion-extension with constant balanced muscle loads was simulated in ABAQUS (Fig 1), and resulting contact areas and contact stresses were calculated. For each specimen, the contact mechanics of the intact and DHH reconstructed joints were calculated. A design optimization algorithm in Matlab was used to determine the optimal offset distance which resulted in contact stress distributions on the ulna and radius which most closely resembled their intact conditions. This procedure was repeated in order to generate specimen-optimal offsets, as well as population-optimal offsets. Results. The population-optimal offset distance was 0.72 mm; whereas the specimen-optimal offsets ranged from 0.52 to 1.04 mm. Compared to the BRE design, which is effectively an offset distance of 0 mm, contact area generally increased at both the ulna (Fig 2) and radius (Fig 3) when either optimized design was used. On average, the specimen-optimal implant designs yielded only slightly larger contact areas than the population-optimal offsets, and only at mid-flexion (40–60 deg). Neither optimization strategy increased contact areas to those of the intact joint. Conclusions. Design optimization is a promising technique for improving patient-specific implants by offering customization in terms of contact mechanics, instead of simply reproducing osseous geometry. In this study, our models predict a large increase in contact area if optimal offsets are used when designing subject-specific DHH, and a population-optimal offset distance seems to be just as good as a subject-optimal offset. For any figures or tables, please contact authors directly (see Info & Metrics tab above).

Total knee arthroplasty (TKA) is widely accepted as a successful surgical intervention to treat osteoarthritis and other degenerative diseases of the knee. However, present statistics on limited survivorship and patient-satisfaction emphasise the need for an optimal endoprosthetic care. Although, the implant design is directly associated with the clinical outcome comprehensive knowledge on the complex relationship between implant design (morphology) and function is still lacking. The goal of this study was to experimentally analyse the relationship between the trochlear groove design of the femoral component (iTotal CR, ConforMIS, Inc., Bedford, MA, USA) and kinematics in an in vitro test setup based on rapid prototyping of polymer-based replica knee implants. The orientation of the trochlear groove was modified in five different variations in a self-developed computational framework. On the basis of the reference design, one was medially tilted (−2°) and four were laterally tilted (+2°, +4°, +6°, +8°). For manufacturing, we used rapid prototyping to produce synthetic replicates made of Acrylnitril-Butadien-Styrol (ABS) and subsequent post-processing with acetone vapor. The morpho-functional analysis of the replicates was performed in our experimental knee simulator. Tibiofemoral and patellofemoral kinematics were recorded with an optical tracking system during a semi-active flexion/extension (∼10° to 90°) motion. Looking at the results, the patellofemoral kinematics, especially the medial/lateral translation and internal/external rotation were mainly affected. During low flexion, the patella had a more laterally position relative to the femur with increasing lateral trochlear orientation. The internal/external rotation initially differentiated and converged with flexion. Regarding the tibiofemoral kinematics, only the tibial internal/external rotation showed notable differences between the modified replica implants. We presented a workflow for an experimental morpho-functional analysis of the knee and demonstrated its feasibility on the example of the trochlear groove orientation which might be used in the future for comprehensive implant design parameter optimisation, especially in terms of image based computer assisted patient-specific implants

Introduction. Total knee arthroplasty is the standard treatment for advanced knee osteoarthritis. Patient-specific instrument (PSI)has been reported by several authors using different techniques produced by implant companies. The implant manufacturers produce PSI exclusively for their own knee implants and for easy straightforward cases. However, the PSI has become very expensive and unusable as a universal or an open platform. In addition, planning the implant is done by technicians and not by surgeons and needs long waiting time before surgery (6 weeks). Methods. We proposed a new technique which is a device and method for preparing a knee joint in a patient undergoing TKA surgery of any knee implant (prosthesis). The device is patient specific, based on a method comprised of image-based 3D preoperative planning (CT, MRI or computed X-ray) to design the templates (PSI) that are used to perform the knee surgery by converting them to physical templates using computer-aided manufacturing such as computer numerical control (CNC) or additive-manufacturing technologies. The device and method are used for preparing a knee joint in a universal and open-platform fashion for any currently available knee implant. Results. All patient-specific implants and any knee implant could be produced. The technique was applied on NExGen implant (Zimmer)on 21 patients, PFC implant (Depuy, J & J) on 5 patients, Scorpio NRG implant (Stryker) on 24 patients and SLK Evo implant (Implant International) on 81 patients. The >15 degrees varus gave a mean of 10.44 degrees in 56.67% of cases and the <15 degrees varus gave a mean of 24.04 degrees in 43.33% of cases. The total varus of 5–30 degrees gave a mean of 16.33 degrees in 90.9% of cases and the total valgus of 20–40 gave a mean of 25 degrees in 9.1% of cases. The fixed flexion deformity of < 20 degrees gave a mean of 9.4 degrees in 75.3% of cases while the fixed flexion deformity of >20 gave a mean of 31.87 degrees in 24.7% of cases. Discussion. The system is based on CT images, generic data of implant sizes, average bone geometry and standard TKA parameters for bone cutting, mechanical axis and rotation (e.g., zero-degree coronal cut, adjustable posterior slope, femoral flexion, epicondylar axis, no notching or overhang, etc.). The method of planning and completing virtual surgery of TKA includes several steps based on 3D reconstruction and segmentation of computed tomography (CT) or MRI scan data. The universal device and method are suitable to be used for any commercially and currently available knee implant. They are used for all on-shelf implants and all patient-specific instruments. The device is specifically designed for TKA and the planning is based on the 3D files of a universal TKA prosthesis. There are four standard sizes of the universal TKA prosthesis which were built depending on the average bone geometry. These 4 sizes are 55, 60, 65 and 70 mm. These sizes are consistent with the six most common implants available today: NexGen Zimmer, PFC Depuy, Sigma Knee, Triathlon Stryker, Vanguard Biomet, and Smith & Nephew Proflex. However, for extreme cases, one size above or below the maximum and minimum range can be used. The device has 2 parts: a femoral part and a tibial part, both of which are independent of any commercially available knee implant

The use of 3D imaging methodologies in orthopaedics has allowed the introduction of new technologies, such as the design of patient-specific implants or surgical instrumentation. This has introduced the need for high accuracy, in addition to a correct diagnosis. Until recently, little was known about the accuracy of MR imaging to reconstruct 3D models of the skeletal anatomy. This study was conducted to quantify the accuracy of MRI-based segmentation of the knee joint. Nine knees of unfixed human cadavers were used to compare the accuracy of MR imaging to an optical scan. MR images of the specimens were obtained with a 1.5T clinical MRI scanner (GE Signa HDxt), using a slice thickness of 2 mm and a pixel size of 0.39 mm × 0.39 mm. Manual segmentation of the images was done using Mimics® (Materialise NV, Leuven, Belgium). The specimens were cleaned using an acetone treatment to remove soft-tissue but to keep the cartilage intact. The cleaned bones were optically scanned using a white-light optical scanner (ATOS II by GOM mbH, Braunschweig, Germany) having a resolution of 1.2 million pixels per measuring volume, yielding an accuracy of 0.02 mm. The optical scan of each bone reflects the actual dimensions of the bone and is considered as a ground truth measurement. First, a registration of the optical scan and the MRI-based 3D reconstruction was performed. Then, the optical scan was compared to the 3D model of the bone by calculating the distance of the vertices of the optical scan to the reconstructed 3D object. Comparison of the 3D reconstruction using MRI images and the optical scans resulted in an average absolute error of 0.67 mm (± 0.52 mm standard deviation) for segmentation of the cartilage surface, with an RMS value of circa twice the pixel size. Segmenting the bone surface resulted in an average absolute error of 0.42 mm (± 0.38 mm standard deviation) and an RMS error of 1.5 times the pixel size. This accuracy is higher than reported previously by White, who compared MRI and CT imaging by looking at the positioning of landmarks on 3D printed models of the segmented images using a calliper [White, 2008]. They reported an average accuracy of 2.15 mm (± 2.44 mm) on bone using MRI images. In comparison, Rathnayaka compared both CT- and MRI-based 3D models to measurements of the real bone using a mechanical contact scanner [Rathnayaka, 2012]. They listed an accuracy of 0.23 mm for MRI segmentation using five ovine limbs. This study is one of the first to report on the segmentation accuracy of MRI technology on knee cartilage, using human specimens and a clinical scanning protocol. The results found for both bone and cartilage segmentation demonstrate the feasibility of accurate 3D reconstructions of the knee using MRI technology

Introduction. The introduction of the Stanmore Implants Savile Row mobile-bearing UKA procedure in July 2011 marked a world first – the use of a patient-specific knee implanted with robotic technology – the Sculptor Robotic Guidance Arm (RGA). This union gives a truly personalised solution by designing an implant for each patient based upon preoperative CT data and using Sculptor RGA to prepare the bone accurately so that the implant is correctly positioned as planned. The purpose of this study is to evaluate the accuracy of Sculptor RGA both in-vitro and in-vivo. We report on the accuracy of our first clinical procedures. Methods. In-vitro:. CTs of plastic-bones were used to create plans for Sculptor RGA, establishing a relationship between the implant position and plastic-bone (planned-transform). Sculptor RGA was then used to prepare bones for 16 UKA implants mimicking the clinical set-up. The implants were placed in the prepared bones without cement. A coordinate-measuring-arm was used to register a)the bone, and b)the implant in relation to the bone (achieved-transform). The difference between planned-and-achieved transforms gives the error in implant position. In-vivo:. Preoperative CTs of 8 OA patients, acquired using the low-dose Imperial Knee CT protocol, were used to plan the position and the shape of the patient-specific implants. Intra-operatively, Sculptor RGA was used to register and prepare the bone and the implants were cemented in place. Post-operative CTs were also acquired. Two techniques were used to measure planned-to-achieved positions of the implants: 1). Preoperative-to-postoperative CT image registration followed by extraction of the achieved implant position and comparison with the plan, 2). Surface-to-surface registration of bone-models segmented from the preoperative and postoperative CTs followed by extraction of the achieved implant position and comparison with the plan. Results. For the in-vitro tests, femoral RMS errors averaged 0.8 mm and 1.6° and tibial RMS errors averaged 1.2 mm and 1.6°. For the clinical cases, femoral RMS errors averaged 1.2 mm and 2.6° and tibial RMS errors averaged 1.3 mm and 2.4°. Discussion. The planned-versus-achieved errors are lower for the in-vitro cases compared to the clinical cases. This is partly due to the increased ease of registration in-vitro and also due to the error introduced during cementing in-vivo, which has been reported to give average errors of 2° in UKA. 1. The clinical results also compare favourably with previously published results for robotic UKA: Conditt et al report 1.4 mm and 2.6° for the femur and 1.2 mm and 2.1° for the tibia. 2. . We have previously reported on the accuracy of the predecessor to Sculptor RGA in a study implanting an off-the-shelf UKA prosthesis with the bones clamped and comparing this to the manual technique. 3. In that study the error in the robotic technique averaged femur: 1.0 mm and 2.6°, tibia: 1.1 mm and 2.5° compared to femur: 2.7 mm and 5.5°, tibia: 2.5 mm and 5.3° in the manual group. Conclusion. This study has shown that the combination of Sculptor RGA and a patient-specific knee results in accurate and reproducible implant placement

Background. The combination of patient-specific “just-in-time” implant manufacture and robotic technology has not yet been reported. The robot enables accurate placement of anatomically-matched implants. It should be cost-effective, simplify the procedure, and reduce instrumentation. The aims of this study were to determine whether the procedure was safe, radiographically accurate, and comparable in time and cost to conventional arthroplasty. Methods. All patients over 3 months post-op were included. Component position, orientation and size were determined from CT scans by the surgeon prior to manufacture. The implants were inserted using the Sculptor robot, which is supplied free of cost (Savile Row, Stanmore Implants, UK). Following registration, bone was milled away using a high-speed burr under haptic control of the robot. The implants were cemented and a mobile bearing inserted. Patients were followed up clinically and radiographically. Oxford and EQ-5D scores were obtained. Costs of the implant, instruments, and consumables were calculated and compared to published data for conventional UKA and TKA. Results. 17 patients (7M:10F) have reached 3 months follow-up. Mean age was 67 (range 49–84). Mean “robotic surgical time” was 25 minutes (range 14–39) contributing to a mean tourniquet time of 79 minutes (range 57–105). Median length of stay was 3 days (range 1–8). Post-op radiographs showed satisfactory component position. At a median follow-op of 4 months (range 3–6), mean Oxford score was 32 (range 23–41), and mean EQ-5DVAS was 70 (range 40–90). There were no serious complications. Total cost was £1665 per patient compared with £1334 for conventional UKA and £2620 for TKA. Conclusions. Patient-specific UKA can be made and placed safely, with radiographical accuracy, using a “no-cost” haptic robot. The time taken is comparable to other knee arthroplasty procedures, uses less instrumentation, and costs £1000 less than a typical TKA