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Evaluation of Liver Fibrosis Using Texture Analysis on Combined-Contrast-Enhanced Magnetic Resonance Images at 3.0T
المؤلفون المشاركون
Peterson, Michael R.
Yokoo, Takeshi
Wolfson, Tanya
Iwaisako, Keiko
Goodman, Zachary
Changchien, Christopher
Middleton, Michael S.
Gamst, Anthony C.
Mazhar, Sameer M.
Kono, Yuko
Ho, Samuel B.
Sirlin, Claude B.
Mani, Haresh
المصدر
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-09-01
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
Purpose.
To noninvasively assess liver fibrosis using combined-contrast-enhanced (CCE) magnetic resonance imaging (MRI) and texture analysis.
Materials and Methods.
In this IRB-approved, HIPAA-compliant prospective study, 46 adults with newly diagnosed HCV infection and recent liver biopsy underwent CCE liver MRI following intravenous administration of superparamagnetic iron oxides (ferumoxides) and gadolinium DTPA (gadopentetate dimeglumine).
The image texture of the liver was quantified in regions-of-interest by calculating 165 texture features.
Liver biopsy specimens were stained with Masson trichrome and assessed qualitatively (METAVIR fibrosis score) and quantitatively (% collagen stained area).
Using L1 regularization path algorithm, two texture-based multivariate linear models were constructed, one for quantitative and the other for quantitative histology prediction.
The prediction performance of each model was assessed using receiver operating characteristics (ROC) and correlation analyses.
Results.
The texture-based predicted fibrosis score significantly correlated with qualitative (r=0.698, P<0.001) and quantitative (r=0.757, P<0.001) histology.
The prediction model for qualitative histology had 0.814–0.976 areas under the curve (AUC), 0.659–1.000 sensitivity, 0.778–0.930 specificity, and 0.674–0.935 accuracy, depending on the binary classification threshold.
The prediction model for quantitative histology had 0.742–0.950 AUC, 0.688–1.000 sensitivity, 0.679–0.857 specificity, and 0.696–0.848 accuracy, depending on the binary classification threshold.
Conclusion.
CCE MRI and texture analysis may permit noninvasive assessment of liver fibrosis.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Yokoo, Takeshi& Wolfson, Tanya& Iwaisako, Keiko& Peterson, Michael R.& Mani, Haresh& Goodman, Zachary…[et al.]. 2015. Evaluation of Liver Fibrosis Using Texture Analysis on Combined-Contrast-Enhanced Magnetic Resonance Images at 3.0T. BioMed Research International،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1055283
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Yokoo, Takeshi…[et al.]. Evaluation of Liver Fibrosis Using Texture Analysis on Combined-Contrast-Enhanced Magnetic Resonance Images at 3.0T. BioMed Research International No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1055283
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Yokoo, Takeshi& Wolfson, Tanya& Iwaisako, Keiko& Peterson, Michael R.& Mani, Haresh& Goodman, Zachary…[et al.]. Evaluation of Liver Fibrosis Using Texture Analysis on Combined-Contrast-Enhanced Magnetic Resonance Images at 3.0T. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1055283
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1055283
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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