Breast Ultrasound Scanner Research Articles

Clinical application of novel mobile AI solution for real-time detection and differential diagnosis in breast ultrasound: The first prospective feasibility study.

574 Background: Existing artificial intelligence (AI) solutions for breast ultrasound faced limitations due to their non-real-time detection and server dependency. However, novel mobile real-time AI solution now enable on-device detection and differential diagnosis, aiding in immediate decision-making. This study aims to evaluate the feasibility and effectiveness of such a mobile AI solution in clinical settings, by comparing it against expert breast imaging diagnoses. Methods: From August to December 2023, a feasibility study was conducted in tertiary medical center of Taiwan using mobile AI solution (CadAI-B for breast, BeamWorks Inc., Korea). CadAI-B is connected via HDMI or DVI to an ultrasound equipment using tablet PC. It supports healthcare providers to detect suspicious breast lesions by highlighting suspicious area during breast ultrasound scanning, and to make a differential diagnosis by providing BI-RADS categories and malignancy score (0-100%). The rate of real-time detection in malignancies and area under the receiver operating characteristic curve (AUC) was calculated. Distribution of BI-RADS categorized by CadAI-B were compared with those by breast imaging experts on independent review. Results: The analysis included 33 patients with an average age of 47 years (IQR, 44 – 62). There were 14 malignancies, 17 benign lesions, and 2 normal cases, and 30 patients (90.9%) underwent biopsy. For patients with malignancies, CadAI-B successfully identified all malignancies. Overall diagnostic performance, as AUCs calculated by the malignancy score and BI-RADS, was 0.835 and 0.850, respectively. The per-patient sensitivity of CadAI-B was 100.0%, while the specificity was 52.6%. The BI-RADS distribution between CadAI-B and expert was the same in malignant cases. In benign cases, CadAI-B categorized 9 cases (50.0%) as C4A or C4B, while experts classified 13 cases (72.2%), indicating a potential reduction in the need for biopsy. Conclusions: This study demonstrates that real-time processing capabilities of CadAI-B enable the identification of critical lesions during breast ultrasound, helping to reduce unnecessary biopsy. These findings may be helpful in diagnostic decisions and training of non-experts in clinical settings and offer the potential to improve workflow efficiency. [Table: see text]

Patient perception of meander-like versus radial breast ultrasound.

Background Radial breast ultrasound scanning (r-US) and commonly used meander-like ultrasound scanning (m-US) have recently been shown to be equally sensitive and specific with regard to the detection of breast malignancies. As patient satisfaction has a strong influence on patient compliance and thus on the quality of health care, we compare here the two US scanning techniques with regard to patient comfort during breast ultrasound (BUS) and analyze whether the patient has a preference for either scanning technique. Materials and Methods Symptomatic and asymptomatic women underwent both m-US and r-US scanning by two different examiners. Patient comfort and preference were assessed using a visual analog scale-based (VAS) questionnaire and were compared using a Mann-Whitney U test. Results Analysis of 422 VAS-based questionnaires showed that perceived comfort with r-US (r-VAS 8 cm, IQR [5.3, 9.1]) was significantly higher compared to m-US (m-VAS 5.6 cm, IQR [5.2, 7.4]) (p < 0.001). 53.8% of patients had no preference, 44.3% of patients clearly preferred r-US, whereas only 1.9% of patients preferred m-US. Conclusion: Patients experience a higher level of comfort with r-US and favor r-US over m-US. As the diagnostic accuracy of r-US has been shown to be comparable to that of m-US and the time required for examination is shorter, a switch from m-US to r-US in routine clinical practice might be beneficial. R-US offers considerable potential to positively affect patient compliance but also to save examination time and thus costs.

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 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.

Full-Coverage Path Planning and Stable Interaction Control for Automated Robotic Breast Ultrasound Scanning

Ultrasound examination is widely used for diagnosis of breast cancer, which requires a full-coverage scan of the whole organ and stable probe–breast interaction for high-quality image acquisition. In this study, a robotic system for automated breast ultrasound scanning is proposed. To avoid occlusion, point cloud of the breast is obtained from multiple angles and registered together for accurate tissue shape reconstruction, then scan path planning is performed with isometric 3-D point cloud searching algorithm for full and uniform coverage. To reduce the adverse influence of large tissue deformation during ultrasound scanning, a contact force–strain regression model is built for tissue deformation estimation and used as a feedforward to correct the planned scanning path, and a probe–tissue interaction model with scanning resistance is built for normal probe orientation adjustment. To maintain normal probe orientation and stable contact force during robotic ultrasound scanning, a hybrid force–velocity control framework is proposed based on admittance control algorithm. Experiment results show that the robotic system can successfully maintain a constant contact force and keep the probe's posture along the normal orientation of probe–breast interaction both in in-plane direction and out-of-plane direction.

Ultrasound-guided breast biopsy using an adapted automated cone-based ultrasound scanner: a feasibility study.

Among available breast biopsy techniques, ultrasound (US)-guided biopsy is preferable because it is relatively inexpensive and provides live imaging feedback. The availability of magnetic resonance imaging (MRI)-3D US image fusion would facilitate US-guided biopsy even for US occult lesions to reduce the need for expensive and time-consuming MRI-guided biopsy. In this paper, we propose a novel Automated Cone-based Breast Ultrasound Scanning and Biopsy System (ACBUS-BS) to scan and biopsy breasts of women in prone position. It is based on a previously developed system, called ACBUS, that facilitates MRI-3D US image fusion imaging of the breast employing a conical container filled with a coupling medium. The purpose of this study was to introduce the ABCUS-BS system and demonstrate its feasibility for biopsy of US occult lesions. The biopsy procedure with the ACBUS-BS comprises four steps: target localization, positioning, preparation, and biopsy. The biopsy outcome can be impacted by 5 types of errors: due to lesion segmentation, MRI-3D US registration, navigation, lesion tracking during repositioning, and US inaccuracy (due to sound speed difference between the sample and the one used for image reconstruction). For the quantification, we use a soft custom-made polyvinyl alcohol phantom (PVA) containing 8 lesions (3 US-occult and 5 US-visible lesions of 10 mm in diameter) and a commercial breast mimicking phantom with a median stiffness of 7.6 kPa and 28 kPa, respectively. Errors of all types were quantified using the custom-made phantom. The error due to lesion tracking was also quantified with the commercial phantom. Finally, the technology was validated by biopsying the custom-made phantom and comparing the size of the biopsied material to the original lesion size. The average size of the 10-mm-sized lesions in the biopsy specimen was 7.00 ± 0.92 mm (6.33 ± 1.16 mm for US occult lesions, and 7.40 ± 0.55 mm for US-visible lesions). For the PVA phantom, the errors due to registration, navigation, lesion tracking during repositioning, and US inaccuracy were 1.33 mm, 0.30 mm, 2.12 mm, and 0.55 mm. The total error was 4.01 mm. For the commercial phantom, the error due to lesion tracking was estimated at 1.10 mm, and the total error was 4.11 mm. Given these results, the system is expected to successfully biopsy lesions larger than 8.22 mm in diameter. Patient studies will have to be carried out to confirm this in vivo. The ACBUS-BS facilitates US-guided biopsy of lesions detected in pre-MRI and therefore might offer a low-cost alternative to MRI-guided biopsy. We demonstrated the feasibility of the approach by successfully taking biopsies of 5 US-visible and 3 US-occult lesions embedded in a soft breast-shaped phantom. This article is protected by copyright. All rights reserved.

Iatrogenic Breast Lymphoedema: Incidence, Diagnosis, and Associated Risk Factors.

While upper limb lymphoedema following breast and axillary surgery is well established in the literature, breast lymphoedema is rarely documented. Our primary objective was to identify risk factors of breast lymphoedema, and our secondary aim was to assess the possibility of using a breast ultrasound scan to assess breast lymphoedema. This study was a case series analysis, including patients who had wide local excision for primary breast cancer treatment between January 2013 and January 2018. Patients' demographics, including age, weight, body mass index (BMI), breast volume, tumour characteristics, and histological findings, were noted. All patients had a clinical assessment and ultrasound scan 6months and 12months after surgery, comparing ipsilateral to the contralateral breast skin, subcutaneous thickness, as well as parenchymal changes. We have included two hundred eighty-six breast cancer; the mean age was 54.7years SD 17.3, the mean weight was 76.5kg SD 12.6, the mean BMI was 31.5 SD 5.2, and the mean breast volume was 1223ml SD 179. This study identified breast lymphoedema in patients with clinically detected skin oedema in the absence of radiotherapy skin changes; skin and subcutaneous 5mm added thickness more than the contralateral side, and based on that, 22 patients (7.7%) were found to have breast lymphoedema. We have also found that patients with high BMI, larger breast volume, upper outer quadrant tumours, and patients who had axillary lymph node clearance had an increased incidence of breast lymphoedema. The incidence of breast lymphoedema in this cohort was 7.7%. We suggest that breast lymphoedema should be considered if skin and subcutaneous thickness are 5mm more than the contralateral side in the absence of severe radiotherapy skin changes. Also, we have found that high body mass index (BMI), larger breast volume, upper outer quadrant tumours, and patients who had axillary lymph node clearance are associated with an increased incidence of breast lymphoedema.

Development and Testing of a Durable and Novel Breast Phantom for Robotic Autonomous Ultrasound Systems

For the safe and effective development of evolving autonomous medical robotic systems that traverse the surface of the body, like in breast ultrasound scans, developing phantoms that are durable and mechanically mimic human tissue is critical. In this work, a long lasting, inexpensive, and geometrically customizable phantom is described with mechanical and ultrasound acoustic properties that simulate human breast tissue. In comparison to prior work, a priority was designing a highly elastic phantom outer layer modulus 20 kPa and inner semi-liquid layer to mimic the difficulties of traversing human breast tissue with autonomous medical robotic systems. In addition, ultrasound images of the novel phantom with enclosed tumor are similar to in vivo image of human breast tissue with invasive ductal carcinoma, representing 80% of breast cancer cases. The performance of a force feedback controller on an autonomous ultrasound scanning system was compared for the novel phantom and a commercial phantom. Overall, the controller performed worse on the novel phantom — highlighting the importance of testing autonomous systems on realistic phantoms.

No sonographer, no radiologist: Assessing accuracy of artificial intelligence on breast ultrasound volume sweep imaging scans.

Breast ultrasound provides a first-line evaluation for breast masses, but the majority of the world lacks access to any form of diagnostic imaging. In this pilot study, we assessed the combination of artificial intelligence (Samsung S-Detect for Breast) with volume sweep imaging (VSI) ultrasound scans to evaluate the possibility of inexpensive, fully automated breast ultrasound acquisition and preliminary interpretation without an experienced sonographer or radiologist. This study was conducted using examinations from a curated data set from a previously published clinical study of breast VSI. Examinations in this data set were obtained by medical students without prior ultrasound experience who performed VSI using a portable Butterfly iQ ultrasound probe. Standard of care ultrasound exams were performed concurrently by an experienced sonographer using a high-end ultrasound machine. Expert-selected VSI images and standard of care images were input into S-Detect which output mass features and classification as "possibly benign" and "possibly malignant." Subsequent comparison of the S-Detect VSI report was made between 1) the standard of care ultrasound report by an expert radiologist, 2) the standard of care ultrasound S-Detect report, 3) the VSI report by an expert radiologist, and 4) the pathological diagnosis. There were 115 masses analyzed by S-Detect from the curated data set. There was substantial agreement of the S-Detect interpretation of VSI among cancers, cysts, fibroadenomas, and lipomas to the expert standard of care ultrasound report (Cohen's κ = 0.73 (0.57-0.9 95% CI), p<0.0001), the standard of care ultrasound S-Detect interpretation (Cohen's κ = 0.79 (0.65-0.94 95% CI), p<0.0001), the expert VSI ultrasound report (Cohen's κ = 0.73 (0.57-0.9 95% CI), p<0.0001), and the pathological diagnosis (Cohen's κ = 0.80 (0.64-0.95 95% CI), p<0.0001). All pathologically proven cancers (n = 20) were designated as "possibly malignant" by S-Detect with a sensitivity of 100% and specificity of 86%. Integration of artificial intelligence and VSI could allow both acquisition and interpretation of ultrasound images without a sonographer and radiologist. This approach holds potential for increasing access to ultrasound imaging and therefore improving outcomes related to breast cancer in low- and middle- income countries.

Metachronous Contralateral Breast Cancer in Ahmadu Bello University Teaching Hospital, Zaria, Northwestern Nigeria.

Breast cancer is the most frequent cancer of women. Metachronous contralateral breast cancer (MCBC) is a cancer in the contralateral breast after 6 months of the initial diagnosis of the first breast cancer. It is an important public health issue because of an increased incidence of a primary breast cancer and improved survival. There is a paucity of data in the Northwestern region of the country. The study was to document the incidence, the method of detection, clinicopathological features, and the treatment of MCBC in our hospital. It was a 7-year prospective study from January 2011 to December 2017. Patients who had treatment for nonmetastatic breast cancer, American Joint Committee on Cancer (AJCC) Stages 1-111, were followed up. Those that developed MCBC were studied. Age, the method of detection, stage at presentation, pathological types, hormone receptor status, and treatment were documented. Data obtained were analysed using SPSS version 21.0. Results were presented as simple percentages and charts. Of 1285 women with nonmetastatic breast cancer, 47 had MCBC (incidence of 3.7%); 30 (63.8%) were aged 21-50 years; 23 (48.9%) detected by self-breast examination; 13 (27.7%) by clinical breast examination; seven (14.9%) by mammography; and four (8.5%) by breast ultrasound scan. Fourteen (29.8%) were AJCC stage I; 23 (48.9%), stage II; seven (14.9%), stage III; and three (6.4%), stage IV. Thirty-nine (83%) were invasive ductal carcinoma; 22 (50.0%) were estrogen receptor/progesterone receptor (ER/PR) positive, human epidermal receptor (HER)-2 neu negative; nine were (20.5%) ER/PR and HER-2 neu positive; six (13.6%) were ER/PR negative, HER-2 neu positive, whereas seven (15.9%) were triple negative. Forty-three (91.5%) had modified radical mastectomy and 19 (40.4%) had cytotoxics. With an average of six cases in a year, MCBC is common in our hospital. Majority (63.8%) were young. The commonest method of detection was by self-breast examination. Majority (78.3%) presented at an early stage. Most (91.5%) still had modified radical mastectomy.

Can Pre-biopsy Second-Look Breast Ultrasound Affect Clinical Management? Experience From a Single Tertiary Hospital.

ObjectivesInterpretation discrepancy is a major disadvantage of breast imaging. This study aimed to determine the clinical benefit of the pre-biopsy second-look breast ultrasound (US).MethodsPatients with suspicious breast masses referred to our tertiary hospital for US-guided breast biopsy were retrospectively reviewed between August 2017 and November 2019. Here, second-look assessments were performed by experienced specialized breast radiologists via performing a bilateral breast US scan plus reviewing former imaging studies, and results were compared with the initial assessment. Interpretation changes in terms of biopsy recommendation and surgical management (i.e., lumpectomy to mastectomy) were analyzed.ResultsA total of 537 patients were enrolled in this study. Interpretation discrepancies occurred in 109 patients (20%; 95% CI, 17%–24%). Among them, there were 84 patients (16%; 95% CI, 13%–19%) whose masses were re-classified as BI-RADS 3 by the second-look US and underwent 2-year follow-up, showing 82 benign, 1 malignant, and 1 high-risk lesions. On the other hand, 16 patients (3%; 95% CI, 2%–5%) undertook biopsy at an additional site, identifying 10 new malignant lesions, 3 high-risk lesions, and 3 benign lesions, resulting in surgical management changes in 12 patients. In addition, nine (2%; 95% CI, 1%–3%) patients received discrepant disease ranges, which also altered surgical management. Overall, 21 patients (4%; 95% CI, 3%–6%) got their surgical management altered by the second-look US.ConclusionPre-biopsy second-look assessment of breast US can reduce unnecessary biopsies in 16% of patients and alter surgical management in 4% of patients, suggesting it is a practical and valuable method for patient care improvement.

Correlation of Sonographic Findings and Histopathological Diagnoses in Women Presenting With Breast Masses.

Background:Breast lumps have been reported as the most common breast symptom among adult females in Western Nigeria and are benign in 60% of cases. In South-Eastern Nigeria, fibroadenoma has been reported as the most common breast disease (47.5%), followed by carcinoma (30.4%) and fibrocystic disease. The aim of this study was to determine the correlation between sonographic and histopathologic findings in women who presented with breast masses.Materials and Methods:This was a cross-sectional study conducted among 160 consecutive female patients who presented with breast masses. A breast ultrasound scan was carried out to categorize the masses using the American College of Radiology Breast Imaging Reporting and Data System classification, and the histopathological diagnoses of the masses were obtained. The correlation of the sonographic findings and histopathological diagnoses was determined using the Statistical Package for Social Sciences (SPSS) IBM version 23.0.Results:Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were found to be 79.5%, 98.3%, 93.9%, 93.7%, and 93.8%, respectively. There was a positive correlation between the sonographic findings and histopathological diagnoses of the breast masses, which was statistically significant (P = 0.000, r = 0.846).Conclusion:This study found a statistically significant positive correlation between sonographic findings and histopathological diagnoses of breast masses.

Development of a focal lesion phantom with clinically relevant lesion characteristics for image quality evaluation of breast ultrasound scanners.

Contrast-detail (C-D) and anechoic-target (A-T) detectability are measures of an ultrasound scanner's ability to image lesions of varying contrast and size from background tissue and, as such, they are important tools for grading the imaging capabilities of ultrasound scanners. The objective of this study was to develop a range of contrast- and anechoic-detail phantoms with clinically relevant lesions, of various contrast and sizes, for performance testing of breast ultrasound equipment. Tissue mimicking materials that represent the acoustic properties of breast fibroglandular tissue were produced and moulded to construct a range of C-D and A-T phantoms. Two phantom designs were produced, containing cylindrical and spherical targets. Both phantom types were constructed with contrast targets covering the range anechoic, -1, -2, -3 and -4dB, with lesion diameters of 1-4mm, positioned at four clinically relevant depths (10, 25, 40 and 55mm). An image analysis program was developed to objectively analyse the lesion images and to determine the lesion-signal-noise-ratio (LSNR). Both phantoms were used to evaluate the performance of a breast ultrasound scanner. The use of cylindrical phantoms led to an artificially higher image quality performance compared with the more clinically relevant spherical lesion phantom, thus indicating the importance of using the appropriate targets in ultrasound phantoms. The spherical lesion phantoms, coupled with the quantitative metric of LSNR, provides a comprehensive approach for performance and quality control testing, as well as the evaluation of advanced ultrasound imaging modes and technologies.

Factors influencing breast cancer screening practices among women of reproductive age in South Kayonza District, Rwanda.

Breast cancer in Rwanda is a major concern for women's health, as most breast cancer diagnoses are made at an advanced stage. Yet, diagnosis can be done early with breast cancer screening practices. To assess factors influencing breast cancer screening practices among women of reproductive age in South Kayonza District of Rwanda. A quantitative survey was conducted with 246 women between 16 and 49 years of age from four health centres in South Kayonza District. A structured, pretested, and self-administered questionnaire was used to assess the influence of knowledge, health facilities, and socioeconomic and cultural factors on breast screening practices among women in South Kayonza. Among all respondents, 55.5% had moderate knowledge about breast cancer risk factors and 60.2% also had moderate knowledge on the influence of breast cancer screening. While 28% were knowledgeable about Breast Self-Examination (BSE), 16.4% were knowledgeable about Clinical Breast Examination (CBE) and breast ultrasound. Responses about the practice of breast screening in the last two years showed 72% of respondents had never practiced BSE and 81.3% had not used CBE or breast ultrasound scan. The main source of information about breast cancer screening was the radio, used by 30.4% of respondents. Significant relationships were found between age and marital status with breast cancer screening practices. This study revealed low levels of knowledge about breast cancer, breast cancer screening, and practice regarding breast cancer screening. There is a need to promote awareness of breast cancer and create a program, which can influence breast cancer screening knowledge and practice to ultimately improve health among women in south Kayonza.

The concordance in lesion detection and characteristics between the Anatomical Intelligence and conventional breast ultrasound Scan method

BackgroundThe aim of this study was to investigate the concordance in lesion detection, between conventional Handhold Ultrasound (HHUS) and The Anatomical Intelligence for Breast ultrasound scan method.ResultThe AI-breast showed the absolute agreement between the resident and an experienced breast radiologist. The ICC for the scan time, number, clockface location, distance to the nipple, largest diameter and mean diameter of the lesion obtained by a resident and an experienced breast radiologist were 0.7642, 0.7692, 0.8651, 0.8436, 0.7502, 0.8885, respectively. The ICC of the both practitioners of AI-breast were 0.7971, 0.7843, 0.9283, 0.8748, 0.7248, 0.8163, respectively. The k value of Anatomical Intelligence breast between experienced breast radiologist and resident in these image characteristics of boundary, morphology, aspect ratio, internal echo, and BI-RADS assessment were 0.7424, 0.7217, 0.6741, 0.6419, 0.6241, respectively. The k value of the two readers of AI-breast were 0.6531, 0.6762, 0.6439, 0.6137, 0.5981, respectively.ConclusionThe anatomical intelligent breast US scanning method has excellent reproducibility in recording the lesion location and the distance from the nipple, which may be utilized in the lesions surveillance in the future.

Epidemiology and Predictive Factors for Persistent Breast Pain Following Breast-Conserving Surgery.

BackgroundIn general, breast pain is one of the most common causes for referral to breast units; treatment-related breast pain is frequently seen in clinical practice but not well addressed in the literature. While our primary objective was to identify the incidence of persistent breast pain following breast-conserving surgery and possible risk factors, our secondary aim was to assess the possibility of using a breast ultrasound scan to detect parenchymal changes that can contribute to breast pain.MethodsWe have conducted a prospective study including patients who had wide local excision for primary breast cancer treatment between January 2017 and January 2019. Patients’ demographics, including age, BMI, breast volume, and tumour characteristics, were noted. All patients had a clinical assessment and were asked standard questions about their breast pain each visit; they also had an ultrasound scan of the breast and axilla 6 and 12 months after surgery to look for parenchymal changes.ResultsA total of 239 female breast cancer patients were included in our analysis. The mean age was 43.9 years, mean weight was 72.8 kg, mean BMI was 27.4 and mean breast volume was 1173 ml. In total, 38.5% had standard wide local excision, and 61.5% had oncoplastic resection; the mean specimen weight was 74.6 grams. All patients had adjuvant whole breast radiotherapy. We found that patients with younger age, larger breast size, high BMI, oncoplastic resections, and persistent parenchymal changes are associated with an increased incidence of postoperative breast pain while the type of axillary procedure and adjuvant chemotherapy had no significant effect.ConclusionPersistent postoperative breast pain was noted in 33% of our patients. We have also indicated that younger patients, patients with larger breast, those with high BMI, with preoperative breast pain, who had oncoplastic resections, and patients with persistent parenchymal changes, as fat necrosis and scarring, are associated more with persistent breast pain.

Association between ovarian and breast masses among Chinese women in Chongqing based on ultrasonography screening: A cross-sectional study.

To explore associations between breast and ovarian tumors among the general healthcare population. We conducted a cross-sectional retrospective study that enrolled 47951 consecutive Chinese women who took health check-ups between January 2015 and July 2018 and accepted both breast and gynecologic ultrasound scans during one healthcare examination in The Quality Control Center of Health Examination in Chongqing (China). Prevalence of breast and ovarian tumors was addressed. Multivariable logistic regressions were applied to assess the association between breast and ovarian lesions after adjusting for age, height, and body mass index, using ultrasonographic reports. Among participants, 8481 (17.7%) had breast masses (BM), and 2994 (6.2%) had ovarian masses (OM). After adjusting for age, height and body mass index (BMI), women with OM had an increased risk of BM (odds ratio [OR] 1.139, 95% confidence interval [CI] 1.040-1.249, P=0.005) than those without OM. Furthermore, subgroup analysis based on menopausal status revealed a positive association between the occurrence of OM and BM in premenopausal women (adjusted OR 1.155, 95% CI 1.052-1.269, P=0.012) but this was not significant in perimenopausal or postmenopausal women. In subgroup analysis on BMI, positive correlations between OM and BM were found in women with an underweight BMI (OR 1.433, 95% CI 1.048-1.960, P=0.024) and with a normal BMI (OR 1.130, 95% CI 1.018-1.253, P=0.021), but this was not significant in overweight or obese cohorts. A high prevalence of ultrasound-revealed breast and ovarian tumors were found in Chinese women. Women with OM or BM have an increased prevalence of BM or OM, particularly among younger women and women with a lower BMI.

Quantitative Evaluation of an Automated Cone-Based Breast Ultrasound Scanner for MRI-3D US Image Fusion.

Breast cancer is one of the most diagnosed types of cancer worldwide. Volumetric ultrasound breast imaging, combined with MRI can improve lesion detection rate, reduce examination time, and improve lesion diagnosis. However, to our knowledge, there are no 3D US breast imaging systems available that facilitate 3D US - MRI image fusion. In this paper, a novel Automated Cone-based Breast Ultrasound System (ACBUS) is introduced. The system facilitates volumetric ultrasound acquisition of the breast in a prone position without deforming it by the US transducer. Quality of ACBUS images for reconstructions at different voxel sizes (0.25 and 0.50 mm isotropic) was compared to quality of the Automated Breast Volumetric Scanner (ABVS) (Siemens Ultrasound, Issaquah, WA, USA) in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and resolution using a custom made phantom. The ACBUS image data were registered to MRI image data utilizing surface matching and the registration accuracy was quantified using an internal marker. The technology was also evaluated in vivo. The phantom-based quantitative analysis demonstrated that ACBUS can deliver volumetric breast images with an image quality similar to the images delivered by a currently commercially available Siemens ABVS. We demonstrate on the phantom and in vivo that ACBUS enables adequate MRI-3D US fusion. To our conclusion, ACBUS might be a suitable candidate for a second-look breast US exam, patient follow-up, and US guided biopsy planning.

Adaptive Curved Breast Ultrasound Scanning Method Based on Improved Impedance Control

Adaptive Curved Breast Ultrasound Scanning Method Based on Improved Impedance Control

Nipple Localization in Automated Whole Breast Ultrasound Coronal Scans Using Ensemble Learning.

Nipple is a vital landmark in the breast lesion diagnosis. Although there are advanced computer-aided detection (CADe) systems for nipple detection in breast mediolateral oblique (MLO) views of mammogram images, few academic works address the coronal views of breast ultrasound (BUS) images. This paper addresses a novel CADe system to locate the Nipple Shadow Area (NSA) in ultrasound images. Here the Hu Moments and Gray-level Co-occurrence Matrix (GLCM) were calculated through an iterative sliding window for the extraction of shape and texture features. These features are then concatenated and fed into an Artificial Neural Network (ANN) to obtain probable NSA's. Later, contour features, such as shape complexity through fractal dimension, edge distance from the periphery and contour area, were computed and passed into a Support Vector Machine (SVM) to identify the accurate NSA in each case. The coronal plane BUS dataset is built upon our own, which consists of 64 images from 13 patients. The test results show that the proposed CADe system achieves 91.99% accuracy, 97.55% specificity, 82.46% sensitivity and 88% F-score on our dataset.