Breast Ultrasound Examination Research Articles

Therapeutic impact of 18F-FDG PET/CT for initial staging in patients with clinical stage I and IIA, HER2-positive, or triple-negative breast cancer.

While 18F-FDG PET/CT (FDG-PET/CT) is consensual for clinical stage ≥ IIB breast cancers (BC), its benefit for stage I or IIA HER2+ or triple-negative breast cancer (TNBC) patients lacks sufficient evidence. We reported a single-institution, retrospective study evaluating FDG-PET/CT impact on patient management and staging for stage I or IIA HER2+ or Triple-Negative BC. Patients who underwent FDG-PET/CT staging before any treatment between January 2015 and December 2020 at Oscar Lambret Center were included. patients with symptoms or conventional imaging suggestive of metastatic dissemination, or with prior malignancies. Initial stage was determined from mammography, breast ultrasound, breast MRI, and clinical examination. Staging and therapeutic impact based on FDG-PET/CT findings collected, including intra- (modification of dose/site/strategy in a type of management previously indicated) and inter-modality (modification of planned treatment strategy) changes. The cohort included 287 female patients with clinical stage I or IIA, HER2+ , or TNBC. Therapeutic impact observed for 18% of patients (n = 52), with 2% (n = 7) undergoing inter-modality change with omission of planned surgery. The impact on patient management was higher for stage IIA patients (20%, 47/237) than for stage I patients (10%, 5/50). Among stage IIA disease, changes in management were more important for T2N0 patients (22%, 44/205) than for T1N1 patients (9%, 3/32). While not statistically significant, trends suggest usefulness of FDG-PET/CT for T2N0 patients. Considering substantial therapeutic implications, our study suggests the usefulness of FDG-PET/CT for patients with stage IIA, HER2-positive, or Triple-Negative BC with tumor size > 2cm (T2N0).

Diagnosis of some rare forms of breast cancer

Background. Breast cancer (BC) is a heterogeneous disease, in which it is crucial not only to detect the tumor, but also to determine its biological characteristics to choose an optimal treatment strategy. Herein, we review existing literature on the subject and analyze own data.Aim. To analyze clinical and morphological characteristics of rare histological types of BC.Materials and methods. In this retrospective study, we analyzed the results of instrumental examination of 180 patients with mucinous BC treated in Sverdlovsk Regional Oncology Dispensary between 2020 and 2022. The mean age of the participants was 62.5 years. All patients underwent comprehensive examination, including digital mammography using the Fujifilm Amulet Innovality system, multiparametric ultrasound breast examination using the EPIQ 5 system (Phillips, Netherlands), and 1.5 T dynamic contrast-enhanced magnetic resonance imaging with a 16-channel – dedicated breast coil (GE Healthcare, USA).Results and conclusion. The incidence of mucinous BC was 1.8 %. Other rare types of BC, such as occult, medullary, papillary, tubular, and cribriform cancer were observed in less than 1 % of cases, which is consistent with the available literature data. Mucinous tumors were primarily represented by luminal B histology (73.3 %); the Ki-67 proliferation index was usually 35 %. The most common radiological manifestation was a hyperdense formation with clear contours (85 %). Ultrasound examination usually revealed a hypoechoic formation with clear and irregular contours (92 %); however, 8 % of patients presented with isoechoic formations that can hardly be distinguished from the background. Magnetic resonance imaging showed the following patterns: mass (87.5 %) with a persistent type of contrast accumulation (56.2 %) (type I curve) or curve exhibiting a plateau (43.8 %) (type II curve). Contrast agent accumulation started from the first minutes and was >100 % in all patients. Limitation of diffusion was observed in 25 % of patients. Patients with mucinous BC were usually characterized by late manifestation; 3 patients additionally had other cancers, including colorectal cancer, mucoepidermal tumor of the salivary gland, pancreatic cancer. None of these patients had family history of cancer. Isolated findings of X-ray mammography, ultrasound, and magnetic resonance imaging suggested benign breast tumors and no cancer-specific features.A multimodal approach enabled early detection of non-specific signs of rare forms of BC characterized by a specific clinical pattern with symptoms typical of this particular cancer from.

Abstract PO1-01-07: Cryoablation and endocrine therapy for clinical stage I/II, ER+ breast cancer in patients with omission of surgical axillary staging. A retrospective study

Abstract OBJECTIVE To evaluate the efficacy of combined treatment with ultrasound-guided cryoablation and endocrine therapy (ET) in hormone receptor-positive (ER+), HER2-negative (HER-) invasive breast cancer (BC) patients with clinical stage I/II who are not candidates for axillary surgery. PATIENTS AND METHODS Patients with ER+, HER- invasive BC in clinical stage I/II who did not undergo sentinel lymph node biopsy (SLNB) or target axillary dissection (TAD) were included. They received treatment consisting of ultrasound-guided cryoablation combined with daily letrozole 2.5 mg orally. Cryoablation was performed as the initial treatment for BC < 15mm, followed by adjuvant ET, while neoadjuvant ET was administered for 6-12 months before cryoablation for BC ≥ 15mm. Cryoablation was performed using the ICEfx Galil argon gas system (Boston Scientific, USA) and the ProSense liquid nitrogen system (IceCure Medical Ltd, Caesarea, Israel). Follow-up breast ultrasound examinations were conducted every six months. Patients with a minimum follow-up of 12 months after cryoablation were included in the study. Core needle biopsies were performed if recurrence was suspected, and rescue cryoablation was considered for confirmed relapse. The tolerance and safety of the procedures were recorded. RESULTS From March 2019 to July 2023, a total of 96 patients with 105 ER+, HER2- invasive BC in clinical stage I/II who did not undergo SLNB or TAD were treated with ultrasound-guided cryoablation and ET. Among them, 58 patients (aged 58-96 years, mean 83, SD ±7.64) with 64 BC lesions (ranging from 5 to 60mm, mean 17, SD ±13.75) were followed up for a minimum of 12 months, with a mean follow-up period of 24 months (ranging from 12 to 50 months). The invasive carcinomas included 40 ductal, 16 lobular, 5 colloid, and 3 papillary cases. The ipsilateral breast tumor recurrence rate was 1,72% (1/58 patients). One patient with lobular carcinoma experienced a relapse at 17 months. Rescue cryoablation was performed, and after 25 months, she remains free of recurrence. Therefore, local control was achieved in all patients. Six patients died from causes unrelated to BC during the follow-up period. All procedures were well-tolerated with local anesthesia, and no serious complications were reported. CONCLUSION Ultrasound-guided cryoablation with ET constitutes an effective combined treatment for the local control of ER+, HER2- BC in patients with clinical stage I/II and omission for surgical axillary staging. Cryoablation is a very well tolerated procedure without morbidity. Citation Format: José María Oliver Goldaracena, Pilar Zamora, Covadonga Marti, Vicenta Córdoba Chicote, Maria José Roca Navarro, Diego Garrido Alonso, Ylenia Navarro Monforte, Teresa Diaz de Bustamante Durban, Fernando García Martínez, Jose Ignacio Sanchez-Mendez, Elisa York Pineda, Laura Yebenes Gregorio, Adolfo Loayza, Laura Frías Aldeguer, Elisa Moreno Palacios, Marcos Melendez Gisper, Joaquin Gomez Ramirez, Luis Asensio Gómez, Virginia Martínez Marín, David Hardisson Hernáez, Alberto Berjón García. Cryoablation and endocrine therapy for clinical stage I/II, ER+ breast cancer in patients with omission of surgical axillary staging. A retrospective study [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 PO1-01-07.

Prospective study of AI-assisted prediction of breast malignancies in physical health examinations: role of off-the-shelf AI software and comparison to radiologist performance.

In physical health examinations, breast sonography is a commonly used imaging method, but it can lead to repeated exams and unnecessary biopsy due to discrepancies among radiologists and health centers. This study explores the role of off-the-shelf artificial intelligence (AI) software in assisting radiologists to classify incidentally found breast masses in two health centers. Female patients undergoing breast ultrasound examinations with incidentally discovered breast masses were categorized according to the 5th edition of the Breast Imaging Reporting and Data System (BI-RADS), with categories 3 to 5 included in this study. The examinations were conducted at two municipal health centers from May 2021 to May 2023.The final pathological results from surgical resection or biopsy served as the gold standard for comparison. Ultrasonographic images were obtained in longitudinal and transverse sections, and two junior radiologists and one senior radiologist independently assessed the images without knowing the pathological findings. The BI-RADS classification was adjusted following AI assistance, and diagnostic performance was compared using receiver operating characteristic curves. A total of 196 patients with 202 breast masses were included in the study, with pathological results confirming 107 benign and 95 malignant masses. The receiver operating characteristic curve showed that experienced breast radiologists had higher diagnostic performance in BI-RADS classification than junior radiologists, similar to AI classification (AUC = 0.936, 0.806, 0.896, and 0.950, p < 0.05). The AI software improved the accuracy, sensitivity, and negative predictive value of the adjusted BI-RADS classification for the junior radiologists' group (p< 0.05), while no difference was observed in the senior radiologist group. Furthermore, AI increased the negative predictive value for BI-RADS 4a masses and the positive predictive value for 4b masses among radiologists (p < 0.05). AI enhances the sensitivity of invasive breast cancer detection more effectively than ductal carcinoma in situ and rare subtypes of breast cancer. The AI software enhances diagnostic efficiency for breast masses, reducing the performance gap between junior and senior radiologists, particularly for BI-RADS 4a and 4b masses. This improvement reduces unnecessary repeat examinations and biopsies, optimizing medical resource utilization and enhancing overall diagnostic effectiveness.

Using Patient Navigation to Reduce Time to Diagnosis of Breast Cancer in Uganda

PurposeThe Ugandan Ministry of Health adopted BI-RADS as standard of care in 2016. The authors performed a medical audit of breast ultrasound practices at four tertiary-level hospitals to assess interpretive performance. The authors also determined the effect of a low-cost navigation program linking breast imaging and pathology on the percentage of patients completing diagnostic care. MethodsThe authors retrieved 966 consecutive diagnostic breast ultrasound reports, with complete data, for studies performed on women aged >18 years presenting with symptoms of breast cancer between 2018 and 2020 from participating hospitals. Ultrasound results were linked to tumor registries and patient follow-up. A medical audit was performed according to the ACR’s BI-RADS Atlas, fifth edition, and results were compared with those of a prior audit performed in 2013. At Mulago Hospital, an intervention was piloted on the basis of patient navigation, cost sharing, and same-day imaging, tissue sampling, and pathology. ResultsIn total, 888 breast ultrasound examinations (91.9%) were eligible for inclusion. Compared with 2013, the postintervention cancer detection rate increased from 38 to 148.7 cancers per 1,000 examinations, positive predictive value 2 from 29.6% to 48.9%, and positive predictive value 3 from 62.7% to 79.9%. Specificity decreased from 90.5% to 87.7% and sensitivity from 92.3% to 81.1%. The mean time from tissue sampling to receipt of a diagnosis decreased from 60 to 7 days. The intervention increased the percentage of patients completing diagnostic care from 0% to 100%. ConclusionsEfforts to establish a culture of continuous quality improvement in breast ultrasound require robust data collection that links imaging results to pathology and patient follow-up. Interpretive performance met BI-RADS benchmarks for palpable masses, except sensitivity. This resource-appropriate strategy linking imaging, tissue sampling, and pathology interpretation decreased time to diagnosis and rates of loss to follow-up and improved the precision of the audit.

The utility of quantifying the orientation of breast masses in ultrasound imaging.

The aim of this study was to quantify the orientation of breast masses and determine whether it can enhance the utility of a not parallel orientation in predicting breast mass malignancy. A total of 15,746 subjects who underwent breast ultrasound examinations were initially enrolled in the study. Further evaluation was performed on subjects with solid breast masses (≤ 5cm) intended for surgical resection and/or biopsy. The orientation angle, defined as the acute angle between the align of the maximal longitudinal diameter of the breast mass and the surface of the breast skin, was measured. Receiver operating characteristic (ROC) curve analysis was conducted, and various performance measures including sensitivity, specificity, positive and negative predictive values, accuracy, odds ratio, and the area under the ROC curve (AUC) were calculated. Multivariate analysis was performed to determine if the orientation angle was an independent predictor of breast malignancy. Decision curve analysis (DCA) was also conducted to assess the net benefit of adopting the orientation angle for predicting breast mass malignancy. The final analysis included 83 subjects with breast cancer and 135 subjects with benign masses. The intra-group correlation coefficient for the measurement of the orientation angle of breast masses was 0.986 (P = 0.001), indicating high reproducibility. The orientation angles of malignant and benign breast masses were 36.51 ± 14.90 (range: 10.7-88.6) degrees and 15.28 ± 8.40 (range: 0.0-58.7) degrees, respectively, and there was a significant difference between them (P < 0.001). The cutoff value for the orientation angle was determined to be 22.9°. The sensitivity, specificity, positive and negative predictive values, accuracy, odds ratio, and AUC for the prediction of breast malignancy using the orientation angle were 88.0%, 87.4%, 81.1%, 92.2%, 87.6%, 50.67%, and 0.925%, respectively. Multivariate analysis revealed that the orientation angle (> 22.9°), not circumscribed margin, and calcifications of the breast mass were independent factors predicting breast malignancy. The net benefit of adopting the orientation angle for predicting breast malignancy was 0.303. Based on these findings, it can be concluded that quantifying the orientation angle of breast masses is useful in predicting breast malignancy, as it demonstrates high sensitivity, specificity, AUC, and standardized net benefit. It optimizes the utility of the not parallel orientation in assessing breast mass malignancy.

Curated benchmark dataset for ultrasound based breast lesion analysis

A new detailed dataset of breast ultrasound scans (BrEaST) containing images of benign and malignant lesions as well as normal tissue examples, is presented. The dataset consists of 256 breast scans collected from 256 patients. Each scan was manually annotated and labeled by a radiologist experienced in breast ultrasound examination. In particular, each tumor was identified in the image using a freehand annotation and labeled according to BIRADS features and lexicon. The histopathological classification of the tumor was also provided for patients who underwent a biopsy. The BrEaST dataset is the first breast ultrasound dataset containing patient-level labels, image-level annotations, and tumor-level labels with all cases confirmed by follow-up care or core needle biopsy result. To enable research into breast disease detection, tumor segmentation and classification, the BrEaST dataset is made publicly available with the CC-BY 4.0 license.

A comparative study on the features of breast sclerosing adenosis and invasive ductal carcinoma via ultrasound and establishment of a predictive nomogram.

To analyze the clinical and ultrasonic characteristics of breast sclerosing adenosis (SA) and invasive ductal carcinoma (IDC), and construct a predictive nomogram for SA. A total of 865 patients were recruited at the Second Hospital of Shandong University from January 2016 to November 2022. All patients underwent routine breast ultrasound examinations before surgery, and the diagnosis was confirmed by histopathological examination following the operation. Ultrasonic features were recorded using the Breast Imaging Data and Reporting System (BI-RADS). Of the 865 patients, 203 (252 nodules) were diagnosed as SA and 662 (731 nodules) as IDC. They were randomly divided into a training set and a validation set at a ratio of 6:4. Lastly, the difference in clinical characteristics and ultrasonic features were comparatively analyzed. There was a statistically significant difference in multiple clinical and ultrasonic features between SA and IDC (P<0.05). As age and lesion size increased, the probability of SA significantly decreased, with a cut-off value of 36 years old and 10 mm, respectively. In the logistic regression analysis of the training set, age, nodule size, menopausal status, clinical symptoms, palpability of lesions, margins, internal echo, color Doppler flow imaging (CDFI) grading, and resistance index (RI) were statistically significant (P<0.05). These indicators were included in the static and dynamic nomogram model, which showed high predictive performance, calibration and clinical value in both the training and validation sets. SA should be suspected in asymptomatic young women, especially those younger than 36 years of age, who present with small-size lesions (especially less than 10 mm) with distinct margins, homogeneous internal echo, and lack of blood supply. The nomogram model can provide a more convenient tool for clinicians.

The application of traditional machine learning and deep learning techniques in mammography: a review.

Breast cancer, the most prevalent malignant tumor among women, poses a significant threat to patients' physical and mental well-being. Recent advances in early screening technology have facilitated the early detection of an increasing number of breast cancers, resulting in a substantial improvement in patients' overall survival rates. The primary techniques used for early breast cancer diagnosis include mammography, breast ultrasound, breast MRI, and pathological examination. However, the clinical interpretation and analysis of the images produced by these technologies often involve significant labor costs and rely heavily on the expertise of clinicians, leading to inherent deviations. Consequently, artificial intelligence(AI) has emerged as a valuable technology in breast cancer diagnosis. Artificial intelligence includes Machine Learning(ML) and Deep Learning(DL). By simulating human behavior to learn from and process data, ML and DL aid in lesion localization reduce misdiagnosis rates, and improve accuracy. This narrative review provides a comprehensive review of the current research status of mammography using traditional ML and DL algorithms. It particularly highlights the latest advancements in DL methods for mammogram image analysis and offers insights into future development directions.

Ultrasound as a Method for Early Diagnosis of Breast Pathology.

Ultrasound is a non-invasive, low-cost technique that does not use ionising radiation and provides a "real-time" image, and for these reasons, this method is ideal in several situations. To demonstrate breast ultrasound evaluation as a first-line diagnostic method and to evaluate the variation of breast characteristics with age. A total of 105 women with a mean age of 30 years participated and were divided into three age groups: 18-39, 40-59, and 60-79 years, excluding participants subject to mastectomy. After completing the informed consent, all participants answered personal and sociodemographic questions, such as personal and family history, menstrual cycle, pregnancy, ultrasound, and mammography, among others. They were then submitted to a bilateral breast ultrasound examination. Subsequently, all the images and their data were analysed, and a technical report of the examination was given to all the participants. A total of 105 women with a mean age of 30 years participated, 58 of whom underwent the examination for the first time. In 31, changes (of which only 7 were known) were diagnosed. It was verified that, according to age group, the density of the breast stroma varied; older women have less breast density. Ultrasound is a good method for breast evaluation and can be considered important for the early evaluation of breast pathology and follow-up of the pathology.

A Flexible and Fully Autonomous Breast Ultrasound Scanning System

The quality of breast ultrasound imaging is greatly affected by the contact force of the probe, which largely requires experienced sonographers to complete the clinical examination. We propose a flexible and fully autonomous ultrasound scanning system for breast ultrasound imaging. It consists of an ultrasound machine, a dual robotic arms system, a multi-structured light system, a human&#x2013;computer interaction system, and a flexible ultrasound probe clamping device (FUPCD). First, the dynamics model of the FUPCD was analyzed, and a closed-loop force control strategy was established. We then implemented an automatic scanning system. The hysteresis characteristics of the FUPCD and transient response of the force controller were experimentally verified. The system could keep the steady-state error less than <inline-formula> <tex-math notation="LaTeX">$\pm$</tex-math> </inline-formula> 5<inline-formula> <tex-math notation="LaTeX">$\%$</tex-math> </inline-formula> within 0.5 s. Second, the performance of the control system to maintain constant contact force at different scanning speeds (<inline-formula> <tex-math notation="LaTeX">$&lt;$</tex-math> </inline-formula>20 mm/s) was evaluated. In a series of comparative studies, the fluctuation range of the target contact force applied by the flexible automatic scanning was 10<inline-formula> <tex-math notation="LaTeX">$\%$</tex-math> </inline-formula>. The force control capability of the system was 30.84 times higher than that of traditional manual scanning, 18.48 times higher than that of flexible automatic scanning (FC off), and 24.3 times higher than that of rigid automatic scanning (FC on). Furthermore, the effectiveness of the FUPCD arc design and flexibility was verified. In addition, the change trend of the average grayscale level (GSL) of the ultrasound image was basically the same as the contact force, demonstrating that the stability and repeatability of the ultrasound image can be improved by controlling the stability of the contact force. In conclusion, the proposed system can simplify the workflow of breast ultrasound examination and improve the diagnostic capabilities of the ultrasound imaging system. <i>Note to Practitioners</i>&#x2014;The motivation of this study is to solve the problem of poor image reproducibility in breast ultrasound scanning, but the proposed system can also be applied to ultrasound scanning of other parts of the body. The position, direction, and contact force of the ultrasound probe affects the image quality and repeatability of the ultrasound, thereby affecting the diagnostic ability. Therefore, we propose and develop a flexible and fully autonomous breast ultrasound scanning system. We aimed to improve the autonomy and stability of the scanning process by designing end-to-end automated scanning strategies, flexible clamping devices, and closed-loop force control strategies. Among them, the fully automatic three-dimensional perception and trajectory planning can provide global fitting capabilities to different forms of breast surfaces and control the probe to maintain the best contact posture. At the same time, the fully automatic workflow reduces additional interference and reduces the complexity of the workflow. The flexible ultrasound probe clamping device improves the passive applicability to flexible tissues and reduces the resistance in the scanning process. The closed-loop force control strategy can adjust the contact force in real time. Experiments verified that the repeatability could be evaluated by contact force. A series of human&#x2013;machine comparison experiments verified the advancement and effectiveness of the system. In future research, we will further solve the problem of abnormalities and repeatability of ultrasound images acquired during the scanning process by combining the multi-modal feedback of images and forces.

Breast ultrasound diagnostic performance and outcomes for mass lesions in Dharma Yadnya general hospital in 2018-2023

Background: The latest report by the world health organization and international agency for research on cancer told that the incidence and mortality of breast cancer is the most among female cancer patients. Methods: This is descriptive study which uses medical record of 50 samples patients in Dharma Yadnya general hospital. This study include patients at least 25 years old who presented to the Dharma Yadnya general hospital between January 2019 to March 2023 which get breast ultrasound examination and pathology examination, benign or malignant mass. Results: In ultrasound findings, there are 43 (86%) people with benign cancer, 7 (14%) people with malignant cancer, 43 (86%) people with hipoechoic density and solid lession, 7 (14%) people with isoechoic density and cystic lession, 43 (86%) people with regular margin, 7 (14%) people with irregular margin, 43 (86%) people without lymph nodes axillary, 7 (14%) people with lymph nodes axillary, and by Doppler there are 43 (86%) people without neovascularitation inside lession and 7 (14%) people with neovascularitation inside lession. There are statistically significant relationship (p&lt;0.05) between diagnosis (benign and malignant) with age of patients, density, margin, existence of lymph nodes axillary, and neovascularitation inside the lession by doppler. Conclusions: Breast sonography is the modality of choice for further investigation of palpable breast findings that are not clearly benign and mammographic screen-detected abnormalities.

Evaluation of a population-based breast cancer screening in North China

BackgroundDespite mammography-based screening for breast cancer has been conducted in many countries, there are still little data on participation and diagnostic yield in population-based breast cancer screening in China.MethodsWe enrolled 151,973 eligible women from four cities in Hebei Province within the period 2013–2021 and followed up until December 31, 2021. Participants aged 40–74 who assessed as high risk were invited to undergo breast ultrasound and mammography examination. Overall and group-specific participation rates were calculated. Multivariable analyses were used to estimate the factors associated with participation rates. The diagnostic yield of both screening and no screening groups was calculated. We further analyzed the stage distribution and molecular subtype of breast cancer cases by different modes of cancer detection.ResultsA total of 42,547 participants were evaluated to be high risk of breast cancer. Among them, 23,009 subjects undertook screening services, with participation rate of 54.08%. Multivariable logistic regression model showed that aged 45–64, high education level, postmenopausal, current smoking, alcohol consumption, family history of breast cancer, and benign breast disease were associated with increased participation of screening. After median follow-up of 3.79 years, there were 456 breast cancer diagnoses of which 65 were screen-detected breast cancers (SBCs), 27 were interval breast cancers (IBCs), 68 were no screening cancers, and 296 were cancers detected outside the screening program. Among them, 92 participants in the screening group (0.40%) and 364 in the non-screening group (0.28%) had breast cancer detected, which resulted in an odds ratio of 1.42 (95% CI 1.13–1.78; P = 0.003). We observed a higher detection rate of breast cancer in the screening group, with ORs of 2.42 (95% CI 1.72–3.41) for early stage (stages 0–I) and 2.12 (95% CI 1.26–3.54) for luminal A subtype. SBCs had higher proportion of early stage (71.93%) and luminal A subtype (47.22%) than other groups.ConclusionsThe significant differences in breast cancer diagnosis between the screening and non-screening group imply an urgent need for increased breast cancer awareness and early detection in China.

Deep learning radiomics model based on breast ultrasound video to predict HER2 expression status.

The detection of human epidermal growth factor receptor 2 (HER2) expression status is essential to determining the chemotherapy regimen for breast cancer patients and to improving their prognosis. We developed a deep learning radiomics (DLR) model combining time-frequency domain features of ultrasound (US) video of breast lesions with clinical parameters for predicting HER2 expression status. Data for this research was obtained from 807 breast cancer patients who visited from February 2019 to July 2020. Ultimately, 445 patients were included in the study. Pre-operative breast ultrasound examination videos were collected and split into a training set and a test set. Building a training set of DLR models combining time-frequency domain features and clinical features of ultrasound video of breast lesions based on the training set data to predict HER2 expression status. Test the performance of the model using test set data. The final models integrated with different classifiers are compared, and the best performing model is finally selected. The best diagnostic performance in predicting HER2 expression status is provided by an Extreme Gradient Boosting (XGBoost)-based time-frequency domain feature classifier combined with a logistic regression (LR)-based clinical parameter classifier of clinical parameters combined DLR, particularly with a high specificity of 0.917. The area under the receiver operating characteristic curve (AUC) for the test cohort was 0.810. Our study provides a non-invasive imaging biomarker to predict HER2 expression status in breast cancer patients.

AI: Can It Make a Difference to the Predictive Value of Ultrasound Breast Biopsy?

(1) Background: This study aims to compare the ground truth (pathology results) against the BI-RADS classification of images acquired while performing breast ultrasound diagnostic examinations that led to a biopsy and against the result of processing the same images through the AI algorithm KOIOS DS TM (KOIOS). (2) Methods: All results of biopsies performed with ultrasound guidance during 2019 were recovered from the pathology department. Readers selected the image which better represented the BI-RADS classification, confirmed correlation to the biopsied image, and submitted it to the KOIOS AI software. The results of the BI-RADS classification of the diagnostic study performed at our institution were set against the KOIOS classification and both were compared to the pathology reports. (3) Results: 403 cases were included in this study. Pathology rendered 197 malignant and 206 benign reports. Four biopsies on BI-RADS 0 and two images are included. Of fifty BI-RADS 3 cases biopsied, only seven rendered cancers. All but one had a positive or suspicious cytology; all were classified as suspicious by KOIOS. Using KOIOS, 17 B3 biopsies could have been avoided. Of 347 BI-RADS 4, 5, and 6 cases, 190 were malignant (54.7%). Because only KOIOS suspicious and probably malignant categories should be biopsied, 312 biopsies would have resulted in 187 malignant lesions (60%), but 10 cancers would have been missed. (4) Conclusions: KOIOS had a higher ratio of positive biopsies in this selected case study vis-à-vis the BI-RADS 4, 5 and 6 categories. A large number of biopsies in the BI-RADS 3 category could have been avoided.

Pencegahan Kanker Payudara melalui Sadari dan Sadanis di Era Pandemi Covid-19

Breast cancer is a contributor to high mortality rates in women, with a mortality rate of 18% of women's deaths. Public awareness in recognizing and identifying cancer symptoms at an early stage is still low, making cancer in Indonesia more at an advanced stage. This community service activity aims to increase community knowledge and skills in preventing and detecting breast cancer early through counseling about breast cancer and breast self-examination (BSE). This partner is the activity of PKK cadres who contribute to the implementation of health education and health cadres in their area. Community service methods with breast cancer counseling and BSE training. In this activity, a clinical breast examination (SADANIS) was also carried out in the form of a breast ultrasound examination to detect any abnormalities in the breast by a Radiology specialist. The speaker delivered material on breast cancer prevention and participants were given a pocket book on breast cancer prevention. Prior to participating in the counseling, participants were tested for their knowledge of breast cancer prevention using a pretest. After getting the presentation of the material, a posttest was conducted. The results of the pre and post analysis showed an increase in participants' knowledge about breast cancer prevention. Community service with counseling, pocket books and health checks succeeded in increasing participants' knowledge about breast cancer prevention.Keywords: SADARI, SADANIS, breast cancer.

Вторичная профилактика опухолей репродуктивной системы у женщин, проживающих в городских и сельских условиях

Aim: to analyze specific aspects of diagnosing reproductive system disorders in women depending on the place of residence, medical activity and awareness of the female population, staffing resources and the availability of equipment in medical institutions. Patients and Methods: the analysis covered medical records of 9,785 women who, at their own volition, visited the medical center for medical check-up. Gynecological examination, colposcopy, liquid-based cytology, pelvic and breast ultrasound examination, and mammography were performed in all patients. The patients were asked to fill out a questionnaire including the following data: conditions of life and work, lifestyle, and risk factors of malignant tumors of the female reproductive system. Results and Discussion: women over 40 years of age were more concerned about their health status. Thus, it is necessary to find mechanisms for the additional motivation of women of early and middle reproductive age for expanding the screening coverage. It was found out that the differences in the organization of secondary prevention of reproductive system tumors in women living in the urban and rural environments are underpinned by the impact of demographic and social factors, characteristics of medical activity of the population, and staffing shortages in healthcare institutions. These aspects should be taken into consideration for developing methods aimed at overcoming the current failures in the diagnostic process. Conclusion: the establishing of regional "Women's Health Centers" based on multi-disciplinary comprehensive approach will help to improve the detection of tumors of the female reproductive system at the pre-cancer stage, facilitate the timely identification and mitigation of the risk factors of tumor development, and to ensure the prevention of recurrences and progression of hyperplastic processes of the reproductive system in women. KEYWORDS: tumors of reproductive system, prevention, diagnosis, organizational measures. FOR CITATION: Aminodova I.P., Vasiliev M.D., Makarova E.V., Makarova V.I. Secondary prevention of reproductive system tumors in women living in the urban and rural environments. Russian Journal of Woman and Child Health. 2023;6(2):112–118 (in Russ.). DOI: 10.32364/2618- 8430-2023-6-2-112-118.

Shear wave elastography as a supplemental tool in the assessment of unsuspicious axillary lymph nodes in patients undergoing breast ultrasound examination.

To define reference values for shear wave elastography (SWE) in unsuspicious axillary lymph nodes in patients undergoing breast ultrasound examination. In total, 177 clinically and sonographically unsuspicious axillary lymph nodes were prospectively evaluated with SWE using Virtual Touch Tissue Imaging Quantification (VTIQ) in 175 women. Mean values of tissue stiffness for axillary fatty tissue, lymph node cortex, and lymph node hilus were measured. Additionally, test-retest reliability of SWE in the assessment of axillary lymph node stiffness was evaluated by repeating each measurement three times. In 177 axillary lymph nodes, the mean stiffness of lymph node cortex, hilus, and surrounding fatty tissue as quantified by SWE was 1.90 m/s (SD: 0.34 m/s), 2.02 m/s (SD: 0.37 m/s), and 1.75 m/s (SD: 0.38 m/s), respectively. The mean stiffness of cortex and hilus was significantly higher compared to fatty tissue (p < 0.0001). SWE demonstrated good test-retest reliability in the assessment of stiffness of the lymph node hilus, cortex, and the surrounding fatty tissue with an intraclass correlation of 0.79 (95% CI: 0.75; 0.83), 0.75 (95% CI: 0.70; 0.79), and 0.78 (95% CI: 0.74; 0.82), respectively, (p < 0.0001). Reference values for SWE in unsuspicious axillary lymph nodes are determined. These results may help to better identify axillary lymph node metastasis for breast cancer patients when combined with other lymph node features. SWE is a reliable method for the objective quantification of tissue stiffness of axillary lymph nodes. This study presents physiological reference values for tissue stiffness by examining the axillary lymph nodes with SWE in 175 women with sonomorphologically unsuspicious lymph nodes.

Ultrasound Radiomics-Based Logistic Regression Model to Differentiate Between Benign and Malignant Breast Nodules.

To explore the potential value of ultrasound radiomics in differentiating between benign and malignant breast nodules by extracting the radiomic features of two-dimensional (2D) grayscale ultrasound images and establishing a logistic regression model. The clinical and ultrasound data of 1000 female patients (500 pathologically benign patients, 500 pathologically malignant patients) who underwent breast ultrasound examinations at our hospital were retrospectively analyzed. The cases were randomly divided into training and validation sets at a ratio of 7:3. Once the region of interest (ROI) of the lesion was manually contoured, Spearman's rank correlation, least absolute shrinkage and selection operator (LASSO) regression, and the Boruta algorithm were adopted to determine optimal features and establish a logistic regression classification model. The performance of the model was assessed using the area under the receiver operating characteristic curve (AUC), and calibration and decision curves (DCA). Eight ultrasound radiomic features were selected to establish the model. The AUC values of the model were 0.979 and 0.977 in the training and validation sets, respectively (P=.0029), indicating good discriminative ability in both datasets. Additionally, the calibration and DCAsuggested that the model's calibration efficiency and clinical application value were both superior. The proposed logistic regression model based on 2D grayscale ultrasound images could facilitate differential diagnosis of benign and malignant breast nodules. The model, which was constructed using ultrasound radiomic features identified in this study, demonstrated good diagnostic performance and could be useful in helping clinicians formulate individualized treatment plans for patients.

Evaluation of physician performance using a concurrent-read artificial intelligence system to support breast ultrasound interpretation

PurposeThe purpose of this study was to compare the diagnostic performance and the interpretation time of breast ultrasound examination between reading without and with the artificial intelligence (AI) system as a concurrent reading aid. Material and methodsA fully crossed multi-reader and multi-case (MRMC) reader study was conducted. Sixteen participating physicians were recruited and retrospectively interpreted 172 breast ultrasound cases in two reading scenarios, once without and once with the AI system (BU-CAD™, TaiHao Medical Inc.) assistance for concurrent reading. Interpretations of any given case set with and without the AI system were separated by at least 5 weeks. These reading results were compared to the reference standard and the area under the LROC curve (AUCLROC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for performance evaluations. The interpretation time was also compared between the unaided and aided scenarios. ResultsWith the help of the AI system, the readers had higher diagnostic performance with an increase in the average AUCLROC from 0.7582 to 0.8294 with statistically significant. The sensitivity, specificity, PPV, and NPV were also improved from 95.77%, 24.07%, 44.18%, and 93.50%–98.17%, 30.67%, 46.91%, and 96.10%, respectively. Of these, the improvement in specificity reached statistical significance. The average interpretation time was significantly reduced by approximately 40% when the readers were assisted by the AI system. ConclusionThe concurrent-read AI system improves the diagnostic performance in detecting and diagnosing breast lesions on breast ultrasound images. In addition, the interpretation time is effectively reduced for the interpreting physicians.