15 february partial volume correction for liver metastases and lymph nodes1institute for medical...
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15 FebruaryPartial volume correction for liver metastases and lymph nodes
1Institute for Medical Image Computing /16SPIE 2010
Partial volume correction for volume estimation
of liver metastases and lymph nodes in CT scans
using spatial subdivisionFrank Heckel1, Volker Dicken1, Tilman Bostel2,
Michael Fabel3, Andreas Kießling4, Heinz-Otto Peitgen1
1 Fraunhofer MEVIS, Institute for Medical Image Computing, Bremen, Germany2 Johannes Gutenberg University, Clinic and Out-patients’ Clinic for Diagnostic and Interventional Radiology, Mainz, Germany3 Christian-Albrechts-University, Department of Diagnostic Radiology, Kiel, Germany4 Philipps-University, Department of Diagnostic Radiology, Marburg, Germany
15 FebruaryPartial volume correction for liver metastases and lymph nodes
2Institute for Medical Image Computing /16SPIE 2010
Overview
› Motivation
› Basic Idea
› Algorithm
› Evaluation
› Open Problems
› Conclusion
› Outlook
Motivation | Basic Idea | Algorithm | Evaluation | Open Problems | Conclusion | Outlook
15 FebruaryPartial volume correction for liver metastases and lymph nodes
3Institute for Medical Image Computing /16SPIE 2010
Motivation
› Clinical application: Oncological therapy monitoring» Assessment of tumor growth from consecutive CT scans» RECIST 1.11: Sum of maximum diameters (clinical standard)
» Volume is more reliable2
- Unfortunately: Progress / Response clinically not yet defined- Segmentation needed
Motivation | Basic Idea | Algorithm | Evaluation | Open Problems | Conclusion | Outlook
+ 20% Progressive disease
- 30% Partial response
1 Eisenhauer, E., Therasse, P., Bogaerts, J., Schwartz, L., Sargent, D., Ford, R., Dancey, J., Arbuck, S., Gwyther, S., Mooney, M., Rubinstein, L., Shankar, L., Dodd, L., Kaplan, R., Lacombe, D., and Verweij, J.,“New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1),” European journal of cancer 45, 228–247 (2009)
2 Bornemann, L., Dicken, V., Kuhnigk, J.-M., Wormanns, D., Shin, H.-O., Bauknecht, H.-C., Diehl, V., Fabel, M., Meier, S., Kress, O., Krass, S., and Peitgen, H.-O., “OncoTREAT: a software assistant for cancer therapy monitoring,” International Journal of Computer Assisted Radiology and Surgery 1(5), 231–242 (2007)
15 FebruaryPartial volume correction for liver metastases and lymph nodes
4Institute for Medical Image Computing /16SPIE 2010
Motivation
› Border of tumor not clear
Motivation | Basic Idea | Algorithm | Evaluation | Open Problems | Conclusion | Outlook
Partial volume effect:One voxel represents two or more
tissues because of limited spatial resolution of
CT
Liver tissue
Tumor + Liver tissue(partial-volume-voxels)
Tumor
15 FebruaryPartial volume correction for liver metastases and lymph nodes
5Institute for Medical Image Computing /16SPIE 2010
Motivation
› Border of tumor not clear Threshold for segmentation not clear» Different segmentations by different readers / in different scans» Significant difference in volume
Motivation | Basic Idea | Algorithm | Evaluation | Open Problems | Conclusion | Outlook
56.61ml (-20%) 70.8ml 86.46ml (+22.1%)
eroded initial dilated
15 FebruaryPartial volume correction for liver metastases and lymph nodes
6Institute for Medical Image Computing /16SPIE 2010
Basic Idea
› Weight each partial-volume-voxels based on its value and the values of its influencing tissues and calculate volume by the weighted sum of all voxels
› Challenge: Typically different types of tissue outside the lesion
› Assumptions: » Lesion is ellipsoidal and compact» Partial volume voxels are a
mixture of 2 tissues
Consider partial volume effectwhen calculating the tumor’s volume
1.0
0.75
0.5
0.25
0.0
Motivation | Basic Idea | Algorithm | Evaluation | Open Problems | Conclusion | Outlook
15 FebruaryPartial volume correction for liver metastases and lymph nodes
7Institute for Medical Image Computing /16SPIE 2010
Algorithm
› Definition of 5 parts» Calculated by successive erosion / dilation
› Spatial subdivision of the lesion into 3D equiangular parts» To cover different tissues (inside and outside of the lesion)
Motivation | Basic Idea | Algorithm | Evaluation | Open Problems | Conclusion | Outlook
Segmentation
Inner partial volume area
Outer partial volume area
Inner tissue area
Outer tissue area
Lesion core
15 FebruaryPartial volume correction for liver metastases and lymph nodes
8Institute for Medical Image Computing /16SPIE 2010
Algorithm
Motivation | Basic Idea | Algorithm | Evaluation | Open Problems | Conclusion | Outlook
› Calculate weight w for each voxel
› Core and inner tissue w = 1
› Outer tissue w = 0
› For each segment of the subdivision» Calculate the weight w of each partial volume
voxel as a linear combination of:- The value of the partial volume voxel- The average outer tissue value- The average inner tissue value
» w is clamped to [0,1]
15 FebruaryPartial volume correction for liver metastases and lymph nodes
9Institute for Medical Image Computing /16SPIE 2010
Algorithm
› Volume is given by weighted sum of the volume of each voxel in partial volume areas, tissue areas and lesion core
› Calculation time: 2s
› Result:
Motivation | Basic Idea | Algorithm | Evaluation | Open Problems | Conclusion | Outlook
64.57ml (-12.8%) 74.06ml 83.18ml (+12.3%)
1.0
0.75
0.5
0.25
0.056.61ml (-20%) 70.8ml 86.46ml (+22.1%)voxel-
count:corrected:
eroded initial dilated
15 FebruaryPartial volume correction for liver metastases and lymph nodes
10Institute for Medical Image Computing /16SPIE 2010
Algorithm
› Special cases: » Average outer partial volume value similar to average outer tissue
value w = 0 (assumption: intended by user)
» Lesion too small- Not enough voxels in inner tissue- Use average lesion core value instead
» Inner and outer tissue do not represent tissues of partial volume voxels (w << 0 or w >> 1)
- Use distance to inner tissue instead
Motivation | Basic Idea | Algorithm | Evaluation | Open Problems | Conclusion | Outlook
15 FebruaryPartial volume correction for liver metastases and lymph nodes
11Institute for Medical Image Computing /16SPIE 2010
-30
-20
-10
0
10
20
30
40
50
Voxel-Count
Rela
tive
diff
ere
nce
to r
eal v
olu
me in
%
1mm
B30
1mm
B40
2mm
B30
2mm
B40
3mm
B30
3mm
B40
4mm
B30
4mm
B40
5mm
B30
5mm
B40
Evaluation
› Phantom:» 31 lesions (liver metastases, lymph nodes)» More accurate estimation of the volume:
Motivation | Basic Idea | Algorithm | Evaluation | Open Problems | Conclusion | Outlook
Average difference
to real volume in %
Standard deviation in %
15 FebruaryPartial volume correction for liver metastases and lymph nodes
12Institute for Medical Image Computing /16SPIE 2010
-30
-20
-10
0
10
20
30
40
50
Voxel-CountCorrected
Rela
tive
diff
ere
nce
betw
een
readers
in %
Evaluation
› Multi-reader:» 132 liver metastases (no rim-enhancing), 2 readers» Significant reduction of inter-observer variability:
Motivation | Basic Idea | Algorithm | Evaluation | Open Problems | Conclusion | Outlook
3.68ml 4.29ml
4.03ml 4.08ml
= +16.9%= +1.12%
voxel-count:correcte
d:
Reader 2Reader 1
15 FebruaryPartial volume correction for liver metastases and lymph nodes
13Institute for Medical Image Computing /16SPIE 2010
Open Problems
› Rim-enhancing lesions» Rim is not always correctly covered
by the inner tissue area
› Separated “islands” might begenerated» Because only a voxel’s value is used
for calculation, not its position
› Subdivision segments might includedifferent tissue classes
› Calculated volume is inconsistentwith the visible segmentation result
Motivation | Basic Idea | Algorithm | Evaluation | Open Problems | Conclusion | Outlook
15 FebruaryPartial volume correction for liver metastases and lymph nodes
14Institute for Medical Image Computing /16SPIE 2010
Conclusion
› Algorithm:» Considers different tissues around a lesion» Fast» Not restricted to liver metastases and lymph nodes
› Result of evaluations:» More accurate volume estimation» Significant reduction of inter-observer-variability
Motivation | Basic Idea | Algorithm | Evaluation | Open Problems | Conclusion | Outlook
More robust, reliable and reproducible volume quantificationeven for complex lesions
15 FebruaryPartial volume correction for liver metastases and lymph nodes
15Institute for Medical Image Computing /16SPIE 2010
Outlook
› Investigate 5mm phantom results
› Improve subdivision so each segment covers exactly one tissue-class
› Adaptive calculation of the size of partial volume and the tissue areas, to cover rim-enhancing lesions correctly
› Solve “island” issue
› Further evaluations
Motivation | Basic Idea | Algorithm | Evaluation | Open Problems | Conclusion | Outlook
15 FebruaryPartial volume correction for liver metastases and lymph nodes
16Institute for Medical Image Computing /16SPIE 2010
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