Quantifying Heterogeneity in Dynamic Contrast-Enhanced MRI Parameter Maps

C. J. Rose; S. Mills; J O'Connor; G. A. Buonaccorsi; C. Roberts; Y. Watson; B. Whitcher; Gordon Jayson; Alan Jackson; G. J. M. Parker

doi:10.1007/978-3-540-75759-7_46

Quantifying Heterogeneity in Dynamic Contrast-Enhanced MRI Parameter Maps

C. J. Rose, S. Mills, J O'Connor, G. A. Buonaccorsi, C. Roberts, Y. Watson, B. Whitcher, Gordon Jayson, Alan Jackson, G. J. M. Parker

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Simple summary statistics of Dynamic Contrast-Enhanced MRI (DCE-MRI) parameter maps (e.g. the median) neglect the spatial arrangement of parameters, which appears to carry important diagnostic and prognostic information. This paper describes novel statistics that are sensitive to both parameter values and their spatial arrangement. Binary objects are created from 3-D DCE-MRI parameter maps by "extruding" each voxel into a fourth dimension; the extrusion distance is proportional to the voxel's value. The following statistics are then computed on these 4-D binary objects: surface area, volume, surface area to volume ratio, and box counting (fractal) dimension. An experiment using 4 low and 5 high grade gliomas showed significant differences between the two grades for box counting dimension computed for extruded v(e) maps, surface area of extruded K(trans) and v(e) maps and the volume of extruded v(e) maps (all p <0.05). An experiment using 18 liver metastases imaged before and after treatment with a vascular endothelial growth factor (VEGF) inhibitor showed significant differences for surface area to volume ratio computed for extruded K(trans) and v(e) maps (p = 0.0013 and p = 0.045 respectively).

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007
Publisher	Springer Nature
Pages	376-84
Number of pages	9
Volume	2
DOIs	https://doi.org/10.1007/978-3-540-75759-7_46
Publication status	Published - Oct 2007
Event	10th International Conference Medical Image Computing and Computer-Assisted Intervention : MICCAI 2007 - Brisbane, Australia Duration: 29 Oct 2007 → 2 Nov 2007

Publication series

Name	Lecture Notes in Computer Science
Number	4792

Conference

Conference	10th International Conference Medical Image Computing and Computer-Assisted Intervention
Country/Territory	Australia
City	Brisbane
Period	29/10/07 → 2/11/07

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10.1007/978-3-540-75759-7_46

Cite this

Rose, C. J., Mills, S., O'Connor, J., Buonaccorsi, G. A., Roberts, C., Watson, Y., Whitcher, B., Jayson, G., Jackson, A., & Parker, G. J. M. (2007). Quantifying Heterogeneity in Dynamic Contrast-Enhanced MRI Parameter Maps. In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007 (Vol. 2, pp. 376-84). (Lecture Notes in Computer Science; No. 4792). Springer Nature. https://doi.org/10.1007/978-3-540-75759-7_46

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title = "Quantifying Heterogeneity in Dynamic Contrast-Enhanced MRI Parameter Maps",

abstract = "Simple summary statistics of Dynamic Contrast-Enhanced MRI (DCE-MRI) parameter maps (e.g. the median) neglect the spatial arrangement of parameters, which appears to carry important diagnostic and prognostic information. This paper describes novel statistics that are sensitive to both parameter values and their spatial arrangement. Binary objects are created from 3-D DCE-MRI parameter maps by {"}extruding{"} each voxel into a fourth dimension; the extrusion distance is proportional to the voxel's value. The following statistics are then computed on these 4-D binary objects: surface area, volume, surface area to volume ratio, and box counting (fractal) dimension. An experiment using 4 low and 5 high grade gliomas showed significant differences between the two grades for box counting dimension computed for extruded v(e) maps, surface area of extruded K(trans) and v(e) maps and the volume of extruded v(e) maps (all p <0.05). An experiment using 18 liver metastases imaged before and after treatment with a vascular endothelial growth factor (VEGF) inhibitor showed significant differences for surface area to volume ratio computed for extruded K(trans) and v(e) maps (p = 0.0013 and p = 0.045 respectively).",

author = "Rose, {C. J.} and S. Mills and J O'Connor and Buonaccorsi, {G. A.} and C. Roberts and Y. Watson and B. Whitcher and Gordon Jayson and Alan Jackson and Parker, {G. J. M.}",

note = "Journal Article Germany MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention; 10th International Conference Medical Image Computing and Computer-Assisted Intervention : MICCAI 2007 ; Conference date: 29-10-2007 Through 02-11-2007",

year = "2007",

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doi = "10.1007/978-3-540-75759-7_46",

language = "English",

volume = "2",

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Rose, CJ, Mills, S, O'Connor, J, Buonaccorsi, GA, Roberts, C, Watson, Y, Whitcher, B, Jayson, G , Jackson, A & Parker, GJM 2007, Quantifying Heterogeneity in Dynamic Contrast-Enhanced MRI Parameter Maps. in Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007. vol. 2, Lecture Notes in Computer Science, no. 4792, Springer Nature, pp. 376-84, 10th International Conference Medical Image Computing and Computer-Assisted Intervention , Brisbane, Australia, 29/10/07. https://doi.org/10.1007/978-3-540-75759-7_46

Quantifying Heterogeneity in Dynamic Contrast-Enhanced MRI Parameter Maps. / Rose, C. J.; Mills, S.; O'Connor, J et al.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007. Vol. 2 Springer Nature, 2007. p. 376-84 (Lecture Notes in Computer Science; No. 4792).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Simple summary statistics of Dynamic Contrast-Enhanced MRI (DCE-MRI) parameter maps (e.g. the median) neglect the spatial arrangement of parameters, which appears to carry important diagnostic and prognostic information. This paper describes novel statistics that are sensitive to both parameter values and their spatial arrangement. Binary objects are created from 3-D DCE-MRI parameter maps by "extruding" each voxel into a fourth dimension; the extrusion distance is proportional to the voxel's value. The following statistics are then computed on these 4-D binary objects: surface area, volume, surface area to volume ratio, and box counting (fractal) dimension. An experiment using 4 low and 5 high grade gliomas showed significant differences between the two grades for box counting dimension computed for extruded v(e) maps, surface area of extruded K(trans) and v(e) maps and the volume of extruded v(e) maps (all p <0.05). An experiment using 18 liver metastases imaged before and after treatment with a vascular endothelial growth factor (VEGF) inhibitor showed significant differences for surface area to volume ratio computed for extruded K(trans) and v(e) maps (p = 0.0013 and p = 0.045 respectively).

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ER -

Quantifying Heterogeneity in Dynamic Contrast-Enhanced MRI Parameter Maps

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