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Abstract Forthcoming

Multiparametric Classification of Skin from Osteogenesis Imperfecta Patients and Controls by Quantitative Magnetic Resonance Microimaging

<div><p>The purpose of this study is to evaluate the ability of quantitative magnetic resonance imaging (MRI) to discriminate between skin biopsies from individuals with osteogenesis imperfecta (OI) and skin biopsies from individuals without OI. Skin biopsies from nine controls (unaffected) and nine OI patients were imaged to generate maps of five separate MR parameters, T₁, T₂, k_m, MTR and ADC. Parameter values were calculated over the dermal region and used for univariate and multiparametric classification analysis. A substantial degree of overlap of individual MR parameters was observed between control and OI groups, which limited the sensitivity and specificity of univariate classification. Classification accuracies ranging between 39% and 67% were found depending on the variable of investigation, with T₂ yielding the best accuracy of 67%. When several MR parameters were considered simultaneously in a multivariate analysis, the classification accuracies improved up to 89% for specific combinations, including the combination of T₂ and k_m. These results indicate that multiparametric classification by quantitative MRI is able to detect differences between the skin of OI patients and of unaffected individuals, which motivates further study of quantitative MRI for the clinical diagnosis of OI.</p></div

OI and Control patient characteristics.

<p>OI and Control patient characteristics.</p

Support vector machine classification results for all MR parameter combinations.

<p>Support vector machine classification results for all MR parameter combinations.</p

Representative histology samples from a control (a) and OI (Type I) (b) biopsies.

<p>Arrows indicate distinct epidermal and dermal layers in both tissues.</p

T₂ parameter maps of control (a) and OI (b) skin samples.

<p>Regions of interest are outlined and labeled. The static magnetic field, B₀, is oriented vertically. Parameters for analysis were obtained by averaging over the entire dermal region.</p

Univariate classification results for the training and test sets using the Mahalanobis distance metric for each MR parameter.

<p>Univariate classification results for the training and test sets using the Mahalanobis distance metric for each MR parameter.</p

MRI Parameters Maps

MRI parameters maps from skin from control and OI patient

Average MR parameter values.

<p>Control subjects are represented as open squares and OI subjects are represented as shaded triangles with their corresponding group mean values. Error bars represented as solid squares and triangles, respectively, for A) MTR (control vs OI: p = 0.88), B) k_m (control vs OI: p = 0.32), C) T₂ (control vs OI: p = 0.01), D) T₁ (control vs OI: p = 0.38), E) ADC (control vs OI: p = 0.37). Note the high degree of overlap between groups for each parameter. Further, there is no trend for the OI values based on degree of severity for any MR parameter.</p