J Yeungnam Med Sci.  2022 Jan;39(1):24-30. 10.12701/yujm.2021.01165.

Magnetic resonance imaging texture analysis for the evaluation of viable ovarian tissue in patients with ovarian endometriosis: a retrospective case-control study

• Lee D
• Lee HJ

• KMID: 2525024
• DOI: http://doi.org/10.12701/yujm.2021.01165

Abstract

Background
Texture analysis has been used as a method for quantifying image properties based on textural features. The aim of the present study was to evaluate the usefulness of magnetic resonance imaging (MRI) texture analysis for the evaluation of viable ovarian tissue on the perfusion map of ovarian endometriosis.
Methods
To generate a normalized perfusion map, subtracted T1-weighted imaging (T1WI), T1WI and contrast-enhanced T-WI with sequences were performed using the same parameters in 25 patients with surgically confirmed ovarian endometriosis. Integrated density is defined as the sum of the values of the pixels in the image or selection. We investigated the parameters for texture analysis in ovarian endometriosis, including angular second moment (ASM), contrast, correlation, inverse difference moment (IDM), and entropy, which is equivalent to the product of area and mean gray value.
Results
The perfusion ratio and integrated density of normal ovary were 0.52±0.05 and 238.72±136.21, respectively. Compared with the normal ovary, the affected ovary showed significant differences in total size (p<0.001), fractional area ratio (p<0.001), and perfusion ratio (p=0.010) but no significant differences in perfused tissue area (p=0.158) and integrated density (p=0.112). In comparison of parameters for texture analysis between the ovary with endometriosis and the contralateral normal ovary, ASM (p=0.004), contrast (p=0.002), IDM (p<0.001), and entropy (p=0.028) showed significant differences. A linear regression analysis revealed that fractional area had significant correlations with ASM (r2=0.211), IDM (r2=0.332), and entropy (r2=0.289).
Conclusion
Magnetic resonance texture analysis could be useful for the evaluation of viable ovarian tissues in patients with ovarian endometriosis.

Keyword

Endometriosis; Gadolinium; Gadolinium; Ovary; Texture analysis

Figure

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  Fig. 1. (A) Region of interest (ROI) for normal ovary (arrow) and endometriosis (arrowhead) is defined on the T2-weighted image. (B, C) Division of the subtraction image by the contrast-enhanced T1-weighted image generates a normalized perfusion map. To measure only the perfusion of the surviving ovarian tissue, pixels corresponding to endometriotic cysts with a low perfusion state of 0.2 or less were removed using the threshold technique. (D) The saved ROI is applied to the normalized perfusion map.

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  Fig. 2. Comparison of the number of pixels for the perfusion ratio between normal ovary (black line) and affected ovary by endometriosis (red line).

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  Fig. 3. Comparison of texture analysis parameters, including (A) angular second moment, (B) inverse difference moment, and (C) entropy, between affected ovary by endometriosis and the contralateral normal ovary.

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  Fig. 4. Linear regression analysis of the parameters for texture analysis, including (A) angular second moment, (B) inverse difference moment, and (C) entropy, of the affected ovary according to fractional area.

Reference

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