Types Of Breast Lesions Research Articles

SONOGRAPHIC FREQUENCY AND DISTRIBUTION OF BREAST LESIONS IN WOMEN OF LAHORE: A CROSS-SECTIONAL STUDY

Background and Aims: Breast cancer is a significant health issue worldwide, and early detection is crucial for effective treatment and management. In Pakistan, breast cancer incidence rates are increasing, and late-stage diagnoses are common. Therefore, it is essential to understand the frequency and types of breast lesions to achieve early detection and management. The primary objective of this study was to find out the sonographic frequency of breast lesions in females of Lahore city. Methods: A cross sectional study was conducted at Gilani Ultrasound Center Lahore, 185 females of different age groups were enrolled in this study with Non-probability convenient sampling. All asymptomatic and symptomatic females come for breast Ultrasound were included in this study and females with breast cancer were excluded.Ultrasound Machine Xario Z-3272 with a linear probe of high frequency 7-12 MHz was used. Results: In the study of 185 female patients in Lahore city, 59 (31.9%) had breast lesions. The lesions were most commonly found on the left side (24.3%) and in the upper outer quadrant of the breast (11.4%). Out of 145 married patients, 48 (33.1%) had breast lesions. The majority of patients (70.8%) reported experiencing breast pain, and of these, 39 (29.8%) had breast lesions. Of the 34 patients who were in menopause, 9 (26.5%) had breast lesions. A small number of patients (1.6%) showed dimpling of the breast skin. The results showed that 126 (68.1%) patients had BI-Rads-I findings and 59 (31.9%) had BI-Rads-II findings. The average age of the patients was 34.3568 years with a standard deviation of 11.69830. Conclusion: This study reveals a high frequency of breast lesions among women in Lahore, with 31.9% of participants presenting with sonographic abnormalities. The majority of lesions were seen on the left side and in the upper outer quadrant, highlighting the importance of comprehensive imaging methods in these areas.The connection of breast lesions with discomfort and menopausal status emphasises the significance of clinical examination in addition to imaging. These findings highlight the importance of early detection with routine breast ultrasonography in lowering the burden of breast illnesses.

Breast Lesions in Qassim Region, Saudi Arabia: A Retrospective Study.

A breast lesion is an unusual development in the breast tissue that typically appears as a lump or swelling. It encompasses a wide range of disorders, from benign to malignant, posing significant health challenges globally. The study was a retrospective study conducted at King Fahad Specialist Hospital (KFSH), Buraidah, Qassim region in Saudi Arabia between March 10, 2017, and April 2, 2024. Data was cleaned, coded, and analyzed using SPSS version 27. The results revealed that most (639 (79.7%)) patients had symptomatic clinical presentations, with breast lump (470 (73.5%)) being the main presenting symptom. The majority (565 (70.4%)) of the patients presented malignant conditions, while 237 (29.6%) presented benign conditions. Of the patients who presented benign conditions, more than half (131 (55.3%)) were fibroadenoma benign lesions. Stage IIB cancer was the most common, constituting 192 (33.9%) of the patients. No complications were reported in the majority (480 (85.0%)). The study revealed a considerably high prevalence of malignant conditions among patients.Fibroadenoma was the most common breast lesion type, followed by intra-ductal papilloma and benign phyllodes. Age and BMI were found to be the risk factors that predicted the development of breast cancers. Knowledge and awareness of the prevalence, risk factors, and treatment of breast illnesses, as well as early screening and diagnosis, promote better patient outcomes and healthcare delivery.

Meta-analysis of contrast-enhanced ultrasound in differential diagnosis of breast adenosis and breast cancer.

This systematic review and meta-analysis study aimed to determine the total capacity of contrast-enhanced ultrasound (CEUS) in the differential diagnosis of breast lesions and breast cancer. For collecting papers, four groups of keywords were searched in five databases. The required information was extracted from the selected papers. In addition to the descriptive findings, a meta-analysis was also conducted. Thirty-three of thirty-six studies (91.67%) on the differential diagnosis of various degrees and types of breast lesions showed that CEUS has proper performance. The pooled values related to the sensitivity and specificity of CEUS were computed by 88.00 and 76.17.

MELODY: A prospective non-interventional multicenter cohort study to evaluate different imaging-guided methods for localization of malignant breast lesions (EUBREAST-4/iBRA-NET).

TPS623 Background: In the last decades, the proportion of breast cancer patients receiving breast-conserving surgery has increased, reaching 70-80% in developed countries. In case of non-palpable lesions, surgical excision requires some form of breast localization. While wire-guided localization has long been considered gold standard, it carries several limitations, including logistical difficulties, the potential for displacement and patient discomfort, and re-excision rates reaching 21%. Other techniques (radioactive seed or radio-occult lesion localization, intraoperative ultrasound, magnetic, radiofrequency, and radar localization) have been developed with the aim of overcoming these disadvantages. However, comparative data on the rates of successful lesion removal, negative margins, and re-operations are limited. In most studies, the patient perspective, addressing e.g. discomfort and pain, has not been evaluated. The aim of MELODY (Methods for Localization of Different Types of Breast Lesions) is to evaluate different imaging-guided localization methods with regard to oncological safety, patient-reported outcomes, and surgeon and radiologist satisfaction. Methods: The EUBREAST and the iBRA-NET have initiated the MELODY study to assess breast localization techniques and devices from several perspectives (NCT05559411, http://eubreast.org/melody ). MELODY is a prospective intergroup cohort study which enrolls female and male patients. planned for breast-conserving surgery with imaging-guided localization for invasive breast cancer or DCIS. Multiple or bilateral lesions and neoadjuvant chemotherapy are allowed. Primary outcomes are: 1) Intended target lesion and/or marker removal and 2) Negative resection margin rates. Secondary outcomes are, among others: rates of second surgery and secondary mastectomy, Resection Ratio (defined as actual resection volume divided by the calculated optimum specimen volume), duration of surgery, marker dislocation rates, rates of marker placement or localization failure, patient-reported outcomes, rates of “lost markers”, radiologist and surgeon satisfaction, and health economic evaluation of the different techniques. Target accrual: 7,416 patients. The study will be conducted in 30 countries. Clinical trial information: NCT05559411 .

Abstract PO4-18-12: MELODY: A prospective non-interventional multicenter cohort study to evaluate different imaging-guided methods for localization of malignant breast lesions (EUBREAST-4/iBRA-NET, NCT 05559411)

Abstract Background: In the last decades, the proportion of breast cancer patients receiving breast-conserving surgery has increased, reaching 70-80% in developed countries. In case of non-palpable lesions, surgical excision requires some form of breast localization. While wire-guided localization has long been considered gold standard, it carries several limitations, including logistical difficulties, the potential for displacement and patient discomfort, and re-excision rates reaching 21%. Other techniques (radioactive seed or radio-occult lesion localization, intraoperative ultrasound, magnetic, radiofrequency and radar localization) have been developed with the aim of overcoming these disadvantages. However, comparative data on the rates of successful lesion removal, negative margins and re-operations are limited. In the majority of studies, the patient’s perspective with regard to discomfort and pain level has not been evaluated. The aim of MELODY (MEthods for LOcalization of Different types of breast lesions) is to evaluate different imaging-guided localization methods with regard to oncological safety, patient-reported outcomes, and surgeon and radiologist satisfaction. Methods: The EUBREAST and the iBRA-NET have initiated the MELODY study to assess breast localization techniques and devices from several perspectives (NCT05559411, http://melody.eubreast.com). MELODY is a prospective intergroup cohort study which enrolls female and male pts. requiring breast-conserving surgery and imaging-guided localization for invasive breast cancer or DCIS. Multiple or bilateral lesions and neoadjuvant chemotherapy are allowed. Primary outcomes are: 1) Intended target lesion and/or marker removal, independent of margin status on final histopathology, and 2) Negative resection margin rates at first surgery. Secondary outcomes are, among others: rates of second surgery and secondary mastectomy, Resection Ratio (defined as actual resection volume divided by the calculated optimum specimen volume), duration of surgery, marker dislocation rates, rates of marker placement or localization failure, comparison of patient-reported outcomes, rates of “lost markers” and diagnostician/radiologist’s and surgeon’s satisfaction as well as the health economic evaluation of the different techniques. Target accrual: 7,416 patients. Enrollment started in January 2023. The study will be conducted in 30 countries and is supported by the Oncoplastic Breast Consortium (OPBC), AWOgyn, AGO-B and SENATURK. Financial support will be provided by Endomag, Merit Medical, Sirius Medical and Hologic. Citation Format: Maggie Banys-Paluchowski, Thorsten Kühn, Yazan Masannat, Nina Ditsch, Antonio Esgueva, Neslihan Cabıoğlu, Dawid Murawa, Nuh Zafer Canturk, Isabel Rubio, Jana de Boniface, Andreas Karakatsanis, Rajiv Dave, Shelley Potter, Ashutosh Kothari, Oreste Davide Gentilini, Walter Weber, Natalia Krawczyk, Steffi Hartmann, Guldeniz Karadeniz Cakmak, Markus Hahn, Michael P. Lux, Tove Tvedskov, Lina Pankratjevaite, Michalis Kontos, Florentia Peintinger, Aoife Lowery, Marjolein Smidt, Lia Rebaza, Maria Vasconcelos, Bahadir M. Gulluoglu, Bilge Aktas Sezen, Rosa Di Micco, Sarah Nietz, Francois Malherbe, Maria Luisa Gasparri, Séverine Alran, SVS Deo, Mah Muneer Khan, James Harvey. MELODY: A prospective non-interventional multicenter cohort study to evaluate different imaging-guided methods for localization of malignant breast lesions (EUBREAST-4/iBRA-NET, NCT 05559411) [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-18-12.

Current and Future Role of HIFU in Obstetric Gynaecology

Obstetric gynaecology, as a field in which diagnostic ultrasound has quickly found its place, especially in screening for birth defects and monitoring pregnancies, is also a speciality in which therapeutic ultrasound is used extensively.In pelvic gynaecology, HIFU therapy is used more specifically in two types of uterine conditions: fibroids and adenomyosis. In both cases, studies have shown significant efficacy in reducing pain and bleeding associated with the conditions, secondarily (more moderately but still significantly) reducing the volume of the lesions. Impact on fertility has yet to be demonstrated.In rectosigmoid endometriosis, clinical data indicates good treatment feasibility and significant efficacy on digestive and gynaecologic pain symptoms, as well as on quality of life, with no associated severe complications. Should the efficacy of HIFU in treating endometriosis be confirmed over time, it could revolutionise the management of digestive endometriosis by offering a valid minimally invasive alternative to rectosigmoid surgery.In senology, where visible scars have a particularly significant psychological impact, several teams have been researching the use of HIFU for the destruction of some types of breast lesions (fibroadenomas and breast tumours).In obstetrics, HIFU could become a treatment of choice for vascular anomalies such as twin-to-twin transfusion syndrome in twin pregnancies. Promising studies are also available regarding the use of HIFU in the treatment of post-partum placenta accreta.

Using the Kaiser Score as a clinical decision rule for breast lesion classification: Does computer-assisted curve type analysis improve diagnosis?

PurposeWe aimed to investigate the effect of using visual or automatic enhancement curve type assessment on the diagnostic performance of the Kaiser Score (KS), a clinical decision rule for breast MRI. MethodThis IRB-approved retrospective study analyzed consecutive conventional BI-RADS 0, 4 or 5 patients who underwent biopsy after 1.5T breast MRI according to EUSOBI recommendations between 2013 and 2015. The KS includes five criteria (spiculations; signal intensity (SI)-time curve type; margins of the lesion; internal enhancement; and presence of edema) resulting in scores from 1 (=lowest) to 11 (=highest risk of breast cancer). Enhancement curve types (Persistent, Plateau or Wash-out) were assessed by two radiologists independently visually and using a pixel-wise color-coded computed parametric map of curve types. KS diagnostic performance differences between readings were compared by ROC analysis. ResultsIn total 220 lesions (147 benign, 73 malignant) including mass (n = 148) and non-mass lesions (n = 72) were analyzed. KS reading performance in distinguishing benign from malignant lesions did not differ between visual analysis and parametric map (P = 0.119; visual: AUC 0.875, sensitivity 95 %, specificity 63 %; and map: AUC 0.901, sensitivity 97 %, specificity 65 %). Additionally, analyzing mass and non-mass lesions separately, showed no difference between parametric map based and visual curve type-based KS analysis as well (P = 0.130 and P = 0.787). ConclusionsThe performance of the Kaiser Score is largely independent of the curve type assessment methodology, confirming its robustness as a clinical decision rule for breast MRI in any type of breast lesion in clinical routine.

Immunohistochemistry in the Diagnosis and Classification of Breast Tumors.

In the clinical practice of breast pathology, immunohistochemistry (IHC) of different markers is widely used for the diagnosis and classification of breast lesions. To provide an overview of currently used and recently identified IHC stains that have been implemented in the field of diagnostic breast pathology. Data were obtained from literature review and clinical experience of the authors as breast pathologists. In the current review, we summarize the common uses of IHC stains for diagnosing different types of breast lesions, especially invasive and noninvasive breast lesions, and benign and malignant spindle cell lesions. In addition, the cutting-edge knowledge of diagnostic carcinoma markers will lead us to further understand the different types of breast carcinoma and differentiate breast carcinomas from other carcinomas of similar morphology. Knowing the strengths and limitations of these markers is essential to the clinical practice of breast pathology.

Breast Cancer Classification through Meta-Learning Ensemble Technique Using Convolution Neural Networks.

This study aims to develop an efficient and accurate breast cancer classification model using meta-learning approaches and multiple convolutional neural networks. This Breast Ultrasound Images (BUSI) dataset contains various types of breast lesions. The goal is to classify these lesions as benign or malignant, which is crucial for the early detection and treatment of breast cancer. The problem is that traditional machine learning and deep learning approaches often fail to accurately classify these images due to their complex and diverse nature. In this research, to address this problem, the proposed model used several advanced techniques, including meta-learning ensemble technique, transfer learning, and data augmentation. Meta-learning will optimize the model's learning process, allowing it to adapt to new and unseen datasets quickly. Transfer learning will leverage the pre-trained models such as Inception, ResNet50, and DenseNet121 to enhance the model's feature extraction ability. Data augmentation techniques will be applied to artificially generate new training images, increasing the size and diversity of the dataset. Meta ensemble learning techniques will combine the outputs of multiple CNNs, improving the model's classification accuracy. The proposed work will be investigated by pre-processing the BUSI dataset first, then training and evaluating multiple CNNs using different architectures and pre-trained models. Then, a meta-learning algorithm will be applied to optimize the learning process, and ensemble learning will be used to combine the outputs of multiple CNN. Additionally, the evaluation results indicate that the model is highly effective with high accuracy. Finally, the proposed model's performance will be compared with state-of-the-art approaches in other existing systems' accuracy, precision, recall, and F1 score.

MELODY (Methods for Localization of Different Types of Breast Lesions): A prospective non-interventional multicenter cohort study to evaluate different imaging-guided methods for localization of malignant breast lesions (EUBREAST-4/iBRA-NET).

TPS626 Background: In the last decades, the proportion of breast cancer patients receiving breast-conserving surgery has increased, reaching 70-80% in developed countries. In case of non-palpable lesions, surgical excision requires some form of breast localization. While wire-guided localization has long been considered gold standard, it carries several limitations, including logistical difficulties, the potential for displacement and patient discomfort, and re-excision rates reaching 21%. Other techniques (radioactive seed or radio-occult lesion localization, intraoperative ultrasound, magnetic, radiofrequency and radar localization) have been developed with the aim of overcoming these disadvantages. However, comparative data on the rates of successful lesion removal, negative margins and re-operations are limited. In the majority of studies, the patient’s perspective with regard to discomfort and pain level has not been evaluated. The aim of MELODY is to evaluate different imaging-guided localization methods with regard to oncological safety, patient-reported outcomes, and surgeon and radiologist satisfaction. Methods: The EUBREAST and the iBRA-NET have initiated the MELODY study to assess breast localization techniques and devices from several perspectives (NCT05559411, http://melody.eubreast.com ). MELODY is a prospective intergroup cohort study which enrolls female and male pts. requiring breast-conserving surgery and imaging-guided localization for invasive breast cancer or DCIS. Multiple or bilateral lesions and neoadjuvant chemotherapy are allowed. Primary outcomes are: 1) Intended target lesion and/or marker removal, independent of margin status on final histopathology, and 2) Negative resection margin rates at first surgery. Secondary outcomes are, among others: rates of second surgery and secondary mastectomy, Resection Ratio (defined as actual resection volume divided by the calculated optimum specimen volume), duration of surgery, marker dislocation rates, rates of marker placement or localization failure, comparison of patient-reported outcomes, rates of “lost markers” and diagnostician/radiologist’s and surgeon’s satisfaction as well as the health economic evaluation of the different techniques. Target accrual: 7,416 patients. Enrollment started in January 2023. The study will be conducted in 20 countries and is supported by the Oncoplastic Breast Consortium (OPBC), AWOgyn, AGO-B and SENATURK. Clinical trial information: NCT05559411 .

Trans-axillary single port insufflation technique-assisted endoscopic surgery for breast diseases: Clinic experience, cosmetic outcome and oncologic result.

With an increasing demand for postoperative cosmetic effects in breast diseases, the single port by trans-axillary incision and air-inflation system, which provided better space and spared the assistant the effort of retraction, is widely used in clinic surgical treatment for multiple breast diseases. According to inclusion and exclusion criteria, patients who underwent trans-axillary single-incision surgery at Tianjin Medical University Cancer Hospital between December 2020 and July 2022 were included in the study. We collected and analyzed data on age, fertility history, ultrasound grade, clinical stage, pathological results, oncological prognosis, patient-centered cosmetic outcome, etc. A total of 115 cases were included, of which 33 patients with benign disease underwent mass resection, 68 patients with malignant tumors underwent mastectomy. 10 patients had a special type of breast lesion. A mastectomy was performed in 4 patients with male mammary gland development. Of the 115 cases, the maximum mass diameter was 3.00 ± 1.644 (0.6-8.5) cm. Blood loss during surgery was 85.77 ± 50.342 (10-200) ml. The surgery took 131.84 ± 59.332 (30-280) minutes to complete. The patient spent a total of 5.05 ± 2.305 (2-18) days in the hospital. And the length of surgical incision in all patients was 3.83 ± 0.884 (3-8) cm. All patients were very satisfied with the appearance of their breasts after dressing. 94.78% of patients were satisfied with the position of the incision. Through this study, we believe that in benign breast diseases and malignant breast tumors, trans-axillary single port insufflation technique-assisted endoscopic surgery has oncological safety and an aesthetic effect for most people with breast diseases.

Exploration of utility of combined optical photothermal infrared and Raman imaging for investigating the chemical composition of microcalcifications in breast cancer.

Microcalcifications play an important role in cancer detection. They are evaluated by their radiological and histological characteristics but it is challenging to find a link between their morphology, their composition and the nature of a specific type of breast lesion. Whilst there are some mammographic features that are either typically benign or typically malignant often the appearances are indeterminate. Here, we explore a large range of vibrational spectroscopic and multiphoton imaging techniques in order to gain more information about the composition of the microcalcifications. For the first time, we validated the presence of carbonate ions in the microcalcifications by O-PTIR and Raman spectroscopy at the same time, the same location and the same high resolution (0.5 μm). Furthermore, the use of multiphoton imaging allowed us to create stimulated Raman histology (SRH) images which mimic histological images with all chemical information. In conclusion, we established a protocol for efficiently analysing the microcalcifications by iteratively refining the area of interest.

Effects of Hormones on Breast Development and Breast Cancer Risk in Transgender Women.

Transgender women experience gender dysphoria due to a gender assignment at birth that is incongruent with their gender identity. Transgender people undergo different surgical procedures and receive sex steroids hormones to reduce psychological distress and to induce and maintain desired physical changes. These persons on feminizing hormones represent a unique population to study the hormonal effects on breast development, to evaluate the risk of breast cancer and perhaps to better understand the precise role played by different hormonal components. In MTF (male to female) patients, hormonal treatment usually consists of antiandrogens and estrogens. Exogenous hormones induce breast development with the formation of ducts and lobules and an increase in the deposition of fat. A search of the existing literature dedicated to hormone regimens for MTF patients, their impact on breast tissue (incidence and type of breast lesions) and breast cancer risk provided the available information for this review. The evaluation of breast cancer risk is currently complicated by the heterogeneity of administered treatments and a lack of long-term follow-up in the great majority of studies. Large studies with longer follow-up are required to better evaluate the breast cancer risk and to understand the precise mechanisms on breast development of each exogenous hormone.

Natural Language Processing Approaches for Automated Multilevel and Multiclass Classification of Breast Lesions on Free-Text Cytopathology Reports.

The extensive growth and use of electronic health records (EHRs) and extending medical literature have led to huge opportunities to automate the extraction of relevant clinical information that helps in concise and effective clinical decision support. However, processing such information has traditionally been dependent on labor-intensive processes with human errors such as fatigue, oversight, and interobserver variability. Hence, this study aims at the processing of EHRs and performing multilevel and multiclass classification by fetching dominant characteristic features that are sufficient to detect and differentiate various types of breast lesions. In this study, unstructured EHRs on breast lesions obtained through fine-needle aspiration cytology technique are considered. The raw text was normalized into structured tabular form and converted to scores by performing sentiment analysis that helps to decide the total polarity or class label of the EHR. Supervised machine learning approaches, namely random forest and feed-forward neural network trained using Levenberg-Marquardt training function, are used for classification of the collected EHR data set containing 2,879 records that are split in the ratio of 80:20 as training and testing data sets, respectively. Random forest and feed-forward neural network classifiers gave the best performance with an accuracy of 99.36%, an overall receiver operating characteristic-area under the curve of 99.2%, a correlation with ground truth of 98.3%, and a histopathologic correlation of 98.6%. Natural language processing has huge potential to automate the extraction of clinical features from breast lesions. The proposed multilevel and multiclass classification approach is used to classify 13 different types of breast lesions with 20 different labels into five classes to decide the type of treatment that should be given to patients by a physician or oncologist.

Lesion-specific exposure parameters for breast cancer diagnosis on digital breast tomosynthesis and full-field digital mammography

ObjectivesTo explore lesion-specific exposure parameters on digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) and evaluate their efficiency for breast cancer diagnosis. MethodsWe reviewed the DBT and FFDM images of 492 women with unilateral breast lesions and compared the findings with a healthy group comprising the contralateral breasts of all patients. The tube voltage (kVp), tube load (mAs), compressed breast thickness (CBT), and mean glandular dose (MGD) for each image were retrieved from the DICOM metadata, and the difference in MGD between DBT and FFDM images (△MGD) was calculated. Three models were developed to discriminate breast cancer: logistic model, comprising traditional risk factors alone; FFDM model, comprising exposure parameters from FFDM images alone, and a hybrid model, comprising traditional risk factors and exposure parameters from DBT and FFDM images. Model performance was assessed in an independent dataset of 189 women by determining the area under the receiver operating characteristic curve (AUC). ResultsThe malignant group showed greater kVp, mAs, CBT, and MGD values than the benign and healthy groups on both FFDM and DBT. Breast thickness, density, and lesion size were independently associated with △MGD. The hybrid model showed a significantly higher AUC value (0.78 ± 0.04) than the logistic (0.68 ± 0.05) and FFDM models (0.56 ± 0.05). ConclusionsThe breast lesion type has an influence on exposure parameters when using automatic exposure control. Our results provide evidence for lesion-specific exposure parameters, which can be helpful in distinguishing benign lesions from malignancies.

Evaluation of Different Types of Breast Lesions With Apparent Diffusion Coefficient and Shear Wave Elastography Values: Comparison of Shear Wave Elastography and Apparent Diffusion Coefficient in Breast Lesions

Objective: The aim of this study was to compare the stiffness of different histological types of breast lesions by obtaining shear wave elastography (SWE) and apparent diffusion coefficient (ADC) values, and to determine the contribution of these two methods to the diagnosis. Materials and Methods: In total, 70 patients with biopsy-proven breast lesions were included in the study. The mean SWE values of breast lesions were recorded and ADC values of these lesions were calculated. Receiver operating characteristic (ROC) curve analyses and the diagnostic accuracies of SWE-ADC values were determined. Results: The mean SWE values were 45.47 ± 25.11 kPa and 3.51 ± 1.04 m/s in benign group, and 161.11 ± 219.34 kPa and 5.96 ± 1.06 m/s in malignant group, respectively. The mean ADC values were 1.38 ± 0.32 (×10–3 mm2/s) in benign group and 0.96 ± 0.22 (×10–3 mm2/s) in malignant group, respectively. When the diagnostic performances of both imaging modalities on mass stiffness are evaluated, statistically significant negative correlations were found between SWE lesion values and ADC lesion values. Conclusion: Evaluation of tissue elasticity has recently been used frequently in the diagnosis of breast diseases. SWE-ADC values, which are negatively correlated in the diagnosis of breast masses, may prove to be a powerful alternative diagnostic tool that can be used interchangeably, as appropriate.

Distribution Of The Breast Lesions Based On The Mammogram Scoring Among Different Age Groups

Background: The mammary glands are prone to various lesions, either benign or malignant, many of benign types that can mature to malignant if untreated. The breast glandular structure can undergo changes from puberty to pregnancy and menopause due to hormonal effects, so the type of lesion occurrence among women varies depending on the age.
 Aims: This study aimed to identify if there is an association between age and BIRADS classification and/ or association between age and type of lesions.
 Methods: One hundred women from the city of Kirkuk participated in this study; they underwent mammography screening for detecting breast lesions. The relationship between age and mammography screening classification has been analyzed.
 Results: There is a significant association between age and BIRADS, and the age over 40 year was more frequent in most scores of BIRADS classification. In addition the number of patients with breast lesions in both BIRADS-3 and BIRADS-4 increased significantly with age. On the other hand, there is no significant association between age and types of breast lesion. 
 Conclusion: There is significant association between age and BIRADS.

Is Elevated Choline on Magnetic Resonance Spectroscopy a Reliable Marker of Breast Lesion Malignancy?

BackgroundContemporary magnetic resonance imaging (MRI) of the breast represents a powerful diagnostic modality for cancer detection, with excellent sensitivity and high specificity. Magnetic resonance spectroscopy (MRS) is being explored as an additional tool for improving specificity in breast cancer detection, using multiparametric MRI. The aim of this study was to examine the possibility of 1H-MRS to discriminate malignant from benign breast lesions, using elevated choline (Cho) peak as an imaging biomarker.MethodsA total of 60 patients were included in this prospective study: 30 with malignant (average age, 55.2 years; average lesion size, 35 mm) and 30 with benign breast lesions (average age, 44.8 years; average lesion size, 20 mm), who underwent multiparametric MRI with multivoxel 3D 1H-MRS on a 1.5-T scanner in a 3-year period. Three patients with benign breast lesions were excluded from the study. All lesions were histologically verified. Peaks identified on 1H-MRS were lipid (0.9, 2.3, 2.8, and 5.2 ppm), choline (3.2 ppm), and water peaks (4.7 ppm). Sensitivity and specificity, as well as positive and negative predictive values, were defined using ROC curves. Cohen’s Kappa test of inter-test reliability was performed [testing the agreement between 1H-MRS and histologic finding, and 1H-MRS and MR mammography (MRM)].ResultsCholine peak was elevated in 24/30 malignant lesions and in 20/27 benign breast lesions. The sensitivity of 1H-MRS was 0.8, specificity was 0.741, positive predictive value was 0.774, and negative predictive value was 0.769. Area under ROC was 0.77 (CI 0.640–0.871). Inter-test reliability between 1H-MRS and histologic finding was 0.543 (moderate agreement) and that between 1H-MRS and MRM was 0.573 (moderate agreement). False-negative findings were most frequently observed in invasive lobular cancers, while false-positive findings were most frequently observed in adenoid fibroadenomas.ConclusionAlthough elevation of the choline peak has a good sensitivity and specificity in breast cancer detection, both are significantly lower than those of multiparametric MRM. Inclusion of spectra located on tumor margins as well as analysis of lipid peaks could aid both sensitivity and specificity. An important ratio of false-positive and false-negative findings in specific types of breast lesions (lobular cancer and adenoid fibroadenoma) suggests interpreting these lesions with a caveat.

Does automated breast ultrasound (ABUS) add to breast tomosynthesis (DBT) in assessment of lesions in dense breasts?

BackgroundAs mammography has its known limitations in dense breast, additional imaging is usually needed. We aimed to evaluate the role of automated breast ultrasound in addition to tomosynthesis in detection and diagnosis of breast lesions in dense breasts. Seventy patients with dense breasts subjected to full-field digital mammography (FFDM) including digital breast tomosynthesis (DBT) and automated breast ultrasound (ABUS). Both studies were evaluated by two experienced radiologists to assess breast composition, mass characterization, asymmetry, calcification, axillary lymphadenopathy, extent of disease (EOD), skin thickening, retraction, architectural distortion, and BIRADS classification. All breast masses were interpreted as above described and then correlated with final pathological diagnosis.ResultsStudy included 70 females presenting with different types of breast lesions. Eighty-two masses were detected: 53 benign (n = 53/82), 29 malignant (n = 29/82). Histopathology of the masses was reached by core biopsy (n = 30), FNAC (n = 14), and excisional biopsy (n = 11). The rest of the masses (n = 27/82) were confirmed by their characteristic sonographic appearances; 20 cases of multiple bilateral anechoic simple cysts, 7 typical fibroadenomas showed stationary course on follow-up. As regards the final BIRADS score given for both modalities, tomosynthesis showed accuracy of 93.1% in characterization of malignant masses with accuracy of 94.3% in benign masses, on the other hand automated ultrasound showed 100% accuracy in characterization of malignant masses with 98.1% accuracy in benign masses.ConclusionAdding ABUS to tomosynthesis has proven a valuable imaging tool for characterization of breast lesions in dense breasts both as screening and diagnostic tool. They proved to be more sensitive and specific than digital mammography alone in showing tissue overlap, tumor characterization, lesion margins, extent, and multiplicity of malignant lesions.

Deep learning of mammary gland distribution for architectural distortion detection in digital breast tomosynthesis

Computer aided detection (CADe) for breast lesions can provide an important reference for radiologists in breast cancer screening. Architectural distortion (AD) is a type of breast lesion that is difficult to detect. A majority of CADe methods focus on detecting the radial pattern, which is a main characteristic of typical ADs. However, a few atypical ADs do not exhibit such a pattern. To improve the performance of CADe for typical and atypical ADs, we propose a deep-learning-based model that used mammary gland distribution as prior information to detect ADs in digital breast tomosynthesis (DBT). First, information about gland distribution, including the Gabor magnitude, the Gabor orientation field, and a convergence map, were produced using a bank of Gabor filters and convergence measures. Then, this prior information and an original slice were input into a Faster R-CNN detection network to obtain the 2-D candidates for each slice. Finally, a 3-D aggregation scheme was employed to fuse these 2-D candidates as 3-D candidates for each DBT volume. Retrospectively, 64 typical AD volumes, 74 atypical AD volumes, and 127 normal volumes were collected. Six-fold cross-validation and mean true positive fraction (MTPF) were used to evaluate the model. Compared to an existing convergence-based model, our proposed model achieved an MTPF of 0.53 ± 0.04, 0.61 ± 0.05, and 0.45 ± 0.04 for all DBT volumes, typical + normal volumes, and atypical + normal volumes, respectively. These results were significantly better than those of 0.36 ± 0.03, 0.46 ± 0.04, and 0.28 ± 0.04 for a convergence-based model (p ≪ 0.01). These results indicate that employing the prior information of gland distribution and a deep learning method can improve the performance of CADe for AD.