Browsing by Author "Ferreira, Hugo Alexandre"
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- Apparent diffusion coefficient in the analysis of prostate cancer: determination of optimal b-value pair to differentiate normal from malignant tissuePublication . Adubeiro, Nuno; Nogueira, Maria Luísa; Nunes, Rita G.; Ferreira, Hugo Alexandre; Ribeiro, Eduardo; La Fuente, José Maria FerreiraPurpose Determining optimal b-value pair for differentiation between normal and prostate cancer (PCa) tissues. Methods Forty-three patients with diagnosis or PCa symptoms were included. Apparent diffusion coefficient (ADC) was estimated using minimum and maximum b-values of 0, 50, 100, 150, 200, 500 s/mm2 and 500, 800, 1100, 1400, 1700 and 2000s/mm2, respectively. Diagnostic performances were evaluated when Area-under-the-curve (AUC) > 95%. Results 15 of the 35 b-values pair surpassed this AUC threshold. The pair (50, 2000 s/mm2) provided the highest AUC (96%) with ADC cutoff 0.89 × 10–3 mm2/s, sensitivity 95.5%, specificity 93.2% and accuracy 94.4%. Conclusions The best b-value pair was b = 50, 2000 s/mm2.
- Application of the diffusion kurtosis model for the study of breast lesionsPublication . Nogueira, Luísa; Brandão, Sofia; Matos, Eduarda; Nunes, Rita Gouveia; Loureiro, Joana; Ramos, Isabel; Ferreira, Hugo AlexandreObjectives To evaluate diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in the differentiation and characterisation of breast lesions. Methods Thirty-six women underwent breast magnetic resonance imaging (MRI) including a DWI sequence with multiple b-values (50–3,000 s/mm2). Mean values for apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) were calculated by lesion type and histological subtype. Differences and correlation between parameters were determined. Results Forty-four lesions were found. There were significant differences between benign and malignant lesions for all parameters (ADC, p = 0.017; MD, p = 0.028; MK, p = 0.017). ADC and MD were higher for benign (1.96 ± 0.41 × 10−3 and 2.17 ± 0.42 × 10−3 mm2/s, respectively) than for malignant lesions (1.33 ± 0.18 × 10−3 and 1.52 ± 0.50 × 10−3 mm2/s). MK was higher for malignant (0.61 ± 0.27) than benign lesions (0.37 ± 0.18). We found differences between invasive ductal carcinoma (IDC) and fibroadenoma (FA) for all parameters (ADC, MD and MK): p = 0.016, 0.022 and 0.016, respectively. FA and fibrocystic change (FC) showed differences only in MK (p = 0.016). Conclusions Diffusion in breast lesions follows a non-Gaussian distribution. MK enables differentiation and characterisation of breast lesions, providing new insights into microstructural complexity. To confirm these results, further investigation in a broader sample should be performed.
- Breast DWI at 3 T: influence of the fat-suppression technique on image quality and diagnostic performancePublication . Nogueira, Luisa; Brandão, Sofia; Nunes, Rita G.; Ferreira, Hugo Alexandre; Loureiro, Joana; Ramos, IsabelAim To evaluate two fat-suppression techniques: short tau inversion recovery (STIR) and spectral adiabatic inversion recovery (SPAIR) regarding image quality and diagnostic performance in diffusion-weighted imaging (DWI) of breast lesions at 3 T. Materials and methods Ninety-two women (mean age 48 ± 12.1 years; range 21–78 years) underwent breast MRI. Two DWI pulse sequences, with b-values (50 and 1000 s/mm2) were performed with STIR and SPAIR. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), suppression homogeneity, and apparent diffusion coefficient (ADC) values were quantitatively assessed for each technique. Values were compared between techniques and lesion type. Receiver operating characteristics (ROC) analysis was used to evaluate lesion discrimination. Results One hundred and fourteen lesions were analysed (40 benign and 74 malignant). SNR and CNR were significantly higher for DWI-SPAIR; fat-suppression uniformity was better for DWI-STIR (p < 1 × 10−4). ADC values for benign and malignant lesions and normal tissue were 1.92 × 10−3, 1.18 × 10−3, 1.86 × 10−3 s/mm2 for DWI-STIR and 1.80 × 10−3, 1.11 × 10−3, 1.79 × 10−3 s/mm2 for SPAIR, respectively. Comparison between fat-suppression techniques showed significant differences in mean ADC values for benign (p = 0.013) and malignant lesions (p = 0.001). DWI-STIR and -SPAIR ADC cut-offs were 1.42 × 10−3 and 1.46 × 10−3 s/mm2, respectively. Diagnostic performance for DWI-STIR versus SPAIR was: accuracy (81.6 versus 83.3%), area under curve (87.7 versus 89.2%), sensitivity (79.7 versus 85.1%), and specificity (85 versus 80%). Positive predictive value was similar. Conclusion The fat-saturation technique used in the present study may influence image quality and ADC quantification. Nevertheless, STIR and SPAIR techniques showed similar diagnostic performances, and therefore, both are suitable for use in clinical practice.
- Fat suppression techniques (STIR vs. SPAIR) on diffusion-weighted imaging of breast lesions at 3.0 T: preliminary experiencePublication . Brandão, Sofia; Nogueira, Luísa; Matos, Eduarda; Nunes, Rita Gouveia; Ferreira, Hugo Alexandre; Loureiro, Joana; Ramos, IsabelPurpose The aim of this work was to perform a qualitative and quantitative comparison of the performance of two fat suppression techniques on breast diffusion-weighted imaging (DWI). Materials and methods Fifty-one women underwent clinical breast magnetic resonance imaging, including DWI with short TI inversion recovery (STIR) and spectral attenuated inversion recovery (SPAIR). Four were excluded from the analysis due to image artefacts. Rating of fat suppression uniformity and lesion visibility were performed. Agreement between the two sequences was evaluated. Additionally, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values for normal gland, benign and malignant lesions were compared. Receiver operating characteristic analysis was also performed. Results From the 52 lesions found, 47 were detected by both sequences. DWI-STIR evidenced more homogeneous fat suppression (p = 0.03). Although these lesions were seen with both techniques, DWI-SPAIR evidenced higher score for lesion visibility in nine of them. SNR and CNR were comparable, except for SNR in benign lesions (p < 0.01), which was higher for DWI-SPAIR. Mean ADC values for lesions were similar. ADC for normal fibroglandular tissue was higher when using DWI-STIR (p = 0.006). Sensitivity, specificity, accuracy and area under the curve values were alike: 84.0 % for both; 77.3, 71.4 %; 80.9, 78.3 %; 82.5, 81.3 % for DWI-SPAIR and DWI-STIR, respectively. Conclusion DWI-STIR showed superior fat suppression homogeneity. No differences were found for SNR and CNR, except for SNR in benign lesions. ADCs for lesions were comparable. Findings in this study are consistent with previous studies at 1.5 T, meaning that both fat suppression techniques are appropriate for breast DWI at 3.0 T.
- Improving malignancy prediction in breast lesions with the combination of apparent diffusion coefficient and dynamic contrast-enhanced kinetic descriptorsPublication . Nogueira, Luisa; Brandão, Sofia; Matos, Eduarda; Gouveia Nunes, Rita; Ferreira, Hugo Alexandre; Loureiro, Joana; Ramos, IsabelAim To assess how the joint use of apparent diffusion coefficient (ADC) and kinetic parameters (uptake phase and delayed enhancement characteristics) from dynamic contrast-enhanced (DCE) can boost the ability to predict breast lesion malignancy. Materials and methods Breast magnetic resonance examinations including DCE and diffusion-weighted imaging (DWI) were performed on 51 women. The association between kinetic parameters and ADC were evaluated and compared between lesion types. Models with binary outcome of malignancy were studied using generalized estimating equations (GEE), (GEE), and using kinetic parameters and ADC values as malignancy predictors. Model accuracy was assessed using the corrected maximum quasi-likelihood under the independence confidence criterion (QICC). Predicted probability of malignancy was estimated for the best model. Results ADC values were significantly associated with kinetic parameters: medium and rapid uptake phase (p<0.001) and plateau and washout curve types (p=0.004). Comparison between lesion type showed significant differences for ADC (p=0.001), early phase (p<0.001), and curve type (p<0.001). The predicted probabilities of malignancy for the first ADC quartile (≤1.17×10−3 mm2/s) and persistent, plateau and washout curves, were 54.6%, 86.9%, and 97.8%, respectively, and for the third ADC quartile (≥1.51×10−3 mm2/s) were 3.2%, 15.5%, and 54.8%, respectively. The predicted probability of malignancy was less than 5% for 18.8% of the lesions and greater than 33% for 50.7% of the lesions (24/35 lesions, corresponding to a malignancy rate of 68.6%). Conclusion The best malignancy predictors were low ADCs and washout curves. ADC and kinetic parameters provide differentiated information on the microenvironment of the lesion, with joint models displaying improved predictive performance.
- Region of interest demarcation for quantification of the apparent diffusion coefficient in breast lesions and its interobserver variabilityPublication . Nogueira, Luísa; Brandão, Sofia; Matos, Eduarda; Nunes, Rita Gouveia; Ferreira, Hugo Alexandre; Loureiro, Joana; Ramos, IsabelPURPOSE We aimed to compare two different methods of region of interest (ROI) demarcation and determine interobserver variability on apparent diffusion coefficient (ADC) in breast lesions. METHODS Thirty-two patients with 39 lesions were evaluated with a 3.0 Tesla scanner using a diffusion-weighted sequence with several b-values. Two observers independently performed the ADC measurements using: 1) a small fixed area of 10 mm2 ROI within the area with highest restriction; 2) a large ROI so as to include the whole lesion. Differences were assessed using the Wilcoxon-rank test. Bland-Altman method and Spearman coefficient were applied for interobserver variability and correlation analysis. RESULTS ADC values measured using the two ROI demarcation methods were significantly different for both observers (P = 0.026; P = 0.033). There was no interobserver variability in ADC values using either method (large ROI, P = 0.21; small ROI, P = 0.64). ADC values of malignant lesions were significantly different between the two methods (P < 0.001). Variability in ADC was ≤0.008×10−3 mm2/s for both methods. When using the same method, ADC values were significantly correlated between the observers (small ROI: r=0.990, P < 0.001; large ROI: r=0.985, P < 0.001). CONCLUSION The choice of ROI demarcation method influences ADC measurements. Small ROIs show less overlap in ADC values and higher ADC reproducibility, suggesting that this method may improve lesion discrimination. Interobserver variability was low for both methods.