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OBJECTIVE:To investigate changes in bone metabolism by positron emission tomography (PET), as well as spatial relationships between bone metabolism and magnetic resonance imaging (MRI) quantitative markers of early cartilage degradation, in anterior cruciate ligament (ACL)-reconstructed knees. DESIGN:Both knees of 15 participants with unilateral reconstructed ACL tears and unaffected contralateral knees were scanned using a simultaneous 3.0T PET-MRI system following injection of 18F-sodium fluoride (18F-NaF). The maximum pixel standardized uptake value (SUVmax) in the subchondral bone and the average T2 relaxation time in cartilage were measured in each knee in eight knee compartments. We tested differences in SUVmax and cartilage T2 relaxation times between the ACL-injured knee and the contralateral control knee as well as spatial relationships between these bone and cartilage changes. RESULTS:Significantly increased subchondral bone 18F-NaF SUVmax and cartilage T2 times were observed in the ACL-reconstructed knees (median [inter-quartile-range (IQR)]: 5.0 [5.8], 36.8 [3.6] ms) compared to the contralateral knees (median [IQR]: 1.9 [1.4], 34.4 [3.8] ms). A spatial relationship between the two markers was also seen. Using the contralateral knee as a control, we observed a significant correlation of r = 0.59 between the difference in subchondral bone SUVmax (between injured and contralateral knees) and the adjacent cartilage T2 (between the two knees) [P

We systematically evaluate the training methodology and efficacy of two inpainting-based pretext tasks of context prediction and context restoration for medical image segmentation using self-supervised learning (SSL). Multiple versions of self-supervised U-Net models were trained to segment MRI and CT datasets, each using a different combination of design choices and pretext tasks to determine the effect of these design choices on segmentation performance. The optimal design choices were used to train SSL models that were then compared with baseline supervised models for computing clinically-relevant metrics in label-limited scenarios. We observed that SSL pretraining with context restoration using 32 × 32 patches and Poission-disc sampling, transferring only the pretrained encoder weights, and fine-tuning immediately with an initial learning rate of 1 × 10-3 provided the most benefit over supervised learning for MRI and CT tissue segmentation accuracy ( p < 0.001). For both datasets and most label-limited scenarios, scaling the size of unlabeled pretraining data resulted in improved segmentation performance. SSL models pretrained with this amount of data outperformed baseline supervised models in the computation of clinically-relevant metrics, especially when the performance of supervised learning was low. Our results demonstrate that SSL pretraining using inpainting-based pretext tasks can help increase the robustness of models in label-limited scenarios and reduce worst-case errors that occur with supervised learning.

Diffusion tensor imaging (DTI) measures water diffusion in skeletal muscle tissue and allows for muscle assessment in a broad range of neuromuscular diseases. However, current DTI measurements, typically performed using pulsed gradient spin echo (PGSE) diffusion encoding, are limited to the assessment of non-contracted musculature, therefore providing limited insight into muscle contraction mechanisms and contraction abnormalities. In this study, we propose the use of an oscillating gradient spin echo (OGSE) diffusion encoding strategy for DTI measurements to mitigate the effect of signal voids in contracted muscle and to obtain reliable diffusivity values. Two OGSE sequences with encoding frequencies of 25 and 50 Hz were tested in the lower leg of five healthy volunteers with relaxed musculature and during active dorsiflexion and plantarflexion, and compared with a conventional PGSE approach. A significant reduction of areas of signal voids using OGSE compared with PGSE was observed in the tibialis anterior for the scans obtained in active dorsiflexion and in the soleus during active plantarflexion. The use of PGSE sequences led to unrealistically elevated axial diffusivity values in the tibialis anterior during dorsiflexion and in the soleus during plantarflexion, while the corresponding values obtained using the OGSE sequences were significantly reduced. Similar findings were seen for radial diffusivity, with significantly higher diffusivity measured in plantarflexion in the soleus muscle using the PGSE sequence. Our preliminary results indicate that DTI with OGSE diffusion encoding is feasible in human musculature and allows to quantitatively assess diffusion properties in actively contracting skeletal muscle. OGSE holds great potential to assess microstructural changes occurring in the skeletal muscle during contraction, and for non-invasive assessment of contraction abnormalities in patients with muscle diseases., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Mazzoli, Moulin, Kogan, Hargreaves and Gold.)

Background: To assess diagnostic accuracy of quantitative double-echo in steady-state (qDESS) MRI for detecting synovitis in knee osteoarthritis (OA)., Methods: Patients with different degrees of radiographic knee OA were included prospectively. All underwent MRI with both qDESS and contrast-enhanced T1-weighted magnetic resonance imaging (CE-MRI). A linear combination of the two qDESS images can be used to create an image that displays contrast between synovium and the synovial fluid. Synovitis on both qDESS and CE-MRI was assessed semi-quantitatively, using a whole-knee synovitis sum score, indicating no/equivocal, mild, moderate, and severe synovitis. The correlation between sum scores of qDESS and CE-MRI (reference standard) was determined using Spearman's rank correlation coefficient and intraclass correlation coefficient for absolute agreement. Receiver operating characteristic analysis was performed to assess the diagnostic performance of qDESS for detecting different degrees of synovitis, with CE-MRI as reference standard., Results: In the 31 patients included, very strong correlation was found between synovitis sum scores on qDESS and CE-MRI (ρ = 0.96, p < 0.001), with high absolute agreement (0.84 (95%CI 0.14-0.95)). Mean sum score (SD) values on qDESS 5.16 (3.75) were lower than on CE-MRI 7.13 (4.66), indicating systematically underestimated synovitis severity on qDESS. For detecting mild synovitis or higher, high sensitivity and specificity were found for qDESS (1.00 (95%CI 0.80-1.00) and 0.909 (0.571-1.00), respectively). For detecting moderate synovitis or higher, sensitivity and specificity were good (0.727 (95%CI 0.393-0.927) and 1.00 (0.800-1.00), respectively)., Conclusion: qDESS MRI is able to, however with an underestimation, detect synovitis in patients with knee OA.

Purpose: To organize a multi-institute knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthritis progression., Materials and Methods: A dataset partition consisting of three-dimensional knee MRI from 88 retrospective patients at two time points (baseline and 1-year follow-up) with ground truth articular (femoral, tibial, and patellar) cartilage and meniscus segmentations was standardized. Challenge submissions and a majority-vote ensemble were evaluated against ground truth segmentations using Dice score, average symmetric surface distance, volumetric overlap error, and coefficient of variation on a holdout test set. Similarities in automated segmentations were measured using pairwise Dice coefficient correlations. Articular cartilage thickness was computed longitudinally and with scans. Correlation between thickness error and segmentation metrics was measured using the Pearson correlation coefficient. Two empirical upper bounds for ensemble performance were computed using combinations of model outputs that consolidated true positives and true negatives., Results: Six teams ( T 1 - T 6 ) submitted entries for the challenge. No differences were observed across any segmentation metrics for any tissues ( P = .99) among the four top-performing networks ( T 2 , T 3 , T 4 , T 6 ). Dice coefficient correlations between network pairs were high (> 0.85). Per-scan thickness errors were negligible among networks T 1 - T 4 ( P = .99), and longitudinal changes showed minimal bias (< 0.03 mm). Low correlations (ρ < 0.41) were observed between segmentation metrics and thickness error. The majority-vote ensemble was comparable to top-performing networks ( P = .99). Empirical upper-bound performances were similar for both combinations (P = .99)., Conclusion: Diverse networks learned to segment the knee similarly, where high segmentation accuracy did not correlate with cartilage thickness accuracy and voting ensembles did not exceed individual network performance.See also the commentary by Elhalawani and Mak in this issue. Keywords: Cartilage, Knee, MR-Imaging, Segmentation © RSNA, 2020 Supplemental material is available for this article., Competing Interests: Disclosures of Conflicts of Interest: A.D.D. Activities related to the present article: grants and travel support from the National Science Foundation, the National Institute of Arthritis and Musculoskeletal and Skin Diseases, the National Institute of Biomedical Imaging and Bioengineering, GE Healthcare, and Philips. Activities not related to the present article: grants from the National Institutes of Health. Other relationships: disclosed no relevant relationships. F.C. disclosed no relevant relationships. C. Iriondo disclosed no relevant relationships. A.M. disclosed no relevant relationships. S.J. disclosed no relevant relationships. U.B. disclosed no relevant relationships. M.P. Activities related to the present article: grant from the Independent Research Fund Denmark. Activities not related to the present article: disclosed no relevant relationships. Other relationships: disclosed no relevant relationships. C. Igel Activities related to the present article: grant from the Danish Council for Independent Research. Activities not related to the present article: disclosed no relevant relationships. Other relationships: disclosed no relevant relationships. E.B.D. Activities related to the present article: disclosed no relevant relationships. Activities not related to the present article: stockholder in Biomediq and Cerebriu. Other relationships: disclosed no relevant relationships. S.G. disclosed no relevant relationships. M.Y. disclosed no relevant relationships. X.L. disclosed no relevant relationships. C.M.D. Activities related to the present article: grant from the National Institute of Arthritis and Musculoskeletal and Skin Diseases. Activities not related to the present article: disclosed no relevant relationships. Other relationships: disclosed no relevant relationships. V.J. disclosed no relevant relationships. R.R. disclosed no relevant relationships. G.E.G. Activities related to the present article: grants from the National Institutes of Health. Activities not related to the present article: board member for HeartVista; consultant for Canon; grants from GE Healthcare. Other relationships: disclosed no relevant relationships. B.A.H. Activities related to the present article: grant from the National Institutes of Health. Activities not related to the present article: royalties from patents licensed by Siemens and GE Healthcare; stockholder in LVIS. Other relationships: disclosed no relevant relationships. V.P. disclosed no relevant relationships. A.S.C. Activities related to the present article: grants from the National Institutes of Health, GE Healthcare, and Philips. Activities not related to the present article: board member for BrainKey and Chondrometrics; consultant for Skope, Subtle Medical, Chondrometrics, Image Analysis Group, Edge Analytics, ICM, and Culvert Engineering; stockholder in Subtle Medical, LVIS, and BrainKey; travel support from Paracelsus Medical Private University. Other relationships: disclosed no relevant relationships., (2021 by the Radiological Society of North America, Inc.)

Purpose: Identifying small lung lesions during minimally invasive thoracic surgery can be challenging. We describe 3-dimensional mixed-reality visualization technology that may facilitate noninvasive nodule localization., Description: A software application and medical image processing pipeline were developed for the Microsoft HoloLens to incorporate patient-specific data and provide a mixed-reality tool to explore and manipulate chest anatomy with a custom-designed user interface featuring gesture and voice recognition., Evaluation: A needs assessment between engineering and clinical disciplines identified the potential utility of mixed-reality technology in facilitating safe and effective resection of small lung nodules. Through an iterative process, we developed a prototype employing a wearable headset that allows the user to (1) view a patient's original preoperative imaging; (2) manipulate a 3-dimensional rendering of that patient's chest anatomy including the bronchial, osseus, and vascular structures; and (3) simulate lung deflation and surgical instrument placement., Conclusions: Mixed-reality visualization during surgical planning may facilitate accurate and rapid identification of small lung lesions during minimally invasive surgeries and reduce the need for additional invasive preoperative localization procedures., (Copyright © 2020 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)

Chronic sciatica is a major cause of disability worldwide, but accurate diagnosis of the causative pathology remains challenging. In this report, the feasibility of an 18 F-FDG PET/MRI approach for improved diagnosis of chronic sciatica is presented. Methods: 18 F-FDG PET/MRI was performed on 9 chronic sciatica patients and 5 healthy volunteers (healthy controls). Region-of-interest analysis using SUV max was performed, and 18 F-FDG uptake in lesions was compared with that in the corresponding areas in healthy controls. Results: Significantly increased 18 F-FDG uptake was observed in detected lesions in all patients and was correlated with pain symptoms. 18 F-FDG-avid lesions not only were found in impinged spinal nerves but also were associated with nonspinal causes of pain, such as facet joint degeneration, pars defect, or presumed scar neuroma. Conclusion: The feasibility of 18 F-FDG PET/MRI for diagnosing pain generators in chronic sciatica was demonstrated, revealing various possible etiologies., (© 2018 by the Society of Nuclear Medicine and Molecular Imaging.)

To evaluate the performance of computed high b value diffusion-weighted images (DWI) in prostate cancer detection. 97 consecutive patients who had undergone multiparametric MRI of the prostate followed by biopsy were reviewed. Five radiologists independently scored 138 lesions on native high b-value images (b = 1200 s/mm 2 ), apparent diffusion coefficient (ADC) maps, and computed high b-value images (contrast equivalent to b = 2000 s/mm 2 ) to compare their diagnostic accuracy. Receiver operating characteristic (ROC) analysis and McNemar's test were performed to assess the relative performance of computed high b value DWI, native high b-value DWI and ADC maps. No significant difference existed in the area under the curve (AUC) for ROCs comparing B1200 (b = 1200 s/mm 2 ) to computed B2000 (c-B2000) in 5 readers. In 4 of 5 readers c-B2000 had significantly increased sensitivity and/or decreased specificity compared to B1200 (McNemar's p < 0.05), at selected thresholds of interpretation. ADC maps were less accurate than B1200 or c-B2000 for 2 of 5 readers (P < 0.05). This study detected no consistent improvement in overall diagnostic accuracy using c-B2000, compared with B1200 images. Readers detected more cancer with c-B2000 images (increased sensitivity) but also more false positive findings (decreased specificity).

Purpose: To identify focal lesions of elevated MRI T 2 and T 1ρ relaxation times in articular cartilage of an ACL-injured group using a novel cluster analysis technique., Materials and Methods: Eighteen ACL-injured patients underwent 3T MRI T 2 and T 1ρ relaxometry at baseline, 6 months and 1 year and six healthy volunteers at baseline, 1 day and 1 year. Clusters of contiguous pixels above or below T 2 and T 1ρ intensity and area thresholds were identified on a projection map of the 3D femoral cartilage surface. The total area of femoral cartilage plate covered by clusters (%CA) was split into areas above (%CA+) and below (%CA-) the thresholds and the differences in %CA(+ or -) over time in the ACL-injured group were determined using the Wilcoxon signed rank test., Results: %CA+ was greater in the ACL-injured patients than the healthy volunteers at 6 months and 1 year with average %CA+ of 5.2 ± 4.0% (p = 0.0054) and 6.6 ± 3.7% (p = 0.0041) for T 2 and 6.2 ± 7.1% (p = 0.063) and 8.2 ± 6.9% (p = 0.042) for T 1ρ , respectively. %CA- at 6 months and 1 year was 3.0 ± 1.8% (p > 0.1) and 5.9 ± 5.0% (p > 0.1) for T 2 and 4.4 ± 4.9% (p > 0.1) and 4.5 ± 4.6% (p > 0.1) for T 1ρ , respectively., Conclusion: With the proposed cluster analysis technique, we have quantified cartilage lesion coverage and demonstrated that the ACL-injured group had greater areas of elevated T 2 and T 1ρ relaxation times as compared to healthy volunteers., (Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.)

Purpose: To determine the reliability of arterial phase capture and evaluate hypervascular lesion contrast kinetics with a combined view-sharing and parallel imaging dynamic contrast-enhanced acquisition, DIfferential Sub-sampling with Cartesian Ordering (DISCO), in patients with known chronic liver disease., Methods: A retrospective review of 3T MR images from 26 patients with known chronic liver disease referred for hepatocellular carcinoma surveillance or post-treatment follow up was performed. After administration of a gadolinium-based contrast agent, a multiphasic acquisition was obtained in a 28 s breath-hold, from which seven sequential post-contrast image volumes were reconstructed., Results: The late arterial phase was successfully captured in all cases (26/26, 95% CI 87-100%). Images obtained 26 s post-injection had the highest frequency of late arterial phase capture (20/26) and lesion detection (23/26) of any individual post-contrast time; however, the multiphasic data resulted in a significantly higher frequency of late arterial phase capture (26/26, p=0.03) and a higher relative contrast (5.37+/-0.97 versus 7.10+/-0.98, p < 0.01)., Conclusion: Multiphasic acquisition with combined view-sharing and parallel imaging reliably captures the late arterial phase and provides sufficient temporal resolution to characterize hepatic lesion contrast kinetics in patients with chronic liver disease while maintaining high spatial resolution.

Rationale and Objectives: To compare the effectiveness of multiacquisition with variable resonance image combination selective (MAVRIC SL) with conventional two-dimensional fast spin-echo (2D-FSE) magnetic resonance (MR) techniques at 3T in imaging patients with a variety of metallic implants., Materials and Methods: Twenty-one 3T MR studies were obtained in 19 patients with different types of metal implants. Paired MAVRIC SL and 2D-FSE sequences were reviewed by two radiologists and compared for in-plane and through-plane metal artifact, visualization of the bone implant interface and surrounding soft tissues, blurring, and overall image quality using a two-tailed Wilcoxon signed rank test. The area of artifact on paired images was measured and compared using a paired Wilcoxon signed rank test. Changes in patient management resulting from MAVRIC SL imaging were documented., Results: Significantly less in-plane and through-plane artifact was seen with MAVRIC SL, with improved visualization of the bone-implant interface and surrounding soft tissues, and superior overall image quality (P = .0001). Increased blurring was seen with MAVRIC SL (P = .0016). MAVRIC SL significantly decreased the image artifact compared to 2D-FSE (P = .0001). Inclusion of MAVRIC SL to the imaging protocol determined the need for surgery or type of surgery in five patients and ruled out the need for surgery in 13 patients. In three patients, the area of interest was well seen on both MAVRIC SL and 2D-FSE images, so the addition of MAVRIC had no effect on patient management., Conclusions: Imaging around metal implants with MAVRIC SL at 3T significantly improved image quality and decreased image artifact compared to conventional 2D-FSE imaging techniques and directly impacted patient management., (Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.)

Objective: To measure the variability of T1ρ relaxation times using CubeQuant, T2 relaxation times using quantitative double echo in steady state (DESS), and normalized sodium signals using 3D cones sodium magnetic resonance imaging (MRI) of knee cartilage in vivo at 3 T., Design: Eight healthy subjects were scanned at 3 T at baseline, 1 day, 5 months, and 1 year. Ten regions of interest (ROIs) of knee cartilage were segmented in the medial and lateral compartments of each subject's knee. T1ρ and T2 relaxation times and normalized sodium signals were measured and the root-mean-square coefficient of variation (CVRMS) was calculated. Intra-subject variability was measured over short, moderate and long-term, as well as intra-observer and inter-observer variability., Results: The average intra-subject CVRMS measurements over short, moderate, and long-term time periods were 4.6%, 6.1%, and 6.0% for the T1ρ measurements, 6.4%, 9.3%, and 10.7% for the T2 measurements and 11.3%, 11.6%, and 12.9% for the sodium measurements, respectively. The average CVRMS measurements for intra-observer and inter-observer segmentation were 3.8% and 5.7% for the T1ρ measurements, 4.7% and 6.7% for the T2 measurements, and 8.1% and 11.4% for the sodium measurements, respectively., Conclusions: These CVRMS measurements are substantially lower than previously measured changes expected in patients with advanced osteoarthritis compared to healthy volunteers, suggesting that CubeQuant T1ρ, quantitative DESS T2 and 3D cones sodium measurements are sufficiently sensitive for in vivo cartilage studies., (Copyright © 2014 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.)

Background: The prevalence of pseudotumors in patients with large-head metal-on-metal (MOM) THA has been the subject of implant recalls and warnings from various regulatory agencies. To date, there is no consensus on whether ultrasound or MRI is superior for the detection of pseudotumors., Questions/purposes: We prospectively compared ultrasound to MRI for pseudotumor detection in an asymptomatic cohort of patients with MOM THAs. We also compared ultrasound to MRI for assessment of pseudotumor growth and progressive soft tissue involvement at a 6-month interval., Methods: We enrolled 40 patients with large-head MOM THAs in the study. The mean age was 54 years (range, 34-76 years). The mean time from surgery was 54 months (range, 40-81 months). There were 28 men and 12 women. All patients underwent ultrasound and MRI using slice encoding for metal artifact correction. The gold standard was defined as follows: if both ultrasound and MRI agreed, this was interpreted as concordant and the result was considered accurate., Results: Ultrasound and MRI agreed in 37 of 40 patients (93%). The prevalence of pseudotumors was 31% (12 of 39) in our cohort. Twenty-three of 39 patients (59%) had completely normal tests and four (10%) had simple fluid collections. Ultrasound had a sensitivity of 100% and specificity of 96% while MRI had a sensitivity of 92% and specificity of 100%., Conclusions: A negative ultrasound rules out pseudotumor in asymptomatic patients as this test is 100% sensitive. Given its lower cost, we recommend ultrasound as the initial screening tool for pseudotumors.

Objective: Changes in T1ρ and T2 magnetic resonance relaxation times have been associated with articular cartilage degeneration, but similar relationships for meniscal tissue have not been extensively investigated. This work examined relationships between T1ρ and T2 measurements and biochemical and mechanical properties across regions of degenerate human menisci., Design: Average T1ρ and T2 relaxation times were determined for nine regions each of seven medial and 13 lateral menisci from 14 total knee replacement patients. Sulfated glycosaminoglycan (sGAG), collagen and water contents were measured for each region. Biomechanical measurements of equilibrium compressive, dynamic compressive and dynamic shear moduli were made for anterior, central and posterior regions., Results: T1ρ and T2 times showed similar regional patterns, with longer relaxation times in the (radially) middle region compared to the inner and outer regions. Pooled over all regions, T1ρ and T2 times showed strong correlations both with one another and with water content. Correlations with biochemical content varied depending on normalization to wet or dry mass, and both imaging parameters showed stronger correlations with collagen compared to sGAG content. Mechanical properties displayed moderate inverse correlations with increasing T1ρ and T2 times and water content., Conclusion: Both T1ρ and T2 relaxation times correlated strongly with water content and moderately with mechanical properties in osteoarthritic menisci, but not as strongly with sGAG or collagen contents alone. While the ability of magnetic resonance imaging (MRI) to detect early osteoarthritic changes remains the subject of investigation, these results suggest that T1ρ and T2 relaxation times have limited ability to detect compositional variations in degenerate menisci., (Copyright © 2013 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.)

Magnetic resonance (MR) guided optical breast imaging is a promising modality to improve the specificity of breast imaging, because it provides high-resolution quantitative maps of total hemoglobin, oxygen saturation, water content, and optical scattering. These properties have been shown to distinguish malignant from benign lesions. However, the optical detection hardware required for deep tissue imaging has poor spectral sensitivity which limits accurate water quantification; this reduces the accuracy of hemoglobin quantification. We present a methodology to improve optical quantification by utilizing the ability of Dixon MR imaging to quantitatively estimate water and fat; this technique effectively reduces optical crosstalk between water and oxyhemoglobin. The techniques described in this paper reduce hemoglobin quantification error by as much as 38%, as shown in a numerical phantom, and an experimental phantom. Error is reduced by as much 20% when imperfect MR water quantification is given. These techniques may also increase contrast between diseased and normal tissue, as shown in breast tissue in vivo. It is also shown that using these techniques may permit fewer wavelengths to be used with similar quantitative accuracy, enabling higher temporal resolution. In addition, it is shown that these techniques can improve the ability of MRI to quantify water in the presence of bias in the Dixon water/fat separation.