Automated Opportunistic Osteoporosis Screening Using Low-Dose Chest CT among Individuals Undergoing Lung Cancer Screening in a Korean Population.

Opportunistic osteoporosis screening using deep learning (DL) analysis of low-dose chest CT (LDCT) scans is a potentially promising approach for the early diagnosis of this condition. We explored bone mineral density (BMD) profiles across all adult ages and prevalence of osteoporosis using LDCT with DL in a Korean population. This retrospective study included 1915 participants from two hospitals who underwent LDCT during general health checkups between 2018 and 2021. Trabecular volumetric BMD of L1-2 was automatically calculated using DL and categorized according to the American College of Radiology quantitative computed tomography diagnostic criteria. BMD decreased with age in both men and women. Women had a higher peak BMD in their twenties, but lower BMD than men after 50. Among adults aged 50 and older, the prevalence of osteoporosis and osteopenia was 26.3% and 42.0%, respectively. Osteoporosis prevalence was 18.0% in men and 34.9% in women, increasing with age. Compared to previous data obtained using dual-energy X-ray absorptiometry, the prevalence of osteoporosis, particularly in men, was more than double. The automated opportunistic BMD measurements using LDCT can effectively predict osteoporosis for opportunistic screening and identify high-risk patients. Patients undergoing lung cancer screening may especially profit from this procedure requiring no additional imaging or radiation exposure.

Evaluation of deep learning-based quantitative computed tomography for opportunistic osteoporosis screening.

To evaluate diagnostic efficacy of deep learning (DL)-based automated bone mineral density (BMD) measurement for opportunistic screening of osteoporosis with routine computed tomography (CT) scans. A DL-based automated quantitative computed tomography (DL-QCT) solution was evaluated with 112 routine clinical CT scans from 84 patients who underwent either chest (N:39), lumbar spine (N:34), or abdominal CT (N:39) scan. The automated BMD measurements (DL-BMD) on L1 and L2 vertebral bodies from DL-QCT were validated with manual BMD (m-BMD) measurement from conventional asynchronous QCT using Pearson's correlation and intraclass correlation. Receiver operating characteristic curve (ROC) analysis identified the diagnostic ability of DL-BMD for low BMD and osteoporosis, determined by dual-energy X-ray absorptiometry (DXA) and m-BMD. Excellent concordance were seen between m-BMD and DL-BMD in total CT scans (r = 0.961/0.979). The ROC-derived AUC of DL-BMD compared to that of central DXA for the low-BMD and osteoporosis patients was 0.847 and 0.770 respectively. The sensitivity, specificity, and accuracy of DL-BMD compared to central DXA for low BMD were 75.0%, 75.0%, and 75.0%, respectively, and those for osteoporosis were 68.0%, 80.5%, and 77.7%. The AUC of DL-BMD compared to the m-BMD for low BMD and osteoporosis diagnosis were 0.990 and 0.943, respectively. The sensitivity, specificity, and accuracy of DL-BMD compared to m-BMD for low BMD were 95.5%, 93.5%, and 94.6%, and those for osteoporosis were 88.2%, 94.5%, and 92.9%, respectively. DL-BMD exhibited excellent agreement with m-BMD on L1 and L2 vertebrae in the various routine clinical CT scans and had comparable diagnostic performance for detecting the low-BMD and osteoporosis on conventional QCT.

Clinical validation of a deep-learning-based bone age software in healthy Korean children.

PURPOSE: Bone age (BA) is needed to assess developmental status and growth disorders. We evaluated the clinical performance of a deep-learning-based BA software to estimate the chronological age (CA) of healthy Korean children. METHODS: This retrospective study included 371 healthy children (217 boys, 154 girls), aged between 4 and 17 years, who visited the Department of Pediatrics for health check-ups between January 2017 and December 2018. A total of 553 left-hand radiographs from 371 healthy Korean children were evaluated using a commercial deep-learning-based BA software (BoneAge, Vuno, Seoul, Korea). The clinical performance of the deep learning (DL) software was determined using the concordance rate and Bland-Altman analysis via comparison with the CA. RESULTS: A 2-sample t-test (P<0.001) and Fisher exact test (P=0.011) showed a significant difference between the normal CA and the BA estimated by the DL software. There was good correlation between the 2 variables (r=0.96, P<0.001); however, the root mean square error was 15.4 months. With a 12-month cutoff, the concordance rate was 58.8%. The Bland-Altman plot showed that the DL software tended to underestimate the BA compared with the CA, especially in children under the age of 8.3 years. CONCLUSION: The DL-based BA software showed a low concordance rate and a tendency to underestimate the BA in healthy Korean children.

T2 Black Synovitis in Musculoskeletal MRI: Disease Spectrum and Imaging Characteristics of Joint Diseases

The synovium may be affected by a wide spectrum of disorders, including inflammatory, infectious, degenerative, traumatic, hemorrhagic, and tumorous conditions. Magnetic resonance imaging (MRI) is a valuable imaging modality to characterize synovial disorders. Most abnormal lesions appear as areas of nonspecific high signal intensity on T2-weighted images (T2-WI) due to high water content or increased perfusion. However, T2 hypointensity can be attributed to blood components of varying ages, calcification, inorganic crystals, fibrosis, caseous necrosis and/or amyloid deposition. Hypointense lesions on T2-WI are infrequent and additional clinical and imaging characteristics can help to limit the list of differential diagnoses, which may include tenosynovial giant cell tumor, synovial chondromatosis, rheumatoid arthritis, tuberculous arthritis, chronic tophaceous gout, amyloid arthropathy, synovial hemangioma, lipoma arborescens and hemosiderotic synovitis. Recently, susceptibility weighted imaging has been developed and may contribute to more accurate diagnosis for deoxygenated blood and calcium. We review the MRI features of hypointense synovial lesions on MRI and emphasize the characteristic findings that suggest a correct diagnosis.

Extraskeletal Osteochondroma in the Posterior Neck of a Middle-Aged Female: A Case Report.

Extraskeletal osteochondroma, a variant of chondroma, typically arises in the para-articular location of hands and feet. It is a rare disease and is particularly uncommon when joint components are not involved or localized away from joints. Herein, we report a case of extraskeletal osteochondroma in the posterior neck of a 66-year-old female. The characteristic radiologic finding of our case is presented, along with the typical findings of the disease and review of related literature reports.

A Systematic Approach to Diagnosing Arthritis Based on Radiological Imaging.

Radiology plays a key role in the diagnosis of arthritis. We herein suggest an algorithmic approach to diagnosing arthritis. First, the number of joint involvements is reviewed. Monoarticular arthritis includes septic arthritis, pigmented villonodular synovitis, and synovial chondromatosis. Second, polyarticular arthritis can be categorized by its characteristics: erosive, productive, and mixed. Erosive disease includes rheumatoid arthritis, hemophilia, and amyloidosis, while productive disease includes osteoarthritis and hemochromatosis. Third, mixed diseases are subcategorized by symmetricity. Ankylosing spondylitis and inflammatory bowel disease related arthritis affect joints symmetrically, while psoriatic arthritis, reactive arthritis, and crystalline arthropathy are asymmetric. Adjacent soft tissue density, periostitis, and bone density are ancillary findings that can be used as additional differential diagnostic clues. The final step in identifying the type of arthritis is to check whether the location is a site frequently affected by one particular disease over another. This systematic approach would be helpful for radiologists in diagnosing arthritis.

Lumbar Spine Computed Tomography to Magnetic Resonance Imaging Synthesis Using Generative Adversarial Network: Visual Turing Test.

(1) Introduction: Computed tomography (CT) and magnetic resonance imaging (MRI) play an important role in the diagnosis and evaluation of spinal diseases, especially degenerative spinal diseases. MRI is mainly used to diagnose most spinal diseases because it shows a higher resolution than CT to distinguish lesions of the spinal canals and intervertebral discs. When it is inevitable for CT to be selected instead of MR in evaluating spinal disease, evaluation of spinal disease may be limited. In these cases, it is very helpful to diagnose spinal disease with MR images synthesized with CT images. (2) Objective: To create synthetic lumbar magnetic resonance (MR) images from computed tomography (CT) scans using generative adversarial network (GAN) models and assess how closely the synthetic images resembled the true images using visual Turing tests (VTTs). (3) Material and Methods: Overall, 285 patients aged ≥ 40 years who underwent lumbar CT and MRI were enrolled. Based on axial CT and T2-weighted axial MR images from 285 patients, an image synthesis model using a GAN was trained using three algorithms (unsupervised, semi-supervised, and supervised methods). Furthermore, VTT to determine how similar the synthetic lumbar MR images generated from lumbar CT axial images were to the true lumbar MR axial images were conducted with 59 patients who were not included in the model training. For the VTT, we designed an evaluation form comprising 600 randomly distributed axial images (150 true and 450 synthetic images from unsupervised, semi-supervised, and supervised methods). Four readers judged the authenticity of each image and chose their first- and second-choice candidates for the true image. In addition, for the three models, structural similarities (SSIM) were evaluated and the peak signal to noise ratio (PSNR) was compared among the three methods. (4) Results: The mean accuracy for the selection of true images for all four readers for their first choice was 52.0% (312/600). The accuracies of determining the true image for each reader's first and first + second choices, respectively, were as follows: reader 1, 51.3% and 78.0%; reader 2, 38.7% and 62.0%, reader 3, 69.3% and 84.0%, and reader 4, 48.7% and 70.7%. In the case of synthetic images chosen as first and second choices, supervised algorithm-derived images were the most often selected (supervised, 118/600 first and 164/600 second; semi-supervised, 90/600 and 144/600; and unsupervised, 80/600 and 114/600). For image quality, the supervised algorithm received the best score (PSNR: 15.987 ± 1.039, SSIM: 0.518 ± 0.042). (5) Conclusion: This was the pilot study to apply GAN to synthesize lumbar spine MR images from CT images and compare training algorithms of the GAN. Based on VTT, the axial MR images synthesized from lumbar CT using GAN were fairly realistic and the supervised training algorithm was found to provide the closest image to true images.

Difference between bone age at the hand and elbow at the onset of puberty.

ABSTRACT: In the pubertal period, bone age advances rapidly in conjunction with growth spurts. Precise bone-age assessments in this period are important, but results from the hand and elbow can be different. We aimed to compare the bone age between the hand and elbow around puberty onset and to elucidate the chronological age confirming puberty onset according to elbow-based bone age.A total of 211 peripubertal subjects (127 boys and 84 girls) who underwent hand and elbow radiographs within 2 months was enrolled. Two radiologists and a pediatric orthopedic surgeon assessed bone age. Hand bone age was graded using the Greulich-Pyle (GP) method, and elbow bone age was determined using the Sauvegrain method. The correlation of 2 methods was evaluated by Demining regression analysis, and the mean absolute difference (MAD) with chronological age was compared between pre-pubertal and pubertal subjects. Receiver-operating characteristic curve analysis was performed to determine the chronological age confirming puberty onset.There was a statistically significant difference in bone age revealed by the GP and Sauvegrain methods in the pubertal group. In the pubertal group, the MAD was 1.26 ±â€Š0.90 years with the GP method and 0.61 ±â€Š0.47 years with the Sauvegrain method in boys (P < .001), while in girls, the MAD was 0.84 ±â€Š0.60 years and 0.53 ±â€Š0.36 years with the same 2 methods (P = .033). The chronological age for confirming puberty onset using the elbow was 12.2 years in boys and 10.3 years in girls.The bone ages of hand and elbow were different at puberty, and the elbow was a more reliable location for bone-age assessment at puberty. Puberty onset according to elbow occurred slightly earlier than expected.

External validation of deep learning-based bone-age software: a preliminary study with real world data.

Artificial intelligence (AI) is increasingly being used in bone-age (BA) assessment due to its complicated and lengthy nature. We aimed to evaluate the clinical performance of a commercially available deep learning (DL)-based software for BA assessment using a real-world data. From Nov. 2018 to Feb. 2019, 474 children (35 boys, 439 girls, age 4-17 years) were enrolled. We compared the BA estimated by DL software (DL-BA) with that independently estimated by 3 reviewers (R1: Musculoskeletal radiologist, R2: Radiology resident, R3: Pediatric endocrinologist) using the traditional Greulich-Pyle atlas, then to his/her chronological age (CA). A paired t-test, Pearson's correlation coefficient, Bland-Altman plot, mean absolute error (MAE) and root mean square error (RMSE) were used for the statistical analysis. The intraclass correlation coefficient (ICC) was used for inter-rater variation. There were significant differences between DL-BA and each reviewer's BA (P < 0.025), but the correlation was good with one another (r = 0.983, P < 0.025). RMSE (MAE) values were 10.09 (7.21), 10.76 (7.88) and 13.06 (10.06) months between DL-BA and R1, R2, R3 BA. Compared with the CA, RMSE (MAE) values were 13.54 (11.06), 15.18 (12.11), 16.19 (12.78) and 19.53 (17.71) months for DL-BA, R1, R2, R3 BA, respectively. Bland-Altman plots revealed the software and reviewers' tendency to overestimate the BA in general. ICC values between 3 reviewers were 0.97, 0.85 and 0.86, and the overall ICC value was 0.93. The BA estimated by DL-based software showed statistically similar, or even better performance than that of reviewers' compared to the chronological age in the real world clinic.

Diagnostic performance of electron-density dual-energy CT in detection of cervical disc herniation in comparison with standard gray-scale CT and virtual non-calcium images.

OBJECTIVES: To assess the diagnostic performance of dual-energy CT (DECT) with electron-density (ED) image reconstruction compared with standard CT (SC) and virtual non-calcium (VNCa) image CT reconstruction for detecting cervical disc herniation. METHODS: This cross-sectional study was approved by the IRB. We enrolled 64 patients (336 intervertebral discs from C2/3 to C7/T1; mean age, 55 years; 17 women and 47 men) who underwent DECT with spectral reconstruction and 3-T MRI within 2 weeks between January 2018 and June 2020. Four radiologists independently evaluated the first image set of randomized SC, VNCa, and ED images to detect cervical disc herniation. After 8 weeks, the readers re-evaluated the second and the last image sets with an 8-week interval. MRI evaluations performed by two other experienced served as the reference standard. Comparing diagnostic performance between each images set was evaluated by a generalized estimating equation. RESULTS: A total of 233 cervical disc herniations were noted on MRI. For detecting cervical disc herniation, electron-density images showed higher sensitivity (94% [219/233; 95% CI, 90-97] vs. 76% [177/233; 70-81] vs. 69% [160/233; 62-76]) (p < 0.001) and similar specificity (90% [93/103; 83-95] vs. 89% [92/103; 82-96] vs. 90% [93/103; 83-95]) (p > 0.05) as SC and VNCa images, respectively. Inter-reader agreement for cervical disc herniation calculated among the four readers was moderate for all image sets (κ = 0.558 for ED, κ = 0.422 for SC, and κ = 0.449 for VNCa). CONCLUSION: DECT with ED reconstruction can improve cervical disc herniation detection and diagnostic confidence compared with SC and VNCa images. KEY POINTS: • Intervertebral discs with high material density are well visualized on electron-density images obtained from dual-energy CT. • Electron-density images showed much higher sensitivity and diagnostic accuracy than standard CT and virtual non-calcium images for the detection of cervical disc herniation. • Electron-density images can have false-negative results, especially for disc herniation with high signal intensity on T2W images and can show pseudo-disc extrusion at the lower cervical spine.

Clinical Validation of a Deep Learning-Based Hybrid (Greulich-Pyle and Modified Tanner-Whitehouse) Method for Bone Age Assessment.

OBJECTIVE: To evaluate the accuracy and clinical efficacy of a hybrid Greulich-Pyle (GP) and modified Tanner-Whitehouse (TW) artificial intelligence (AI) model for bone age assessment. MATERIALS AND METHODS: A deep learning-based model was trained on an open dataset of multiple ethnicities. A total of 102 hand radiographs (51 male and 51 female; mean age ± standard deviation = 10.95 ± 2.37 years) from a single institution were selected for external validation. Three human experts performed bone age assessments based on the GP atlas to develop a reference standard. Two study radiologists performed bone age assessments with and without AI model assistance in two separate sessions, for which the reading time was recorded. The performance of the AI software was assessed by comparing the mean absolute difference between the AI-calculated bone age and the reference standard. The reading time was compared between reading with and without AI using a paired t test. Furthermore, the reliability between the two study radiologists' bone age assessments was assessed using intraclass correlation coefficients (ICCs), and the results were compared between reading with and without AI. RESULTS: The bone ages assessed by the experts and the AI model were not significantly different (11.39 ± 2.74 years and 11.35 ± 2.76 years, respectively, p = 0.31). The mean absolute difference was 0.39 years (95% confidence interval, 0.33-0.45 years) between the automated AI assessment and the reference standard. The mean reading time of the two study radiologists was reduced from 54.29 to 35.37 seconds with AI model assistance (p < 0.001). The ICC of the two study radiologists slightly increased with AI model assistance (from 0.945 to 0.990). CONCLUSION: The proposed AI model was accurate for assessing bone age. Furthermore, this model appeared to enhance the clinical efficacy by reducing the reading time and improving the inter-observer reliability.

Additive values of pelvic tomosynthesis in comparison to pelvic radiography alone for the diagnosis of sacroiliitis in patients with suspected axial spondyloarthritis.

OBJECTIVES: To compare inter-reader agreement and diagnostic confidence in detecting sacroiliitis by the modified New York criteria (mNY) on digital radiography (DR) versus digital pelvic tomosynthesis assisted DR (DR+DPT), and to evaluate changes in the presence of axial spondyloarthritis (axSpA) according to the Assessment of Spondyloarthritis International Society (ASAS) criteria. METHODS: One hundred and thirty-eight patients who underwent both DR and DPT with suspicious axSpA in our rheumatologic clinic were included from February 2017 to February 2018. Three radiologists independently graded sacroiliitis and confidence level on DR first and then re-graded them on DPT in a paired manner. Agreement, confidence, and diagnostic accuracy were evaluated for readers. Changes in the presence of disease by mNY and ASAS criteria were assessed between DR alone and DR+DPT. RESULTS: On DR alone, 73 patients were assessed with radiographic sacroiliitis, and 85 were classified into axSpA by the ASAS criteria; however, 78 and 85, respectively, were classified on DR+DPT. With the assistance of DPT, 17 and 12 patients changed to the disease positivity according to the mNY and ASAS criteria, respectively; the negative results changed to positive in 11 and six patients, respectively. For all readers, agreement improved with DPT (0.79 to 0.89). DR+DPT achieved higher diagnostic accuracy (AUC, P < 0.05). CONCLUSION: The combination of DR and DPT achieved a higher diagnostic performance than that of DR alone, with better agreement. On DR+DPT, the diagnoses of 9.0% of patients with suspicious axSpA (12 of 134) were changed to the status of disease by the ASAS criteria.

Imaging appearance of post-arthroscopic radiocarpal chondrolysis: comparison with osteoarthritis associated with scapholunate dissociation.

BACKGROUND: Since the diagnosis of post-arthroscopic chondrolysis is very difficult, it can be underdiagnosed and confused with other diseases in clinical practice. PURPOSE: To propose imaging features of post-arthroscopic radiocarpal chondrolysis (PRCC) and to compare these with osteoarthritis associated with scapholunate dissociation which are the most common misdiagnoses of PRCC. MATERIAL AND METHODS: To identify missed diagnoses of PRCC, 994 magnetic resonance imaging scans performed in 910 patients were retrospectively reviewed. After the identification of 73 patients who exhibited significant radiocarpal cartilage loss, 11 were diagnosed with PRCC. Since scapholunate advanced collapse was the most common incorrect diagnosis of PRCC (4/11), the imaging findings were compared among the 11 patients with PRCC and 14 patients with osteoarthritis caused by scapholunate dissociation who were diagnosed in the same period. The following imaging features were evaluated: scapholunate dissociation; the center of disease and grade of radiocarpal joint destruction; characteristics of bone marrow edema; the presence of radial styloid and distal scaphoid osteophytes; and the extent of joint effusion and synovitis. RESULTS: The imaging diagnosis of PRCC was significantly differentiated from osteoarthritis associated with scapholunate dissociation based on occurrence at a younger age, bone marrow edema crossing the joint, center of disease in the proximal radioscaphoid joint, and absence of radial styloid and scaphoid osteophytes (P < 0.05). PRCC occasionally presented with arch-shape bone marrow edema based on the proximal carpal row. CONCLUSION: The diagnosis of PRCC can be aided if its characteristic imaging findings are differentiated from other disease entities in patients with a history of arthroscopy.

The correlation between follow-up MRI findings and laboratory results in pyogenic spondylodiscitis.

BACKGROUND: Although MRI is the gold-standard imaging method in the diagnosis of spondylodiscitis, role of follow-up imaging is debated and there can be discrepancies with regard to the significance of bony or soft tissue responses to treatment. Purpose of our study is to test whether the MRI changes on follow-up imaging correlate with laboratory findings of treatment response. METHODS: A total of 48 patients with pyogenic spondylodiscitis who underwent baseline and follow-up MRI were retrospectively reviewed. The extent of bone marrow edema, paravertebral soft tissue inflammation, and disc height were compared on baseline and follow-up MRIs with the C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) levels obtained from the medical records at baseline and on follow-up. Relationships between the MRI and laboratory changes were analyzed using the Spearmann correlation test. RESULTS: The mean MRI follow-up period was 42.25 days. Based on the CRP (resolved: n = 19, resolving: n = 19, and aggravated: n = 10), there was significant correlation between the laboratory results and the changes in the bone and soft tissues (p < 0.01, both). The correlation was best with soft tissue changes (rho: 0.48) followed by bony changes (rho: 0.41). Based on the ESR (resolved: n = 8, resolving: n = 22, and worsened: n = 18), the correlation was stronger with bone changes (rho: 0.45, p < 0.01) than it was with soft tissue changes (rho: 0.39, p = 0.01). CONCLUSION: Follow-up MRI findings of pyogenic spondylodiscitis show variable tissue responses. CRP was best correlated with soft tissue changes, while ESR showed the best association with bony changes.

Prognostic Impact of Low Skeletal Muscle Mass on Major Adverse Cardiovascular Events in Coronary Artery Disease: A Propensity Score-Matched Analysis of a Single Center All-Comer Cohort.

The impact of sarcopenia on atherosclerotic cardiovascular disease remains unclear. We aimed to investigate the prognostic impact of sarcopenia on coronary artery disease (CAD). A total of 475 patients with CAD who underwent successful percutaneous coronary intervention (PCI) and computed tomography (CT) were enrolled. The cross-sectional area of skeletal muscle at the first lumbar (L1) vertebral level was measured, and sex-specific cut-off values of L1 skeletal muscle index (L1 SMI; male <31.00 cm2/m2, female <25.00 cm2/m2) were obtained. The primary outcome was 3-year all-cause mortality and the secondary outcome was 3-year major adverse cardiovascular events (MACEs). Low L1 SMI was present in 141 (29.7%) of 475 patients. The incidence of all-cause mortality (23.7% vs. 5.9%, p < 0.001) and MACEs (39.6% vs. 11.8%, p < 0.001) was significantly higher in patients with low L1 SMI than in those with high L1 SMI. In multivariate analysis, low L1 SMI was an independent predictor of higher risk of all-cause mortality (hazard ratio (HR): 4.07; 95% confidence interval (CI): 1.95-8.45; p < 0.001) and MACEs (HR: 3.76; 95% CI: 2.27-6.23; p < 0.001). These findings remained consistent after propensity score-matched analysis with 91 patient pairs (C-statistic = 0.848). CT-diagnosed low skeletal muscle mass is a powerful predictor of adverse outcomes in patients with CAD undergoing PCI.

MRI Diagnosis for Post-Traumatic Osteomyelitis of Extremities Using Conventional Metal-Artifact Reducing Protocols: Revisited.

RATIONALE AND OBJECTIVES: To assess the diagnostic power of MR imaging features for post-traumatic osteomyelitis (PTOM) of the extremities with metal implants using a 3.0-T machine with conventional metal-artifact reducing (MAR) protocols. MATERIALS AND METHODS: Between December 2012 and September 2016, 261 consecutive patients underwent MRI for clinical suspicion of PTOM in the appendicular skeleton at our hospital. A total of 72 enrolled patients with metal implants were divided into two groups, one with surgical, histologic, or microbiologic proven to be PTOM, and the other proven not to be PTOM. Their MR images were reviewed by two musculoskeletal radiologists who qualitatively analyzed various findings regarding PTOM, and concluded diagnosis of PTOM or without PTOM for each patient. All MR images were obtained using conventional MAR protocols. RESULTS: The sensitivity, specificity, positive and negative predictive values, and accuracy of MR diagnosis by two observers were 55%/38%, 81%/93%, 67%/40%, 73%/78%, and 71%/71%, respectively. Among the findings, T1 low signal intensity, medullary location, confluent pattern, typical features (concurrence of T1 low signal intensity, medullary, and confluent patterns), heterogeneous or no enhancement, and cortical destruction were statistically significant by univariate analysis (p<0.05). Among these features, only medullary involvement was significant by multivariate analysis (p = 0.007). Medullary involvement and no enhancement pattern were significant by step-wise discrimination analysis. Interobserver correlation was moderate with a weighted kappa value of 0.512 (confidence interval: 0.3-0.723). CONCLUSION: The overall accuracy for diagnosis of PTOM of the extremities using 3.0-T MRI with conventional metal-artifact reduction parameters was 71%. The strongest diagnostic MR imaging feature was medullary involvement of T1 low signal intensity. PTOM of the extremities can be accurately diagnosed with a 3.0-T MR machine using conventional MAR protocols.

Degree of Agreement between Electrodiagnostic Testing and Magnetic Resonance Imaging in the Evaluation of Brachial Plexopathy.

OBJECTIVE: Electrodiagnostic study (EDX) and magnetic resonance imaging (MRI) are commonly used in the diagnosis of brachial plexopathy, but the agreement between these 2 studies is unknown. The aim of this study was to evaluate the agreement of EDX and MRI in patients with brachial plexopathy. DESIGN: The records of 69 patients with symptoms of brachial plexopathy who underwent EDX and MRI were reviewed. Based on the degree of agreement of EDX and MRI results, patients were classified as a "complete match," "partial match," or "mismatch." RESULTS: Both studies yielded similar results for the majority of patients (63.2%). Among the enrolled patients, 26.4% were classified as a "complete match," 36.8% as "partial match," and 36.8% as "mismatch." However, only 1 test, either EDX or MRI, revealed abnormal findings in 21.1% of patients. CONCLUSIONS: The agreement between EDX and MRI was high in patients with brachial plexopathy. However, only one of these tests, not both, revealed abnormal findings in several cases. Although both EDX and MRI were in accord with the diagnosis of brachial plexopathy in majority of cases, these 2 studies remain complementary diagnostic modalities for evaluating brachial plexopathies.

Contrast-enhanced Magnetic Resonance Imaging of Pelvic Bone Metastases at 3.0 T: Comparison Between 3-dimensional T1-weighted CAIPIRINHA-VIBE Sequence and 2-dimensional T1-weighted Turbo Spin-Echo Sequence.

OBJECTIVE: This study aimed to compare 3-dimensional T1-weighted gradient-echo sequence (CAIPIRINHA-volumetric interpolated breath-hold examination [VIBE]) with 2-dimensional T1-weighted turbo spin-echo sequence for contrast-enhanced magnetic resonance imaging (MRI) of pelvic bone metastases at 3.0 T. METHODS: Thirty-one contrast-enhanced MRIs of pelvic bone metastases were included. Two contrast-enhanced sequences were evaluated for the following parameters: overall image quality, sharpness of pelvic bone, iliac vessel clarity, artifact severity, and conspicuity and edge sharpness of the smallest metastases. Quantitative analysis was performed by calculating signal-to-noise ratio and contrast-to-noise ratio of the smallest metastases. Significant differences between the 2 sequences were assessed. RESULTS: CAIPIRINHA-VIBE had higher scores for overall image quality, pelvic bone sharpness, iliac vessel clarity, and edge sharpness of the metastatic lesions, and had less artifacts (all P < 0.05). There was no significant difference in conspicuity, signal-to-noise ratio, or contrast-to-noise ratio of the smallest metastases (P > 0.05). CONCLUSIONS: Our results suggest that CAIPIRINHA-VIBE may be superior to turbo spin-echo for contrast-enhanced MRI of pelvic bone metastases at 3.0 T.

The Association between the Magnetic Resonance Imaging Findings of Adhesive Capsulitis and Shoulder Muscle Fat Quantification Using a Multi-Echo Dixon Method.

Objective: To investigate the association between the magnetic resonance imaging (MRI) findings of adhesive capsulitis and shoulder muscle fat percentages using a multi-echo Dixon method. Materials and Methods: Twenty-four patients with clinical diagnoses of adhesive capsulitis and either intact rotator cuffs or Ellman grade 1 partial tears as indicated by MRI scans were included. Two radiologists independently evaluated MRI scans of adhesive capsulitis as follows: presence or absence of axillary recess capsular and extracapsular hyperintensities; thickness of the coracohumeral ligament; thickness of abnormal rotator interval soft tissue; and thickness of glenoidal/humeral axillary recess capsules. Fat quantifications of the supraspinatus, infraspinatus, teres minor, subscapularis, teres major and posterior deltoid muscles were performed using multi-echo Dixon imaging at three locations. Inter-rater agreement was assessed. Differences in fat percentages were assessed and correlations between fat percentages and quantitative measurements were evaluated. Results: The fat percentage of the supraspinatus was significantly higher in patients with extracapsular hyperintensity (present, 3.00 ± 1.74%; absent, 1.81 ± 0.80%; p = 0.022). There were positive correlations between the fat percentage of the teres minor and the thicknesses of the abnormal rotator interval soft tissue (r = 0.494, p = 0.014) and the glenoidal axillary recess capsule (r = 0.475, p = 0.019). After controlling for the effects of age, sex and clinical stage, the relationship between the teres minor fat percentage and the thickness of the abnormal rotator interval soft tissue was statistically significant (r = 0.384, p = 0.048). Inter-rater agreement was almost perfect for fat quantification (intraclass correlation coefficients [ICC] > 0.9) and qualitative analyses (k = 0.824), but were variable for quantitative measurements (ICC, 0.170-0.606). Conclusion: Several MRI findings of adhesive capsulitis were significantly related to higher fat percentages of shoulder muscles.

Multiparametric MR Imaging of Age-related Changes in Healthy Thigh Muscles.

Purpose To use multiparametric magnetic resonance (MR) imaging to assess for and establish age-related differences in healthy thigh muscles. Materials and Methods Ninety-five subjects (47 men, 48 women; median age, 47 years) with healthy body mass index were grouped according to age: 30-39 years (n = 25), 40-49 years (n = 25), 50-59 years (n = 25), and 60-69 years (n = 20). Multiparametric MR imaging (intravoxel incoherent motion diffusion-weighted, diffusion-tensor, multiecho Dixon, and dynamic contrast material-enhanced MR imaging) was performed at 3.0 T. Two radiologists independently evaluated parametric maps of the anterior, medial, and posterior compartments. Welch-modified one-way analysis of variance and post hoc Dunnet T3 test were used to evaluate differences in apparent diffusion, true diffusion, and pseudodiffusion coefficients; perfusion fraction; fractional anisotropy (FA); fat percentage; volume transfer constant; constant efflux rate from the extravascular-extracellular space to plasma; volume fraction of the extravascular-extracellular space (Ve); incremental area under the curve; and Pearson and Spearman correlation coefficients were used to evaluate relationship strength. Multiple regression analysis was performed to identify independent predictors of age, and interrater reliability was assessed with intraclass correlation coefficients. Results There were significant differences among the age groups in apparent diffusion coefficients (P = .010), true diffusion coefficients (P = .045), FA (P < .001), Ve (P = .029) of the anterior compartment muscles, and fat percentages of all three compartments (P ≤ .001). Moreover, FA (Pearson r = 0.428, Spearman ρ = 0.431; P < .001) and Ve (r = 0.226, P = .030 and ρ = 0.309, P = .003) in the anterior compartment and fat percentages in all three compartments (r = 0.481, 0.475, and 0.573; ρ = 0.515, 0.487, and 0.667; respectively; P < .001) were positively associated with age. Multiple regression analysis showed that age was predictive of fat percentage in the posterior compartment (ß = 0.500, P < .001) and of FA in the anterior compartment (ß = 0.194, P = .042). Interrater reliability was excellent (intraclass correlation coefficient, 0.745-0.992). Conclusion Multiple MR imaging parameters were significantly associated with age in thigh muscles. © RSNA, 2017 Online supplemental material is available for this article.