Nonmasslike Lesions Research Articles

Combination of Breast Ultrasound With Magnetic Resonance Imaging in the Diagnosis of Non-mass-like Breast Lesions Detected on Ultrasound: A New Integrated Strategy to Improve Diagnostic Performance

The aim of the work described here was to evaluate the diagnostic performance of a new integrated strategy using breast ultrasound (US) combined with magnetic resonance imaging (MRI) to differentiate benign and malignant breast non-mass-like lesions (NMLs) detected on US. From October 2017 to January 2021, 183 NMLs detected on US that had undergone MRI examinations were included in this respective study. Pathological results were used as the reference standard. The integrated diagnostic strategy of breast US combined with MRI based on a combination of MRI Breast Imaging Reporting and Data System (BI-RADS) with discriminant sonographic indicators highly associated with malignancy was established and validated in a cohort of 61 women. The diagnostic performances of US, MRI and the combined method were calculated and compared. In the training set, the area under the receiver operating characteristic curve (AUC), sensitivity and specificity of US, MRI and the integrated diagnostic strategy using US combined with MRI for NMLs were 0.730, 93.7% and 52.3%; 0.849, 94.7% and 75.0%; and 0.901, 92.6% and 87.5%, respectively. Compared with US or MRI alone, the integrated diagnostic strategy significantly increased the AUC (p < 0.001, p=0.007) and specificity (p < 0.001, p=0.034) while maintaining high sensitivity (p=0.774, p=0.551). In the validation set, the integrated strategy of US combined with MRI (AUC=0.899) also had good performance compared with US (AUC=0.728) or MRI (AUC=0.838). The integrated diagnostic strategy of US combined with MRI exhibited good performance for breast NMLs compared with either modality used alone, which can improve the diagnostic specificity while maintaining high sensitivity.

Diagnostic value of multimodal ultrasound strategies in the differentiation of non-mass-like breast lesions.

The study aims to assess the diagnostic performance of convention ultrasound (US), Angio PLUS microvascular US imaging (AP), and shear-wave elastography (SWE) in differentiating malignant and benign non-mass-like (NML) breast lesions. Sixty patients aged 21-70 years with 60 NML lesions were recruited. All patients were examined by conventional US, AP, and SWE. According to the pathological results, the performances of the multimodal US strategies were analyzed, while the diagnostic efficiency of AP and SWE in serial and parallel was also explored. Age, together with posterior features, microcalcification, and architectural distortion were considered significant in evaluating NML lesions. The sensitivity, specificity, PPV, NPV, and accuracy of AP combined SWE in serial were 72.7, 96.3, 96.0, 74.3, and 83.3%, while those in parallel were 90.9, 63.0, 75.0, 85.0, and 78.3%, respectively. The two in serial indicated the highest specificity, PPV, accuracy, and AUC value, which could increase the true positive rate and reduce the chance of misdiagnosis, while the two in parallel exhibited the best sensitivity and NPV, which might serve as an effective tool to avoid excessive or nonessential biopsy. The multimodal US strategies could provide precise and reliable diagnostic results for NML breast lesions.

Determining whether the diagnostic value of B-ultrasound combined with contrast-enhanced ultrasound and shear wave elastography in breast mass-like and non-mass-like lesions differs: a diagnostic test.

Mass-like (ML) and non-mass-like (NML) are two manifestations of breast lesions on ultrasound. Contrast-enhanced ultrasound (CEUS) can make up for the limitation of B-ultrasound (US) in the observation of focal blood flow, and shear wave elastography (SWE) can supplement the hardness information of the lesion. The present study aimed to analyze the characteristic manifestations of US, CEUS, and SWE in NML and ML breast and evaluate whether the diagnostic performance of these three ultrasound techniques differs in terms of differentiating between benign and malignant breast lesions. From January to August 2021, 382 patients (417 breast lesions) underwent US, CEUS, and SWE examinations. Of these, 204 women (218 breast lesions) were included in our study due to subsequent biopsy or surgery with pathological findings. The patients were divided into ML and NML groups according to the ultrasound characteristics, and the differences in multimodal ultrasound performance between benign and malignant NML and benign and malignant ML breast lesions were compared. The diagnostic performance of US, US + CEUS, US + SWE, US + CEUS + SWE for ML, NML and all breast lesions was evaluated by analyzing sensitivity, specificity and area under receiver operating characteristic (ROC) curve (AUC). Pathologically, the 218 lesions included 96 malignant and 122 benign breast lesions. The sensitivity and specificity of US + CEUS + SWE in all lesion groups, ML group and NML group were 92.7% and 90.2%, 95.9% and 90.3%, 91.3% and 79.3%, respectively. In all breast group, AUCs of US + CEUS, US + SWE, US + CEUS + SWE were statistically different from AUC of US (P=0.0010, 0.0001, 0.0001). In the ML group, the AUC of US + CEUS, US + SWE, US + CEUS + SWE were statistically different from that of US (P=0.0120, 0.0008, 0.0002). In the NML group, there was a statistical difference between US + SWE and US AUC (P=0.0149). US, CEUS, and SWE have an important diagnostic value for benign and malignant ML and NML breast lesions. Multimodal ultrasound combined with US, CEUS, and SWE can improve the diagnostic efficacy in distinguishing between benign and malignant ML and NML lesions.

Non-mass Breast Lesions: Could Multimodal Ultrasound Imaging Be Helpful for Their Diagnosis?

To develop a prediction model for discriminating malignant from benign breast non-mass-like lesions (NMLs) using conventional ultrasound (US), strain elastography (SE) of US elastography and contrast-enhanced ultrasound (CEUS). A total of 101 NMLs from 100 patients detected by conventional US were enrolled in this retrospective study. The characteristics of NMLs in conventional US, SE and CEUS were compared between malignant and benign NMLs. Histopathological results were used as the reference standard. Binary logistic regression analysis was performed to identify the independent risk factors. A multimodal method to evaluate NMLs based on logistic regression was developed. The diagnostic performance of conventional US, US + SE, US + CEUS and the combination of these modalities was evaluated and compared. Among the 101 lesions, 50 (49.5%) were benign and 51 (50.5%) were malignant. Age ≥45 y, microcalcifications in the lesion, elasticity score &gt;3, earlier enhancement time and hyper-enhancement were independent diagnostic indicators included to establish the multimodal prediction method. The area under the receiver operating characteristic curve (AUC) of US + SE + CEUS was significantly higher than that of US (p &lt; 0.0001) and US + SE (p &lt; 0.0001), but there was no significant difference between the AUC of US + SE + CEUS and the AUC of US + CEUS (p = 0.216). US + SE + CEUS and US + CEUS could significantly improve the diagnostic efficiency and accuracy of conventional US in the diagnosis of NMLs.

Comparison and risk factors analysis of multiple breast cancer screening methods in the evaluation of breast non-mass-like lesions

ObjectiveTo compare multiple breast cancer screening methods for evaluating breast non-mass-like lesions (NMLs), and investigate new best screening method for breast non-mass-like lesions and the value of the lexicon of ACR BI-RADS in NML evaluation.MethodsThis retrospective study examined 253 patients aged 24–68 years who were diagnosed with breast NMLs and described the lexicon of ACR BI-RADS from April 2017 to December 2019. All lesions were evaluated by HHUS, MG, and ABUS to determine BI-RADS category, and underwent pathological examination within six months or at least 2 years of follow-up. The sensitivity, specificity, accuracy, positive predictive values (PPV), and negative predictive values (NPV) of MG, HHUS and ABUS in the prediction of malignancy were compared. Independent risk factors for malignancy were assessed using non-conditional logistic regression.ResultsHHUS, MG and ABUS findings significantly differed between benign and malignant breast NML, including internal echo, hyperechoic spot, peripheral blood flow, internal blood flow, catheter change, peripheral change, coronal features of ABUS, and structural distortion, asymmetry, and calcification in MG. ABUS is superior to MG and HHUS in sensitivity, specificity, PPV, NPV, as well as in evaluating the necessity of biopsy and accuracy in identifying malignancy. MG was superior to HHUS in specificity, PPV, and accuracy in evaluating the need for biopsy.ConclusionsABUS was superior to HHUS and MG in evaluating the need for biopsy in breast NMLs. Compared to each other, HHUS and MG had their own relative advantages. Internal blood flow, calcification, and coronal plane feature was independent risk factors in NMLs Management, and different screening methods had their own advantages in NML management. The lexicon of ACR BI-RADS could be used not only in the evaluation of mass lesions, but also in the evaluation of NML.

Comparison of diagnostic potential of shear wave elastography between breast mass lesions and non–mass–like lesions

BackgroundShear wave elastography (SWE) can improve the specificity of B-mode ultrasound (US) without reducing the sensitivity for breast cancer diagnosis. Existing research on SWE includes both mass lesions and non‑mass‑like (NML) lesions or only NML lesions; however, there are no studies comparing the diagnostic potential of SWE in the detection of mass and NML lesions in the same trial. ObjectiveThis study aimed to compare the diagnostic performance of SWE in detecting mass lesions and NML lesions and determine the different individualised thresholds of the SWE parameters according to the lesion type. MethodsThis Study included 623 breast lesions of 562 consecutive women, who were scheduled for conventional US and SWE between January 2021 and December 2021. The diagnostic performances of conventional US and each quantitative SWE parameter (maximum elastic modulus [Emax], mean elastic modulus [Emean], and elastic modulus standard deviation [Esd]) were assessed. Histological diagnosis for all Breast Imaging Reporting and Database System (BI-RADS) category 4/5 patients and some BI-RADS category 3 patients and the follow-up results of other BI-RADS category 3 patients were used as the reference standard. ResultsIn this study, 281 benign lesions and 342 malignant lesions were identified. The diagnostic performance of conventional US and SWE was better in the mass lesion group than in the NML lesion group. Every SWE parameter had a different threshold in each group, and the thresholds of the SWE parameters were higher in the mass lesion group than in the NML lesion group. In the mass lesion group, Esd had the highest Az value, whereas in the NML lesion group, Emax had the highest Az value. In both the mass and NML lesion groups, the diagnostic specificity of the combination of conventional US and SWE was significantly higher than that of conventional US alone (P < 0.05), without a significantly decrease in the diagnosticsensitivity. ConclusionsSWE could increase the confidence of breast ultrasound diagnosis, especially for NML lesions. NML lesions had lower thresholds of SWE parameters than did the mass lesions.

Re-evaluation of high-risk breast mammography lesions by target ultrasound and ABUS of breast non-mass-like lesions

ObjectiveThe purpose of this study was to reevaluate the high-risk breast non-mass-like lesions (NMLs) in mammography (MG) by target ultrasound (US) and Automated breast ultrasonography (ABUS), and to analyze the correlation between different imaging findings and the factors influencing the classification of lesions.MethodsA total of 161 patients with 166 breast lesions were recruited in this retrospectively study. All cases were diagnosed as BI-RADS 4 or 5 by MG and as NML on ultrasound. While all NMLs underwent mammography, target US and ABUS before breast surgery or biopsy in the consistent position of breast. The imaging and pathological features of all cases were collected. All lesions were classified according to the lexion of ACR BI-RADS®.ResultsThere were significant differences between benign and malignant breast NML in all the features of target US and ABUS. US, especially ABUS, was superior to MG in determining the malignant breast NML. There was a significant difference in the detection rate of calcification between MG and Target US (P < 0.001), and there was a significant difference in the detection rate of structural distortion between ABUS and MG (P < 0.001).ConclusionsTarget US, especially ABUS, can significantly improve the sensitivity, specificity and accuracy of the diagnosis of high-risk NMLs in MG. The features of Target US and ABUS such as blood supply, hyperechogenicity, ductal changes, peripheral changes and coronal features could be employed to predict benign and malignant lesions. The coronal features of ABUS were more sensitive than those of Target HHUS in showing structural abnormalities. Target US was less effective than MG in local micro-calcification.

Breast non-mass-like lesions on contrast-enhanced ultrasonography: Feature analysis, breast image reporting and data system classification assessment

BACKGROUNDBreast non-mass-like lesions (NMLs) account for 9.2% of all breast lesions. The specificity of the ultrasound diagnosis of NMLs is low, and it cannot be objectively classified according to the 5th Edition of the Breast Imaging Reporting and Data System (BI-RADS). Contrast-enhanced ultrasound (CEUS) can help to differentiate and classify breast lesions but there are few studies on NMLs alone.AIMTo analyze the features of benign and malignant breast NMLs in grayscale ultrasonography (US), color Doppler flow imaging (CDFI) and CEUS, and to explore the efficacy of the combined diagnosis of NMLs and the effect of CEUS on the BI-RADS classification of NMLs.METHODSA total of 51 breast NMLs verified by pathology were analyzed in our hospital from January 2017 to April 2019. All lesions were examined by US, CDFI and CEUS, and their features from those examinations were analyzed. With pathology as the gold standard, binary logic regression was used to analyze the independent risk factors for malignant breast NMLs, and a regression equation was established to calculate the efficiency of combined diagnosis. Based on the regression equation, the combined diagnostic efficiency of US combined with CEUS (US + CEUS) was determined. The initial BI-RADS-US classification of NMLs was adjusted according to the independent risk factors identified by CEUS, and the diagnostic efficiency of CEUS combined with BI-RADS (CEUS + BI-RADS) was calculated based on the results. ROC curves were drawn to compare the diagnostic values of the three methods, including US, US + CEUS, and CEUS + BI-RADS, for benign and malignant NMLs.RESULTSMicrocalcification, enhancement time, enhancement intensity, lesion scope, and peripheral blood vessels were significantly different between benign and malignant NMLs. Among these features, microcalcification, higher enhancement, and lesion scope were identified as independent risk factors for malignant breast NMLs. When US, US + CEUS, and CEUS + BI-RADS were used to identify the benign and malignant breast NMLs, their sensitivity rates were 82.6%, 91.3%, and 87.0%, respectively; their specificity rates were 71.4%, 89.2%, and 92.9%, respectively; their positive predictive values were 70.4%, 87.5%, and 90.9%, respectively; their negative predictive values were 83.3%, 92.6%, and 89.7%, respectively; their accuracy rates were 76.5%, 90.2%, and 90.2%, respectively; and their corresponding areas under ROC curves were 0.752, 0.877 and 0.903, respectively. Z tests showed that the area under the ROC curve of US was statistically smaller than that of US + CEUS and CEUS + BI-RADS, and there was no statistical difference between US + CEUS and CEUS + BI-RADS.CONCLUSIONUS combined with CEUS can improve diagnostic efficiency for NMLs. The adjustment of the BI-RADS classification according to the features of contrast-enhanced US of NMLs enables the diagnostic results to be simple and intuitive, facilitates the management of NMLs, and effectively reduces the incidence of unnecessary biopsy.

Non-mass versus mass-like ultrasound patterns in ductal carcinoma in situ: is there an association with high-risk histology?

To review the ultrasound (US) patterns of pure ductal carcinoma in situ (DCIS) using a non-mass-like (NML) versus mass-like (ML) classification and to investigate histopathological associations. The present study was a retrospective analysis of sonographically evident pure DCIS lesions detected in a mammographic (MG) screening programme over a 7-year period from 2008. All lesions had undergone US-guided 14 G core biopsies with no upgrades to invasive disease on surgical histopathology. Lesions that were three-dimensional with convex margins were classified as ML and all others as NML. ML lesions were subdivided into solid, cystic, or mixed, and NML lesions into ductal and non-ductal. Imaging and pathological characteristics of NML versus ML lesions were investigated using logistic regression. There were 78 lesions in 75 participants. NML lesions accounted for 45 (58%) lesions, comprising 27 (60%) ductal and 18 (40%) non-ductal subtypes. There were 33 (42%) ML lesions; the largest subgroup being solid (n=21, 64%). Significant associations between lesion type and lesion size on US (<15 versus ≥15 mm), presence of US and mammographic calcification and posterior shadowing on sonography were identified. NML lesions had fivefold higher odds (OR=5.41 95% confidence interval [CI]: 2.03, 14.39, p=0.001) to be high grade and sevenfold higher odds (OR=7 95% CI: 1.75, 27.99, p=0.006) to have comedo necrosis on histopathology. DCIS lesions can be successfully classified using ML and NML lesion descriptors and NML morphology on US is associated with histological features of "high-risk" DCIS.

A graph-based lesion characterization and deep embedding approach for improved computer-aided diagnosis of nonmass breast MRI lesions.

Nonmass-like enhancements are a common but diagnostically challenging finding in breast MRI. Nonmass-like lesions can be described as clusters of spatially and temporally inter-connected regions of enhancements, so they can be modeled as networks and their properties characterized via network-based connectivity. In this work, we represented nonmass lesions as graphs using a link formation energy model that favors linkages between regions of similar enhancement and closer spatial proximity. However, adding graph features to an existing computer-aided diagnosis (CAD) pipeline incurs an increase of feature space dimensionality, which poses additional challenges to traditional supervised machine learning techniques due to the inability to increase accordingly the number of training datasets. We propose the combination of unsupervised dimensionality reduction and embedded space clustering followed by a supervised classifier to improve the performance of a CAD system for nonmass-like lesions in breast MRI. Our work extends a previoulsy proposed framework for deep embedded unsupervised clustering (DEC) to embedding space classification, with the joint optimization of objective functions for DEC and supervised multi-layered perceptron (MLP) classification. The strength of the method lies in the ability to learn and further optimize an embedded feature representation of lower dimensionality that maximizes the diagnostic accuracy of a CAD lesion classifier to discriminate between benign and malignant lesions. We identified 792 nonmass-like enhancements (267 benign, 110 malignant and 415 unknown) in 411 patients undergoing breast MRI at our institution. The diagnostic performance of the proposed method was evaluated and compared to the performance of a conventional supervised MLP classifier in original feature space. A statistically significant increase in diagnostic area under the ROC curve (AUC) was achieved. Generalization AUC increased from 0.67 ± 0.08 to 0.81 ± 0.10 (21% increase, p-value=4.2×10-8) with the proposed graph-based lesion characterization and deep embedding framework.

Shear-Wave Elastography: Could it be Helpful for the Diagnosis of Non-Mass-Like Breast Lesions?

The goal of this study was to analyze the diagnostic performance of shear wave elastography (SWE) in differentiation of benign and malignant non-mass-like (NML) breast lesions. Three hundred sixteen consecutive breast lesions in 305 patients who have been scheduled for ultrasound (US)-guided core needle biopsy or vacuum-assisted biopsy or surgical excision between January 2013 and August 2013 were initially included in this study. Finally, 63 patients with 67 lesions classified as NML lesions comprised our study population. The features of SWE and its diagnostic performance in NML lesions were analyzed. Among the 67 NML lesions, 33 were malignant and 34 were benign. The maximum elastic modulus, mean elastic modulus, minimum elastic modulus, elastic modulus ratio and stiff rim sign of the malignant lesions were all significantly higher than those of benign lesions (p < 0.05). The combination of conventional US with maximum elastic modulus and stiff rim sign got significantly higher diagnostic specificity and positive predictive value (PPV) than conventional US (p < 0.05 for both). In the benign lesions, 23 (67.6%) unnecessary biopsies could have been eliminated after the combination of conventional US and SWE. SWE could increase diagnostic specificity and positive predictive values of NML breast lesions. The combination of conventional US and SWE could reduce unnecessary benign biopsies of NML lesions.

Non-mass-like breast lesions at ultrasonography: Feature analysis and BI-RADS assessment

ObjectiveTo analyze the features of non-mass-like (NML) breast lesions on ultrasound (US) and determine their corresponding malignancy rate and to stratify these lesion patterns according to US BI-RADS categories. Materials and methodsOne hundred sixty-four consecutive lesions were retrospectively classified into four types according to the US features, the corresponding positive predictive values (PPVs) were obtained. Clinical, imaging, and histopathological findings were reviewed. ResultsAmong the 164 lesions, 39 (24%) were classified as type Ia, 14 (8%) as type Ib, 39 (24%) as type IIa, 19 (12%) as type IIb, 19 (12%) as type III, and 34 (21%) as type IV. The PPVs for malignancy were 21% for type Ia, 79% for type Ib, 10% for type IIa, 58% for type IIb, 16% for type III, and 21% for type IV. All NML lesions were classified as BI-RADS category 4a (type IIa), 4b (type Ia, III and IV) and 4c (type Ib and IIb) according to their PPVs. There was a significantly higher frequency of malignancy among lesions of type Ib and type IIb compared with the other types (P<0.01 for each). Lesions with associated calcifications, presence of abnormal axillary nodes, or a mammographic finding of suspected malignancy had a higher probability of malignancy (P<0.05 for each). ConclusionUS is useful in clarifying the indication for biopsy of NML lesions. The types of US classifications used in our study establish reliable references for the NML patterns when stratified according to the BI-RADS categories.

Nonmasslike Lesions on Breast Sonography

To compare the imaging and clinical features of benign and malignant nonmasslike lesions in the breast. During a 2-year period at a single institution, 186 nonmasslike lesions in 158 women were pathologically confirmed through surgery or sonographically guided biopsy. The sonographic patterns (mottled, geographic, and indistinct) and distributions (focal and regional) were compared between benign and malignant lesions. The presence of sonographically visible calcifications, amount of color Doppler signals, presence of positive findings on mammography, and presence of symptoms were also compared between the two groups. A total of 156 lesions (84%) were confirmed as benign and 30 (16%) as malignant. On sonography, malignant nonmasslike lesions more frequently had mottled and geographic patterns and regional distribution than benign lesions (P < .0001). Malignant lesions also more frequently had sonographically visible calcifications (40% versus 0%; P < 0.0001) and a greater amount of color Doppler signals than benign lesions (P < .0001). On mammography, malignant lesions more frequently had densities and calcifications than benign lesions (30.4% versus 7.1%; P = 0.0052; 73.9% versus 6.1%; P < .0001, respectively). Clinically, malignant lesions were more frequently palpable and accompanied by localized pain than benign lesions (50% versus 2.6%; P< .0001; 13.3% versus 0.6%; P = .0025). The imaging and clinical features of malignant nonmasslike lesions differed significantly from those of benign nonmasslike lesions.

Positive predictive value of MRI vacuum biopsies in the diagnosis of nonmass-like lesions of the breast

Positive predictive value of MRI vacuum biopsies in the diagnosis of nonmass-like lesions of the breast

Second‐look us examination of MR‐detected breast lesions

To review our institutional experience in using second-look ultrasound (SLUS) to identify breast lesions initially detected on MR imaging that were indeterminate or suspicious for malignancy. This Health Insurance Portability and Accountability Act compliant retrospective review included 83 women with 131 lesions initially identified as indeterminate or suspicious for malignancy on MR imaging from February 1, 2008 through July 31, 2009. An SLUS correlate was confirmed on the basis of concordant location, size, and morphologic features. The detection rate of SLUS was determined. Patients' demographics, lesion size, and MR imaging morphologic features (focus, mass, non-masslike) were reviewed to identify which factors led to successful detection on SLUS. Likelihood ratio χ(2) tests were used for statistical analysis. SLUS correlates were found for 88 of 131 (67%) lesions initially detected on MR imaging; 27 of 88 (31%) were malignant. SLUS detected foci (67%) and masses (73%) more frequently than it did non-masslike lesions (54%). The detection rate of SLUS was independent of lesion size on MR imaging. Malignant lesions were not more likely than benign lesions to be detected on SLUS (61% versus 70%). SLUS provides value in the clinical workup of breast lesions that are indeterminate or suspicious for malignancy. It identified two thirds of the MR-detected lesions evaluated and permitted performance of US-guided needle biopsy on 70 of 88lesions. The likelihood of finding MR-detected lesions on SLUS was significantly higher for foci and masses than for non-masslike lesions (P < 0.05).

Abstract P2-02-12: Utility of Targeted Sonography Using Real-Time Virtual Sonography (RVS) for Breast Lesions That Were Suspicious on MRI

Abstract PURPOSE : MRI-detected suspicious breast lesions that are not expected from previous MMG or sonography, are detectable initially on MRI in 48% maximum. Therefore, biopsy is required for definitive diagnosis of MRI-detected lesions. Although MRI-guided biopsy is often necessary, sonographically guided biopsy after targeted sonography is more broadly available and less time-consuming and costly. The aim of this study was to verify the utility of targeted sonography using Real-time Virtual Sonography (RVS) for the identification of MRI-detected suspicious lesions. METHOD AND MATERIALS : From 196 breast MRI examinations, all MRI-detected suspicious lesions and subsequent biopsy were identified between February 2006 and December 2009. All patients were examined using MMG, sonography, MRI and RVS that could synchronize a sonography image and the MRI cutaway images of the same site to be displayed in real time using magnetic navigation system. Following the conventional dynamic enhanced image, MRI was obtained on a 1.5-T imager in the supine position using a flexible body surface coil in order to achieve the same position as in sonography. We searched all cases for MRI-detected suspicious lesions and investigated targeted sonography with or without RVS in identifying the lesions. RESULTS : Of the 196 patients, MRI-detected suspicious lesions were detected in 55 (28%) patients. A total of 67 suspicious lesions in 55 patients comprised this analysis. Of the study lesions, 24 (36%) were malignant and 43 (64%) were benign. Overall mean lesion size was 6.7mm. A total of 46 (69%) mass lesions were identified, compared with 16 (24%) foci and 5 (7%) nonmasslike lesions. 18 (27%) lesions were detected in targeted sonography without RVS and were revealed as cancers in eight, benign lesions in 10. In contrast, 60 (90%) lesions were detected in targeted sonography with RVS and were revealed as cancers in 21, benign lesions in 39. Although seven (10%) lesions were not detected with RVS, all lesions were able to project enhanced MRI information onto a body surface correctly as we checked ultrasound form images without the use of large-scale equipment. CONCLUSION: The present results suggest that targeted sonography with RVS appears to be not time consuming technique which can identify a large part of MRI-detected suspicious lesions. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P2-02-12.

MR-Directed (“Second-Look”) Ultrasound Examination for Breast Lesions Detected Initially on MRI: MR and Sonographic Findings

The objective of our study was to assess the clinical utility of MR-directed ("second-look") ultrasound examination to search for breast lesions detected initially on MRI. A retrospective review was performed of the records of 158 consecutive patients (202 lesions) with breast abnormalities initially detected on MRI between July 2003 and May 2006. All lesions were detected as enhancing findings on a dynamic contrast MR study and were subsequently evaluated with ultrasound. Ultrasound was performed using MR images as a guide to lesion location, size, and morphology. Pathology findings were confirmed by subsequent percutaneous biopsy or lesion excision. Imaging follow-up was used for probably benign lesions, which were not biopsied. Of the 202 MRI-detected lesions, ultrasound correlation was made in 115 (57%) including 33 malignant lesions and 82 benign lesions. The remaining 87 lesions were not sonographically correlated and included 11 malignant lesions and 76 nonmalignant lesions. Mass lesions identified on MRI were more likely to have a sonographic correlate than nonmasslike lesions (65% vs 12%, respectively); malignant mass lesions were more likely to show an ultrasound correlation (85%). The malignant lesions with successful sonographic correlation tended to present with subtle sonographic findings. MR-directed ultrasound of MRI-detected lesions was useful for decision making as part of the diagnostic workup. Malignant lesions were likely to have an ultrasound correlate, especially when they presented as masses on MRI. However, the sonographic findings of these lesions were often subtle, and careful scanning technique was needed for successful MRI-ultrasound correlation.

Incidental breast lesions found on computer tomography – what is their significance?

To analyze the features of non-mass-like (NML) breast lesions on ultrasound (US) and determine their corresponding malignancy rate and to stratify these lesion patterns according to US BI-RADS categories.One hundred sixty-four consecutive lesions were retrospectively classified into four types according to the US features, the corresponding positive predictive values (PPVs) were obtained. Clinical, imaging, and histopathological findings were reviewed.Among the 164 lesions, 39 (24%) were classified as type Ia, 14 (8%) as type Ib, 39 (24%) as type IIa, 19 (12%) as type IIb, 19 (12%) as type III, and 34 (21%) as type IV. The PPVs for malignancy were 21% for type Ia, 79% for type Ib, 10% for type IIa, 58% for type IIb, 16% for type III, and 21% for type IV. All NML lesions were classified as BI-RADS category 4a (type IIa), 4b (type Ia, III and IV) and 4c (type Ib and IIb) according to their PPVs. There was a significantly higher frequency of malignancy among lesions of type Ib and type IIb compared with the other types (P < 0.01 for each). Lesions with associated calcifications, presence of abnormal axillary nodes, or a mammographic finding of suspected malignancy had a higher probability of malignancy (P < 0.05 for each).US is useful in clarifying the indication for biopsy of NML lesions. The types of US classifications used in our study establish reliable references for the NML patterns when stratified according to the BI-RADS categories.