Browsing by Author "Loureiro, Joana"
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- Alzheimer’s disease: Development of a sensitive label-free electrochemical immunosensor for detection of amyloid beta peptidePublication . Carneiro, Pedro; Loureiro, Joana; Delerue-Matos, Cristina; Morais, Simone; Pereira, Maria do CarmoIn this work, a highly sensitive label-free immunosensor for detection of the main biomarker of Alzheimer’s disease (AD), amyloid beta 1–42 (Aβ (1–42)), is presented. A gold electrode was modified with a mercaptopropionic acid (MPA) self-assembled monolayer, electrodeposited gold nanoparticles (AuNPs) and a monoclonal antibody mAb DE2B4 to recognize Aβ; all the relevant experimental variables were optimized. Antibodies were functionalized through chemical modification (thiolation) to promote the antibody immobilization on the AuNPs surface with proper orientation which enabled the direct detection of Aβ(1–42). Scanning electron microscopy, square-wave voltammetry and electrochemical impedance spectroscopy were used to characterize the construction of the biosensor. Using the proposed immunosensor, Aβ(1–42) was specifically detected within the linear range of 10–1000 pg mL−1 with a 5.2 pg mL−1 and 17.4 pg mL−1 detection and quantification limit, respectively; recovery values for the tested spiking levels ranged from 90.3 to 93.6%. The immunosensor enables rapid, accurate, precise, reproducible and highly sensitive detection (14.6%reduction mL pg−1) of Aβ with low-cost and opens the possibilities for diagnostic ex vivo applications and research-based in vivo studies.
- Alzheimer’s disease: Development of a sensitive label-freeelectrochemical immunosensor for detection of amyloid beta peptidePublication . Carneiro, Pedro; Loureiro, Joana; Delerue-Matos, Cristina; Morais, Simone; Pereira, Maria do CarmoIn this work, a highly sensitive label-free immunosensor for detection of the main biomarker of Alzheimer’s disease (AD), amyloid beta 1–42 (A (1–42)), is presented. A gold electrode was modified with a mercaptopropionic acid (MPA) self-assembled monolayer, electrodeposited gold nanoparticles (AuNPs) and a monoclonal antibody mAb DE2B4 to recognize A ; all the relevant experimental variables were optimized. Antibodies were functionalized through chemical modification (thiolation) to promote the antibody immobilization on the AuNPs surface with proper orientation which enabled the direct detection of A (1–42). Scanning electron microscopy, square-wave voltammetry and electrochemical impedance spectroscopy were used to characterize the construction of the biosensor. Using the pro-posed immunosensor, A (1–42) was specifically detected within the linear range of 10–1000 pg mL−1 with a 5.2 pg mL−1 and 17.4 pg mL−1 detection and quantification limit, respectively; recovery values for the tested spiking levels ranged from 90.3 to 93.6%. The immunosensor enables rapid, accurate, precise, reproducible and highly sensitive detection (14.6%reduction mL pg−1) of A with low-cost and opens the possibilities for diagnostic ex vivo applications and research-based in vivo studies.
- 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.
- Gamma distribution model in breast cancer diffusion-weighted imagingPublication . Borlinhas, Filipa; Nogueira, Luisa; Brandao, Sofia; Nunes, Rita G.; Loureiro, Joana; Ramos, Isabel; Ferreira, Hugo ASummary form only given. Many diffusion models have been proposed in order to obtain more information from breast tumor tissues through Magnetic Resonance Imaging (MRI) (1). The Gamma distribution (GD) may model MRI signal decay based on a statistical approach. This model considers the Theta parameter, which indicates the statistical dispersion of the distribution, and the k parameter, which is responsible for the probability distribution shape. If Theta shows higher values, then there will be a more spread out distribution and if k shows lower values the distribution shape will be more affected, which would be expected in malignant tumors due to tissue heterogeneity (1). The purpose of this study was to evaluate if GD model is capable of distinguishing between different breast tumors. Materials and Methods: In this study 85 breast tumor lesions were analyzed, including 17 benign lesions (Fibroadenoma, FA) and 68 malignant lesions (43 Invasive Ductal Carcinomas, IDC 19 Invasive Lobular Carcinomas, ILC and 6 Ductal Carcinoma in situ, CDIS). Informed consent was obtained for all patients. Data were acquired using a 3T MRI scanner with a dedicated breast coil and a DWI sequence with 3 orthogonal diffusion gradient directions and 8 b values between 0 and 3000s/mm 2 . Theta and k parameters were acquired from fitting data to the GD model, and mean values were obtained to compare between benign and malignant lesions, and between histological types. Non-parametric statistics were used (α=0.05). Results and Discussion: Significantly lower Theta and higher k values were observed in benign lesions ((0.65±0.43)×10 -3 mm 2 /s, 4.29±1.90, respectively) when compared to malignant lesions ((0.97±0.50)×10 -3 mm 2 /s, 1.23±0.52, respectively). It was also possible to differentiate FA from IDC lesions with both Theta and k probably due to IDC heterogeneity, which restricts diffusion. Unlike other diffusion model parameters, these were able to differentiate FA and ILC, and FA and CDIS lesions, suggesting that the GD model could bring advantages over other diffusion models in characterizing breast tumors.
- 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.