Detection of cardiovascular disease with MRI myocardial
texture changes on routine non-contrast sequences
Poster No.:
B-1372
Congress:
ECR 2017
Type:
Scientific Paper
Authors:
P. Talarczyk, J. R. Weir-McCall, S. A. Waugh, P. Guntur
Ramkumar, G. Houston; Dundee/UK
Keywords:
Cardiac, MR, Computer Applications-Detection, diagnosis,
Ischemia / Infarction
DOI:
10.1594/ecr2017/B-1372
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Page 1 of 11
Purpose
Cardiac Magnetic Resonance (MR) is an increasingly used technique due to its versatility,
non-invasiveness and lack of ionising radiation. The majority of image analysis is
currently performed by visual inspection of the anatomical structures which is constrained
by the limitations of the human eye.
Texture analysis is based on mathematical parameters representing structure of the
tissue and is sensitive to very subtle differences in voxel grey levels [1] Texture analysis
uses images obtained in routine diagnostic practice and is an interesting field of research,
particularly well explored in cancer imaging. Tumour heterogeneity has been proven to
provide prognostic and diagnostic information on malignant tumours. [2-4] A recent study
performed in our centre has shown that texture analysis can even be used to distinguish
histological subtypes of breast cancer. [5] To date no study has focused on diseaserelated changes to myocardial MR texture.
The purpose of this study is to investigate whether patients with diabetes and
cardiovascular disease have more heterogeneous myocardium on MR than those
without.
Methods and materials
Demographics
This study was a single centre observational sub-study of the SUMMIT study (multicentre
SUrrogate markers for Micro- and Macrovascular hard endpoints for Innovative diabetes
Tools). 143 volunteers were enrolled and divided into 4 groups:
•
•
•
•
Group 1: type 2 diabetes mellitus (T2DM) with a clinical diagnosis of
cardiovascular disease (CVD) that included coronary artery disease (CAD),
cerebrovascular disease and/or lower extremity arterial disease (LEAD)
Group 2: T2DM with no clinical evidence of cardiovascular disease
Group 3: absence of diabetes mellitus with clinical evidence of CVD
Group 4: healthy controls, with no biochemical evidence of diabetes mellitus
and no clinical evidence of CVD.
Disease
Number
Male
Age
BMI
Page 2 of 11
Group 1
T2DM &
CVD
31
76%
65 ± 7
31 ± 4
Group 2
T2DM, No
CVD
55
56%
63 ± 8
30 ± 6
Group 3
CVD
28
73%
67 ± 9
29 ± 4
Group 4
Healthy
29
41%
62 ± 8
volunteers
Table 1: Demographics of study participants divided into 4 groups
28 ± 4
Equipment:
•
•
3T MR (Siemens Tim Trio, Germany)
Gadoteric acid (Guerbet, France)
Image Acquisition:
Image analysis was performed on pre-contrast balanced steady-state free precession
images. These were obtained in the short axis mid-ventricular slice at end systole. Region
of interest was drawn in the interventricular septum to reduce effects of artefacts.
Page 3 of 11
Fig. 1: Region of interest in the interventricular septum on mid-ventricular slice of the
heart at end-systole
References: Radiology, NHS Tayside - Dundee/UK
Texture analysis:
Texture features were measured using MazDa software, using the co-occurrence matrix
(using a fine and coarse filter) and run-length matrix. Twenty six texture features were
selected by our physicist experienced in texture analysis:
•
•
•
•
•
•
•
•
•
•
•
Variance of absolute gradient
Mean absolute gradient
Grey level nonuniformity
Run length nonuniformity
Difference entropy - coarse and fine
Difference variance - coarse and fine
Entropy - coarse and fine
Sum entropy - coarse and fine
Sum variance - coarse and fine
Sum average - coarse and fine
Inverse difference moment - coarse and fine
Page 4 of 11
•
•
•
•
Sum of squares - coarse and fine
Correlation - coarse and fine
Contrast - coarse and fine
Angular second moment - coarse and fine
Statistical analysis:
One-way analysis of variance test was used to detect differences between the 4 groups.
Post-hoc testing was performed on variables which demonstrated significant intergroup
differences on ANOVA. Statistical analysis was performed using SPSS software v 22.0.
Results
On the one-way analysis of variance test there were significant differences between the
four groups in:
•
•
•
•
Fine entropy (F-test = 2.96, p=0.034)
Coarse entropy (F-test = 2.94, p=0.035)
Fine sum of squares measure (F-test = 2.76, p=0.044)
Coarse sum of squares measure (F-test = 3.48, p=0.018)
Texture
feature
Sum of
Squares
Mean Square
F-test
Significance
Entropy coarse
0.27
0.09
2.937
0.035
Sum of
squares coarse
1168.099
389.37
3.479
0.018
Entropy - fine
0.1
0.033
2.958
0.034
Sum of
689.764
229.92
2.761
0.04
squares - fine
Table 1: One-way analysis of texture features variance between the groups. For the full
table see Fig. 2 on page 6.
Post hoc testing of these variables showed that a significant difference existed between
group 3 (CVD) and 4 (Healthy volunteers), with group 3 exhibiting significantly higher
entropy:
Page 5 of 11
•
•
2.58±0.1 vs 2.50±0.1, p=0.025 for fine, and
2.33±0.2 vs 2.21±0.2, p=0.041 for coarse feature entropy.
DependentI Group
Variable
J Group
Mean
Std.
Difference Error
(I-J)
Significance
95%
95%
ConfidenceConfidence
Interval: Interval:
Lower
Upper
Bound
Bound
Entropy
- fine
4
-0.0804
0.025
3
0.0276
-0.154
-0.007
Entropy 3
4
-0.1251 0.0456
0.041
0.0065
0.1543
- coarse
Table 2: Post-hoc test of features highlighted by analysis of variance test. For the full
table see Fig. 3 on page 8.
Differences between groups in fine and coarse sum of squares measure were not
significant on the post hoc test.
No significant differences in myocardial texture was present between groups 1 and 2.
Discussion:
Our study shows that patients with cardiovascular disease have statistically higher
myocardial entropy (feature of texture heterogeneity) in comparison with healthy
individuals. This suggests that important additional information can be gathered from
analysing routinely acquired cardiac MR sequences. Increased myocardial texture
heterogeneity may be due to scarring or myocardial fibrosis. This proof of concept study
warrants validation and further research in this field.
Images for this section:
Page 6 of 11
Page 7 of 11
Fig. 2: One-way analysis of texture features variance between the groups
© Radiology, NHS Tayside - Dundee/UK
Page 8 of 11
Fig. 3: Bonferroni post-hoc test of features highlighted by analysis of variance test
Page 9 of 11
© Radiology, NHS Tayside - Dundee/UK
Page 10 of 11
Conclusion
Myocardial heterogeneity on routine non-contrast MR sequences is increased in those
with cardiovascular disease compared with controls, suggesting the technique holds
potential as a new and novel way of quantifying myocardial structure without the need
for additional sequences.
Personal information
References
1.
2.
3.
4.
5.
Castellano G, Bonilha L, Li LM, Cendes F. Texture analysis of medical
images. Clin Radiol. 2004 Dec; 59(12):1061-9
Assessment of primary colorectal cancer heterogeneity by using wholetumor texture analysis: contrast-enhanced CT texture as a biomarker of 5year survival. Ng F, Ganeshan B, Kozarski R, Miles KA, Goh V. Radiology.
2013 Jan;266(1):177-84.
Texture analysis in non-contrast enhanced CT: impact of malignancy on
texture in apparently disease-free areas of the liver. Ganeshan B, Miles KA,
Young RC, Chatwin CR. Eur J Radiol. 2009 Apr;70(1):101-10.
Naqa I et al. Exploring feature-based approaches in PET images for
predicting cancer treatment outcomes. Pattern Recognit. 2009 Jun 1; 42(6):
1162-1171.
Waugh SA, Purdie CA, Jordan B, Vinnicombe S, Lerski RA, Martin P,
Thompson AM. Magnetic resonance imaging texture analysis classification
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