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Resumen La mamografía contrastada (CEDM, contrast-enhanced digital mammography) es una herramienta nueva que ha ido implementándose de forma creciente. Aparece como alternativa a la resonancia magnética (RM), y al igual que esta, tiene como principio el uso de contraste endovenoso para explorar la angiogénesis tumoral. Combina la imagen de mamografía convencional (Mx) con la técnica de sustracción con energía dual poscontraste, lo que resulta en un incremento en la detección de cáncer de mama, en un tiempo corto de estudio y a un bajo costo. Es un método prometedor en casos seleccionados y de fácil lectura, siendo útil principalmente en pacientes con diagnóstico de cáncer de mama para detectar lesiones adicionales y determinar el tamaño tumoral, ayudando en la planificación quirúrgica, así como también en la evaluación de la respuesta a la neoadyuvancia. También en el seguimiento de pacientes operadas, para caracterizar lesiones dudosas en Mx y ecografía, o como alternativa ante contraindicación de la RM. El objetivo de este trabajo es valorar la utilidad de la mamografía contrastada en la práctica diaria y determinar sus principales indicaciones. Repasamos con casos propios las utilidades y características del método.
Abstract Contrast-enhanced digital mammography (CEDM) is an emerging tool that has been increasingly implemented. It appears as an alternative to magnetic resonance imaging (MRI), using intravenous contrast to explore tumor angiogenesis. It combines conventional mammography (Mx) with post-contrast dual energy subtraction technique, resulting in increased detection of breast cancer, in a short study time and at a low cost. It is a promising method in selected cases and easy to read, being useful mainly in patients with breast cancer to detect additional lesions and determine the tumor size, that helps surgical planning, as well as in the evaluation of post-neoadjuvant chemotherapy response in the follow-up of patients treated with surgery, to address inconclusive findings in screening mammogram, or as an alternative when MRI is contraindicated. The purpose of this article is to assess the usefulness of contrasted mammography in daily practice and to determine its main indications. We review with our own cases the applications and characteristics of this method.
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Objective To investigate the average glandular dose of digital mammography in Zigong, China, and to explore the methods of reducing average glandular dose. Methods A total of 260 patients who underwent digital mammography at six hospitals located in Zigong during the year 2022 were included in this study. Their personal information, photography position, breast compression thickness, exposure parameters, and average glandular dose were collected. Analysis of variance and correlation analysis were performed for data analysis. Results Among the 260 patients who underwent digital mammography, the average breast compression thickness was 46.3 mm and the average glandular dose was 1.70 mGy. There was a significant difference in average glandular dose between patients with different breast compression thickness(P <0.05), and average glandular dose was positively correlated with breast compression thickness. There were no significant differences in average glandular dose between patients with different photography positions and patients with different ages (P>0.05). Conclusion The average glandular dose of patients undergoing digital mammography is at an acceptable level in Zigong. The average glandular dose is impacted by the breast compression thickness, target/filter, and exposure parameters. These factors should be optimized to reduce glandular dose during digital mammography.
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Objective:To compare radiation dose between digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM), and explore the correlation of average glandular dose(AGD) with breast density and compression thickness.Methods:The mammographic data of patients with breast diseases who underwent digital breast tomosynthesis (DBT) and the population who underwent full-field digital mammography (FFDM) screening in the First Affiliated Hospital of Kunming Medical University from October 2020 to May 2022 were retrospectively collected. The compression thickness, compression force and AGD were recorded. According to the 2013 ACR BI-RADS MAMMOGRAPHY, the breast gland density was classified into 4 types: a(glandular tissue<25%), b(glandular tissue 25%~50%), c(glandular tissue 50%~75%) and d(glandular tissue >75%), by two senior doctors engaged in breast imaging diagnosis. The relationships between different gland densities, different compression thicknesses and AGD under FFDM and DBT mode were analyzed.Results:In both FFDM and DBT modes, the AGD increased significantly with the increase of breast density( F=861.63, 617.83, 330.33, 451.45, 290.47, P<0.001), and AGD a<AGD b<AGD c<AGD d. For type c and d breasts undergoing FFDM, AGD was lowest when the compression thickness was 31~40 mm. Under the same compression thickness, The AGD DBT was significantly higher than the AGD FFDMin all types (Type a: t=-17.88, -42.19, -29.90, -28.14, -24.95, P<0.001; Type b: t=-49.18, -35.94, -27.25, -28.37, -24.10, P<0.001; Type c: t=-11.78, -32.90, -23.13, -20.51, -18.24, P<0.001; Type d: t=-7.94, -26.24, -17.24, -15.44, -13.81, P<0.001). The difference between two AGDs of Type d with compression thickness of 61~70 mm was the largest, which was 1.07 mGy (95% CI: 0.92~1.22). The AGD was positively correlated with breast density and compression thickness, and the relationship of FFDM was stronger than that of DBT. Conclusions:The AGD is positively correlated with breast density and compression thickness in mammography. Compared with FFDM, DBT can increase AGD, The AGD would increase in DBT than FFDM but be safe. DBT would be beneficial to patients with breast diseases in clinical practice.
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BACKGROUND: Mammograms are one of the most effective preventive means for the early detection of breast cancer. OBJECTIVE: To describe the features of patients and results of mammograms performed at a public breast imaging service of the Santiago Metropolitan Area. MATERIAL AND METHODS: We reviewed the reports of mammograms performed on 174,017 women and 18 men, between 2008 and 2018 in an Imaging Center. The BI-RADS classification was used in the reports. RESULTS: Forty-six percent of mammograms (75,781) were reported as BI-RADS 2. The high proportion of BI-RADS 4 reports (674 reports) was seen in patients aged 40 to 49 years, corresponding to 30% of reports in this age range. Among patients aged 50 to 59 years, there were 779 BI-RADS 4 reports (35%). BI-RADS 5 reports were more common among patients aged 50 to 59 years (50 reports, 30%) and among patients aged 70 years or older (83 reports, 28%). CONCLUSIONS: The presence of a significant number of women between 40 and 49 years of age with a BI-RADS 4 mammography result stands out; being an opportunity to develop new clinical research and public health strategies within the framework of the Universal Health Care policy for breast cancer in Chile.
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Humans , Male , Female , Adult , Middle Aged , Breast Neoplasms/epidemiology , Breast Neoplasms/diagnostic imaging , Mammography/methods , Chile/epidemiologyABSTRACT
Objective:To evaluate the effect of reducing mAs on image quality when different target/filter combinations are used in digital mammography.Methods:In different target/filter combinations, based on the mAs of automatic exposure control(AEC), the reduction of mAs by 10%, 20%, 30%, 40% and 50% respectively were used to expose the phantom with 4.4 cm thickness. The contrast to noise ratio(CNR), signal to noise ratio(SNR), figure of merit(FOM)and average glandular dose(AGD) of the resulting image were calculated. While the image quality was ensured, the optimal mAs and the corresponding AGD under the two target/filter combination were conducted by calculating the FOM. The image features of three tissues of phantom were subjectively evaluated, and the relationship between the calculated AGD and displayed AGD was compared. The mAs that meets the image quality requirements is corresponded with the density exposure gear, and the average values of the mAs for two method were calculated and compared.Results:In two targets/filters combinations, the displayed AGD was less than the calculated AGD, and Mo/Mo was underestimated by 22.5% to 23.7%. The calculated and displayed AGD values were statistically different ( F=4 982.86, 5 555.48, P<0.05). W/Rh was underestimated by 13.1% to 14.2%. The calculated and displayed AGD values were statistically different ( F=18 859.09, 15 973.55, P<0.05). In the Mo/Mo combination, when the mAs was reduced by 20%, the FOM could be increased by 9.6% for the maximum value, and the calculated AGD was decreased by 18.8%. In the W/Rh combination, when the mAs was reduced by 10%, the FOM was increased by 5.1% for the maximum value, and the calculated AGD was decreased by 11.9%. While the image quality was ensured, the mAs was reduced by 30% for evaluating simulated fibers, and by 20% for evaluating simulated specks in the two targets/filter combinations. For evaluating simulated masses, Mo/Mo combination reduced the mAs by 40%, and the W/Rh combination reduced the mAs by 30%. And the image quality scores in above were not significantly different from those in AEC method ( P>0.05). The density exposure gear(-1 to -3) could correspond with the reduced mAs(10%-30%). Conclusions:Under different target/filter combination, the tube mAs could be reduced when the image quality was ensured.
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Recently, breast cancer is one of the most popular cancers that women could suffer from. The gravity and seriousness of breast cancer can be evidenced by the fact that the mortality rates associated with it are the second highest after lung cancer. For the treatment of breast cancer, Mammography has emerged as the one whose modality when it comes to the defection of this cancer is most effective despite the challenges posed by dense breast parenchyma. In thisregard, computer-aided diagnosis (CADe) leverages the mammography systems’ output to facilitate the radiologist’s decision. It can be defined as a system that makes a similar diagnosis to the one done by a radiologist who relies for his/her interpretationon the suggestions generated by a computer after it analyzed a set of patient radiological images when making. Against this backdrop, the current paper examines different ways of utilizing known image processing and techniques of machine learning detection of breast cancer using CAD –more specifically, using mammogram images. This, in turn, helps pathologist in their decision-making process. For effective implementation of this methodology, CADe system was developed and tested on the public and freely available mammographic databases named MIAS database. CADe system is developed to differentiate between normal and abnormal tissues, and it assists radiologists to avoid missing breast abnormalities. The performance of all classifiers is the best by using thesequential forward selection (SFS) method. Also, we can conclude that the quantization grey level of (gray-level co-occurrence matrices) GLCM is a very significant factor to get robust high order features where the results are better with L equal to the size of ROI. Using an enormous number of several features assist the CADe system to be strong enough to distinguish between the different tissues
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Objective The aim of this study was to investigate FFDM differential diagnosis between breast mastitis,benign hyperplasia and breast cancer. Methods Fifty-nine cases of non-puerperal breast mastitis,sixty-eight cases of benign hyperpla-sia and two hundred and forty cases with non-mass type breast cancer were analyzed retrospectively,which were verified by surgery and pathology by contrast with FFDM signs,pathological types,grouped and statistics processed. The observation indexes of lamellar shadow included shape,density and edge. The observation indexes of linear shadow included direction,form and diameter. Results The FFDM signs in three groups of breast diseases were statistically significant(P<0. 05):the form of linear shadow,accompanied by calcifications,the shape of lamellar shadow,the direction of linear shadow,the distribution of lesion,the sharp angle of shadow edge. χ2 segmentation show that there were significant differences between three groups(P<0. 0125):the shape of lamellar shadow,the direc-tion of linear shadow. Conclusion There have some values for the diagnosis of breast cancer by rigid form and radial distribution of linear shadow,rigid shape and segmental distribution of lamellar shadow,the polymorphic calcifications and the sharp angle sign.
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OBJECTIVE@#To develop a deep features-based model to classify benign and malignant breast lesions on full- filed digital mammography.@*METHODS@#The data of full-filed digital mammography in both craniocaudal view and mediolateral oblique view from 106 patients with breast neoplasms were analyzed. Twenty-three handcrafted features (HCF) were extracted from the images of the breast tumors and a suitable feature set of HCF was selected using -test. The deep features (DF) were extracted from the 3 pre-trained deep learning models, namely AlexNet, VGG16 and GoogLeNet. With abundant breast tumor information from the craniocaudal view and mediolateral oblique view, we combined the two extracted features (DF and HCF) as the two-view features. A multi-classifier model was finally constructed based on the combined HCF and DF sets. The classification ability of different deep learning networks was evaluated.@*RESULTS@#Quantitative evaluation results showed that the proposed HCF+DF model outperformed HCF model, and AlexNet produced the best performances among the 3 deep learning models.@*CONCLUSIONS@#The proposed model that combines DF and HCF sets of breast tumors can effectively distinguish benign and malignant breast lesions on full-filed digital mammography.
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Female , Humans , Breast Neoplasms , Classification , Diagnostic Imaging , Deep Learning , Diagnosis, Computer-Assisted , Methods , Mammography , MethodsABSTRACT
Objective To compare the values of dynamic enhanced magnetic resonance imaging(DCE-MRI),digital breast tomosynthesis(DBT),and digital mammography(DM)in the early detection and diagnosis of breast cancer.Methods We retrospectively analyzed the clinical and imaging data of 65 cases with early breast cancer confirmed by surgical pathology from June 2017 to December 2018.All patients underwent breast DCE-MRI,DM and DBT before surgery.The receiver operating characteristic(ROC)curves were drawn,with the pathological results as the gold standard,to evaluate the diagnostic performance of different examination methods.The areas under ROC curves(AUCs)were compared using test.The differences among DCE-MRI,DBT and DM in detecting early breast cancer were compared using chi-square test in terms of positive rates,accuracy,sensitivity,and specificity.Pearson correlation analysis was performed to assess the accuracy of these imaging methods in detecting the size of early breast cancer.Results The AUCs of DCE-MRI,DBT,and DM based on the BI-RADS classification for early diagnosis of breast cancer were 0.910,0.832,and 0.700,respectively(=2.132,=0.001);the sensitivity of DCE-MRI,DBT,and DM for early breast cancer was 92.3%,70.8%,and 52.5%,the specificity was 65.0%,85.0%,and 79.3%,and the accuracy was 83.1%,70.8%,and 50.8%,indicating that DCE-MRI(=15.330,=0.0001) and DBT(=5.450,=0.020) had significantly higher diagnostic accuracy than DM.The measurement results of DM,DBT,and DCE-MRI were positively correlated with the pathological measurements(=0.781,=0.847,=0.946;all <0.01). Conclusions DCE-MRI and DBT have higher positive rates and accuracies than DM in detecting early breast cancer.Medical institutions where DCE-MRI is still not available can use DBT to improve the early detection of breast cancer.
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Female , Humans , Breast , Diagnostic Imaging , Breast Neoplasms , Diagnostic Imaging , Magnetic Resonance Imaging , Mammography , Methods , Retrospective StudiesABSTRACT
OBJECTIVE: To investigate the effects of different types of mammography equipment on screening outcomes by comparing the performance of film-screen mammography (FSM), computed radiography mammography (CRM), and digital mammography (DM).MATERIALS AND METHODS: We retrospectively enrolled 128756 sets of mammograms from 10 hospitals participating in the Alliance for Breast Cancer Screening in Korea between 2005 and 2010. We compared the diagnostic accuracy of the types of mammography equipment by analyzing the area under the receiver operating characteristic curve (AUC) with a 95% confidence interval (CI); performance indicators, including recall rate, cancer detection rate (CDR), positive predictive value₁ (PPV₁), sensitivity, specificity, and interval cancer rate (ICR); and the types of breast cancer pathology.RESULTS: The AUCs were 0.898 (95% CI, 0.878–0.919) in DM, 0.860 (0.815–0.905) in FSM, and 0.866 (0.828–0.903) in CRM (p = 0.150). DM showed better performance than FSM and CRM in terms of the recall rate (14.8 vs. 24.8 and 19.8%), CDR (3.4 vs. 2.2 and 2.1 per 1000 examinations), PPV₁ (2.3 vs. 0.9 and 1.1%), and specificity (85.5 vs. 75.3 and 80.3%) (p < 0.001) but not in terms of sensitivity (86.3 vs. 87.4 and 86.3%) and ICR (0.6 vs. 0.4 and 0.4). The proportions of carcinoma in situ (CIS) were 27.5%, 13.6%, and 11.8% for DM, CRM, and FSM, respectively (p = 0.003).CONCLUSION: In comparison to FSM and CRM, DM showed better performance in terms of the recall rate, CDR, PPV₁, and specificity, although the AUCs were similar, and more CISs were detected using DM. The application of DM may help to improve the quality of mammography screenings. However, the overdiagnosis issue of CIS using DM should be evaluated.
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Area Under Curve , Breast Neoplasms , Breast , Carcinoma in Situ , Korea , Mammography , Mass Screening , Medical Overuse , Pathology , Radiography , Retrospective Studies , ROC Curve , Sensitivity and SpecificityABSTRACT
Objective To investigate the diagnostic value of full-field digital mammography (FFDM) combined with three-dimentional digital breast tomosynthesis (3D-DBT) in the lesions of dense breast mass. Methods A total of 121 patients with breast mass (135 lesions) in Shanxi Provincial People's Hospital from January 2018 to May 2018 were retrospectively analyzed. The differences of FFDM combined with 3D-DBT technique and FFDM alone in the diagnosis of dense breast mass lesions were compared and analyzed by using American Radiological Society's Breast Imaging Reporting and Data System (BI-RADS) grading diagnosis, and then the pathological results were compared. Results The sensitivity, accuracy rate and specificity of FFDM combined with 3D-DBT in the diagnosis of breast cancer among 135 lesions was 97.3％ (36/37), 80.0％ (108/135) and 73.5％ (72/98), respectively. The sensitivity, accuracy rate and specificity of FFDM in the diagnosis of breast cancer was 86.5％ (32/37), 70.4％ (95/135) and 64.3％ (63/98), respectively. Area under the receiver operating characteristic curve of FFDM combined with 3D-DBT was higher than that of FFDM alone (0.854 vs. 0.754). Compared with FFDM, mass diameter measured by 3D-DBT was close to the pathological results. The detection rates of mass, burr features and suspected malignant aggregation calcification by using FFDM combined with 3D-DBT were superior than those by using FFDM [100.0％ (72/72) vs. 81.9％ (59/72), 52.8％ (19/36) vs. 41.7％ (15/36), 75.0％ (27/36) vs. 66.7％ (24/36), respectively]. Conclusions For the focal mass of compact glands, compared with FFDM alone, the accuracy rate of the mass measurement, the detection rate of the suspected mass, the malignant mass burr, and themicro-calcification of aggregation treated by FFDM combined with 3D-DBT have been increased in a varying degree.
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Abstract Objective: To evaluate suspicious amorphous calcifications diagnosed on full-field digital mammography (FFDM) and establish correlations with histopathology findings. Materials and Methods: This was a retrospective study of 78 suspicious amorphous calcifications (all classified as BI-RADS® 4) detected on FFDM. Vacuum-assisted breast biopsy (VABB) was performed. The histopathological classification of VABB core samples was as follows: pB2 (benign); pB3 (uncertain malignant potential); pB4 (suspicion of malignancy); and pB5 (malignant). Treatment was recommended for pB5 lesions. To rule out malignancy, surgical excision was recommended for pB3 and pB4 lesions. Patients not submitted to surgery were followed for at least 6 months. Results: Among the 78 amorphous calcifications evaluated, the histopathological analysis indicated that 8 (10.3%) were malignant/suspicious (6 classified as pB5 and 2 classified as pB4) and 36 (46.2%) were benign (classified as pB2). The remaining 34 lesions (43.6%) were classified as pB3: 33.3% were precursor lesions (atypical ductal hyperplasia, lobular neoplasia, or flat epithelial atypia) and 10.3% were high-risk lesions. For the pB3 lesions, the underestimation rate was zero. Conclusion: The diagnosis of precursor lesions (excluding atypical ductal hyperplasia, which can be pB4 depending on the severity and extent of the lesion) should not necessarily be considered indicative of underestimation of malignancy. Suspicious amorphous calcifications correlated more often with precursor lesions than with malignant lesions, at a ratio of 3:1.
Resumo Objetivo: Correlacionar o achado mamográfico de calcificações amorfas suspeitas diagnosticadas na mamografia digital com seus diagnósticos anatomopatológicos. Materiais e Métodos: Setenta e oito casos de calcificações amorfas suspeitas (todas classificadas como BI-RADS® 4) detectadas na mamografia digital e submetidas a biópsia percutânea assistida à vácuo foram retrospectivamente avaliados. A classificação anatomopatológica utilizada na biópsia foi: pB2 para lesão benigna, pB3 para lesão com potencial incerto de malignidade, pB4 para lesão suspeita, e pB5 para lesão considerada maligna. O tratamento foi recomendado para as lesões pB5, a exérese cirúrgica foi indicada para lesões pB3 e pB4, para descartar malignidade, e o seguimento evolutivo foi adotado para as demais pacientes. Resultados: A histologia demonstrou 8 (10,3%) casos malignos (6 lesões pB5 e 2 lesões pB4) e 36 (46,2%) casos benignos (pB2). As demais 34 (43,6%) lesões foram classificadas como pB3 (33,3% foram lesões precursoras - hiperplasia ductal atípica, neoplasia lobular ou atipia epitelial plana - e 10,3% foram lesões de alto risco). A taxa de subestimação das lesões pB3 foi zero. Conclusão: O diagnóstico de lesões precursoras (excluindo hiperplasia ductal atípica, que pode corresponder a lesão pB4 dependendo da severidade e extensão dos achados) na biópsia percutânea assistida à vácuo por calcificações amorfas suspeitas não necessariamente representa lesão subestimada. Calcificações amorfas suspeitas se associaram a lesões precursoras numa proporção de 3:1 em relação às lesões malignas.
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Objective To explore the diagnostic value of calcification by full field digital mammography in cases without breast palpable lumps or nodules in ductal carcinoma in situ(DC1S).Methods Based on breast imaging-reporting and data system (BI-RADS)proposed by the American College of Radiology (ACR),the cases without palpable lumps or nodules,but with calcification (over Category 4a)found by full field digital mammography admitted from Oct.2014 to Oct.2016 were analyzed.They underwent excisional biopsy after three-dimensional guide wire positioning or three-dimensional vacuum rotary cutting.After being filmed again to make sure the resection was complete,the isolated specimen were sent to pathological examination.The pathology and calcification were analyzed and summarized.Results Among 126 cases,71 (56.3％)were breast adenosis,41 (32.5％) were DCIS,6(4.8％) were infiltrating ductal carcinoma (IDC),and 8 (6.3％)were other types.The detection rate of DCIS in younger group was higher.The calcifications in DCIS were mostly linear-branching,segmental calcification,and those in IDC were mostly pleomorphic,clustering or regional calcification.Conclusion Full field digital mammography has great diagnostic value for DCIS in cases with calcification but without palpable breast lumps or nodules.
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Abstract Introduction Breast cancer is the first leading cause of death for women in Brazil as well as in most countries in the world. Due to the relation between the breast density and the risk of breast cancer, in medical practice, the breast density classification is merely visual and dependent on professional experience, making this task very subjective. The purpose of this paper is to investigate image features based on histograms and Haralick texture descriptors so as to separate mammographic images into categories of breast density using an Artificial Neural Network. Methods We used 307 mammographic images from the INbreast digital database, extracting histogram features and texture descriptors of all mammograms and selecting them with the K-means technique. Then, these groups of selected features were used as inputs of an Artificial Neural Network to classify the images automatically into the four categories reported by radiologists. Results An average accuracy of 92.9% was obtained in a few tests using only some of the Haralick texture descriptors. Also, the accuracy rate increased to 98.95% when texture descriptors were mixed with some features based on a histogram. Conclusion Texture descriptors have proven to be better than gray levels features at differentiating the breast densities in mammographic images. From this paper, it was possible to automate the feature selection and the classification with acceptable error rates since the extraction of the features is suitable to the characteristics of the images involving the problem.
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Objective To test the spatial resolution and average glandular dose (AGD) of full field digital mammography system to obtain high-resolution and contrast breast X-ray images with the lowest dose.Methods The M12 breast X-ray performance test phantom was placed on the breast support center position,then line-pair card was put on the M12 phantom and fixed groove,and exposure was carried out with auto exposure control,28 kV tube voltage and common anode filtration combination so as to detect the spatial resolution.Half-value layer (HVL) was measured by Fluke TNT12000 ray detection tools,2 mm-thickness plate and aluminum sheets with different thicknesses,and then AGD was calculated accordingly.Results The spatial resolutions were all higher than 7 lp/mm and proved to meet the quality standard,which had the vertical spatial resolution being 8 lp/mm,the maximum value of the lateral spatial resolution being 10 lp/mm and the minimum value being 8 lp/mm.AGD was lower than 2 mGy and then proved qualified which was limited within 0.60 and 0.61 mGy.Conclusion The test of spatial resolution and AGD of full digital mammography system can assess the performance and radiation dose,reflect the performance of equipment,ensure image quality and lower radiation dose.
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Objective To test the spatial resolution and average glandular dose (AGD) of full field digital mammography system to obtain high-resolution and contrast breast X-ray images with the lowest dose.Methods The M12 breast X-ray performance test phantom was placed on the breast support center position,then line-pair card was put on the M12 phantom and fixed groove,and exposure was carried out with auto exposure control,28 kV tube voltage and common anode filtration combination so as to detect the spatial resolution.Half-value layer (HVL) was measured by Fluke TNT12000 ray detection tools,2 mm-thickness plate and aluminum sheets with different thicknesses,and then AGD was calculated accordingly.Results The spatial resolutions were all higher than 7 lp/mm and proved to meet the quality standard,which had the vertical spatial resolution being 8 lp/mm,the maximum value of the lateral spatial resolution being 10 lp/mm and the minimum value being 8 lp/mm.AGD was lower than 2 mGy and then proved qualified which was limited within 0.60 and 0.61 mGy.Conclusion The test of spatial resolution and AGD of full digital mammography system can assess the performance and radiation dose,reflect the performance of equipment,ensure image quality and lower radiation dose.
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Objective To compare the accuracy of full field digital mammography (FFDM) and digital breast tomosynthesis (DBT) in predicting size of ductal carcinoma in situ (DCIS).Methods Totally 30 women pateints with DCIS confirmed by histology were analyzed retrospectively.Two radiologists measured the size of the lesions on FFDM,DBT images respectively,and compared with pathological results.Two kinds of inspection methods correlation with pathology were compared with Pearson correlation analysis.Results Size of DCIS measured by doctor 1 and doctor 2 between FFDM and histology had correlation (r=0.857,0.818,both P＜0.01),and those between DBT and histology also had correlation (r=0.924,0.885,both P＜0.01).Intraclass correlation coefficient (ICC) of two doctors was 0.947 on FFDM,and 0.908 on DBT.Conclusion DBT provides a better estimation of the size of DCIS.Two physicians had high consistency for lesion size evaluation.For DCIS with microcalcifications,both FFDM and DBT provide smaller estimations compared with pathology,thus a bigger surgical resection of lesion is needed.
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Objective To evaluate the clinical value of full-field digital mammography three-dimensional (3D) positioning system for localization and excision of nonpalpable breast lesions.Methods 106 patients with nonpalpable breast lesions and underwent preoperative localization were analyzed retrospectively.They underwent wire-localization operation guided by mammography 3D positioning system (GE Senogrphe DS).The depth of wire insertion was calculated manually and automatically.Combined with the manual measurement, systematic measurement, skin elasticity and breast parenchyma structure, the positioning wire was placed.Then, the clinical resection was performed according to the wire localization.Results The localization accuracy of mammography 3D positioning system was 100%.11 patients appearedsyncope.With the rest, psychological comfort and fluid infusion, patients recovered quickly.Conclusion Full-field digital mammography 3D positioning system can improve the accuracy of clinical resection of nonpalpable breast lesion.
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Background and purpose:Breast cancer is the most common malignancy in women. The new technology of mammography is helpful in breast cancer diagnosis. This study aimed to compare the efficacy of digital breast tomosynthesis (DBT) with conventional imaging methods in the diagnosis of benign and malignant breast lesions.Methods:During the period from Mar. 2015 to Dec. 2015, 227 patients with suspected lesions (by palpation or sonography) underwent further imaging exam in our hospital. The sonography, full-field digital mammography (FFDM), DBT and breast MRI were performed on all the patients. A double-blind assessment was carried out according to BI-RADS (version 2013) by experienced radiologists. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficiency of all methods, referring to the pathological data as the golden standard; the difference in the efficiency of DBT from the other methods was determined byZ-test.Results:Thirty patients were excluded for the unsatisfactory images, and 205 lesions (132 malignant and 73 benign lesions) were detected in the remaining 197 patients. Area under the curve (AUC) of sonography, FFDM, DBT, DBT+FFDM and MRI based on the BI-RADS were 0.8308, 0.8592, 0.9167, 0.9198, and 0.9354, respectively. The AUC of DBT was significantly higher than those of sonography (Z=7.36,P=0.0067) and FFDM (Z=4.89,P=0.0271), while there was no significantly difference between DBT and MRI (Z=0.02,P=0.9002) or FFDM+DBT (Z=0.69,P=0.4048).Conclusion:DBT could significantly improve the diagnostic performance for breast lesions compared with sonography and FFDM, providing a comparable efficiency to MRI. As a new mammography technology, DBT has good clinical application prospect.
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Objective@#To assess the value of digital breast tomosynthesis (DBT) in the diagnosis of breast lesions.@*Methods@#Two hundred and fifty-three breast lesions in 250 patients were selected in this study. All lesions were confirmed pathologically. Preoperative diagnosis was performed independently with full-field digital mammography (FFDM), DBT and DBT plus FFDM, respectively. The diagnostic value of DBT for breast lesions was evaluated based on the pathological diagnosis as the gold standard. The diagnostic performance of DBT and FFDM for breast lesions was compared between the groups with different ages, mammary gland densities and hormone levels. The sensitivity of DBT and FFDM was compared between the groups with different pathological types and different sizes of breast cancer. The correlation between the longest diameter of breast cancers and pathological measurements shown on DBT and FFDM was analyzed.@*Results@#The areas under ROC curves were 0.890, 0.833 and 0.890 for DBT, FFDM and DBT plus FFDM, respectively. The areas under ROC curves for DBT or DBT plus FFDM were significantly greater than that for FFDM (P<0.05). In the group with breast density>50%, group with age ≤50 and non-menopause group, all the areas under ROC curves for DBT or DBT plus FFDM were all significantly larger than that for FFDM (P<0.05). No significant differences were observed in the group with breast density ≤50%, group with age>50 and menopause group (P>0.05). The sensitivity for both DBT and FFDM in the diagnosis of carcinoma in situ was 90.9% (10/11). The sensitivity for DBT and FFDM in the diagnosis of non-carcinoma in situ was 92.3% (120/130) and 83.8% (109/130), respectively. The sensitivity in the groups with the longest diameter of foci >0 mm but ≤10 mm, >10 mm but ≤20 mm, >20 mm but ≤30 mm, and >30 mm but ≤40 mm were 51.7% (4/7), 93.8% (61/65), 96.7% (30/31) and 100% (11/11), respectively, for DBT, and were 51.7% (4/7), 78.5% (51/65), 93.5% (29/31), and 100% (11/11), respectively, for FFDM. The correlation coefficients between the longest diameter of breast cancers and pathological measurements shown on DBT and FFDM were 0.905 and 0.849, respectively (P<0.001).@*Conclusions@#Compared with FFDM, DBT shows a higher diagnostic efficiency in patients with breast density >50%, age ≤50 years and non-menopause, non-carcinoma in situ, and the longest diameter of lesions >10 mm but ≤ 20 mm. The longest diameter of breast lesions is more accurately shown on DBT.