US-guided Breast Biopsy Research Articles

Machine learning can reliably predict malignancy of breast lesions based on clinical and ultrasonographic features.

To establish a reliable machine learning model to predict malignancy in breast lesions identified by ultrasound (US) and optimize the negative predictive value to minimize unnecessary biopsies. We included clinical and ultrasonographic attributes from 1526 breast lesions classified as BI-RADS 3, 4a, 4b, 4c, 5, and 6 that underwent US-guided breast biopsy in four institutions. We selected the most informative attributes to train nine machine learning models, ensemble models and models with tuned threshold to make inferences about the diagnosis of BI-RADS 4a and 4b lesions (validation dataset). We tested the performance of the final model with 403 new suspicious lesions. The most informative attributes were shape, margin, orientation and size of the lesions, the resistance index of the internal vessel, the age of the patient and the presence of a palpable lump. The highest mean negative predictive value (NPV) was achieved with the K-Nearest Neighbors algorithm (97.9%). Making ensembles did not improve the performance. Tuning the threshold did improve the performance of the models and we chose the algorithm XGBoost with the tuned threshold as the final one. The tested performance of the final model was: NPV 98.1%, false negative 1.9%, positive predictive value 77.1%, false positive 22.9%. Applying this final model, we would have missed 2 of the 231 malignant lesions of the test dataset (0.8%). Machine learning can help physicians predict malignancy in suspicious breast lesions identified by the US. Our final model would be able to avoid 60.4% of the biopsies in benign lesions missing less than 1% of the cancer cases.

Use of a commercial artificial intelligence-based mammography analysis software for improving breast ultrasound interpretations.

To evaluate the use of a commercial artificial intelligence (AI)-based mammography analysis software for improving the interpretations of breast ultrasound (US)-detected lesions. A retrospective analysis was performed on 1109 breasts that underwent both mammography and US-guided breast biopsy. The AI software processed mammograms and provided an AI score ranging from 0 to 100 for each breast, indicating the likelihood of malignancy. The performance of the AI score in differentiating mammograms with benign outcomes from those revealing cancers following US-guided breast biopsy was evaluated. In addition, prediction models for benign outcomes were constructed based on clinical and imaging characteristics with and without AI scores, using logistic regression analysis. The AI software had an area under the receiver operating characteristics curve (AUROC) of 0.79 (95% CI, 0.79-0.82) in differentiating between benign and cancer cases. The prediction models that did not include AI scores (non-AI model), only used AI scores (AI-only model), and included AI scores (integrated model) had AUROCs of 0.79 (95% CI, 0.75-0.83), 0.78 (95% CI, 0.74-0.82), and 0.85 (95% CI, 0.81-0.88) in the development cohort, and 0.75 (95% CI, 0.68-0.81), 0.82 (95% CI, 0.76-0.88), and 0.84 (95% CI, 0.79-0.90) in the validation cohort, respectively. The integrated model outperformed the non-AI model in the development and validation cohorts (p < 0.001 for both). The commercial AI-based mammography analysis software could be a valuable adjunct to clinical decision-making for managing US-detected breast lesions. The commercial AI-based mammography analysis software could potentially reduce unnecessary biopsies and improve patient outcomes. • Breast US has high rates of false-positive interpretations. • A commercial AI-based mammography analysis software could distinguish mammograms having benign outcomes from those revealing cancers after US-guided breast biopsy. • A commercial AI-based mammography analysis software may improve interpretations for breast US-detected lesions.

Population-Level Access to Breast Cancer Early Detection and Diagnosis in Nigeria.

Mammography, breast ultrasound (US), and US-guided breast biopsy are essential services for breast cancer early detection and diagnosis. This study undertook a comprehensive evaluation to determine population-level access to these services for breast cancer early detection and diagnosis in Nigeria using a previously validated geographic information system (GIS) model. A comprehensive list of public and private facilities offering mammography, breast US, and US-guided breast biopsy was compiled using publicly available facility data and a survey administered nationally to Nigerian radiologists. All facilities were geolocated. A cost-distance model using open-source population density (GeoData Institute) and road network data (OpenStreetMap) was used to estimate population-level travel time to the nearest facility for mammography, breast US, and US-guided biopsy using GIS software (ArcMAP). In total, 1,336 facilities in Nigeria provide breast US, of which 47.8% (639 of 1,336) are public facilities, and 218 provide mammography, of which 45.4% (99 of 218) are public facilities. Of the facilities that provide breast US, only 2.5% (33 of 1,336) also provide US-guided breast biopsy. At the national level, 83.1% have access to either US or mammography and 61.7% have access to US-guided breast biopsy within 120 minutes of a continuous one-way travel. There are differences in access to mammography (64.8% v 80.6% with access at 120 minutes) and US-guided breast biopsy (49.0% v 77.1% with access at 120 minutes) between the northern and southern Nigeria and between geopolitical zones. To our knowledge, this is the first comprehensive evaluation of breast cancer detection and diagnostic services in Nigeria, which demonstrates geospatial inequalities in access to mammography and US-guided biopsy. Targeted investment is needed to improve access to these essential cancer care services in the northern region and the North East geopolitical zone.

Abstract P3-04-02: Population level access to diagnostic mammography and ultrasound guided breast biopsy in Nigeria: a geospatial analysis

Abstract Introduction: Breast cancer is the most common cause of cancer-related mortality among women in Nigeria. Physical proximity to a diagnostic center is an important component of access, which has direct implication on the cost and timeliness of diagnosis and treatment. Beyond diagnostic mammography, ultrasound (US)-guided biopsy is an essential tool in the diagnostic pathway for suspicious lesions of the breast and is recommended by the Whole Health Organization Breast Health Global Initiative for LMICs. Unfortunately, there is a dearth of data on the population level access to mammography and US-guided breast biopsy in Nigeria and little is known about the geospatial inequities in access that targeted programming or investment could potentially address. This study undertook a comprehensive evaluation of breast imaging and diagnostic services in Nigeria and using a previously validated geographic information system (GIS) model, evaluated geospatial access to diagnostic mammography and US-guided breast biopsy in Nigeria. Methods: A comprehensive list of public and private facilities offering diagnostic mammography and/or US-guided breast biopsy was compiled using publicly available facility data from the Nigerian Ministry of Health, a survey administered to members of the Breast Imaging Society of Nigeria (BISON) as well as key stakeholder interviews from each of the countries six geopolitical zones. A novel survey was delivered to BISON members to identify additional/new facilities not captured by the latest Nigerian Ministry of Health data. Facility location, administration (public vs. private) and duration of service delivery were elicited from respondents and paired with the Ministry of Health facility dataset. Data on provider training and volume were also captured in the survey. All facilities were geolocated using Google Earth™ (Google, Mountain View, CA). A previously described cost-distance model, that uses open-source population density data to 100m2 (GeoData Institute) and road network data (OpenStreetMap) was used to estimate population level travel time to the nearest diagnostic center. Any portion of a route that included travel over terrain without roads was assigned a walking speed of 5 kmh-1. Geospatial access was calculated for mammography and US-guided biopsy separately and as well as by geopolitical zone. This study was approved by the research ethics board at Obafemi Awolowo University. Results: In addition to publicly available data from the Ministry of Health, facility and practice data was obtained from 63 Nigerian Radiologists from across the country. In total, 124 centers were identified that offer diagnostic mammography, of which 78 (63%) are privately administered. Nine of the countries 36 states did not have a center offering this service. Across the country, 33 centers offer US-guided breast biopsy, of which the majority (72.7%) are public. At a population level, 83.1% of the population has access within 120 minutes of continuous one-way travel to a center with diagnostic mammogram or US. At 240 minutes of continuous one-way travel, which corresponds to a full day of travel round-trip, 80.8% of the population has access to US-guided breast biopsy. However, there are differences in access between geopolitical zones. Just 68.7% of the population in the North East geopolitical zone has access to US-guided biopsy within a day’s travel (i.e. 240 minutes one-way). The remaining five geopolitical zones have population level access to this service of ≥80%. Conclusions: This is the first comprehensive evaluation of breast cancer imaging and diagnostic services in Nigeria. Our results, demonstrate that the majority of the population in Nigeria has reasonable geospatial access to basic breast cancer imaging services. However, there are inequalities in access between states and geopolitical zones in the north and south of the country, which may have an impact on timely diagnosis and care. Citation Format: Adeleye Omisore, Elizabeth J. Sutton, Gavin Tansley, Rachael Adeyanju AKINOLA, Gregory Knapp. Population level access to diagnostic mammography and ultrasound guided breast biopsy in Nigeria: a geospatial analysis [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-04-02.

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.

Prospective assessment of adjunctive ultrasound-guided diffuse optical tomography in women undergoing breast biopsy: Impact on BI-RADS assessments

PurposeTo assess the impact of adjunctive ultrasound guided diffuse optical tomography (US-guided DOT) on BI-RADS assessment in women undergoing US-guided breast biopsy. MethodThis prospective study enrolled women referred for US-guided breast biopsy between 3/5/2019 and 3/19/2020. Participants underwent US-guided DOT immediately before biopsy. The US-guided DOT acquisition generated average maximum total hemoglobin (HbT) spatial maps and quantitative HbT values. Four radiologists blinded to histopathology assessed conventional imaging (CI) to assign a CI BI-RADS assessment and then integrated DOT information in assigning a CI&DOT BI-RADS assessment. HbT was compared between benign and malignant lesions using an ANOVA test and Tukey’s test. Benign biopsies were tabulated, deeming BI-RADS ≥ 4A as positive. Reader agreement was assessed. ResultsAmong 61 included women (mean age 48 years), biopsy demonstrated 15 (24.6%) malignant and 46 (75.4%) benign lesions. Mean HbT was 55.3 ± 22.6 µM in benign lesions versus 85.4 ± 15.6 µM in cancers (p < .001). HbT threshold of 78.5 µM achieved sensitivity 80% (12/15) and specificity 89% (41/46) for malignancy. Across readers and patients, 197 pairs of CI BI-RADS and CI&DOT BI-RADS assessments were assigned. Adjunctive US-guided DOT achieved a net decrease in 23.5% (31/132) of suspicious (CI BI-RADS ≥ 4A) assessments of benign lesions (34 correct downgrades and 3 incorrect upgrades). 38.3% (31/81) of 4A assessments were appropriately downgraded. No cancer was downgraded to a non-actionable assessment. Interreader agreement analysis demonstrated kappa = 0.48–0.53 for CI BI-RADS and kappa = 0.28–0.44 for CI&DOT BI-RADS. ConclusionsIntegration of US-guided DOT information achieved a 23.5% reduction in suspicious BI-RADS assessments for benign lesions. Larger studies are warranted, with attention to improved reader agreement.

Discrepancies between radiological and histological findings in preoperative core needle (CNB) and vacuum-assisted (VAB) breast biopsies

BackgroundUltrasound (US)-guided breast biopsy is a routine diagnostic method used to correlate imaging finding to a histological diagnosis which is still the gold standard in preoperative diagnostics. The accuracy of US-guided breast biopsies relies on a precise radiologic-histopathologic correlation, which is discussed amongst an interdisciplinary team of gynecologists, radiologists and pathologists. However, false-negative or non-diagnostic biopsy results occur. Hence, a thorough and honest discussion to clarify the reason for discrepancies and to decide the next diagnostic step between specialists of the different disciplines is warranted. In this retrospective study, we analyzed discrepant findings between imaging and pathology results on preoperative breast biopsies.MethodsCore and vacuum-assisted breast biopsies from 232 patients were included in this study. Inclusion criteria were (1) non-diagnostic (B1) category on histology independent from imaging category and (2) histological benign (B2) category with a BIRADS 5 (Breast Imaging Reporting and Data System) rating on imaging. Histological diagnoses were retrieved from all cases. Follow-up data were available in most cases.Results138 biopsies were classified as B1, 94 biopsies as B2 category. 51 of 138 B1 cases (37%) underwent re-biopsy. Re-biopsy found malignancy (B5) in 19 of 51 cases, and B3/4 (premalignant) lesions in 3 of 51 cases. All B2 cases underwent second-look imaging-diagnosis, in 57 of 94 cases (66%) consecutive direct surgery or re-biopsy. Of these, malignancy was diagnosed histologically in 26 of 57 cases (45.6%).ConclusionDetermining imaging-pathology concordance after US-guided breast biopsy is essential. Discrepant cases and further diagnostic steps need to be discussed with an interdisciplinary approach.

Image-guided Procedure Versus 2-year Follow-up for a BI-RADS 3 Probably Benign Lesion: A Cost Comparison Analysis.

Perform a comparison between the costs of image-guided breast procedures versus 2-year imaging follow-up for findings classified as BI-RADS assessment category 3-probably benign. The national payment amount costs at non-facility locations were obtained from the Centers for Medicare and Medicaid Services physician fee schedule for breast imaging-related Current Procedural Terminology codes. Total costs were calculated and compared for management algorithms of 2-year imaging follow-up of a BI-RADS 3 lesion from 2018 through 2019 versus performing an image-guided procedure of the lesion in 2018 after the initial diagnostic imaging. Two-year mammographic follow-up of a BI-RADS 3 finding costs $484. This was less than a stereotactic-guided breast biopsy, which cost at least $1055. Two-year follow-up for a probably benign US finding cost $615 compared to $1173 for the least expensive US-guided breast biopsy scenario. For breast MRI, 2-year imaging follow-up cost $1510, which was also less than most MRI-guided breast biopsy scenarios. The one exception in which biopsy costs less than 2-year imaging follow-up was in the setting of an MRI-guided biopsy in the average-risk population without a post-benign biopsy follow-up breast MRI; in this setting, MRI biopsy cost $1235. In 2018-2019, 2-year imaging follow-up of a BI-RADS 3 finding continues to be less costly than an immediate procedure, except for MRI-guided breast biopsy in the average-risk population without a post-benign biopsy follow-up MRI.

Design of an end-effector for robot-assisted ultrasound-guided breast biopsies

PurposeThe biopsy procedure is an important phase in breast cancer diagnosis. Accurate breast imaging and precise needle placement are crucial in lesion targeting. This paper presents an end-effector (EE) for robotic 3D ultrasound (US) breast acquisitions and US-guided breast biopsies. The EE mechanically guides the needle to a specified target within the US plane. The needle is controlled in all degrees of freedom (DOFs) except for the direction of insertion, which is controlled by the radiologist. It determines the correct needle depth and stops the needle accordingly.MethodIn the envisioned procedure, a robotic arm performs localization of the breast, 3D US volume acquisition and reconstruction, target identification and needle guidance. Therefore, the EE is equipped with a stereo camera setup, a picobeamer, US probe holder, a three-DOF needle guide and a needle stop. The design was realized by prototyping techniques. Experiments were performed to determine needle placement accuracy in-air. The EE was placed on a seven-DOF robotic manipulator to determine the biopsy accuracy on a cuboid phantom.ResultsNeedle placement accuracy was 0.3 ± 1.5 mm in and 0.1 ± 0.36 mm out of the US plane. Needle depth was regulated with an accuracy of 100 µm (maximum error 0.89 mm). The maximum holding force of the stop was approximately 6 N. The system reached a Euclidean distance error of 3.21 mm between the needle tip and the target and a normal distance of 3.03 mm between the needle trajectory and the target.ConclusionAn all in one solution was presented which, attached to a robotic arm, assists the radiologist in breast cancer imaging and biopsy. It has a high needle placement accuracy, yet the radiologist is in control like in the conventional procedure.

Position-based modeling of lesion displacement in ultrasound-guided breast biopsy.

Although ultrasound (US) images represent the most popular modality for guiding breast biopsy, malignant regions are often missed by sonography, thus preventing accurate lesion localization which is essential for a successful procedure. Biomechanical models can support the localization of suspicious areas identified on a preoperative image during US scanning since they are able to account for anatomical deformations resulting from US probe pressure. We propose a deformation model which relies on position-based dynamics (PBD) approach to predict the displacement of internal targets induced by probe interaction during US acquisition. The PBD implementation available in NVIDIA FleX is exploited to create an anatomical model capable of deforming online. Simulation parameters are initialized on a calibration phantom under different levels of probe-induced deformations; then, they are fine-tuned by minimizing the localization error of a US-visible landmark of a realistic breast phantom. The updated model is used to estimate the displacement of other internal lesions due to probe-tissue interaction. The localization error obtained when applying the PBD model remains below 11mm for all the tumors even for input displacements in the order of 30mm. This proposed method obtains results aligned with FE models with faster computational performance, suitable for real-time applications. In addition, it outperforms rigid model used to track lesion position in US-guided breast biopsies, at least halving the localization error for all the displacement ranges considered. Position-based dynamics approach has proved to be successful in modeling breast tissue deformations during US acquisition. Its stability, accuracy and real-time performance make such model suitable for tracking lesions displacement during US-guided breast biopsy.

3:54 PM Abstract No. 298 Simulation-based ultrasound-guided breast biopsy training improves operator knowledge, accuracy, and confidence

Ultrasound (US)-guided breast biopsy is one of the most common techniques employed to obtained tissue for histologic analysis of breast pathology. Experience performing this procedure is almost entirely on patients, an approach fraught with anxiety and potential error. The aim of this study was to assess the efficacy of a breast-phantom in conjunction with a multimedia educational presentation in improving operator knowledge, procedural accuracy, and subjective comfort performing US-guided breast biopsy. Sixteen radiology resident physicians completed a written exam of multiple-choice questions (MCQ) covering the US-appearance of breast anatomy, commonly targeted pathologies, and clinical management of complications. Then residents completed a self-paced, interactive online module describing: mammographic, sonographic, and procedural concepts related to breast biopsy and pathology. Residents were allowed 30 minutes to practice on the breast phantom before completing a formal assessment of US-guided biopsy accuracy graded dichotomously by obtaining a sample of the intended pathology within the phantom. A posttest consisting of pair-matched MCQs was then administered. The average score on the written pretest was 72.7% and the average post-test score 95.3%, a statistically significant improvement (p<0.001). Accuracy obtaining intended sample correlated with post-gradate year and experience performing US-guided biopsy procedures. There was a statistically significant improvement in residents’ qualitative: comfort explaining the procedure (p<0.01), comfort performing the procedure (p<0.01), and handling complications (p<0.05). The phantom allowed residents an unrestricted opportunity to practice and refine their technique. The brief educational multimedia presentation and independent practice with the phantom resulted in both objective and subjective improvement in residents’ knowledge, procedural accuracy, and subjective comfort performing US-guided breast biopsy.

Evaluating imaging-pathology concordance and discordance after ultrasound-guided breast biopsy.

Ultrasound (US)-guided breast biopsy has become the main method for diagnosing breast pathology, and it has a high diagnostic accuracy, approaching that of open surgical biopsy. However, methods for confirming adequate lesion retrieval after US-guided biopsy are relatively limited and false-negative results are unavoidable. Determining imaging-pathology concordance after US-guided biopsy is essential for validating the biopsy result and providing appropriate management. In this review article, we briefly present the results of US-guided breast biopsy; describe general aspects to consider when establishing imaging-pathology concordance; and review the various categories of imaging-pathology correlations and corresponding management strategies.

Development of a fresh cadaver model for instruction of ultrasound-guided breast biopsy during the surgery clerkship: pre-test and post-test results among third-year medical students

BackgroundThe aim of our study was to determine if a fresh cadaver model is a viable method for teaching ultrasound (US)-guided breast biopsy of palpable breast lesions. MethodsThird-year medical students were assessed both preinstruction and postinstruction on their ability to perform US-guided needle aspiration or biopsy of artificially created masses using a 10-item checklist. ResultsForty-one third-year medical students completed the cadaver laboratory as part of the surgery clerkship. Eight items on the checklist were found to be significantly different between pre-testing and post-testing. The mean preinstruction score was 2.4, whereas the mean postinstruction score was 7.10 (P < .001). ConclusionsFresh cadaver models have been widely used in medical education. However, there are few fresh cadaver models that provide instruction on procedures done in the outpatient setting. Our model was found to be an effective method for the instruction of US-guided breast biopsy among medical students.

Abstract P4-03-03: Feasibility study of a new volume navigation system-guided breast biopsy method for incidental enhancing lesions detected by breast contrast-enhanced magnetic resonance imaging

Abstract Background: Incidental enhancing lesions (IELs) undetected by conventional imaging such as mammography and ultrasonography (US) have been reported in 16–29% of patients undergoing subsequent breast contrast-enhanced magnetic resonance imaging (CE-MRI). We recently assessed IELs by performing breast biopsies using a volume navigation system (V-Navi) which synchronizse real-time US images with reconstructed CE-MRI data side-by-side on the same monitor. The aim of this retrospective study was to evaluate the feasibility of V-Navi-guided biopsy method as an IEL diagnostic procedure. Methods: We performed breast biopsies on 333 patients after mammography, US and CE-MRI (GE Signa Excite HDx 1.5T, USA) examinations between January 2011 and May 2012 at Keio University Hospital. Patients with IELs detected by CE-MRI underwent a second-look US and a bilateral CE-MRI in the supine position in order to achieve the same position as in the US. CE-MRI data was then fused with real-time US images using a V-Navi (Logiq E9, GE Healthcare, USA). When an IEL was identified, we performed a V-Navi-guided vacuum-assisted needle biopsy (11G) or an excisional biopsy after V-Navi-guided marking. Results: US-guided and stereo-guided breast biopsies were performed on 77.2% (257) and 16.8% (56) of the 333 patients, respectively. Twenty patients (6.0%) had IELs detected by CE-MRI and all such IELs were identified by the V-Navi. Sixteen (80%) of those 20 patients had IELs clearly detected by the V-Navi and underwent V-Navi-guided needle biopsies. The four remaining patients (20%) had IELs that were not clearly detected by the V-Navi and they underwent excisional biopsies. The median IEL size was 8.8mm (range, 5.0–48) and the median procedure time for V-Navi-guided needle biopsies was 42 minutes. No major complications were encountered in any of the cases. Histopathologically, nine IELs (45%) had malignant findings of invasive ductal carcinoma (5/20) and ductal carcinoma in situ (4/20) and 11 IELs (55%) had benign findings of fibrocystic disease (10/20) and intraductal papilloma (1/20). Conclusion: The V-Navi-guided breast biopsy method was shown to be a safe and effective diagnostic method for the assessment of IELs detected by breast CE-MRI. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P4-03-03.

Indications and Rationale of US-Guided Breast Biopsy: Biopsy or Not?

Indications and Rationale of US-Guided Breast Biopsy: Biopsy or Not?

Advances in the Diagnosis and Excision of Breast Cancer

Until recently little advance in the diagnosis and excision of breast cancer has been made since the inception of needle localization breast biopsy (NLBB). Stereotactic core needle breast biopsy (SCNBB) can avoid most NLBB especially for calcifications. However, when open biopsy is necessary NLBB has been the standard of care. As many as 50 per cent of nonpalpable lesions can be seen by ultrasound (US) to avoid the unpleasantness and complications associated with NLBB. Further SCNBB leaves a blood-filled cavity that can be easily seen by US. Intraoperative US can be used to direct the excision while improving margin negativity. MRI has improved sensitivity in detecting suspicious breast lesions and techniques such as hematoma-directed US-guided breast biopsy can facilitate excision of such masses. Clearly new technologies have improved the ability to diagnosis and excise breast cancer. The onus on the surgeon is to incorporate them into standard practice to improve outcomes.

US-guided breast biopsy with an automated cutting needle

The authors report their experience on the use of a biopsy gun for histological sampling in the field of breast lesions. The use of cytological sampling by (FNAB) fine needle aspiration biopsy has been preferred so far, because it has been thoutht to be simpler, less risky and reliable. Nevertheless, the cytological sampling shows a number of drawbacks such as the need for passes to get sufficient cellular material, frequent problems in diagnosing benign lesions and the decisive influence of the operator's skill. By using a biopsy gun for histological sampling these disadvantages are eliminated. In this case, in fact, the validity of the sample is not influenced by the operator's skill; fewer passes are necessary and their validity does not depend on the nature of the lesion. The personal series of cases involves 91 patients subjected to histological sampling for suspected lesions. Two different kinds of needles were used with one an 18 G diameter and a 23-mm extension of the sytlet, as well as a sampling window 17 mm; the other with the same diameter and extension of the stylet, as as a sampling window 8 mm. The first needle was used in all 91 patients, and the second only in 30. The results were not influenced by the employ of the different kinds of needles. A total of 268 samples were made and 110 lesions were discovered, 79 of which were malignant and 31 benign (fibroadenoma, fibrocystic change and epitheliosis). Three carcinomas were not found (3 false-negative) and one specimen was inadequate. The values of sensibility, specificity and diagnostic accuracy of the method were, respectively, 96.2%, 100% and 97.2%, with 3.8% false-negative due to three cases where the lesion was not centred for guidance mistake.