Recruitment and baseline characteristics of young adults at risk of early-onset knee osteoarthritis after ACL reconstruction in the SUPER-Knee trial.

Objectives: The study aims to (1) report the process of recruiting young adults into a secondary knee osteoarthritis prevention randomised controlled trial (RCT) after anterior cruciate ligament reconstruction (ACLR); (2) determine the number of individuals needed to be screened to include one participant (NNS) and (3) report baseline characteristics of randomised participants. Methods: The SUpervised exercise-therapy and Patient Education Rehabilitation (SUPER)-Knee RCT compares SUPER and minimal intervention for young adults (aged 18-40 years) with ongoing symptoms (ie, mean score of <80/100 from four Knee injury and Osteoarthritis Outcome Score subscales (KOOS4)) 9-36 months post-ACLR. The NNS was calculated as the number of prospective participants screened to enrol one person. At baseline, participants provided medical history, completed questionnaires (demographic, injury/surgery, rehabilitation characteristics) and underwent physical examination. Results: 1044 individuals were screened to identify 567 eligible people, from which 184 participants (63% male) enrolled. The sample of enrolled participants was multicultural (29% born outside Australia; 2% Indigenous Australians). The NNS was 5.7. For randomised participants, mean±SD age was 30±6 years. The mean body mass index was 27.3±5.2 kg/m2, with overweight (43%) and obesity (21%) common. Participants were, on average, 2.3 years post-ACLR. Over half completed <8 months of postoperative rehabilitation, with 56% having concurrent injury/surgery to meniscus and/or cartilage. The most affected KOOS (0=worst, 100=best) subscale was quality of life (mean 43.7±19.1). Conclusion: Young adults post-ACLR were willing to participate in a secondary osteoarthritis prevention trial. Sample size calculations should be multiplied by at least 5.7 to provide an estimate of the NNS. The SUPER-Knee cohort is ideally positioned to monitor and intervene in the early development and trajectory of osteoarthritis. Trial registration number: ACTRN12620001164987.

Post-traumatic and OA-related lesions in the knee at baseline and 2 years after traumatic meniscal injury: Secondary analysis of a randomized controlled trial.

OBJECTIVE: To assess the presence of early degenerative changes on Magnetic Resonance Imaging (MRI) 24 months after a traumatic meniscal tear and to compare these changes in patients treated with arthroscopic partial meniscectomy or physical therapy plus optional delayed arthroscopic partial meniscectomy. DESIGN: We included patients aged 18-45 years with a recent onset, traumatic, MRI verified, isolated meniscal tear without radiographic osteoarthritis. Patients were randomized to arthroscopic partial meniscectomy or standardized physical therapy with optional delayed arthroscopic partial meniscectomy. MRIs at baseline and 24 months were scored using the MRI Osteoarthritis Knee Score (MOAKS). We compared baseline MRIs to healthy controls aged 18-40 years. The outcome was the progression of bone marrow lesions (BMLs), cartilage defects and osteophytes after 24 months in patients. RESULTS: We included 99 patients and 50 controls. At baseline, grade 2 and 3 BMLs were present in 26% of the patients (n = 26), compared to 2% of the controls (n = 1) (between group difference 24% (95% CI 15% to 34%)). In patients, 35% (n = 35) had one or more cartilage defects grade 1 or higher, compared to 2% of controls (n = 1) (between group difference 33% (95% CI 23% to 44%)). At 24 months MRI was available for 40 patients randomized to arthroscopic partial meniscectomy and 41 patients randomized to physical therapy. At 24 months 30% (n = 12) of the patients randomized to arthroscopic partial meniscectomy showed BML worsening, compared to 22% (n = 9) of the patients randomized to physical therapy (between group difference 8% (95% CI -11% to 27%)). Worsening of cartilage defects was present in 40% (n = 16) of the arthroscopic partial meniscectomy group, compared to 22% (n = 9) of the physical therapy group (between group difference 18% (95% CI -2% to 38%)). Of the patients who had no cartilage defect at baseline, 33% of the arthroscopic partial meniscectomy group had a new cartilage defect at follow-up compared to 14% of the physical therapy group. Osteophyte worsening was present in 18% (n = 7) of the arthroscopic partial meniscectomy group and 15% (n = 6) of the physical therapy group (between group difference 3% (95% CI -13% to 19%)). CONCLUSIONS: Our results might suggest more worsening of BMLs and cartilage defects with arthroscopic partial meniscectomy compared to physical therapy with optional delayed arthroscopic partial meniscectomy at 24-month follow-up in young patients with isolated traumatic meniscal tears without radiographic OA.

Chances and challenges of photon-counting CT in musculoskeletal imaging.

In musculoskeletal imaging, CT is used in a wide range of indications, either alone or in a synergistic approach with MRI. While MRI is the preferred modality for the assessment of soft tissues and bone marrow, CT excels in the imaging of high-contrast structures, such as mineralized tissue. Additionally, the introduction of dual-energy CT in clinical practice two decades ago opened the door for spectral imaging applications. Recently, the advent of photon-counting detectors (PCDs) has further advanced the potential of CT, at least in theory. Compared to conventional energy-integrating detectors (EIDs), PCDs provide superior spatial resolution, reduced noise, and intrinsic spectral imaging capabilities. This review briefly describes the technical advantages of PCDs. For each technical feature, the corresponding applications in musculoskeletal imaging will be discussed, including high-spatial resolution imaging for the assessment of bone and crystal deposits, low-dose applications such as whole-body CT, as well as spectral imaging applications including the characterization of crystal deposits and imaging of metal hardware. Finally, we will highlight the potential of PCD-CT in emerging applications, underscoring the need for further preclinical and clinical validation to unleash its full clinical potential.

Towards clinical implementation of an AI-algorithm for detection of cervical spine fractures on computed tomography.

BACKGROUND: Artificial intelligence (AI) applications can facilitate detection of cervical spine fractures on CT and reduce time to diagnosis by prioritizing suspected cases. PURPOSE: To assess the effect on time to diagnose cervical spine fractures on CT and diagnostic accuracy of a commercially available AI application. MATERIALS AND METHODS: In this study (June 2020 - March 2022) with historic controls and prospective evaluation, we evaluated regulatory-cleared AI-software to prioritize cervical spine fractures on CT. All patients underwent non-contrast CT of the cervical spine. The time between CT acquisition and the moment the scan was first opened (DNT) was compared between the retrospective and prospective cohorts. The reference standard for determining diagnostic accuracy was the radiology report created in routine clinical workflow and adjusted by a senior radiologist. Discrepant cases were reviewed and clinical relevance of missed fractures was determined. RESULTS: 2973 (mean age, 55.4 ± 19.7 [standard deviation]; 1857 men) patients were analyzed by AI, including 2036 retrospective and 938 prospective cases. Overall prevalence of cervical spine fractures was 7.6 %. The DNT was 18 % (5 min) shorter in the prospective cohort. In scans positive for cervical spine fracture according to the reference standard, DNT was 46 % (16 min) shorter in the prospective cohort. Overall sensitivity of the AI application was 89.8 % (95 % CI: 84.2-94.0 %), specificity was 95.3 % (95 % CI: 94.2-96.2 %), and diagnostic accuracy was 94.8 % (95 % CI: 93.8-95.8 %). Negative predictive value was 99.1 % (95 % CI: 98.5-99.4 %) and positive predictive value was 63.0 % (95 % CI: 58.0-67.8 %). 22 fractures were missed by AI of which 5 required stabilizing therapy. CONCLUSION: A time gain of 16 min to diagnosis for fractured cases was observed after introducing AI. Although AI-assisted workflow prioritization of cervical spine fractures on CT shows high diagnostic accuracy, clinically relevant cases were missed.

Body composition and respiratory outcomes in children: a population-based prospective cohort study.

BACKGROUND: Body composition might influence lung function and asthma in children, but its longitudinal relations are unclear. We aimed to identify critical periods for body composition changes during childhood and adolescence in relation to respiratory outcomes in adolescents. METHODS: In a population-based prospective cohort study, we measured body mass index, fat mass index (FMI), lean mass index (LMI) and the ratio of android fat mass divided by gynoid fat mass (A/G ratio) by dual-energy X-ray absorptiometry at 6, 10 and 13 years. At 13 years, lung function was measured by spirometry, and current asthma was assessed by questionnaire. RESULTS: Most prominently and consistently, higher FMI and A/G ratio at age 13 years were associated with lower forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) and forced expiratory flow after exhaling 75% of FVC (FEF75) (range Z-score difference -0.13 (95% CI -0.16 to -0.10) to -0.08 (95% CI -0.11 to -0.05) per SD score increase), and higher LMI at all ages was associated with higher FEF75 (range Z-score difference 0.05 (95% CI 0.01 to 0.08) to 0.09 (95% CI 0.06 to 0.13)). Between the ages of 6 and 13 years, normal to high FMI and A/G ratio were associated with lower FEV1/FVC and FEF75 (range Z-score difference -0.20 (95% CI -0.30 to -0.10) to -0.17 (95% CI -0.28 to -0.06)) and high to high LMI with higher FEF75 (range Z-score difference0.32 (95% CI 0.23 to 0.41)). Body composition changes were not associated with asthma. CONCLUSION: Adolescents with higher total and abdominal fat indices may have impaired lung function, while those with a higher lean mass during childhood and adolescence may have better small airway function. Public health measures should focus on a healthy body composition in adolescents to minimise respiratory morbidity.

Automated Deep Learning-Based Segmentation of Abdominal Adipose Tissue on Dixon MRI in Adolescents: A Prospective Population-Based Study.

BACKGROUND. The prevalence of childhood obesity has increased significantly worldwide, highlighting a need for accurate noninvasive quantification of body fat distribution in children. OBJECTIVE. The purpose of this study was to develop and test an automated deep learning method for subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) segmentation using Dixon MRI acquisitions in adolescents. METHODS. This study was embedded within the Generation R Study, a prospective population-based cohort study in Rotterdam, The Netherlands. The current study included 2989 children (1432 boys, 1557 girls; mean age, 13.5 years) who underwent investigational whole-body Dixon MRI after reaching the age of 13 years during the follow-up phase of the Generation R Study. A 2D competitive dense fully convolutional neural network model (2D-CDFNet) was trained from scratch to segment abdominal SAT and VAT using Dixon MRI-based images. The model underwent training, validation, and testing in 62, eight, and 15 children, respectively, who were selected by stratified random sampling, with manual segmentations used as reference. Segmentation performance was assessed using the Dice similarity coefficient and volumetric similarity. Two observers independently performed subjective visual assessments of automated segmentations in 504 children, selected by stratified random sampling, with undersegmentation and oversegmentation scored on a scale of 0-3 (with a score of 3 denoting nearly perfect segmentation). For 2820 children for whom complete data were available, Spearman correlation coefficients were computed among MRI measurements and BMI and dual-energy x-ray absorptiometry (DEXA)-based measurements. The model used (gitlab.com/radiology/msk/genr/abdomen/cdfnet) is publicly available. RESULTS. In the test dataset, the mean Dice similarity coefficient and mean volu-metric similarity, respectively, were 0.94 ± 0.03 [SD] and 0.98 ± 0.01 [SD] for SAT and 0.85 ± 0.05 and 0.92 ± 0.04 for VAT. The two observers assigned a score of 3 for SAT in 94% and 93% for the undersegmentation proportion and in 99% and 99% for the oversegmentation proportion, and they assigned a score of 3 for VAT in 99% and 99% for the undersegmentation proportion and in 95% and 97% for the oversegmentation proportion. Correlations with SAT and VAT were 0.808 and 0.698 for BMI and 0.941 and 0.801 for DEXA-derived fat mass. CONCLUSION. We trained and evaluated the 2D-CDFNet model on Dixon MRI in adolescents. Quantitative and qualitative measures of automated SAT and VAT segmentations indicated strong model performance. CLINICAL IMPACT. The automated model may facilitate large-scale studies investigating abdominal fat distribution on MRI among adolescents as well as associations of fat distribution with clinical outcomes.

Talocrural Arthrodesis Increases Osteoarthritis Severity in Adjacent Joints: A Midterm Computed Tomography Follow-Up Study.

BACKGROUND: After talocrural arthrodesis, adjacent joints (subtalar, talonavicular, and calcaneocuboid) are often affected by osteoarthritis (OA)). It is unclear if OA is pre-existing to talocrural arthrodesis, or whether it develops after talocrural arthrodesis. This retrospective study is unique because it is the first study with preoperative and follow-up computed tomography (CT). The aim of this study is to investigate whether OA develops in adjacent joints after talocrural arthrodesis or if OA is already pre-existing. In addition, associations between degree of OA and patient-reported outcomes are investigated. METHODS: Patients were selected from electronic files, and adjacent joint OA was assessed on preoperative CT and bilateral follow-up CT. Patient-reported outcomes were collected. RESULTS: Twenty-three patients were included with an average follow-up time of 7 years (SD = 2). In participants without pre-existing OA, OA significantly progressed in all adjacent joints. In participants with pre-existing OA, OA progressed in the subtalar joint. Patient-reported outcomes were not correlated to OA. CONCLUSIONS: Osteoarthritis in the adjacent joints progresses after talocrural arthrodesis, especially in participants without pre-existing OA. The severity of OA is not related to patient-reported outcomes. Therefore, the clinical impact of the progression of OA seems to be limited. LEVEL OF EVIDENCE: Level III: retrospective.

Advanced Magnetic Resonance Imaging and Molecular Imaging of the Painful Knee.

Chronic knee pain is a common condition. Causes of knee pain include trauma, inflammation, and degeneration, but in many patients the pathophysiology remains unknown. Recent developments in advanced magnetic resonance imaging (MRI) techniques and molecular imaging facilitate more in-depth research focused on the pathophysiology of chronic musculoskeletal pain and more specifically inflammation. The forthcoming new insights can help develop better targeted treatment, and some imaging techniques may even serve as imaging biomarkers for predicting and assessing treatment response in the future. This review highlights the latest developments in perfusion MRI, diffusion MRI, and molecular imaging with positron emission tomography/MRI and their application in the painful knee. The primary focus is synovial inflammation, also known as synovitis. Bone perfusion and bone metabolism are also addressed.

Clinical Applications of Photon-counting CT: A Review of Pioneer Studies and a Glimpse into the Future.

CT systems equipped with photon-counting detectors (PCDs), referred to as photon-counting CT (PCCT), are beginning to change imaging in several subspecialties, such as cardiac, vascular, thoracic, and musculoskeletal radiology. Evidence has been building in the literature underpinning the many advantages of PCCT for different clinical applications. These benefits derive from the distinct features of PCDs, which are made of semiconductor materials capable of converting photons directly into electric signal. PCCT advancements include, among the most important, improved spatial resolution, noise reduction, and spectral properties. PCCT spatial resolution on the order of 0.25 mm allows for the improved visualization of small structures (eg, small vessels, arterial walls, distal bronchi, and bone trabeculations) and their pathologies, as well as the identification of previously undetectable anomalies. In addition, blooming artifacts from calcifications, stents, and other dense structures are reduced. The benefits of the spectral capabilities of PCCT are broad and include reducing radiation and contrast material dose for patients. In addition, multiple types of information can be extracted from a single data set (ie, multiparametric imaging), including quantitative data often regarded as surrogates of functional information (eg, lung perfusion). PCCT also allows for a novel type of CT imaging, K-edge imaging. This technique, combined with new contrast materials specifically designed for this modality, opens the door to new applications for imaging in the future.

Physical activity, screen time and body composition in 13-year-old adolescents: The Generation R Study.

BACKGROUND: Body composition between prepubertal children and adolescents varies, and it is unclear how physical activity and sedentary behaviour affect adolescent body composition. OBJECTIVES: This study aimed to examine the associations of physical activity and screen time with overall and specific fat depots in the general adolescent population. METHODS: In a population-based prospective cohort study, among 3258 adolescents aged 13 years, physical activity and screen time were assessed via self-report questionnaires. Body mass index, dual-energy X-ray absorptiometry-based measures (i.e. fat mass and lean body mass) and magnetic resonance imaging-based measures (i.e. abdominal subcutaneous and visceral fat mass) were obtained. RESULTS: After adjusting for social-demographic and growth-related factors, each additional hour of daily physical activity was associated with lower fat mass, abdominal visceral fat mass and higher lean body mass (all p < 0.05). However, these associations were not observed in the longitudinal analyses. Each additional hour of daily screen time was associated with higher body mass index, fat mass, abdominal subcutaneous and visceral fat mass (all p < 0.05), which were consistent with the longitudinal analyses. CONCLUSION: Adolescents with higher physical activity and lower screen time had lower levels of adiposity both at the general and visceral levels.

Factors associated with meniscus volume in knees free of degenerative features.

OBJECTIVES: To explore factors that were associated with meniscus volume in knees free of radiographic osteoarthritis (OA) features and symptoms of OA. METHODS: In the third Rotterdam Study cohort, clinical, radiographic, and magnetic resonance data were obtained at baseline (BL) and after 5 years of follow-up. Meniscus volumes and their change over time were calculated after semi-automatic segmentation on Magnetic Resonance Imaging. Knees with radiographic OA features (Kellgren and Lawrence>0) or clinical diagnosis of OA (American College of Rheumatology) at BL were excluded. Ten OA risk factors were adjusted in the multivariable analysis (generalized estimating equations), treating two knees within subjects as repeated measurements. RESULTS: From 1065 knees (570 subjects), the average (standard deviation) age and Body mass index (BMI) of included subjects were 54.3 (3.7) years and 26.5 (4.4) kg/m2. At BL, nine factors (varus alignment, higher BMI, meniscus pathologies, meniscus extrusion, cartilage lesions, injury, greater physical activity level, quadriceps muscle strength, and higher age) were significantly associated with greater meniscus volume. Five factors (injury, meniscus pathologies, meniscus extrusion, higher age, and change of BMI) were significantly associated with meniscus volume loss. CONCLUSIONS: Modifiable factors (varus alignment, BMI, physical activity level, and quadriceps muscle strength) and non-modifiable factors (higher age, injury, meniscus pathologies, meniscus extrusion, and cartilage lesions) were all associated with meniscus volume or meniscus volume loss over time.

Association between clinical findings and the presence of lumbar spine osteoarthritis imaging features: A systematic review.

OBJECTIVE: Spinal osteoarthritis is difficult to study and diagnose, partly due to the lack of agreed diagnostic criteria. This systematic review aims to give an overview of the associations between clinical and imaging findings suggestive of spinal osteoarthritis in patients with low back pain to make a step towards agreed diagnostic criteria. DESIGN: We searched MEDLINE, Embase, Web of Science, and CINAHL from inception to April 29, 2021 to identify observational studies in adults that assessed the association between selected clinical and imaging findings suggestive of spinal osteoarthritis. Risk of bias was assessed using the Newcastle Ottawa Scale and the quality of evidence was graded using an adaptation of the GRADE approach. RESULTS: After screening 7902 studies, 30 met the inclusion criteria. High-quality evidence was found for the longitudinal association between low back pain (LBP) intensity, and both disc space narrowing and osteophytes, as well as for the association between LBP-related physical functioning and lumbar disc degeneration, the presence of spinal morning stiffness and disc space narrowing and for the lack of association between physical functioning and Schmorl's nodes. CONCLUSIONS: There is high- and moderate-quality evidence of associations between clinical and imaging findings suggestive of spinal osteoarthritis. However, the majority of the studied outcomes had low or very low-quality of evidence. Furthermore, clinical and methodological heterogeneity was a serious limitation, adding to the need and importance of agreed criteria for spinal osteoarthritis, which should be the scope of future research.

Rapid Whole-Knee Quantification of Cartilage Using T1, T2*, and TRAFF2 Mapping With Magnetic Resonance Fingerprinting.

OBJECTIVE: Quantitative Magnetic Resonance Imaging (MRI) holds great promise for the early detection of cartilage deterioration. Here, a Magnetic Resonance Fingerprinting (MRF) framework is proposed for comprehensive and rapid quantification of T1, T2*, and TRAFF2 with whole-knee coverage. METHODS: A MRF framework was developed to achieve quantification of Relaxation Along a Fictitious Field in the 2nd rotating frame of reference ( TRAFF2) along with T1 and T2*. The proposed sequence acquires 65 measurements of 25 high-resolution slices, interleaved with 7 inversion pulses and 40 RAFF2 trains, for whole-knee quantification in a total acquisition time of 3:25 min. Comparison with reference T1, T2*, and TRAFF2 methods was performed in phantom and in seven healthy subjects at 3 T. Repeatability (test-retest) with and without repositioning was also assessed. RESULTS: Phantom measurements resulted in good agreement between MRF and the reference with mean biases of -54, 2, and 5 ms for T1, T2*, and TRAFF2, respectively. Complete characterization of the whole-knee cartilage was achieved for all subjects, and, for the femoral and tibial compartments, a good agreement between MRF and reference measurements was obtained. Across all subjects, the proposed MRF method yielded acceptable repeatability without repositioning ( R2 ≥ 0.94) and with repositioning ( R2 ≥ 0.57) for T1, T2*, and TRAFF2. SIGNIFICANCE: The short scan time combined with the whole-knee coverage makes the proposed MRF framework a promising candidate for the early assessment of cartilage degeneration with quantitative MRI, but further research may be warranted to improve repeatability after repositioning and assess clinical value in patients.

Imaging of early-stage osteoarthritis: the needs and challenges for diagnosis and classification.

In an effort to boost the development of new management strategies for OA, there is currently a shift in focus towards the diagnosis and treatment of early-stage OA. It is important to distinguish diagnosis from classification of early-stage OA. Diagnosis takes place in clinical practice, whereas classification is a process to stratify participants with OA in clinical research. For both purposes, there is an important opportunity for imaging, especially with MRI. The needs and challenges differ for early-stage OA diagnosis versus classification. Although it fulfils the need of high sensitivity and specificity for making a correct diagnosis, implementation of MRI in clinical practice is challenged by long acquisition times and high costs. For classification in clinical research, more advanced MRI protocols can be applied, such as quantitative, contrast-enhanced, or hybrid techniques, as well as advanced image analysis methods including 3D morphometric assessments of joint tissues and artificial intelligence approaches. It is necessary to follow a step-wise and structured approach that comprises, technical validation, biological validation, clinical validation, qualification, and cost-effectiveness, before new imaging biomarkers can be implemented in clinical practice or clinical research.

Imaging-based assessment of fatty acid composition in human bone marrow adipose tissue at 7 T: Method comparison and in vivo feasibility.

PURPOSE: To demonstrate the feasibility and accuracy of chemical shift-encoded imaging of the fatty acid composition (FAC) of human bone marrow adipose tissue at 7 T, and to determine suitable image-acquisition parameters using simulations. METHODS: The noise performance of FAC estimation was investigated using simulations with a range of inter-echo time, and accuracy was assessed using a phantom experiment. Furthermore, one knee of 8 knee-healthy subjects (ages 35-54 years) was imaged, and the fractions of saturated fatty acids (SFA) and polyunsaturated fatty acids (PUFA) were mapped. Values were compared between reconstruction methods, and between anatomical regions. RESULTS: Based on simulations, ΔTE = 0.6 ms was chosen. The phantom experiment demonstrated high accuracy of especially SFA using a constrained reconstruction model (slope = 1.1, average bias = -0.2%). The lowest accuracy was seen for PUFA using a free model (slope = 2.0, average bias = 9.0%). For in vivo images, the constrained model resulted in lower intersubject variation compared with the free model (e.g., in the femoral shaft, the SFA percent-point range was within 1.0% [vs. 3.0%]). Furthermore, significant regional FAC differences were detected. For example, using the constrained approach, the femoral SFA in the medial condyle was lower compared with the shaft (median [range]: 27.9% [27.1%, 28.4%] vs. 32.5% [31.8%, 32.8%]). CONCLUSION: Bone marrow adipose tissue FAC quantification using chemical-shift encoding is feasible at 7 T. Both the noise performance and accuracy of the technique are superior using a constrained signal model.

Photon-counting CT: Review of initial clinical results.

Photon-counting computed tomography (PCCT) is a new technology that enables higher spatial resolution compared to conventional CT techniques, energy resolved imaging and spectral post-processing. This leads to improved contrast-to-noise ratio, artifact and potential dose reduction as well as elimination of electronic noise. Since the introduction of clinical PCCT in 2021, a shift has been observed from solely pre-clinical studies to clinical research (i.e. use of PCCT imaging in humans). This review article is focused on the initial clinical results of PCCT by explaining the current PCCT systems, the applications themselves and, the challenges of PCCT.