Emerging Breast Imaging Technologies

2018 ◽  
Author(s):  
Heidi R. Umphrey
Keyword(s):  
Breast Cancer ◽  
Breast Imaging ◽  
High Sensitivity ◽  
Molecular Techniques ◽  
Added Value ◽  
Breast Cancers ◽  
Imaging Technologies ◽  
Molecular Breast Imaging ◽  
Contrast Enhanced ◽  
Cancer Care Continuum

Emerging breast imaging technologies may provide improved care across the entire breast cancer care continuum; however, assessment of these technologies and their added value will require further development and research. Contrast-enhanced mammography was first described in 1985, utilizing digital subtraction angiography of the breast. Molecular techniques in breast imaging are expanding as advances in technology allow for decreased radiotracer dose and reveal high sensitivity for the detection of breast cancers. Molecular breast imaging (MBI) tools may have a role as we develop personalized breast imaging protocols based on risk. This chapter, appearing in the section on breast cancer overview, describes the new emerging technologies in breast imaging, including contrast-enhanced spectral mammography and molecular breast imaging.

scholarly journals Positive molecular breast imaging: challenges and problem solving with contrast-enhanced spectral mammography

2019 ◽  
Vol 12 (10) ◽  
pp. e230043
Author(s):  
Jeremy SL Ong ◽  
Felicity Whitewood ◽  
Donna B Taylor ◽  
Deepthi Dissanayake
Keyword(s):  
Problem Solving ◽  
Breast Imaging ◽  
Cross Correlation ◽  
High Sensitivity ◽  
Full Field ◽  
Molecular Breast Imaging ◽  
Full Field Digital Mammography ◽  
Contrast Enhanced ◽  
Hypervascular Lesion ◽  
Anatomical Information

Molecular breast imaging (MBI) is a relatively new technique with high sensitivity for breast cancer detection. However, because it only provides limited anatomical information, cross-correlation of MBI findings with conventional breast imaging modalities such as full field digital mammography can be challenging. We report a case of a positive MBI study in a supplemental screening setting, where cross-correlation of MBI, ultrasound, mammogram and biopsy findings was difficult. Contrast-enhanced spectral mammography (CESM) demonstrated a hypervascular lesion at the biopsy clip, helping to prove imaging/histopathological concordance. This case highlights the challenges of incorporating MBI into conventional imaging workup, as well as the use of CESM in problem solving.

scholarly journals Diagnostic Performance of MRI, Molecular Breast Imaging, and Contrast-enhanced Mammography in Women with Newly Diagnosed Breast Cancer

Radiology ◽  
2019 ◽  
Vol 293 (3) ◽  
pp. 531-540 ◽  
Author(s):  
Jules H. Sumkin ◽  
Wendie A. Berg ◽  
Gloria J. Carter ◽  
Andriy I. Bandos ◽  
Denise M. Chough ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Imaging ◽  
Diagnostic Performance ◽  
Newly Diagnosed ◽  
Molecular Breast Imaging ◽  
Contrast Enhanced

scholarly journals The Usefulness of Spectral Mammography in Surgical Planning of Breast Cancer Treatment—Analysis of 999 Patients with Primary Operable Breast Cancer

2021 ◽  
Vol 28 (4) ◽  
pp. 2548-2559
Author(s):  
Andrzej Lorek ◽  
Katarzyna Steinhof-Radwańska ◽  
Anna Barczyk-Gutkowska ◽  
Wojciech Zarębski ◽  
Piotr Paleń ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Predictive Value ◽  
Breast Imaging ◽  
Incidence Rates ◽  
Diagnostic Sensitivity ◽  
Breast Cancer Surgery ◽  
Imaging Method ◽  
Treatment Change ◽  
Contrast Enhanced ◽  
General Number

Contrast-enhanced spectral mammography (CESM) is a promising, digital breast imaging method for planning surgeries. The study aimed at comparing digital mammography (MG) with CESM as predictive factors in visualizing multifocal-multicentric cancers (MFMCC) before determining the surgery extent. We analyzed 999 patients after breast cancer surgery to compare MG and CESM in terms of detecting MFMCC. Moreover, these procedures were assessed for their conformity with postoperative histopathology (HP), calculating their sensitivity and specificity. The question was which histopathological types of breast cancer were more frequently characterized by multifocality–multicentrality in comparable techniques as regards the general number of HP-identified cancers. The analysis involved the frequency of post-CESM changes in the extent of planned surgeries. In the present study, MG revealed 48 (4.80%) while CESM 170 (17.02%) MFMCC lesions, subsequently confirmed in HP. MG had MFMCC detecting sensitivity of 38.51%, specificity 99.01%, PPV (positive predictive value) 85.71%, and NPV (negative predictive value) 84.52%. The respective values for CESM were 87.63%, 94.90%, 80.57% and 96.95%. Moreover, no statistically significant differences were found between lobular and NST cancers (27.78% vs. 21.24%) regarding MFMCC. A treatment change was required by 20.00% of the patients from breast-conserving to mastectomy, upon visualizing MFMCC in CESM. In conclusion, mammography offers insufficient diagnostic sensitivity for detecting additional cancer foci. The high diagnostic sensitivity of CESM effectively assesses breast cancer multifocality/multicentrality and significantly changes the extent of planned surgeries. The multifocality/multicentrality concerned carcinoma, lobular and invasive carcinoma of no special type (NST) cancers with similar incidence rates, which requires further confirmation.

Molecular Breast Imaging: A Scientific Review

2021 ◽  
Author(s):  
Katie N Hunt
Keyword(s):  
Breast Cancer ◽  
Breast Imaging ◽  
Breast Mri ◽  
Cancer Staging ◽  
Scientific Review ◽  
Molecular Breast Imaging ◽  
Breast Cancer Staging ◽  
Fast Learning ◽  
Technical Advances ◽  
History Of

Abstract Molecular breast imaging (MBI) is a nuclear medicine technique that has evolved considerably over the past two decades. Technical advances have allowed reductions in administered doses to the point that they are now acceptable for screening. The most common radiotracer used in MBI, 99mTc-sestamibi, has a long history of safe use. Biopsy capability has become available in recent years, with early clinical experience demonstrating technically successful biopsies of MBI-detected lesions. MBI has been shown to be an effective supplemental screening tool in women with dense breasts and is also utilized for breast cancer staging, assessment of response to neoadjuvant chemotherapy, problem solving, and as an alternative to breast MRI in women who have a contraindication to MRI. The degree of background parenchymal uptake on MBI shows promise as a tool for breast cancer risk stratification. Radiologist interpretation is guided by a validated MBI lexicon that mirrors the BI-RADS lexicon. With short interpretation times, a fast learning curve for radiologists, and a substantially lower cost than breast MRI, MBI provides many benefits in the practices in which it is utilized. This review will discuss the current state of MBI technology, clinical applications of MBI, MBI interpretation, radiation dose associated with MBI, and the future of MBI.

scholarly journals The Use of Molecular Breast Imaging to Assess Response in Women Undergoing Neoadjuvant Therapy for Breast Cancer

2012 ◽  
Vol 37 (4) ◽  
pp. 344-350 ◽  
Author(s):  
Dietlind L. Wahner-Roedler ◽  
Judy C. Boughey ◽  
Carrie B. Hruska ◽  
Beiyun Chen ◽  
Deborah J. Rhodes ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Therapy ◽  
Breast Imaging ◽  
Molecular Breast Imaging

scholarly journals The clinical impact of molecular breast imaging in women with proven invasive breast cancer scheduled for breast-conserving surgery

2018 ◽  
Vol 169 (3) ◽  
pp. 513-522 ◽  
Author(s):  
Angela Collarino ◽  
Renato A. Valdés Olmos ◽  
Lotta G. A. J. van Berkel ◽  
Peter A. Neijenhuis ◽  
Lidy M. H. Wijers ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Invasive Breast Cancer ◽  
Breast Imaging ◽  
Breast Conserving Surgery ◽  
Clinical Impact ◽  
Molecular Breast Imaging

Automatic detection of various patterns of calcification distribution on mammograms: a graph convolution network approach (Preprint)

2021 ◽  
Author(s):  
Melissa Min-Szu Yao ◽  
Hao Du ◽  
Mikael Hartman ◽  
Wing P. Chan ◽  
Mengling Feng
Keyword(s):  
Breast Cancer ◽  
Breast Imaging ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Automatic Detection ◽  
Ground Truth ◽  
Architectural Distortion ◽  
Breast Cancers ◽  
Convolutional Network ◽  
Mammographic Images

UNSTRUCTURED Purpose: To develop a novel artificial intelligence (AI) model algorithm focusing on automatic detection and classification of various patterns of calcification distribution in mammographic images using a unique graph convolution approach. Materials and methods: Images from 200 patients classified as Category 4 or 5 according to the American College of Radiology Breast Imaging Reporting and Database System, which showed calcifications according to the mammographic reports and diagnosed breast cancers. The calcification distributions were classified as either diffuse, segmental, regional, grouped, or linear. Excluded were mammograms with (1) breast cancer as a single or combined characterization such as a mass, asymmetry, or architectural distortion with or without calcifications; (2) hidden calcifications that were difficult to mark; or (3) incomplete medical records. Results: A graph convolutional network-based model was developed. 401 mammographic images from 200 cases of breast cancer were divided based on calcification distribution pattern: diffuse (n = 24), regional (n = 111), group (n = 201), linear (n = 8) or segmental (n = 57). The classification performances were measured using metrics including precision, recall, F1 score, accuracy and multi-class area under receiver operating characteristic curve. The proposed achieved precision of 0.483 ± 0.015, sensitivity of 0.606 (0.030), specificity of 0.862 ± 0.018, F1 score of 0.527 ± 0.035, accuracy of 60.642% ± 3.040% and area under the curve of 0.754 ± 0.019, finding method to be superior compared to all baseline models. The predicted linear and diffuse classifications were highly similar to the ground truth, and the predicted grouped and regional classifications were also superior compared to baseline models. Conclusion: The proposed deep neural network framework is an AI solution to automatically detect and classify calcification distribution patterns on mammographic images highly suspected of showing breast cancers. Further study of the AI model in an actual clinical setting and additional data collection will improve its performance.

scholarly journals The value of mammography in women with focal breast complaints in addition to initial targeted ultrasound

2020 ◽  
Author(s):  
L. Appelman ◽  
P. T. M. Appelman ◽  
C. C. N. Siebers ◽  
P. Bult ◽  
H. L. S. Go ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Imaging ◽  
Digital Breast Tomosynthesis ◽  
Breast Disease ◽  
Added Value ◽  
Breast Tomosynthesis ◽  
Targeted Ultrasound ◽  
Symptomatic Breast Cancer ◽  
Symptomatic Breast

Abstract Purpose To determine the added value of mammography in women with focal breast complaints and the utility of initial targeted ultrasound in this setting. Methods Women with symptomatic breast disease who were evaluated by breast imaging (mammography/digital breast tomosynthesis and ultrasound) between January 2016 and December 2016 in the Radboud University Medical Centre were included. We retrospectively collected the following data: date of birth, indication of imaging, visibility on mammography/ultrasound, whether biopsy was taken, additional findings, BI-RADS-classification, pathology and follow-up results. Results A total of 494 women were included (mean age 46.5, range 30 to 93). In 49 women (9.9%), symptomatic breast cancer was diagnosed, all visible during targeted ultrasound. The negative predictive value of targeted ultrasound was very high (99.8%). Additional findings on mammography were significantly more often malignant when the symptomatic lesion was also malignant (3.8% vs 70%, P < 0.05). In only one patient with symptoms caused by a benign finding, an incidental malignancy was detected on mammography outside the area of complaint (detection rate 2.2/1000 examinations). Conclusions The contribution of mammography for cancer detection in women with focal breast complaints is very low when targeted ultrasound is performed. Additional findings are most common in patients with symptomatic breast cancer. Our results suggest that initial targeted ultrasound is a more appropriate initial tool for the evaluation of focal breast complaints. Mammography could be performed on indication only.

scholarly journals Currently Applied Molecular Assays for Identifying ESR1 Mutations in Patients with Advanced Breast Cancer

2020 ◽  
Vol 21 (22) ◽  
pp. 8807
Author(s):  
Nuri Lee ◽  
Min-Jeong Park ◽  
Wonkeun Song ◽  
Kibum Jeon ◽  
Seri Jeong
Keyword(s):  
Breast Cancer ◽  
Advanced Breast Cancer ◽  
Endocrine Therapy ◽  
High Sensitivity ◽  
Digital Pcr ◽  
Advanced Breast ◽  
Sample Type ◽  
Breast Cancers ◽  
Esr1 Mutations ◽  
Next Generation Sequencing Ngs

Approximately 70% of breast cancers, the leading cause of cancer-related mortality worldwide, are positive for the estrogen receptor (ER). Treatment of patients with luminal subtypes is mainly based on endocrine therapy. However, ER positivity is reduced and ESR1 mutations play an important role in resistance to endocrine therapy, leading to advanced breast cancer. Various methodologies for the detection of ESR1 mutations have been developed, and the most commonly used method is next-generation sequencing (NGS)-based assays (50.0%) followed by droplet digital PCR (ddPCR) (45.5%). Regarding the sample type, tissue (50.0%) was more frequently used than plasma (27.3%). However, plasma (46.2%) became the most used method in 2016–2019, in contrast to 2012–2015 (22.2%). In 2016–2019, ddPCR (61.5%), rather than NGS (30.8%), became a more popular method than it was in 2012–2015. The easy accessibility, non-invasiveness, and demonstrated usefulness with high sensitivity of ddPCR using plasma have changed the trends. When using these assays, there should be a comprehensive understanding of the principles, advantages, vulnerability, and precautions for interpretation. In the future, advanced NGS platforms and modified ddPCR will benefit patients by facilitating treatment decisions efficiently based on information regarding ESR1 mutations.

Advanced Imaging Techniques for the Detection of Breast Cancer

2012 ◽  
pp. 65-69 ◽  
Author(s):  
Maxine Jochelson
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Breast Imaging ◽  
Early Stage ◽  
Imaging Techniques ◽  
Breast Cancer Mortality ◽  
Digital Breast Tomosynthesis ◽  
Ct Scanning ◽  
High Risk Women ◽  
Contrast Enhanced

Overview: Mammography is the only breast imaging examination that has been shown to reduce breast cancer mortality. Population-based sensitivity is 75% to 80%, but sensitivity in high-risk women with dense breasts is only in the range of 50%. Breast ultrasound and contrast-enhanced breast magnetic resonance imaging (MRI) have become additional standard modalities used in the diagnosis of breast cancer. In high-risk women, ultrasound is known to detect approximately four additional cancers per 1,000 women. MRI is exquisitely sensitive for the detection of breast cancer. In high-risk women, it finds an additional four to five cancers per 100 women. However, both ultrasound and MRI are also known to lead to a large number of additional benign biopsies and short-term follow-up examinations. Many new breast imaging tools have improved and are being developed to improve on our current ability to diagnose early-stage breast cancer. These can be divided into two groups. The first group is those that are advances in current techniques, which include digital breast tomosynthesis and contrast-enhanced mammography and ultrasound with elastography or microbubbles. The other group includes new breast imaging platforms such as breast computed tomography (CT) scanning and radionuclide breast imaging. These are exciting advances. However, in this era of cost and radiation containment, it is imperative to look at all of them objectively to see which will provide clinically relevant additional information.

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