Luísa Nogueira

Application of the diffusion kurtosis model for the study of breast lesions.

ObjectivesTo evaluate diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in the differentiation and characterisation of breast lesions.MethodsThirty-six women underwent breast magnetic resonance imaging (MRI) including a DWI sequence with multiple b-values (50–3,000xa0s/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.ResultsForty-four lesions were found. There were significant differences between benign and malignant lesions for all parameters (ADC, pu2009=u20090.017; MD, pu2009=u20090.028; MK, pu2009=u20090.017). ADC and MD were higher for benign (1.96u2009±u20090.41u2009×u200910−3 and 2.17u2009±u20090.42u2009×u200910−3xa0mm2/s, respectively) than for malignant lesions (1.33u2009±u20090.18u2009×u200910−3 and 1.52u2009±u20090.50u2009×u200910−3xa0mm2/s). MK was higher for malignant (0.61u2009±u20090.27) than benign lesions (0.37u2009±u20090.18). We found differences between invasive ductal carcinoma (IDC) and fibroadenoma (FA) for all parameters (ADC, MD and MK): pu2009=u20090.016, 0.022 and 0.016, respectively. FA and fibrocystic change (FC) showed differences only in MK (pu2009=u20090.016).ConclusionsDiffusion 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.Key Points• The diffusion kurtosis model provides new information regarding breast lesions• MD and MK are valid parameters to characterise tissue microstructure• MK enables improved lesion differentiation• MK is able to differentiate lesions that display similar ADC values

Region of interest demarcation for quantification of the apparent diffusion coefficient in breast lesions and its interobserver variability

PURPOSEnWe aimed to compare two different methods of region of interest (ROI) demarcation and determine interobserver variability on apparent diffusion coefficient (ADC) in breast lesions.nnnMETHODSnThirty-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.nnnRESULTSnADC 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).nnnCONCLUSIONnThe 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.

Breast DWI at 3 T: influence of the fat-suppression technique on image quality and diagnostic performance.

AIMnTo 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.nnnMATERIALS AND METHODSnNinety-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/mm(2)) 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.nnnRESULTSnOne 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/mm(2) for DWI-STIR and 1.80 × 10(-3), 1.11 × 10(-3), 1.79 × 10(-3) s/mm(2) 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/mm(2), 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.nnnCONCLUSIONnThe 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.

Diffusion-weighted breast imaging at 3 T: Preliminary experience

AIMnTo evaluate the performance of diffusion-weighted imaging (DWI) at 3 T for the detection and characterization of breast lesions.nnnMATERIALS AND METHODSnMagnetic resonance imaging (MRI) of the breast, including DWI single-shot spin-echo echo planar images (SS-SE-EPI; eight b-values, 50-3000 s/mm(2)), were acquired in women with a clinical indication for breast MRI. The exclusion criteria were as follows: (1) previous breast surgery, radiotherapy and/or chemotherapy within the prior 48 months (14 women); (2) only cystic lesions (one woman); (3) no detectable enhancing lesion at dynamic contrast-enhanced (DCE)-MRI (15 women); and (4) breast implants (four women). MRI results were corroborated by histopathology or imaging follow-up. Apparent diffusion coefficients (ADCs) were estimated for lesions and normal glandular tissue. Differences in the ADC between tissue types were evaluated and the sensitivity and specificity of the method calculated by receiver operating characteristics (ROC) curves.nnnRESULTSnThe final cohort comprised 53 patients with 59 lesions. Histopathology was obtained for 58 lesions. One lesion was validated as benign on imaging follow-up. Mean ADCs of 1.99 ± 0.27 × 10(-3) mm(2)/s, 1.08 ± 0.25 × 10(-3) mm(2)/s, and 1.74 ± 0.35 × 10(-3) mm(2)/s were obtained for normal tissue, malignant, and benign lesions, respectively. Mean ADCs of malignancies were significantly lower than those of benign lesions (p < 0.001) and normal tissue (p < 0.0001). The sensitivity and specificity for stratifying lesions, considering an ADC threshold of 1.41 × 10(-3) mm(2)/s, were 94.3% and 87.5%, respectively; accuracy was 91.5%.nnnCONCLUSIONnDWI proved useful for the detection and characterization of breast lesions in the present sample. ADC values provide a high diagnostic performance for differentiation between benign and malignant lesions.

Diffusion-weighted imaging: determination of the best pair of b-values to discriminate breast lesions.

OBJECTIVEnIn breast diffusion-weighted imaging (DWI), the apparent diffusion coefficient (ADC) is used to discriminate between malignant and benign lesions. As ADC estimates can be affected by the weighting factors, our goal was to determine the optimal pair of b-values for discriminating breast lesions at 3.0u2009T.nnnMETHODSn152 females with 157 lesions (89 malignant and 68 benign) underwent breast MRI, including a DWI sequence sampling six b-values 50, 200, 400, 600, 800 and 1000u2009su2009mm(-2). ADC values were computed from different pairs of b-values and compared with ADC obtained by fitting the six b-values using a mono-exponential diffusion model (ADCall). Cut-off ADC values were determined and diagnostic performance evaluated by receiver operating characteristic analysis using Youden statistics. Mean ADCs were determined for normal tissue and lesions. Differences were evaluated by lesion and histological types.nnnRESULTSnConsidering the cut-off values 1.46 and 1.49u2009×u200910(3)mm(2)u2009s(-1), the pairs 50, 1000 and 200, 800u2009su2009mm(-2) showed the highest accuracy, 77.5% and 75.4% with areas under the curve 84.4% and 84.2%, respectively. The best pair for ADC quantification was 50, 1000u2009su2009mm(-2) with 38/49 true-negative and 69/89 true-positive cases respectively; mean ADCs were 1.86u2009±u20090.46, 1.77u2009±u20090.37 and 1.15u2009±u20090.46u2009×u200910(-3)u2009mm(2)u2009s(-1) for normal, benign and malignant lesions. There were no significant differences in these ADC values when compared with ADCallu2009(ADC calculated from the full set of bu2009-u2009values) [differenceu2009=u20090.0075u2009×u200910(-3)u2009mm(2)u2009s(-1); confidence interval 95%: (-0.0036; 0.0186); pu2009=u20090.18].nnnCONCLUSIONnThe diagnostic performance in differentiating malignant and benign lesions was most accurate for the b-value pair 50, 1000u2009su2009mm(-2).nnnADVANCES IN KNOWLEDGEnThe best b-value pair for lesion discrimination and characterization through ADC quantification was 50, 1000u2009su2009mm(-2).

Bone mineral density in vocational and professional ballet dancers.

SummaryAccording to existing literature, bone health in ballet dancers is controversial. We have verified that, compared to controls, young female and male vocational ballet dancers have lower bone mineral density (BMD) at both impact and non-impact sites, whereas female professional ballet dancers have lower BMD only at non-impact sites.IntroductionThe aims of this study were to (a) assess bone mineral density (BMD) in vocational (VBD) and professional (PBD) ballet dancers and (b) investigate its association with body mass (BM), fat mass (FM), lean mass (LM), maturation and menarche.MethodsThe total of 152 VBD (13xa0±xa02.3xa0years; 112 girls, 40 boys) and 96 controls (14xa0±xa02.1xa0years; 56 girls, 40 boys) and 184 PBD (28xa0±xa08.5xa0years; 129 females, 55 males) and 160 controls (27xa0±xa09.5xa0years; 110 female, 50 males) were assessed at the lumbar spine (LS), femoral neck (FN), forearm and total body by dual-energy X-ray absorptiometry. Maturation and menarche were assessed via questionnaires.ResultsVBD revealed lower unadjusted BMD at all anatomical sites compared to controls (pxa0<xa00.001); following adjustments for Tanner stage and gynaecological age, female VBD showed similar BMD values at impact sites. However, no factors were found to explain the lower adjusted BMD values in VBD (female and male) at the forearm (non-impact site), nor for the lower adjusted BMD values in male VBD at the FN. Compared to controls, female PBD showed higher unadjusted and adjusted BMD for potential associated factors at the FN (impact site) (pxa0<xa00.001) and lower adjusted at the forearm (pxa0<xa00.001). Male PBD did not reveal lower BMD than controls at any site.ConclusionsBoth females and males VBD have lower BMD at impact and non-impact sites compared to control, whereas this is only the case at non-impact site in female PBD. Maturation seems to explain the lower BMD at impact sites in female VBD.

Improving malignancy prediction in breast lesions with the combination of apparent diffusion coefficient and dynamic contrast- enhanced kinetic descriptors

AIMnTo 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.nnnMATERIALS AND METHODSnBreast 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.nnnRESULTSnADC 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)xa0mm(2)/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)xa0mm(2)/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%).nnnCONCLUSIONnThe 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.

Genetic variation in Wnt/β-catenin and ER signalling pathways in female and male elite dancers and its associations with low bone mineral density: a cross-section and longitudinal study

SummaryThe association of genetic polymorphisms with low bone mineral density in elite athletes have not been considered previously. The present study found that bone mass phenotypes in elite and pre-elite dancers are related to genetic variants at the Wnt/β-catenin and ER pathways.IntroductionSome athletes (e.g. gymnasts, dancers, swimmers) are at increased risk for low bone mineral density (BMD) which, if untreated, can lead to osteoporosis. To investigate the association of genetic polymorphisms in the oestrogen receptor (ER) and the Wnt/β-catenin signalling pathways with low BMD in elite and pre-elite dancers (impact sport athletes).MethodsThe study included three phases: (1) 151 elite and pre-elite dancers were screened for the presence of low BMD and traditional osteoporosis risk factors (low body weight, menstrual disturbances, low energy availability); (2) a genetic association study was conducted in 151 elite and pre-elite dancers and age- and sex- controls; (3) serum sclerostin was measured in 101 pre-elite dancers and age- and sex-matched controls within a 3-year period.ResultsEighty dancers revealed low BMD: 56.3% had at least one traditional osteoporosis risk factor, whereas 28.6% did not display any risk factor (37.2% revealed traditional osteoporosis risk factors, but had normal BMD). Body weight, menstrual disturbances and energy availability did not fully predict bone mass acquisition. Instead, genetic polymorphisms in the ER and Wnt/β-catenin pathways were found to be risk factors for low BMD in elite dancers. Sclerostin was significantly increased in dancers compared to controls during the 3-year follow-up (pu2009<u20090.05).ConclusionsElite and pre-elite dancers demonstrate high prevalence of low BMD, which is likely related to genetic variants at the Wnt/β-catenin and ER pathways and not to factors usually associated with BMD in athletes (body weight, menstrual disturbances, energy deficiency).

Diffusion-Weighted Breast Imaging: Beyond Morphology

Diffusion-weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique that explores the molecular diffusivity of water in biological tissues to probe its microstructure. Its application to the study of breast lesions has been shown to improve their detection, characterization, and the diagnostic accuracy of breast lesions using MRI. In this chapter, the biophysical basis of diffusion is presented, including the model currently used for DWI in the clinical setting; the concept of apparent diffusion coefficient (ADC) is introduced. A theoretical framework of DWI in healthy conditions and in tissues affected by pathological processes is presented, followed by a literature review on the application of DWI to breast imaging. As the technique has only recently been used in breast imaging studies, controversial issues regarding its application have arisen, namely related to its technical challenges. Therefore, we detail the main technical issues associated with the implementation of DWI in the clinical setting and present potential approaches for obtaining good-quality images. Finally, we identify relevant future research needs involving hardware and software optimization as well as clinical issues which need to be addressed to improve breast lesion diagnosis.

Gamma distribution model in breast cancer diffusion-weighted imaging

Summary 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/mm2. 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)×10-3mm2/s, 4.29±1.90, respectively) when compared to malignant lesions ((0.97±0.50)×10-3mm2/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. This study was partly funded by Fundação para a Ciência e Tecnologia (FCT) under the grant PEst-OE/SAU/UI0645/2014.