Texture analysis of placental MRI: can it aid in the prenatal diagnosis of placenta accreta spectrum?
Abdom Radiol (NY)
; 44(9): 3175-3184, 2019 09.
Article
em En
| MEDLINE
| ID: mdl-31240328
PURPOSE: To determine if texture analysis can differentiate placenta accreta spectrum (PAS) from normal placenta on MRI. METHODS: We performed retrospective image analysis of 80 patients, comprised of 46 patients with PAS and 34 patients without PAS. Histopathology was used as the reference standard. Sagittal single shot fast spin echo T2-weighted MRI sequences acquired from a single institution were analyzed. Placental heterogeneity was quantified using in-house software on a Matlab platform, including the standard deviation of pixel intensity, coefficient of variation, gray-level co-occurrence matrices (GLCM), histogram-oriented gradients (HOG), and fractal analysis with box sizes from 2 to 512. Two-tailed unpaired Student's t test was used with statistical significance of p < 0.05. RESULTS: PAS was associated with higher values for standard deviation of pixel intensity and fractal analysis at every box size. Fractal analysis at box sizes 256 (p = 0.011) and 32 (p = 0.021), and standard deviation of pixel intensity (p = 0.023) were the most statistically significant. Fractal values at box size 256 for PAS was 0.13 versus 0.090 for patients without PAS, while standard deviation of pixel intensity was 3.7 for PAS versus 2.5 for patients without PAS. No statistically significant association between PAS and GLCM, coefficient of variation, and HOG was found. CONCLUSION: Statistically significant differences were found between normal and abnormal groups using standard deviation of pixel intensity and fractal analysis.
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Base de dados:
MEDLINE
Assunto principal:
Placenta Acreta
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Diagnóstico Pré-Natal
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Imageamento por Ressonância Magnética
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Interpretação de Imagem Assistida por Computador
Tipo de estudo:
Diagnostic_studies
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Observational_studies
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Risk_factors_studies
Limite:
Adult
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Female
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Humans
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Middle aged
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Pregnancy
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article