Browsing by Author "Nogueira, Luísa"
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- Apparent diffusion coefficient in the analysis of prostate cancerPublication . Adubeiro, Nuno; Nogueira, Luísa; Ribeiro, Eduardo; Alves, Sandra; Ferreira, Hugo; La Fuente, JoséThe multiparametric magnetic resonance imaging (MPMRI) approach, has allowed the diagnostic performance in the detection and characterization of prostate cancer (PCa). Diffusion-weighted imaging (DWI), is an important technique in the MPMRI, that provides qualitative and quantitative biological information regarding water diffusivity in a non-invasive manner. The apparent diffusion coefficient (ADC) measures water mobility and can be quantified from the signal intensity loss between two or more b-values. Different studies reported that ADC values are directly associated with microvessel density and cellularity. One of the main aspects that is in discussion is the b-values that must be used in the DWI sequence in order to compute ADC.
- 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.
- Associations between nutrition, energy expenditure and energy availability with bone mass acquisition in dance students: a 3-year longitudinal studyPublication . Amorim, Tânia; Freitas, Laura; Metsios, George S.; Thayse, Natacha Gomes; Wyon, Matthew; Flouris, Andreas D.; Maia, José; Marques, Franklim; Nogueira, Luísa; Adubeiro, Nuno; Koutedakis, YiannisThree years of study showed that female and male vocational dancers displayed lower bone mass compared to controls, at forearm, lumbar spine and femoral neck. Energy intake was found to positively predict bone mass accruals only in female dancers at femoral neck. Vocational dancers can be a risk population to develop osteoporosis.
- Avaliação radiológica do refluxo vesico – ureteral em criançasPublication . Nogueira, Luísa; Caldeira, J. P.; Adubeiro, NunoO Refluxo Vesico – Ureteral (RVU) é uma patologia frequente na idade pediátrica. A detecção precoce de RVU é fundamental na orientação terapêutica, de modo a permitir um crescimento renal adequado e prevenir infecções urinárias recorrentes. A investigação radiológica de RVU baseia-se na ecografia e cistouretrografia miccional seriada (CUMS), sendo este último procedimento, o método de eleição, efectuado sob controlo fluoroscópico. Este trabalho tem como objectivo dar a conhecer o papel CUMS na avaliação de RVU e abordar os parâmetros técnicos de aquisição, posicionamento e critérios de qualidade de imagem.
- Avanços da ressonância magnética mamária no diagnóstico do carcinoma da mamaPublication . Costa, Didier; Nogueira, Luísa; Ribeiro, EduardoA Ressonância Magnética Mamaria (RMM), ao longo da década, tem demonstrado um franco desenvolvimento no diagnóstico e caracterização do Carcinoma Mamário. O objectivo deste trabalho científico é demonstrar, através de uma revisão bibliográfica, os avanços desta modalidade na avaliação das lesões da mama, tendo em conta as características: elasticidade (Elastografia), bioquímicas (Espectroscopia), celularidade (Difusão) e vascularização (Perfusão). A avaliação destas em consonância com as morfológicas e cinéticas (RMM), permitem um aumento da especificidade da RMM, reduzindo assim o número de biopsias desnecessárias. Contudo estas evoluções técnicas devem estar em consonância com a inovação em questões de software de processamento de Imagem e hardware dos equipamentos de Ressonância Magnética.
- A colonoscopia virtual no rastreio do cancro colo rectalPublication . Guedes, Mónica; Barbosa, Simão; Nogueira, LuísaO cancro colo - rectal (CCR) é um problema de saúde mundial, estando associadas elevadas taxas de mortalidade e morbilidade. A maioria de CCR deriva de pólipos adenomatosos.. Um estudo retrospectivo, efectuado no serviço de Radiologia, dos achados imagiológicos típicos e atípicos, entre Janeiro de 2008 e Junho 2010. A Colonoscopia Virtual, apresenta uma sensibilidade elevada na detecção de lesões, com dimensão superior a 10mm, permitindo um diagnóstico precoce, é um exame rápido, pouco invasivo, não há necessidade de sedação e é efectuada em ambulatório.
- Diffusion-Weighted Breast Imaging: Beyond MorphologyPublication . Nogueira, Luísa; Nunes, Rita G.; Brandão, Sofia; Ramos, IsabelDiffusion-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.
- Do bone mineral content and density determine fracture in children? A possible threshold for physical activityPublication . Martins, Ana; Monjardino, Teresa; Nogueira, Luísa; Canhão, Helena; Lucas, RaquelBackgroundRelations between bone parameters, physical exertion, and childhood fractures are complex. We aimed to estimate the associations between fracture history and bone mineral content (BMC) and areal bone mineral density (aBMD) at 7 years of age, by levels of physical activity, as a proxy for trauma frequency.MethodsWe used data collected from 2,261 children of the Generation XXI birth cohort, assembled in 2005/6 in Porto, Portugal. At the age of 7 years (2012/4), fracture history, time spent per week in active play, and sports practice were reported by parents. Subtotal and lumbar spine (LS) BMC and aBMD were measured using whole-body dual-energy X-ray absorptiometry.ResultsBoys and girls in the highest categories of time spent in sports practice or active play generally had higher BMC and aBMD. Among girls, BMC and aBMD were protective of fracture only in the highest quarter of active play (>660 min/week)-odds ratios (OR; 95% confidence interval (95% CI)) for subtotal BMC=0.27 (0.11-0.67), subtotal aBMD=0.18 (0.06-0.49), and LS aBMD=0.41 (0.22-0.75). For boys in the highest quarter of sports practice (>240 min/week), subtotal and LS BMC were protective of fracture-OR=0.39 (0.16-0.98) and 0.51 (0.27-0.96), respectively.ConclusionIn prepubertal children, BMC and aBMD predicted fracture history only in the highest levels of physical activity.
- Dual source/dual energy-renal applicationsPublication . Adubeiro, Nuno; Nogueira, Luísa; Guedes, Mónica; Pinho, ErnestoDevelopment of Dual Source Computed Tomography (Definition, Siemens Medical Solutions, Erlanger, Germany) allowed advances in temporal resolution, with the addition of a second X-ray source and an array of detectors to the TCM 64 slices. The ability to run exams on Dual Energy, allows greater differentiation of tissues, showing differences between closer attenuation coefficients. In terms of renal applications, the distinction of kidney stones and masses become one of the main advantages of the use of dual-energy technology. This article pretends to demonstrate operating principles of this equipment, as its main renal applications.
- Editorial for “3D breast cancer segmentation in DCE‐MRI using deep learning with weak annotation”Publication . Nogueira, Luísa; Adubeiro, Nuno; Nunes, Rita G.Magnetic resonance imaging (MRI) shows higher diagnostic performance in the detection of breast tumors, compared with other imaging modalities. Breast MRI protocols include dynamic contrast-enhanced (DCE) images with high spatial and temporal resolution and are central indiagnosis, staging, and follow-up of breast cancer. DCE features provide physiological and anatomical lesion characteristics. To extract these data, manual lesion segmentation is currently performed, which is a critical time-consuming step,introducing bias and variability and impacting the reproducibility of the extracted features. To overcome these limitations, artificial intelligence algorithms have been explored, especially deep learning (DL) methods, for automatic lesion segmentation. This has been an active area of research, pivotal in the analysis of quantitative medical images. Most lesion segmentation methods have been based on semiautomatic or supervised learning approaches, presenting an important limitation: slice-by-slice 2D segmentations are typically performed, leading to suboptimal 3D masks upon concatenation. Recently, DL methods based on vision transformers have gained popularity in breast lesion segmentation, improving results over traditional machine learning. Although fully convolutional neural networks (CNNs) show powerful learning capabilities, their performance in learning long-range dependencies is limited, presenting decreased capacity in the segmentation of structures including different shapes and scales. UNETR is an architecture that replaces the CNN-based encoder with a transformer, which can capture low-level details in 3D segmentation. UNETR directly connects the encoder to the decoder via skip connections and can directly use volumetric data. Compared with CNN or transformer-based segmentation methods, UNETR can better capture dependencies at diverse spatial scales, both local and long-range enabling improved segmentation. In this retrospective study, Kim et al developed a model based on weak annotations, for detection and 3D segmentation of breast cancer in a sample of 736 women, using different input combinations in a three-time point (3TP) approach, from DCE-MRI images, acquired in two 3 T scanners from different manufacturers. The sample was divided into training (N = 544)and test sets (N = 192). To reduce the workload required toobta in ground truth segmentations, tumors were first segmented using weak annotations by two radiologists in consensus drawing bounding rectangles encompassing the lesion on two projection images. The rectangles were used to generate a 3D bounding box applied to the image obtained by subtracting the pre-contrast from the post-contrast image. An automatic thres holding method was used for automatic lesion segmentation; the mask was then refined to better define the lesion boundaries and exclude noisyor confounding regions (false positives). For training the segmen-tation network, images acquired at three different temporal acquisition points (pre-contrast, early, and delayed post-contrast) were used to construct three inputs: input 1 (pre-contrast, early phase),input 2 (pre-contrast, early, and delayed phase), and input 3 (pre-contrast and delayed phase). A different UNETR model wastrained for each input, and segmentation performances were compared, qualitatively and quantitatively, based on MRI features and immunohistochemical (IHC) classification. The best DL model presented a reliable performance for automated 3D segmentation of breast cancer with a median dicesimilarity coefficient (DSC) of 0.75 for the whole breast and 0.89 for the index lesion. The performance of the UNETR model was in accordance with the DSC values reported by other researchers employing alternative segmentation algorithms. Regarding the qualitative analysis of the segmentation results, the segmentation was successfully done in 83% of the cases derived from inputs 1 and 2, and from these, 95% were considered as acceptable detection. The authors also evaluated the performance of the segmentation according to base line characteristics and found significant differences for the whole breast and main lesion. For main lesion, significant differences were observed according to lesion size and IHC type. Regarding visual analysis, significant differences were found between lesion type (mass vs. non-mass enhancement) and background parenchymal enhancement (BPE) level. In their study, there were nine cases of failed segmentation, which corresponded totumors with small volumes, from which five cases were not segmented and four cases corresponded to abundant BPE,meaning false-positive results.© 2023 International Society for Magnetic Resonance in Medicine. 2263 Further developments of 3D UNETR architecture could be done to improve small lesion detection, to distinguish between mass and non-mass lesions, especially the boundaries of non-masses, and to distinguish between BPE and tumors. Attending to the implementation of DL algorithms in the clinical practice, this type of algorithm is expected to improve the detection of small lesions and the prediction of response to treatment, there by reducing the number of performed biopsies and, potentially, enabling the use of an abbreviated MRI pro-tocol, which would reduce MRI exam durations, improving patient comfort, and reducing costs.
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