Pavol Szomolanyi

Objective: To assess the relationship between textural features derived from quantitative MRI (T ₂ mapping) and histological signs of cartilage degeneration. Design: Ten fresh non-frozen knees from body donors were measured at 7T and 3T scanners using 3D-Double Echo Steady State (3D-DESS) as well as 3D-Triple Echo Steady State (3D-TESS) sequence. The 3D-DESS images were automatically segmented and co-registered with T ₂ maps at both field strengths. Nine osteochondral plugs were harvested from standardized regions of the distal femur of each knee. The histological workup included Safranin O and picrosirius red staining. Mankin scoring was performed for each plug. Collagen orientation and parallelism were assessed and quantified based on polarized light microscopy. Each plug was segmented on the 3D model derived from 3D-DESS image and texture analysis was performed on the co-registered T ₂ map. Relationships between T ₂ relaxation time, textural features and the Mankin score, as well as collagen orientation and parallelism, were assessed using partial Spearman’s correlation coefficients and mixed models. Results: Mean T ₂ and six features (autocorrelation, contrast, correlation, entropy, sum entropy and inverse difference moment normalized) correlated with the MS; autocorrelation, contrast and entropy were also found to be correlated with collagen orientation. No features were significantly correlated with parallelism. Statistical models showed no significant effect of sequence or field strength in predicting Mankin score. Conclusions: The presented ex-vivo approach enables a semi-automated assessment of articular cartilage quality that correlates with histological measures of degeneration. Additional studies are warranted to further investigate the reproducibility and validity of the measurements.

Magnetic resonance imaging (MRI) is one of the most important imaging modalities in clinical diagnostics and biomedical research; however, its usability is significantly limited by the high technical and methodological variability across sites, scanners, and acquisition protocols. This lack of uniformity affects quantitative measurements, reduces their reproducibility, and complicates multicenter studies. In recent years, numerous initiatives and technical approaches have emerged, focusing on acquisition standardization, data harmonization, signal quality assessment, and validation of quantitative methods. This review summarizes current knowledge on neuroimaging data harmonization (e.g., ComBat), inter-scanner variability, radiomic feature repeatability, standardized QA procedures, and the challenges associated with integrating artificial intelligence into clinical workflows. Metrological frameworks such as the Quantitative Imaging Biomarker Alliance (QIBA) further emphasize the need for clearly defined measurands, reference methods, and reproducible acquisition conditions. Special attention is given to large dataset initiatives, preclinical standardization platforms, and open tools for MRI quality assessment. The review highlights the need for unified methodologies, transparent protocols, and robust validation frameworks that are essential for the reliable clinical translatability of MRI.

Background/Objectives: To test whether routine T1-weighted spin-echo (T1-SE) and proton-density fast spin-echo (PD-FSE) MRI signal intensity (SI) can index bone regeneration after osteochondral scaffold implantation by correlating MRI metrics with micro-CT and histology. Methods: Twenty-eight sheep with bilateral trochlear defects were evaluated in separate cohorts at 30, 180, and 365 days (n = 7, 11, and 10, respectively). One knee received a tri-layered resorbable scaffold; the contralateral defect was left empty. MRI (T1-SE, PD-FSE) was read by two blinded musculoskeletal radiologists using 10-point Likert scales (T1: apparent mineralization; PD: SI normalization). Contrast-to-noise ratio (CNR) between repair-bone and reference bone was computed. MRI measures were correlated with micro-CT (new bone volume; trabecular bone volume) and histology (ICRS subchondral bone reconstruction; new bone; filling). Results: Likert ratings on both T1-SE and PD-FSE correlated with micro-CT new bone volume and trabecular bone volume and with histological measures of repair. PD-FSE CNR was inversely associated with micro-CT new bone volume and trabecular bone volume (both p < 0.001), indicating lower CNR with greater bone regeneration, whereas T1-SE CNR showed no significant associations. Inter-reader agreement was excellent (ICC 0.947 individual; 0.973 average), with good-to-excellent intra-reader reliability (0.920–0.963). Conclusions: Reader-based Likert assessment on both sequences and PD-FSE CNR provide complementary, non-invasive markers of subchondral bone regeneration, supporting MRI for radiation-free follow-up and endpoint selection in future translational studies. T1-SE CNR did not track incremental mineralization and should not be used as a stand-alone quantitative marker in early healing.

A common problem since the early development of MRI systems, which persists to this day, is the induction of eddy currents (EC) in the conductive parts of the MR scanner during the rise and decay of gradient pulses. The magnitude of the eddy currents, among other factors, is proportional to the magnitude of the gradient pulses and the magnitude of change in the gradient field over time. These eddy currents cause several problems, ranging from heating of the cryostat to undesirable time-varying gradient fields that produce various artefacts in the acquired images or undesirable effects on tissue structures in patients. There are several ways to suppress the eddy current effect. In this article, we focus on eddy current compensation by modulating gradient pre-emphasis.

Objectives: Cartilage repair (CR) surgery and anterior cruciate ligament reconstruction (ACL-R) are common joint procedures, particularly in younger patients. However, the impact of prior or concurrent ACL-R on the outcomes of CR remains uncertain. This study aimed to evaluate whether ACL-R affects the structural quality and clinical outcomes of CR tissue. Methods: In this retrospective multicenter study, 71 patients undergoing CR were followed up with magnetic resonance imaging (MRI) and clinical evaluations at 3, 12, and 60 months. Of these, 22 patients underwent ACL-R before or during CR. Morphological assessment was performed using Magnetic Resonance Observation of Cartilage Repair Tissue (MOCART) 2.0 scores; compositional analysis included T2 mapping ( n = 45). Patient-reported outcome measures (PROM) were assessed at all time points. Statistical tests included the Mann–Whitney U -test, Wilcoxon signed-rank test, and simulation-based power analysis. Results: MOCART 2.0 scores and T2 mapping values showed no significant group differences at any time point. Both groups demonstrated significant improvements in PROMs from baseline to 60 months. However, at 60 months, the ACL-R group had significantly lower PROMs than the non-ACL-R group. Conclusion: Although long-term clinical outcomes were worse in patients with ACL-R, all PROMs improved significantly from baseline to 60 months in both groups. MRI showed no significant differences in focal CR tissue quality, suggesting structural success regardless of ACL-R. While ACL-R patients remain at higher risk of joint degeneration, they can still experience mid-term clinical benefit from CR. These findings support its use in ACL-R patients when joint function is properly restored and expectations are managed.

Objectives: This study aimed to assess the impact of intralesional bony overgrowth (ILBO) after cartilage repair on the integrity of opposing articulating cartilage (OpAC) using T2 mapping and to correlate these findings with clinical outcomes. Methods: In this multicenter study, magnetic resonance imaging (MRI) examinations were performed in the follow-up after cartilage repair (Microfracturing (MFX) and Matrix-Induced Autologous Chondrocyte Implantation (MACI)) in 45 patients up to 5 years after surgery. T2 values of the OpAC after 3, 12, and 60 months in patients with and without ILBO after 60 months were conducted along with clinical assessments (International Knee Documentation Committee (IKDC) and Knee injury and Osteoarthritis Outcome Score (KOOS)). Results: At 60 months post-surgery, 44.4% of patients presented with ILBO, which was associated with significantly higher T2 values in OpAC ( P = 0.004). A tendency toward increased T2 values was observed after 12 months, although this did not reach statistical significance ( P = 0.06). However, no significant differences were found in clinical outcomes between patients with or without ILBO, nor between those with or without T2 values comparable to reference cartilage. Conclusion: ILBO significantly affects the biophysical MRI properties of OpAC as indicated by higher T2 values after 60 months. These alterations, though not reflected in any clinical score, can suggest potential long-term implications for cartilage degeneration and may inform future monitoring strategies for cartilage repair. Further research is required to evaluate the long-term effects of these altered mechanical impacts on articulating cartilage and their clinical implications.

Objective: The objective of this study was to assess the maturation of matrix-associated autologous chondrocyte transplantation (MACT) grafts up to 2 years after the surgery using gray-level co-occurrence matrix (GLCM) texture analysis of quantitative T ₂ maps, compare the results with the microfracturing technique (MFX) control group, and relate these results to the morphological MOCART 2.0 score. Design: A subcohort of 37 patients from prospective, multi-center study underwent examination on a 3T MR scanner, including a T ₂ mapping sequence at 3, 12, and 24 months after surgery. Changes between the time-points in the mean T ₂ values and 20 GLCM features extracted from T ₂ maps were assessed in repair tissue, tissue adjacent to the repair site, and the reference cartilage for both procedures. Results: Significant correlations were found between the MOCART 2.0 and GLCM features for both surgical procedures. There were no significant differences between MACT and MFX. We identified significant intra-group changes in T ₂ and autocorrelation (3M-12M: P = 0.002; 3M-24M: P = 0.004), dissimilarity (3M-24M: P = 0.01), homogeneity (3M-24M: P = 0.013), and correlation (3M-24M: P = 0.036), sum average (3M-12M: P = 0.001; 3M-24M: P = 0.002), and information measure (3M-24M: P < 0.001) in the MACT repair tissue. MACT models revealed differences in GLCM between all combinations of ROI types at almost all time-points. In the case of MFX, the significant differences were mainly between repair and reference tissue at 12 months. Conclusion: Texture analysis provides a useful extension to T ₂ mapping. Texture features are correlated to the morphological outcome and reveal differences in the process of maturation between MACT and MFX.