Evaluation of cartilaginous endplate degeneration with histogram features of multiple parameters in UTE MRI

The cartilaginous endplate (CEP) exhibits an intrinsically short [Formula: see text] relaxation time, making it difficult to visualize using conventional MRI sequences. This limitation hampers early detection and quantitative evaluation of lumbar spine degeneration. This study aimed to perceive microstructural alterations of CEP at early stages of degeneration using a bi-exponential [Formula: see text] model based on ultrashort echo time (UTE) sequence, and to explore the diagnostic utility of bi-exponential [Formula: see text]-derived parameters and monoexponential UTE-[Formula: see text] mapping values in grading CEP damage.         METHODS: This study retrospectively collected 46 patients who underwent lumbar UTE MRI, of whom 43 met the inclusion criteria. CEP was graded into three groups according to morphological features on multiple MRI sequences: healthy (structurally intact), mild damage (localized thinning or concavity with preserved continuity), and moderately damage (defects < 50% with disrupted continuity). Multiple quantities were evaluated using the UTE sequence on the CEP manually drawn by an experienced radiologist. One-way Kruskal-Wallis test was used to inspect the distribution differences among groups. Logistic regression and support vector machine models were applied to predict the level of degeneration with a considerably good precision, and receiver operating characteristic curves suggests a distinguishable performance among those models.

[Formula: see text] values showed significant differences among the groups (p < 0.05), with Tukey's test indicating the most significant difference between the moderately damaged group and the healthy controls. [Formula: see text] values were non-normally distributed but statistically different between the moderate and mild damage groups (p < 0.05), a trend also observed in monoexponential UTE-[Formula: see text] mapping values (p < 0.05). The logistic regression and SVM models performed well in identifying moderate damage (AUC of 0.878 and 0.858, respectively), but had limited ability to detect mild damage (AUC of 0.718 and 0.729).       CONCLUSION: The UTE bi-exponential [Formula: see text] model enable effective separation and quantification of distinct water components within the CEP. Both [Formula: see text] and UTE-[Formula: see text] mapping show promise as imaging biomarkers for grading CEP degeneration even in the early stage of CEP degeneration.