Knee Images Research Articles

Qualitative and Quantitative Evaluation of Morpho-Metabolic Changes in Bone Cartilage Complex of Knee Joint in Osteoarthritis Using Simultaneous 18F-NaF PET/MRI-A Pilot Study.

Background Articular cartilage (AC) loss and deterioration, as well as bone remodeling, are all symptoms of osteoarthritis (OA). As a result, an ideal imaging technique for researching OA is required, which must be sensitive to both soft tissue and bone health. Objective The aim of this study was to assess the potential of simultaneous 18F sodium fluoride (18F-NaF) positron emission tomography/magnetic resonance imaging (PET/MRI) to identify as well as classify osseous metabolic abnormalities in knee OA and to see if degenerative changes in the cartilage and bone on MRI might be correlated with subchondral 18F-NaF uptake on PET. Methods Sixteen (32 knees) volunteers with no past history of knee injury, with or without pain, were enrolled for the research from January to July 2021. The images of both knees were taken utilizing an molecular magnetic resonance (mMR) body matrix coil on a simultaneous PET/MRI biograph mMR. The acquisition was conducted after 45 minutes of intravenous infusion of 18F-NaF 185-370 MBq (5-10 mCi) over one PET bed for 40 minutes, while MRI sequences were performed simultaneously. Results All pathologies showed significantly higher maximum standardized uptake value (SUV max ) than the background. Thirty-four subchondral magic spots were identified on 18F-NaF PET without any structural alteration on MRI. Bone marrow lesions (BMLs) and osteophytes with higher MRI osteoarthritis knee score (MOAKS) score showed higher 18F-NaF uptake (grade1˂grade2˂grade3). BMLs had corresponding AC degeneration. There was discordance between grade 1 osteophytes (86.6%), sclerosis (53.7%) and grade 1 BML in cruciate ligament insertion site (91.66%); they did not have high uptake of 18F-NaF. In case of cartilage, there was significant difference between AC grades and average subchondral SUV max and T2* relaxometry (grade0˂grade1˂grade2˂grade3˂grade4). BMLs are much more metabolically active than other pathologies, while sclerosis is the least. We also found that the subchondral uptake was statistically increased in the areas of pathology: Conclusion 18F-NaF PET/MRI was able to detect knee abnormalities unseen on MRI alone and simultaneously assessed metabolic and structural markers of knee OA across multiple tissues in the joint. Thus, it is a promising tool for detection of early metabolic changes in OA.

PREDICTING MECHANICAL LEG ALIGNMENT FROM KNEE X-RAY IMAGES BY UTILIZING DEEP-LEARNING NEURAL NETWORKS

Several studies have linked leg malalignment to early onset and progression of knee OA. Detecting abnormalities in mechanical alignment before radiographic evidence of knee OA is present, might increase the rate of early detection. Hence, conservative joint preserving interventions or even osteotomies could reduce the need or delay full joint replacement. In addition, medical trials often face high dropout rates, consequently, AI based support could improve the recruitment process. Detecting mechanical leg malalignment: 1) before the malalignment is immediately obvious to the clinician and 2) excluding/including patients recruited for medical trials. This study utilized a dataset of 8,878 digital radiographs ((I) 6,181 AP/PA full-leg x-rays, (II) 2,292 AP/PA knee x-rays with SynaFlexer positioning frame, (III) 405 AP/PA knee x-rays captured without SynaFlexer). The images were obtained from a diverse range of sources, including the OAI study, the University for Continuing Education Krems (AT), and five additional sites in Austria and the US. All knee images in the dataset were accompanied by their corresponding full-leg images, obtained on the same day. To determine the ground-truth hip-knee-ankle angle (HKA), the full-leg images were processed using IB Lab LAMA (ImageBiopsyB Lab, Vienna, Austria), a commercial software that automatically determines clinical measurements from full-leg radiographs. These images were used to train the AI algorithm. The algorithm produced binary outputs for HKA threshold values of 5° (clinically relevant) and 7.5° (clinical trial relevant). The algorithm reached MAE rates of 0.98° (cropped full-leg), 1.56° (SynaFlexer knee) and 2.10° (non-SynaFlexer knee). Summarizing all image modalities, the overall performance for the 5° threshold was 74-86% Sensitivity and 79-90% Specificity. Following, 7.5° threshold performance reached 81-92% Sensitivity and 85-92% Specificity. While this study primarily focused on absolute HKA threshold values of 5° and 7.5° for varus/valgus classification, this threshold determination process is highly adaptable to accommodate specific use cases, such as the desired angle threshold for classification or the preferred balance between sensitivity and specificity. In addition, overestimated HKA have an elevated angle above the normal range and could proceed towards or above mentioned thresholds. Chen K. PhD funding “LowerAustria Society for Scientific Research” (LSC20-020). Salzlechner C. and Lepenik C. are employees of ImageBiopsy Lab. Ljuhar R. is a shareholder of ImageBiopsy Lab. This manuscript was prepared using an OAI public use data set and does not necessarily reflect the opinions or views of the OAI investigators or the NIH. Lepenik C. thanks Avelar C. for comments on an early version of this article. CORRESPONDENCE ADDRESS: [email protected]

Practical Approach to Address Failed ACL Reconstruction Surgery

The causes of ACL reconstruction (ACLR) failure can be divided into 3 major categories. Non-anatomic tunnel placement has been the most widely stated technical error in ACL repair. A thorough medical history is necessary and crucial to determine the likely cause of failure in the initial surgery. As such, the medical history and physical examination should be evaluated. In addition, physical examination of the knee should be performed such as alignment of lower extremities, existence of varus and or valgus deformity, presence of contractures in flexion or extension and special tests to evaluate ACL. Moreover, imaging by radiography which includes anteroposterior, lateral, Merchant and Rosenberg views must be consider evaluating. Failure of an ACLR may not necessarily need revision surgery. Patients with bi/tri-compartmental arthritis or regional pain syndromes, those without recurring instability, those who live a sedentary lifestyle, or those who refuse to participate in post-operative rehabilitation may not be ideal candidates for revision ACLR. Patients with a failed ACL reconstruction commonly presenting with sign and symptoms of instability, stiffness, and pain. The choice of graft is critical to procedure’s success. In the revision setting, fixation is just as critical as graft selection. The aim of the revision surgery is to stabilize the knee joint, prevent further damage to the cartilage and the menisci, and allow the patient to resume normal daily and/or sports activities. A successful revision surgery requires accurate preoperative patient evaluation and knee imaging.

Generation of synthetic FLAIR MRI image from real CT image for accurate synovial fluid segmentation in human knee image

Synthetic MRI FLAIR images of an abdominal 3D multimodality phantom and in vivo human knee have been generated from real CT images using predefined mapping functions of CT mean and standard deviation with the corresponding proton density PD, T1 and T2 that were previously generated from spin-echo sequence. First, the validity of generating synthetic MR images from different sequences were tested and the same PD, T1 and T2 maps that were generated from the real CT image have been used in the simulation of MRI inversion-recovery (IR) sequence. The similarity results between the real and synthetic IR sequence images, using different inversion times TI, showed a very good agreement. After confirming the feasibility of generating synthetic IR images from the PD, T1 and T2-maps, that were originally obtained from spin-echo sequence using the phantom, the simulation of a knee image has been generated from the corresponding knee CT real image using the steady-state transverse magnetization formula of the inversion-recovery sequence. The simulated FLAIR IR sequence MR image are generated using proper TI for nulling the signal from the synovial fluid, where the image complement is used as a mask for segmenting the corresponding tissue region in the real CT image.

Determination of spatial position of tibial graft using X-ray images after anterior cruciate ligament reconstruction

Background/Aim. Anterior cruciate ligament reconstruction is one of the most commonly performed knee surgeries in young adults. The success of this procedure largely depends on the proper formation of the tunnel, which is obtained by drilling the tibia and which serves to position and fix the graft. The aim of the study was to present a method for determining the spatial position of the graft based on only two standard X-rays. Methods. The study was performed on a group of 15 patients in whom the developed software applied the measurement of the angle of the tunnel in the tibia based on the selection of characteristic points on two standard X-rays of the knee (anterior-posterior and lateral projection). The obtained results were compared with the results of measuring the angle of the tunnel in the tibia on knee images by computed tomography (CT) in all patients. Results. The drilling angle measured in CT scans was, on average, some-what greater (59.07? ? 5.61?) than the angle measured by applying a developed application (58.65? ? 5.89?). The obtained results indicated minimal differences without statistical significance in the measurements of the angle of the tunnel in the tibia using the developed software and on CT images (Wilcoxon test: Z = -1.363; p = 0.173). Conclusion. The presented method and developed software are suitable for everyday clinical applications in terms of precision and usability and can be used to assess the position of tunnels in the tibia in the process of determining the success of surgery or in preparing patients for revision surgery.

SYNTHETIC CT GENERATION FROM T1-WEIGHTED KNEE MRIs USING A UNET

Despite recent evolution in magnetic resonance imaging (MRI) techniques for musculoskeletal applications, computed tomography (CT) remains the reference modality for the assessment of bone structure. The use of generative deep learning models, such as U-Nets, was shown to enable the synthesis of CT-like contrasts from MRI images. However, the development and validation of such tools have been hindered by the need for large datasets with paired CT and MRI acquisitions. In this preliminary work, we propose to train a U-Net, a supervised deep learning technique, to generate synthetic CT (sCT) knee images from three-dimensional T1-weighted MRI scans by leveraging a large knee dataset with paired acquisitions. The synthetic CT images were then assessed quantitatively and qualitatively. A cohort consisting of 249 patients (39.7±16.0 years old, 133 females) received both a knee MR examination (3T MAGNETOM Prismafit, Siemens Healthcare, Erlangen, Germany) and a CT scan (Revolution, General Electronics Healthcare). T1-weighted MR images (TR 700ms, TE 11ms, 0.5mm isotropic) were spatially registered to the down-sampled CT data (originally 0.3mm isotropic). To ensure a good voxel-to-voxel correspondence, the 99 best registered image pairs were selected and split between training (80%), testing (10%) and validation sets (10%). During training, 100 central slices were extracted for each orientation (axial, coronal and sagittal) and fed to a 2.5D network as stacks of three consecutive MRI slices. At inference, sCT slices were generated for each orientation, and the voxel-wise median across orientations was computed. Qualitatively, our method successfully generated images with a CT-like contrast exhibiting satisfactory levels of anatomical details, including bone contours, and the femoral and tibial physes. However, the sCT images looked generally oversmoothed compared to the original CT data, hindering the visualization of some of the bone trabeculae, especially in the epiphyses. Some anatomical details such as vascular canals were not depicted accurately. In terms of quantitative evaluation, our model achieved a mean average error of 167±23.1 and 49.5±6.76 Hounsfield Units (HU) in bone and soft tissue, respectively. In this preliminary work, we showed the feasibility of generating sCT images from T1-weighted MR data with a good level of anatomical details and quantitative HU estimation. Future work will focus on reducing the impact of registration errors to further improve the model accuracy.

Knee Osteoarthritis Detection Using an Improved CenterNet With Pixel-Wise Voting Scheme

To detect knee disease, radiologists have been utilizing multi-view images such as computer tomography (CT) scans, MRIs, and X-rays. The cheapest method is X-ray to attain the images that is used widely. There exist various image processing techniques to detect knee disease at the initial stages; however, there is still room for improved accuracy and precision of the existing algorithms. Furthermore, in machine learning-based techniques, hand-crafted feature extraction mechanism is a tedious task. Therefore, in this paper, we suggest a technique based on customized CenterNet with a pixel-wise voting scheme to extract the features automatically. Our model uses the most representative features due to the best localization results and a weighted pixel-wise voting scheme which takes input from a predicted bounding box using modified CenterNet. It gives a more accurate bounding box based on the voting score from each pixel inside the former box. Moreover, we employed the distillation knowledge concept to make our model simple without increasing its computational cost, and transfer knowledge from a complex network to a simple network. Therefore, our proposed model detects the KOA in knee images precisely and determines its severity level according to the KL grading system such as Grade-I, Grade-II, Grade-III, and Grade-IV. Our proposed model is a robust and improved architecture based on CenterNet utilizing a simple DenseNet-201 as a base network for feature extraction. Due to the dense blocks employed in a base network, most representative features are extracted from the knee samples. We employed two benchmarks i.e. Mendeley VI for the training, and testing, and the OAI dataset for cross-validation. We evaluated the performance of the proposed technique using various experiments and it is estimated that our proposed model outperforms the existing techniques with an accuracy of 99.14% over testing and 98.97% over cross-validation.

WEIGHT BEARING 3-D JOINT SPACE WIDTH DISTRIBUTION AT THE KNEE VARIES ACCORDING TO LOCATION AND EXTENT OF MENISCAL EXTRUSION: A MOST INVESTIGATION

Quantitative 3-D measurement of joint space width (JSW) from weight bearing computed tomography (WBCT) allows analysis of knee tibiofemoral compartments in a loaded stance without subregional constraints on analysis. The relationship between 3-D JSW distribution and meniscal extrusion is yet to be established. To demonstrate topographic variations in 3-D JSW distribution at the knee derived from WBCT imaging data according to meniscal extrusion location and extent. WBCT knee imaging was acquired at the 144-month visit of the Multicenter Osteoarthritis Study (MOST). A subset of individuals had medial and lateral meniscal extrusion grading according to the MRI Osteoarthritis Knee Score to identify medial extrusion of the medial meniscus (MMmed), anterior extrusion of the medial meniscus (MMant), anterior extrusion of the lateral meniscus (LMant), and lateral extrusion of the lateral meniscus (LMlat). The extent of extrusion was graded as 0: <2 mm; 1: 2 to 2.9 mm, 2: 3 to 4.9 mm; and 3: >5 mm. After semi-automatic segmentation of 663 baseline knees, joint space mapping was performed to create 3-D JSW maps for each knee registered to a template surface. Statistical parametric mapping (SPM) was performed using a general linear model to test the dependence of 3-D JSW distribution on each of meniscal extrusion type in turn. SPM results were plotted on the canonical joint surface, with unmasked regions demonstrating the topographic difference in JSW for each increment in extrusion score. 568 knees from 330 participants had meniscal extrusion grading available. Participants (178 female) had mean ± SD age 62.0 ± 9.3 years, body mass 82.2 ± 17.4 kg, height 170 ± 9.5 cm, and BMI 28.3 ± 4.8 kg/m2. Analysed knees were bilateral for 238 participants and unilateral for 92 participants. For MMmed (cohort score range 0-3), the central-to-posterior medial compartment had significantly lower JSW by up to 0.4 mm for each increment in meniscal extrusion grade. Both MMmed and MMant (score range 0-3) were associated with a small region of similarly significantly lower JSW along the medial margin of the lateral compartment, but also with significantly greater JSW at the anterior medial compartment of up to 0.6 mm per grade. The posterior medial joint space was significantly narrower (up to 3 mm) comparing knees with LMant scores of 0 vs 1. This same magnitude of narrowed JSW was detected along the periphery of the lateral joint space comparing grades in the lateral tibiofemoral compartment, but this was not statistically significant. LMlat (score range 0-2) was associated with a trend for greater reduction in JSW in the central lateral compartment of up to 0.5 mm per grade, but this was not statistically significant. Direction of meniscal extrusion is represented by the black arrowhead in the figure. Both medial and anterior extrusion of the medial meniscus are associated with significant reduction in JSW at the medial margin of the lateral joint space and widening of the anterior margin, likely from a posteromedial shift of the femoral condyles with respect to the tibia. Medial extrusion of the medial meniscus is also associated with narrowed JSW in the central to posterior medial joint space, likely as a direct effect of the loss of meniscal hoop tension. Anterior (but not lateral) extrusion of the lateral meniscus is associated with significantly lower JSW in the posterior medial joint space. These findings confirm that the extent and location of meniscal extrusion are key factors in weight bearing 3-D JSW distribution.

An automated, web-based triage tool may optimise referral pathways in elective orthopaedic surgery: A proof-of-concept study.

Knee pain is caused by various pathologies, making evaluation in primary-care challenging. Subsequently, an over-reliance on imaging, such as radiographs and MRI exists. Electronic-triage tools represent an innovative solution to this problem. The aims of this study were to establish the magnitude of unnecessary knee imaging prior to orthopaedic surgeon referral, and ascertain whether an e-triage tool outperforms existing clinical pathways to recommend correct imaging. Patients ≥18 years presenting with knee pain treated with arthroscopy or arthroplasty at a single academic hospital between 2015 and 2020 were retrospectively identified. The timing and appropriateness of imaging were assessed according to national guidelines, and classified as 'necessary', 'unnecessary' or 'required MRI'. Based on an eDelphi consensus study, a symptom-based e-triage tool was developed and piloted to preliminarily diagnose five common knee pathologies and suggest appropriate imaging. 1462 patients were identified. 17.2% (n = 132) of arthroplasty patients received an 'unnecessary MRI', 27.6% (n = 192) of arthroscopy patients did not have a 'necessary MRI', requiring follow-up. Forty-one patients trialled the e-triage pilot (mean age: 58.4 years, 58.5% female). Preliminary diagnoses were available for 33 patients. The e-triage tool correctly identified three of the four knee pathologies (one pathology did not present). 79.2% (n = 19) of participants would use the tool again. A substantial number of knee pain patients receive incorrect imaging, incurring delays and unnecessary costs. A symptom-based e-triage tool was developed, with promising performance and user feedback. With refinement using larger datasets, this tool has the potential to improve wait-times, referral quality and reduce cost.

COMPARISON OF NEW MR APPROACHES FOR ACCELERATED KNEE IMAGING

COMPARISON OF NEW MR APPROACHES FOR ACCELERATED KNEE IMAGING

No risk of iatrogenic peroneal nerve injury in all-inside lateral meniscal repair with either 14- or 18-mm needles through the popliteus tendon in the standard arthroscopic knee conditions.

The objectives of this prospective study were to evaluate the risk of peroneal nerve (PN) injury in simulated all-inside lateral meniscal repair with sutures placed through the popliteus tendon (PT) and to determine the optimal needle length. Twenty-nine axial magnetic resonance images (MRI) of postoperative knees with infused intra-articular fluid and in a figure-of-four position were used. The cross-sectional length of the PT was divided into four equal parts with measurements performed at the 25%, 50% and 75% points according to their anteroposterior arrangement. Simulated repairs were performed with 14-mm and 18-mm straight needles via the anteromedial (AM) and anterolateral (AL) portals. Distances from the needle tip following full insertion through the PT to the PN and from the anterior PT border to the posterior knee capsule were measured to determine PN injury risk and ideal needle insertion depths at the different landmarks. Simulated repairs onthe 29 knee MRI images resulted in no incidences of PN injury. The average distances from the needle tip to the PN of the 14-mm needle were significantly greater than the 18-mm needle in all the simulated repairs (P < 0.02), except at the 25% point in the AM approach. When using the 14-mm needle, capsule underpenetration was found in three knees (10.3%) at the 25% point during the AM approach, in one knee (3.4%) at the 50% and 75% points in the AM approach, and in all repairs from the AL portal. The average distances from the anterior PT border to the capsule at the 25%, 50%, and 75% division points on the PT in the AM approach were 7.7 ± 2.7mm, 7.9 ± 2.5mm and 7.6 ± 2.8mm, respectively, whilst in the AL approach were 8.4 ± 2.9mm, 8.1 ± 2.8mm and 7.6 ± 2.7mm. Simulated all-inside lateral meniscal repair with suture placement through the PT with 14-mm and 18-mm needles was safe. The measurements in this study can be used to determine potential PN injury risk in relation to the PT and the appropriate needle length for safe lateral meniscal repairs.

Robust automatic hexahedral cartilage meshing framework enables population-based computational studies of the knee.

Osteoarthritis of the knee is increasingly prevalent as our population ages, representing an increasing financial burden, and severely impacting quality of life. The invasiveness of in vivo procedures and the high cost of cadaveric studies has left computational tools uniquely suited to study knee biomechanics. Developments in deep learning have great potential for efficiently generating large-scale datasets to enable researchers to perform population-sized investigations, but the time and effort associated with producing robust hexahedral meshes has been a limiting factor in expanding finite element studies to encompass a population. Here we developed a fully automated pipeline capable of taking magnetic resonance knee images and producing a working finite element simulation. We trained an encoder-decoder convolutional neural network to perform semantic image segmentation on the Imorphics dataset provided through the Osteoarthritis Initiative. The Imorphics dataset contained 176 image sequences with varying levels of cartilage degradation. Starting from an open-source swept-extrusion meshing algorithm, we further developed this algorithm until it could produce high quality meshes for every sequence and we applied a template-mapping procedure to automatically place soft-tissue attachment points. The meshing algorithm produced simulation-ready meshes for all 176 sequences, regardless of the use of provided (manually reconstructed) or predicted (automatically generated) segmentation labels. The average time to mesh all bones and cartilage tissues was less than 2min per knee on an AMD Ryzen 5600X processor, using a parallel pool of three workers for bone meshing, followed by a pool of four workers meshing the four cartilage tissues. Of the 176 sequences with provided segmentation labels, 86% of the resulting meshes completed a simulated flexion-extension activity. We used a reserved testing dataset of 28 sequences unseen during network training to produce simulations derived from predicted labels. We compared tibiofemoral contact mechanics between manual and automated reconstructions for the 24 pairs of successful finite element simulations from this set, resulting in mean root-mean-squared differences under 20% of their respective min-max norms. In combination with further advancements in deep learning, this framework represents a feasible pipeline to produce population sized finite element studies of the natural knee from subject-specific models.

A Semi-Blind Calibration and Compensation Method for Dynamic Range Recovery of Low-Power Pre-Amplifiers in MRI Receive Chains.

To enable wireless MRI receive arrays, per-channel power consumption must be reduced by a significant factor. To address this, a low-power SiGe alternative to industry standard MRI pre-amplifier blocks has been proposed and its impact on imaging performance evaluated in a benchtop environment. The SiGe amplifier reduces power consumption 28x, but exhibits increased non-linearity and reduced dynamic range relative to industry standard amplifiers. This distorts the images, causing reduced contrast and a blurring of fine features. In conjunction with the amplifier, a semi-blind calibration and compensation framework has been proposed to remove artifacts caused by this non-linearity. Requiring the knowledge of the calibration signal bandwidth, the associated peak transmit powers, and the distorted baseband signals, a second non-linearity is constructed that when cascaded with the receive chain produces a linear response. This method was evaluated for both knee and phantom image datasets of peak input power -20dBm with a -40dBm peak input power image as reference. In the benchtop environment, industry standard amplifiers produced input normalized RMSEs of 0.0199 and 0.0310 for phantom and knee datasets, respectively. The low-power SiGe amplifier resulted in RMSEs of 0.0869 and 0.1130 which were reduced to 0.0158 and 0.0168 following compensation, for phantom and knee images respectively. The ability to effectively compensate for this reduced dynamic range encourages further investigation of low-power SiGe amplifiers for power limited MRI receive arrays.

Mid-term clinical outcomes of a posterior stabilized total knee prosthesis for Japanese patients: A minimum follow-up of 5 years

BackgroundA high–flexion posterior-stabilized total knee prosthesis has been developed for the Asian population. The component design was based on computed tomography images of Japanese osteoarthritic knees. The femoral component is composed of zirconia ceramics, which exhibit low friction and high durability. The present study aimed to evaluate the mid-term clinical outcomes of this implant. MethodsThis study included 334 knees of 210 patients who underwent primary total knee arthroplasty with this implant at our hospital between October 2010 and December 2014. The patients comprised 28 men and 172 women with an average age of 73 years. The average follow-up period was 5.9 years, and the follow-up rate was 71.1%. Clinical outcomes were assessed using the Knee Society scoring system, 2011 Knee Society questionnaire, and Knee Injury and Osteoarthritis Outcome Score. Kaplan–Meier survivorship analysis was performed to determine the cumulative prosthesis survival rate. ResultsIn terms of clinical outcomes at the final follow-up, the average ranges of motion were −2.0 in extension and 126.7 in flexion. The Knee Society knee and function scores were 94.2% and 72.6%, respectively. With revision surgery or radiographic failure for any reason as the endpoint, the survival rates at 5 and 9 years were 98.2% and 95.5%, respectively. The most common reason for revision surgery or radiological failure was aseptic loosening. ConclusionsDespite several revision cases mainly due to aseptic loosening, the present study found that this new high-flexion posterior-stabilized total knee arthroplasty prosthesis design showed comparable results for Asian populations with other PS prosthesis. Levels of evidenceLevel Ⅱ (Prospective cohort study).

The impact of body mass index on patient radiation dose in general radiography

The aim of the present study was to determine the influence of the body mass index (BMI) on the dose area product (DAP) and effective dose (ED) in overweight and obese patients. We also wanted to determine the typical dose values as well as suggest adjustments to clinical practice for overweight and obese patients. In this study we considered 597 patients referred for imaging of the chest in posteroanterior and lateral projection, the lumbar spine in anteroposterior (AP) and lateral projection, the pelvis, the knee in AP and lateral projection, and the shoulder in AP projection. For each examination, the image field size, tube voltage, mAs product, source-to-image receptor distance and values of DAP were collected. Based on their BMI, the patients were divided into three groups (normal weight, overweight and obese). At the end, PCXMC 2.0 software was used to calculate the ED. The study showed a statistically significant DAP and ED increase in overweight and obese patients by 28.9% up to 275.4% in the case of DAP and an increase in ED from 11.0% to 241.9% in all mentioned examinations except knee and shoulder imaging. Typical DAP values ranged from 2.2 to 54.8 µGym2 for normal-weight patients, from 2.2 to 87.6 µGym2 for overweight patients, and from 2.2 to 172.5 µGym2 for obese patients. Spearman’s correlation coefficient revealed very weak to very strong correlations when comparing BMI and DAP, as well as when comparing BMI and ED. A strong and very strong correlation was found in the case of examinations of the torso (except for the comparison of BMI and ED in the case of lateral lumbar spine projection).

Positional MR imaging of normal and injured knees.

This study uses a practical positional MRI protocol to evaluate tibiofemoral translation and rotation in normal and injured knees. Following ethics approval, positional knee MRI of both knees was performed at 35° flexion, extension, and hyperextension in 34 normal subjects (mean age 31.1 ± 10 years) and 51 knee injury patients (mean age 36.4 ± 11.5 years, ACL tear n = 23, non-ACL injury n = 28). At each position, tibiofemoral translation and rotation were measured. Normal knees showed 8.1 ± 3.3° external tibial rotation (i.e., compatible with physiological screw home mechanism) in hyperextension. The unaffected knee of ACL tear patients showed increased tibial anterior translation laterally (p = 0.005) and decreased external rotation (p = 0.002) in hyperextension compared to normal knees. ACL-tear knees had increased tibial anterior translation laterally (p < 0.001) and decreased external rotation (p < 0.001) compared to normal knees. Applying normal thresholds, fifteen (65%) of 23 ACL knees had excessive tibial anterior translation laterally while 17 (74%) had limited external rotation. None (0%) of 28 non-ACL-injured knees had excessive tibial anterior translation laterally while 13 (46%) had limited external rotation. Multidirectional malalignment was much more common in ACL-tear knees. Positional MRI shows (a) physiological tibiofemoral movement in normal knees, (b) aberrant tibiofemoral alignment in the unaffected knee of ACL tear patients, and (c) a high frequency of abnormal tibiofemoral malalignment in injured knees which was more frequent, more pronounced, more multidirectional, and of a different pattern in ACL-tear knees than non-ACL-injured knees. • Positional MRI shows physiological tibiofemoral translation and rotation in normal knees. • Positional MRI shows a different pattern of tibiofemoral alignment in the unaffected knee of ACL tear patients compared to normal control knees. • Positional MRI shows a high prevalence of abnormal tibiofemoral alignment in injured knees, which is more frequent and pronounced in ACL-tear knees than in ACL-intact injured knees.

Characterizing Off-center MRI with ZTE

PurposeTo maximize acquisition bandwidth in zero echo time (ZTE) sequences, readout gradients are already switched on during the RF pulse, creating unwanted slice selectivity. The resulting image distortions are amplified especially when the anatomy of interest is not located at the isocenter. We aim to characterize off-center ZTE MRI of extremities such as the shoulder, knee, and hip, adjusting the carrier frequency of the RF pulse excitation for each TR. MethodsIn ZTE MRI, radial encoding schemes are used, where the distorted slice profile due to the finite RF pulse length rotates with the k-space trajectory. To overcome these modulations for objects far away from the magnet isocenter, the frequency of the RF pulse is shifted for each gradient setting so that artifacts do not occur at a given off-center target position. The sharpness of the edges in the images were calculated and the ZTE acquisition with off-center excitation was compared to an acquisition with isocenter excitation both in phantom and in vivo off-center MRI of the shoulder, knee, and hip at 1.5 and 3T MRI systems. ResultsDistortion and blurriness artifacts on the off-center MRI images of the phantom, in vivo shoulder, knee, and hip images were mitigated with off-center excitation without time or noise penalty, at no additional computational cost. ConclusionThe off-center excitation allows ZTE MRI of the shoulder, knee, and hip for high-bandwidth image acquisitions for clinical settings, where positioning at the isocenter is not possible.

Patella-Posterior Turning Point of the Distal Femur Distance Is a Potential Indicator for Diagnosing Patella Alta in Recurrent Patellar Dislocation Population

To introduce a simple patellar height measurement method (patella-posterior turning point of the distal femur [P-PTP] Distance) independent of patellar anatomy with standardized patient position, and tested the reliability, validity, and diagnostic accuracy compared with commonly used ratios in knee extension. We retrospectively reviewed 418 computed tomography (CT) images of the knee joint in a group of patients who were diagnosed recurrent patellar dislocation (RPD). With the three-dimensional (3D) CT reconstructed knee, patellar height was qualitatively assessed by the patellar engagement with the femoral trochlea in terminal knee extension to divide RPD population into case (patella alta) and control group. With digitally reconstructed lateral radiographs, patellar height was measured with P-PTP distance (perpendicular distances between the distal edge of patella articular surface and posterior turning point of distal femur), and four commonly used ratios: Caton-Deschamps index, Modified Insall-Salvati index, Blackburne-Peel index, and Insall-Salvati index. An unpaired t-test was conducted to determine significant differences between groups. Correlation coefficient, intra- and inter-observer reliability, receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were also calculated. 198 knee images (198 patients) were included for final evaluation. Patella alta was present in 72 knees (36.3%) with RPD. The effect size was relatively large between the case and control group for P-PTP distance (d=-1.619; 95% CI,-1.948 to-1.286). P-PTP distance correlated moderately to strongly with four commonly used ratios (P < .001). Intraobserver and interobserver reliability was good for P-PTP distance. The AUC of the ROC curve was categorized as excellent for P-PTP distance, better than other measurements (P < .001), and the cutoff value was 4.2 mm with the highest sensitivity (86.11%) and specificity (84.92%). The measurement method, P-PTP distance, showed good intra-observer and inter-observer reliability, well correlated with commonly used ratios, and presented best diagnostic accuracy among commonly used ratios for predicting RPD. P-PTP distance might be a potential indicator for identifying patella alta in RPD patients when supine and knee extended. The measurement reported in this study may help in advancing clinical evaluation of patella alta, providing an alternative and simple method to measure patellar height. Standing or weight-bearing plain lateral radiographs obtained from the routine practice should be further assessed in the next step to further validate the method.

Deep Learning-Based Water-Fat Separation from Dual-Echo Chemical Shift-Encoded Imaging.

Conventional water–fat separation approaches suffer long computational times and are prone to water/fat swaps. To solve these problems, we propose a deep learning-based dual-echo water–fat separation method. With IRB approval, raw data from 68 pediatric clinically indicated dual echo scans were analyzed, corresponding to 19382 contrast-enhanced images. A densely connected hierarchical convolutional network was constructed, in which dual-echo images and corresponding echo times were used as input and water/fat images obtained using the projected power method were regarded as references. Models were trained and tested using knee images with 8-fold cross validation and validated on out-of-distribution data from the ankle, foot, and arm. Using the proposed method, the average computational time for a volumetric dataset with ~400 slices was reduced from 10 min to under one minute. High fidelity was achieved (correlation coefficient of 0.9969, error of 0.0381, SSIM of 0.9740, pSNR of 58.6876) and water/fat swaps were mitigated. I is of particular interest that metal artifacts were substantially reduced, even when the training set contained no images with metallic implants. Using the models trained with only contrast-enhanced images, water/fat images were predicted from non-contrast-enhanced images with high fidelity. The proposed water–fat separation method has been demonstrated to be fast, robust, and has the added capability to compensate for metal artifacts.

A bioinspired robotic knee with controlled joint surfaces and adjustable ligaments

The knee joint plays a key role in kinematic and kinetic performances of pedestrain locomotion. The key role of meniscus with matched ligaments in joint stability and movability has not been fully explored in current robotic knee designs. We fabricate a bioinspired robotic knee based on a kinematic model of an anatomical knee in order to reveal the relationship between the meniscus, ligaments and their stability and movability, respectively. The kinematic model was built from magnetic resonance imaging of the human knee with generated contact profiles and customized ligament fibers. Then, the bioinspired knee was designed, and its dynamic stability was maintained by ligaments and specific contact profiles, which were acquired based on the kinematic model. Finally, a monopod robot with the bioinspired knee assembled was developed for dynamic testing. The results show that (1) a smooth rolling–sliding motion can be achieved with the addition of menisci and compatible ligaments; and (2) joint stiffness can be adjusted by changing the springs and activation lengths of ligament fibers. This study gives biomimetic insights into a new design of knee joint for a robotic/prosthetic leg.