Background

Previously, we demonstrated the effectiveness of phase symmetry (PS) features for segmentation and localisation of bone fractures in 3D ultrasound for the purpose of orthopedic fracture reduction surgery. We recently proposed a novel real-time image-processing method of bone surface extraction from local phase features of clinical 3D B-mode ultrasound data. We are presenting a computational study and outline planned future developments for integration into a computer aided orthopedic surgery framework.

Previously, we demonstrated the effectiveness of phase symmetry (PS) features for segmentation and localisation of bone fractures in 3D ultrasound for the purpose of orthopaedic fracture reduction surgery. We recently proposed a novel real-time image-processing method of bone surface extraction from local phase features of clinical 3D B-mode ultrasound data. We are presenting a computational study and outline of planned future developments for integration into a computer aided orthopaedic surgery framework.

Our image-processing pipeline was implemented on three platforms: (1) using an existing PS extraction C++ algorithm on a dual processor machine with two Xeon x5472 CPUs @ 3GHz with 8GB of RAM, (2) using our proposed method implemented in MATLAB running on the same machine as in (1), and (3) CUDA implementation of our method implemented on a professional GPU (Nvidia Tesla c2050).

We ran these three implementations 20 times each on 128×128×128 scans of the iliac crest in live subjects and repeated the processing for 15 combinations of filter parameters. On average, the C++ implementation took 1.93s per volume, the MATLAB implementation 1.28s, and the GPU implementation 0.08s. Overall, our GPU implementation is between 15 and 25 times faster than the state-of-the-art method.

Implementing our algorithm on a professional grade GPU produced dramatic computational improvements, enabling full 3D datasets to be processed in an average time of under 100ms, which, if proven in a clinical system, would allow for near real time computation. We are currently implementing our algorithm on an open research sonography platform (Ultrasonix Medical Corporation). High-powered graphic cards can easily be integrated into the open architecture of this system, thus enabling GPU computation on diagnostic medical and research ultrasound devices.

We intend to use this platform within a surgical environment for accurate and automatic detection of fractures and as an integral part of our developing computer aided surgery pipeline, in which we use PS features to register intra-operative ultrasound to pre-operative computed tomography images.

Shoulder septic arthritis is uncommon and frequently misdiagnosed, resulting in severe consequences. This study evaluated the demographics, bacteriological profile, antibiotic susceptibility, treatment regimens, and clinical outcomes. This is a 10-year retrospective observational analysis of 30 patients (20 males and 10 females) who were treated for septic arthritis of the shoulder. The data collecting process utilised clinical records, laboratory archives, and x-ray archives. We gathered demographic information, pre- and post-intervention clinical data, serum biochemical markers, and the results of imaging examinations. All patients had a surgical arthrotomy and joint debridement in the operating room, and specimens were taken for culture and sensitivity testing. The specimens were cultivated for at least seventy-two hours. Shoulder joint ranges of motion, comorbidities, and the presence of osteomyelitis were assessed clinically to determine the outcome. All statistical analyses were conducted using the STATA 17 statistical software. Analysis of correlation between categorical variables was performed using the chi-squared test. The majority of the study patients were black Africans (97%). The age range of the group was from 8 days to 17 years. At presentation, 33% of patients had a low-grade fever, whereas the majority (60%) had normal body temperature. The average length of symptoms was 3.9 days (ranged from 1 day to 15 days), and the majority of patients had an increased white cell count (83%) and C-reactive protein (98%). There was accumulation of fluid in the joint of all individuals who received shoulder ultrasound imaging. We noted a significant incidence of gram-positive cocci, which were mostly susceptible to first-line antibiotics. Shoulder stiffness affected 63% of patients and chronic osteomyelitis affected 50% of individuals. Neither the severity nor the duration of the symptoms was related to an increased risk of osteomyelitis. The results of this study revealed that the clinical characteristics and bacterial profile of septic arthritis of the shoulder conform to typical patterns. The likelihood of osteomyelitis and an unfavourable prognosis is considerable

A challenging problem in ultrasound based orthopaedic surgery is the identification and interpretation of bone surfaces. Recently we have proposed a new fully automatic ultrasound bone surface enhancement filter in the context of spine interventions. The method is based on the use of a Gradient Energy Tensor filter to construct a new feature enhancement metric, which we call the Local Phase Tensor. The goal of this study is to provide further improvements to the proposed filtering method by incorporating a-priori knowledge about the physics of ultrasound imaging and salient grouping of enhanced bone features. Typical ultrasound scan of the spine, there is a large soft tissue interface present close to the transducer surface with high intensity values similar to those of the bone anatomy response. Typical ultrasound image segmentation or enhancement methods will be affected by this thick soft tissue response. In order to weaken this soft tissue interface we calculate a new transmission map where features deeper in the ultrasound image have higher transmission values and shallow features have lower transmission values. The calculation of this new US transmission/attenuation map allows the proposed image enhancement method to mask out erroneous regions, such as the soft tissue interface, and improve the accuracy and robustness of the spine surface enhancement. The masked US images were used as an input to the LPT image enhancement method. In order to provide a more compact spine surface representation and further reduce the typical US imaging artifacts and soft tissue interfaces we calculate saliency Local Phase Tensor features. The saliency images are computed using Difference of Gaussian filters. Qualitative results, obtained from in vivo clinical scans, show a strong correspondence between enhanced features and the actual bone surfaces present in the ultrasound scans. Future work will include the extension of the proposed method to 3D and validation of the method in the context of intra-operative ultrasound image registration in CAOS applications

The opposable thumb is one of the defining characteristics of human anatomy and is involved in most activities of daily life. Lack of optimal thumb motion results in pain, weakness, and decrease in quality of life. First carpometacarpal (CMC1) osteoarthritis (OA) is one of the most common sites of OA. Current clinical diagnosis and monitoring of CMC1 OA disease are primarily aided by X-ray radiography; however, many studies have reported discrepancies between radiographic evidence of CMC1 OA and patient-related outcomes of pain and disability. Radiographs lack soft-tissue contrast and are insufficient for the detection of early characteristics of OA such as synovitis, which play a key role in CMC OA disease progression. Magnetic resonance imaging (MRI) and two-dimensional ultrasound (2D-US) are alternative options that are excellent for imaging soft tissue pathology. However, MRI has high operating costs and long wait-times, while 2D-US is highly operator dependent and provides 2D images of 3D anatomical structures. Three-dimensional ultrasound imaging may be an option to address the clinical need for a rapid and safe point of care imaging device. The purpose of this research project is to validate the use of mechanically translated 3D-US in CMC OA patients to assess the measurement capabilities of the device in a clinically diverse population in comparison to MRI. Four CMC1-OA patients were scanned using the 3D-US device, which was attached to a Canon Aplio i700 US machine with a 14L5 linear transducer with a 10MHz operating frequency and 58mm. Complimentary MR images were acquired using a 3.0 T MRI system and LT 3D coronal photon dense cube fat suppression sequence was used. The volume of the synovium was segmented from both 3D-US and MR images by two raters and the measured volumes were compared to find volume percent differences. Paired sample t-test were used to determine any statistically significant differences between the volumetric measurements observed by the raters and in the measurements found using MRI vs. 3D-US. Interclass Correlation Coefficients were used to determine inter- and intra-rater reliability. The mean volume percent difference observed between the two raters for the 3D-US and MRI acquired synovial volumes was 1.77% and 4.76%, respectively. The smallest percent difference in volume found between raters was 0.91% and was from an MR image. A paired sample t-test demonstrated that there was no significant difference between the volumetric values observed between MRI and 3D-US. ICC values of 0.99 and 0.98 for 3D-US and MRI respectively, indicate that there was excellent inter-rater reliability between the two raters. A novel application of a 3D-US acquisition device was evaluated using a CMC OA patient population to determine its clinical feasibility and measurement capabilities in comparison to MRI. As this device is compatible with any commercially available ultrasound machine, it increases its accessibility and ease of use, while proving a method for overcoming some of the limitations associated with radiography, MRI, and 2DUS. 3DUS has the potential to provide clinicians with a tool to quantitatively measure and monitor OA progression at the patient's bedside

Introduction. Knee arthroplasty is an effective intervention for painful arthritis when conservative measures have failed. Despite recent advances in component design and implantation techniques, a significant proportion of patients experience problems relating to the patella-femoral joint (PFJ). Detailed knowledge of the shape and orientation of the normal and replaced femoral trochlea groove is critical when considering potential causes of anterior knee pain. Furthermore, to date it has proved difficult to establish a diagnosis due to shortcomings in current imaging techniques for obtaining satisfactory coronal plane motion data of the patella in the replaced knee. The aim of this study was to correlate the trochlea shape of normal and replaced knees with corresponding coronal plane PFJ kinematic data. Method. Bony and cartilagenous trochlea geometries from 3T MRI scans of 20 normal healthy volunteers were compared with both anatomical and standard total knee replacements (TKR) and patellofemoral joint replacement (PFJR) geometries. Following segmentation and standardized alignment, the path of the apex of the trochlea groove was measured using customized Matlab software. (Fig1). Next, kinematic data of the 20 normal healthy volunteers (Normal) was compared with that of 20 TKR, and 20 PFJR patients using the validated MAUS. TM. system (Motion Analysis and UltraSound) comprising a 12-camera, motion capture system used to capture images of reflective markers mounted on subjects lower limbs and an ultrasound probe. A mapping between the ultrasound image and the motion capture system allows the ultrasound probe to be used to determine the locations of the patella relative to bony landmarks on the femur during a squat exercise. Results. In normal knees the arc of the trochlear groove apex was orientated progressively laterally for both cartilage and. Neither of these trends were reproduced by any of the knee prostheses. Indeed far from being a laterally directed trochlea groove, both the anatomic TKR and PFJR have a medially orientated trochlea, whilst the TKR showed a neutral straight path (Figure 2). The direction of displacement in the replaced knee is significantly different (opposite) to that of the native knee (p<0.05). The accuracy of the MAUS technique registering the ultrasound images within the motion capture system is 1.84 mm (2 × SD). The three groups showed very different patella tracking patterns which matched the orientation of the underlying trochlea (Figure 3). The sine wave pattern of coronal plane patella motion displayed by the Normal group was not recreated in the TKR or PFJR groups. Movements of the Normal group were significantly different from the TKR group (p=0.03) and the PFJR group (p<0.01), whilst there was no significant difference between the TKR and PFJR groups (p=0.27). Discussion. We present a new, accurate, reliable in vivo technique for measuring 3D patellofemoral kinematics in native and replaced knees. Our data suggest that many aspects of patellofemoral kinematics are absent following TKR and PFJR. This can be explained by the differences in shape of the underlying femoral component. Anterior knee pain problems might be addressed by alterations to the patellofemoral joint in future designs of knee arthroplasty

Due to its ease of use, portability, low cost, real-time response and absence of ionising radiation, ultrasound (US) imaging could potentially be an important tool for non-invasive diagnostic imaging in orthopaedics. Unfortunately, nonlinear characteristics of ultrasound, low signal-to-noise ratio and speckle make it difficult to accurately and reliably determine the location and shape of the bone surface. Recently, local phase-based image processing methods, named phase symmetry (PS), have been shown to perform very well at locating bone surfaces in ultrasound images, with reported accuracies of better than 0.4mm. The local phase features are extracted by filtering the B-mode US image in the frequency domain with a Log-Gabor filter. Although successful results were achieved, accurate localization is highly affected by the choice of filter parameters. Recently, our group proposed a method of automatically selecting the scale, bandwidth and orientation parameters of Log-Gabor filters. Previously, we showed our first clinical results using local phase information to identify distal radius fractures from B-mode US images using automatically selected filter parameters. The objective of the current study was to determine if the proposed automatic parameter selection method could produce accurate pelvic bone surface shapes in a live clinical setting. CT scans were obtained as part of normal clinical care from ten patients admitted to Vancouver General Hospital for pelvic fractures. A ‘gold standard’ bone surface was computed from the CT scan. After obtaining informed consent, we performed an additional US scan using a commercially-available real-time scanner (Voluson 730, GE Healthcare, Waukesha, WI) with a 3D US transducer. The PS bone surfaces were extracted from the US scans using the empirical Log-Gabor filter parameters and optimised Log-Gabor filter parameters. The bone surfaces on CT were extracted using a standard thresholding approach that minimises the intra-class variance. The US images were then registered to the CT images using a feature-based rigid registration algorithm with manual landmarking. The quality of the resulting surface matching was evaluated by computing the root mean square distance between the two surface representations. The average fiducial registration error was 0.31mm (SD 0.25mm). The average surface fitting error (SFE) was 0.72mm (SD 1.24 mm) for PS surfaces extracted using empirical filter parameters and 0.41mm (SD 0.44 mm) using the optimized filter parameters. In this study, we have demonstrated that our automatic filter parameter selection process can be applied successfully to a bone surface extraction task on 3D US images acquired under clinically realistic conditions. The accuracy of the resulting bone surface is excellent, with an average discrepancy relative to a CT standard of well under a millimeter. This level of accuracy is likely to be sufficiently good for a number of important surgical tasks, including CT to US registration

Percutaneous fixation of scaphoid fractures has become popular in recent years, mainly due to its reduced complexity compared to open surgical approaches. Fluoroscopy is currently used as guidance for this percutaneous approach, however, as a projective imaging modality, it provides only a 2D view of the complex 3D anatomy of the wrist during surgery, and exposes both patient and physician to harmful X-ray radiation. To avoid these drawbacks, 3D ultrasound has been suggested to provide imaging for guidance as a widely available, real-time, radiation-free and low-cost modality. However, the blurred, disconnected, weak and noisy bone responses render interpretation of the US data difficult so far. In this work, we present the integration of 3D ultrasound with a statistical wrist model to allow development of an improved ultrasound-based guidance procedure. For enhancement of bone responses in ultrasound, a phase symmetry based approach is used to exploit the symmetry of the ultrasound signal around the expected bone location. We propose an improved estimation of the local phase symmetry by using the local spectrum variation of the ultrasound image. The statistical wrist model is developed through a group-wise registration based framework in order to capture the major modes of shape and pose variations across 30 subjects at different wrist positions. Finally, the statistical wrist model is registered to the enhanced ultrasound bone surfaces using a probabilistic registration approach. Feasibility experiments are performed using two volunteer wrists, and the results are promising and warrant further development and validation to enable ultrasound guided percutaneous scaphoid fracture reduction

Previous attempts to measure coronal plane patellofemoral kinematics following knee replacement have suffered from methodological drawbacks; the patella being obscured by the components, metal artefact and technical inaccuracies. The aim of this study was to assess whether there was any significant difference in the patellofemoral kinematics between normal, TKR and PFJR patients using the validated MAUS™ technique (combining motion analysis with ultrasound). 60 patients were recruited into three groups; normal healthy volunteers (Normal), TKR, and PFJR patients. The MAUS technique incorporates a 12 camera analysis system (providing gross alignment data for tibial and femoral segments) and an ultrasound probe (providing coordinates of bony landmarks on patella femur and tibia) during a squat exercise. 6 DOF kinematics were described between 0 and 90° flexion. The validated accuracy of the MAUS technique registering the ultrasound images within the motion capture system is 1.84 mm (2 × SD). Movements of the Normal group were significantly different from the TKR group (p=0.03) and the PFJR group (p<0.01), whilst there was no significant difference between the TKR and PFJR groups (p=0.27). Our data suggest that many aspects of patellofemoral kinematics are absent following TKR and PFJR, which could be addressed in future designs of knee TKR and PFJR

Image-guided spine surgery requires registration between the patient anatomy and the preoperative computed tomography (CT) image. We have previously developed an accurate and robust registration technique for this application by using intraoperative ultrasound to acquire patient anatomy and then registering the ultrasound images to the CT images by aligning the posterior vertebral surfaces extracted from both modalities. In this study, we validate our registration technique across 18 vertebrae on three porcine cadavers. We applied the ultrasound-registration technique on the thoracic and lumbar vertebrae of the porcine cadavers using both single sweeps and double orthogonal sweeps. For each sweep pattern at each vertebra, we also randomly simulated 100 different initial misalignments and registered each misalignment. The resulting registration transformations are compared to gold standard registrations to assess the accuracy and the robustness of the technique. Orthogonal-sweep acquisition was found to be the sweep-pattern that performed the best and yielded a registration accuracy of 1.65 mm across all vertebrae on all porcine cadavers. It was found that the target registration errors (TRE) stay relatively constant with increasing initial misalignment and that the majority (82.7%) of the registrations resulted in TREs below the clinically recommended 2 mm threshold. In addition, it was found that the registration accuracy varies by the sweep pattern and the vertebral level, but neighbouring vertebrae tend to result in statistically similar accuracy. We found that our ultrasound-CT registration technique yields clinically acceptable accuracy and robustness on multiple vertebrae across multiple porcine cadavers

Tracked B-mode ultrasound (US) potentially provides a non-invasive and radiation-free alternative to percutaneous pointer digitization for intra-operative determination of the anterior pelvis plane (APP). However, most of the published approaches demand a direct access to the corresponding landmarks, which can only be presumed for surgical approaches with the patient in supine position. In order to avoid any change of the clinical routine for total hip arthroplasties (THAs), we propose a new method to determine the pelvic orientation, which could be performed in lateral position. Our proposed method is based on the acquisition of ultrasound images of the ipsilateral hemi-pelvis, namely the posterior superior iliac spines (PSISs) and iliac crest region. The US images are tracked by a navigation system and further processed to extract three-dimensional point clouds. As only one side of the pelvis is accessible, we estimate the symmetry plane (midsagittal plane) of the pelvis based on additionally digitized bilateral anterior superior iliac spine (ASIS) landmarks. This symmetry plane is further used to mirror the ipsilateral US-derived points to the contralateral side of the pelvis and to register and instantiate a pelvic SSM constructed from 30 CT-scans. The proposed registration method was evaluated using two plastic pelvis models and two cadaveric pelvises together with special custom-made silicone phantoms to simulate the missing soft-tissue. In each trial, the required data were collected with the pelvis rigidly fixed in lateral decubitus position together with ground truth APP landmarks. A registration error of 3.48° ± 1.10° was found for the anteversion angle, while the inclination angle could be reconstructed with a mean error of 1.26° ± 1.62°. The performed in-vitro experiments showed reasonably good results, taking the sparsity of the input point clouds into consideration

Ultrasound imaging has become an essential adjunct to clinical examination when assessing a patient with suspected rotator cuff pathology. With the new high-resolution portable machines it has become feasible for the shoulder surgeon to perform the scans himself in the clinic and save a great deal of time. This study was conducted to examine the accuracy of the ultrasound scans performed by a single surgeon over a period of four years (2001-2004). The ultrasound findings were uniformly documented and collected prospectively. Out of a total of 364 scanned patients we selected 143 who ultimately received an operation and we compared the surgical findings with the ultrasound reports. The intra-operative findings included 77 full thickness supraspinatus tears, 24 partial thickness tears and 42 normal cuffs. Three full thickness tears were missed on ultrasound and reported as normal/ partially torn. Four normal/ partially torn cuffs were thought to have a full thickness tear. This presents 96.3% sensitivity and 94.3% specificity for full thickness tears. Three partial thickness tears were reported normal on ultrasound and eight normal cuffs were thought to have partial thickness tears. This presents 89% sensitivity and 93.7% specificity for partial thickness tears. The size estimation of full thickness tears was more accurate for large/massive tears (96%) than moderate (82%) and small/pinhole tears (75%). The tear sizes were more often underestimated which may partly reflect disease progression during the unavoidable time lag between scan and surgery. We conclude that shoulder ultrasound performed by a sufficiently trained orthopaedic surgeon is a safe and reliable practice to identify rotator cuff tears

Purpose. There are concerns of soft-tissue reactions such as metal hypersensitivity or pseudotumors for metal-on-metal (MoM) bearings in hip arthroplasty, however, such reactions around ceramic or polyethylene bearings are incompletely understood. The present study was conducted to examine the capabilities of ultrasound screening and to compare the prevalence of periarticular soft-tissue lesions among various types of bearings. Methods. Ultrasound examinations were conducted in 163 hips (153 patients) with arthroplasty after mean a follow-up of 8.1 years (range, 1–22 years). This included 39 MoM hip resurfacings (M-HR) including 30 Birmingham hip resurfacings (BHR) and 9 ADEPT resurfacings; 36 MoM total hip arthroplasties (M-THA) with a large femoral head including 26 BHR and 10 ADEPT bearings; 21 ceramic-on-ceramic THAs (C-THA) of Biolox forte alumina bearings; 24 THAs with a conventional polyethylene liner (cPE-THA) including 19 Lubeck and 5 Omnifit systems; and 43 THAs with a highly cross-linked polyethylene liner (hxPE-THA) including 28 Crossfire and 15 Longevity liners. All procedures were performed in the lateral position through the posterior approach without trochanteric osteotomy. The M-HR group had a significantly higher frequency of male patients than the C-THA, cPE-THA, and hxPE-THA groups, and the patients in the M-HR group were younger than those in the other four groups. Ultrasound images were acquired as a still picture and in video format as the hip moved in flexion and rotation, and 4 qualitative classifications for periarticular soft-tissue reactions were determined as normal pattern, joint-expansion pattern (marked hypoechoic space between the anterior capsule and the anterior surface of the femoral component), cystic pattern (irregularly shaped hypoechoic lesions), and mass pattern (a large mass extending anterior to the femoral component). Magnetic resonance imaging (MRI) was subsequently performed in 45 hips with high-frequency encoding bandwidths. For the reliability of ultrasound screening, positive predictive value, negative predictive value, and the accuracy of the presence of abnormal patterns on ultrasound were calculated using the abnormal lesions on MRI as a reference. Results. Among the 45 hips that underwent MRI, periarticular abnormal lesions were detected in 26 hips (58%). Using MRI findings as reference, positive predictive value, negative predictive value, and the accuracy of ultrasound examination for the detection of soft-tissue lesions were 83%, 71%, and 78%, respectively. Abnormal ultrasound lesions with joint expansion, cystic, or mass patterns were most frequently observed in the cPE-THA group (50%), followed by the M-THA (25%), hxPE-THA (23%), M-HR (18%), and C-THA groups (14%). Compared to the hxPE-THA group, the frequency of abnormal patterns did not differ significantly in the two MoM groups. A mass pattern was detected in 3 hips of the M-THA group and 1 hip of the C-THA group (Figure 1). Abnormal ultrasound lesions were significantly associated with the presence of symptoms. Conclusion: Various soft-tissue reactions could be observed other than those for MoM bearings, and pseudotumors may not be a specific feature of MoM bearings. Ultrasound examination may be a suitable screening tool for further large prospective investigations of soft-tissue reactions around various types of bearings

For a successful total knee arthroplasty (TKA) and long prosthesis lifespan, correct alignment of the implant components as well as proper soft tissue balancing are of major importance. In order to overcome weaknesses of existing imaging modalities for TKA planning such as radiation exposure and lack of soft tissue visualisation (X-ray and CT) and high cost, long acquisition times and geometric distortion (MRI), it is investigated if ultrasound (US) imaging is a suitable alternative. Currently, a reconstruction method of the bony knee morphology based on US imaging is developed at our research institute. For capturing the mechanical axis, being crucial for TKA planning, different approaches could be implemented. This work investigates whether a weight-bearing full leg X-ray registered with the local 3D-US knee dataset can be used for this purpose. Also, the impact of incorrect calibration data (i.e. uncalibrated X-rays) on the accuracy of the estimated mechanical axis is investigated. A 3D-2D projective, feature-based registration algorithm was used to spatially align the 3D US-based model to the 2D X-ray image before transferring the mechanical axis from the X-ray to the model. For validation, a CT-based local model and its projection were used and an initial error in translation and rotation was added. Also, calibration parameters such as the centre ray position and the source-to-image-detector distance were altered. The estimation error of the mechanical axis was less than 1°, the median error lower than 0.1° in the frontal plane. Even if the calibration data is not available, the accuracy remains sufficient for TKA planning. In this study, idealised 2D and 3D image information was used. In the future, this method should be tested using clinical X-ray images and 3D-US data

Ultrasound (US) imaging is recommended for early detection of Developmental Dysplasia of the Hip (DDH) to guide decisions about possible surgical treatment. However, a number of studies have raised concerns over the efficacy of US in early diagnosis. The main limitation of US-based diagnosis is sub-standard reliability of the primary dysplasia metric measurements: namely, the alpha and beta angles. In this study, we have proposed a novel and automatic method to extract dysplasia metrics from 2D US, which we hope will improve the overall reliability of US-based DDH measurements by removing error due to subjective measurements. We hypothesise that improvements in reliability of dysplasia metric measurements will reduce the chances of missed early-diagnosis, and therefore reduce the need for later complex surgical treatments. We evaluated performance of the algorithm on 4 infants diagnosed with US scans for DDH. The typical runtime of our algorithm is less than 1 second for an US image. We found a 6° bias between manual and automatic measurements, with automatic measurements tending to be lower in value; the standard deviation in the discrepancy values was also relatively high at 7°. This suggests that there is considerable variability in the angle estimation process, which is typically done manually, which supports our contention that further work needs to be done to establish an accurate and repeatable measurement technique. Further, we found agreements in the Graf-classification types in six out of seven sessions. For the one patient where there was a discrepancy in classification, later US sessions suggest the manual technique possibly missed the opportunity for early detection, in contrast to the automatic method which classified the patient as having evidence of dysplasia. Thus, such an automatic method may improve the reliability of current US-based DDH diagnosis techniques. The primary limitation of this study is that we have done strictly an intra-image discrepancy analysis and have not compared the results with what could be considered a ‘gold standard’ reference. In future work, we plan to assess these indices on 3D images of the hip and assess the accuracy of proposed 2D and 3D-based automatic index calculation techniques against a 3D reference model

INTRODUCTION. Over the last twenty years, image-guided interventions have been greatly expanded by the advances in medical imaging and computing power. A key step for any image-guided intervention is to find the image-to-patient transformation matrix, which is the transformation matrix between the preoperative 3D model of patient anatomy and the real position of the patient in the operating room. In this work, we propose a robust registration algorithm to match ultrasound (US) images with preoperative Magnetic Resonance (MR) images of the Humerus. MATERIALS AND METHODS. The fusion of preoperative MR images with intra-operative US images is performed through an NDI Spectra® Polaris system and a L12-5L60N TELEMED® ultrasound transducer. The use of an ultrasound probe requires a calibration procedure in order to determine the transformation between an US image pixel and its position according to a global reference system. After the calibration step, the patient anatomy is scanned with US probe. US images are segmented in real time in order to extract the desired bone contour. The use of an optical measurement system together with trackers and the previously-computed calibration matrix makes it possible to assign a world coordinate position to any pixel of the 2D US image. As a result, the set of US pixels extracted from the images results in a cloud of 3D points which will be registered with the 3D Humerus model reconstructed from MR images. The proposed registration method is composed of two steps. The first step consists of US 3D points cloud alignment with the 3D bone model. Then, the second step performs the widely-known Iterative Closest Point (ICP) algorithm. In order to perform this, we define the coordinate system of both the 3D Humerus model and the US points cloud. The frame directions correspond to the directions of the principal axes of inertia calculated from the matrices of inertia of both the preoperative 3D model and the US data obtained intra-operatively. Then, we compute the rotation matrix to estimate the transformation between the two coordinate systems previously calculated. Finally the translation is determined by evaluating the distance between the mass centres of the two 3D surfaces. RESULTS. In order to evaluate the performance of this registration method in terms of precision and accuracy, we performed the US/MRI fusion on 8 patients. The evaluation criterion used for the validation step was the fiducial registration error (FRE) estimation based on 8 anatomic fiducials detected on the Humerus of the patient. The mean, standard deviation, minimum and maximum values of the 8 Fiducial Registration Errors were 4.34, 2.20, 2.81 and 9.48 mm, respectively. DISCUSSIONS. In this work, we propose a robust registration method of MR and US data. Thanks to the optical system, this fusion will allow us for example to guide and assist surgeons in the positioning of the radiofrequency probe for bone tumor ablation. In addition to the fact that it is completely automatic, the proposed image-to-patient registration method is minimally invasive

Purpose. Radiographs are the most common imaging modality used to guide orthopaedic interventions. Ultrasound (US) imaging offers potential advantages for intraoperative imaging by its portability and ability to produce real-time 2D or 3D images without radiation to either the patient or surgical team. Our objective in this study was to determine in a live emergency room setting, if a newly-developed image processing method for 3D US would allow us to accurately extract (reproduce) the surfaces of fractured bones. Method. We obtained both CT scans and US images from consenting patients admitted to our Level 1 Trauma Centre for radius or pelvic fractures clinically requiring a CT scan. All US examinations in this clinical study were performed with a GE Voluson 730 machine with a 3D RSP5-12 transducer (a mechanized probe in which a linear array transducer is swept through an arc range of 20). Dorsal, volar, and radial views were obtained in the case of radial fractures and iliac crest views in the case of pelvic fractures. The bone surfaces on CT were extracted using a thresholding algorithm [1]. Standard, clinical 3D reconstructions were also created using GE Voxtool 4.0.1 to serve as a qualitative comparison. The US images were processed using the phase-processing algorithm described in [2] then registered to the CT images using a manually-supervised anatomical landmark-based rigid registration algorithm. The quality of the resulting surface matching was evaluated by computing the root mean square distance between the two surface representations [2] and by inter-observer agreement of the registered images to the clinical renderings. Results. Overall, 8 patients were scanned (3 distal radius and 5 pelvic fracture). Quantitative and qualitative outcomes were recorded. The RMS surface fitting error averaged 0.41mm across the 8 patients, with a maximum point-wise error of under 1.0 mm. Qualitatively, clinicians demonstrated a high level of agreement in the ability of the 3D US surfaces to represent the clinical 3D CT reconstructions. Conclusion. The RMS error in these 8 clinical cases was significantly lower than the threshold of 2–4 mm previously cited as useful for development of clinical fracture care applications in near-real time. While US has some limitations that prevent it from completely replacing conventional radiography, it may minimize radiation following fracture reduction. The encouraging experimental results of this initial clinical study demonstrate the potential benefits of the proposed method; while, further investigation will define its potential opportunities and limitations

Introduction. 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. Methods. 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. Results. The developed system was tested on two cadavers' knees. The cadavers' knees were CT-scanned and manually segmented. The reconstructed models using ultrasound were then compared to the segmented models. An average error of 2 mm was achieved. Figure 6 shows sample ultrasound RF signals, and their processed version and the extracted bone echoes. Figure 7 shows sample ultrasound frames and the extracted bone contours from them. Figure 8 shows the reconstructed point clouds and 3D models for two distal femurs and a proximal tibia

This article presents an overview of mycetoma and offers guidelines for orthopaedic surgeons who may be involved in the care of patients with this condition.

Cite this article: Bone Joint J 2014;96-B:420–5.