Tabu Search and Machine-Learning Classification of Benign and Malignant Proliferative Breast Lesions.

Breast cancer is the most diagnosed cancer among women around the world. The development of computer-aided diagnosis tools is essential to help pathologists to accurately interpret and discriminate between malignant and benign tumors. This paper proposes the development of an automated proliferative breast lesion diagnosis based on machine-learning algorithms. We used Tabu search to select the most significant features. The evaluation of the feature is based on the dependency degree of each attribute in the rough set. The categorization of reduced features was built using five machine-learning algorithms. The proposed models were applied to the BIDMC-MGH and Wisconsin Diagnostic Breast Cancer datasets. The performance measures of the used models were evaluated owing to five criteria. The top performing models were AdaBoost and logistic regression. Comparisons with others works prove the efficiency of the proposed method for superior diagnosis of breast cancer against the reviewed classification techniques.

Value of Hand-held Ultrasound in the Differential Diagnosis and Accurate Breast Imaging Reporting and Data System Subclassification of Complex Cystic and Solid Breast Lesions.

To explore the value of hand-held ultrasound (HHUS) for diagnosing complex cystic and solid breast lesions, 472 pathologically proven lesions were analyzed. The lesions were divided into four types based on ultrasound features. Positive predictive values (PPVs) for lesion types and risk factor performances were assessed. Furthermore, HHUS and mammography (MAM) performances were compared: 27 lesions missed in MAM were detected in HHUS. Ultrasound feature analysis revealed higher PPVs for type III and IV lesions than for type I and II lesions. In patients older than 51 y, a type III or IV lesion with a diameter greater than 18 mm, an irregular shape, a non-parallel orientation, an uncircumscribed margin, calcification, vascularity and abnormal axillary lymph nodes were suggestive of malignancy; the area under the curve reached 0.869. Thus, ultrasound is useful in diagnosing complex cystic and solid breast lesions, which should be categorized as Breast Imaging Reporting and Data System (BI-RADS) 4B or 4C.

Computer-aided diagnosis of breast masses using quantified BI-RADS findings.

The information from radiologists was utilized in the proposed computer-aided diagnosis (CAD) for breast tumor classification. The ultrasound (US) database used in this study contained 166 benign and 78 malignant masses. For each mass, six quantitative feature sets were used to describe the radiologists' grading of six Breast Imaging Reporting and Data System (BI-RADS) categories including shape, orientation, margins, lesion boundary, echo pattern, and posterior acoustic features on breast US. The descriptive abilities were between 76% and 82% and the predicted descriptors were then used for tumor classification. Using receiver operating characteristic curve for evaluation, the area under curve (AUC) of the proposed CAD was slightly better than that of a conventional CAD based on the combination of all quantitative features (0.96 vs. 0.93, p=0.18). The partial AUC over 90% sensitivity of the proposed CAD was significantly better than that of the conventional CAD (0.90 vs. 0.76, p<0.05). In conclusion, the computer-aided analysis with qualitative information from radiologists showed a promising result for breast tumor classification.

Typical and unusual sonoelastographic patterns of breast cystic lesions: impact on BI-RADS classification.

PURPOSE: To describe the sonoelastographic appearance of breast cysts (simple, complicated-cysts with sedimentation and complex-cysts with internal solid parts). To assess the influence of sonoelastography on the BI-RADS classification of complicated cysts. MATERIALS AND METHODS: A prospective study was conducted and all cysts diagnosed by the same radiologist between May 2007 and July 2008 in our breast unit were included. Each lesion was assessed according to BI-RADS and the Tsukuba elasticity score using a Hitachi 8500 US device. Cytology or histopathology was obtained for complicated and complex cysts. RESULTS: 49 simple, 43 complicated and 14 complex cysts were detected. The elasticity patterns were divided into 4 categories: typical BGR (blue-green-red) pattern, appearance similar to that described for solid. lesions, variants of BGR, an inverse score of 3. The BGR pattern was predominant in breast cysts. Atypical elasticity patterns were mostly associated with complicated and complex cysts. BI-RADS classification of complicated cysts before and after elastography showed a statistically significant difference in terms of final category assessment (most of the complicated cysts were downgraded to BI-RADS 2 after elastography). CONCLUSION: Being aware of the wide spectrum of elastographic patterns of breast cysts and considering elastography when assessing the BI-RADS category of complicated cysts may lead radiologists to better patient management.

Patrón difuso de la mama / Diffuse pattern of the breast

Presentación que se observa con más frecuencia al realizar un estudio ultrasonográfico de la mama, en la que pueden visualizarse distintas modificaciones, denominadas displasias mamarias. Se describen las patologías que pueden presentar un patrón difuso.

Patrón difuso de la mama / Diffuse pattern of the breast

Presentación que se observa con más frecuencia al realizar un estudio ultrasonográfico de la mama, en la que pueden visualizarse distintas modificaciones, denominadas displasias mamarias. Se describen las patologías que pueden presentar un patrón difuso.

Multicenter study of ultrasound real-time tissue elastography in 779 cases for the assessment of breast lesions: improved diagnostic performance by combining the BI-RADS®-US classification system with sonoelastography.

PURPOSE: Hitachi real-time tissue elastography (HI-RTE) is an ultrasound technique that facilitates the estimation of tissue elasticity. Our study evaluates whether sonoelastography improves the differentiation of benign and malignant breast lesions. MATERIALS AND METHODS: In a multicenter approach sonoelastography of focal breast lesions was carried out in 779 patients with subsequent histological confirmation. We present data from 3 study centers (Berlin, Bielefeld, Homburg/Saar) focusing on the sensitivity (SE), specificity (SP) and the positive (PPV) and negative predictive value (NPV) of sonoelastography. In addition we performed an analysis of the diagnostic performance, expressed by the pretest and posttest probability of disease (POD), in BI-RADS®-US 3 or 4 lesions as these categories can imply both malignant and benign lesions and a more precise prediction would be a preferable aim. RESULTS: Sonoelastography demonstrated an improved SP (89.5 %) and an excellent PPV (86.8 %) compared to B-mode ultrasound (76.1 % and 77.2 %). Especially in dense breasts ACR III-IV, the SP was even higher (92.8 %). In BI-RADS-US 3 lesions, a suspicious elastogram significantly modified the POD from 8.3 % to a posttest POD of 45.5 %. In BI-RADS-US 4 lesions, we found a pretest POD of 56.6 %. The posttest POD changed significantly to 24.2 % with a normal elastogram and to 81.5 % with a suspicious elastogram. CONCLUSION: Our data demonstrates that the complementary use of sonoelastography definitely improves the performance in breast diagnostics. Finally we present a protocol of how sonoelastography can be integrated into our daily practice.

Hiperplasia intraductal atípica o carcinoma intraductal grado 1 vs. DIN1c / No disponible

Objetivo: La clasificación DIN incluye en el DIN1c la hiperplasiaintraductal atípica (HIA) y el carcinoma intraductal grado1 (CID1). El objetivo de este estudio es ver si esta agrupacióndiagnóstica, con las consecuencias terapéuticas que elloconlleva, implica o no un sobretratamiento de la HIA.Pacientes y métodos: Se ha revisado el tratamiento y laevolución de los casos de HIA y CID1 diagnosticados en nuestrocentro desde 1999 hasta 2008. Se han utilizado los mismoscriterios diagnósticos que utiliza la clasificación DIN paradiferenciar la HIA y el CID1.Resultados: De 117 casos, 49 fueron HIA y 68 CID1. Eltratamiento quirúrgico fue tumorectomía, independientementedel estado del margen, en 47 (96%) HIA y en 53 (78%) CID1consiguiendo siempre un margen libre. En 42 (62%) casos deCID1 el tratamiento se complementó con radioterapia. Uncaso de HIA y otro de CID1 recidivaron tras 24 y 39 mesesen forma de carcinoma ductal infiltrante.Conclusiones: La clasificación DIN simplifica el diagnóstico,no obstante agrupar alguna de estas lesiones puede conllevarsu sobretratamiento. En nuestra serie la simple extirpaciónde una HIA independientemente del estado del margen hasido curativa en la mayoría de casos(AU)

Objective: DIN classification includes into DIN1c the atypicalintraductal hyperplasia (AIH) and intraductal carcinomagrade 1 (IDC1). The aim of this study is to see if this grouping,with its therapeuthical consequences, implies an overtreatmentof AIH.Patients and methods: Treatment and follow-up of allthose cases diagnosed of AIH and IDC1 between 1999 and2008 at our centre have been revised. The diagnostic criteriato differentiate AIH and IDC1 were the same used in DIN classification.Results: Of the 117 studied cases, 49 were diagnosed asAIH and 68 as IDC1. Lumpectomy, independently of the statusof the margin was performed in 47 (96%) AIH, and 53(78%) IDC1 with adequate resection margin. In 42 (62%) casesof IDC1 adjuvant radiotherapy was given. One case of AIHand one case of IDC1 recurred as invasive ductal carcinoma,24 and 39 months later respectively.Conclusions: DIN classification simplifies the diagnosis butgrouping these lesions can result into an overtreatment. In ourserie the surgical excision of AIH independently of the statusof the margin was curative in the majority of the cases(AU)

Automated breast ultrasound: lesion detection and BI-RADS classification--a pilot study.

PURPOSE: Evaluation of an automated breast ultrasound system (ABUS) regarding the detection and classification of breast lesions according to BI-RADS. MATERIALS AND METHODS: Women were selected for the study who had unclear findings in breast diagnosis performed elsewhere (palpation, sonography or mammography) and who were referred for further work-up. All patients received a hand-held ultrasonography (HHUS) with a 13 MHz transducer, clinical examination and mammography of both breasts. Additionally, the affected breast received the ABUS (SomoVuTM, U-Systems, Inc., San Jose, CA, USA; EC Representative: Siemens, Erlangen, Germany) which was performed with an 8 MHz transducer. Five radiologists independently evaluated the ABUS images regarding lesion detectability. All detected lesions were classified according to BI-RADS assessment. The examiners had no knowledge of the patients' clinical examination or of the result of the mammography or the HHUS. Results of the ABUS were compared to HHUS. RESULTS: 35 women were included in the study. 25 BI-RADS 4 or 5 lesions had further histological (n = 23) or cytological (n = 2) work-up which revealed 13 malignant and 12 benign findings. The size of all lesions ranged from 6 to 32 mm (median 14 mm). With the ABUS all examiners detected 29 to 30 lesions while HHUS revealed 30 lesions. One suspicious area in HHUS was not reported by any of the five examiners with the ABUS. Histology of this area revealed mastopathic disease. No benign lesion was classified as BI-RADS 5 with the ABUS or HHUS. All breast cancers were found with the ABUS by all examiners and correctly classified as BI-RADS 4 or 5. There was good agreement regarding BI-RADS classification of HHUS and ABUS for the five different examiners with Kappa values between 0.83 and 0.87. CONCLUSION: These preliminary results show that the ABUS allows detection of solid and cystic lesions and their BI-RADS classification with a high reliability in a selected patient group.

Computer aided classification system for breast ultrasound based on Breast Imaging Reporting and Data System (BI-RADS).

Clinically, the ultrasound findings are evaluated by its sonographic characteristics and then assigned to assessment categories according to the definitions of Breast Imaging Reporting and Data System (BI-RADS) developed by the American College of Radiology. In this study, a computer-aided classification (CAC) system was proposed to classify the masses into assessment categories 3, 4 and 5, which simulated the clinical diagnosis of radiologists. Compared with current computer-aided diagnosis systems, the proposed CAC system classifies the indeterminate cases into BI-RADS category 4 for further diagnosis. Six hundred twenty-six cases were collected from three ultrasound systems and confirmed by pathology and retrospectively classified into categories 3, 4 and 5 by radiologists. The multinomial logistic regression model was trained as the CAC system for predicting the assessment category from the computerized BI-RADS features and from a set of machine-dependent factors. By using the machine-dependent factors to indicate the adopted ultrasound systems, the same regression model could be applied for the cases acquired from different ultrasound systems. A basic CAC system was trained by using the classification result of radiologists. A weighted CAC system, to improve the capacity of the basic CAC system in differentiating benign from malignant lesions, was trained by adding the pathologic result. Between the radiologists and the basic CAC system, a substantial agreement was indicated by Cohen's kappa statistic and the differences in either the performance indices or the A(Z) of receiver operating characteristic (ROC) analysis were not statistically significant. For the weighted CAC system, the performance indices accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 73.00% (457 of 626), 98.17% (215 of 219), 59.46% (242 of 407), 56.58% (215 of 380) and 98.37% (242 of 246), respectively; the A(Z) was 0.94; and the correlation with the radiologists was also substantial agreement. The indices accuracy and specificity of weighted CAC system, compared with those of the radiologists, were improved by 5.91% and 8.85%, respectively and the indices of sensitivity and NPV, compared with those of a conventional CAD system, were improved by 10.5% and 5.21%, respectively; all improvements were statistically significant. To classify the mass into BI-RADS assessment categories by the CAC system is feasible. Moreover, the proposed CAC system is flexible because it can be used to diagnose the cases acquired from different ultrasound systems.

[Fibrocystic mastopathy and cancer of the breast. About 111 cases]. / Mastopathies fibrokystiques et cancers du sein. A propos de 111 cas.

OBJECTIVE: Our aim was to identify the predictive factors of degeneration of the fibrocystic mastopathy. METHODS: This work is a retrospective survey of 111 observations of isolated fibrocystic mastopathies or associated to a breast cancer among 542 women admitted for tumor of the breast during one period of 13 active years from 1991 to 2003. The diagnosis has been gotten by anatomo-pathologic exam in 95.5% (106 cas) on the operative piece and 4.5% (5 cas) on a material of biopsy. RESULTS: The fibrocystic mastopathy represented 30% of the set of the benign tumors of the breast. They were associated to a breast cancer in 45 cases (40.5%). The isolated benign fibrocystic mastopathy was observed in 66 cases with a middle age of 37 years, whereas the shapes associated to a breast carcinoma were noted in 45 cases. The middle age was 53 years. The non proliferative fibrocystic mastopathy is the most frequent histological type and represent 54.6% of the cases. The proliferative form with atypies was observed at 21 women (46.8%). The carcinoma the more frequently associated to the fibrocystic mastopathy was the infiltrating canalled carcinoma in 91% of cases, with a predominance of the II rank (SBR). CONCLUSION: The discovery of a mastopathy must search a luteal failure and risk factors of breast cancer notably a proliferative shape of mastopathy with atypies.

Profile of breast lesions among women with positive biopsy findings in Yemen.

This study described the profile of breast pathology based on records from a reference histopathology laboratory in Yemen of 773 women with positive biopsy or mastectomy findings. Cancers were classified according to the International classification of diseases for oncology. Benign lesions were found in 79.9% of cases. Fibroadenoma was the most prevalent lesion (30.0%) with a mean age at presentation of 22.2 years, followed by fibrocystic disease (27.4%) and breast inflammation (13.1%). Invasive carcinoma was found in 155 cases (20.1%), at a mean age of 44.7 years.

Multimodality computerized diagnosis of breast lesions using mammography and sonography.

RATIONALE AND OBJECTIVES: The purpose of this study is to investigate the use of computer-extracted features of lesions imaged by means of two modalities, mammography and breast ultrasound, in the computerized classification of breast lesions. MATERIAL AND METHODS: We performed computerized analysis on a database of 97 patients with a total of 100 lesions (40 malignant, 40 benign solid, and 20 cystic lesions). Mammograms and ultrasound images were available for these breast lesions. There was an average of three mammographic images and two ultrasound images per lesion. Based on seed points indicated by a radiologist, the computer automatically segmented lesions from the parenchymal background and automatically extracted a set of characteristic features for each lesion. For each feature, its value averaged over all images pertaining to a given lesion was input to a Bayesian neural network for classification. We also investigated different approaches to combine image-based features into this by-lesion analysis. In that analysis, mean, maximum, and minimum feature values were considered for all images representing a lesion. We considered performance by using a leave-one-lesion-out approach, based on image features from mammography alone (two to five features), ultrasound alone (three to four features), and a combination of features from both modalities (three to five features total). RESULTS: For the classification task of distinguishing cancer from other abnormalities in a lesion-based analysis by using a single modality, areas under the receiver operating characteristic curves (A(z) values) increased significantly when the computer selected the manner (mean, minimum, or maximum) in which image-based features were combined into lesion-based features. The highest performance was found for lesion-based analysis and automated feature selection from mean, maximum, and minimum values of features from both modalities (resulting in a total of four features being used). That A(z) value for the task of distinguishing cancer was 0.92, showing a statistically significant increase over that achieved with features from either mammography or ultrasound alone. CONCLUSION: Computerized classification of cancer significantly improved when lesion features from both modalities were combined. Classification performance depended on specific methods for combining features from multiple images per lesion. These results are encouraging and warrant further exploration of computerized methods for multimodality imaging.

Time-domain optical mammography SoftScan: initial results.

RATIONALE AND OBJECTIVES: Near-infrared (NIR) technology appears promising as a noninvasive technique for breast cancer screening and diagnosis. The technology capitalizes on the relative transparency of human tissue in this spectral range and its sensitivity to the main components of the breast: water, lipid, and hemoglobin. In this study, the authors report quantitative measurements of these components and the functional contrast between healthy and diseased tissue. MATERIALS AND METHODS: A four-wavelength time domain optical imaging system was used to perform noninvasive NIR measurements in the breast of 49 women both pre- and postmenopausal, ages 24-80. Algorithms based on a diffusive model of light transport provided absolute bulk and local values of breast constituent concentrations. RESULTS: Important variations in the functional and structural NIR properties of the breast were observed. Demographics trend were noticed in accordance with breast physiology. In the 23 cases imaged with suspicious masses, the optical images were consistent with the mammographic findings. Substantial contrast between masses and adjacent tissue is observed. Moreover, consistent differences between malign and benign cases are found with optical imaging. CONCLUSION: The results of this pilot study illustrate the sensitivity of optical techniques to the composition of the breast. In addition, preliminary data suggest that benign and malignant tumors can potentially be noninvasively differentiated with optical imaging. Moreover, statistically significant discrimination based on deoxy-hemoglobin content between malign and benign cases was found with optical imaging (P = .0184, one-tailed t test).

[Clinical research on relationship between angiogensis and TCM syndrome type of cyclomastopathy].

OBJECTIVE: To study the relationship between angiogensis and TCM Syndrome type of cyclomastopathy (CMP) to investigate the objective standardization of TCM Syndrome diagnosis of the disease. METHODS: One hundred and forty patients with CMP were divided into three groups according to TCM syndrome typing. The pathological type, grade and expressions of vascular endothelial growth factor (VEGF), basic fibroblast growth factor (bFGF) and microvascular density (MVD) in mammary biopsy were observed. RESULTS: The expressions of VEGF, bFGF and MVD was different in CMP patients of different TCM types and pathological grades (P < 0.05). The proportion of atypical proliferation, the count of MVD and the expression of VEGF and bFGF were higher in patients of phlegm and stasis type than those in Gan stagnation caused Qistagnation type and Chong and Ren meridians disorder type. CONCLUSION: TCM Syndrome type of CMP patients is related with vascular activity and grade of angiogensis. The pathological characteristics of mammary tissue and expression of VEGF, bFGF and MVD can be regarded as the objective indexes of TCM typing and clinical efficacy evaluation for CMP.

Is grading of breast fibrosis with mammography feasible?

PURPOSE: To establish a grading system for mammographic fibrosis and correlate it with clinical fibrosis. PATIENTS AND METHODS: Analogous to the LENT/SOMA scale a four-tiered scoring scale of breast fibrosis in mammography (G0 = absent, G1 = barely increased density, G2 = definitely increased density to G3 = very marked density) was established by two observers in a group of 16 patients. Reference mammograms were selected. Independently and blinded to clinical results, three observers scored the fibrosis in mammograms of further 31 patients examined by one radiation oncologist in a cross-sectional follow-up study. Pretreatment parenchyma density was judged according to the American College of Radiology (ACR). Interobserver correlation of mammography scoring as well as correlation of mammography and clinical findings were calculated with Cohen's weighted kappa. All patients had breast-conserving surgery and axillary resection for breast carcinoma T1-2N0-1. The breast was irradiated to a median reference dose of 55 Gy (range 50-60 Gy) with 2 Gy five times weekly or 2.5 Gy four times weekly. Two patients received chemotherapy, 14 patients tamoxifen. Median age was 55 years, median follow-up 8 years (4-15 years). RESULTS: 14 of 31 patients had clinical fibrosis, twelve G1 and two G2. In mammography, mild fibrosis (G1) was seen in 12/12/18 patients (observer 1/2/3) and moderate fibrosis (G2) in 9/10/2 patients. Interobserver correlation for observers 1 and 2 who had developed the score was fair (Cohen's weighted kappa 0.64, 95% confidence interval 0.4-0.88). However, it was weak for observer 3 (0.36 and 0.42, respectively) who relied on reference mammograms only. Independent interobserver correlation of pretreatment breast density was good for all observers (Cohen's weighted kappa 0.73-0.8). The correlation of fibrosis by mammography and palpation was weak (Cohen's weighted kappa 0.32-0.42). CONCLUSION: Grading fibrosis as depicted by mammography is possible, especially if observers prepare by jointly analyzing a training group. It may be useful to study treatment effects, e. g., of fractionation or drugs, because retrospective and repeated analysis is possible. The correlation of mammography with clinical grading should be further evaluated with more objective clinical reference tools.

A case-control study of risk factors for fibrocystic breast conditions: Shanghai Nutrition and Breast Disease Study, China, 1995-2000.

This study was conducted to identify reproductive and dietary factors associated with benign proliferative mammary epithelial cell changes. Subjects were women enrolled in a randomized trial of breast self-examination in Shanghai, China. Women who developed fibrocystic breast conditions classified as nonproliferative (175 women), proliferative (181 women), or proliferative with atypia (33 women) between 1995 and 2000 and 1,070 unaffected trial participants were administered general risk factor and food frequency questionnaires. Conditional logistic regression was used to estimate adjusted odds ratios and 95% confidence intervals. High parity and consumption of fresh fruits and vegetables were more strongly associated with a reduced risk of proliferative and atypical lesions than with nonproliferative conditions. For the fourth quartile of consumption versus the first, odds ratios for lesions diagnosed as nonproliferative, proliferative, and proliferative with atypia were 0.4 (95% confidence interval (CI): 0.2, 0.7), 0.2 (95% CI: 0.1, 0.4), and 0.1 (95% CI: 0.03, 0.5), respectively, for fruit intake and 0.6 (95% CI: 0.3, 1.1), 0.4 (95% CI: 0.2, 0.7), and 0.1 (95% CI: 0.1, 0.9), respectively, for vegetable intake. Reduced but nonsignificant risks in relation to soy products were observed for proliferative and atypical lesions. No single nutrient or botanical family was appreciably more strongly associated with proliferative conditions than with nonproliferative conditions, after results were controlled for total fruit and vegetable consumption. A diet rich in fruits and vegetables may reduce cellular proliferation in the mammary epithelium; this is one mechanism by which such a diet could reduce risk of breast cancer.

Computer-aided classification of BI-RADS category 3 breast lesions.

PURPOSE: To evaluate a system for computer-aided classification (CAC) of lesions assigned to Breast Imaging Reporting and Data System (BI-RADS) category 3 at conventional mammographic interpretation. MATERIALS AND METHODS: A CAC system was used to analyze 106 cases of lesions (42 malignant) that at blinded retrospective interpretation were assigned to BI-RADS category 3 by at least two of four radiologists. The CAC system automatically extracted from the digitized mammograms quantitative features that characterized the lesions. The system then used a classification scheme to score the lesions by the likelihood of their malignancy on the basis of these features. The classification scheme was trained with 646 pathologically proved cases (323 malignant), and the results were tested with receiver operating characteristic (ROC) analysis by using the jackknife method. Sensitivity, specificity, positive predictive value, and accuracy were calculated. Category 3 lesions were stratified among BI-RADS categories 2-5 according to CAC-assigned lesion score, and this classification was compared with the results of pathologic analysis. RESULTS: Jackknife analysis of CAC results in the training data set yielded a sensitivity of 94%, specificity of 78%, positive predictive value of 81%, and area under the ROC curve of 0.90. Of the 42 malignant lesions that had been classified at conventional interpretation as probably benign, nine were assigned by the CAC system to BI-RADS category 4, and 29 were assigned to category 5. The CAC system correctly upgraded the BI-RADS classification of these 38 lesions (sensitivity, 90%) and incorrectly upgraded the classification of only 20 benign lesions (specificity, 69%). CONCLUSION: The CAC system scored 38 of the 42 malignant lesions initially assigned to BI-RADS category 3 as BI-RADS category 4 or 5, and thus correctly upgraded the category in 90% of these lesions.

Fibroadenoma juvenil gigante / Fiboadenoma gigant youthful

El fibroadenoma es responsable del 75 por ciento de los tumores de mama en las mujeres entre 10 y 20 años de edad: la variedad Juvenil o Gigante corresponde al 2 por ciento de todos los fibroadenomas y al 7 por ciento de todas las lesiones de la mama en menores de 20 años. Presentamos el caso de una niña de 11 años con fibroadenoma juvenil gigante de mama de aparición en la premenarca y con 2 recurrencias, hacemos consideraciones sobre el caso y la entidad