TY - JOUR
T1 - Multiparametric classification of skin from osteogenesis imperfecta patients and controls by quantitative magnetic resonance microimaging
AU - Ashinsky, Beth G.
AU - Fishbein, Kenneth W.
AU - Carter, Erin M.
AU - Lin, Ping Chang
AU - Pleshko, Nancy
AU - Raggio, Cathleen L.
AU - Spencer, Richard G.
N1 - Funding Information:
The authors would like to thank Stephen Doty and the Analytical Microscopy Laboratory at the Hospital for Special Surgery for providing the histological data. Support for this study was provided by The Pediatric Society of North America and the National Institutes of Health, National Institute on Aging, Intramural Research Program.
Publisher Copyright:
© This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
PY - 2016/7
Y1 - 2016/7
N2 - 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 ,km , 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 km . 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.
AB - 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 ,km , 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 km . 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.
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U2 - 10.1371/journal.pone.0157891
DO - 10.1371/journal.pone.0157891
M3 - Article
C2 - 27416032
AN - SCOPUS:84978767486
SN - 1932-6203
VL - 11
JO - PloS one
JF - PloS one
IS - 7
M1 - e0157891
ER -