How AI May Transform Musculoskeletal Imaging.

While musculoskeletal imaging volumes are increasing, there is a relative shortage of subspecialized musculoskeletal radiologists to interpret the studies. Will artificial intelligence (AI) be the solution? For AI to be the solution, the wide implementation of AI-supported data acquisition methods in clinical practice requires establishing trusted and reliable results. This implementation will demand close collaboration between core AI researchers and clinical radiologists. Upon successful clinical implementation, a wide variety of AI-based tools can improve the musculoskeletal radiologist's workflow by triaging imaging examinations, helping with image interpretation, and decreasing the reporting time. Additional AI applications may also be helpful for business, education, and research purposes if successfully integrated into the daily practice of musculoskeletal radiology. The question is not whether AI will replace radiologists, but rather how musculoskeletal radiologists can take advantage of AI to enhance their expert capabilities.

A perspective on the evolution of semi-quantitative MRI assessment of osteoarthritis: Past, present and future.

OBJECTIVE: This perspective describes the evolution of semi-quantitative (SQ) magnetic resonance imaging (MRI) in characterizing structural tissue pathologies in osteoarthritis (OA) imaging research over the last 30 years. METHODS: Authors selected representative articles from a PubMed search to illustrate key steps in SQ MRI development, validation, and application. Topics include main scoring systems, reading techniques, responsiveness, reliability, technical considerations, and potential impact of artificial intelligence (AI). RESULTS: Based on original research published between 1993 and 2023, this article introduces available scoring systems, including but not limited to Whole-Organ Magnetic Resonance Imaging Score (WORMS) as the first system for whole-organ assessment of the knee and the now commonly used MRI Osteoarthritis Knee Score (MOAKS) instrument. Specific systems for distinct OA subtypes or applications have been developed as well as MRI scoring instruments for other joints such as the hip, the fingers or thumb base. SQ assessment has proven to be valid, reliable, and responsive, aiding OA investigators in understanding the natural history of the disease and helping to detect response to treatment. AI may aid phenotypic characterization in the future. SQ MRI assessment's role is increasing in eligibility and safety evaluation in knee OA clinical trials. CONCLUSIONS: Evidence supports the validity, reliability, and responsiveness of SQ MRI assessment in understanding structural aspects of disease onset and progression. SQ scoring has helped explain associations between structural tissue damage and clinical manifestations, as well as disease progression. While AI may support human readers to more efficiently perform SQ assessment in the future, its current application in clinical trials still requires validation and regulatory approval.

Imaging Biomarkers of Osteoarthritis.

Currently no disease-modifying osteoarthritis drug has been approved for the treatment of osteoarthritis (OA) that can reverse, hold, or slow the progression of structural damage of OA-affected joints. The reasons for failure are manifold and include the heterogeneity of structural disease of the OA joint at trial inclusion, and the sensitivity of biomarkers used to measure a potential treatment effect.This article discusses the role and potential of different imaging biomarkers in OA research. We review the current role of radiography, as well as advances in quantitative three-dimensional morphological cartilage assessment and semiquantitative whole-organ assessment of OA. Although magnetic resonance imaging has evolved as the leading imaging method in OA research, recent developments in computed tomography are also discussed briefly. Finally, we address the experience from the Foundation for the National Institutes of Health Biomarker Consortium biomarker qualification study and the future role of artificial intelligence.

Emerging Quantitative Imaging Techniques in Sports Medicine.

This article describes recent advances in quantitative imaging of musculoskeletal extremity sports injuries, citing the existing literature evidence and what additional evidence is needed to make such techniques applicable to clinical practice. Compositional and functional MRI techniques including T2 mapping, diffusion tensor imaging, and sodium imaging as well as contrast-enhanced US have been applied to quantify pathophysiologic processes and biochemical compositions of muscles, tendons, ligaments, and cartilage. Dual-energy and/or spectral CT has shown potential, particularly for the evaluation of osseous and ligamentous injury (eg, creation of quantitative bone marrow edema maps), which is not possible with standard single-energy CT. Recent advances in US technology such as shear-wave elastography or US tissue characterization as well as MR elastography enable the quantification of mechanical, elastic, and physical properties of tissues in muscle and tendon injuries. The future role of novel imaging techniques such as photon-counting CT remains to be established. Eventual prediction of return to play (ie, the time needed for the injury to heal sufficiently so that the athlete can get back to playing their sport) and estimation of risk of repeat injury is desirable to help guide sports physicians in the treatment of their patients. Additional values of quantitative analyses, as opposed to routine qualitative analyses, still must be established using prospective longitudinal studies with larger sample sizes.

Impact of Initial Body Weight Loss on Prognosis in Advanced Pancreatic Cancer: Insights From a Single-Center Retrospective Study.

BACKGROUND: Pancreatic cancer (PC) has a poor prognosis, with body weight loss commonly observed at diagnosis. However, the impact on PC prognosis of weight loss at the time of diagnosis on PC prognosis is unknown. METHODS: This retrospective, single-center study enrolled consecutively patients diagnosed with metastatic or locally advanced PC or resectable PC who were intolerant of or refused surgery. Patients who had lost more than 5% of their body weight or more than 2% and had a body mass index (BMI) of less than 20 kg/m2 at diagnosis were classified as experiencing body weight loss. Patients were subclassified into 2 groups: patients with and without weight loss. The study evaluated patient-related and PC-related factors affecting prognosis. Cox proportional hazards models were used to assess factors affecting prognosis. The primary endpoint was overall survival. Additionally, 1:1 propensity score matching was performed to reduce bias. RESULTS: In total, 220 patients were included in the study. The median age of the patients was 74 years, and 49.1% were male. Weight loss at diagnosis was observed in 43.2% of patients. There were no significant differences in clinical factors, except for anthropometric parameters, between the groups. The median survival time did not differ between the weight loss and no weight loss groups (149 and 173 days, respectively, P = .669). After matching, no significant differences in survival times were observed between the 2 groups. CONCLUSIONS: This study found no association between weight loss at diagnosis and prognosis in patients with advanced PC treated with best supportive care or chemotherapy.

Update on recent developments in imaging of inflammation in osteoarthritis: a narrative review.

Synovitis is an important component of the osteoarthritis (OA) disease process, particularly regarding the "inflammatory phenotype" of OA. Imaging plays an important role in the assessment of synovitis in OA with MRI and ultrasound being the most deployed imaging modalities. Contrast-enhanced (CE) MRI, particularly dynamic CEMRI (DCEMRI) is the ideal method for synovitis assessment, but for several reasons CEMRI is not commonly performed for OA imaging in general. Effusion-synovitis and Hoffa-synovitis are commonly used as surrogate markers of synovitis on non-contrast-enhanced (NCE) MRI and have been used in many epidemiological observational studies of knee OA. Several semiquantitative MRI scoring systems are available for the evaluation of synovitis in knee OA. Synovitis can be a target tissue for disease-modifying OA drug (DMOAD) clinical trials. Both MRI and ultrasound may be used to determine the eligibility and assess the therapeutic efficacy of DMOAD approaches. Ultrasound is mostly used for evaluation of synovitis in hand OA, while MRI is typically used for larger joints, namely knees and hips. The role of other modalities such as CT (including dual-energy CT) and nuclear medicine imaging (such as positron-emission tomography (PET) and its hybrid imaging) is limited in the context of synovitis assessment in OA. Despite research efforts to develop NCEMRI-based synovitis evaluation methods, these typically underestimate the severity of synovitis compared to CEMRI, and thus more research is needed before we can rely only on NCEMRI.

A call for screening MRI as a tool for osteoarthritis clinical trials.

Conventional radiography is the most commonly used imaging modality for the evaluation of osteoarthritis (OA) in clinical trials of disease-modifying OA drugs (DMOADs). Unfortunately, radiography has many shortcomings as an imaging technique to meaningfully assess the pathological features of OA. In this perspective paper, we will describe the reasons why radiography is not an ideal tool for structural OA assessment and why magnetic resonance imaging (MRI) should be preferred for such purposes. These shortcomings include a lack of reproducibility of radiographic joint space measurements (if conducted without using a standardized positioning frame), a lack of sensitivity and specificity, an insufficient definition of disease severity, a weak association of radiographic structural damage and pain, a lack of ability to depict many faces of OA, and incapability to depict diagnoses of exclusion. MRI offers solutions to these limitations of radiography. Several different phenotypes of OA have been recognized and it is important to recruit appropriate patients for specific therapeutic approaches in DMOAD trials. Radiography does not allow such phenotypical stratification. We will explain known hurdles for widespread deployment of MRI at eligibility screening and how they can be overcome by technological advances and the use of simplified image assessment.

Structural phenotypes of knee osteoarthritis: potential clinical and research relevance.

A joint contains many different tissues that can exhibit pathological changes, providing many potential targets for treatment. Researchers are increasingly suggesting that osteoarthritis (OA) comprises several phenotypes or subpopulations. Consequently, a treatment for OA that targets only one pathophysiologic abnormality is unlikely to be similarly efficacious in preventing or delaying the progression of all the different phenotypes of structural OA. Five structural phenotypes have been proposed, namely the inflammatory, meniscus-cartilage, subchondral bone, and atrophic and hypertrophic phenotypes. The inflammatory phenotype is characterized by marked synovitis and/or joint effusion, while the meniscus-cartilage phenotype exhibits severe meniscal and cartilage damage. Large bone marrow lesions characterize the subchondral bone phenotype. The hypertrophic and atrophic OA phenotype are defined based on the presence large osteophytes or absence of any osteophytes, respectively, in the presence of concomitant cartilage damage. Limitations of the concept of structural phenotyping are that they are not mutually exclusive and that more than one phenotype may be present. It must be acknowledged that a wide range of views exist on how best to operationalize the concept of structural OA phenotypes and that the concept of structural phenotypic characterization is still in its infancy. Structural phenotypic stratification, however, may result in more targeted trial populations with successful outcomes and practitioners need to be aware of the heterogeneity of the disease to personalize their treatment recommendations for an individual patient. Radiologists should be able to define a joint at risk for progression based on the predominant phenotype present at different disease stages.

Improving Radiographic Fracture Recognition Performance and Efficiency Using Artificial Intelligence.

Background Missed fractures are a common cause of diagnostic discrepancy between initial radiographic interpretation and the final read by board-certified radiologists. Purpose To assess the effect of assistance by artificial intelligence (AI) on diagnostic performances of physicians for fractures on radiographs. Materials and Methods This retrospective diagnostic study used the multi-reader, multi-case methodology based on an external multicenter data set of 480 examinations with at least 60 examinations per body region (foot and ankle, knee and leg, hip and pelvis, hand and wrist, elbow and arm, shoulder and clavicle, rib cage, and thoracolumbar spine) between July 2020 and January 2021. Fracture prevalence was set at 50%. The ground truth was determined by two musculoskeletal radiologists, with discrepancies solved by a third. Twenty-four readers (radiologists, orthopedists, emergency physicians, physician assistants, rheumatologists, family physicians) were presented the whole validation data set (n = 480), with and without AI assistance, with a 1-month minimum washout period. The primary analysis had to demonstrate superiority of sensitivity per patient and the noninferiority of specificity per patient at -3% margin with AI aid. Stand-alone AI performance was also assessed using receiver operating characteristic curves. Results A total of 480 patients were included (mean age, 59 years ± 16 [standard deviation]; 327 women). The sensitivity per patient was 10.4% higher (95% CI: 6.9, 13.9; P < .001 for superiority) with AI aid (4331 of 5760 readings, 75.2%) than without AI (3732 of 5760 readings, 64.8%). The specificity per patient with AI aid (5504 of 5760 readings, 95.6%) was noninferior to that without AI aid (5217 of 5760 readings, 90.6%), with a difference of +5.0% (95% CI: +2.0, +8.0; P = .001 for noninferiority). AI shortened the average reading time by 6.3 seconds per examination (95% CI: -12.5, -0.1; P = .046). The sensitivity by patient gain was significant in all regions (+8.0% to +16.2%; P < .05) but shoulder and clavicle and spine (+4.2% and +2.6%; P = .12 and .52). Conclusion AI assistance improved the sensitivity and may even improve the specificity of fracture detection by radiologists and nonradiologists, without lengthening reading time. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Link and Pedoia in this issue.

Update: Posttreatment Imaging of the Knee after Cartilage Repair.

Focal cartilage lesions are common pathologies at the knee joint that are considered important risk factors for the premature development of osteoarthritis. A wide range of surgical options, including but not limited to marrow stimulation, osteochondral auto- and allografting, and autologous chondrocyte implantation, allows for targeted treatment of focal cartilage defects. Arthroscopy is the standard of reference for the assessment of cartilage integrity and quality before and after repair. However, deep cartilage layers, intrachondral composition, and the subchondral bone are only partially or not at all visualized with arthroscopy. In contrast, magnetic resonance imaging offers noninvasive evaluation of the cartilage repair site, the subchondral bone, and the soft tissues of the joint pre- and postsurgery. Radiologists need to be familiar with the different surgical procedures available and their characteristic postsurgical imaging appearances to assess treatment success and possible complications adequately. We provide an overview of the most commonly performed surgical procedures for cartilage repair at the knee and typical postsurgical imaging characteristics.

Assessment of an artificial intelligence aid for the detection of appendicular skeletal fractures in children and young adults by senior and junior radiologists.

BACKGROUND: As the number of conventional radiographic examinations in pediatric emergency departments increases, so, too, does the number of reading errors by radiologists. OBJECTIVE: The aim of this study is to investigate the ability of artificial intelligence (AI) to improve the detection of fractures by radiologists in children and young adults. MATERIALS AND METHODS: A cohort of 300 anonymized radiographs performed for the detection of appendicular fractures in patients ages 2 to 21 years was collected retrospectively. The ground truth for each examination was established after an independent review by two radiologists with expertise in musculoskeletal imaging. Discrepancies were resolved by consensus with a third radiologist. Half of the 300 examinations showed at least 1 fracture. Radiographs were read by three senior pediatric radiologists and five radiology residents in the usual manner and then read again immediately after with the help of AI. RESULTS: The mean sensitivity for all groups was 73.3% (110/150) without AI; it increased significantly by almost 10% (P<0.001) to 82.8% (125/150) with AI. For junior radiologists, it increased by 10.3% (P<0.001) and for senior radiologists by 8.2% (P=0.08). On average, there was no significant change in specificity (from 89.6% to 90.3% [+0.7%, P=0.28]); for junior radiologists, specificity increased from 86.2% to 87.6% (+1.4%, P=0.42) and for senior radiologists, it decreased from 95.1% to 94.9% (-0.2%, P=0.23). The stand-alone sensitivity and specificity of the AI were, respectively, 91% and 90%. CONCLUSION: With the help of AI, sensitivity increased by an average of 10% without significantly decreasing specificity in fracture detection in a predominantly pediatric population.

Automated detection of acute appendicular skeletal fractures in pediatric patients using deep learning.

OBJECTIVE: We aimed to perform an external validation of an existing commercial AI software program (BoneView™) for the detection of acute appendicular fractures in pediatric patients. MATERIALS AND METHODS: In our retrospective study, anonymized radiographic exams of extremities, with or without fractures, from pediatric patients (aged 2-21) were included. Three hundred exams (150 with fractures and 150 without fractures) were included, comprising 60 exams per body part (hand/wrist, elbow/upper arm, shoulder/clavicle, foot/ankle, leg/knee). The Ground Truth was defined by experienced radiologists. A deep learning algorithm interpreted the radiographs for fracture detection, and its diagnostic performance was compared against the Ground Truth, and receiver operating characteristic analysis was done. Statistical analyses included sensitivity per patient (the proportion of patients for whom all fractures were identified) and sensitivity per fracture (the proportion of fractures identified by the AI among all fractures), specificity per patient, and false-positive rate per patient. RESULTS: There were 167 boys and 133 girls with a mean age of 10.8 years. For all fractures, sensitivity per patient (average [95% confidence interval]) was 91.3% [85.6, 95.3], specificity per patient was 90.0% [84.0,94.3], sensitivity per fracture was 92.5% [87.0, 96.2], and false-positive rate per patient in patients who had no fracture was 0.11. The patient-wise area under the curve was 0.93 for all fractures. AI diagnostic performance was consistently high across all anatomical locations and different types of fractures except for avulsion fractures (sensitivity per fracture 72.7% [39.0, 94.0]). CONCLUSION: The BoneView™ deep learning algorithm provides high overall diagnostic performance for appendicular fracture detection in pediatric patients.

Sports injuries at the Rio de Janeiro 2016 Summer Paralympic Games: use of diagnostic imaging services.

OBJECTIVE: To describe the occurrence of imaging-depicted sports-related injuries (bone, muscle, tendon, and ligament injuries) during the Rio 2016 Summer Paralympic Games. METHODS: Descriptive data on all imaging examinations by using radiography, ultrasonography (US), and MRI were collected and retrospectively analyzed centrally by five musculoskeletal radiologists according to imaging modality, country of origin of the athletes, type of sport, type of disability, and type and location of injury. RESULTS: We report 109 injuries in 4378 athletes. A total of 382 radiologic examinations were performed in 261 athletes, including 118 (31%) radiographic, 22 (6%) US, and 242 (63%) MRI examinations. Para athletes from Africa had the highest utilization rate (20.1%, 67 out of 333). Athletes from Europe underwent the most examinations with 29 radiographic, 12 US, and 66 MRI examinations. The highest utilization rate of imaging modalities by sport was among Judo para athletes (16.7%, 22 out of 132). Most injuries were reported in athletics discipline (37.6%, 41 out of 109). Most injuries were also reported among para athletes with visual impairment (40 injuries, 36.7% of all injuries). Bone stress injuries were most common among para athletes with visual impairment (6 out of 7). Para athletes with visual impairment were also more prone to bone stress injuries than traumatic fractures, unlike para athletes with neurologic and musculoskeletal impairments. CONCLUSIONS: Imaging was used in 6.0% of para athletes. MRI comprised 63% of imaging utilization. Identification of patterns of injuries may help building future prevention programs in elite para athletes. KEY POINTS: • The highest imaging utilization rates were found among para athletes competing in Judo, sitting volleyball, powerlifting, and football. • Utilization of diagnostic imaging at the Rio 2016 Paralympic Games demonstrated similar trends to what was observed at the Rio 2016 Olympic Games. • Comparison of the rate of imaging-depicted injuries between Olympic and Paralympic athletes is limited due to inherent differences between the two athlete populations and the manner in which injury risk in the Paralympic athlete varies dependent on impairment type, which is not the case for the Olympic athlete.

MRI-detected spinal disc degenerative changes in athletes participating in the Rio de Janeiro 2016 Summer Olympics games.

OBJECTIVE: To describe the frequency and the distribution of degenerative disc disease (DDD) detected in athletes who underwent spine MRI in the 2016 Summer Olympic Games in Rio de Janeiro. METHODS: Data on spine MRI examinations from the 2016 Summer Olympics were retrospectively analyzed. We assessed the frequency of DDD of the cervical (Cs), thoracic (Ts), and lumbar (Ls) spine using Pfirrmann's classification. Grade II and III were considered as mild, grade IV as moderate, and grade V as severe disc degeneration. Data were analyzed according to the location of the degenerative disc, type of sport, age-groups, and gender of the athletes. RESULTS: One hundred out of 11,274 athletes underwent 108 spine MRI's (21 C, 6 T, and 81 L) (53% Females (F), 47% Males (M)). The frequency of DDD was 40% (42% F, 58% M) over the entire spine (28% mild, 9% moderate and 3% severe). There were 58% (12%F, 88%M) of the cervical spine discs that showed some degree of degeneration (44% mild, 13.5% moderate and 1% severe). Athletics, Boxing, and Swimming were the sports most affected by DDD in the Cs. There were 12.5% of the thoracic discs that showed some degree of degeneration, all were mild DDD and were exclusively seen in female athletes. There were 39% (53% F, 47% M) of the lumbar discs with DDD (26% mild, 9% moderate, and 4% severe). CONCLUSION: Athletes who underwent spine MRI during the 2016 Summer Olympic Games show a high frequency of DDD of cervical and lumbar spines. Recognition of these conditions is important to develop training techniques that may minimize the development of degenerative pathology of the spine.

Magnetic resonance imaging assessment of knee osteoarthritis: current and developing new concepts and techniques.

Magnetic resonance imaging (MRI) is a well-established imaging technique for structural assessment of knee osteoarthritis (OA) particularly in a research context. Conventional MRI allows evaluation of morphological changes in osteoarthritis, and advanced compositional MRI techniques enable assessment of 'premorphologic' biochemical compositional changes of articular and periarticular tissues. Limitations of conventional radiography are well known, although radiography remains the primary imaging modality applied in osteoarthritis clinical trials to date. Hybrid techniques such as PET/MRI have been introduced, which may potentially supplement conventional imaging techniques. Artificial Intelligence (AI) such as deep learning with convolutional neural networks is becoming increasingly recognised as a supportive instrument to deepen our understanding of morphologic OA development and progression. In this narrative review article, we will first give summary of current concepts and widely used MRI assessment techniques of knee osteoarthritis. We will then describe more recent and novel MRI techniques focusing primarily on publications from the last 4 years (2016-2019).

Severity of heterotopic ossification in patients following surgery for hip fracture: a retrospective observational study.

BACKGROUND: Heterotopic ossification (HO) is a relatively common complication following hip surgery treated with open reduction and internal fixation, total arthroplasty or hemiarthroplasty. Development of HO after hip surgery is an important clinical issue as it can affect functional status. We aimed to determine whether there was association between severity of heterotopic ossification about the hip and the interval between the time of hip fracture and surgery. MATERIALS AND METHODS: Our retrospective study included 151 patients (age range 33-95 years) treated for hip fractures by hemiarthroplasty. Medical records were reviewed for time interval to surgery, laterality, surgical approach, and patient age. Patients who had any post-operative complications were excluded. Radiographs were semiquantitatively assessed for the degree of heterotopic ossification based on Brooker Classification (5-point scale). Statistical analysis was performed utilizing Chi-square, Kruskal-Wallis, and Score tests, and also a proportional odds model (significance level set at 0.05). RESULTS: Thirty eight patients had no heterotopic ossification, 43 had class 1, 55 had class 2, and 15 had class 3 or greater heterotopic ossification. The majority of patients (59.6%) had surgery within 2 days of acute injury. Severe heterotopic ossification (HO 3+) was associated with the longer interval between the time of acute hip fracture and surgery (median 6 days) vs. median 2 days in all other groups (HO classes 0-2) (p = 0.0015). The odds ratio and 95% CI for one level higher HO class was 1.296 (1.152, 1.459), which meant that the odds of having HO class one level higher increased by about 29.6% for every one-day increase in the days to surgery. No significant association was found for other variables. CONCLUSION: Class 3 or greater HO was associated with longer time interval between time of acute hip fracture and surgery compared to all other groups (HO class 0-2).

Modified technique for imaging the wrist and elbow in obese and claustrophobic patients using a non-open standard MRI scanner.

OBJECTIVE: It is challenging to image extremely obese and claustrophobic patients using a standard, non-open, magnetic resonance imaging (MRI) scanner. On the other hand, installing an additional upright or open MRI scanner may not be cost-effective for most practices. Our technique with a patient in a sitting or standing position behind the standard MRI scanner may be helpful in the MR examination of the wrist/elbow in these patients using a standard wrist/elbow coil. MATERIAL AND METHODS: We performed wrist and elbow MRI of extremely obese and claustrophobic patients by using our modified technique with the patient sitting or standing outside the standard non-open MRI scanner. A total number of 20 cases with the following diagnosis were examined: triquetral and scaphoid bone contusions and fractures, scapholunate ligament tears, triangular fibrocartilage complex tear, and biceps tear. RESULTS: Comparison of image quality for diagnostic information between the standard technique and our technique showed no significant difference, which is necessary for making the diagnosis. CONCLUSIONS: Our technique enables wrist and elbow imaging of extremely obese and claustrophobic patients who cannot otherwise be imaged using a standard MRI scanner without compromising the image quality that is essential for making a diagnosis.

Sports Injuries at the Rio de Janeiro 2016 Summer Olympics: Use of Diagnostic Imaging Services.

Purpose To describe the occurrence of imaging-depicted sports-related stress injuries, fractures, and muscle and tendon disorders during the 2016 Summer Olympic Games in Rio de Janeiro, Brazil. Materials and Methods Data on radiologic examinations were collected and retrospectively analyzed centrally by two board-certified musculoskeletal radiologists (with a third musculoskeletal radiologist acting as an adjudicator in case of discrepancies). Descriptive data on all imaging examinations by using radiography, ultrasonography (US), and magnetic resonance (MR) imaging were collected and analyzed according to imaging modality, country of origin of the athletes, type of sport, and type and location of injury. Results There were 1101 injuries that occurred in 11 274 (9.8%) athletes. A total of 1015 radiologic examinations were performed, including 304 (30.0%) radiographic, 104 (10.2%) US, and 607 (59.8%) MR examinations. Excluding 10 athletes categorized as refugees, athletes from Africa had the highest utilization rate (14.8%, 148 of 1001). Athletes from Europe underwent the most examinations with 103 radiographic, 39 US, and 254 MR examinations. Gymnastics (artistic) had the highest percentage of athletes who underwent imaging (15.5%, 30 of 194). Athletics (track and field) had the most examinations (293, including 53 radiographic, 50 US, and 190 MR examinations). Conclusion The overall occurrence of imaging used to help diagnose sports-related injuries at the Rio de Janeiro 2016 Summer Olympics was 6.4% of athletes. In these cases, MR imaging comprised 60% of imaging utilization. © RSNA, 2018 Online supplemental material is available for this article.

Limb saving surgery for Ewing's sarcoma of the distal tibia: a case report.

BACKGROUND: Ewing's sarcoma is a primary malignant tumor of bone occurring mostly in childhood. Few effective reconstruction techniques are available after wide resection of Ewing's sarcoma at the distal end of the tibia. Reconstruction after wide resection is especially difficult in children, as it is necessary to consider the growth and activity of the lower limbs. CASE PRESENTATION: A 12-year-old Japanese boy had presented with right lower leg pain at age 8 years. Imaging examination showed a bone tumor accompanied by a large extra-skeletal mass in the distal part of his tibia. The tumor was histologically diagnosed as Ewing's sarcoma. The patient received chemotherapy, followed by wide resection. Reconstruction consisted of a bone transport method involving external fixation of Taylor Spatial Frame. To prevent infection after surgery, the external fixation pin was coated with iodine. One year after surgery, the patient showed poor consolidation of bone, so iliac bone transplantation was performed on the extended bones and docking site of the distal tibia. After 20 months, tibia formation was good. Three years after surgery, there was no evidence of tumor recurrence or metastases; bone fusion was good, and he was able to run. CONCLUSIONS: The bone transport method is an effective surgical method of reconstruction after wide resection of a bone tumor at the distal end of the tibia, if a pin can be inserted into the distal bone fragment. Coating external fixation pins with iodine may prevent postoperative infection.

Recent advances in research imaging of osteoarthritis with focus on MRI, ultrasound and hybrid imaging.

For imaging of osteoarthritis (OA), MRI plays a major role in the research setting, with compositional MRI techniques becoming increasingly more important thanks to their capacity to assess 'premorphologic' biochemical compositional changes of articular and periarticular tissues. Although radiography remains the primary imaging modality in OA clinical trials, known limitations for visualisation of OA features significantly limits the utility of radiography both clinically and in the research arena. Compositional MRI techniques can potentially supplement routine clinical MRI sequences to identify cartilage degeneration at an earlier stage when radiographs may be normal. Ultrasound can be a useful adjunct to radiography and MRI particularly for evaluation of hand OA and for the evaluation of synovitis. Emerging hybrid imaging techniques including PET/MRI and PET/CT allow evaluation of the joint with simultaneous assessment of morphological changes and metabolic activities, showing a potential for these hybrid systems to play an increasing role in OA research.