Contrast-enhanced Breast Magnetic Resonance Imaging Research Articles

Detection and Diagnosis of Breast Cancer Using Artificial Intelligence Based assessment of Maximum Intensity Projection Dynamic Contrast-Enhanced Magnetic Resonance Images.

We aimed to evaluate an artificial intelligence (AI) system that can detect and diagnose lesions of maximum intensity projection (MIP) in dynamic contrast-enhanced (DCE) breast magnetic resonance imaging (MRI). We retrospectively gathered MIPs of DCE breast MRI for training and validation data from 30 and 7 normal individuals, 49 and 20 benign cases, and 135 and 45 malignant cases, respectively. Breast lesions were indicated with a bounding box and labeled as benign or malignant by a radiologist, while the AI system was trained to detect and calculate possibilities of malignancy using RetinaNet. The AI system was analyzed using test sets of 13 normal, 20 benign, and 52 malignant cases. Four human readers also scored these test data with and without the assistance of the AI system for the possibility of a malignancy in each breast. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were 0.926, 0.828, and 0.925 for the AI system; 0.847, 0.841, and 0.884 for human readers without AI; and 0.889, 0.823, and 0.899 for human readers with AI using a cutoff value of 2%, respectively. The AI system showed better diagnostic performance compared to the human readers (p = 0.002), and because of the increased performance of human readers with the assistance of the AI system, the AUC of human readers was significantly higher with than without the AI system (p = 0.039). Our AI system showed a high performance ability in detecting and diagnosing lesions in MIPs of DCE breast MRI and increased the diagnostic performance of human readers.

Side of contrast injection and breast size correlate with motion artifacts grade and image quality on breast MRI.

Motion is a relevant cause of artifacts in breast magnetic resonance imaging (MRI), potentially degrading image quality, even with optimized protocols. To investigate the causes of motion artifacts (MA) impacting on image quality (IQ) of contrast-enhanced breast MRI. Retrospective two-center study on consecutive 1.5-T contrast-enhanced breast MRI, independently reviewed by two radiologists on first subtracted and maximum intensity projection images to define the side most affected by MA. IQ was scored as 1 (optimal), 2 (reduced, but without reduction of diagnostic power), or 3 (reduced, with reduced diagnostic power). Correlations with injection side, breast size (A/B vs. C/D cups), patient age, clinical indication, and MRI scanner/protocol were assessed using χ2 and Fisher's exact statistics. In total, 237 examinations were included, with right injection performed in 124 (52%) and left in 113 (48%). MA were more frequent on the side ipsilateral to the injection (144/237, 61%, 95% confidence interval [CI] 54-67%) than on the contralateral (93/237, 95% CI 33-46%) (P < 0.001); IQ was scored 1 in 154/237 (65%), 2 in 63/237 (27%), and 3 in 20/237 (8%) examinations; patients with A/B cups showed higher IQ score than patients with C/D cups (scores 1, 2, and 3: 54% vs. 70%; 29% vs. 25%; 17% vs. 5%, respectively, P = 0.002). No significant correlations were found for MA (P≥0.106) or IQ (P ≥ 0.318) between ipsi- or contralateral injection and right/left injection, breast size, age, indication, or scanner/protocol. MA were more frequent in breasts ipsilateral to contrast injection and showed a reduced IQ for small breasts.

Molecular Subtypes Recognition of Breast Cancer in Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging Phenotypes from Radiomics Data.

Background and Objective Breast cancer is a major cause of mortality among women if not treated in early stages. Recognizing molecular markers from DCE-MRI directly to distinguish the four molecular subtypes without invasive biopsy is helpful for guiding treatment plans for breast cancer, which provides a fast way to consequential treatment plan decision in early time and best opportunity for patients. Methods This study presents an approach of molecular subtypes recognition from breast cancer image phenotypes by radiomics. An improved region growth algorithm with dynamic threshold without user interaction is proposed for cancer lesion segmentation, which gives the precise border of lesion other than area with background. The lesions are extracted automatically based on radiologists' annotation which guarantees the lesion is segmented correctly. Various features are extracted on lesions data including texture, morphology, dynamic kinetics, and statistics features carried out on a large patient cohort, which are used to validate the relationship between image phenotypes and the molecular subtypes. A new algorithm of multimodel-based recursive feature elimination is applied on the radiomics data generated by the feature extraction process. This method obtains the feature subset with stable performance for different classification models, and the gradient boosting decision tree model gets the best results of both classification performance and imbalance performance on molecular subtypes. Result From the experimental results, 69 optimal features from 143 original features are found by the multimodel-based recursive feature elimination algorithms and the gradient boosting decision tree classifier obtains a good performance with accuracy 0.87, precise 0.88, recall 0.87, and F1-score 0.87. The dataset with 637 patients in this paper has serious imbalance problem on different molecular subtypes, and the the robust features that are generated by multimodel-based recursive feature eliminiation algorithm make the gradient boosting decision tree classifier have good behaviors. The recognition precision for the four molecular subtypes of luminal A, luminal B, HER-2, and basal-like are 0.91, 0.89, 0.83, and 0.87, respectively. Conclusions The improved lesion segmentation method gives more precise lesion edge, which not only saves the time of automatic extraction of lesion region of interest without threshold setting for each case, but also prevents the segmentation error by manual and prejudice from different radiologists. The feature selection algorithm of multimodel-based recursive feature elimination has the ability to find robust and optimal features that distinguish the four molecular subtypes from image phenotypes. The gradient boosting decision tree classifier rather plays a main role in recognition than other models used in this paper.

Contrast agent-free breast MRI : Advantages and potential disadvantages

Contrast-enhanced breast magnetic resonance imaging (MRI) is the most sensitive method for detection of breast cancer. The further spread of breast MRI is limited by the complicated examination procedure and the need for intravenously administered contrast media. Can diffusion-weighted imaging (DWI) replace contrast-enhanced sequences to achieve an unenhanced breast MRI examination? Narrative review and meta-analytic assessment of previously published studies. DWI can visualize breast lesions and distinguish benign from malignant findings. It is thus avalid alternative to contrast-enhanced sequences. As an additional technique, the use of DWI can reduce the numbers of unnecessary breast biopsies. The lack of robustness leading to variable sensitivity that is currently lower than that of contrast-enhanced breast MRI is adisadvantage of DWI. Presently, DWI can be recommended as an integral part of clinical breast MRI protocols. The application as astand-alone technique within unenhanced protocols is still under evaluation.

Multireader Study on the Diagnostic Accuracy of Ultrafast Breast Magnetic Resonance Imaging for Breast Cancer Screening.

Breast cancer screening using magnetic resonance imaging (MRI) has limited accessibility due to high costs of breast MRI. Ultrafast dynamic contrast-enhanced breast MRI can be acquired within 2 minutes. We aimed to assess whether screening performance of breast radiologist using an ultrafast breast MRI-only screening protocol is as good as performance using a full multiparametric diagnostic MRI protocol (FDP). The institutional review board approved this study, and waived the need for informed consent. Between January 2012 and June 2014, 1791 consecutive breast cancer screening examinations from 954 women with a lifetime risk of more than 20% were prospectively collected. All women were scanned using a 3 T protocol interleaving ultrafast breast MRI acquisitions in a full multiparametric diagnostic MRI protocol consisting of standard dynamic contrast-enhanced sequences, diffusion-weighted imaging, and T2-weighted imaging. Subsequently, a case set was created including all biopsied screen-detected lesions in this period (31 malignant and 54 benign) and 116 randomly selected normal cases with more than 2 years of follow-up. Prior examinations were included when available. Seven dedicated breast radiologists read all 201 examinations and 153 available priors once using the FDP and once using ultrafast breast MRI only in 2 counterbalanced and crossed-over reading sessions. For reading the FDP versus ultrafast breast MRI alone, sensitivity was 0.86 (95% confidence interval [CI], 0.81-0.90) versus 0.84 (95% CI, 0.78-0.88) (P = 0.50), specificity was 0.76 (95% CI, 0.74-0.79) versus 0.82 (95% CI, 0.79-0.84) (P = 0.002), positive predictive value was 0.40 (95% CI, 0.36-0.45) versus 0.45 (95% CI, 0.41-0.50) (P = 0.14), and area under the receiver operating characteristics curve was 0.89 (95% CI, 0.82-0.96) versus 0.89 (95% CI, 0.82-0.96) (P = 0.83). Ultrafast breast MRI reading was 22.8% faster than reading FDP (P < 0.001). Interreader agreement is significantly better for ultrafast breast MRI (κ = 0.730; 95% CI, 0.699-0.761) than for the FDP (κ = 0.665; 95% CI, 0.633-0.696). Breast MRI screening using only an ultrafast breast MRI protocol is noninferior to screening with an FDP and may result in significantly higher screening specificity and shorter reading time.

Ultrafast Dynamic Contrast-Enhanced Breast MRI: Kinetic Curve Assessment Using Empirical Mathematical Model Validated with Histological Microvessel Density

To evaluate whether parameters from empirical mathematical model (EMM) for ultrafast dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) correlate with histological microvessel density (MVD) in invasive breast cancer. Ninety-eight consecutive patients with invasive breast cancer underwent an institutional review board-approved ultrafast DCE-MRI including a pre- and 18 postcontrast whole breast ultrafast scans (3 seconds) followed by four standard scans (60 seconds) using a 3T system. Region of interest was placed within each lesion where the highest signal increase was observed on ultrafast DCE-MRI, and the increase rate of enhancement was calculated as follows: ΔS = (SIpost - SIpre)/SIpre. The kinetic curve obtained from ultrafast DCE-MRI was analyzed using a truncated EMM: ΔS(t) = A(1 - e-αt), where A is the upper limit of the signal intensity, α (min-1) is the rate of signal increase. The initial slope of the kinetic curve is given by Aα. Initial area under curve (AUC30) and time of initial enhancement was calculated. From the standard DCE-MRI, the initial enhancement rate (IER) and the signal enhancement ratio (SER) were calculated as follows: IER = (SIearly - SIpre)/SIpre, SER = (SIearly - SIpre)/(SIdelayed - SIpre). The parameters were compared to MVD obtained from surgical specimens. A, α, Aα, AUC30, and time of initial enhancement significantly correlated with MVD (r = 0.29, 0.40, 0.51, 0.43, and -0.32 with p = 0.0027, p < 0.0001, p < 0.0001, p < 0.0001, and p = 0.0012, respectively), whereas IER and SER from standard DCE-MRI did not. The parameters of the EMM, especially the initial slope or Aα, for ultrafast DCE-MRI correlated with MVD in invasive breast cancer.

MRI background parenchymal enhancement, breast density and serum hormones in postmenopausal women.

Background parenchymal enhancement (BPE) is the degree to which normal breast tissue enhances on contrast‐enhanced magnetic resonance imaging (MRI). MRI‐density is a volumetric measure of breast density that is highly correlated with mammographic density, an established breast cancer risk factor. Endogenous estrogen concentrations are positively associated with postmenopausal breast cancer risk and BPE has been shown to be sensitive to hormonal exposures. The objective of our study was to examine the relationship between BPE and MRI‐density and serum hormone concentrations in postmenopausal women. This was a study of cancer‐free postmenopausal women undergoing contrast‐enhanced breast MRI (N = 118). At the time of MRI all women completed a self‐administered questionnaire and blood samples were collected for hormone analyses. Serum concentrations of estrone (E1), estradiol (E2) and bioavailable E2 were examined by category of BPE and MRI‐density. Compared to women with “minimal” BPE, those who had “marked” BPE had significantly higher serum concentrations of E1, E2 and bioavailable E2 (90% increase, p trend across all categories = 0.001; 150% increase, p trend = 0.001; and 158% increase, p trend = 0.001, respectively). These associations were only affected to a minor extent by adjustment for BMI and other variables. After adjustment for BMI, no significant associations between MRI‐density and serum E1, E2 and bioavailable E2 were observed. Serum estrogen concentrations were significantly positively associated with BPE. Our study provides further evidence of the hormone‐sensitive nature of BPE, indicating a potential role for BPE as an imaging marker of endogenous and exogenous hormonal exposures in the breast.

Abstract P4-02-10: Breast cancer surveillance in high-risk women with dynamic contrast-enhanced magnetic resonance imaging every 6 months: Results from a single institution study

Abstract Purpose: To develop a novel approach for early detection of breast cancer and examine molecular features of screen detected cancers in prospectively ascertained high-risk women undergoing semi-annual dynamic contrast-enhanced breast magnetic resonance imaging (DCE-MRI) for women at high genetic risk. Background: Women with a personal or family history of breast cancer and genetic mutation carriers of BRCA1 and BRCA2 have a higher than normal risk of breast cancer. An intensified screening surveillance regimen is an early detection strategy in high-risk women. The American Cancer Society recommends annual DCE-MRI in addition to annual mammogram based off several pivotal screening studies that demonstrated improved sensitivity and cancer detection rates and decreased interval cancer rates with the addition of annual DCE-MRI. Questions remain regarding the optimal screening modality and interval regimen in these high-risk women. Methods: Between 2004 and 2016, we assembled a prospective cohort of high-risk women undergoing semi-annual DCE-MRI and annual mammography. To be eligible, women had a lifetime breast cancer risk &amp;gt;20% and/or tested positive for a pathogenic mutation using a cancer gene panel including BRCA1, BRCA2, CDH1, PALB2, CHEK2 and other cancer susceptibility genes in the DNA repair pathway. Somatic mutation events in screen-detected tumors were investigated using UW-OncoPlex cancer gene panel using DNA extracted from FFPE shavings. Results: 295 women were recruited to the study; 44% of the study participants had pathogenic mutations in BRCA1 or BRCA2 genes. At a median follow-up of 3.3 years (range 0-12 years), 3 DCIS and 13 early stage invasive breast cancers were detected, of which 14 occurred in subjects with identifiable pathogenic mutations (11 BRCA1, 2 BRCA2, 1 CDH1). The incidence rate is 1.3% in all subjects, but 3.5 % per year in BRCA1 carriers. DCE-MRI identified all 13 invasive cancers at a mean size of 0.61 cm (range 0.1-1.0 cm); none had lymph node metastasis. No interval cancers occurred. In addition, 7 of the breast cancers were detected on DCE-MRI imaging obtained at the 6 months screening interval; they would be interval cancers if only annual screening were implemented. There was very little DNA for somatic mutation testing in the majority of cases. However, as expected, there was heterogeneity in the spectrum of mutations but the most commonly somatically mutated gene in the early cancers was TP53. Conclusions: DCE-MRI every 6 months performed well for early detection of invasive breast cancer in high-risk women, accomplishing the ultimate goal of breast cancer screening—detecting node-negative, invasive tumors less than 1 cm. Semi-annual DCE-MRI performed especially well in BRCA1 mutation carriers at risk for the most aggressive subtype of breast cancer. Further interventional studies evaluating this novel screening approach are warranted to personalize breast cancer risk assessment and prevention. Citation Format: Whitaker K, Guindalini R, Abe H, Sheeth D, Huo D, Hong S, Churpek J, Verp M, Obeid E, Zheng Y, Amico A, Yoshimatsu T, Olopade O. Breast cancer surveillance in high-risk women with dynamic contrast-enhanced magnetic resonance imaging every 6 months: Results from a single institution study [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P4-02-10.

Clinical and Pathologic Features of Clinically Occult Synchronous Bilateral Breast Cancers

PurposeTo investigate clinicopathologic breast cancer characteristics associated with the identification of synchronous bilateral breast cancer (SBBC) on dynamic contrast-enhanced breast magnetic resonance imaging. MethodsWe performed a retrospective review of 311 consecutive patients newly diagnosed with breast cancer who underwent diagnostic mammography, ultrasonography, and dynamic contrast-enhanced breast magnetic resonance imaging (DCE-MRI) at our institution. Tumor histology, grade, biomarker status (estrogen receptor, progesterone receptor, and HER2), TNM staging, and unifocal or multifocal/multicentric status were compared between the index tumors in the unilateral disease and the SBBC groups, as well as between the index tumors in the unilateral disease group and the synchronous contralateral tumors (SCT) in the SBBC group, using the Fisher exact test. ResultsA total of 326 cancers in 311 patients were reviewed. Fifteen (4.8%) patients were diagnosed with SBBC. The index tumors in patients with SBBC were more frequently lower T stage (p = 0.007), lower grade (p = 0.04), and multifocal/multicentric (p = 0.004) compared with the index tumors in the unilateral group. Biomarkers, N status, and M status did not significantly differ between the index tumors in both groups. ConclusionsSBBC was more likely to be identified in women with lower T stage, lower tumor grade and multifocal/multicentric tumors. Multimodality imaging including DCE-MRI is essential in detection and diagnosis of SBBC.

Contrast Enhanced Spectral Mammography: A Review

Contrast-enhanced spectral mammography (CESM) provides low-energy 2D mammographic images comparable to standard digital mammography and a post-contrast recombined image to assess tumor neovascularity similar to magnetic resonance imaging (MRI). The utilization of CESM in the United States is currently low but could increase rapidly given many potential indications for clinical use. This article discusses historical background and literature review of indications and diagnostic accuracy of CESM to date. CESM is a growing technique for breast cancer detection and diagnosis that has levels of sensitivity and specificity on par with contrast-enhanced breast MRI. Because of its similar performance and ease of implementation, CESM is being adopted for multiple indications previously reserved for MRI, such as problem-solving, disease extent in newly diagnosed patients, and evaluating the treatment response of neoadjuvant chemotherapy.

Newly Diagnosed Breast Cancer: Comparison of Contrast-enhanced Spectral Mammography and Breast MR Imaging in the Evaluation of Extent of Disease.

Purpose To compare the diagnostic performances of contrast material-enhanced spectral mammography and breast magnetic resonance (MR) imaging in the detection of index and secondary cancers in women with newly diagnosed breast cancer by using histologic or imaging follow-up as the standard of reference. Materials and Methods This institutional review board-approved, HIPAA-compliant, retrospective study included 52 women who underwent breast MR imaging and contrast-enhanced spectral mammography for newly diagnosed unilateral breast cancer between March 2014 and October 2015. Of those 52 patients, 46 were referred for contrast-enhanced spectral mammography and targeted ultrasonography because they had additional suspicious lesions at MR imaging. In six of the 52 patients, breast cancer had been diagnosed at an outside institution. These patients were referred for contrast-enhanced spectral mammography and targeted US as part of diagnostic imaging. Images from contrast-enhanced spectral mammography were analyzed by two fellowship-trained breast imagers with 2.5 years of experience with contrast-enhanced spectral mammography. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value were calculated for both imaging modalities and compared by using the Bennett statistic. Results Fifty-two women with 120 breast lesions were included for analysis (mean age, 50 years; range, 29-73 years). Contrast-enhanced spectral mammography had similar sensitivity to MR imaging (94% [66 of 70 lesions] vs 99% [69 of 70 lesions]), a significantly higher PPV than MR imaging (93% [66 of 71 lesions] vs 60% [69 of 115 lesions]), and fewer false-positive findings than MR imaging (five vs 45) (P < .001 for all results). In addition, contrast-enhanced spectral mammography depicted 11 of the 11 secondary cancers (100%) and MR imaging depicted 10 (91%). Conclusion Contrast-enhanced spectral mammography is potentially as sensitive as MR imaging in the evaluation of extent of disease in newly diagnosed breast cancer, with a higher PPV. © RSNA, 2017.

Practical Considerations for the Use of Breast MRI for Breast Cancer Evaluation in the Preoperative Setting

Preoperative contrast-enhanced (CE) breast magnetic resonance imaging (MRI) remains controversial in the newly diagnosed breast cancer patient. Additional lesions are frequently discovered in these patients with CE breast MRI. As staging and treatment planning evolve to include more information on tumor biology and aggression, so should our consideration of extent of disease. Directing CE breast MRI to those patients most likely to have additional disease may be beneficial. We sought to develop practical guidance for the use of preoperative CE breast MRI in the newly diagnosed breast cancer patient based on recent scientific data. Our review suggests several populations for whom preoperative breast MRI is most likely to find additional disease beyond that seen on conventional imaging. These can be viewed in three categories: (1) tumor biology-patients with invasive lobular carcinoma or aggressive tumors such as triple negative breast cancer (estrogen receptor negative, progesterone receptor negative, and human epidermal growth factor receptor 2 (HER2) negative) and HER2 positive tumors; (2) patient characteristics-dense breast tissue or younger age, especially those age <60; and (3) clinical scenarios-patients with more sonographic disease than expected or those who are node positive at initial diagnosis. Focusing breast MRI on patients with any of the aforementioned characteristics may help utilize preoperative breast MRI where it is likely to have the most impact.

Abstract P3-02-12: Impact of magnetic resonance imaging on conversion from wide local excision to mastectomy in patients with ductal carcinoma in situ: First results from the ECOG-ACRIN 4112 prospective study

Abstract Purpose: To estimate the proportion of patients with ductal carcinoma in situ (DCIS) judged to be candidates for wide local excision (WLE) based on mammography (+/- sonography) and clinical exam who: (A) convert from WLE to mastectomy as the first surgical procedure based on magnetic resonance imaging (MRI) findings, and (B) have a mastectomy as the final surgical procedure. Patients and Methods: The study population included women with DCIS diagnosed by core needle biopsy (and no evidence of invasive or micro-invasive disease) judged to be candidates for WLE by their surgeon based on standard imaging (mammogram +/-sonography) and clinical exam without prior breast MRI. After registration bilateral contrast enhanced breast MRI was performed, and a protocol management algorithm was followed. Before and after MRI, the surgeon documented the planned surgical procedure, including reason for conversion from WLE to mastectomy if the surgical plan changed. Prior evidence suggests that about 8-12% of patients initially considered candidates for WLE based on mammography ultimately require mastectomy, and the addition of MRI increases the likelihood of mastectomy by about 1.5-fold. A sample size of 350 (332 evaluable) was planned to ensure a 95% confidence interval (C.I.) of 8% if the actual mastectomy conversion rate was as high as 16%. Two-sided 95% Wilson confidence interval for proportion of patients converting to mastectomy based on MRI was derived. Results: Of 363 patients enrolled, 340 had sufficient information to assess aim A (conversion to mastectomy after MRI), and 322 for aim B (mastectomy as final surgical procedure). At study entry, median age (range) was 59 years (34-87). Features of DCIS lesions included: median longest diameter (range) 11 mm (1-100); ER positivity 76.2%; low, intermediate and high grade 15.9%, 40.9% and 39.4% respectively (3.8% unknown). Based on MRI findings (Aim A), mastectomy rather than WLE was recommended as the first surgical procedure in 25/340 (7.4%, 95% CI: 5.0%, 10.6%). Reasons included large lesion size (N=15), multi-centric disease (N=6), and contralateral disease prompting bilateral mastectomy (N=4). An additional 28/340 (8.2%) converted to mastectomy as the first surgery based on other factors, including patient preference (N=25), interval discovery of genetic mutation (N=2), or inability to receive radiation treatment (N=1). Of the 278 patients for whom initial WLE was performed after MRI, 10/278 (3.7%) converted to mastectomy, all due to positive or close (&amp;lt; 2 mm) surgical margins. Overall (Aim B), 62/322 (19.3%, 95% CI 15.3%, 23.9%) had mastectomy as the final surgical procedure. Conclusion: In women with DCIS judged to be candidates for WLE based on mammography (+/- sonography), conversion to mastectomy is fairly common with nearly 1 in 5 patients ultimately undergoing mastectomy. Breast MRI findings account for less than half of the conversions to mastectomy. For patients who remained candidates for WLE after MRI, 96.3% achieve successful WLE as the final surgical procedure. Citation Format: Lehman CD, Gatsonis C, Greco E, Khan SA, Sparano JA, Solin LJ, Badve SS, Corsetti RL, Rahbar H, Spell DW, Blankstein KB, Han LK, Sabol JL, Bumberry JR, Miller KD, Comstock C. Impact of magnetic resonance imaging on conversion from wide local excision to mastectomy in patients with ductal carcinoma in situ: First results from the ECOG-ACRIN 4112 prospective study [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P3-02-12.

Application of Breast Ultrasound Elastography to Differentiate Intracapsular Collection from Silicone-Induced Granuloma of Breast Implant Capsule Complementarily to Contrast-Enhanced Breast Magnetic Resonance Imaging.

Background:To determine whether there is correlation between magnetic resonance imaging (MRI) findings and breast elastography to differentiate seroma/hematoma from silicone-induced granuloma of breast implant capsule (SIGBIC).Methods:Prospective study of 99 patients with breast implants submitted to breast MRI during the period from February 1 to May 1, 2017. Patients who present MRI findings of seroma/hematoma or SIGBIC were submitted to a complementary ultrasound elastography study to evaluate the correlation of the results. The criteria adopted for the diagnosis of granuloma by MRI were heterogeneous hypersignal in the T2-weighted sequences, late contrast enhancement, and black drop sign. Lesions that did not enhance after the use of contrast were considered as seroma/hematoma. By elastography, the results were considered positive for granuloma when presented as hard lesions, whereas seroma/hematoma presented as soft lesions.Results:Of the 99 patients evaluated, 15 were included in the study. Of the 15 patients, 9 had solid intracapsular MRI masses, whereas 6 presented collections without contrast enhancement. The complementary elastography study showed correlation with MRI results in all cases of SIGBIC and seroma/hematoma, being elastography able to differentiate lesions from solid to cystic.Conclusions:Elastography of intracapsular masses in breast implants presented results compatible with those found by MRI to differentiate solid lesions from collections.

Dynamic contrast-enhanced breast magnetic resonance imaging for the prediction of early and late recurrences in breast cancer.

The aim of the study was to evaluate dynamic contrast-enhanced breast magnetic resonance imaging (DCE-MRI) features for the prediction of early and late recurrences in patients with breast cancer.Of 1030 breast cancer patients who underwent surgery at our hospital from January 2007 to July 2011, 83 recurrent breast cancer patients were enrolled in this study. We compared MRI features (background parenchymal enhancement [BPE], internal enhancement, adjacent vessel sign, whole-breast vascularity, initial enhancement pattern, kinetic curve types, and quantitative kinetic parameters) and clinico-pathologic variables (age, stage, histologic grade, nuclear grade, existence of lymphovascular invasion and extensive intraductal carcinoma component, and immunohistochemical profiles) between patients with early (≤2.5 years after surgery) and late recurrence (>2.5 years after surgery). Cox proportional hazard regression analysis was performed to evaluate independent risk factors for early and late recurrence.On breast MRI, prominent ipsilateral whole-breast vascularity was independently associated with early recurrence (hazard ratio [HR], 2.86; 95% confidence intervals [CI], 1.39–5.88) and moderate or marked BPE (HR, 2.08; 95% CI, 1.04–4.18) and rim enhancement (HR, 2.14; 95% CI, 1.00–4.59) were independently associated with late recurrence. Clinico-pathologic variables independently associated with early recurrence included negative estrogen receptor (HR, 0.53; 95% CI, 0.29–0.96), whereas T2 stage (HR, 2.08; 95% CI, 1.04–4.16) and nuclear grade III (HR, 2.54; 95% CI, 1.29–4.98) were associated with late recurrence.In DCE-MRI, prominent ipsilateral whole-breast vascularity, moderate or marked BPE, and rim enhancement could be useful for predicting recurrence timing in patients with breast cancer.

Advanced Breast MRI Techniques: Helpful for Screening Breast Cancer?

Breast magnetic resonance imaging (MRI) is increasingly used in conjunction with mammography as a screening tool to detect breast cancers in asymptomatic high-risk women. Conventional dynamic contrast-enhanced (DCE) breast MRI has a high sensitivity but only moderate specificity for the detection of breast cancer. The primary goal of developing and applying advanced breast MRI techniques that can assess tissue biology is to improve lesion specificity. This review provides a summary of the advances in DCE-MRI techniques and the use of diffusion-weighted imaging and magnetic resonance spectroscopy for breast cancer detection. Publications on the use of these advanced MRI techniques are largely single-institution studies with small numbers of patients, which limits the generalization of this data to a wider screening population. In their current forms, these adjunctive techniques require further research, incorporating an expanded patient population, to validate their utility for breast cancer screening.

B1 Field Correction of T1 Estimation Should Be Considered for Breast Dynamic Contrast-enhanced MR Imaging Even at 1.5 T.

Purpose To prospectively quantify the effect of T1 estimation in fat by B1 correction in breast magnetic resonance (MR) imaging at 1.5 T and to examine the subsequent quantitative dynamic contrast material-enhanced parameters in breast cancer with and without B1 correction. Materials and Methods This study had institutional review board approval, and informed consent was obtained from 72 patients with breast cancer before breast MR imaging studies were performed between January and July 2015. B1+ field and variable flip angle (FA) mapping were included in the dynamic contrast-enhanced breast MR imaging protocol with a 1.5-T MR imaging system. Precontrast T1 relaxation in fat and breast tumors was computed with and without B1 correction. The pharmacokinetic parameters of breast cancer were calculated by using the Tofts model with T1 values before and after B1 correction. The Mann-Whitney U test and linear regression model were used for statistical analysis. Results The FA was 19% higher in the left breast and 3% lower in the right breast than the prescribed value. This 22% average FA difference created a 43% T1 estimation bias in fat between the breasts. The T1 variation in fat was reduced to 0.96% after B1 correction. There was a 50% overestimation and a 7% underestimation of tumor T1 in the left breast and the right, respectively, associated with B1 error. Assuming T1 after B1 correction represents the true tumor T1, 41% underestimation in the left breast and 10% overestimation in the right without B1 correction were seen in the dynamic contrast-enhanced parameters (including the volume transfer constant, or Ktrans, fraction of extracellular extravascular space, or ve, and blood normalized initial area under the gadolinium concentration curve to 90 seconds, or IAUGCBN90). Conclusion B1 correction for more accurate T1 values should be considered for quantitative dynamic contrast-enhanced breast MR imaging, even at 1.5 T, to offset significant systemic error. © RSNA, 2016.

Computed Tomography Demonstration of the Production and Distribution of Oxygen Gas Following Intratumoral Injection of a New Radiosensitizer (KORTUC) for Patients with Breast Cancer—Is Intratumoral Injection Not an Ideal Approach to Solve the Major Problem of Tumor Hypoxia in Radiotherapy?

We previously developed a new enzyme-targeting radiosensitization treatment named Kochi Oxydol-Radiation Therapy for Unresectable Carcinomas, Type II (KORTUC II), which contains hydrogen peroxide and sodium hyaluronate for injection into various types of tumors. For breast cancer treatment, the radiosensitization agent was injected into the tumor tissue twice a week under ultrasonographic guidance, immediately prior to each administration of radiation therapy. At approximately three hours after the second or third injection, computed tomography (CT) was performed to confirm the production and distribution of oxygen gas generated from the KORTUC radiosensitization agent by catalysis of peroxidases contained mainly in tumor tissue. The purpose of this study was to demonstrate that tumor hypoxia could be overcome by such a procedure and to evaluate the method of intratumoral injection in terms of confirming oxygen distribution in the target tumor tissue and around the tumor to be visualized on dedicated CT imaging. Three-dimensional reconstructed maximum intensity projection imaging of contrast-enhanced breast magnetic resonance imaging was used to compare the position of the tumor and that of the generated oxygen. Distributed oxygen gas was confirmed in the tumor tissue and around it in all 10 patients examined in the study. A region of oxygen gas was measured as an average value of −457.2 Hounsfield units (HU) as a region of interest. A slightly increased HU value compared to the density of air or oxygen was considered due to the presence of tumor tissue in the low-density area on 5-mm-thick reconstructed CT imaging. The results of this study showed that intratumoral oxygen was successfully produced by intratumoral KORTUC injection under ultrasonographic guidance, and that tumor hypoxia, which is considered a main cause of radioresistance in currently used Linac (linear accelerator) radiation therapy for malignant neoplasms, could be resolved by this method.

Magnetic resonance imaging texture analysis classification of primary breast cancer.

Patient-tailored treatments for breast cancer are based on histological and immunohistochemical (IHC) subtypes. Magnetic Resonance Imaging (MRI) texture analysis (TA) may be useful in non-invasive lesion subtype classification. Women with newly diagnosed primary breast cancer underwent pre-treatment dynamic contrast-enhanced breast MRI. TA was performed using co-occurrence matrix (COM) features, by creating a model on retrospective training data, then prospectively applying to a test set. Analyses were blinded to breast pathology. Subtype classifications were performed using a cross-validated k-nearest-neighbour (k = 3) technique, with accuracy relative to pathology assessed and receiver operator curve (AUROC) calculated. Mann-Whitney U and Kruskal-Wallis tests were used to assess raw entropy feature values. Histological subtype classifications were similar across training (n = 148 cancers) and test sets (n = 73 lesions) using all COM features (training: 75%, AUROC = 0.816; test: 72.5%, AUROC = 0.823). Entropy features were significantly different between lobular and ductal cancers (p < 0.001; Mann-Whitney U). IHC classifications using COM features were also similar for training and test data (training: 57.2%, AUROC = 0.754; test: 57.0%, AUROC = 0.750). Hormone receptor positive and negative cancers demonstrated significantly different entropy features. Entropy features alone were unable to create a robust classification model. Textural differences on contrast-enhanced MR images may reflect underlying lesion subtypes, which merits testing against treatment response. • MR-derived entropy features, representing heterogeneity, provide important information on tissue composition. • Entropy features can differentiate between histological and immunohistochemical subtypes of breast cancer. • Differing entropy features between breast cancer subtypes implies differences in lesion heterogeneity. • Texture analysis of breast cancer potentially provides added information for decision making.

Unenhanced Magnetic Resonance Imaging in the evaluation of High Risk Breast Cancer Individuals.

e12579 Background: Individuals at high risk of developing breast cancer benefit from an annual surveillance with contrast enhanced breast magnetic resonance imaging (CEMRI). However, this technique...