Sensitivity For Breast Cancer Detection Research Articles

Interval Breast Cancers Versus Screen Detected Breast Cancers: A Retrospective Cohort Study

Mammographic screening detects most breast cancers but there are still women diagnosed with breast cancer between annual mammograms. We aim to identify features that differentiate screen detected breast cancers from interval breast cancer. All screening mammograms (n=211,517) performed 7/1/2013-6/30/2020 at our institution were reviewed. Patients with breast cancer diagnosed within one year of screening were included and divided into two distinct groups: screen detected cancer group and interval cancer group. Characteristics in these groups were compared using the chi square test, fisher test, and student's T test. A total of 1,232 patients were included (mean age 64 +/- 11). Sensitivity of screening mammography was 92% (1,136 screen detected cancers, 96 interval cancers). Patient age, race, and personal history of breast cancer were similar between the groups (p > 0.05). Patients with interval cancers more often had dense breast tissue (75/96=78% versus 694/1136=61%, p < 0.001). Compared to screen detected cancers, interval cancers were more often primary tumor stage two or higher (41/96=43% versus 139/1136=12%, p < 0.001) and regional lymph node stage one or higher (21/96=22% versus 132/1136=12%, p=0.003). Interval cancers were more often triple negative (16/77=21% versus [48/813=6%], p < 0.001) with high Ki67 proliferation indices (28/45=62% versus 188/492=38%, p=0.002). Mammographic screening had high sensitivity for breast cancer detection (92%). Interval cancers were associated with dense breast tissue and had higher stage with less favorable molecular features compared to screen detected cancers.

Limited value of multiparametric MRI with dynamic contrast-enhanced and diffusion-weighted imaging in non-mass enhancing breast tumors

PurposeTo investigate the diagnostic value of multiparametric MRI (mpMRI) including dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) in non-mass enhancing breast tumors. MethodPatients who underwent mpMRI, who were diagnosed with a suspicious non-mass enhancement (NME) on DCE-MRI (BI-RADS 4/5), and who subsequently underwent image-guided biopsy were retrospectively included. Two radiologists independently evaluated all NMEs, on both DCE-MR images and high-b-value DW images. Different mpMRI reading approaches were evaluated: 1) with a fixed apparent diffusion coefficient (ADC) threshold (<1.3 malignant, ≥1.3 benign) based on the recommendation by the European Society of Breast Imaging (EUSOBI); 2) with a fixed ADC threshold (<1.5 malignant, ≥1.5 benign) based on recently published trial data; 3) with an ADC threshold adapted to the assigned BI-RADS classification using a previously published reading method; and 4) with individually determined best thresholds for each reader. Results: The final study sample consisted of 66 lesions in 66 patients. DCE-MRI alone had the highest sensitivity for breast cancer detection (94.8–100 %), outperforming all mpMRI reading approaches (R1 74.4–87.1 %, R2 71.7–94.8 %) and DWI alone (R1 74.4 %, R2 79.4 %). The adapted approach achieved the best specificity for both readers (85.1 %), resulting in the best diagnostic accuracy for R1 (86.5 %) but a moderate diagnostic accuracy for R2 (77.2 %). ConclusionmpMRI has limited added diagnostic value to DCE-MRI in the assessment of NME.

Multi-detector CT chest: can it omit the further need for contrast enhnaced spectral mammography in breast cancer patients candidate for CT staging?

BackgroundDuring multi-detector computed tomography (MDCT) of the chest, incidental breast lesions (IBLs) are occasionally encountered. Mammography remains the gold standard for the early detection of breast cancer. However, limitations exist in patients with dense breasts. Contrast spectral mammography (CESM) is widely available compared to MRI; it increases the sensitivity for breast cancer detection without decreasing the specificity.ResultsThe study is a prospective study that included 113 female breast cancer patients for CT staging. One hundred and six of the patients had unilateral carcinoma and 7 of them had bilateral cancer with a total of 120 breasts evaluated. The CT findings were correlated with CESM findings regarding the multiplicity and bilaterality of the disease. The sensitivity, specificity, PPV, NPV, and accuracy of the CT in the detection of multiplicity were 97.44%, 100%, 100%, 95.45%, and 98.33%, respectively, and the sensitivity, specificity, PPV, NPV, and accuracy of the CT in the detection of bilateral disease were 68.18%, 97.96%, 88.24%, 93.20%, and 92.50%, respectively.ConclusionsBreast cancer patients for MDCT chest as a part of their metastatic workup can omit the further need for CESM.

Spatially tracked whole-breast three-dimensional ultrasound system toward point-of-care breast cancer screening in high-risk women with dense breasts.

Mammographic screening has reduced mortality in women through the early detection of breast cancer. However, the sensitivity for breast cancer detection is significantly reduced in women with dense breasts, in addition to being an independent risk factor. Ultrasound (US) has been proven effective in detecting small, early-stage, and invasive cancers in women with dense breasts. To develop an alternative, versatile, and cost-effective spatially tracked three-dimensional (3D) US system for whole-breast imaging. This paper describes the design, development, and validation of the spatially tracked 3DUS system, including its components for spatial tracking, multi-image registration and fusion, feasibility for whole-breast 3DUS imaging and multi-planar visualization in tissue-mimicking phantoms, and a proof-of-concept healthy volunteer study. The spatially tracked 3DUS system contains (a) a six-axis manipulator and counterbalanced stabilizer, (b) an in-house quick-release 3DUS scanner, adaptable to any commercially available US system, and removable, allowing for handheld 3DUS acquisition and two-dimensional US imaging, and (c) custom software for 3D tracking, 3DUS reconstruction, visualization, and spatial-based multi-image registration and fusion of 3DUS images for whole-breast imaging. Spatial tracking of the 3D position and orientation of the system and its joints (J1-6 ) were evaluated in a clinically accessible workspace for bedside point-of-care (POC) imaging. Multi-image registration and fusion of acquired 3DUS images were assessed with a quadrants-based protocol in tissue-mimicking phantoms and the target registration error (TRE) was quantified. Whole-breast 3DUS imaging and multi-planar visualization were evaluated with a tissue-mimicking breast phantom. Feasibility for spatially tracked whole-breast 3DUS imaging was assessed in a proof-of-concept healthy male and female volunteer study. Mean tracking errors were 0.87 ± 0.52, 0.70 ± 0.46, 0.53 ± 0.48, 0.34 ± 0.32, 0.43 ± 0.28, and 0.78 ± 0.54mm for joints J1-6 , respectively. Lookup table (LUT) corrections minimized the error in joints J1 , J2 , and J5 . Compound motions exercising all joints simultaneously resulted in a mean tracking error of 1.08 ± 0.88mm (N=20) within the overall workspace for bedside 3DUS imaging. Multi-image registration and fusion of two acquired 3DUS images resulted in a mean TRE of 1.28 ± 0.10mm. Whole-breast 3DUS imaging and multi-planar visualization in axial, sagittal, and coronal views were demonstrated with the tissue-mimicking breast phantom. The feasibility of the whole-breast 3DUS approach was demonstrated in healthy male and female volunteers. In the male volunteer, the high-resolution whole-breast 3DUS acquisition protocol was optimized without the added complexities of curvature and tissue deformations. With small post-acquisition corrections for motion, whole-breast 3DUS imaging was performed on the healthy female volunteer showing relevant anatomical structures and details. Our spatially tracked 3DUS system shows potential utility as an alternative, accurate, and feasible whole-breast approach with the capability for bedside POC imaging. Future work is focused on reducing misregistration errors due to motion and tissue deformations, to develop a robust spatially tracked whole-breast 3DUS acquisition protocol, then exploring its clinical utility for screening high-risk women with dense breasts.

Evaluation of Breast Mass by Mammography and Ultrasonography with Histopathological Correlation.

Mammography, ultrasound and Magnetic Resonance Imaging are the available modalities for the evaluation of breast masses. Advances and ongoing improvements in imaging technologies have improved the sensitivity of breast cancer detection and diagnosis, but each modality is most beneficial when utilized according to individual traits such as age, risk factors, and breast density. However, pathological diagnosis is most crucial for the treatment of breast masses. A cross-sectional study were conducted from January 2017 to April 2018. There were total of 50 patients with clinically diagnosed palpable breast lumps who attended Gynaecological OPD/surgical OPD/medicine OPD in the study period. The patients above 30 years were evaluated by mammography and ultrasound in Department of Radiology, National Academy of Medical Sciences, Bir Hospital. The patients were then send for FNAC/biopsy and histopathology examination. Data were collected and analyzed using SPSS version 16. Specificity and sensitivity of MG and USG individually and in combination to determine the nature of breast lump in relation to histopathological findings were calculated. Ultrasound had 88.90% sensitivity and 68.80% specificity whereas mammogram had 94.40% and 87.50% sensitivity and specificity respectively. When combined, both sensitivity of diagnosing malignant lesions increases up to 94.4% and specificity decreases up to 31.2%. Most of the variables of ultrasound and mammography (except density of the lesion) had significance in predicting nature of the lesion (p< 0.05). Combined Mammography and Ultrasound had higher sensitivity than sensitivity rate observed for either single modality. A combined Mammography and Ultrasound approach to detect breast diseases was significantly more helpful in accurate evaluation of breast pathologies.

Diagnostic performance of digital breast tomosynthesis for predicting response to neoadjuvant systemic therapy in breast cancer patients: A comparison with magnetic resonance imaging, ultrasound, and full-field digital mammography.

BackgroundThe goals of neoadjuvant systemic therapy (NST) are to reduce tumor volume and to provide a prognostic indicator in assessing treatment response. Digital breast tomosynthesis (DBT) was developed and has increased interest in clinical settings due to its higher sensitivity for breast cancer detection compared to full-field digital mammography (FFDM).PurposeTo evaluate the accuracy of DBT in assessing response to NST compared to FFDM, ultrasound (US), and magnetic resonance imaging (MRI) in breast cancer patients.Material and MethodsIn this retrospective study, 95 stages II–III breast cancer patients undergoing NST and subsequent surgeries were enrolled. After NST, the longest diameter of residual tumor measured by DBT, FFDM, US, and MRI was compared with pathology. Agreements and correlations of tumor size were assessed, and the diagnostic performance for predicting pathologic complete response (pCR) was evaluated.ResultsMean residual tumor size after NST was 19.9 mm for DBT, 18.7 mm for FFDM, 16.0 mm for US, and 18.4 mm for MRI, compared with 17.9 mm on pathology. DBT and MRI correlated better with pathology than that of FFDM and US. The ICC values were 0.85, 0.87, 0.74, and 0.77, respectively. Twenty-five patients (26.3%) achieved pCR after NST. For predicting pCR, area under the receiver operating characteristic (ROC) curve for DBT, FFDM, US, and MRI were 0.79, 0.66, 0.68, and 0.77, respectively.ConclusionDBT has good correlation with histopathology for measuring residual tumor size after NST. DBT was comparable to MRI in assessing tumor response after completion of NST.

What's Hot in Breast MRI.

Several articles in the literature have demonstrated a promising role for breast MRI techniques that are more economic in total exam time than others when used as supplement to mammography for detection and diagnosis of breast cancer. There are many technical factors that must be considered in the shortened breast MRI protocols to cut down time of standard ones, including using optimal fat suppression, gadolinium-chelates intravascular contrast administrations for dynamic imaging with post processing subtractions and maximum intensity projections (MIP) high spatial and temporal resolution among others. Multiparametric breast MRI that includes both gadolinium-dependent, i.e., dynamic contrast-enhanced (DCE-MRI) and gadolinium-free techniques, i.e., diffusion-weighted/diffusion-tensor magnetic resonance imaging (DWI/DTI) are shown by several investigators that can provide extremely high sensitivity and specificity for detection of breast cancer. This article provides an overview of the proven indications for breast MRI including breast cancer screening for higher than average risk, determining chemotherapy induced tumor response, detecting residual tumor after incomplete surgical excision, detecting occult cancer in patients presenting with axillary node metastasis, detecting residual tumor after incomplete breast cancer surgical excision, detecting cancer when results of conventional imaging are equivocal, as well patients suspicious of having breast implant rupture. Despite having the highest sensitivity for breast cancer detection, there are pitfalls, however, secondary to false positive and false negative contrast enhancement and contrast-free MRI techniques. Awareness of the strengths and limitations of different approaches to obtain state of the art MR images of the breast will facilitate the work-up of patients with suspicious breast lesions.

Mammographic Breast Density in Pakistani Women, Factors Affecting It, and Inter-Observer Variability in Assessment.

IntroductionBreast density on mammography can affect the sensitivity of breast cancer detection and is an independent risk factor for breast cancer. The incidence of breast cancer in Pakistani women is reported to be the highest among women in Asia. No published data is describing the patterns of mammographic breast density in this population. We undertook this study to assess the Breast Imaging Reporting and Data System (BI-RADS) patterns of breast density on mammography, factors that affect breast density, and inter-observer variability in breast density assessment.MethodsBilateral breast mammograms were retrospectively reviewed for breast density by two separate readers (resident and attending radiologist). Breast density was categorized into four types according to the BI-RADS lexicon. Types 1 and 2 were grouped into non-dense and types 3 and 4 into dense breasts. The association of patient factors with breast density was assessed, with p < 0.05 considered statistically significant. The inter-observer variability in breast density assessment between the two readers was calculated using Cohen's κ coefficient.ResultsA total of 612 women underwent mammography in the study period. Type 3 (heterogeneously dense breast parenchyma) was the most frequent pattern (51.6%) followed by type 2 (scattered fibroglandular) pattern (38.9%). Fatty parenchyma (type 1) and extremely dense parenchyma (type 4) were the least common. Breast density was inversely related to age (p < 0.001) and parity (p <0.002). Breast density was also lower in postmenopausal women (p < 0.001). There was no statistically significant difference in mean age at menarche, age at first delivery, family history of breast cancer, or presence of cancer among women with dense and non-dense breasts. The inter-observer agreement was almost perfect (κ = 0.86). ConclusionThe majority of women in our population (56.9%) had dense breasts (BI-RADS type 3 and 4) which decrease the sensitivity of breast cancer detection on mammography suggesting it may be insufficient as the sole screening/diagnostic tool in this population. Lower breast density was associated with increasing age, parity, and post-menopausal status. Breast density assessment was almost perfect among the resident and attending radiologist.

Abbreviated Breast MRI: Road to Clinical Implementation.

Breast MRI offers high sensitivity for breast cancer detection, with preferential detection of high-grade invasive cancers when compared to mammography and ultrasound. Despite the clear benefits of breast MRI in cancer screening, its cost, patient tolerance, and low utilization remain key issues. Abbreviated breast MRI, in which only a select number of sequences and postcontrast imaging are acquired, exploits the high sensitivity of breast MRI while reducing table time and reading time to maximize availability, patient tolerance, and accessibility. Worldwide studies of varying patient populations have demonstrated that the comparable diagnostic accuracy of abbreviated breast MRI is comparable to a full diagnostic protocol, highlighting the emerging role of abbreviated MRI screening in patients with an intermediate and high lifetime risk of breast cancer. The purpose of this review is to summarize the background and current literature relating to abbreviated MRI, highlight various protocols utilized in current multicenter clinical trials, describe workflow and clinical implementation issues, and discuss the future of abbreviated protocols, including advanced MRI techniques.

Development and Characterization of B7-H3-specific Affibody-coated Microbubbles for Breast US Imaging.

HomeRadiology: Imaging CancerVol. 2, No. 2 PreviousNext Research HighlightsFree AccessDevelopment and Characterization of B7-H3-specific Affibody-coated Microbubbles for Breast US ImagingAdeline N. BoettcherAdeline N. BoettcherAdeline N. BoettcherPublished Online:Mar 27 2020https://doi.org/10.1148/rycan.2020204008MoreSectionsPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked InEmail Take-Away Points■ Major Focus: Improving differentiation between normal and benign breast tissue with US imaging using engineered B7-H3-specific affibody-coated microbubbles (MBABY-B7-H3).■ Key Result: MBABY-B7-H3 targeting enhanced US signal from breast tumors.■ Impact: Clinical development of an affibody and microbubble-based targeting agent for US may help to increase accurate breast cancer detection.Mammography and US imaging are two widely used imaging modalities to screen and assess potential breast lesions. US imaging in particular has low sensitivity and low positive predictive value, which leads to unnecessary follow-up and biopsy collection. Thus, there is a need to develop imaging methods that better differentiate between normal and benign tissues.Microbubbles are gas-filled lipid or protein particles that can enhance US imaging contrast due to differences in acoustic pressure upon US imaging. In recent years, microbubbles have been functionalized to target different cellular and molecular markers that would allow for a more specific signal to be observed if a breast lesion was present. B7-H3 is an emerging molecular imaging and immunotherapy target that is differentially expressed on endothelial cells surrounding benign or malignant breast tissues. Affibodies are small affinity molecules that have higher tissue penetrability than antibodies. Taken together, Bam et al developed and assessed B7-H3-specific affibody (ABY B7-H3)-coated microbubbles (MBABY-B7-H3) for US visualization of breast tumors in two preclinical mouse models.In a first model, the authors use an orthotopic xenograft model with human breast MDA-MB-231 cells with MS1 endothelial cell line that did (MSB7-H3) or did not (MSWT) express B7-H3. A single mouse in these experiments had MDA-MB-231 tumors in both flanks that were co-engrafted with MSB7-H3 in the left flank and MSWT in the right flank. US imaging with MBABY-B7-H3 resulted in a significantly higher imaging signal in the left flank with MSB7-H3. They additionally tested nonspecific microbubbles (MBNon-targeted) and found that mice injected with MBABY-B7-H3 had higher US signal at the tumor site. The authors then performed a second experiment in a MMTV-PyMT transgenic mouse model that spontaneously develops mammary tumors expressing mouse B7-H3. Similar to the previous experiment, mice that received MBABY-B7-H3 had significantly higher US imaging signals than control mice that received MBNon-targeted at the tumor site.Taken together, the development and clinical translation of targeted microbubbles for US imaging signal enhancement may help to increase the sensitivity of breast cancer detection in the clinic.Highlighted ArticleBam R, Lown PS, Stern LA, et al. Efficacy of affibody-based ultrasound molecular imaging of vascular B7-H3 for breast cancer detection. Clin Cancer Res 2020;1655. doi: 10.1158/1078-0432.CCR-19-1655Highlighted ArticleBam R, Lown PS, Stern LA, et al. Efficacy of affibody-based ultrasound molecular imaging of vascular B7-H3 for breast cancer detection. Clin Cancer Res 2020;1655. doi: 10.1158/1078-0432.CCR-19-1655 Google ScholarArticle HistoryPublished online: Mar 27 2020 FiguresReferencesRelatedDetailsRecommended Articles US Molecular Imaging Sensitively Captures Acute Ileitis Therapy ResponseRadiology2018Volume: 289Issue: 1pp. 101-102Molecular Breast Imaging in Breast Cancer Screening and Problem SolvingRadioGraphics2017Volume: 37Issue: 5pp. 1309-1606Precision Medicine and Radiogenomics in Breast Cancer: New Approaches toward Diagnosis and TreatmentRadiology2018Volume: 287Issue: 3pp. 732-747Development of Multispectral Optoacoustic Tomography as a Clinically Translatable Modality for Cancer ImagingRadiology: Imaging Cancer2020Volume: 2Issue: 6High-Resolution Photoacoustic Tomography for Early-Stage Cancer Detection and Its Clinical TranslationRadiology: Imaging Cancer2020Volume: 2Issue: 3See More RSNA Education Exhibits Acute Imaging of Flank Pain: What to Look for When the Kidney Appears NormalDigital Posters2017The Good, the Bad, and the Ugly: LTB Quantification an Unknown Tool in the Differentiation of Breast Cancer with Impact on the Prognosis Prior BiopsyDigital Posters2017Personalized Breast Cancer Screening: Algorithm based on Breast Cancer Risk Stratification and Breast Composition CategoriesDigital Posters2017 RSNA Case Collection Lung Carcinoma Metastatic to the BreastRSNA Case Collection2020Solitary Fibrous Tumor of the BreastRSNA Case Collection2020Malignancy on abbreviated screening breast MRIRSNA Case Collection2020 Vol. 2, No. 2 Metrics Downloaded 171 times Altmetric Score

Abstract P1-02-05: Breast cancer development at the fat-gland interface (FGI): Importance of coronal imaging and ultrasound tomography

Abstract PURPOSE. Recent analyses of tumor location by breast magnetic resonance (MR) imaging have shown that breast cancers were significantly more likely to be located, at or near the fat-gland interface (FGI). However, these analyses did not include benign masses or coronal evaluations. Ultrasound tomography (UST) is a novel multi-sequence tomographic form of sonography with anatomic and physiologic information that can improve the sensitivity of breast cancer detection, particularly in women with dense breasts. The purpose of this study was to use the native coronal imaging plane of UST SoftVue (Delphinus Medical Technologies, Inc.) to map the locations of cancers, fibroadenomas and cysts, relative to the FGI, in order to facilitate the detection and characterization of breast masses in future UST screening. METHODS AND MATERIALS. Mass location in coronal UST images was determined by a MQSA certified radiologist with extensive UST imaging experience. The relationship of the lesion to the FGI was noted for a total of 427 breast masses (117 cancers, 135 fibroadenomas, 135 cysts and 40 other benign findings), confirmed by biopsy or by hand-held ultrasound for masses that fulfilled all criteria for a simple cyst. The FGI was defined as the circumferential interface between the peripheral fat and parenchyma as determined by examining sound speed (SS) images, which reliably differentiate the much lower SS of fat compared to that of dense tissue. Mass location was placed into three groups: (i) completely surrounded by dense fibroglandular tissue, (ii) completely surrounded by fat or (iii) partially surrounded by both (i.e., the FGI). Lesion locations relative to FGI were compared using the chi-squared test. RESULTS. Cancers were located at the FGI in 93.2% (109/117) of the cases and were surrounded by fat in 6.0% (7/117) or parenchyma in 0.9% (1/117) (p&amp;lt;0.001) of the cases, respectively (Table 1). For fibroadenomas, 63.0% (85/135) were found at the FGI while 29.9% of cysts were found at the FGI. Moreover, 68.9% of cysts and 31.1% of fibroadenomas were fully surrounded by dense tissue which was dramatically more than cancers (0.9%). DISCUSSION. Coronal imaging by UST provides reliable circumferential evaluation of the FGI, which can be augmented by axial/sagittal reconstructions as needed for additional confirmation of anterior/posterior aspects of the FGI. Our results confirm the previously reported MRI findings that cancers have a very strong tendency to be located at the FGI and extend these findings by demonstrating that benign masses have a weaker tendency in that regard. With the introduction of UST, our finding that breast cancers occur more frequently at the fat-gland interface may facilitate the conspicuity, rapid search and localization of cancers during screening of women with dense breasts. Perhaps equally important for future specificity of screening women with dense breasts, fibroglandular tissue surrounded only 0.9% of cancers and was much more commonly associated with benign masses. CONCLUSIONS. The native coronal imaging plane by SoftVue UST facilitated detection and localization of cancers, which were much more likely to be found at the FGI (p&amp;lt;0.001), compared to masses surrounded by fibroglandular tissue were much more likely to be benign. UST is a novel new technology that has the potential for improved breast cancer detection. This study supports its possible integration into clinical practice. Table 1Type of massAt FGIIn Dense tissueIn FatCancer109 (93%)1 (1%)7 (6%)Fibroadenoma85 (63%)42 (31%)8 (6%)Cyst39 (29%)93 (69%)3 (2%) Citation Format: Peter Littrup, Mark Sak, Neb Duric, Rachel Brem. Breast cancer development at the fat-gland interface (FGI): Importance of coronal imaging and ultrasound tomography [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-02-05.

The Diagnostic Performance of Contrast Enhanced Spectral Mammography in Detecting Occult Breast Lesions in Patients with Dense Breasts

Abstract Background: Contrast Enhanced Spectral Mammography (CESM) is an evolving imaging technique using contrast media to enhance the sensitivity for breast cancer detection and to extend the capability of mammography. Aim of Study: To evaluate the added benefit of Contrast Enhanced Mammography (CESM) in detecting occult breast lesions that escaped conventional Digital Mammography (DM). Patients and Methods: 68 female patients (121 breasts) with dense breasts were enrolled in this study. CESM was performed after conventional DM which was negative. CESM results were compared to sonography and histopathologic results. Diagnostic accuracy of CESM in differentiating malignant from benign lesions was determined. Results: By using CESM, 18 cancers were detected in 68 patients with negative conventional mammographic studies. CESM had sensitivity 88.9%, specificity was 100%, PPV was 100%, NPV was 60% while the overall diagnostic accuracy of CESM was 85.7% in cancer detection. Conclusion: CESM has the potential to increase breast cancer detection rate over conventional DM especially in women with dense breasts. CESM has high specificity and positive predictive value in identifying malignant breast lesions. CESM is a promising tool for screening women with dense breasts and high risk for breast cancer.

SNiPER: a novel hypermethylation biomarker panel for liquid biopsy based early breast cancer detection.

Mammography is the gold standard for early breast cancer detection, but shows important limitations. Blood-based approaches on basis of cell-free DNA (cfDNA) provide minimally invasive screening tools to characterize epigenetic alterations of tumor suppressor genes and could serve as a liquid biopsy, complementing mammography. Potential biomarkers were identified from The Cancer Genome Atlas (TCGA), using HumanMethylation450-BeadChip data. Promoter methylation status was evaluated quantitatively by pyrosequencing in a serum test cohort (n = 103), a serum validation cohort (n = 368) and a plasma cohort (n = 125). SPAG6, NKX2-6 and PER1 were identified as novel biomarker candidates. ITIH5 was included on basis of our previous work. In the serum test cohort, a panel of SPAG6 and ITIH5 showed 63% sensitivity for DCIS and 51% sensitivity for early invasive tumor (pT1, pN0) detection at 80% specificity. The serum validation cohort revealed 50% sensitivity for DCIS detection on basis of NKX2-6 and ITIH5. Furthermore, an inverse correlation between methylation frequency and cfDNA concentration was uncovered. Therefore, markers were tested in a plasma cohort, achieving a 64% sensitivity for breast cancer detection using SPAG6, PER1 and ITIH5. Although liquid biopsy remains challenging, a combination of SPAG6, NKX2-6, ITIH5 and PER1 (SNiPER) provides a promising tool for blood-based breast cancer detection.

Breast MRI: State of the Art.

MRI of the breast has the highest sensitivity for breast cancer detection among current clinical imaging modalities and is indispensable for breast imaging practice. While the basis of breast MRI consists of T1-weighted contrast-enhanced imaging, T2-weighted, ultrafast, and diffusion-weighted imaging may be used to improve lesion characterization. Such multiparametric assessment of breast lesions allows for excellent discrimination between benign and malignant breast lesions. Indications for breast MRI are expanding. In preoperative staging, multiple studies confirm the superiority of MRI to other imaging modalities for tumor size estimation and detection of additional tumor foci in the ipsilateral and contralateral breast. Ongoing studies show that in experienced hands this can be used to improve breast cancer surgery, although there is no evidence of improved long-term outcomes. Screening indications are likewise growing as evidence is accumulating that OncologicRI depicts cancers at an earlier stage than mammography in all women. To manage the associated costs for screening, the use of abbreviated protocols may be beneficial. In patients treated with neoadjuvant chemotherapy, MRI is used to document response. It is essential to realize that oncologic and surgical response are different, and evaluation should be adapted to the underlying question.

Role of diffusion weighted imaging and magnetic resonance spectroscopy in breast cancer patients with indeterminate dynamic contrast enhanced magnetic resonance imaging findings

PurposeDynamic contrast enhanced MRI (DCEMRI), diffusion weighted imaging (DWI) and in vivo proton (1H) magnetic resonance spectroscopy (MRS) provides functional and molecular nature of breast cancer. This study evaluates the potential of the combination of three MR parameters [curve kinetics, apparent diffusion coefficient (ADC) and total choline (tCho) concentration] determined from these techniques in increasing the sensitivity of breast cancer detection. MethodsMR investigations were carried out at 1.5 T on 56 patients with cytologically/histologically confirmed breast carcinoma. Single-voxel MRS was used to determine the tCho concentration. 3D FLASH was used for DCEMRI while single shot EPI based DWI was used for ADC determination. ResultsOn DCEMRI, one patient showed type I curve, while 8 showed type II and 47 showed type III curve thus giving a sensitivity of 83.9% as detection rate of malignancy. tCho concentration was above cut-off value (2.54 mmol/kg) for 50/56 cases giving a sensitivity of 89.3%. Among 9 indeterminate DCEMRI cases, tCho showed malignancy in 6 cases with type II curve. DWI detected malignancy in 54/56 cases that included 9 cases that were false negative on DCEMRI, yielding a sensitivity of 96.4%. A total of 54 cases showed malignancy when any two of the three MR parameters was positive for malignancy yielding a sensitivity of 96.4% while it increased to 100% when any one parameters showed positive result. ConclusionDWI showed highest sensitivity of detection compared to DCEMRI and MRS. Multi-parametric approach yielded 96.4% and 100% sensitivity when any two or one of the three parameters was taken as positive for malignancy, respectively. Also the results demonstrated that addition of DWI and MRS play a significant role in establishing the final diagnosis of malignancy, especially in cases where DCEMRI is indeterminate.

MAMMOGRAPHY AND MAMMOSCINTIGRAPHY WITH 99M TC-MIBI IN THE DIAGNOSIS OF MULTICENTRIC BREAST CANCER

Objective: To compare diagnostic capability of mammography and mammoscintigraphy with 99mTc-methoxyisobutylisonitrile (MIBI) in diagnostic of multicentric breast cancer. Material and Methods: We respectively analyzed 437 consecutive women with suspected breast cancer between 2014 to 2016. All of them underwent mammography and mammoscintigraphy. Craniocaudal and mediolateral oblique images were obtained. Mammoscintigraphy was performed 15-20 min. after intravenous injection 740 MBq of 99mTc-methoxyisobutylisonitrile (MIBI). Final interpretation of the data was done according to histological examination. Results: Breast cancer was detect in 367(84%) of patients. Most of them 320(87%) had single node breast cancer and 47(13%) - multicentric breast cancer. Sensitivity, specificity and accuracy in diagnostic of multicentric breast cancer were 40,4%, 95,3%, 88% for mammography and 83%, 98%, 96% for mammoscintigraphy respectively. The combination of these methods allowed significantly increase sensitivity of breast cancer detection up to 93,6%. Specificity was 93,4%.

Shear Wave Elastography of the Breast Lesions: Quantitative Analysis of the Heterogeneous Elasticity Improves the Diagnosis Performance

To evaluate whether addition of quantitative analysis of the heterogeneous elasticity (Ehetero) could improve the diagnosis performance of shear wave (SW) elastography in breast cancers. From October 2015 to February 2017, 239 patients with 255 breast lesions (126 benign, 129 malignant) were enrolled in this study. All lesions were evaluated with ultrasound Breast Imaging Reporting and Data System (BI-RADS) and VirtualTouch IQ shear wave elastography. Three region of interests were placed over the highest stiffness or lowest stiffness area of the lesions to measure the SW velocity (SWV), respectively. Ehetero was determined as the difference between the averaged highest SWV and lowest SWV. The diagnosis performances including area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive and negative likelihood ratio were determined for BI-RADS, SWVmax and Ehetero. Ehetero showed the highest AUC (0.953; 95% confidence interval [CI]: 0.924 - 0.983), which was higher than SWVmax (0.938; 95% CI: 0.908 - 0.968) (P<0.001) and BI-RADS (0.705; 95% CI: 0.662 - 0.748) (P<0.001), with a positive likelihood ratio of 19.53 (95% CI: 8.9 - 42.7) and a negative likelihood ratio of 0.07 (95% CI: 0.04 - 0.10). The sensitivity of Ehetero was 93.02% (95% CI: 87.2% - 96.8%), which was significant higher than SWVmax (83.72%, 95% CI: 76.2% - 89.6%) (P<0.001), while there was no significant difference for the specificity between Ehetero (95.24%, 95% CI: 89.9 - 98.2) and SWVmax (92.86%, 95% CI: 86.9 - 96.7) (P=0.375). Quantitative analysis of the heterogeneous elasticity can improve SW elastography sensitivity in breast cancer detection, without losing of specificity.

Breast Core-Needle Biopsy in a Large Tertiary Oncologic Centre—1-Year Experience after the Introduction of the Method

Ultrasound (US)-guided core-needle biopsy (CNB) is currently the procedure of choice for work-up of suspicious breast lesion. It is mainly used for evaluation of suspicious breast lesions categorized as BI-RADS 4 and 5 (Breast Imaging-Reporting and Data System). The conducted study included 56 female patients with detected suspicious breast leasions, and they underwent US-guided CNB during 1-year period with the aim to investigate the value of US-guided CNB of the breast in a tertiary-level large-volume oncological centre setting with respect of indications, technical adequacy and safety. 2 patients who entered the study were previously diagnosed as BIRADS 2, 3 patients as BIRADS 3, 18 patients as BIRADS 4 and 33 patients as BIRADS 5. In 14 patients with BC (breast cancer), both FNA (fine-needle aspiration) and CNB were performed, and the malignancy was accurately diagnosed by cytology in 9 patients, confirmed by subsequent CNB in all of them. ADH (atypical ductal hyperplasia) was initialy diagnosed by FNA in 5 patients, and in 2 of them, BC was initialy missed by FNA, but deteced by CNB. As it is known, the cytology has lower sensitivity for detection of BC than hystology, with false-negative rate ranging from 2.5% to 17.9%. In our material, 18.7% of carcinomas were initialy left undetected by FNAC, and subsequently confirmed by CNB. All confirmed carcinomas were correctly suspected on imaging, and categorized as BI-RADS 4 or 5, while all BI-RADS 2 and 3 findings were confirmed as benign on hystology. False-positive rate of imaging was 8%. An average number of 4 tissue cores (range: 2 - 7) was taken in our experience if good quality of the first 3 core was achieved, and there was no consistent reason to proceed with sampling.

Computer-based automated estimation of breast vascularity and correlation with breast cancer in DCE-MRI images

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) with gadolinium constitutes one of the most promising protocols for boosting up the sensitivity in breast cancer detection. The aim of this study was twofold: first to design an image processing methodology to estimate the vascularity of the breast region in DCE-MRI images and second to investigate whether the differences in the composition/texture and vascularity of normal, benign and malignant breasts may serve as potential indicators regarding the presence of the disease. Clinical material comprised thirty nine cases examined on a 3.0-T MRI system (SIGNA HDx; GE Healthcare). Vessel segmentation was performed using a custom made modification of the Seeded Region Growing algorithm that was designed in order to identify pixels belonging to the breast vascular network. Two families of features were extracted: first, morphological and textural features from segmented images in order to quantify the extent and the properties of the vascular network; second, textural features from the whole breast region in order to investigate whether the nature of the disease causes statistically important changes in the texture of affected breasts. Results have indicated that: (a) the texture of vessels presents statistically significant differences (p<0.001) between normal, benign and malignant cases, (b) the texture of the whole breast region for malignant and non-malignant breasts, produced statistically significant differences (p<0.001), (c) the relative ratios of the texture between the two breasts may be used for the discrimination of non-malignant from malignant patients, and (d) an area under the receiver operating characteristic curve of 0.908 (AUC) was found when features were combined in a logistic regression prediction rule according to ROC analysis.

Detection of masses and microcalcifications in digital mammogram images using fuzzy logic

Abstract Background Detection of small breast lesions is a challenging task for radiologists. Computer aided detection (CAD) systems are implemented to aid radiologists in detecting masses and microcalcifications. This has the potential to raise the level of sensitivity in breast cancer detection. Objectives To evaluate a new system to detect suggestions of suspicious small lesions. Methods Small samples were extracted from different tissue types. Texture features were calculated, and the best features were selected using Waikato Environment for Knowledge Analysis (WEKA) software. Subsequently, 7 selected features were used to form a decision tree. To reduce false negative cases, fuzzy logic was used. In the implementation phase, input images were divided into 8 pixel ´ 8 pixel tiles. For each tile, all selected features were computed as fuzzy inputs. Results To evaluate the technique, the suggested system was applied to 326 images obtained from the National Cancer Society of Malaysia. Based on this application, results showed that the suggested system has an acceptable sensitivity of 85.6% and specificity of 90.7%. Conclusions The fuzzy system is a promising technique for early detection of breast cancer.