Three-dimensional analysis for quantification of knee joint space width with weight-bearing CT: comparison with non-weight-bearing CT and weight-bearing radiography

Subchondral bone expansion in advanced knee osteoarthritis: Relation with radiographic severity and role in surgical decision-making

Background

Joint space width (JSW) is a traditional imaging marker for knee osteoarthritis (OA) severity, but it lacks sensitivity in advanced cases. We propose tibial subchondral bone area (TSBA), a new CT imaging marker to explore its relationship with OA radiographic severity, and to test its performance for classifying surgical decisions between unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) compared to JSW.

Methods

We collected clinical, radiograph, and CT data from 182 patients who underwent primary knee arthroplasty (73 UKA, 109 TKA). The radiographic severity was scored using Kellgren-Lawrence (KL) grading system. TSBA and JSW were extracted from 3D CT-reconstruction model. We used independent t-test to investigate the relationship between TSBA and KL grade, and binary logistic regression to identify factors associated with TKA risk. The accuracy of TSBA, JSW and established classification model in differentiating between UKA and TKA was assessed using AUC.

Results

All parameters exhibited inter- and intra-class coefficients greater than 0.966. Patients with KL grade 4 had significantly larger TSBA than those with KL grade 3. TSBA (0.708 of AUC) was superior to minimal/average JSW (0.547/0.554 of AUC) associated with the risk of receiving TKA. Medial TSBA, together with gender and Knee Society Knee Score, emerged as independent classification factors in multivariate analysis. The overall AUC of composite model for surgical decision-making was 0.822.

Conclusion

Tibial subchondral bone area is an independent imaging marker for radiographic severity, and is superior to JSW for surgical decision-making between UKA and TKA in advanced OA patients.

Incorporating patient-specific hip orientation from weightbearing computed tomography affects discrete element analysis-computed regional joint contact mechanics in individuals treated with periacetabular osteotomy for hip dysplasia

Computational models of the hip often omit patient-specific functional orientation when placing imaging-derived bony geometry into anatomic landmark-based coordinate systems for application of joint loading schemes. The purpose of this study was to determine if this omission meaningfully alters computed contact mechanics. Discrete element analysis models were created from non-weightbearing (NWB) clinical CT scans of 10 hip dysplasia patients (11 hips) and oriented in the International Society of Biomechanics (ISB) coordinate system (NWB-ISB). Three additional models were generated for each hip by adding patient-specific stance information obtained via weightbearing CT (WBCT) to each ISB-oriented model: (1) patient-specific sagittal tilt added (WBCT-sagittal), (2) coronal and axial rotation from optical motion capture added to (1; WBCT-combo), and (3) WBCT-derived axial, sagittal, and coronal rotation added to (1; WBCT-original). Identical gait cycle loading was applied to all models for a given hip, and computed contact stress and contact area were compared between model initialization techniques. Addition of sagittal tilt did not significantly change whole-joint peak (p = 0.922) or mean (p = 0.871) contact stress or contact area (p = 0.638). Inclusion of motion-captured coronal and axial rotation (WBCT-combo) decreased peak contact stress (p = 0.014) and slightly increased average contact area (p = 0.071) from WBCT-sagittal models. Including all WBCT-derived rotations (WBCT-original) further reduced computed peak contact stress (p = 0.001) and significantly increased contact area (p = 0.001). Variably significant differences (p = 0.001-1.0) in patient-specific acetabular subregion mechanics indicate the importance of functional orientation incorporation for modeling applications in which local contact mechanics are of interest.

Assessment of knee instability in ACL-injured knees using weight-bearing computed tomography (WBCT): a novel protocol and preliminary results

OBJECTIVE

To propose a protocol for assessing knee instability in ACL-injured knees using weight-bearing computed tomography (WBCT).

MATERIALS AND METHODS

We enrolled five patients with unilateral chronic ACL tears referred for WBCT. Bilateral images were obtained in four positions: bilateral knee extension, bilateral knee flexion, single-leg stance with knee flexion and external rotation, and single-leg stance with knee flexion and internal rotation. The radiation dose, time for protocol acquisition, and patients' tolerance of the procedure were recorded. A blinded senior radiologist assessed image quality and measured the anterior tibial translation (ATT) and femorotibial rotation (FTR) angle in the ACL-deficient and contralateral healthy knee.

RESULTS

All five patients were male, aged 23-30 years old. The protocol resulted in a 16.2 mGy radiation dose and a 15-min acquisition time. The procedure was well-tolerated, and patient positioning was uneventful, providing good-quality images. In all positions, the mean ATT and FTR were greater in ACL-deficient knees versus the healthy knee, with more pronounced differences observed in the bilateral knee flexion position. Mean lateral ATT in the flexion position was 9.1±2.8 cm in the ACL-injured knees versus 4.0±1.8 cm in non-injured knees, and mean FTR angle in the bilateral flexion position was 13.5°±7.7 and 8.6°±4.6 in the injured and non-injured knees, respectively.

CONCLUSION

Our protocol quantitatively assesses knee instability with WBCT, measuring ATT and FTR in diverse knee positions. It employs reasonable radiation, is fast, well-tolerated, and yields high-quality images. Preliminary findings suggest ACL-deficient knees show elevated ATT and FTR, particularly in the 30° flexion position.

Functional Imaging of the Knee-A Comprehensive Review

Knee pain is a common presenting problem in the general population. Radiographs and magnetic resonance imaging (MRI) are the cornerstones of imaging in current clinical practice. With advancements in technology, there has been increasing utilization of other modalities to evaluate knee disorders. Dynamic assessment utilizing computed tomography and portable ultrasounds have demonstrated the capacity to accurately assess and reproducibly quantify kinematics of knee disorders. Cartilage physiology can be evaluated with MRI. Emerging research has even demonstrated novel musculoskeletal applications of positron emission tomography to evaluate anterior cruciate ligament graft metabolic activity following reconstruction. As technology continues to evolve and traditional ways are improved upon, future comparative studies will elucidate the distinct advantages of the various modalities. Although radiology is still primarily an anatomic specialty, there is immense potential for functional imaging to be the standard of care. This review focuses on the most common musculoskeletal applications of functional imaging as well as future utilization.

CT in osteoarthritis: its clinical role and recent advances

Computed tomography (CT) is a widely available imaging method and considered as one of the most reliable techniques in bone assessment. Although CT has limited tissue contrast and needs radiation exposure, it has several advantages like fast scanning time and high spatial resolution. In this regard, CT has unique roles in osteoarthritis (OA) and its variable utilities have been reported. Hence, this review highlights the clinical role of CT in OA of representative joints. In addition, CT showed the several technical advancements recently, for example, acquiring the CT image with standing, obtaining the dual-energy data, and novel photon-counting detector development. Therefore, the recent studies and potential utility of these new CT systems in OA are also discussed.

A Correspondence-Based Network Approach for Groupwise Analysis of Patient-Specific Spatiotemporal Data

Methods for statistically analyzing patient-specific data that vary both spatially and over time are currently either limited to summary statistics or require elaborate surface registration. We propose a new method, called correspondence-based network analysis, which leverages particle-based shape modeling to establish correspondence across a population and preserve patient-specific measurements and predictions through statistical analysis. Herein, we evaluated this method using three published datasets of the hip describing cortical bone thickness of the proximal femur, cartilage contact stress, and dynamic joint space between control and patient cohorts to evaluate activity- and group-based differences, as applicable, using traditional statistical parametric mapping (SPM) and our proposed spatially considerate correspondence-based network analysis approach. The network approach was insensitive to correspondence density, while the traditional application of SPM showed decreasing area of the region of significance with increasing correspondence density. In comparison to SPM, the network approach identified broader and more connected regions of significance for all three datasets. The correspondence-based network analysis approach identified differences between groups and activities without loss of subject and spatial specificity which could improve clinical interpretation of results.

Magnetic Resonance Imaging of Total Ankle Arthroplasty: State-of-The-Art Assessment of Implant-Related Pain and Dysfunction

Total ankle arthroplasty (TAA) is an effective alternative for treating patients with end-stage ankle degeneration, improving mobility, and providing pain relief. Implant survivorship is constantly improving; however, complications occur. Many causes of pain and dysfunction after total ankle arthroplasty can be diagnosed accurately with clinical examination, laboratory, radiography, and computer tomography. However, when there are no or inconclusive imaging findings, magnetic resonance imaging (MRI) is highly accurate in identifying and characterizing bone resorption, osteolysis, infection, osseous stress reactions, nondisplaced fractures, polyethylene damage, nerve injuries and neuropathies, as well as tendon and ligament tears. Multiple vendors offer effective, clinically available MRI techniques for metal artifact reduction MRI of total ankle arthroplasty. This article reviews the MRI appearances of common TAA implant systems, clinically available techniques and protocols for metal artifact reduction MRI of TAA implants, and the MRI appearances of a broad spectrum of TAA-related complications.

The role of imaging in osteoarthritis

Osteoarthritis is a complex whole-organ disorder that involves molecular, anatomic, and physiologic derangement. Advances in imaging techniques have expanded the role of imaging in evaluating osteoarthritis and functional changes. Radiography, magnetic resonance imaging, computed tomography (CT), and ultrasonography are commonly used imaging modalities, each with advantages and limitations in evaluating osteoarthritis. Radiography comprehensively analyses alignment and osseous features, while MRI provides detailed information about cartilage damage, bone marrow edema, synovitis, and soft tissue abnormalities. Compositional imaging derives quantitative data for detecting cartilage and tendon degeneration before structural damage occurs. Ultrasonography permits real-time scanning and dynamic joint evaluation, whereas CT is useful for assessing final osseous detail. Imaging plays an essential role in the diagnosis, management, and research of osteoarthritis. The use of imaging can help differentiate osteoarthritis from other diseases with similar symptoms, and recent advances in deep learning have made the acquisition, management, and interpretation of imaging data more efficient and accurate. Imaging is useful in monitoring and predicting the prognosis of osteoarthritis, expanding our understanding of its pathophysiology. Ultimately, this enables early detection and personalized medicine for patients with osteoarthritis. This article reviews the current state of imaging in osteoarthritis, focusing on the strengths and limitations of various imaging modalities, and introduces advanced techniques, including deep learning, applied in clinical practice.

Fully automatic extraction of knee kinematics from dynamic CT imaging; normative tibiofemoral and patellofemoral kinematics of 100 healthy volunteers

BACKGROUND

Accurate assessment of knee kinematics is important in the diagnosis and quantification of knee disorders and to determine the effect of orthopaedic interventions. Despite previous studies showing the usefulness of dynamic imaging and providing valuable insights in knee kinematics, dynamic imaging is not widely used in clinics due to a variety of causes. In this study normative knee kinematics of 100 healthy subjects is established using a fully automatic workflow feasible for use in the clinic.

METHODS

One-hundred volunteers were recruited and a dynamic CT scan was made during a flexion extension movement. Image data was automatically segmented and dynamic and static images were superimposed using image registration. Coordinate systems for the femur, patella and tibia were automatically calculated as well as their dynamic position and orientation.

RESULTS

Dynamic CT scans weremade withan effective radiation dose of 0.08 mSv. The median tibial internal rotation was 4° and valgus rotation is 5° at full flexion. Femoral rollback of the lateral condyle was 7 mm versus 2 mm of the medial condyle. The median patella flexion reached 65% of tibiofemoral flexion and the median tilt and rotation were 5° and 0° at full flexion, respectively. The median mediolateral translation of the patella was 3 mm (medially) in the first 30° of flexion.

CONCLUSION

The current study presents TF and PF kinematic data of 97 healthy individuals, providing a unique dataset of normative knee kinematics. The short scanning time, simple motion and, automatic analysis make the methods presented suitable for daily clinical practice.

Statistical modeling: Assessing the anatomic variability of knee joint space width

Population-based knee joint space width (JSW) assessments are promising for the prevention and early diagnosis of osteoarthritis. This study aimed to establish the statistical shape and alignment model (SSAM) of knee joints for assessing anatomic variation in knee JSW in the healthy Chinese male population. CT scans of asymptomatic knee joints of healthy male participants (n = 107) were collected for manual segmentation to create mesh samples. The as-scanned positional error was reduced by a standard processing flow of deformable mesh registration. Principal component analysis (PCA) was performed to create a tibiofemoral SSAM that was trained on all mesh samples. The anatomic variability of the JSW in the healthy Chinese male population was then assessed using the SSAM with regression analysis and 3D analysis by color-coded mapping. Almost all PCA modes had a linear influence on the anatomic variation of the medial and lateral JSW. The JSW variability within the SSAM was mainly explained by mode 1 (45.1 % of variation), demonstrating that this mode had the greatest influence on JSW variation. 3D assessment of the JSW showed that the minimum medial JSW varied from 2.76 to 3.23 mm, and its site shifted a short distance on the medial tibial plateau. The root-mean-square fitting and generalization errors of the SSAM were below 1 mm. This study will benefit the design and optimization of prosthetic devices, and may be applicable to the prevention and early diagnosis of osteoarthritis.

Latest advancements in imaging techniques in OA

The osteoarthritis (OA) research community has been advocating a shift from radiography-based screening criteria and outcome measures in OA clinical trials to a magnetic resonance imaging (MRI)-based definition of eligibility and endpoint. For conventional morphological MRI, various semiquantitative evaluation tools are available. We have lately witnessed a remarkable technological advance in MRI techniques, including compositional/physiologic imaging and automated quantitative analyses of articular and periarticular structures. More recently, additional technologies were introduced, including positron emission tomography (PET)-MRI, weight-bearing computed tomography (CT), photon-counting spectral CT, shear wave elastography, contrast-enhanced ultrasound, multiscale X-ray phase contrast imaging, and spectroscopic photoacoustic imaging of cartilage. On top of these, we now live in an era in which artificial intelligence is increasingly utilized in medicine. Osteoarthritis imaging is no exception. Successful implementation of artificial intelligence (AI) will hopefully improve the workflow of radiologists, as well as the level of precision and reproducibility in the interpretation of images.