Abstract. Aim. This study aims to Inter and intra observer reliability compare, use of a standard goniometer (SG) to measure intermetacarpal angle (degrees) vs use of a new technique of using a digital vernier calliper (DVC) (mm) to measure the distance between the first and second metacarpal head. Method. Maximal active abduction and extension of both thumbs was measured in 20 healthy volunteers on two occasions at least one week apart by two assessors. Results. The inter and intra-observer agreement was higher & the variance of the data was lower using the DVC with the new technique than the SG for both thumb abduction and extension. Additionally, the correlation between measurement of extension and abduction was higher using the DVC than the SG. Conclusion. Whilst both tools provide acceptable intra and inter-observer agreement, the new technique using a DVC is consistently better and more reliable than a SG in measuring thumb abduction and extension. The study also supports our hypothesis that the thumb rotates around the second metacarpal head with a consistent radius

INTRODUCTION. In computer-aided total knee arthroplasty (TKA), surgical navigation systems (SNS) allow accurate tibio-femoral joint (TFJ) prosthesis implantation only. Unfortunately, TKA alters also normal patello-femoral joint (PFJ) functioning. Particularly, without patellar resurfacing, PFJ kinematics is influenced by TFJ implantation; with resurfacing, this is further affected by patellar implantation. Patellar resurfacing is performed only by visual inspections and a simple calliper, i.e. without computer assistance. Patellar resurfacing and motion via patient-specific bone morphology had been assessed successfully in-vitro and in-vivo in pilot studies aimed at including these evaluations in traditional navigated TKA. The aim of this study was to report the current experiences in-vivo in two patient cohorts during TKA with patellar resurfacing. MATERIALS AND METHODS. Twenty patients with knee gonarthrosis were divided in two cohorts of ten subjects each and implanted with as many fixed-bearing posterior-stabilised prostheses (NRG® and Triathlon®, Stryker®-Orthopaedics, Mahwah, NJ-USA) with patellar resurfacing. Fifteen patients were implanted; five patients of the Triathlon cohort are awaiting hospital admission. TKAs were performed using two SNS (Stryker®-Leibinger, Freiburg-Germany). In addition to the traditional knee SNS (KSNS), the novel procedure implies the use of the patellar SNS (PSNS) equipped with a specially-designed patellar tracker. Standard navigated procedures for intact TFJ survey were performed using KSNS. These were performed also with PSNS together intact PFJ survey. Standard navigated procedures for TFJ implantation were performed using KSNS. During patellar resurfacing, the patellar cutting jig was fixed at the desired position with a plane probe into the saw-blade slot; PSNS captured tracker data to calculate bone cut level/orientation. After sawing, resection accuracy was assessed using a plane probe. TFJ/PFJ kinematics were captured with all three trial components in place for possible adjustments, and after final component cementing. A calliper and pre/post-TKA X-rays were used to check for patellar thickness/alignment. RESULTS. This protocol was performed successfully in TKAs, resulting in 30 min longer TKA. Final lower limb misalignment was within 0.5°, resurfaced patella was 0.4±1.2 mm thinner than the native, and patellar cut was 0.4°±4.1° laterally tilted. Final PFJ kinematics was taken within the reference normality in both series. PFJ flexion, tilt and medio-lateral shift range were 66.9°±8.5° (minimum÷maximum, 15.6°÷82.5°), 8.0°±3.1° (−5.3°÷2.8°), and 5.3±2.0 mm (−5.5÷0.2 mm), respectively. Significant (p<0.005) correlations were found between the internal/external rotation of the femoral component and PFJ tilt (R. 2. =0.41), and between the mechanical axis on the sagittal plane and PFJ flexion (R. 2. =0.44) and antero-posterior shift (R. 2. =0.45). Patellar implantation parameters were confirmed by X-ray inspections. Discrepancies in thickness up to 5 mm were observed between SNS- and calliper-based measurements. CONCLUSIONS. These results support relevance/efficacy of patellar tracking in in-vivo navigated TKA and may contribute to a more comprehensive assessment of the original whole knee, i.e. including also PFJ. Patellar preparation would be supported for suitable component positioning in case of resurfacing, but, conceptually, also in not-resurfacing if SNS does not reveal PFJ abnormalities., Using this procedure in the future, TFJ/PFJ abnormalities can be corrected intra-operatively by more cautious bone cut preparation and prosthetic positioning on the femur, tibia and patella

During total knee replacement (TKR), surgical navigation systems (SNS) allow accurate prosthesis component implantation by tracking the tibio-femoral joint (TFJ) kinematics in the original articulation at the beginning of the operation, after relevant trial components implantation, and, ultimately, after final component implantation and cementation. It is known that TKR also alters normal patello-femoral joint (PFJ) kinematics resulting frequently in PFJ disorders and TKR failure. More importantly, patellar tracking in case of resurfacing is further affected by patellar bone preparation and relevant component positioning. The traditional technique used to perform patellar resurfacing, even in navigated TKR, is based only on visual inspection of the patellar articular aspect for clamping patellar cutting jig and on a simple calliper to check for patellar thickness before and after bone cut, and, thus, without any computer assistance. Even though the inclusion in in-vivo navigated TKR of a procedure for supporting also patellar resurfacing based on patient-specific bone morphology seems fundamental, this have been completely disregarded till now, whose efficacy being assessed only in-vitro. This procedure has been developed, together with relevant software and surgical instrumentation, as an extension of current SNS, i.e. TKR is navigated, at the same time measuring the effects of every surgical action on PFJ kinematics. The aim of this study was to report on the first in-vivo experiences during TKR with patellar resurfacing. Four patients affected by primary gonarthrosis were implanted with a fixed bearing posterior-stabilised prosthesis (NRG, Stryker®-Orthopaedics, Mahwah, NJ-USA) with patellar resurfacing. All TKR were performed by means of two SNS (Stryker®-Leibinger, Freiburg, Germany) with the standard femoral/tibial trackers, the pointer, and a specially-designed patellar tracker. The novel procedure for patellar tracking was approved by the local ethical committee; the patients gave informed consent prior the surgery. This procedure implies the use of a second system, i.e. the patellar SNS (PSNS), with dedicated software for supporting patellar resurfacing and relative data processing/storing, in addition to the traditional knee SNS (KSNS). TFJ anatomical survey and kinematics data are shared between the two. Before surgery, both systems were initialised and the patellar tracker was assembled with a sterile procedure by shaping a metal grid mounted with three markers to be tracked by PSNS only. The additional patellar-resection-plane and patellar-cut-verification probes were instrumented with a standard tracker and a relevant reference frame was defined on these by digitisation with PSNS. Afterwards, the procedures for standard navigation were performed to calculate preoperative joint deformities and TFJ kinematics. The anatomical survey was performed also with PSNS, with relevant patellar anatomical reference frame definition and PFJ kinematics assessment according to a recent proposal. Standard procedures for femoral and tibial component implantation, and TFJ kinematics assessment were then performed by using relevant trial components. Afterwards, the procedure for patellar resection begun. Once the surgeon had arranged and fixed the patellar cutting jig at the desired position, the patellar-resection-plane probe was inserted into the slot for the saw blade. With this in place, the PSNS captured tracker data to calculate the planned level of patellar bone cut and the patellar cut orientation. Then the cut was executed, and the accuracy of this actual bone cut was assessed by means of the patellar-cut-verification probe. The trial patellar component was positioned, and, with all three trial components in place, TFJ and PFJ kinematics were assessed. Possible adjustments in component positioning could still be performed, until both kinematics were satisfactory. Finally, final components were implanted and cemented, and final TFJ and PFJ kinematics were acquired. A sterile calliper and pre- and post-implantation lower limb X-rays were used to check for the patellar thickness and final lower limb alignment. The novel surgical technique was performed successfully in all four cases without complication, resulting in 30 min longer TKR. The final lower limb alignment was within 0.5°, the resurfaced patella was 0.4±1.3 mm thinner than in the native, the patellar cut was 1.5°±3.0° laterally tilted. PFJ kinematics was taken within the reference normality. The patella implantation parameters were confirmed also by X-ray inspection; discrepancies in thickness up to 5 mm were observed between SNS- and calliper-based measurements. At the present experimental phase, a second separate PSNS was utilised not to affect the standard navigated TKR. The results reported support relevance, feasibility and efficacy of patellar tracking and PFJ kinematics assessment in in-vivo navigated TKR. The encouraging in-vivo results may lay ground for the design of a future clinical patella navigation system the surgeon could use to perform a more comprehensive assessment of the original whole knee anatomy and kinematics, i.e. including also PFJ. Patellar bone preparation would be supported for suitable patellar component positioning in case of resurfacing but, conceptually, also in not resurfacing if patellar anatomy and tracking assessment by SNS reveals no abnormality. After suitable adjustment and further tests, in the future if this procedure will be routinely applied during navigated TKR, abnormalities at both TFJ and PFJ can be corrected intra-operatively by more cautious bone cut preparation on the femur, tibia and also patella, in case of resurfacing, and by correct prosthetic component positioning

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