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Breast DCE-MRI Kinetic Heterogeneity Tumor Markers: Preliminary Associations With Neoadjuvant Chemotherapy Response.

Ashraf A, Gaonkar B, Mies C, DeMichele A, Rosen M, Davatzikos C, Kontos D - Transl Oncol (2015)

Bottom Line: We propose a set of kinetic statistic descriptors and present preliminary results showing the discriminatory capacity of the proposed descriptors for predicting complete and non-complete responders as assessed from pre-treatment imaging exams.We compare the predictive value of our features against commonly used MRI features including kinetics of the characteristic kinetic curve (CKC), maximum peak enhancement (MPE), hotspot signal enhancement ratio (SER), and longest tumor diameter that give lower AUCs of 0.71, 0.66, 0.64, and 0.54, respectively.Our proposed kinetic statistics thus outperform the conventional kinetic descriptors as well as the classifier using a combination of all the conventional descriptors (i.e., CKC, MPE, SER, and longest diameter), which gives an AUC of 0.74.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA. Electronic address: ahmed.bilal@alumni.cmu.edu.

No MeSH data available.


Related in: MedlinePlus

Illustration of kinetic pixel partitioning for two post-contrast time points. (A) Segmented lesion, (B) set 1 pixels that achieve peak enhancement at the first post-contrast time point (highlighted in yellow), and (C) set 2 pixels that achieve peak enhancement at the second post-contrast time point (highlighted in green).
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f0010: Illustration of kinetic pixel partitioning for two post-contrast time points. (A) Segmented lesion, (B) set 1 pixels that achieve peak enhancement at the first post-contrast time point (highlighted in yellow), and (C) set 2 pixels that achieve peak enhancement at the second post-contrast time point (highlighted in green).

Mentions: We extract these kinetic statistics in a two-phase process: In the first phase, the time to peak (TTP) for every pixel within the tumor is computed. We then cluster the pixels based on their TTP values. This step partitions the pixels into as many sets as the number of post-contrast time points, i.e., set i consists of pixels that achieve their peak enhancement at the ith post contrast time point. FigureĀ 2 illustrates these partitions for a sample case.


Breast DCE-MRI Kinetic Heterogeneity Tumor Markers: Preliminary Associations With Neoadjuvant Chemotherapy Response.

Ashraf A, Gaonkar B, Mies C, DeMichele A, Rosen M, Davatzikos C, Kontos D - Transl Oncol (2015)

Illustration of kinetic pixel partitioning for two post-contrast time points. (A) Segmented lesion, (B) set 1 pixels that achieve peak enhancement at the first post-contrast time point (highlighted in yellow), and (C) set 2 pixels that achieve peak enhancement at the second post-contrast time point (highlighted in green).
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4487265&req=5

f0010: Illustration of kinetic pixel partitioning for two post-contrast time points. (A) Segmented lesion, (B) set 1 pixels that achieve peak enhancement at the first post-contrast time point (highlighted in yellow), and (C) set 2 pixels that achieve peak enhancement at the second post-contrast time point (highlighted in green).
Mentions: We extract these kinetic statistics in a two-phase process: In the first phase, the time to peak (TTP) for every pixel within the tumor is computed. We then cluster the pixels based on their TTP values. This step partitions the pixels into as many sets as the number of post-contrast time points, i.e., set i consists of pixels that achieve their peak enhancement at the ith post contrast time point. FigureĀ 2 illustrates these partitions for a sample case.

Bottom Line: We propose a set of kinetic statistic descriptors and present preliminary results showing the discriminatory capacity of the proposed descriptors for predicting complete and non-complete responders as assessed from pre-treatment imaging exams.We compare the predictive value of our features against commonly used MRI features including kinetics of the characteristic kinetic curve (CKC), maximum peak enhancement (MPE), hotspot signal enhancement ratio (SER), and longest tumor diameter that give lower AUCs of 0.71, 0.66, 0.64, and 0.54, respectively.Our proposed kinetic statistics thus outperform the conventional kinetic descriptors as well as the classifier using a combination of all the conventional descriptors (i.e., CKC, MPE, SER, and longest diameter), which gives an AUC of 0.74.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA. Electronic address: ahmed.bilal@alumni.cmu.edu.

No MeSH data available.


Related in: MedlinePlus