Sensitivity and specificity of univariate MRI analysis of experimentally degraded cartilage under clinical imaging conditions

Abstract

Purpose To evaluate the sensitivity and specificity of classification of pathomimetically-degraded bovine nasal cartilage (BNC) at 3 T and 37°C using univariate MRI measurements of both pure parameter values and intensities of parameter-weighted images. Materials and Methods Pre- and post-trypsin degradation values of T1, T2, T2*, magnetization transfer ratio (MTR), and apparent diffusion coefficient (ADC), and corresponding weighted images, were analyzed. Classification based on the Euclidean distance was performed and the quality of classification was assessed through sensitivity, specificity and accuracy (ACC). Results The classifiers with the highest accuracy values were ADC (ACC = 0.82 ± 0.06), MTR (ACC = 0.78 ± 0.06), T1 (ACC = 0.99 ± 0.01), T2 derived from a 3D spin-echo sequence (ACC = 0.74 ± 0.05), and T2 derived from a 2D spin-echo sequence (ACC = 0.77 ± 0.06), along with two of the diffusion-weighted signal intensities (b = 333 s/mm2: ACC = 0.80 ± 0.05; b = 666 s/mm2: ACC = 0.85 ± 0.04). In particular, T1 values differed substantially between the groups, resulting in atypically high classification accuracy. The second-best classifier, diffusion weighting with b = 666 s/mm2, as well as all other parameters evaluated, exhibited substantial overlap between pre- and post-degradation groups, resulting in decreased accuracies. Conclusion Classification according to T1 values showed excellent test characteristics (ACC = 0.99), with several other parameters also showing reasonable performance (ACC > 0.70). Of these, diffusion weighting is particularly promising as a potentially practical clinical modality. As in previous work, we again find that highly statistically significant group mean differences do not necessarily translate into accurate clinical classification rules.

Classification of histologically scored human knee osteochondral plugs by quantitative analysis of magnetic resonance images at 3T

“…46 We have recently shown high classification accuracy when using T 1 to distinguish between normal and enzymatically degraded BNC at both preclinical (9.4 T) and clinical (3 T) field strengths, and under reduced (4˚C) and in vivo (37˚C) sample temperatures. 15,16 In spite of this high classification accuracy of T 1 observed at 3 T and 37˚C, T 1 W was one of the poorest classifiers in BNC, with an accuracy of 0.45. 16 These differences in classification results between experimental conditions underscore the importance of the current work which uses human articular cartilage, clinical field strength, and in vivo sample temperature.…”

“…14 Recently, we examined the classification accuracy of several quantitative MRI parameters in enzymatically degraded bovine nasal cartilage (BNC) -a model system for articular cartilage. 15,16 This work detailed a variety of approaches for building classification models and showed differences in the accuracy of several quantitative MRI parameters in classifying cartilage to either control or enzymatically-degraded groups. T 1 proved to be the most accurate MRI parameter at 9.4 T for discriminating between normal and severely degraded BNC, with sensitivity and specificity of 0.90 and 0.94, respectively.…”

“…15 In a recent study on the classification of normal and enzymatically degraded BNC at 3 T, T 1 showed comparable classification accuracy. 16 These previous studies utilized the Euclidian distance metric of classification, which assigns group membership of a sample based on the proximity of its parameter value to the group means. Other preliminary work performed using ultra-high field preclinical MRI has demonstrated the potential for MRI parameters to discriminate between various stages of OA using receiver operating characteristic (ROC) analysis.…”

“…17 Here, we extend our previous classification work to human osteochondral plugs to examine the diagnostic accuracy of several quantitative MRI measurements at clinical field strength and physiological body temperature. 15,16 Plugs were scored for OA severity using the Osteoarthritis Research Society International (OARSI) histological system, a gold standard for tissue characterization. 18 Classification models were constructed using the Mahalanobis distance metric, a variant of the Euclidean distance metric, which normalizes the distance between the sample parameter value and the group mean parameter value by the standard deviation of the group.…”

Multi‐parametric MRI characterization of enzymatically degraded articular cartilage

“…However, T 1 relaxation time had a very weak correlation with the bulk water content in these enzymatically treated specimens for bovine patella, in contrast to earlier study on non-treated cartilage specimens from different joint surfaces in the bovine knee. 4 T 1 relaxation time constant has been occasionally reported in cartilage MRI investigations and found sensitive to changes in cartilage, often with increased values due to disease or treatment, 5,55,56 but also with decreased values due to treatment 57 or to correlate with, for example mechanical properties or GAG content. 6,58 This may be due to the effect of different degrading medium on tissue proteins, hence, differently reflected in relaxation times…”