Valor preditivo positivo das categorias 3, 4 e 5 do Breast Imaging Reporting and Data System (BI-RADS®)

OBJETIVO: O objetivo deste trabalho foi avaliar o BI-RADS® como fator preditivo de suspeição de malignidade em lesões mamárias não palpáveis nas categorias 3, 4 e 5, correlacionando as mamografias com os resultados histopatológicos através do cálculo do valor preditivo positivo do exame mamográfico. MATERIAIS E MÉTODOS: Trezentas e setenta e uma pacientes encaminhadas a um serviço de referência em tratamento de câncer em Teresina, PI, para realização de exames histopatológicos em mama no período de julho de 2005 a março de 2008, por terem mamografia de categorias 3, 4 ou 5, tiveram seus exames revisados. Das 371 pacientes, 265 foram submetidas a biópsia por agulha grossa e 106, a marcação pré-cirúrgica. RESULTADOS: Em relação às mamografias, 11,32% foram classificadas como categoria 3, 76,28% como categoria 4 e 12,4% como categoria 5. Os resultados histológicos demonstraram 24% de exames positivos para malignidade. Os valores preditivos positivos das categorias 3, 4 e 5 foram, respectivamente, de 7,14%, 16,96% e 82,61%. Foram calculados os valores preditivos positivos, separadamente, para as biópsias percutâneas (7,14%, 15,76%, 76,47%) e para as marcações pré-cirúrgicas (7,14%, 20%, 100%). CONCLUSÃO: Achados malignos foram subestimados pelo laudo radiológico e houve superestimação de achados benignos, o que resultou na realização desnecessária de alguns procedimentos invasivos.

Aesthetic breast augmentation with hyaluronic acid: imaging findings and implications for radiological assessment

New injectable fillers such as hyaluronic acid have recently been employed as a non-surgical alternative to implants such as silicone for aesthetic breast enhancement. Although their utilization is not yet widespread in Brazil, radiologists should be aware of the imaging findings in this context and of the implications of the presence of this filler for the radiological evaluation in the screening for breast cancer.

Positive predictive values of Breast Imaging Reporting and Data System (BI-RADS®) categories 3, 4 and 5 in breast lesions submitted to percutaneous biopsy

Objective To evaluate the BI-RADS as a predictive factor of suspicion for malignancy in breast lesions by correlating radiological with histological results and calculating the positive predictive value for categories 3, 4 and 5 in a breast cancer reference center in the city of São Paulo. Materials and Methods Retrospective, analytical and cross-sectional study including 725 patients with mammographic and/or sonographic findings classified as BI-RADS categories 3, 4 and 5 who were referred to the authors' institution to undergo percutaneous biopsy. The tests results were reviewed and the positive predictive value was calculated by means of a specific mathematical equation. Results Positive predictive values found for categories 3, 4 and 5 were respectively the following: 0.74%, 33.08% and 92.95%, for cases submitted to ultrasound-guided biopsy, and 0.00%, 14.90% and 100% for cases submitted to stereotactic biopsy. Conclusion The present study demonstrated high suspicion for malignancy in lesions classified as category 5 and low risk for category 3. As regards category 4, the need for systematic biopsies was observed.

Complete internal audit of a mammography service in a reference institution for breast imaging

Objective Undertaking of a complete audit of the service of mammography, as recommended by BI-RADS®, in a private reference institution for breast cancer diagnosis in the city of São Paulo, SP, Brazil, and comparison of results with those recommended by the literature. Materials and Methods Retrospective, analytical and cross-sectional study including 8,000 patients submitted to mammography in the period between April 2010 and March 2011, whose results were subjected to an internal audit. The patients were followed-up until December 2012. Results The radiological classification of 7,249 screening mammograms, according to BI-RADS, was the following: category 0 (1.43%), 1 (7.82%), 2 (80.76%), 3 (8.35%), 4 (1.46%), 5 (0.15%) and 6 (0.03%). The breast cancer detection ratio was 4.8 cases per 1,000 mammograms. Ductal carcinoma in situ was found in 22.8% of cases. Positive predictive values for categories 3, 4 and 5 were 1.3%, 41.3% and 100%, respectively. In the present study, the sensitivity of the method was 97.1% and specificity, 97.4%. Conclusion The complete internal audit of a service of mammography is essential to evaluate the quality of such service, which reflects on an early breast cancer detection and reduction of mortality rates.

Avaliação de microcalcificações mamárias de acordo com as classificações do Breast Imaging Reporting and Data System (BI-RADS TM) e de Le Gal

OBJETIVO: avaliar a acurácia da mamografia para o diagnóstico de microcalcificações mamárias suspeitas, com as classificações do Breast Imaging Reporting and Data System (BI-RADS TM) e Le Gal em comparação com o resultado histopatológico utilizado como padrão-ouro. MÉTODOS: foram selecionados dos arquivos dos blocos cirúrgicos, 130 casos operados com mamografias contendo somente microcalcificações mamárias, inicialmente classificadas como suspeitas sem lesões detectáveis ao exame clínico. Estas foram reclassificadas por dois examinadores, utilizando as classificações de Le Gal e BI-RADS TM, obtendo-se diagnóstico de consenso. As biópsias foram revistas por dois patologistas e foi obtido diagnóstico de consenso. A leitura das mamografias e a revisão das lâminas foram feitas em duplo-cego. As análises estatísticas utilizadas neste estudo foram o teste do chi2, o modelo Fleiss quadrático para VPP e o programa Epi-Info 6.0. RESULTADOS: a correlação entre a análise histopatológica e mamográfica, usando BI-RADS TM e Le Gal, mostrou a mesma sensibilidade de 96,4%, especificidade de 55,9 e 30,3%, valor preditivo positivo (VPP) de 37,5% e 27,5% e acurácia de 64,6 e 44,6%, respectivamente. Quando discriminamos por categorias de BI-RADS TM, obtivemos VPPs: categoria 2, 0%; categoria 3, 1,8%; categoria 4, 31,6% e categoria 5, 60%. Os VPPs pela classificação de Le Gal foram: categoria 2, 3,1%; categoria 3, 18,1 %; categoria 4, 26,4%; categoria 5, 66,7% e não classificável, 5,2%. CONCLUSÕES: observou-se uma maior precisão com a classificação de BI-RADS TM, porém não se conseguiu reduzir a ambigüidade na avaliação das microcalcificações mamárias.

Quantitative ultrasound imaging during shear wave propagation for application related to breast cancer diagnosis

Dans le contexte de la caractérisation des tissus mammaires, on peut se demander ce que l’examen d’un attribut en échographie quantitative (« quantitative ultrasound » - QUS) d’un milieu diffusant (tel un tissu biologique mou) pendant la propagation d’une onde de cisaillement ajoute à son pouvoir discriminant. Ce travail présente une étude du comportement variable temporel de trois paramètres statistiques (l’intensité moyenne, le paramètre de structure et le paramètre de regroupement des diffuseurs) d’un modèle général pour l’enveloppe écho de l’onde ultrasonore rétrodiffusée (c.-à-d., la K-distribution homodyne) sous la propagation des ondes de cisaillement. Des ondes de cisaillement transitoires ont été générés en utilisant la mèthode d’ imagerie de cisaillement supersonique ( «supersonic shear imaging » - SSI) dans trois fantômes in-vitro macroscopiquement homogènes imitant le sein avec des propriétés mécaniques différentes, et deux fantômes ex-vivo hétérogénes avec tumeurs de souris incluses dans un milieu environnant d’agargélatine. Une comparaison de l’étendue des trois paramètres de la K-distribution homodyne avec et sans propagation d’ondes de cisaillement a montré que les paramètres étaient significativement (p < 0,001) affectès par la propagation d’ondes de cisaillement dans les expériences in-vitro et ex-vivo. Les résultats ont également démontré que la plage dynamique des paramétres statistiques au cours de la propagation des ondes de cisaillement peut aider à discriminer (avec p < 0,001) les trois fantômes homogènes in-vitro les uns des autres, ainsi que les tumeurs de souris de leur milieu environnant dans les fantômes hétérogénes ex-vivo. De plus, un modéle de régression linéaire a été appliqué pour corréler la plage de l’intensité moyenne sous la propagation des ondes de cisaillement avec l’amplitude maximale de déplacement du « speckle » ultrasonore. La régression linéaire obtenue a été significative : fantômes in vitro : R2 = 0.98, p < 0,001 ; tumeurs ex-vivo : R2 = 0,56, p = 0,013 ; milieu environnant ex-vivo : R2 = 0,59, p = 0,009. En revanche, la régression linéaire n’a pas été aussi significative entre l’intensité moyenne sans propagation d’ondes de cisaillement et les propriétés mécaniques du milieu : fantômes in vitro : R2 = 0,07, p = 0,328, tumeurs ex-vivo : R2 = 0,55, p = 0,022 ; milieu environnant ex-vivo : R2 = 0,45, p = 0,047. Cette nouvelle approche peut fournir des informations supplémentaires à l’échographie quantitative statistique traditionnellement réalisée dans un cadre statique (c.-à-d., sans propagation d’ondes de cisaillement), par exemple, dans le contexte de l’imagerie ultrasonore en vue de la classification du cancer du sein.

Refraction corrected transmission ultrasound computed tomography for application in breast imaging

Purpose: We present an iterative framework for CT reconstruction from transmission ultrasound data which accurately and efficiently models the strong refraction effects that occur in our target application: Imaging the female breast. Methods: Our refractive ray tracing framework has its foundation in the fast marching method (FNMM) and it allows an accurate as well as efficient modeling of curved rays. We also describe a novel regularization scheme that yields further significant reconstruction quality improvements. A final contribution is the development of a realistic anthropomorphic digital breast phantom based on the NIH Visible Female data set. Results: Our system is able to resolve very fine details even in the presence of significant noise, and it reconstructs both sound speed and attenuation data. Excellent correspondence with a traditional, but significantly more computationally expensive wave equation solver is achieved. Conclusions: Apart from the accurate modeling of curved rays, decisive factors have also been our regularization scheme and the high-quality interpolation filter we have used. An added benefit of our framework is that it accelerates well on GPUs where we have shown that clinical 3D reconstruction speeds on the order of minutes are possible.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

Suspicious axillary lymph nodes in patients with unremarkable imaging of the breast

The aim of this study was to evaluate the pathological findings and the method of tissue harvesting in those patients who have both suspicious axillary lymph nodes and normal imaging of the breast.

Multicenter, double-blind, randomized, intraindividual crossover comparison of gadobenate dimeglumine and gadopentetate dimeglumine for Breast MR imaging (DETECT Trial)

To intraindividually compare 0.1 mmol/kg doses of gadobenate dimeglumine and gadopentetate dimeglumine for contrast material-enhanced breast magnetic resonance (MR) imaging by using a prospective, multicenter double-blind, randomized protocol.