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1.
Anticancer Res ; 41(9): 4423-4429, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34475064

RESUMO

AIM: To evaluate the image quality and time saving using simultaneous multi-slice (SMS)-accelerated T2-weighted turbo spin echo (TSE) sequences compared to standard T2 TSE sequences in breast magnetic resonance imaging (MRI). PATIENTS AND METHODS: Thirty patients were examined with an SMS-accelerated T2 TSE sequence and a standard T2 TSE sequence as part of a breast MRI protocol at 1.5T. Image quality, signal homogeneity and tissue delineation were evaluated. For quantitative assessment, the signal-to-noise ratio (SNR) was measured from representative SNR maps. RESULTS: There were no significant differences regarding tissue delineation and signal homogeneity. Image quality was rated equal at the chest wall and the breasts but decreased in the axilla on SMS-T2 TSE (p=0.01) with a simultaneous decrease of SNR (p=0.03). This did not significantly impact the overall image quality (p=0.2). The acquisition time for SMS-T2 TSE was 48% shorter compared to standard T2 TSE. CONCLUSION: SMS-acceleration for T2-weighted imaging of the breast at 1.5T substantially reduces acquisition time while maintaining comparable quantitative and qualitative image quality. This may pave the way for protocol abbreviation especially in a high-throughput clinical workspace.


Assuntos
Neoplasias da Mama/diagnóstico por imagem , Mama/diagnóstico por imagem , Imageamento por Ressonância Magnética/métodos , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Adulto , Idoso , Estudos de Viabilidade , Feminino , Humanos , Pessoa de Meia-Idade , Razão Sinal-Ruído
2.
J Int Med Res ; 49(9): 300060520973092, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34488484

RESUMO

OBJECTIVE: We compared the diagnostic values of mammography and magnetic resonance imaging (MRI) for evaluating breast masses. METHODS: We retrospectively analyzed mammography, MRI, and histopathological data for 377 patients with breast masses on mammography, including 73 benign and 304 malignant masses. RESULTS: The sensitivities and negative predictive values (NPVs) were significantly higher for MRI compared with mammography for detecting breast cancer (98.4% vs. 89.8% and 87.8% vs. 46.6%, respectively). The specificity and positive predictive values (PPV) were similar for both techniques. Compared with mammography alone, mammography plus MRI improved the specificity (67.1% vs. 37.0%) and PPV (91.8% vs. 85.6%), but there was no significant difference in sensitivity or NPV. Compared with MRI alone, the combination significantly improved the specificity (67.1% vs. 49.3%), but the sensitivity (88.5% vs. 98.4%) and NPV (58.3% vs. 87.8%) were reduced, and the PPV was similar in both groups. There was no significant difference between mammography and MRI in terms of sensitivity or specificity among 81 patients with breast masses with calcification. CONCLUSION: Breast MRI improved the sensitivity and NPV for breast cancer detection. Combining MRI and mammography improved the specificity and PPV, but MRI offered no advantage in patients with breast masses with calcification.


Assuntos
Mama , Mamografia , Mama/diagnóstico por imagem , Humanos , Imageamento por Ressonância Magnética , Estudos Retrospectivos , Sensibilidade e Especificidade
3.
BMJ Case Rep ; 14(9)2021 Sep 08.
Artigo em Inglês | MEDLINE | ID: mdl-34497052

RESUMO

Ectopic breast tissue (EBT) is relatively common and can occur along the milk line or mammary ridge and often outside this line. We report a case of a female patient presenting with a suprapubic mass for 2 years, found later to be EBT containing a fibroadenoma. We believe this is a very rare finding. Moreover, we highlight the importance of considering EBT in the differential diagnoses of soft tissue masses.


Assuntos
Doenças Mamárias , Neoplasias da Mama , Fibroadenoma , Axila , Mama/diagnóstico por imagem , Mama/cirurgia , Neoplasias da Mama/diagnóstico por imagem , Feminino , Fibroadenoma/diagnóstico por imagem , Fibroadenoma/cirurgia , Humanos
4.
J Coll Physicians Surg Pak ; 31(9): 1024-1029, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34500515

RESUMO

OBJECTIVE: To compare the effect of different quantification methods of ADC values in the evaluation of breast lesions and compare contralateral normal breast tissue ADC value by calculating ADC ratios. STUDY DESIGN: Descriptive study. Place and Duration of the Study: Sisli Etfal Training and Research Hospital, Turkey, between February 2019 and December 2020. METHODOLOGY: Two hundred and forty-six breast MRI scans with DWI of the patients with biopsy proven unilateral breast lesions were studied. ADC measurements were done by placing ROI. Two ADC values and two ADC ratios were obtained by different methods. The diagnostic accuracies of these four techniques were compared. RESULTS: Mean ADC values and ratios of benign and malignant lesions were statistically significant in all of four methods to quantify ADC (p< 0.001). Highest positive value and negative predictive value, and diagnostic accuracy rates were achieved when the most restricted part ADC value was calculated. However; highest sensitivity rate and negative predictive value were achieved by calculating the ratio of darkest point ADC to contralateral breast tissue. Positive predictive value, negative predictive value, and diagnostic accuracy rate of calculated ADC values and ratios were higher when lesions were larger than the mean size (3.15 mm2). CONCLUSION: Highest diagnostic accuracy rate was obtained with most restricted part ADC value. Obtained ratios by calculating contralateral breast tissue ADC value did not improve the diagnostic accuracy rate. Positive and negative predictive values and diagnostic accuracy rates of ADC values and ratios increased as the lesion size increased. Key Words: Breast mass, Diffusion weighted imaging, ADC value, ADC ratio, Normalised ADC.


Assuntos
Neoplasias da Mama , Imagem de Difusão por Ressonância Magnética , Biópsia , Mama/diagnóstico por imagem , Neoplasias da Mama/diagnóstico por imagem , Diagnóstico Diferencial , Feminino , Humanos , Imageamento por Ressonância Magnética , Valor Preditivo dos Testes , Sensibilidade e Especificidade
5.
BMC Womens Health ; 21(1): 284, 2021 08 04.
Artigo em Inglês | MEDLINE | ID: mdl-34348700

RESUMO

BACKGROUND: Adenomyoepithelioma (AME) of the breast is a rare subtype of breast tumor. Most of AMEs reported are solid, however, cystic or prominent cystic changes are extremely rare. CASE PRESENTATION: A 51-year-old woman presented a lump in the upper outer quadrant of right breast, and it was accompanied by continuous breast pain and bilateral axillary itching for more than 2 months. There were no other symptoms found. Preoperative mammography and ultrasound examination were performed. Mammography showed a noncalcified lobulated mass, and it was considered to be a benign cyst with septum on ultrasound, but ductal carcinoma of breast, adenoid cystic carcinoma could not be excluded. At first, AME was not considered preoperatively, because the imaging features of this rare tumor may vary widely, which may result in an incorrect diagnosis. But eventually, AME was diagnosed by postoperative pathology and immunohistochemistry. CONCLUSION: We herein present a rare case of breast AME with prominent cystic changes. AME has no-specific imaging features, but the benign or malignant nature of the lesion might be suspected on imaging.


Assuntos
Adenomioepitelioma , Neoplasias da Mama , Carcinoma Adenoide Cístico , Adenomioepitelioma/diagnóstico por imagem , Adenomioepitelioma/cirurgia , Mama/diagnóstico por imagem , Mama/cirurgia , Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/cirurgia , Feminino , Humanos , Imuno-Histoquímica , Pessoa de Meia-Idade
6.
Zhonghua Zhong Liu Za Zhi ; 43(8): 872-877, 2021 Aug 23.
Artigo em Chinês | MEDLINE | ID: mdl-34407594

RESUMO

Objective: To explore the diagnostic value of synthetic magnetic resonance imaging (syMRI) quantitative parameters for benign and malignant breast lesions. Methods: From September 2018 to March 2019, a total of 43 cases of breast lesions which were confirmed by surgery and pathology in Cancer Hospital, Chinese Academy of Medical Sciences were enrolled in this study. All patients underwent syMRI sequence scans before and after enhancement except for conventional T2WI, DWI, and enhancement scans. GE AW4.7 workstation was used to generate syMRI parameter maps (T1, T2, proton density mappings), and ITK-SNAP software was used to delineate the volume of interest. The T1, T2, PD values before and after dynamic contrast enhanced (DCE) were obtained, and the change values of each parameter were calculated. Meanwhile, the apparent diffusion coefficient (ADC) and time intensity curve (TIC) of the lesions were measured. The differences of each parameter value were compared between benign and malignant breast lesions, and the receiver operating characteristic (ROC) curve was used to analyze the diagnostic performance of each parameter. Results: Among the 43 enrolled cases, 13 were benign and 30 were malignant. Among the syMRI parameters, the pre-enhancement parameters including T1pre (median 1 663.07 ms), T2pre (median 103.33 ms), post-enhancement parameters ΔT1 (median 1 022.68 ms) and ΔT2 (median 27.67 ms) of benign group, significantly higher than those of the malignant group (the medians were 1 141.74, 92.53, 664.95, and 16.19 ms, respectively, P<0.05). The ADC value of the benign group (median 1.66×10(-3)mm(2)/s) was significantly higher than that of the malignant group (median 1.00×10(-3)mm(2)/s, P<0.05). The benign group included 6 cases of TIC curve type Ⅰ, 5 cases of type Ⅱ, and 2 cases of type Ⅲ. The malignant group included 2 cases of TIC curve type Ⅰ, 17 cases of type Ⅱ, and 11 cases of type Ⅲ. The difference between the two groups was statistically significant (P<0.05). The area under the ROC curve (AUC) of T1pre before DCE was 0.869, higher than 0.806 of ADC and 0.697 of TIC. When the best cut-off value of 1 282.94 ms was chosen, the sensitivity and specificity of diagnosis were 76.9% and 93.3%, respectively. The combination of T1pre and T2pre can further improve the diagnostic performance (AUC=0.908). Conclusions: Among the syMRI quantitative parameters, T1pre, T2pre, ΔT1 and ΔT2 have good value for the differential diagnosis of benign and malignant breast lesions. T1pre has the best diagnostic performance, and the combination of T1pre and T2pre can further improve the diagnostic performance.


Assuntos
Neoplasias da Mama , Meios de Contraste , Mama/diagnóstico por imagem , Neoplasias da Mama/diagnóstico por imagem , Diagnóstico Diferencial , Imagem de Difusão por Ressonância Magnética , Feminino , Humanos , Imageamento por Ressonância Magnética , Curva ROC , Estudos Retrospectivos , Sensibilidade e Especificidade
7.
Medicine (Baltimore) ; 100(31): e26823, 2021 Aug 06.
Artigo em Inglês | MEDLINE | ID: mdl-34397844

RESUMO

ABSTRACT: Low specificity and operator dependency are the main problems of breast ultrasound (US) screening. We investigated the added value of deep learning-based computer-aided diagnosis (S-Detect) and shear wave elastography (SWE) to B-mode US for evaluation of breast masses detected by screening US.Between February 2018 and June 2019, B-mode US, S-Detect, and SWE were prospectively obtained for 156 screening US-detected breast masses in 146 women before undergoing US-guided biopsy. S-Detect was applied for the representative B-mode US image, and quantitative elasticity was measured for SWE. Breast Imaging Reporting and Data System final assessment category was assigned for the datasets of B-mode US alone, B-mode US plus S-Detect, and B-mode US plus SWE by 3 radiologists with varied experience in breast imaging. Area under the receiver operator characteristics curve (AUC), sensitivity, and specificity for the 3 datasets were compared using Delong's method and McNemar test.Of 156 masses, 10 (6%) were malignant and 146 (94%) were benign. Compared to B-mode US alone, the addition of S-Detect increased the specificity from 8%-9% to 31%-71% and the AUC from 0.541-0.545 to 0.658-0.803 in all radiologists (All P < .001). The addition of SWE to B-mode US also increased the specificity from 8%-9% to 41%-75% and the AUC from 0.541-0.545 to 0.709-0.823 in all radiologists (All P < .001). There was no significant loss in sensitivity when either S-Detect or SWE were added to B-mode US.Adding S-Detect or SWE to B-mode US improved the specificity and AUC without loss of sensitivity.


Assuntos
Neoplasias da Mama , Mama , Aprendizado Profundo , Diagnóstico por Computador/métodos , Técnicas de Imagem por Elasticidade/métodos , Ultrassonografia Mamária/métodos , Mama/diagnóstico por imagem , Mama/patologia , Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/epidemiologia , Neoplasias da Mama/patologia , Diagnóstico Diferencial , Detecção Precoce de Câncer/métodos , Feminino , Humanos , Interpretação de Imagem Assistida por Computador , Pessoa de Meia-Idade , Estudos Prospectivos , República da Coreia/epidemiologia , Sensibilidade e Especificidade
8.
J Pak Med Assoc ; 71(8): 2087-2089, 2021 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-34418037

RESUMO

Primary breast sarcoma (PBS) is a rare group of non-epithelial tumours arising from connective tissue of the breast. We report the case of a 55-year-old female who presented with rapidly increasing mass in the left breast. The mammogram showed a large high density mass occupying the whole of the left breast, while Doppler ultrasound showed a mass of increased vascularity. Diagnosis was confirmed by histopathology of ultrasound-guided biopsy. Although there are no pathognomonic imaging features of PBS, presence of a solitary large mass showing rapid growth, with circumscribed or indistinct margins without axillary lymph node involvement should raise the suspicion of sarcoma and prompt biopsy to ensure early diagnosis and treatment; particularly considering the aggressive nature of these sarcomas.


Assuntos
Sarcoma , Mama/diagnóstico por imagem , Feminino , Humanos , Biópsia Guiada por Imagem , Mamografia , Pessoa de Meia-Idade , Sarcoma/diagnóstico por imagem , Ultrassonografia
9.
Eur J Radiol ; 142: 109882, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34392105

RESUMO

Significant advances in imaging analysis and the development of high-throughput methods that can extract and correlate multiple imaging parameters with different clinical outcomes have led to a new direction in medical research. Radiomics and artificial intelligence (AI) studies are rapidly evolving and have many potential applications in breast imaging, such as breast cancer risk prediction, lesion detection and classification, radiogenomics, and prediction of treatment response and clinical outcomes. AI has been applied to different breast imaging modalities, including mammography, ultrasound, and magnetic resonance imaging, in different clinical scenarios. The application of AI tools in breast imaging has an unprecedented opportunity to better derive clinical value from imaging data and reshape the way we care for our patients. The aim of this study is to review the current knowledge and future applications of AI-enhanced breast imaging in clinical practice.


Assuntos
Inteligência Artificial , Neoplasias da Mama , Mama/diagnóstico por imagem , Neoplasias da Mama/diagnóstico por imagem , Feminino , Humanos , Processamento de Imagem Assistida por Computador , Mamografia
10.
Comput Methods Programs Biomed ; 209: 106313, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34364182

RESUMO

BACKGROUND AND OBJECTIVE: Accurate segmentation of breast mass in 3D automated breast ultrasound (ABUS) images plays an important role in qualitative and quantitative ABUS image analysis. Yet this task is challenging due to the low signal to noise ratio and serious artifacts in ABUS images, the large shape and size variation of breast masses, as well as the small training dataset compared with natural images. The purpose of this study is to address these difficulties by designing a dilated densely connected U-Net (D2U-Net) together with an uncertainty focus loss. METHODS: A lightweight yet effective densely connected segmentation network is constructed to extensively explore feature representations in the small ABUS dataset. In order to deal with the high variation in shape and size of breast masses, a set of hybrid dilated convolutions is integrated into the dense blocks of the D2U-Net. We further suggest an uncertainty focus loss to put more attention on unreliable network predictions, especially the ambiguous mass boundaries caused by low signal to noise ratio and artifacts. Our segmentation algorithm is evaluated on an ABUS dataset of 170 volumes from 107 patients. Ablation analysis and comparison with existing methods are conduct to verify the effectiveness of the proposed method. RESULTS: Experiment results demonstrate that the proposed algorithm outperforms existing methods on 3D ABUS mass segmentation tasks, with Dice similarity coefficient, Jaccard index and 95% Hausdorff distance of 69.02%, 56.61% and 4.92 mm, respectively. CONCLUSIONS: The proposed method is effective in segmenting breast masses on our small ABUS dataset, especially breast masses with large shape and size variations.


Assuntos
Mama , Ultrassonografia Mamária , Algoritmos , Mama/diagnóstico por imagem , Feminino , Humanos , Processamento de Imagem Assistida por Computador , Ultrassonografia , Incerteza
11.
In Vivo ; 35(5): 2957-2961, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34410994

RESUMO

BACKGROUND/AIM: Hematoma is the most frequent complication after Vacuum-Assisted Breast Biopsy (VABB) in 13% of cases. A direct communication channel with patients eases the diagnosis of VABB complications and ensures treatment at an early stage, as outpatients, in most cases. In 2020, due to the COVID-19 pandemic, we observed a reduction of self-reported postoperative complication leading to delay in the identification of harmful complications, therefore leading to need for more invasive treatment. CASE REPORT: A 50-year-old patient was admitted to the Emergency Department for dry cough, fever, chest discomfort, dyspnea, and slight confusion four days after VABB. Due to the reported symptoms, the patient was sent to our COVID-19 Emergency Department. The COVID-19 swab was negative. Ultrasound revealed a large hematoma at the biopsy site, with active bleeding. Open evacuation with accurate hemostasis was planned with rapid and complete resolution of the clinical symptoms. After surgery, the patient reported that she intentionally avoided admittance in the hospital due to the risk of COVID-19 infection. The patient was discharged in the first postoperative day and maintained in quarantine for 14 days. CONCLUSION: In the COVID-19 era due to the risk of hospital cross-infections, reduction of patient-doctor communication could lead to misdiagnosis, delay in recognition of procedural complications thus leading to requirement for invasive treatment, hospitalization, while also further multiplying the risk of COVID-19 infection.


Assuntos
COVID-19 , Pandemias , Mama/diagnóstico por imagem , Mama/cirurgia , Feminino , Hematoma/diagnóstico por imagem , Hematoma/etiologia , Humanos , Pessoa de Meia-Idade , SARS-CoV-2
12.
Acad Radiol ; 28(9): 1191-1197, 2021 09.
Artigo em Inglês | MEDLINE | ID: mdl-34257025

RESUMO

INTRODUCTION: Following vaccination of Israeli population with Pfizer-BioNTech COVID-19 Vaccine, an unusual increase in axillary-lymphadenopathy was noted. This study assesses the rate and magnitude of this trend from breast-imaging standpoint. MATERIALS AND METHODS: Participants undergoing breast-imaging, in whom isolated axillary-lymphadenopathy was detected were questioned regarding SARS-CoV-2 vaccine to the ipsilateral arm. Patients' and imaging characteristics were statistically compared. In order to perform a very short-term follow-up, twelve healthy vaccinated medical staff-members, underwent axillary-ultrasound shortly after the second dose, and follow-up. RESULTS: Axillary-lymphadenopathy attributed to vaccination was found in 163 women undergoing breast-imaging, including BRCA-carriers. During the study, number of detected lymphadenopathies increased by 394% (p = 0.00001) in comparison with previous 2 consecutive years. Mean cortical-thickness of abnormal lymph-nodes after second dose vaccination was 5 ± 2 mm. Longer lymph-node diameter after second vaccination was noted (from 15 ± 5 mm, to 18 ± 6 mm, p = 0.005). In the subgroup of medical staff members, following trends were observed: in patients with positive antibodies, lymph-node cortical-thickness was larger than patients with negative serology (p = 0.03); lymph-node cortical-thickness decreased in 4-5 weeks follow-up (p = 0.007). Lymphadenopathy was evident on mammography in only 49% of cases. DISCUSSION: Vaccine-associated lymphadenopathy is an important phenomenon with great impact on breast-imaging clinic workload. Results suggest the appearance of cortical thickening shortly after both doses. Positive serology is associated with increased lymph-node cortical-thickness. In asymptomatic vaccinated women with ipsilateral axillary-lymphadenopathy as the only abnormal finding, radiological follow-up is probably not indicated. BRCA-carriers, although at higher risk for breast-cancer, should probably receive the same management as average-risk patients.


Assuntos
Mama/diagnóstico por imagem , Vacinas contra COVID-19/efeitos adversos , COVID-19 , Linfadenopatia/induzido quimicamente , Axila , COVID-19/prevenção & controle , Feminino , Humanos , Israel/epidemiologia , Linfonodos , Linfadenopatia/epidemiologia , Vacinação/efeitos adversos
13.
Comput Biol Med ; 135: 104553, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34246159

RESUMO

Breast cancer is the second most common cancer in the world. Early diagnosis and treatment increase the patient's chances of healing. The temperature of cancerous tissues is generally different from that of healthy neighboring tissues, making thermography an option to be considered in the fight against cancer because it does not use ionizing radiation, venous access, or any other invasive process, presenting no damage or risk to the patient. In this paper, we propose a hybrid computational method using the Dynamic Infrared Thermography (DIT) and Static Infrared Thermography (SIT) for abnormality screening and diagnosis of malignant tumor (cancer), applying supervised and unsupervised machine learning techniques. We use the area under receiver operating characteristic curve, sensitivity, specificity, and accuracy as performance measures to compare the hybrid methodology with previous work in the literature. The K-Star classifier achieved accuracy of 99% in the screening phase using DIT images. The Support Vector Machines (SVM) classifier applied on SIT images yielded accuracy of 95% in the diagnosis of cancer. The results confirm the potential of the proposed approaches for screening and diagnosis of breast cancer.


Assuntos
Neoplasias da Mama , Termografia , Mama/diagnóstico por imagem , Neoplasias da Mama/diagnóstico por imagem , Detecção Precoce de Câncer , Feminino , Humanos , Máquina de Vetores de Suporte
14.
Med Biol Eng Comput ; 59(10): 1973-1989, 2021 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-34331636

RESUMO

Breast cancer is the most common cancer in women occurring worldwide. Some of the procedures used to diagnose breast cancer are mammogram, breast ultrasound, biopsy, breast magnetic resonance imaging, and blood tests such as complete blood count. Detecting breast cancer at an early stage plays an important role in diagnostic and curative procedures. This paper aims to develop a predictive model for detecting the breast cancer using blood samples data containing age, body mass index (BMI), glucose, insulin, homeostasis model assessment (HOMA), leptin, adiponectin, resistin, and chemokine monocyte chemoattractant protein 1 (MCP-1).The two main challenges encountered in this process are identification of biomarkers and the precision of disease prediction accuracy. The proposed methodology employs principal component analysis in a peculiar approach followed by random forest tree prediction model to discriminate between healthy and breast cancer patients. This approach extracts high communalities, a linear combination of input attributes in a systematic procedure as principal axis elements. The iteratively extracted principal axis elements combined with minimum number of input attributes are able to predict the disease with higher accuracy of classification with increased sensitivity and specificity score. The results proved that the proposed approach generates a higher predictor performance than the previous reported results by opting relevant extracted principal axis elements and attributes that commend the classifier with increased performance measures.


Assuntos
Neoplasias da Mama , Análise de Componente Principal , Mama/diagnóstico por imagem , Neoplasias da Mama/diagnóstico por imagem , Feminino , Testes Hematológicos , Humanos , Imageamento por Ressonância Magnética
15.
Clin Imaging ; 78: 304-307, 2021 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-34218941

RESUMO

The early detection of breast cancer has been shown to reduce deaths through randomized, controlled trials. Numerous observational studies, failure analyses, and "incidence of death" studies have confirmed that screening reduces deaths in the general population. Digital Breast Tomosynthesis (DBT) which collects mammographic images from different angles and uses them to synthesize planes through the breast is simply another advance in mammography among others that have been made over the years. DBT "absolutely" detects more cancers at a time when cure is more likely while also having the advantage of reducing recall rates. The Tomosynthesis Mammographic Imaging Screening Trial (TMIST) has been designed to compare DBT with 2-Dimensional Full Field Digital Mammography (FFDM), but it's major design issues may provide misleading results. Instead of using a reduction in deaths as the endpoint, benefit in TMIST is predicated on a reduction in advanced cancers in the DBT group. This is a questionable "endpoint" (a reduction in advanced cancers is not necessary as proof of benefit). In addition, the trial may be underpowered so that even if DBT shows a benefit it may not be able to achieve "statistical significance". The six CISNET models of the National Cancer Institute have shown that annual mammography beginning at the age of 40 will save the most lives. Yet TMIST will only include women ages 45 and over and will screen postmenopausal women every two years instead of annually. Consequently, TMIST results may be used, inappropriately, to limit access to breast cancer screening starting at the age of 45, and only offer biennial screening for post-menopausal women.


Assuntos
Neoplasias da Mama , Mamografia , Mama/diagnóstico por imagem , Neoplasias da Mama/diagnóstico por imagem , Detecção Precoce de Câncer , Feminino , Humanos , Programas de Rastreamento , Pessoa de Meia-Idade
16.
Comput Methods Programs Biomed ; 208: 106246, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34218169

RESUMO

INTRODUCTION: Intraoperative radiotherapy (IORT) by low energy X-rays is a single fraction treatment modality for tumor bed irradiation after breast-conserving surgery. It has been shown that the variations of breast tissue composition can affect the absorbed dose in this method. Apart from physical quantities such as absorbed dose value, radiobiological quantities including relative biological effectiveness (RBE) may also change with the variations of breast tissue composition. Accordingly, the current study aims to quantify both single and double-strand break RBE values (RBESSB and RBEDSB) of low energy X-rays at different breast glandular fractions using a hybrid Monte Carlo (MC) simulation approach. MATERIALS AND METHODS: Produced low-energy X-rays by a validated MC model of INTRABEAM machine with 50 kV nominal voltage were considered as the radiation source. The secondary electron energy spectra at various depths inside the breast tissue with different glandular fractions were scored through GEANT4 MC Toolkit. Calculated spectra were then imported to MCDS MC code for DNA strand break calculation and RBE assessment. Both RBESSB and RBEDSB were calculated for various breast glandular fractions. RESULTS: Changing the breast glandularity can affect both the trend of secondary electron spectra and relevant RBE values at different depths inside the breast volume. In this regard, RBESSB increments by about 1% with increasing the breast glandular fraction from 0% to 100%. On the other hand, RBEDSB decrements by about 3.3% with increasing the glandular fraction in the range of 0% to 100%. Variations of the depth within the breast tissue can also influence the RBE value so that RBESSB reduces by about 1% with increasing the depth from 2 mm to 10 mm one, while RBEDSB increases about 3.4%. The relevant RBESSB and RBEDSB values to the entire target volume (breast PTV) respectively increment and decrement by about 0.8% and 3.2% with increasing the breast glandularity from 0% to 100%. CONCLUSION: From the results, it can be concluded that the breast tissue composition has a measurable effect on RBE values of employed low energy X-rays during breast IORT which can cause variations of prescribed dose for patients with distinct breast glandularity fractions.


Assuntos
Mama , Mama/diagnóstico por imagem , Simulação por Computador , Humanos , Método de Monte Carlo , Eficiência Biológica Relativa , Raios X
17.
Breast Cancer Res Treat ; 189(2): 585-592, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34196899

RESUMO

PURPOSE: A dense breast on mammogram is a strong risk factor for breast cancer. Identifying factors that reduce mammographic breast density could thus provide insight into breast cancer prevention. Due to the limited number of studies and conflicting findings, we investigated the associations of medication use (specifically statins, aspirin, and ibuprofen) with mammographic breast density. METHODS: We evaluated these associations in 775 women who were recruited during an annual screening mammogram at Washington University School of Medicine, St. Louis. We measured mammographic breast density using Volpara. We used multivariable-adjusted linear regressions to determine the associations of medication use (statins, aspirin, and ibuprofen) with mammographic breast density. Least squared means were generated and back-transformed for easier interpretation. RESULTS: The mean age of study participants was 52.9 years. Statin use in the prior 12 months was not associated with volumetric percent density or dense volume, but was positively associated with non-dense volume. The mean volumetric percent density was 8.6% among statin non-users, 7.2% among women who used statins 1-3 days/week, and 7.3% among women who used statins ≥ 4 days/week (p trend = 0.07). The non-dense volume was 1297.1 cm3 among statin non-users, 1368.7 cm3 among women who used statins 1-3 days/week, and 1408.4 cm3 among those who used statins ≥ 4 days/week (p trend = 0.02). We did not observe statistically significant differences in mammographic breast density by aspirin or ibuprofen use. CONCLUSION: Statin, aspirin, and ibuprofen use was not associated with volumetric percent density and dense volume, but statin use was positively associated with non-dense volume. Any potential associations of these medications with breast cancer risk are unlikely to be mediated through an effect on volumetric percent density.


Assuntos
Densidade da Mama , Neoplasias da Mama , Mama/diagnóstico por imagem , Neoplasias da Mama/induzido quimicamente , Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/epidemiologia , Feminino , Humanos , Mamografia , Pessoa de Meia-Idade , Fatores de Risco
18.
Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi ; 35(7): 918-922, 2021 Jul 15.
Artigo em Chinês | MEDLINE | ID: mdl-34308603

RESUMO

Objective: To review the diagnosis and management of fat necrosis after autologous fat transplantation of breast. Methods: Based on the latest related literature, the pathology, clinical and radiographic examinations, influence factors, as well as the management of fat necrosis after autologous fat transplantation for breast augmentation and reconstruction were summarized. Results: Fat necrosis after breast autologous fat transplantation is histologically manifested as hyaline degeneration, fibrosis, and calcification. The diagnosis of fat necrosis includes clinical examination, imaging examination (ultrasound, mammography, and MRI), and biopsy. The occurrence of fat necrosis is closely related to patient's own reason and fat transplantation technology. Optimizing the process of fat acquisition, purification, and transplantation can reduce the occurrence of fat necrosis. Intervention or not after fat necrosis depends on the nature of the nodules. According to the nature of the the nodules, various methods such as simple aspiration, vibration amplification of sound energy at resonance liposuction, or direct excision can be selected. Conclusion: Fat necrosis after autologous fat transplantation of breast are difficult to control. How to process fat to minimize the injury and maximize the activity of grafted fat needs further researches.


Assuntos
Necrose Gordurosa , Mamoplastia , Tecido Adiposo , Mama/diagnóstico por imagem , Mama/cirurgia , Necrose Gordurosa/diagnóstico , Necrose Gordurosa/etiologia , Humanos , Mamoplastia/efeitos adversos , Transplante Autólogo
19.
Math Biosci Eng ; 18(4): 3680-3689, 2021 04 27.
Artigo em Inglês | MEDLINE | ID: mdl-34198406

RESUMO

Objective Traditional breast ultrasound relies too much on the operation skills of diagnostic doctors, and the repeatability in different doctors was low. This study aimed to evaluate the assistant diagnostic value of S-Detect artificial intelligence (AI) system in differentiating benign from malignant breast masses. Methods The ultrasound images of 40 patients who underwent ultrasound examination in our hospital were collected. The conventional ultrasound images, elastic images, and S-Detect mode of breast lesions were analyzed. The breast imaging reporting and data system recommended by the American Society of Radiology (BI-RADS) classification for each breast mass was evaluated both by the doctor and AI. The receiver operator characteristics (ROC) curves were drawn to compare the diagnostic efficiency. Result Among the 40 lesions, 16 were benign, and 24 were malignant. The S-Detect AI system had a high diagnostic efficiency for malignant mass, with sensitivity, specificity, and accuracy of 95.8%, 93.8%, and 89.6%. The accuracy of AI was higher than the elastic image and then than the conventional gray-scale image. With the assistance of the S-Detect AI system, the accuracy of BI-RADS classification was improved significantly. Conclusion The S-Detect AI system will enhance breast cancer diagnostic accuracy and improve ultrasound examination quality.


Assuntos
Neoplasias da Mama , Inteligência Artificial , Mama/diagnóstico por imagem , Neoplasias da Mama/diagnóstico por imagem , Diagnóstico Diferencial , Feminino , Humanos , Sensibilidade e Especificidade , Ultrassonografia Mamária
20.
Medicine (Baltimore) ; 100(25): e25912, 2021 Jun 25.
Artigo em Inglês | MEDLINE | ID: mdl-34160380

RESUMO

ABSTRACT: The incidence of granulomatous mastitis (GLM) in multiparae as seriously affected the quality of life and breastfeeding of pregnant women after delivery, but the treatment is rarely reported. In this article, the development, healing, and lactation of 13 cases were reported and a retrospective analysis was performed. 10 cases of GLM were treated at the Breast Disease Prevention and Treatment Center of Haidian Maternal & Child Health Hospital of Beijing and 3 cases of GLM were treated in the Breast Department of Weihai Municipal Hospital of Shandong province from February 2017 to May 2019.Among the 13 patients, conservative symptomatic treatment was adopted during pregnancy and lactation: anti-infective therapy consisting of oral cephalosporin antibiotic for patients; ultrasound-guided puncture and drainage of pus or incision and drainage after abscess formation. Observation continued during the sinus tract phase. Postpartum breastfeeding was encouraged, especially on the affected side. In this study, the median healing time was 20 months and the average healing time was 30.4 months in 5 healthy breast lactation cases. In 8 cases of bilateral breast lactation, the median healing time was 30 months and the average healing time was 26.5 months. Linear regression test analysis: whether the affected breast was breast-fed after delivery had no effect on the postpartum wound healing time, P = .792. The wounds of 13 patients healed well after lactation, and none of them recurred since the last follow-up visit. There were no adverse events in all infants.Conservative symptomatic treatment for GLM of multiparous women during pregnancy and lactation and encouraging breastfeeding after delivery have no effect on infant health and the recovery time of patients.


Assuntos
Antibacterianos/administração & dosagem , Tratamento Conservador/métodos , Drenagem/métodos , Mastite Granulomatosa/terapia , Complicações na Gravidez/terapia , Administração Oral , Adulto , Mama/diagnóstico por imagem , Mama/cirurgia , Aleitamento Materno , Cefalosporinas/administração & dosagem , Feminino , Seguimentos , Idade Gestacional , Mastite Granulomatosa/diagnóstico , Mastite Granulomatosa/epidemiologia , Mastite Granulomatosa/fisiopatologia , Humanos , Lactente , Recém-Nascido , Lactação/fisiologia , Paridade/fisiologia , Gravidez , Complicações na Gravidez/diagnóstico , Complicações na Gravidez/epidemiologia , Complicações na Gravidez/fisiopatologia , Estudos Retrospectivos , Fatores de Tempo , Resultado do Tratamento , Ultrassonografia de Intervenção
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