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Quantitative MRI techniques such as T2 and T1ρ mapping are beneficial in evaluating knee joint pathologies; however, long acquisition times limit their clinical adoption. MIXTURE (Multi-Interleaved X-prepared Turbo Spin-Echo with IntUitive RElaxometry) provides a versatile turbo spin-echo (TSE) platform for simultaneous morphologic and quantitative joint imaging. Two MIXTURE sequences were designed along clinical requirements: “MIX1”, combining proton density (PD)-weighted fat-saturated (FS) images and T2 mapping (acquisition time: 4:59 min), and “MIX2”, combining T1-weighted images and T1ρ mapping (6:38 min). MIXTURE sequences and their reference 2D and 3D TSE counterparts were acquired from ten human cadaveric knee joints at 3.0 T. Contrast, contrast-to-noise ratios, and coefficients of variation were comparatively evaluated using parametric tests. Clinical radiologists (n = 3) assessed diagnostic quality as a function of sequence and anatomic structure using five-point Likert scales and ordinal regression, with a significance level of α = 0.01. MIX1 and MIX2 had at least equal diagnostic quality compared to reference sequences of the same image weighting. Contrast, contrast-to-noise ratios, and coefficients of variation were largely similar for the PD-weighted FS and T1-weighted images. In clinically feasible scan times, MIXTURE sequences yield morphologic, TSE-based images of diagnostic quality and quantitative parameter maps with additional insights on soft tissue composition and ultrastructure.

Abstract Background To investigate the influence of benign prostatic hyperplasia (BPH) patterns detected with MRI on clinical outcomes after prostatic artery embolization (PAE). Materials & methods This retrospective study included 71 consecutive patients with lower urinary tract symptoms (LUTS), who underwent magnetic resonance imaging (MRI) of the prostate followed by PAE at a single centre. MRI scans were evaluated and BPH patterns were determined according to Wasserman type and a modified BPH classification. Additionally, scans were evaluated regarding the presence of adenomatous-dominant benign prostatic hyperplasia (AdBPH). LUTS were assessed using the International Prostate Symptom Score (IPSS) and urinary flow rate (Qmax). Follow-up examination included MRI and clinical outcome. Results For clinical outcome at follow-up, IPSS showed median reduction of 54% (IQR 41—75%) and Qmax improved by 4.1 ml/s. We noted significant reduction in volume, intraprostatic protrusion, and prostatic urethral angle in our collective (p

In medicine, especially in radiology, artificial intelligence has sparked a growing interest in automated systems, image analysis, and acquisition standardization. In the wake of this standardization, the research field of “radiomics” has gained importance. Using computer-aided analysis, image data and contours can be evaluated to determine numerical values for shape, size, and gray-scale texture, which can then be examined in a clinical context. Especially in cardiovascular imaging, data acquisition and analysis in different cardiac and respiratory phases are of great interest. However, most research studies use parameters that have been laboriously calculated by hand. “ShortCardiac” is a Python-based framework with a user-friendly GUI for the quantitative determination of cardiac MR parameters. This allows researchers to utilize quantitative MR research for their studies without programming knowledge, with just a few clicks. All calculated parameters can be displayed graphically. “shortCardiac” allows the visualization of segmentation contours, the angle-dependent length measurement, the center of gravity and much more, in addition, the background can be hidden, and the images can be cropped automatically. In addition, “shortCardiac” can also be called via python and due to the object-oriented design, it is possible to integrate new segmentation frameworks with little effort in the future as well as to determine additional parameters. However, “ShortCardiac” comes with certain limitations. It only assesses cardiac short-axis data and functions merely as a post-processing framework for determining surrogate parameters based on segmentation and image information. Manual segmentations or usage of fully automated segmentations, such as Circle cvi42, require additional software tools. Regardless of these restrictions, “ShortCardiac” provides an efficient, user-friendly tool, enabling researchers to capitalize on the expanding domain of radiomics.

Based on in silico, in vitro, in situ, and in vivo evaluations, this study aims to establish and optimize the chemical exchange saturation transfer (CEST) imaging of lactate (Lactate-CEST—LATEST). To this end, we optimized LATEST sequences using Bloch–McConnell simulations for optimal detection of lactate with a clinical 3 T MRI scanner. The optimized sequences were used to image variable lactate concentrations in vitro (using phantom measurements), in situ (using nine human cadaveric lower leg specimens), and in vivo (using four healthy volunteers after exertional exercise) that were then statistically analyzed using the non-parametric Friedman test and Kendall Tau-b rank correlation. Within the simulated Bloch–McConnell equations framework, the magnetization transfer ratio asymmetry (MTRasym) value was quantified as 0.4% in the lactate-specific range of 0.5–1 ppm, both in vitro and in situ, and served as the imaging surrogate of the lactate level. In situ, significant differences (p < 0.001) and strong correlations (τ = 0.67) were observed between the MTRasym values and standardized intra-muscular lactate concentrations. In vivo, a temporary increase in the MTRasym values was detected after exertional exercise. In this bench-to-bedside comprehensive feasibility study, different lactate concentrations were detected using an optimized LATEST imaging protocol in vitro, in situ, and in vivo at 3 T, which prospectively paves the way towards non-invasive quantification and monitoring of lactate levels across a broad spectrum of diseases.

Chemical Exchange Saturation Transfer (CEST) magnetic resonance imaging (MRI) provides a novel method for analyzing biomolecule concentrations in tissues without exogenous contrast agents. Despite its potential, achieving a high signal-to-noise ratio (SNR) is imperative for detecting small CEST effects. Traditional metrics such as Magnetization Transfer Ratio Asymmetry (MTRasym) and Lorentzian analyses are vulnerable to image noise, hampering their precision in quantitative concentration estimations. Recent noise-reduction algorithms like principal component analysis (PCA), nonlocal mean filtering (NLM), and block matching combined with 3D filtering (BM3D) have shown promise, as there is a burgeoning interest in the utilization of neural networks (NNs), particularly autoencoders, for imaging denoising. This study uses the Bloch–McConnell equations, which allow for the synthetic generation of CEST images and explores NNs efficacy in denoising these images. Using synthetically generated phantoms, autoencoders were created, and their performance was compared with traditional denoising methods using various datasets. The results underscored the superior performance of NNs, notably the ResUNet architectures, in noise identification and abatement compared to analytical approaches across a wide noise gamut. This superiority was particularly pronounced at elevated noise intensities in the in vitro data. Notably, the neural architectures significantly improved the PSNR values, achieving up to 35.0, while some traditional methods struggled, especially in low-noise reduction scenarios. However, the application to the in vivo data presented challenges due to varying noise profiles. This study accentuates the potential of NNs as robust denoising tools, but their translation to clinical settings warrants further investigation.

Abstract Clinical Magnetic Resonance Imaging (MRI) of joints is limited to mere morphologic evaluation and fails to directly visualize joint or ligament function. In this controlled laboratory study, we show that knee joint functionality may be quantified in situ and as a function of graded posterior cruciate ligament (PCL)-deficiency by combining MRI and standardized loading. 11 human knee joints underwent MRI under standardized posterior loading in the unloaded and loaded (147 N) configurations and in the intact, partially, and completely PCL-injured conditions. For each specimen, configuration, and condition, 3D joint models were implemented to analyse joint kinematics based on 3D Euclidean vectors and their projections on the Cartesian planes. Manual 2D measurements served as reference. With increasing PCL deficiency, vector projections increased significantly in the anteroposterior dimension under loading and manual measurements demonstrated similar patterns of change. Consequently, if combined with advanced image post-processing, stress MRI is a powerful diagnostic adjunct to evaluate ligament functionality and joint laxity in multiple dimensions and may have a role in differentiating PCL injury patterns, therapeutic decision-making, and treatment monitoring.

(1) Background: We aim to investigate age-related changes in cartilage structure and composition in the metacarpophalangeal (MCP) joints using magnetic resonance (MR) biomarkers. (2) Methods: The cartilage tissue of 90 MCP joints from 30 volunteers without any signs of destruction or inflammation was examined using T1, T2, and T1ρ compositional MR imaging techniques on a 3 Tesla clinical scanner and correlated with age. (3) Results: The T1ρ and T2 relaxation times showed a significant correlation with age (T1ρ: Kendall-τ-b = 0.3, p < 0.001; T2: Kendall-τ-b = 0.2, p = 0.01). No significant correlation was observed for T1 as a function of age (T1: Kendall-τ-b = 0.12, p = 0.13). (4) Conclusions: Our data show an increase in T1ρ and T2 relaxation times with age. We hypothesize that this increase is due to age-related changes in cartilage structure and composition. In future examinations of cartilage using compositional MRI, especially T1ρ and T2 techniques, e.g., in patients with osteoarthritis or rheumatoid arthritis, the age of the patients should be taken into account.

Abstract Background To compare the glycosaminoglycan (GAG) content of lumbar intervertebral disks (IVDs) of patients with ankylosing spondylitis (AS) and healthy volunteers and to investigate the association of GAG depletion and disease-related clinical and imaging features. Methods Lumbar spines of 50 AS patients (mean age 50 ± 10.5 years) and 30 age-matched volunteers were studied with 3-T magnetic resonance imaging (MRI) and conventional radiographs (CR). The MRI protocol included high-resolution morphological sequences and the compositional GAG chemical exchange saturation transfer imaging technique (gagCEST). Morphological images were analyzed by three raters for inflammatory activity, fat deposition, disk degeneration, and structural changes on CR. Clinical and serological measures included the Bath AS Disease Activity (BASDAI) and Bath AS Function (BASFI) Indices and C-reactive protein (CRP) levels. GagCEST values of both groups were compared using a linear mixed model. Kendall-Tau correlation analyses were performed. Results GagCEST values were significantly lower in AS patients (2.0 ± 1.7%) vs. healthy volunteers (2.4 ± 1.8%), p = 0.001. Small, yet significant correlations were found between gagCEST values and CRP levels (τ = − 0.14, p = 0.007), BASFI (τ = − 0.18, p

Abstract Background Even though cartilage loss is a known feature of psoriatic arthritis (PsA), little is known about its role in the pathogenesis of PsA. Using delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC) as a non-invasive marker of the tissue’s proteoglycan content, such early (i.e., pre-morphological) changes have been associated with inflammation in rheumatoid arthritis (RA). Yet, this association has not been studied before in PsA. Methods The metacarpophalangeal (MCP), proximal interphalangeal (PIP), and distal interphalangeal (DIP) joints of 17 patients with active PsA were evaluated by high-resolution clinical standard morphological and dGEMRIC sequences using a 3T MRI scanner (Magnetom Skyra, Siemens) and a dedicated 16-channel hand coil. Images were analyzed by two independent raters for dGEMRIC indices, PsA MRI scores (PsAMRIS), and total cartilage thickness (TCT). Kendall tau correlation coefficients (τ) were calculated. Results We found significant negative correlations between dGEMRIC indices and total PsAMRIS (τ = − 0.5, p = 0.012), synovitis (τ = − 0.56, p = 0.006), flexor tenosynovitis (τ = − 0.4, p = 0.049), and periarticular inflammation (τ = − 0.72, p

Abstract Background To evaluate the value of 3 Tesla (T) magnetic resonance imaging (MRI) changes of flexor tendon pulleys for the differentiation of psoriatic (PsA) and rheumatoid arthritis (RA), using a novel 16-channel high-resolution hand coil. Methods Seventeen patients with active PsA, 20 patients with active RA, and 16 healthy controls (HC) underwent high-resolution 3 T MRI using the dedicated 16-channel hand coil. Images were analyzed by three independent readers for the degree of inflammatory changes, thickness of flexor tendon pulleys, and comparison to the outcome measures for RA clinical trials (OMERACT) PsA MRI score (PsAMRIS) and to its sub-scores. For correlation analyses, Spearman rho correlation was calculated. Results Flexor tendon pulleys were thicker in PsA than in RA patients (mean difference 0.16 mm, p

In recent years, much research evaluating the radiographic destruction of finger joints in patients with rheumatoid arthritis (RA) using deep learning models was conducted. Unfortunately, most previous models were not clinically applicable due to the small object regions as well as the close spatial relationship. In recent years, a new network structure called RetinaNets, in combination with the focal loss function, proved reliable for detecting even small objects. Therefore, the study aimed to increase the recognition performance to a clinically valuable level by proposing an innovative approach with adaptive changes in intersection over union (IoU) values during training of Retina Networks using the focal loss error function. To this end, the erosion score was determined using the Sharp van der Heijde (SvH) metric on 300 conventional radiographs from 119 patients with RA. Subsequently, a standard RetinaNet with different IoU values as well as adaptively modified IoU values were trained and compared in terms of accuracy, mean average accuracy (mAP), and IoU. With the proposed approach of adaptive IoU values during training, erosion detection accuracy could be improved to 94% and an mAP of 0.81 ± 0.18. In contrast Retina networks with static IoU values achieved only an accuracy of 80% and an mAP of 0.43 ± 0.24. Thus, adaptive adjustment of IoU values during training is a simple and effective method to increase the recognition accuracy of small objects such as finger and wrist joints.

Currently, clinical indications for the application of gadolinium-based contrast agents (GBCA) in magnetic resonance imaging (MRI) are increasingly being questioned. Consequently, this study aimed to evaluate the additional diagnostic value of contrast enhancement in MRI of the hand in patients with rheumatoid arthritis (RA). Thirty-one patients with RA (mean age, 50 ± 14 years (range, 18–72 years)) underwent morphologic MRI scans on a clinical 3 T scanner. MRI studies were analyzed based on (1) the Rheumatoid Arthritis Magnetic Resonance Imaging Score (RAMRIS) and (2) the GBCA-free RAMRIS version, termed RAMRIS Sine-Gadolinium-For-Experts (RAMRIS-SAFE), in which synovitis and tenosynovitis were assessed using the short-tau inversion-recovery sequence instead of the post-contrast T1-weighted sequence. The synovitis subscores in terms of Spearman’s ρ, as based on RAMRIS and RAMRIS-SAFE, were almost perfect (ρ = 0.937; p < 0.001), while the tenosynovitis subscores were less strongly correlated (ρ = 0.380 p = 0.035). Correlation between the total RAMRIS and RAMRIS-SAFE was also almost perfect (ρ = 0.976; p < 0.001). Inter-rater reliability in terms of Cohen’s κ was high (0.963 ≤ κ ≤ 0.925). In conclusion, RAMRIS-SAFE as the GBCA-free version of the well-established RAMRIS is a patient-friendly and resource-efficient alternative for assessing disease-related joint changes in RA. As patients with RA are subject to repetitive GBCA applications, non-contrast imaging protocols should be considered.

T2 mapping assesses tissue ultrastructure and composition, yet the association of imaging features and tissue functionality is oftentimes unclear. This study aimed to elucidate this association for the posterior cruciate ligament (PCL) across the micro- and macroscale and as a function of loading. Ten human cadaveric knee joints were imaged using a clinical 3.0T scanner and high-resolution morphologic and T2 mapping sequences. Emulating the posterior drawer test, the joints were imaged in the unloaded (δ0) and loaded (δ1) configurations. For the entire PCL, its subregions, and its osseous insertion sites, loading-induced changes were parameterized as summary statistics and texture variables, i.e., entropy, homogeneity, contrast, and variance. Histology confirmed structural integrity. Statistical analysis was based on parametric and non-parametric tests. Mean PCL length (37.8 ± 1.8 mm [δ0]; 44.0 ± 1.6 mm [δ1] [p < 0.01]), mean T2 (35.5 ± 2.0 ms [δ0]; 37.9 ± 1.3 ms [δ1] [p = 0.01]), and mean contrast values (4.0 ± 0.6 [δ0]; 4.9 ± 0.9 [δ1] [p = 0.01]) increased significantly under loading. Other texture features or ligamentous, osseous, and meniscal structures remained unaltered. Beyond providing normative T2 values across various scales and configurations, this study suggests that ligaments can be imaged morphologically and functionally based on joint loading and advanced MRI acquisition and post-processing techniques to assess ligament integrity and functionality in variable diagnostic contexts.

While morphologic magnetic resonance imaging (MRI) is the imaging modality of choice for the evaluation of ligamentous wrist injuries, it is merely static and incapable of diagnosing dynamic wrist instability. Based on real-time MRI and algorithm-based image post-processing in terms of convolutional neural networks (CNNs), this study aims to develop and validate an automatic technique to quantify wrist movement. A total of 56 bilateral wrists (28 healthy volunteers) were imaged during continuous and alternating maximum ulnar and radial abduction. Following CNN-based automatic segmentations of carpal bone contours, scapholunate and lunotriquetral gap widths were quantified based on dedicated algorithms and as a function of wrist position. Automatic segmentations were in excellent agreement with manual reference segmentations performed by two radiologists as indicated by Dice similarity coefficients of 0.96 ± 0.02 and consistent and unskewed Bland–Altman plots. Clinical applicability of the framework was assessed in a patient with diagnosed scapholunate ligament injury. Considerable increases in scapholunate gap widths across the range-of-motion were found. In conclusion, the combination of real-time wrist MRI and the present framework provides a powerful diagnostic tool for dynamic assessment of wrist function and, if confirmed in clinical trials, dynamic carpal instability that may elude static assessment using clinical-standard imaging modalities.

Background: Traumatic cartilage injuries predispose articulating joints to focal cartilage defects and, eventually, posttraumatic osteoarthritis. Current clinical-standard imaging modalities such as morphologic MRI fail to reliably detect cartilage trauma and to monitor associated posttraumatic degenerative changes with oftentimes severe prognostic implications. Quantitative MRI techniques such as T2 mapping are promising in detecting and monitoring such changes yet lack sufficient validation in controlled basic research contexts. Material and Methods: 35 macroscopically intact cartilage samples obtained from total joint replacements were exposed to standardized injurious impaction with low (0.49 J, n = 14) or high (0.98 J, n = 14) energy levels and imaged before and immediately, 24 h, and 72 h after impaction by T2 mapping. Contrast, homogeneity, energy, and variance were quantified as features of texture on each T2 map. Unimpacted controls (n = 7) and histologic assessment served as reference. Results: As a function of impaction energy and time, absolute T2 values, contrast, and variance were significantly increased, while homogeneity and energy were significantly decreased. Conclusion: T2 mapping and texture feature analysis are sensitive diagnostic means to detect and monitor traumatic impaction injuries of cartilage and associated posttraumatic degenerative changes and may be used to assess cartilage after trauma to identify “cartilage at risk”.

Using glycosaminoglycan Chemical Exchange Saturation Transfer (gagCEST) magnetic resonance imaging (MRI), this study comparatively evaluated the GAG contents of lumbar intervertebral disks (IVDs) of patients with non-specific low back pain (nsLBP), radiculopathy, and asymptomatic volunteers to elucidate the association of clinical manifestation and compositional correlate. A total of 18 patients (mean age 57.5 ± 22.5 years) with radiculopathy, 16 age-matched patients with chronic nsLBP and 20 age-matched volunteers underwent standard morphologic and compositional gagCEST MRI on a 3T scanner. In all cohorts, GAG contents of lumbar IVDs were determined using gagCEST MRI. An assessment of morphologic IVD degeneration based on the Pfirrmann classification and T2-weighted sequences served as a reference. A linear mixed model adjusted for multiple confounders was used for statistical evaluation. IVDs of patients with nsLBP showed lower gagCEST values than those of volunteers (nsLBP: 1.3% [99% confidence intervals (CI): 1.0; 1.6] vs. volunteers: 1.9% [99% CI: 1.6; 2.2]). Yet, IVDs of patients with radiculopathy (1.8% [99% CI: 1.4; 2.1]) were not different from patients with nsLBP or volunteers. In patients with radiculopathy, IVDs directly adjacent to IVD extrusions demonstrated lower gagCEST values than distant IVDs (adjacent: 0.9% [99% CI: 0.3; 1.5], distant: 2.1% [99% CI: 1.7; 2.5]). Advanced GAG depletion in nsLBP and directly adjacent to IVD extrusions in radiculopathy indicates close interrelatedness of clinical pathology and compositional degeneration.