Search

The aim of this study was to investigate the potential of magnetic resonance imaging (MRI) for a non-invasive synergistic assessment of tumor microenvironment (TME) hypoxia and induced neovascularization for the identification of aggressive breast cancer. Fifty-three female patients with breast cancer underwent multiparametric breast MRI including quantitative blood-oxygen-level-dependent (qBOLD) imaging for hypoxia and vascular architecture mapping for neovascularization. Quantitative MRI biomarker maps of oxygen extraction fraction (OEF), metabolic rate of oxygen (MRO2), mitochondrial oxygen tension (mitoPO2), microvessel radius (VSI), microvessel density (MVD), and microvessel type indicator (MTI) were calculated. Histopathology was the standard of reference. Histopathological markers (vascular endothelial growth factor receptor 1 (FLT1), podoplanin, hypoxia-inducible factor 1-alpha (HIF-1alpha), carbonic anhydrase 9 (CA IX), vascular endothelial growth factor C (VEGF-C)) were used to confirm imaging biomarker findings. Univariate and multivariate regression analyses were performed to differentiate less aggressive luminal from aggressive non-luminal (HER2-positive, triple negative) malignancies and assess the interplay between hypoxia and neoangiogenesis markers. Aggressive non-luminal cancers (n = 40) presented with significantly higher MRO2 (i.e., oxygen consumption), lower mitoPO2 values (i.e., hypoxia), lower MTI, and higher MVD than less aggressive cancers (n = 13). Data suggest that a model derived from OEF, mitoPO2, and MVD can predict tumor proliferation rate. This novel MRI approach, which can be easily implemented in routine breast MRI exams, aids in the non-invasive identification of aggressive breast cancer.

Microcalcifications are a common finding in mammography and usually require invasive procedures to diagnose or exclude malignancy. As many microcalcifications are due to benign lesions, we wanted to assess whether breast MRI as an additional diagnostic tool may be used to distinguish benign from malignant in this setting.Eligible for this retrospective, IRB-approved observational study were 858 consecutive patients (mean age 54±11years) undergoing stereotactically-guided biopsies of suspicious mammographic microcalcifications during three year at our institution. Finally included were 152 patients who also underwent breast MRI8weeks prior to biopsy. In case of malignant or lesions of uncertain malignant potential, subsequent surgery was performed. Benign findings were confirmed by imaging follow-up. BI-RADS category assignments from the original mammography and breast MRI reports were compared to the final diagnosis (benign vs. malignant) to determine diagnostic benchmarks.Histopathology revealed 81 benign (53.3%), 41 DCIS (27%) and 30 (19.7%) invasive cancers. Sensitivity, specificity, positive and negative predictive values for breast MRI were 97.2% (69/71), 39.5% (32/81), 58.5% (69/118) and 94.1% (32/34), respectively. Thus, 32/81 unnecessary biopsies in benign lesions (39.5%) may have been avoided, missing 2/71 malignant lesions (2.8%), both DCIS G2.Breast MRI as an additional diagnostic tool can be used to accurately distinguish benign from malignant mammographic microcalcifications and may thus be helpful to reduce unnecessary breast biopsies.

Background Otherwise healthy women at high risk for breast cancer undergo annual contrast agent-enhanced breast MRI screening examinations, resulting in high cumulative doses of gadolinium-based contrast agents (GBCAs). Whereas the majority of studies showed no T1 signal ratio increase in deep brain nuclei after more than six doses of macrocyclic GBCA, this has not been explored in a healthy study population. Purpose To assess whether women who are administered large cumulative doses of macrocyclic GBCA with breast MRI at high-risk breast cancer screening exhibit T1 alterations in deep brain nuclei. Materials and Methods In this prospective study from November 2017 to March 2018, healthy women who were either exposed (because of high-risk breast cancer screening) or unexposed to only gadoterate meglumine underwent 3.0-T brain MRI with a dedicated head coil, including T1 mapping and magnetization-prepared rapid gradient-echo sequences. T1 times and T1 signal intensities were measured in the dentate nucleus (DN), globus pallidus (GP), crus anterior of capsula interna (CA), and pons. Ratios of DN to pons and GP to CA were calculated, and univariable Pearson correlation coefficients were calculated. Multivariable analysis included partial regression analysis. Results This study evaluated 25 women (mean age, 51 years ± 11 [standard deviation]) who were exposed to a mean GBCA dose of 129 mL (median 112 mL; range, 70-302 mL) and 16 women (mean age, 37 years ± 10) who were never exposed to any GBCA. Infratentorially, no correlation between cumulative GBCA dose and T1 times or signal intensity ratios was detected (

Background: We aimed to investigate an automated semi-quantitative software as an imaging biomarker for the prediction of tissue response (TR) after completion of neoadjuvant chemotherapy (NAC). Methods: Breast magnetic resonance imaging (MRI) (1.5T, protocol according to international recommendations) of 67 patients with biopsy-proven invasive breast cancer were examined before and after NAC. After completion of NAC, histopathologic assessments of TR were classified according to the Chevallier grading system (CG1/4: full/non-responder; CG2/C3: partial responder). A commercially available fully automatic software (CADstream) extracted MRI parameters of tumor extension (tumor diameter/volume: TD/TV). Pre- versus post-NAC values were compared (ΔTV and ΔTD). Additionally, the software performed volumetric analyses of vascularization (VAV) after NAC. Accuracy of MRI parameters to predict TR were identified (cross-tabs, ROC, AUC, Kruskal-Wallis). Results: There were 37 (34.3%) CG1, 7 (6.5%) CG2, 53 (49.1%) CG3, and 11 (10.2%) CG4 lesions. The software reached area under the curve levels of 79.5% (CG1/complete response: ΔTD), 68.6% (CG2, CG3/partial response: VAV), and 88.8% to predict TR (CG4/non-response: ΔTV). Conclusion: Semi-quantitative automated analysis of breast MRI data enabled the prediction of tissue response to NAC.

Objectives To evaluate the performance of MRI for diagnosis of breast cancer in non-calcified equivocal breast findings. Materials and Methods We performed a systematic review and meta-analysis of peer-reviewed studies in PubMed from 01/01/1986 until 06/15/2015. Eligible were studies applying dynamic contrast-enhanced breast MRI as an adjunct to conventional imaging (mammography, ultrasound) to clarify equivocal findings without microcalcifications. Reference standard for MRI findings had to be established by histopathological sampling or imaging follow-up of at least 12 months. Number of true or false positives and negatives and other characteristics were extracted, and possible bias was determined using the QUADAS-2 applet. Statistical analyses included data pooling and heterogeneity testing. Results Fourteen out of 514 studies comprising 2,316 lesions met our inclusion criteria. Pooled diagnostic parameters were: sensitivity (99%, 95%-CI: 93–100%), specificity (89%, 95%-CI: 85–92%), PPV (56%, 95%-CI: 42–70%) and NPV (100%, 95%-CI: 99–100%). These estimates displayed significant heterogeneity (P

Endothelial cells are often present at inflammation sites. This is the case of endothelial cells of the blood-brain barrier (BBB) of patients afflicted with neurodegenerative disorders such as Alzheimer's, Parkinson's, or multiple sclerosis, as well as in cases of bacterial meningitis, trauma, or tumor-associated ischemia. Inflammation is a known modulator of gene expression through the activation of transcription factors, mostly NF-κB. RLIP76 (a.k.a. RALBP1), an ATP-dependent transporter of electrophile-glutathione conjugates, modulates BBB permeability through the regulation of tight junction function, cell adhesion, and exocytosis. Genes and pathways regulated by RLIP76 are transcriptional targets of tumor necrosis factor alpha (TNF-α) pro-inflammatory molecule, suggesting that RLIP76 may also be an inflammation target. To assess the effects of TNF-α on RLIP76, we faced the problem of choosing reference genes impervious to TNF-α. Since such genes were not known in human BBB endothelial cells, we subjected these to TNF-α, and measured by quantitative RT-PCR the expression of housekeeping genes commonly used as reference genes. We find most to be modulated, and analysis of several inflammation datasets as well as a metaanalysis of more than 5000 human tissue samples encompassing more than 300 cell types and diseases show that no single housekeeping gene may be used as a reference gene. Using three different algorithms, however, we uncovered a reference geneset impervious to TNF-α, and show for the first time that RLIP76 expression is induced by TNF-α and follows the induction kinetics of inflammation markers, suggesting that inflammation can influence RLIP76 expression at the BBB. We also show that MRP1 (a.k.a. ABCC1), another electrophile-glutathione transporter, is not modulated in the same cells and conditions, indicating that RLIP76 regulation by TNF-α is not a general property of glutathione transporters. The reference geneset uncovered herein should aid in future gene expression studies in inflammatory conditions of the BBB.

Several gene databases, including heavily used ones such as the National Center for Biotechnology Information (NCBI) database, erroneously assign, on occasion, literature references to genes or proteins. These mistakes are mostly due to an overlap in gene aliases, whereby two distinct genes share a pseudonym. This is particularly confusing when the gene products have also biological properties in common, are part of signaling pathways that cross-talk to one another, or are regulated by the same effectors. We present examples spanning several research fields including apoptosis, ubiquitin-dependent degradation, signaling by Notch, Wnt, and small G proteins, transporters of glutathione conjugates of electrophiles, and mitochondrial and ribosomal RNA genes. To solve the problem, we argue in favor of including Entrez gene numbers in papers submitted for publication as unique gene identifiers to allow precise identification of genes and species studied.

The blood-brain barrier (BBB) maintains the homeostasis between the central nervous system and the blood circulation [1]. One of the main efflux transporter proteins at the BBB is P-glycoprotein (P-gP) also known as ABCB1 or MDR1. Recently, transport studies with antidepressants suggested presence and functional activity of P-gP in an in vitro model of the BBB based on porcine cell line PBMEC/C1-2 [2]. Due to the important role of P-gP for the transport barrier function of the BBB, the presence and functionability of P-gP was investigated in cell line PBMEC/C1-2 maybe leading to an in vitro BBB model suitable for P-gP substrate screening.

PURPOSE: To develop a novel magnetic resonance imaging (MRI) approach for the noninvasive assessment of hypoxia and neovascularization in breast tumors. PROCEDURES: In this IRB-approved prospective study, 20 patients with suspicious breast lesions (BI-RADS 4/5) underwent multiparametric breast MRI including quantitative BOLD (qBOLD) and vascular architecture mapping (VAM). Custom-made in-house MatLab software was used for qBOLD and VAM data postprocessing and calculation of quantitative MRI biomarker maps of oxygen extraction fraction (OEF), metabolic rate of oxygen (MRO(2)), mitochondrial oxygen tension (mitoPO(2)) to measure tissue hypoxia and neovascularization including vascular architecture including microvessel radius (VSI), density (MVD), and type (MTI). Histopathology was used as standard of reference. Appropriate statistics were performed to assess and compare correlations between MRI biomarkers for hypoxia and neovascularization. RESULTS: qBOLD and VAM data with good quality were obtained from all patients with 13 invasive ductal carcinoma (IDC) and 7 benign breast tumors with a lesion diameter of at least 10 mm in all spatial directions. MRI biomarker maps of oxygen metabolism and neovascularization demonstrated intratumoral spatial heterogeneity with a broad range of biomarker values. Bulk tumor neovasculature consisted of draining venous microvasculature with slow flowing blood. High OEF and low mitoPO(2) was associated with low MVD and vice-versa. The heterogeneous pattern of MRO(2) values showed spatial congruence with VSI. IDCs showed significantly higher MRO(2) (P = 0.007), lower mitoPO(2) (P = 0.021), higher MVD (P = 0.005), and lower (i.e., more pathologic) MTI (P = 0.001) compared with benign breast tumors. These results indicate that IDCs consume more oxygen and are more hypoxic and neovascularized than benign tumors. CONCLUSIONS: We developed a novel MRI approach for the noninvasive assessment of hypoxia and neovascularization in benign and malignant breast tumors that can be easily integrated in a diagnostic MRI protocol and provides insight into intratumoral heterogeneity.