Electron density dual-energy CT can improve the detection of lumbar disc herniation with higher image quality than standard and virtual non-calcium images.

OBJECTIVES: To compare the diagnostic performance and image quality of dual-energy computed tomography (DECT) with electron density (ED) image reconstruction with those of DECT with standard CT (SC) and virtual non-calcium (VNCa) image reconstructions, for diagnosing lumbar disc herniation (L-HIVD). METHODS: A total of 59 patients (354 intervertebral discs from T12/L1 to L5/S1; mean age, 60 years; 30 women and 29 men) who underwent DECT with spectral reconstruction and 3-T MRI within 2 weeks were enrolled between March 2021 and February 2022. Four radiologists independently assessed three image sets of randomized ED, SC, and VNCa images to detect L-HIVD at 8-week intervals. The coefficient of variance (CV) and the Weber contrast of the ROIs in the normal and diseased disc to cerebrospinal fluid space (NCR-normal/-diseased, respectively) were calculated to compare the image qualities of the noiseless ED and other series. RESULTS: Overall, 129 L-HIVDs were noted on MRI. In the detection of L-HIVD, ED showed a higher AUC and sensitivity than SC and VNCa; 0.871 vs 0.807 vs 833 (p = 0.002) and 81% vs 70% vs 74% (p = 0.006 for SC), respectively. CV was much lower in all measurements of ED than those for SC and VNCa (p < 0.001). Furthermore, NCR-normal and NCR-diseased were the highest in ED (ED vs SC in NCR-normal and NCR-diseased, p = 0.001 and p = 0.004, respectively; ED vs VNCa in NCR-diseased, p = 0.044). CONCLUSION: Compared to SC and VNCa images, DECT with ED reconstruction can enhance the AUC and sensitivity of L-HIVD detection with a lower CV and higher NCR. CLINICAL RELEVANCE STATEMENT: To our knowledge, this is the first study to quantify the image quality of noiseless ED images. ED imaging may be helpful for detecting L-HIVD in patients who cannot undergo MRI. KEY POINTS: ED images have diagnostic potential, but relevant quantitative analyses of image quality are limited. ED images detect disc herniation, with a better coefficient of variance and normalized contrast ratio values. ED images could detect L-HIVD when MRI is not an option.

Developing a deep learning model for sleep stage prediction in obstructive sleep apnea cohort using 60 GHz frequency-modulated continuous-wave radar.

Given the significant impact of sleep on overall health, radar technology offers a promising, non-invasive, and cost-effective avenue for the early detection of sleep disorders, even prior to relying on polysomnography (PSG)-based classification. In this study, we employed an attention-based bidirectional long short-term memory (Attention Bi-LSTM) model to accurately predict sleep stages using 60 GHz frequency-modulated continuous-wave (FMCW) radar. Our dataset comprised 78 participants from an ongoing obstructive sleep apnea (OSA) cohort, recruited between July 2021 and November 2022, who underwent overnight polysomnography alongside radar sensor monitoring. The dataset encompasses comprehensive polysomnography recordings, spanning both sleep and wakefulness states. The predictions achieved a Cohen's kappa coefficient of 0.746 and an overall accuracy of 85.2% in classifying wakefulness, rapid-eye-movement (REM) sleep, and non-REM (NREM) sleep (N1 + N2 + N3). The results demonstrated that the models incorporating both Radar 1 and Radar 2 data consistently outperformed those using only Radar 1 data, indicating the potential benefits of utilising multiple radars for sleep stage classification. Although the performance of the models tended to decline with increasing OSA severity, the addition of Radar 2 data notably improved the classification accuracy. These findings demonstrate the potential of radar technology as a valuable screening tool for sleep stage classification.

Clinical Validation of an Artificial Intelligence Model for Detecting Distal Radius, Ulnar Styloid, and Scaphoid Fractures on Conventional Wrist Radiographs.

This study aimed to assess the feasibility and performance of an artificial intelligence (AI) model for detecting three common wrist fractures: distal radius, ulnar styloid process, and scaphoid. The AI model was trained with a dataset of 4432 images containing both fractured and non-fractured wrist images. In total, 593 subjects were included in the clinical test. Two human experts independently diagnosed and labeled the fracture sites using bounding boxes to build the ground truth. Two novice radiologists also performed the same task, both with and without model assistance. The sensitivity, specificity, accuracy, and area under the curve (AUC) were calculated for each wrist location. The AUC for detecting distal radius, ulnar styloid, and scaphoid fractures per wrist were 0.903 (95% C.I. 0.887-0.918), 0.925 (95% C.I. 0.911-0.939), and 0.808 (95% C.I. 0.748-0.967), respectively. When assisted by the AI model, the scaphoid fracture AUC of the two novice radiologists significantly increased from 0.75 (95% C.I. 0.66-0.83) to 0.85 (95% C.I. 0.77-0.93) and from 0.71 (95% C.I. 0.62-0.80) to 0.80 (95% C.I. 0.71-0.88), respectively. Overall, the developed AI model was found to be reliable for detecting wrist fractures, particularly for scaphoid fractures, which are commonly missed.

Subsidence Performance of the Bioactive Glass-Ceramic (CaO-SiO2-P2O5-B2O3) Spacer in Terms of Modulus of Elasticity and Contact Area: Mechanical Test and Finite Element Analysis.

OBJECTIVE: The objective of this study is to evaluate the subsidence performance of a bioactive glass-ceramic (CaO-SiO2-P2O5-B2O3) spacer in terms of its modulus of elasticity and contact area using mechanical tests and finite element analysis. METHODS: Three spacer three-dimensional models (Polyether ether ketone [PEEK]-C: PEEK spacer with a small contact area; PEEK-NF: PEEK spacer with a large contact area; and Bioactive glass [BGS]-NF: bioactive glass-ceramic spacer with a large contact area) are constructed and placed between bone blocks for compression analysis. The stress distribution, peak von Mises stress, and reaction force generated in the bone block are predicted by applying a compressive load. Subsidence tests are conducted for three spacer models in accordance with ASTM F2267. Three types of blocks measuring 8, 10, and 15 pounds per cubic foot are used to account for the various bone qualities of patients. A statistical analysis of the results is conducted using a one-way Analysis of variance and post hoc analysis (Tukey's Honestly Significant Difference) by measuring the stiffness and yield load. RESULTS: The stress distribution, peak von Mises stress, and reaction force predicted via the finite element analysis are the highest for PEEK-C, whereas they are similar for PEEK-NF and BGS-NF. Results of mechanical tests show that the stiffness and yield load of PEEK-C are the lowest, whereas those of PEEK-NF and BGS-NF are similar. CONCLUSIONS: The main factor affecting subsidence performance is the contact area. Therefore, bioactive glass-ceramic spacers exhibit a larger contact area and better subsidence performance than conventional spacers.

Non-Contact VITAL Signs Monitoring of a Patient Lying on Surgical Bed Using Beamforming FMCW Radar.

Respiration and heartrates are important information for surgery. When the vital signs of the patient lying prone are monitored using radar installed on the back of the surgical bed, the surgeon's movements reduce the accuracy of these monitored vital signs. This study proposes a method for enhancing the monitored vital sign accuracies of a patient lying on a surgical bed using a 60 GHz frequency modulated continuous wave (FMCW) radar system with beamforming. The vital sign accuracies were enhanced by applying a fast Fourier transform (FFT) for range and beamforming which suppress the noise generated at different ranges and angles from the patient's position. The experiment was performed for a patient lying on a surgical bed with or without surgeon. Comparing a continuous-wave (CW) Doppler radar, the FMCW radar with beamforming improved almost 22 dB of signal-to-interference and noise ratio (SINR) for vital signals. More than 90% accuracy of monitoring respiration and heartrates was achieved even though the surgeon was located next to the patient as an interferer. It was analyzed using a proposed vital signal model included in the radar IF equation.

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.

The Effect of Whitlockite as an Osteoconductive Synthetic Bone Substitute Material in Animal Bony Defect Model.

This study aimed to evaluate the biomechanical properties in vitro and the bone regeneration of whitlockite (WH) compared with hydroxyapatite (HA) or ß-tricalcium phosphate (ß-TCP)-based material. We investigated the morphology and phase composition of the bone grafts using a scanning electron microscope and X-ray diffractometer patterns and tested the compressive strength. Four circular defects of 8 mm in diameter were created on the calvaria of twelve rabbits. One defect was left empty, and each of the other defects was filled with WH, HA, and ß-TCP. At 4 and 8 weeks, the specimens were harvested to evaluate for the new bone formation and the remaining bone grafts. Regarding the biomechanical properties, the three grafts had a similar micropore size, and WH showed nanopores. The compressive strength of WH was higher than HA and ß-TCP without statistical significance. The radiological and histomorphometric analyses demonstrated that the new bone formation was similar among the groups. The remaining bone graft of the WH group was greater than that of the HA and ß-TCP groups at 4 weeks (p < 0.05), and the total bone area of the WH, HA, and ß-TCP groups was greater than that of the other (p < 0.01). WH has excellent volumetric stability and osteoconductivity compared with HA and ß-TCP.

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.

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.

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.

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.

Assessment of rapidly advancing bone age during puberty on elbow radiographs using a deep neural network model.

OBJECTIVES: Bone age is considered an indicator for the diagnosis of precocious or delayed puberty and a predictor of adult height. We aimed to evaluate the performance of a deep neural network model in assessing rapidly advancing bone age during puberty using elbow radiographs. METHODS: In all, 4437 anteroposterior and lateral pairs of elbow radiographs were obtained from pubertal individuals from two institutions to implement and validate a deep neural network model. The reference standard bone age was established by five trained researchers using the Sauvegrain method, a scoring system based on the shapes of the lateral condyle, trochlea, olecranon apophysis, and proximal radial epiphysis. A test set (n = 141) was obtained from an external institution. The differences between the assessment of the model and that of reviewers were compared. RESULTS: The mean absolute difference (MAD) in bone age estimation between the model and reviewers was 0.15 years on internal validation. In the test set, the MAD between the model and the five experts ranged from 0.19 to 0.30 years. Compared with the reference standard, the MAD was 0.22 years. Interobserver agreement was excellent among reviewers (ICC: 0.99) and between the model and the reviewers (ICC: 0.98). In the subpart analysis, the olecranon apophysis exhibited the highest accuracy (74.5%), followed by the trochlea (73.7%), lateral condyle (73.7%), and radial epiphysis (63.1%). CONCLUSIONS: Assessment of rapidly advancing bone age during puberty on elbow radiographs using our deep neural network model was similar to that of experts. KEY POINTS: • Bone age during puberty is particularly important for patients with scoliosis or limb-length discrepancy to determine the phase of the disease, which influences the timing and method of surgery. • The commonly used hand radiographs-based methods have limitations in assessing bone age during puberty due to the less prominent morphological changes of the hand and wrist bones in this period. • A deep neural network model trained with elbow radiographs exhibited similar performance to human experts on estimating rapidly advancing bone age during puberty.

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.

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.

Full color-tunable vertically stacked quantum dot light emitting diodes for next-generation displays and lighting.

We report solution-processed color tunable vertically stacked electroluminescent red, green, and blue quantum dot light emitting diodes (QLEDs). These QLEDs can be independently driven to produce all primary, secondary, and white lights. We have fabricated the device by chemical and electrical isolation of each QLED with transparent polymers and by the use of transparent electrodes. These stacked QLEDs can be used for next-generation display and lighting applications that need high pixel density along with quantum dots' intrinsic benefits such as low turn-on voltage, color purity, and solution processability.

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.

Sensor Fault Detection and Signal Restoration in Intelligent Vehicles.

This paper presents fault diagnosis logic and signal restoration algorithms for vehicle motion sensors. Because various sensors are equipped to realize automatic operation of the vehicle, defects in these sensors lead to severe safety issues. Therefore, an effective and reliable fault detection and recovery system should be developed. The primary idea of the proposed fault detection system is the conversion of measured wheel speeds into vehicle central axis information and the selection of a reference central axis speed based on this information. Thus, the obtained results are employed to estimate the speed for all wheel sides, which are compared with measured values to identify fault and recover the fault signal. For fault diagnosis logic, a conditional expression is derived with only two variables to distinguish between normal and fault; further, an analytical redundancy structure and a simple diagnostic logic structure are presented. Finally, an off-line test is conducted using test vehicle information to validate the proposed method; it demonstrates that the proposed fault detection and signal restoration algorithm can satisfy the control performance required for each sensor failure.

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.

An intracortical chondromyxoid fibroma in the diaphysis of the metatarsal.

Chondromyxoid fibromas (CMFs) are rare, benign, primary tumors of bones, and occur in the metaphyses of the medullary canals of the long bones. The occurrence of intracortical CMFs is extremely rare. Very few cases of intracortical CMFs located in the long tubular bones have been reported to date. Moreover, even though the feet are the second most common site for CMF (after the knees), intracortical metatarsal CMF has not been reported previously, to our knowledge. We report an intracortical CMF occurring in the diaphysis of the metatarsal in a 17-year-old man. It showed the same imaging findings as usual intramedullary CMFs, except for its cortical location. The development and serial increase in this tumor over time are also demonstrated in this report. Additionally, we present a review of current literature on intracortical CMFs.