Breast MRI during Neoadjuvant Chemotherapy: Lack of Background Parenchymal Enhancement Suppression and Inferior Treatment Response.

Background Suppression of background parenchymal enhancement (BPE) is commonly observed after neoadjuvant chemotherapy (NAC) at contrast-enhanced breast MRI. It was hypothesized that nonsuppressed BPE may be associated with inferior response to NAC. Purpose To investigate the relationship between lack of BPE suppression and pathologic response. Materials and Methods A retrospective review was performed for women with menopausal status data who were treated for breast cancer by one of 10 drug arms (standard NAC with or without experimental agents) between May 2010 and November 2016 in the Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis 2, or I-SPY 2 TRIAL (NCT01042379). Patients underwent MRI at four points: before treatment (T0), early treatment (T1), interregimen (T2), and before surgery (T3). BPE was quantitatively measured by using automated fibroglandular tissue segmentation. To test the hypothesis effectively, a subset of examinations with BPE with high-quality segmentation was selected. BPE change from T0 was defined as suppressed or nonsuppressed for each point. The Fisher exact test and the Z tests of proportions with Yates continuity correction were used to examine the relationship between BPE suppression and pathologic complete response (pCR) in hormone receptor (HR)-positive and HR-negative cohorts. Results A total of 3528 MRI scans from 882 patients (mean age, 48 years ± 10 [standard deviation]) were reviewed and the subset of patients with high-quality BPE segmentation was determined (T1, 433 patients; T2, 396 patients; T3, 380 patients). In the HR-positive cohort, an association between lack of BPE suppression and lower pCR rate was detected at T2 (nonsuppressed vs suppressed, 11.8% [six of 51] vs 28.9% [50 of 173]; difference, 17.1% [95% CI: 4.7, 29.5]; P = .02) and T3 (nonsuppressed vs suppressed, 5.3% [two of 38] vs 27.4% [48 of 175]; difference, 22.2% [95% CI: 10.9, 33.5]; P = .003). In the HR-negative cohort, patients with nonsuppressed BPE had lower estimated pCR rate at all points, but the P values for the association were all greater than .05. Conclusions In hormone receptor-positive breast cancer, lack of background parenchymal enhancement suppression may indicate inferior treatment response. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Philpotts in this issue.

Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL.

Dynamic contrast-enhanced (DCE) MRI provides both morphological and functional information regarding breast tumor response to neoadjuvant chemotherapy (NAC). The purpose of this retrospective study is to test if prediction models combining multiple MRI features outperform models with single features. Four features were quantitatively calculated in each MRI exam: functional tumor volume, longest diameter, sphericity, and contralateral background parenchymal enhancement. Logistic regression analysis was used to study the relationship between MRI variables and pathologic complete response (pCR). Predictive performance was estimated using the area under the receiver operating characteristic curve (AUC). The full cohort was stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status (positive or negative). A total of 384 patients (median age: 49 y/o) were included. Results showed analysis with combined features achieved higher AUCs than analysis with any feature alone. AUCs estimated for the combined versus highest AUCs among single features were 0.81 (95% confidence interval [CI]: 0.76, 0.86) versus 0.79 (95% CI: 0.73, 0.85) in the full cohort, 0.83 (95% CI: 0.77, 0.92) versus 0.73 (95% CI: 0.61, 0.84) in HR-positive/HER2-negative, 0.88 (95% CI: 0.79, 0.97) versus 0.78 (95% CI: 0.63, 0.89) in HR-positive/HER2-positive, 0.83 (95% CI not available) versus 0.75 (95% CI: 0.46, 0.81) in HR-negative/HER2-positive, and 0.82 (95% CI: 0.74, 0.91) versus 0.75 (95% CI: 0.64, 0.83) in triple negatives. Multi-feature MRI analysis improved pCR prediction over analysis of any individual feature that we examined. Additionally, the improvements in prediction were more notable when analysis was conducted according to cancer subtype.

Discrimination of Malignant and Benign Breast Lesions Using Quantitative Multiparametric MRI: A Preliminary Study.

We aimed to compare diagnostic performance in discriminating malignant and benign breast lesions between two intravoxel incoherent motion (IVIM) analysis methods for diffusion-weighted magnetic resonance imaging (DW-MRI) data and between DW- and dynamic contrast-enhanced (DCE)-MRI, and to determine if combining DW- and DCE-MRI further improves diagnostic accuracy. DW-MRI with 12 b-values and DCE-MRI were performed on 26 patients with 28 suspicious breast lesions before biopsies. The traditional biexponential fitting and a 3-b-value method were used for independent IVIM analysis of the DW-MRI data. Simulations were performed to evaluate errors in IVIM parameter estimations by the two methods across a range of signal-to-noise ratio (SNR). Pharmacokinetic modeling of DCE-MRI data was performed. Conventional radiological MRI reading yielded 86% sensitivity and 21% specificity in breast cancer diagnosis. At the same sensitivity, specificity of individual DCE- and DW-MRI markers improved to 36%-57% and that of combined DCE- or combined DW-MRI markers to 57%-71%, with DCE-MRI markers showing better diagnostic performance. The combination of DCE- and DW-MRI markers further improved specificity to 86%-93% and the improvements in diagnostic accuracy were statistically significant (P < .05) when compared with standard clinical MRI reading and most individual markers. At low breast DW-MRI SNR values (<50), like those typically seen in clinical studies, the 3-b-value approach for IVIM analysis generates markers with smaller errors and with comparable or better diagnostic performances compared with biexponential fitting. This suggests that the 3-b-value method could be an optimal IVIM-MRI method to be combined with DCE-MRI for improved diagnostic accuracy.

Using autochthonous Bdellovibrio as a predatory bacterium for reduction of Gram-negative pathogenic bacteria in urban wastewater and reuse it.

BACKGROUND AND OBJECTIVES: The microbial contamination of wastewater is associated with health risks. The aim of this study was to use the autochthonous Bdellovibrio potential to prey Gram-negative pathogenic bacteria as a bio-control agent to treat urban wastewater. MATERIALS AND METHODS: Thirty-six raw sewage samples were collected for isolation of Bdellovibrio. Double layer plaque assay was used for isolation and the isolates were identified by microscopic examination and molecular analysis. To evaluate the predatory potential for decrease number of Gram-negative pathogenic bacteria, plaque perdition assay, reduction in host cells viability by colony-forming unit (CFU) counting, reduction in optical density (OD) in co-cultures and assay of killing efficiency were carried out. Also, the raw wastewater was treated by Bdellovibrio then the reduction in CFU counting and reduction in OD was evaluated. RESULTS: Four strains of Bdellovibrio were isolated and were registered in Gene Bank. Clear plaques were observed after 3-6 days of incubation for all prey cells. The CFU enumerations of all preys were decreased after 48 hrs in co-cultures and raw wastewater. Also, OD was decreased down to 0.2 nm after 48 hrs. CONCLUSION: These autochthonous Bdellovibrio strains are proposed to use for bio-control of Gram-negative pathogenic bacteria in wastewater and reuse it for irrigation in arid regions.

Early Prediction of Breast Cancer Therapy Response using Multiresolution Fractal Analysis of DCE-MRI Parametric Maps.

We aimed to determine whether multiresolution fractal analysis of voxel-based dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps can provide early prediction of breast cancer response to neoadjuvant chemotherapy (NACT). In total, 55 patients underwent 4 DCE-MRI examinations before, during, and after NACT. The shutter-speed model was used to analyze the DCE-MRI data and generate parametric maps within the tumor region of interest. The proposed multiresolution fractal method and the more conventional methods of single-resolution fractal, gray-level co-occurrence matrix, and run-length matrix were used to extract features from the parametric maps. Only the data obtained before and after the first NACT cycle were used to evaluate early prediction of response. With a training (N = 40) and testing (N = 15) data set, support vector machine was used to assess the predictive abilities of the features in classification of pathologic complete response versus non-pathologic complete response. Generally the multiresolution fractal features from individual maps and the concatenated features from all parametric maps showed better predictive performances than conventional features, with receiver operating curve area under the curve (AUC) values of 0.91 (all parameters) and 0.80 (Ktrans), in the training and testing sets, respectively. The differences in AUC were statistically significant (P < .05) for several parametric maps. Thus, multiresolution analysis that decomposes the texture at various spatial-frequency scales may more accurately capture changes in tumor vascular heterogeneity as measured by DCE-MRI, and therefore provide better early prediction of NACT response.

DCE-MRI Texture Features for Early Prediction of Breast Cancer Therapy Response.

This study investigates the effectiveness of hundreds of texture features extracted from voxel-based dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps for early prediction of breast cancer response to neoadjuvant chemotherapy (NAC). In total, 38 patients with breast cancer underwent DCE-MRI before (baseline) and after the first of the 6-8 NAC cycles. Quantitative pharmacokinetic (PK) parameters and semiquantitative metrics were estimated from DCE-MRI time-course data. The residual cancer burden (RCB) index value was computed based on pathological analysis of surgical specimens after NAC completion. In total, 1043 texture features were extracted from each of the 13 parametric maps of quantitative PK or semiquantitative metric, and their capabilities for early prediction of RCB were examined by correlating feature changes between the 2 MRI studies with RCB. There were 1069 pairs of feature-map combinations that showed effectiveness for response prediction with 4 correlation coefficients >0.7. The 3-dimensional gray-level cooccurrence matrix was the most effective feature extraction method for therapy response prediction, and, in general, the statistical features describing texture heterogeneity were the most effective features. Quantitative PK parameters, particularly those estimated with the shutter-speed model, were more likely to generate effective features for prediction response compared with the semiquantitative metrics. The best feature-map pair could predict pathologic complete response with 100% sensitivity and 100% specificity using our cohort. In conclusion, breast tumor heterogeneity in microvasculature as measured by texture features of voxel-based DCE-MRI parametric maps could be a useful biomarker for early prediction of NAC response.

Male Breast: Clinical and Imaging Evaluations of Benign and Malignant Entities with Histologic Correlation.

Breast cancer is an uncommon disease in men. As a result, the diagnosis may not initially be considered. Understanding the common benign and malignant entities affecting the male breast is critical for timely and accurate diagnosis in the primary care setting. Most patients present with a palpable breast mass or pain. The usual etiology is gynecomastia, the most common breast condition in males, but breast cancer must always be excluded through careful imaging evaluation when physical examination findings are suspicious or inconclusive. Imaging of the male breast generally relies on mammography and ultrasound, with mammography employed as the initial imaging modality of choice and ultrasound when a mass is detected or suspected. Here we describe the normal male breast anatomy and present an evaluation algorithm for the male patient with breast signs or symptoms. The most common benign and malignant entities are described.

Pharmacokinetics of dehydroepiandrosterone and its metabolites after long-term daily oral administration to healthy young men.

OBJECTIVE: To determine the effects of dehydroepiandrosterone (DHEA) supplementation on the pharmacokinetics of DHEA and its metabolites and the reproductive axis of healthy young men. DESIGN: A prospective, randomized, double-blind, placebo-controlled pharmacokinetic study. SETTING: General Clinical Research Center and laboratories at the Keck School of Medicine of the University of Southern California, Los Angeles, California. PATIENT(S): Fourteen healthy men, ages 18-42 years. INTERVENTION(S): Daily oral administration of placebo (n = 5), 50 mg DHEA (n = 4), or 200 mg DHEA (n = 5) for 6 months. Blood samples were collected at frequent intervals on day 1 and at months 3 and 6 of treatment. MAIN OUTCOME MEASURE(S): Quantification of DHEA, DHEA sulfate (DHEAS), androstenedione, T, E(2), dihydrotestosterone (DHT), and 5alpha-androstane-3alpha-17beta-diol glucuronide (ADG). Physical examination, semen analysis, serum LH, FSH, prostate-specific antigen, and general chemistries were carried out. RESULT(S): Baseline DHEA, DHEAS, and ADG levels increased significantly from day 1 to months 3 and 6 in the DHEA treatment groups but not in the placebo group. No significant changes were observed in pharmacokinetic values. Clinical parameters were not affected. CONCLUSION(S): DHEA, DHEAS, and ADG increased significantly during 6 months of daily DHEA supplementation. Although the pharmacokinetics of DHEA and its metabolites are not altered, sustained baseline elevation of ADG, a distal DHT metabolite, raises concerns about the potential negative impact of DHEA supplementation on the prostate gland.