This paper summarizes information about breast MRI to be provided to women and referring physicians. After listing contraindications, procedure details are described, stressing the need for correct ...scheduling and not moving during the examination. The structured report including BI-RADS® categories and further actions after a breast MRI examination are discussed. Breast MRI is a very sensitive modality, significantly improving screening in high-risk women. It also has a role in clinical diagnosis, problem solving, and staging, impacting on patient management. However, it is not a perfect test, and occasionally breast cancers can be missed. Therefore, clinical and other imaging findings (from mammography/ultrasound) should also be considered. Conversely, MRI may detect lesions not visible on other imaging modalities turning out to be benign (false positives). These risks should be discussed with women before a breast MRI is requested/performed. Because breast MRI drawbacks depend upon the indication for the examination, basic information for the most important breast MRI indications is presented. Seventeen notes and five frequently asked questions formulated for use as direct communication to women are provided. The text was reviewed by
Europa Donna–The European Breast Cancer Coalition
to ensure that it can be easily understood by women undergoing MRI.
Key Points
•
Information on breast MRI concerns advantages/disadvantages and preparation to the examination
•
Claustrophobia, implantable devices, allergic predisposition, and renal function should be checked
•
Before menopause, scheduling on day 7–14 of the cycle is preferred
•
During the examination, it is highly important that the patient keeps still
•
Availability of prior examinations improves accuracy of breast MRI interpretation
Background
Patient motion can degrade image quality of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) due to subtraction artifacts. By objectively and subjectively assessing the ...impact of principal component analysis (PCA)-based registration on pretreatment DCE-MRIs of breast cancer patients, we aim to validate four-dimensional registration for DCE breast MRI.
Results
After applying a four-dimensional, PCA-based registration algorithm to 154 pretreatment DCE-MRIs of histopathologically well-described breast cancer patients, we quantitatively determined image quality in unregistered and registered images. For subjective assessment, we ranked motion severity in a clinical reading setting according to four motion categories (0: no motion, 1: mild motion, 2: moderate motion, 3: severe motion with nondiagnostic image quality). The median of images with either moderate or severe motion (median category 2, IQR 0) was reassigned to motion category 1 (IQR 0) after registration. Motion category and motion reduction by registration were correlated (Spearman’s rho: 0.83,
p
< 0.001). For objective assessment, we performed perfusion model fitting using the extended Tofts model and calculated its volume transfer coefficient
K
trans
as surrogate parameter for motion artifacts. Mean
K
trans
decreased from 0.103 (± 0.077) before registration to 0.097 (± 0.070) after registration (
p
< 0.001). Uncertainty in perfusion quantification was reduced by 7.4% after registration (± 15.5,
p
< 0.001).
Conclusions
Four-dimensional, PCA-based image registration improves image quality of breast DCE-MRI by correcting for motion artifacts in subtraction images and reduces uncertainty in quantitative perfusion modeling. The improvement is most pronounced when moderate-to-severe motion artifacts are present.
Key points
PCA-based registration improved motion-related image quality according to subjective and objective criteria.
The impact of registration was positively correlated with motion severity.
Registration improved perfusion quantification by reducing model-related uncertainty.
Abstract
An increasing array of tools is being developed using artificial intelligence (AI) and machine learning (ML) for cancer imaging. The development of an optimal tool requires multidisciplinary ...engagement to ensure that the appropriate use case is met, as well as to undertake robust development and testing prior to its adoption into healthcare systems. This multidisciplinary review highlights key developments in the field. We discuss the challenges and opportunities of AI and ML in cancer imaging; considerations for the development of algorithms into tools that can be widely used and disseminated; and the development of the ecosystem needed to promote growth of AI and ML in cancer imaging.
To estimate the risk for contralateral breast cancer in members of BRCA1- and BRCA2-positive families and to determine predictive risk factors.
A retrospective, multicenter, cohort study was ...performed from 1996 until 2008 and comprised 2,020 women with unilateral breast cancer (index patients, n = 978; relatives, n = 1.42) from 978 families who had a BRCA1 or BRCA2 mutation. Cox regression analysis was applied to assess the association of age at first breast cancer with time from first to contralateral breast cancer, stratified by the affected BRCA gene.
The cumulative risk for contralateral breast cancer 25 years after first breast cancer was 47.4% (95% CI, 38.8% to 56.0%) for patients from families with BRCA1 or BRCA2 mutations. Members of families with BRCA1 mutations had a 1.6-fold (95% CI, 1.2-fold to 2.3-fold) higher risk of contralateral breast cancer than members of families with BRCA2 mutations. Younger age at first breast cancer was associated with a significantly higher risk of contralateral breast cancer in patients with BRCA1 mutation, and a trend was observed in patients with BRCA2 mutation. After 25 years, 62.9% (95% CI, 50.4% to 75.4%) of patients with BRCA1 mutation who were younger than 40 years of age at first breast cancer developed contralateral breast cancer, compared with only 19.6% (95% CI, 5.3% to 33.9%) of those who were older than 50 years of age at first breast cancer.
Contralateral breast cancer risk depends on age at first breast cancer and on the affected BRCA gene, and this risk should be considered in treatment planning.
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast is being used increasingly in the detection and diagnosis of breast cancer as a complementary modality to mammography and ...sonography. Although the potential diagnostic value of kinetic curves in DCE-MRI is established, the method for generating kinetic curves is not standardized. The inherent reason that curve identification is needed is that the uptake of contrast agent in a breast lesion is often heterogeneous, especially in malignant lesions. It is accepted that manual region of interest selection in 4D breast magnetic resonance (MR) images to generate the kinetic curve is a time-consuming process and suffers from significant inter- and intraobserver variability. We investigated and developed a fuzzy c-means (FCM) clustering-based technique for automatically identifying characteristic kinetic curves from breast lesions in DCE-MRI of the breast. Dynamic contrast-enhanced MR images were obtained using a T1-weighted 3D spoiled gradient echo sequence with Gd-DTPA dose of
0.2
mmol
∕
kg
and temporal resolution of
69
s
. FCM clustering was applied to automatically partition the signal-time curves in a segmented 3D breast lesion into a number of classes (i.e., prototypic curves). The prototypic curve with the highest initial enhancement was selected as the representative characteristic kinetic curve (CKC) of the lesion. Four features were then extracted from each characteristic kinetic curve to depict the maximum contrast enhancement, time to peak, uptake rate, and washout rate of the lesion kinetics. The performance of the kinetic features in the task of distinguishing between benign and malignant lesions was assessed by receiver operating characteristic analysis. With a database of 121 breast lesions (77 malignant and 44 benign cases), the classification performance of the FCM-identified CKCs was found to be better than that from the curves obtained by averaging over the entire lesion and similar to kinetic curves generated from regions drawn within the lesion by a radiologist experienced in breast MRI.
This article summarises the information that should be provided to women and referring physicians about breast ultrasound (US). After explaining the physical principles, technical procedure and ...safety of US, information is given about its ability to make a correct diagnosis, depending on the setting in which it is applied. The following
definite indications
for breast US in female subjects are proposed: palpable lump; axillary adenopathy; first diagnostic approach for clinical abnormalities under 40 and in pregnant or lactating women; suspicious abnormalities at mammography or magnetic resonance imaging (MRI); suspicious nipple discharge; recent nipple inversion; skin retraction; breast inflammation; abnormalities in the area of the surgical scar after breast conserving surgery or mastectomy; abnormalities in the presence of breast implants; screening high-risk women, especially when MRI is not performed; loco-regional staging of a known breast cancer, when MRI is not performed; guidance for percutaneous interventions (needle biopsy, pre-surgical localisation, fluid collection drainage); monitoring patients with breast cancer receiving neo-adjuvant therapy, when MRI is not performed.
Possible indications
such as supplemental screening after mammography for women aged 40–74 with dense breasts are also listed. Moreover,
inappropriate indications
include screening for breast cancer as a stand-alone alternative to mammography. The structure and organisation of the breast US report and of classification systems such as the BI-RADS and consequent management recommendations are illustrated. Information about additional or new US technologies (colour-Doppler, elastography, and automated whole breast US) is also provided. Finally, five frequently asked questions are answered.
Teaching Points
• US is an established tool for suspected cancers at all ages and also the method of choice under 40.
• For US-visible suspicious lesions, US-guided biopsy is preferred, even for palpable findings.
• High-risk women can be screened with US, especially when MRI cannot be performed.
• Supplemental US increases cancer detection but also false positives, biopsy rate and follow-up exams.
• Breast US is inappropriate as a stand-alone screening method.
Abstract Purpose The goal of this prospective study was to evaluate the possible diagnostic benefits of contrast-enhanced digital mammography (CEDM) over conventional mammography. Materials and ...methods Our analysis included data from 70 patients with a total of 80 lesions (30 malignant and 50 benign). A series of contrast-enhanced images was acquired from each patient using a modified imaging system (GE Senographe 2000D with copper filter) suitable for displaying iodine contrast medium. After the mask image had been taken, the contrast medium was administered using a dosage of 1 ml/kg body weight at a rate of 4 ml/s. Three contrast-enhanced images in the cranio-caudal projection plane were then captured at intervals of 60 s. The mask image was logarithmically subtracted from the contrast-enhanced images. We performed a ROC analysis of diagnostic quality with three readers. Results On average, 5.66 more malignant lesions were detected with the addition of digital dynamic contrast mammography versus conventional mammography alone. The sensitivity was increased from an average of 0.43 in conventional mammography to an average of 0.62 with contrast mammography. Even in dense breast parenchyma, the sensitivity increased from an average of 0.35–0.59. In the multi-reader-ROC analyses of all readers, the differences in the AUC with p = 0.02 (BI-RADS) proved statistically significant in all cases. The Wilcoxon test showed that Readers I and II primarily used the CEDM to upgrade enhancing lesions to a higher BI-RADS category or a higher probability of malignancy. These two readers benefited most from the CEDM in the ROC analysis. Conclusion Overall, we conclude that the addition of dynamic digital subtraction mammography to conventional mammography can significantly improve diagnostic quality. The increased sensitivity is particularly pronounced in the case of dense breast tissue.
The advantages of breast MRI using contrast agent Gd-DTPA in the diagnosis of breast cancer have been well established. The variation of interpretation criteria and absence of interpretation ...guidelines, however, is a major obstacle for applications of MRI in the routine clinical practice of breast imaging. Our study aims to increase the objectivity and reproducibility of breast MRI interpretation by developing an automated interpretation approach for ultimate use in computer-aided diagnosis. The database in this study contains 121 cases: 77 malignant and 44 benign masses as revealed by biopsy. Images were obtained using a T1-weighted 3D spoiled gradient echo sequence. After the acquisition of the precontrast series, Gd-DTPA contrast agent was injected intravenously by power injection with a dose of 0.2 mmol/kg. Five postcontrast series were then taken with a time interval of 60 s. Each series contained 64 coronal slices with a matrix of
128×256
pixels
and an in-plane resolution of
1.25×1.25
mm
2
.
Slice thickness ranged from 2 to 3 mm depending on breast size. The lesions were delineated by an experienced radiologist as well as independently by computer using an automatic volume-growing algorithm. Fourteen features that were extracted automatically from the lesions could be grouped into three categories based on (I) morphology, (II) enhancement kinetics, and (III) time course of enhancement-variation over the lesion. A stepwise feature selection procedure was employed to select an effective subset of features, which were then combined by linear discriminant analysis (LDA) into a discriminant score, related to the likelihood of malignancy. The classification performances of individual features and the combined discriminant score were evaluated with receiver operating characteristic (ROC) analysis. With the radiologist-delineated lesion contours, stepwise feature selection yielded four features and an
A
z
value of 0.80 for the LDA in leave-one-out cross-validation testing. With the computer-segmented lesion volumes, it yielded six features and an
A
z
value of 0.86 for the LDA in the leave-one-out testing.
Background: Primary prevention and early detection of hereditary breast cancer has been one of the main topics of breast cancer research in recent decades. The knowledge of risk factors for breast ...cancer has been increasing continuously just like the recommendations for risk management. Pathogenic germline variants (mutations, class 4/5) of risk genes are significant susceptibility factors in healthy individuals. At the same time, germline mutations serve as biomarkers for targeted therapy in breast cancer treatment. Therefore, management of healthy mutation carriers to enable primary prevention is in the focus as much as the consideration of pathogenic germline variants for therapeutic decisions. Since 1996, the German Consortium has provided quality-assured care for counselees and patients with familial burden of breast and ovarian cancer. Summary: Currently, there are 23 university centers with over 100 cooperating DKG-certified breast and gynecological cancer centers. These centers provide standardized, evidence-based, and knowledge-generating care, which includes aspects of primary as well as secondary and tertiary prevention. An important aspect of quality assurance and development was the inclusion of the HBOC centers in the certification system of the German Cancer Society (GCS). Since 2020, the centers have been regularly audited and their quality standards continuously reviewed according to quality indicators adapted to the current state of research. The standard of care at GC-HBOC’ centers involves the evaluation as well as evolution of various aspects of care like inclusion criteria, identification of new risk genes, management of variants of unknown significance (class 3), evaluation of risk-reducing options, intensified surveillance, and communication of risks. Among these, the possibility of intensified surveillance in the GC-HBOC for early detection of breast cancer is an important component of individual risk management for many counselees. As has been shown in recent years, in carriers of pathogenic variants in high-risk genes, this approach enables the detection of breast cancer at very early, more favorable stages although no reduction of mortality has been demonstrated yet. The key component of the intensified surveillance is annual contrast-enhanced breast MRI, supplemented by up to biannual breast ultrasound and mammography usually starting at age 40. Key Messages: Apart from early detection, the central goal of care is the prevention of cancer. By utilizing individualized risk calculation, the optimal timeframe for risk-reducing surgery can be estimated, and counselees can be supported in reaching preference-sensitive decisions.
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