Akademik Veri Yönetim Sistemi
Türk Manyetik Rezonans Derneği 26. Yıllık Bilimsel Toplantısı, Ankara, Türkiye, 26 - 28 Mayıs 2022
Objectives: This study aimed to assess baseline variability in
first-order texture features derived from apparent diffusion coefficient
(ADC) maps from diffusion-weighted imaging (DWI) and to identify
treatment responses in patients with sellar-parasellar tumors under-
going gamma knife radiosurgery (GKRS).
Methods: This retrospective study included 20 consecutive pa-
tients with sellar-parasellar tumors who underwent GKRS. DWI MRI
sequences were obtained before radiosurgery, at 6 months. Texture
parameters were extracted from MRI performed (DWI, and ADC se-
quences) using LifeX Software, dedicated software for extracting tex-
ture parameters from radiological imaging (Figure 1). Quantitative
ADC first-order texture features were analyzed for baseline and fol-
lowing GKRS.
Results: The study included 7 male (65.0%) and 13 female
(35.0%) patients with an average age of 52.90 ± 14.46 years (range,
30–74 years).
Texture Features: The mean and standard deviation of the
first-order texture parameters in patients with sellar and parasellar
tumors before and after GKRS are summarized in Table 1.
Except for the Skewness, Kurtosis, and Range, all first-order tex-
ture features were significantly different in patients with sellar and
parasellar tumors before and after GKRS (p<0.05).
Multivariate Logistic Regression Analysis of Texture
Parameters: Table 2 shows the results of the multivariate logistic
regression analyses on texture parameters.
Among the texture parameters extracted from first-order features,
Mean, Median, 10th percentile, 75th percentile, and Standard devia-
tion were independent predictors for evaluating treatment response
in patients with sellar and parasellar tumors after GKRS.
ROC Analysis results: Table 3 shows the ROC analysis results
for univariate and multivariate texture features for evaluating treat-
ment response in patients with sellar and parasellar tumors after
GKRS. The first-order regression model showed excellent diagnostic
performance for evaluating treatment response in patients with sel-
lar and parasellar tumors after GKRS and the AUC, sensitivity, and
specificity were 0.870, %80, and %90, respectively (Figure 2).
Conclusion: Our study suggests that first-order texture features
that derive from ADC maps hold great potential to evaluate response
to gamma knife radiosurgery treatment in sellar-parasellar tumors.