TWO REVIEW ARTICLES PUBLISHED ON CARTILAGE IMAGING (NRR) & CARTILAGE T2 (PPExMed)

We are overly happy that our review on: “Advances in Cartilage Imaging Techniques”, including Felix Eckstein and Wolfgang Wirth as authors, has just been published in Nature Reviews Rheumatology (NRR) https://pubmed.ncbi.nlm.nih.gov/41634466/.

This poly-author article covers the following areas: Introduction – MRI technique – semiquantitative MRI – cartilage assessment – cartilage morphometry – high field (3 & 7T) vs. 1.5T – compositional MRI – CT – PET – ultrasound – AI – clinical & research application – conclusions

NRR is the most influential journal in the field (top of rheumatology, IF >32.7) and widely read by decision-makers in academia & pharma/biotech. The article provides a comprehensive overview of the current status of cartilage imaging, explaining why it is central to clinical trials, biomarker development, and disease-modifying drug (DMOAD) programs.

MRI currently still represents the reference standard in cartilage imaging, offering detailed evaluation of cartilage morphology (e.g. thickness) and matrix composition. Quantitative morphometry enables highly precise and sensitive analysis of changes over time, making it most relevant for longitudinal studies and clinical trials. Compositional MRI (e.g. T2, T1ρ, dGEMRIC, sodium, diffusion & UTE), in contrast, aim at detecting early matrix alterations prior to morphological damage. Such approaches aid in developing imaging biomarkers for early disease detection, patient stratification, and prognosis

An overarching theme is AI, used to accelerate MRI acquisition, improve image quality, enable automated cartilage segmentation, and support scalable, high-throughput analysis. These applications are critical enablers for large, multi-centre trials, for consistent data acquisition across sites, magnets and vendors, in epidemiology and therapeutic monitoring.

In summary, robust and sensitive imaging biomarkers are no longer optional. They are essential for efficient trial design, earlier signal detection, reduced development risk, and regulatory-grade evidence, to support decision-making across the drug development pipeline. With DMOADS becoming available eventually, they will play an increasing role in the clinic and in personalized management of cartilage pathology.

In a further review article by Felix Eckstein, Neal Bangerter (Univ. of Boise, USA) and Wolfgang Wirth (Paracelsus Proceedings of Experimental Medicine [PPExMed]) we are summarizing our recent work on the analysis of cartilage transverse relaxation time (T2), with a focus on the qDESS MRI sequence and on fully automated segmentation & analysis by AI- (convolutional neural network-) based algorithms. http://ppexmed.com/articles/000642.html.

T2 is thought to be a measure of cartilage matrix composition that reflects hydration and collagen content & orientation. It has been related to cartilage pathology, mechanical properties, and clinical stages of osteoarthritis and has hence been considered as “non-invasive histology” and an early disease marker, with changes preceding morphological cartilage lesions and tissue loss.

The selfie review is a special format by which published data are not synthesized horizontally and broadly across the research field, but integration is performed vertically, entailing a historical perspective. The main focus is on work by one research group that pursued a continuous strategy. This review picks up our first steps in quantifying laminar (deep and superficial) cartilage T2 using multi-echo-spin-echo (MESE) MRI and manual segmentation to our current approach that relies on a more efficient qDESS and fully automated analysis. The paper tells a story on findings, funding, papers and abstracts published over the past 15 years on cartilage T2, with a perspective on where the field may move in the future.