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- Editorial for “Three‐dimensional multifrequency MR elastography for microvascular invasion and prognosis assessment in Hepatocellular Carcinoma”Publication . Adubeiro, Nuno; Nunes, Rita G.; Nogueira, LuísaThe prognosis of individuals with hepatocellular carcinoma(HCC), the most prevalent primary liver malignancy, is closely linked to the aggressiveness and recurrence of the tumor. The occurrence of complications after surgery continues to be a major and persistent challenge. MR elastography (MRE) employs a modified phase-contrast imaging sequence, combined with the use of an external driver to transmit mechanical vibrations to the tissues, to identify propagating shear waves within the liver. This technique allows the assessment of a substantial portion of the liver and provides information on multiple mechanical properties associated with various pathophysiological states. Due to substantial progress in MR technology, MRE has proven to be a precise noninvasive diagnostic method for detecting and monitoring various liver diseases. MRE imaging could serve as a valuable tool for staging malignancy and predict disease prognosis.
- Impact of walking on knee articular cartilage T2 values estimated with a dictionary-based approach - A pilot studyPublication . Coelho, José M.; Fernandes, T.T.; Alves, Sandra Maria; Nunes, R.G.; Nogueira, Luísa; Oliveira, A.Walking is crucial for knee articular cartilage (KAC) health. Routine MRI sequences lack sensitivity for early cartilage changes, and the use of parametric T2 maps to study the effect of walking on KAC composition is limited. This study aimed to evaluate if quantitative T2 maps using an Echo Modulation Curve (EMC) matching algorithm can detect KAC T2 variations due to water content changes after walking. Seven asymptomatic volunteers (3 females, 4 males, mean age 28.3 years) without knee pathologies participated. Sagittal knee MRI scans were performed before and after a 9-min treadmill walk using a Modified Bruce protocol. T2-weighted Multi-Echo Spin-Echo KAC images were acquired at 3T. Tibiofemoral cartilage was segmented semi-automatically on three slices per knee, defining 39 KAC samples. Quantitative T2 maps were created using a dictionary-matching algorithm. Paired t-tests assessed exercise impact on KAC T2 values, independent t-tests compared group differences, and Friedman test with Bonferroni correction evaluated regional T2 changes. Walking increased KAC T2 values (mean difference (md) 0.61 ± 1.71 ms; p ¼ 0.016). Significant differences were observed in “normal” BMI group (md 0.69 ± 1.27 ms; p ¼ 0.021). Regional analysis revealed significant differences in medial femur in males (md 0.9 ± 2.1 ms; p ¼ 0.049) and lateral tibia in females (md 1.4 ± 2.5 ms; p ¼ 0.046). The medial tibia showed significant differences across sub-regions (p ¼ 0.026). Quantitative T2 maps using the EMC matching algorithm detected consistent changes in KAC T2 values after a short walking period. Implications for practice: EMC quantitative T2 maps effectively detected knee cartilage changes postwalking. This technique could improve cartilage hydration assessments, aiding early detection in atrisk patients. It also suggests potential for personalized monitoring and rehabilitation, advancing musculoskeletal imaging and non-invasive joint health monitoring.
- Investigação clínica – Aspectos globaisPublication . Adubeiro, NunoO campo da investigação na saúde é inerentemente uma área de extrema compexidade, com muitas particularidades, mas cujo aporte é fulcral pra que se possam tomar decisões baseadas na evidência.
- Editorial for “Detecting adverse pathology of prostate cancer with a deep learning approach based on a 3D swin-transformer model and biparametric MRI: A multicenter retrospective study"Publication . Adubeiro, Nuno; Nogueira, LuísaProstate cancer (PCa) is the second most prevalent cancer among men worldwide. Timely and accurate diagnosis is important to avoid overtreatment of men with indolent, clinically insignificant PCa and to offer radical curative treatment with life-threatening, clinically significant PCa. Radical prostatectomy (RP) has become the standard care for eligible patients because of its cancer control and improved survival. Although most patients remained disease-free after RP, 20%–30% of patients develop recurrence of the disease at follow-up.3 Therefore, the assessment of reliable prognostic predictors of recurrence after RP is clinically important for guiding clinical decision-making and patient counseling. To date, several factors are considered adverse pathology (AP) features such as preoperative prostate-specific antigen (PSA) levels, Gleason score, tumor stage, surgical margin status, lymph node invasion, extracapsular extension (ECE), and seminal vesicle invasion (SVI). All of them have been identified as prognostic factors for recurrence after RP.
- 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.
- Risco de burnout nos técnicos de radiologia das unidades de saúde do PortoPublication . Silva, Cristiana Alexandra Vieira da; Pereira, José Manuel RodriguesO burnout é descrito como uma síndroma que envolve exaustão emocional, física e mental e que resulta da exposição continuada ao stress laboral. É caracterizada por elevada exaustão emocional, despersonalização e baixa realização pessoal. Este estudo procurou avaliar o risco de burnout nos técnicos de radiologia que exercem funções em instituições de saúde da região do Porto, Portugal. Os níveis de burnout foram estimados através do Maslach Burnout Inventory – Human Services Survey composto por 22 questões. A amostra foi constituída por 122 indivíduos, provenientes de sete instituições de saúde, públicas e privadas, em que 61,5% eram do sexo feminino, com média de idades e desvio-padrão de 38,3 (±9,3) anos. Na análise relacional entre as variáveis sociodemográficas e os resultados do MBI-HSS foram utilizados os testes Qui-quadrado de Pearson ou Exato de Fisher, conforme a percentagem de células com contagem menor que 5 era menor ou maior que 20% para as variáveis qualitativas. Para as variáveis quantitativas realizaram-se os testes ANOVA ou Kruskal-Wallis, conforme a homogeneidade da variância entre grupos. A interpretação dos testes estatísticos correlacionais foi efetuada com base no nível de significância de α=0,05 com intervalo de confiança de 95%. A análise dos níveis das dimensões do burnout revelou valores médios de 21,73 (±11,37) para a exaustão emocional, de 7,42 (±5,40) para a despersonalização e de 32,79 (±8,46) para a realização pessoal, o que se coaduna com níveis moderados para as duas primeiras dimensões e baixos para a última. Deste grupo de técnicos, 39,3% e 29,5% exibem elevados níveis de exaustão emocional e despersonalização, respetivamente. A baixa realização pessoal é experienciada por 48,4% dos inquiridos. As mulheres são mais afetadas pela exaustão emocional (51%), bem como os profissionais com tempo na função entre os 11 e os 30 anos. Em serviços compostos por 20 a 40 técnicos observa-se um nível mais elevado de exaustão emocional (63%). A maioria dos inquiridos afirma que o trabalho afeta a sua autoestima, vida familiar e social, nomeadamente de forma negativa, o que posteriormente se relaciona com alguns valores elevados de exaustão emocional e despersonalização e baixos de realização pessoal. A ocorrência de burnout nos técnicos de radiologia é relevante e estes resultados alertam para a necessidade de intervir no sentido de melhorar as condições de trabalho, formação contínua e implementação de medidas de suporte emocional dos profissionais de saúde, de forma a garantir a qualidade do serviço prestado aos utentes e o bem-estar pessoal destes profissionais.
- High resolution sagittal T2 in the study of the female pelvis by MRI: comparative study of motion-artifact reduction techniquesPublication . Freitas, Davide; Araújo, C. S. D. S. M.; Themudo, R.; Abreu, E. M.The high contrast resolution, possibility of tissue characterization, multiplanar imaging, lack of ionizing radiation and the increasing availability of scanners, made MRI an important tool in female pelvis diagnostic, specifically in ovarian and uterine pathology. Fasting, empty bladder and compression by a pelvic band, reduce the movement and phase artifacts caused by peristaltic movements of the intestine and other organs (fig.1), as well as pelvic respiratory artifacts. However, other resources, such as the intravenous administration of anti-spasmodic drugs (glucagon or hyoscine butyl-bromide) are often required to increase imaging quality, and its routine application is often recommended . These drugs have few contraindications, such as glaucoma and myasthenia gravis, and low incidence of allergic reactions. The most common side effect is blurred vision, which occurs in about 10 % of the patients and is reversible in 30-45 minutes. The majority of modern MRI scanners include advances in image acquisition, such as the sequences PROPPLER / BLADE (General Electric and Siemens terms, respectively). These sequences have a radial k-space sampling concept with parallel data lines rotating around the k-space center, which allows spatial inconsistencies. Data indicating through-plane motion based on correlation measurement are rejected. Motion artifacts are further reduced through averaging in low spatial frequencies. Thus, considering the side effects that antispasmodic drugs can provoke, and the existence of modern scanners with advanced acquisition techniques that minimize movement artifacts, the aim of our study was to compare image quality, anatomic detail and presence of artifacts on high resolution sagittal T2-turbo-spin-echo (TSE), T2-TSE-BLADE and on T2-TSE after intravenous administration of an antispasmodic drug, hereby referred as T2-TSE-iv, in the female pelvic MRI study.
- Impacto da pandemia COVID-19 na qualidade de imagem na radiografia do tórax em Unidade de Cuidados IntensivosPublication . Freitas, Davide; Silva, Cristiana; Pereira, José ManuelA imagem nas Unidade de Cuidados Intensivos (UCI) desempenha um papel crucial na assistência ao paciente, sendo a radiografia ao tórax o exame mais requisitado aos pacientes COVID-19 em contexto de UCI. O elevado risco de exposição ao vírus poderá influenciar a qualidade de execução dos exames. O objetivo deste estudo é comparar o cumprimento dos critérios de boa realização em radiografia do tórax em UCI, antes e durante a fase crítica da pandemia COVID-19. Avaliaram-se 32 imagens, 16 realizadas antes da pandemia e 16 a doentes COVID-19, de acordo com uma escala de 8 itens, com pontuação entre 8 e 25 pontos, inversamente proporcional ao grau de cumprimento. Não se observaram diferenças significativas ao nível dos valores médios entre os grupos, exceto na presença de artefactos, constatando se que os exames realizados a doentes COVID-19 cumpriram melhor/mais eficazmente este critério. Os resultados sugerem que, apesar do acréscimo de stress derivado à exposição ao novo vírus, se mantém o padrão de qualidade na realização de exames em UCI.
- Papel atual da radiologia geral na avaliação de fetos e recém-nascidos post-mortemPublication . M. Figueiredo Correia, Ricarda; Cardoso, Paula; Botelho, Nuno Alexandre Rodrigues da Rocha; Ventura, Sandra RuaO grande leque de aplicações e potencialidades da imagem médica forense tem sofrido uma enorme expansão e desenvolvimento nos últimos anos. Este estudo pretende demonstrar o papel da osteometria radiográfica na orientação da autópsia de fetos ou recém-nascidos post-mortem. Em termos metodológicos, este estudo teve por base uma pesquisa bibliográfica extensa, seguindo-se de um estudo observacional e retrospetivo. De seguida procedeu-se à recolha de dados biométricos e antropométricos, obtidos a partir dos relatórios das autópsias e das radiografias apensas realizadas em 152 fetos e recém-nascidos com idades inferiores a um ano, no período do ano de 2014 a 2015, observando-se que os valores variam principalmente em função da idade gestacional. Como principal resultado constatou-se que existem evidências estatísticas na osteometria radiográfica dos ossos longos (r=0,529, p<0,01), cujas medidas se relacionam diretamente com a idade gestacional. Conclui-se, assim, que a avaliação radiográfica nas autópsias de fetos e recém-nascidos é importante na determinação do subdesenvolvimento fetal ou pós-natal.
- Preprocessing of magnetic resonance images with multiple Sclerosis lesionsPublication . Pinto, Rafaela; Ventura, Sandra Rua; Silva, Vitor; Tavares, Manuel R.S.According to the World Health Organization, it is estimated that multiple sclerosis (MS) affects around 2.5 million people worldwide and more than 5000 in Portugal. Multiple sclerosis is an inflammatory, demyelinating, idiopathic, and often disabling central nervous system disease that affects the white matter diagnosed in young adults and predominantly affects womens. Multiple sclerosis is the most common neurological disorder with unexplained causes and major repercussions in the lives of patients, causing the active search for answers by the researchers. Although the disease cannot be cured or prevented at this time, the available treatments only reduce its severity and delay its progression. In recent years, there has been a major development of image processing and analysis techniques in order to facilitate early diagnosis and suitable treatment. In general, images acquired by imaging devices and specialized techniques require transformations and enhancements to make them more suitable in order to extract as much information as desired with greater efficiency. Several authors, have described techniques of image preprocessing and segmentation of MS lesions, making evident the advantages of such computational tools. In this work, different preprocessing algorithms were applied in order to perform the brain extraction from resonance magnetic (RM) images for their easier further analysis.