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Digital reference object toolkit of breast DCE MRI for quantitative evaluation of image reconstruction and analysis methods.
Bae, Jonghyun; Tan, Zhengguo; Solomon, Eddy; Huang, Zhengnan; Heacock, Laura; Moy, Linda; Knoll, Florian; Kim, Sungheon Gene.
Afiliación
  • Bae J; Vilcek Institute of Graduate Biomedical Science, New York University School of Medicine, New York, New York, USA.
  • Tan Z; Center for Biomedical Imaging, Radiology, New York University School of Medicine, New York, New York, USA.
  • Solomon E; Center for Advanced Imaging Innovation and Research, Radiology, New York University School of Medicine, New York, New York, USA.
  • Huang Z; Department of Radiology, Weill Cornell Medical College, New York, New York, USA.
  • Heacock L; Biomedical Engineering, Friedrich-Alexander-Universitat Erlangen-Nurnberg, Erlangen, Germany.
  • Moy L; Department of Radiology, Weill Cornell Medical College, New York, New York, USA.
  • Knoll F; Vilcek Institute of Graduate Biomedical Science, New York University School of Medicine, New York, New York, USA.
  • Kim SG; Center for Biomedical Imaging, Radiology, New York University School of Medicine, New York, New York, USA.
Magn Reson Med ; 92(4): 1728-1742, 2024 Oct.
Article en En | MEDLINE | ID: mdl-38775077
ABSTRACT

PURPOSE:

To develop a digital reference object (DRO) toolkit to generate realistic breast DCE-MRI data for quantitative assessment of image reconstruction and data analysis methods.

METHODS:

A simulation framework in a form of DRO toolkit has been developed using the ultrafast and conventional breast DCE-MRI data of 53 women with malignant (n = 25) or benign (n = 28) lesions. We segmented five anatomical regions and performed pharmacokinetic analysis to determine the ranges of pharmacokinetic parameters for each segmented region. A database of the segmentations and their pharmacokinetic parameters is included in the DRO toolkit that can generate a large number of realistic breast DCE-MRI data. We provide two potential examples for our DRO toolkit assessing the accuracy of an image reconstruction method using undersampled simulated radial k-space data and assessing the impact of the B 1 + $$ {\mathrm{B}}_1^{+} $$ field inhomogeneity on estimated parameters.

RESULTS:

The estimated pharmacokinetic parameters for each region showed agreement with previously reported values. For the assessment of the reconstruction method, it was found that the temporal regularization resulted in significant underestimation of estimated parameters by up to 57% and 10% with the weighting factor λ = 0.1 and 0.01, respectively. We also demonstrated that spatial discrepancy of v p $$ {v}_p $$ and PS $$ \mathrm{PS} $$ increase to about 33% and 51% without correction for B 1 + $$ {\mathrm{B}}_1^{+} $$ field.

CONCLUSION:

We have developed a DRO toolkit that includes realistic morphology of tumor lesions along with the expected pharmacokinetic parameter ranges. This simulation framework can generate many images for quantitative assessment of DCE-MRI reconstruction and analysis methods.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Procesamiento de Imagen Asistido por Computador / Mama / Neoplasias de la Mama / Imagen por Resonancia Magnética Límite: Adult / Female / Humans / Middle aged Idioma: En Revista: Magn Reson Med Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Procesamiento de Imagen Asistido por Computador / Mama / Neoplasias de la Mama / Imagen por Resonancia Magnética Límite: Adult / Female / Humans / Middle aged Idioma: En Revista: Magn Reson Med Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos