Voriconazole-induced periostitis in two post-transplant patients

While drug-related periostitis has been known of for many years, the specific association of diffuse periostitis with voriconazole (most frequently in transplant patients) has only been recently explicitly addressed in the literature. Recognition of the radiologic and clinical manifestations of voriconazole-related periostitis is important for helping to narrow an otherwise broad differential diagnosis. We present two cases that illustrate different radiologic presentations of this painful cause of diffuse periostitis. Case 1 features a 60 year-old woman with a history of orthotopic heart transplant who was hospitalized for “full body pain” with progressively worsening bone tenderness involving the humeri, knees, femurs, hips, and hands. Case 2 describes a 48 year-old man with a history of acute lymphoblastic leukemia status post stem cell transplant who presented with diffuse arthralgias involving bilateral ankles, knees, wrists, and elbows

Voriconazole-induced periostitis in two post-transplant patients.

While drug-related periostitis has been known of for many years, the specific association of diffuse periostitis with voriconazole (most frequently in transplant patients) has only been recently explicitly addressed in the literature. Recognition of the radiologic and clinical manifestations of voriconazole-related periostitis is important for helping to narrow an otherwise broad differential diagnosis. We present two cases that illustrate different radiologic presentations of this painful cause of diffuse periostitis. Case 1 features a 60 year-old woman with a history of orthotopic heart transplant who was hospitalized for "full body pain" with progressively worsening bone tenderness involving the humeri, knees, femurs, hips, and hands. Case 2 describes a 48 year-old man with a history of acute lymphoblastic leukemia status post stem cell transplant who presented with diffuse arthralgias involving bilateral ankles, knees, wrists, and elbows

Imaging bone–cartilage interactions in osteoarthritis using [18F]-NaF PET-MRI

Purpose: Simultaneous positron emission tomography–magnetic resonance imaging (PET-MRI) is an emerging technology providing both anatomical and functional images without increasing the scan time. Compared to the traditional PET/computed tomography imaging, it also exposes the patient to significantly less radiation and provides better anatomical images as MRI provides superior soft tissue characterization. Using PET-MRI, we aim to study interactions between cartilage composition and bone function simultaneously, in knee osteoarthritis (OA). Procedures: In this article, bone turnover and remodeling was studied using [18F]-sodium fluoride (NaF) PET data. Quantitative MR-derived T1ρ relaxation times characterized the biochemical cartilage degeneration. Sixteen participants with early signs of OA of the knee received intravenous injections of [18F]-NaF at the onset of PET-MR image acquisition. Regions of interest were identified, and kinetic analysis of dynamic PET data provided the rate of uptake (Ki) and the normalized uptake (standardized uptake value) of [18F]-NaF in the bone. Morphological MR images and quantitative voxel-based T1ρ maps of cartilage were obtained using an atlas-based registration technique to segment cartilage automatically. Voxel-by-voxel statistical parameter mapping was used to investigate the relationship between bone and cartilage. Results: Increases in cartilage T1ρ, indicating degenerative changes, were associated with increased turnover in the adjoining bone but reduced turnover in the nonadjoining compartments. Associations between pain and increased bone uptake were seen in the absence of morphological lesions in cartilage, but the relationship was reversed in the presence of incident cartilage lesions. Conclusion: This study shows significant cartilage and bone interactions in OA of the knee joint using simultaneous [18F]-NaF PET-MR, the first in human study. These observations highlight the complex biomechanical and biochemical interactions in the whole knee joint in OA, which potentially could help assess therapeutic targets in treating OA

Imaging bone–cartilage interactions in osteoarthritis using [18F]-NaF PET-MRI

Purpose: Simultaneous positron emission tomography–magnetic resonance imaging (PET-MRI) is an emerging technology providing both anatomical and functional images without increasing the scan time. Compared to the traditional PET/computed tomography imaging, it also exposes the patient to significantly less radiation and provides better anatomical images as MRI provides superior soft tissue characterization. Using PET-MRI, we aim to study interactions between cartilage composition and bone function simultaneously, in knee osteoarthritis (OA). Procedures: In this article, bone turnover and remodeling was studied using [18F]-sodium fluoride (NaF) PET data. Quantitative MR-derived T1ρ relaxation times characterized the biochemical cartilage degeneration. Sixteen participants with early signs of OA of the knee received intravenous injections of [18F]-NaF at the onset of PET-MR image acquisition. Regions of interest were identified, and kinetic analysis of dynamic PET data provided the rate of uptake (Ki) and the normalized uptake (standardized uptake value) of [18F]-NaF in the bone. Morphological MR images and quantitative voxel-based T1ρ maps of cartilage were obtained using an atlas-based registration technique to segment cartilage automatically. Voxel-by-voxel statistical parameter mapping was used to investigate the relationship between bone and cartilage. Results: Increases in cartilage T1ρ, indicating degenerative changes, were associated with increased turnover in the adjoining bone but reduced turnover in the nonadjoining compartments. Associations between pain and increased bone uptake were seen in the absence of morphological lesions in cartilage, but the relationship was reversed in the presence of incident cartilage lesions. Conclusion: This study shows significant cartilage and bone interactions in OA of the knee joint using simultaneous [18F]-NaF PET-MR, the first in human study. These observations highlight the complex biomechanical and biochemical interactions in the whole knee joint in OA, which potentially could help assess therapeutic targets in treating OA

3D convolutional neural networks for detection and severity staging of meniscus and PFJ cartilage morphological degenerative changes in osteoarthritis and anterior cruciate ligament subjects.

BackgroundSemiquantitative assessment of MRI plays a central role in musculoskeletal research; however, in the clinical setting MRI reports often tend to be subjective and qualitative. Grading schemes utilized in research are not used because they are extraordinarily time-consuming and unfeasible in clinical practice.PurposeTo evaluate the ability of deep-learning models to detect and stage severity of meniscus and patellofemoral cartilage lesions in osteoarthritis and anterior cruciate ligament (ACL) subjects.Study typeRetrospective study aimed to evaluate a technical development.PopulationIn all, 1478 MRI studies, including subjects at various stages of osteoarthritis and after ACL injury and reconstruction.Field strength/sequence3T MRI, 3D FSE CUBE.AssessmentAutomatic segmentation of cartilage and meniscus using 2D U-Net, automatic detection, and severity staging of meniscus and cartilage lesion with a 3D convolutional neural network (3D-CNN).Statistical testsReceiver operating characteristic (ROC) curve, specificity and sensitivity, and class accuracy.ResultsSensitivity of 89.81% and specificity of 81.98% for meniscus lesion detection and sensitivity of 80.0% and specificity of 80.27% for cartilage were achieved. The best performances for staging lesion severity were obtained by including demographics factors, achieving accuracies of 80.74%, 78.02%, and 75.00% for normal, small, and complex large lesions, respectively.Data conclusionIn this study we provide a proof of concept of a fully automated deep-learning pipeline that can identify the presence of meniscal and patellar cartilage lesions. This pipeline has also shown potential in making more in-depth examinations of lesion subjects for multiclass prediction and severity staging.Level of evidence2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:400-410

Bone Remodeling after MR Imaging–guided High-Intensity Focused Ultrasound Ablation: Evaluation with MR Imaging, CT, Na18F-PET, and Histopathologic Examination in a Swine Model

PurposeTo serially monitor bone remodeling in the swine femur after magnetic resonance (MR) imaging-guided high-intensity focused ultrasound (HIFU) ablation with MR imaging, computed tomography (CT), sodium fluorine 18 (Na(18)F)-positron emission tomography (PET), and histopathologic examination, as a function of sonication energy.Materials and methodsExperimental procedures received approval from the local institutional animal care and use committee. MR imaging-guided HIFU was used to create distal and proximal ablations in the right femurs of eight pigs. The energy used at the distal target was higher (mean, 419 J; range, 390-440 J) than that used at the proximal target (mean, 324 J; range, 300-360 J). Imaging was performed before and after ablation with 3.0-T MR imaging and 64-section CT. Animals were reevaluated at 3 and 6 weeks with MR imaging (n = 8), CT (n = 8), Na(18)F-PET (n = 4), and histopathologic examination (n = 4). Three-dimensional ablation lengths were measured on contrast material-enhanced MR images, and bone remodeling in the cortex was measured on CT images.ResultsAblation sizes at MR imaging 3 and 6 weeks after MR imaging-guided HIFU ablation were similar between proximal (low-energy) and distal (high-energy) lesions (average, 8.7 × 21.9 × 16.4 mm). However, distal ablation lesions (n = 8) demonstrated evidence of subperiosteal new bone formation at CT, with a subtle focus of new ossification at 3 weeks and a larger focus of ossification at 6 weeks. New bone formation was associated with increased uptake at Na(18)F-PET in three of four animals; this was confirmed at histopathologic examination in four of four animals.ConclusionMR imaging-guided HIFU ablation of bone may result in progressive remodeling, with both subcortical necrosis and subperiosteal new bone formation. This may be related to the use of high energies. MR imaging, CT, and PET are suitable noninvasive techniques to monitor bone remodeling after MR imaging-guided HIFU ablation

Automatic Deep Learning-assisted Detection and Grading of Abnormalities in Knee MRI Studies.

PurposeTo test the hypothesis that artificial intelligence (AI) techniques can aid in identifying and assessing lesion severity in the cartilage, bone marrow, meniscus, and anterior cruciate ligament (ACL) in the knee, improving overall MRI interreader agreement.Materials and methodsThis retrospective study was conducted on 1435 knee MRI studies (n = 294 patients; mean age, 43 years ± 15 [standard deviation]; 153 women) collected within three previous studies (from 2011 to 2014). All MRI studies were acquired using high-spatial-resolution three-dimensional fast-spin-echo CUBE sequence. Three-dimensional convolutional neural networks were developed to detect the regions of interest within MRI studies and grade abnormalities of the cartilage, bone marrow, menisci, and ACL. Evaluation included sensitivity, specificity, and Cohen linear-weighted ĸ. The impact of AI-aided grading in intergrader agreement was assessed on an external dataset.ResultsBinary lesion sensitivity reported for all tissues was between 70% and 88%. Specificity ranged from 85% to 89%. The area under the receiver operating characteristic curve for all tissues ranged from 0.83 to 0.93. Deep learning-assisted intergrader Cohen ĸ agreement significantly improved in 10 of 16 comparisons among two attending physicians and two trainees for all tissues.ConclusionThe three-dimensional convolutional neural network had high sensitivity, specificity, and accuracy for knee-lesion-severity scoring and also increased intergrader agreement when used on an external dataset.Supplemental material is available for this article. Keywords: Bone Marrow, Cartilage, Computer Aided Diagnosis (CAD), Computer Applications-3D, Computer Applications-Detection/Diagnosis, Knee, Ligaments, MR-Imaging, Neural Networks, Observer Performance, Segmentation, Statistics © RSNA, 2021See also the commentary by Li and Chang in this issue.: An earlier incorrect version of this article appeared online. This article was corrected on April 16, 2021