Diffusion Is Directional: Innovative Diffusion Tensor Imaging to Improve Prostate Cancer Detection.

In the prostate, water diffusion is faster when moving parallel to duct and gland walls than when moving perpendicular to them, but these data are not currently utilized in multiparametric magnetic resonance imaging (mpMRI) for prostate cancer (PCa) detection. Diffusion tensor imaging (DTI) can quantify the directional diffusion of water in tissue and is applied in brain and breast imaging. Our aim was to determine whether DTI may improve PCa detection. We scanned patients undergoing mpMRI for suspected PCa with a DTI sequence. We calculated diffusion metrics from DTI and diffusion weighted imaging (DWI) for suspected lesions and normal-appearing prostate tissue, using specialized software for DTI analysis, and compared predictive values for PCa in targeted biopsies, performed when clinically indicated. DTI scans were performed on 78 patients, 42 underwent biopsy and 16 were diagnosed with PCa. The median age was 62 (IQR 54.4-68.4), and PSA 4.8 (IQR 1.3-10.7) ng/mL. DTI metrics distinguished PCa lesions from normal tissue. The prime diffusion coefficient (λ1) was lower in both peripheral-zone (p < 0.0001) and central-gland (p < 0.0001) cancers, compared to normal tissue. DTI had higher negative and positive predictive values than mpMRI to predict PCa (positive predictive value (PPV) 77.8% (58.6-97.0%), negative predictive value (NPV) 91.7% (80.6-100%) vs. PPV 46.7% (28.8-64.5%), NPV 83.3% (62.3-100%)). We conclude from this pilot study that DTI combined with T2-weighted imaging may have the potential to improve PCa detection without requiring contrast injection.

Effect of IV Administration of a Gadolinium-Based Contrast Agent on Breast Diffusion-Tensor Imaging.

OBJECTIVE. The purpose of this study was to quantify changes in diffusion-tensor imaging (DTI) parameters before and after IV administration of a gadolinium-based contrast agent (GBCA) and explore the influence of those parameters on breast cancer diagnosis. SUBJECTS AND METHODS. A prospective cohort of 26 women with BI-RADS categories 0, 4, 5, or 6 underwent 3-T breast MRI with sequential DTI before GBCA administration and immediately after. Quantitative image analysis using dedicated DTI software yielded parametric DTI maps of each directional diffusion coefficient (DDC), mean diffusivity, and maximal anisotropy of the lesions and normal tissue. The color maps were evaluated and the lesion DTI parameters were compared before and after GBCA administration using appropriate statistical tests. RESULTS. Of the cohort, 58% had cancer (13 infiltrating ductal carcinoma, two ductal carcinoma in situ) and 42% had benign or normal results. All breast cancers were visually detected in the DDC λ1 maps before and after GBCA administration. Mean cancer size derived from λ1 maps before GBCA administration was 15.3 mm (range, 3.3-72.3 mm), and was not statistically significantly different from the size derived after GBCA administration of 17.3 mm (range, 3.9-71.0 mm). After GBCA administration, the cancers exhibited statistically significantly lower DDCs, mean diffusivity, and b0 intensity (p < 0.05), and no change in maximal anisotropy compared with before GBCA administration, whereas these parameters in normal and benign lesions did not change significantly after GBCA administration. The mean AUC values before and after GBCA administration, ranging from 0.735 to 0.985 and from 0.867 to 0.990, respectively, were not statistically significantly different for all parameters aside from λ3. CONCLUSION. Diagnostic accuracy using DTI was equivalent before and after GBCA administration, despite a change in the values of the DTI parameters. However, the limitations in standardization of contrast enhancement implies that unenhanced diffusion measurements should be preferred.

Quantitative evaluation of breast cancer response to neoadjuvant chemotherapy by diffusion tensor imaging: Initial results.

BACKGROUND: Diffusion tensor imaging (DTI) yields several parameters that have not been tested in response evaluation to neoadjuvant chemotherapy (NAC). PURPOSE: To evaluate and compare in reference to histopathology findings the ability of DTI and dynamic contrast-enhanced (DCE) MRI to monitor response to NAC. STUDY TYPE: Retrospective. POPULATION: Twenty patients treated with neoadjuvant chemotherapy. FIELD STRENGTH/SEQUENCE: 1.5T MRI axial, bilateral T2 -weighted, DTI, and DCE-MRI. ASSESSMENT: A standardized blinded image analysis at pixel resolution generated color-coded maps of DTI and DCE parameters STATISTICAL TESTS: Pearson's correlation analysis and Bland-Altman plots of the DTI and DCE size changes and of the pathological final residual tumor diameter and DCE or DTI final diameter, from pre- to post-NAC. Spearman coefficient of rank correlation between the DTI and DCE size changes from pre- to post-NAC and Miller and Payne (M&P) pathological response grading. Receiver operating characteristic curve analyses to differentiate between responders to nonresponders on the basis of the DTI and DCE percent size changes and the changes in DTI parameters. RESULTS: DTI and DCE changes in the cancers' diameter and volume from pre- to post-NAC exhibited high and significant Pearson correlation (r = 0.82 P = 1.2 × 10-5 ). The DTI volume changes exhibited a significant Spearman coefficient rank correlation (0.68, P = 0.001) with the pathological M&P grading and differentiated between responders and nonresponders with area-under-the-curve (AUC) of 0.83 ± 0.10. A similar AUC for differentiating responders from nonresponders was exhibited by the changes in the highest diffusion coefficient (0.84 ± 0.11) and the mean diffusivity (0.83 ± 0.11). The DTI residual-tumor-diameter showed a high and significant Pearson correlation (r = 0.87 P = 1.2 × 10-6 ) to pathology tumor diameter. DATA CONCLUSION: DTI monitors changes in cancer size and diffusion tensor parameters in response to NAC with an accuracy equivalent to that of DCE, enabling differentiation of responders from nonresponders and assessment of residual tumor size in high congruence with pathology. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2018;47:1080-1090.

Monitoring In-Vivo the Mammary Gland Microstructure during Morphogenesis from Lactation to Post-Weaning Using Diffusion Tensor MRI.

Lactation and the return to the pre-conception state during post-weaning are regulated by hormonal induced processes that modify the microstructure of the mammary gland, leading to changes in the features of the ductal / glandular tissue, the stroma and the fat tissue. These changes create a challenge in the radiological workup of breast disorder during lactation and early post-weaning. Here we present non-invasive MRI protocols designed to record in vivo high spatial resolution, T2-weighted images and diffusion tensor images of the entire mammary gland. Advanced imaging processing tools enabled tracking the changes in the anatomical and microstructural features of the mammary gland from the time of lactation to post-weaning. Specifically, by using diffusion tensor imaging (DTI) it was possible to quantitatively distinguish between the ductal / glandular tissue distention during lactation and the post-weaning involution. The application of the T2-weighted imaging and DTI is completely safe, non-invasive and uses intrinsic contrast based on differences in transverse relaxation rates and water diffusion rates in various directions, respectively. This study provides a basis for further in-vivo monitoring of changes during the mammary developmental stages, as well as identifying changes due to malignant transformation in patients with pregnancy associated breast cancer (PABC).

Estrogen Receptor-Targeted Contrast Agents for Molecular Magnetic Resonance Imaging of Breast Cancer Hormonal Status.

The estrogen receptor (ER) α is overexpressed in most breast cancers, and its level serves as a major prognostic factor. It is important to develop quantitative molecular imaging methods that specifically detect ER in vivo and assess its function throughout the entire primary breast cancer and in metastatic breast cancer lesions. This study presents the biochemical and molecular features, as well as the magnetic resonance imaging (MRI) effects of two novel ER-targeted contrast agents (CAs), based on pyridine-tetra-acetate-Gd(III) chelate conjugated to 17ß-estradiol (EPTA-Gd) or to tamoxifen (TPTA-Gd). The experiments were conducted in solution, in human breast cancer cells, and in severe combined immunodeficient mice implanted with transfected ER-positive and ER-negative MDA-MB-231 human breast cancer xenografts. Binding studies with ER in solution and in human breast cancer cells indicated affinities in the micromolar range of both CAs. Biochemical and molecular studies in breast cancer cell cultures showed that both CAs exhibit estrogen-like agonistic activity, enhancing cell proliferation, as well as upregulating cMyc oncogene and downregulating ER expression levels. The MRI longitudinal relaxivity was significantly augmented by EPTA-Gd in ER-positive cells as compared to ER-negative cells. Dynamic contrast-enhanced studies with EPTA-Gd in vivo indicated specific augmentation of the MRI water signal in the ER-positive versus ER-negative xenografts, confirming EPTA-Gd-specific interaction with ER. In contrast, TPTA-Gd did not show increased enhancement in ER-positive tumors and did not appear to interact in vivo with the tumors' ER. However, TPTA-Gd was found to interact strongly with muscle tissue, enhancing muscle signal intensity in a mechanism independent of the presence of ER. The specificity of EPTA-Gd interaction with ER in vivo was further verified by acute and chronic competition with tamoxifen. The chronic tamoxifen treatment also revealed that this drug increases the microvascular permeability of breast cancer xenograft in an ER-independent manner. In conclusion, EPTA-Gd has been shown to serve as an efficient molecular imaging probe for specific assessment of breast cancer ER in vivo.

Can diffusion tensor anisotropy indices assist in breast cancer detection?

PURPOSE: To evaluate whether the various anisotropy indices derived from breast diffusion tensor imaging (DTI) can characterize the healthy breast structure and differentiate cancer from normal breast tissue. MATERIALS AND METHODS: Six healthy volunteers and retrospectively selected 24 breast cancer patients were imaged at 3T. DTI included two b-values 0 and 700 sec/mm2 with 20-64 gradient directions and TE of 120 or 90 msec. The normalized anisotropy indices: fractional anisotropy (FA), relative anisotropy (RA), and 1-volume ratio (1-VR), as well as the absolute maximal anisotropy index (λ1 -λ3 ) were compared. RESULTS: The spatial distribution of the various anisotropy indices in healthy volunteers exhibited a high congruence (Pearson correlation coefficients range: 0.79-1.0). All indices showed a statistically significant reduction (P < 0.001) following shortening of the diffusion time. Significantly lower λ1 -λ3 values were found in cancers as compared to normal breast tissue (P < 6.0 × 10-7 ), while the values of the normalized indices in cancers were not significantly different from those in normal breast tissue (P < 0.65 for FA, P < 0.6 for RA, and P < 0.2 for 1-VR). The contrast-to-noise ratio of λ1 -λ3 was significantly higher (P < 0.001) than those of the normalized anisotropy indices, and the area under the curve in a receiver operating characteristic analysis exhibited the highest value for λ1 -λ3 (0.89 ± 0.04 vs. 0.51-0.54 for the other anisotropy indices). CONCLUSION: Water diffusion anisotropy in the healthy breast can be similarly mapped by the normalized indices and by λ1 -λ3 . However, the normalized anisotropy indices fail to differentiate cancer from normal breast tissue, whereas λ1 -λ3 can assist in differentiating cancer from normal breast tissue. J. Magn. Reson. Imaging 2016;44:1624-1632.

Overcoming limitations in diffusion-weighted MRI of breast by spatio-temporal encoding.

PURPOSE: Evaluating the usefulness of diffusion-weighted spatio-temporal encoding (SPEN) methods to provide quantitative apparent diffusion coefficient (ADC)-based characterizations of healthy and malignant human breast tissues, in comparison with results obtained using techniques based on spin-echo echo planar imaging (SE-EPI). METHODS: Twelve healthy volunteers and six breast cancer patients were scanned at 3T using scanner-supplied diffusion-weighted imaging EPI sequences, as well as two fully refocused SPEN variants programmed in-house. Suitable codes were written to process the data, including calculations of the actual b-values and retrieval of the ADC maps. RESULTS: Systematically better images were afforded by the SPEN scans, with negligible geometrical distortions and markedly weaker ghosting artifacts arising from either fat tissues or from strongly emitting areas such as cysts. SPEN-derived images provided improved characterizations of the fibroglandular tissues and of the lesions' contours. When translated into the calculation of the ADC maps, there were no significant differences between the mean ADCs derived from SPEN and SE-EPI: if reliable images were available, both techniques showed that ADCs decreased by nearly two-fold in the malignant lesion areas. CONCLUSION: SPEN-based sequences yielded diffusion-weighted breast images with minimal artifacts and distortions, enabling the calculation of improved ADC maps and the identification of decreased ADCs in malignant regions.

Tracking the mammary architectural features and detecting breast cancer with magnetic resonance diffusion tensor imaging.

Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of life and survival of breast cancer patients. In this paper a new approach for the detection of breast cancer is described, based on tracking the mammary architectural elements using diffusion tensor imaging (DTI). The paper focuses on the scanning protocols and image processing algorithms and software that were designed to fit the diffusion properties of the mammary fibroglandular tissue and its changes during malignant transformation. The final output yields pixel by pixel vector maps that track the architecture of the entire mammary ductal glandular trees and parametric maps of the diffusion tensor coefficients and anisotropy indices. The efficiency of the method to detect breast cancer was tested by scanning women volunteers including 68 patients with breast cancer confirmed by histopathology findings. Regions with cancer cells exhibited a marked reduction in the diffusion coefficients and in the maximal anisotropy index as compared to the normal breast tissue, providing an intrinsic contrast for delineating the boundaries of malignant growth. Overall, the sensitivity of the DTI parameters to detect breast cancer was found to be high, particularly in dense breasts, and comparable to the current standard breast MRI method that requires injection of a contrast agent. Thus, this method offers a completely non-invasive, safe and sensitive tool for breast cancer detection.

Diffusion tensor magnetic resonance imaging of the pancreas.

PURPOSE: To develop a diffusion-tensor-imaging (DTI) protocol that is sensitive to the complex diffusion and perfusion properties of the healthy and malignant pancreas tissues. MATERIALS AND METHODS: Twenty-eight healthy volunteers and nine patients with pancreatic-ductal-adenocacinoma (PDAC), were scanned at 3T with T2-weighted and DTI sequences. Healthy volunteers were also scanned with multi-b diffusion-weighted-imaging (DWI), whereas a standard clinical protocol complemented the PDAC patients' scans. Image processing at pixel resolution yielded parametric maps of three directional diffusion coefficients λ1, λ2, λ3, apparent diffusion coefficient (ADC), and fractional anisotropy (FA), as well as a λ1-vector map, and a main diffusion-direction map. RESULTS: DTI measurements of healthy pancreatic tissue at b-values 0,500 s/mm² yielded: λ1 = (2.65±0.35)×10⁻³, λ2 = (1.87±0.22)×10⁻³, λ3 = (1.20±0.18)×10⁻³, ADC = (1.91±0.22)×10⁻³ (all in mm²/s units) and FA = 0.38±0.06. Using b-values of 100,500 s/mm² led to a significant reduction in λ1, λ2, λ3 and ADC (p<.0001) and a significant increase (p<0.0001) in FA. The reduction in the diffusion coefficients suggested a contribution of a fast intra-voxel-incoherent-motion (IVIM) component at b≤100 s/mm², which was confirmed by the multi-b DWI results. In PDACs, λ1, λ2, λ3 and ADC in both 0,500 s/mm² and 100,500 s/mm² b-values sets, as well as the reduction in these diffusion coefficients between the two sets, were significantly lower in comparison to the distal normal pancreatic tissue, suggesting higher cellularity and diminution of the fast-IVIM component in the cancer tissue. CONCLUSION: DTI using two reference b-values 0 and 100 s/mm² enabled characterization of the water diffusion and anisotropy of the healthy pancreas, taking into account a contribution of IVIM. The reduction in the diffusion coefficients of PDAC, as compared to normal pancreatic tissue, and the smaller change in these coefficients in PDAC when the reference b-value was modified from 0 to 100 s/mm², helped identifying the presence of malignancy.

Diffusion-tensor MR imaging of the breast: hormonal regulation.

PURPOSE: To investigate the parameters obtained with magnetic resonance (MR) diffusion-tensor imaging (DTI) of the breast throughout the menstrual cycle phases, during lactation, and after menopause, with and without hormone replacement therapy (HRT). MATERIALS AND METHODS: All protocols were approved by the internal review board, and signed informed consent was obtained from all participants. Forty-five healthy volunteers underwent imaging by using T2-weighted and DTI MR sequences at 3 T. Premenopausal volunteers (n = 16) underwent imaging weekly, four times during one menstrual cycle. Postmenopausal volunteers (n = 19) and lactating volunteers (n = 10) underwent imaging once. The principal diffusion coefficients (λ1, λ2, and λ3), apparent diffusion coefficient (ADC), fractional anisotropy (FA), and maximal anisotropy (λ1-λ3) were calculated pixel by pixel for the fibroglandular tissue in the entire breast. RESULTS: In all premenopausal volunteers, the DTI parameters exhibited high repeatability, remaining almost equal along the menstrual cycle, with a low mean within-subject coefficient of variance of λ1, λ2, λ3, and ADC (1%-2% for all) and FA (5%), as well as a high intraclass correlation of 0.92-0.98. The diffusion coefficients were significantly lower (a) in the group without HRT use as compared with the group with HRT use (P < .01) and premenopausal volunteers (P < .01) and (b) in the lactating volunteers as compared with the premenopausal volunteers (P < .005). No significant differences in DTI parameters were found between premenopausal volunteers free of oral contraceptives and those who used oral contraceptives (P = .28-0.82) and between premenopausal volunteers and postmenopausal volunteers who used HRT (P = .31-0.93). CONCLUSION: DTI parameters are not sensitive to menstrual cycle changes, while menopause, long-term HRT, and presence of milk in lactating women affected the DTI parameters. Therefore, the timing for performing breast DTI is not restricted throughout the menstrual cycle, whereas the modulations in diffusion parameters due to HRT and lactation should be taken into account in DTI evaluation.

In vivo magnetic resonance of hyperpolarized [(13)C1]pyruvate: metabolic dynamics in stimulated muscle.

The metabolic status of muscle changes according to the energetic demands of the organism. Two key regulators of these changes include exercise and insulin, with exercise eliciting catabolic expenditure within seconds and insulin enabling anabolic energy investment over minutes to hours. This study explores the potential of time-resolved hyperpolarized dynamic (13)C spectroscopy to characterize the in vivo metabolic phenotype of muscle during functional and biochemical insulin-induced stimulation of muscle. Using [(13)C1]pyruvic acid as a tracer, we find that despite the different time scales of these forms of stimulation, increases in pyruvate label transport and consumption and concomitant increases in initial rates of the tracer metabolism to lactate were observed for both stimuli. By contrast, rates of tracer metabolism to labeled alanine increased incrementally for insulin but remained unchanged following exercise-like muscle stimulation. Kinetic analysis revealed that branching of the hyperpolarized [(13)C]pyruvate tracer between lactate and alanine provides significant tissue-specific biomarkers that distinguish between anabolic and catabolic fates in vivo according to the routing of metabolites between glycolytic and amino acid pathways.

Characterization of estrogen-receptor-targeted contrast agents in solution, breast cancer cells, and tumors in vivo.

The estrogen receptor (ER) is a major prognostic biomarker of breast cancer, currently determined in surgical specimens by immunohistochemistry. Two new ER-targeted probes, pyridine-tetra-acetate-Gd chelate (PTA-Gd) conjugated either to 17ß-estradiol (EPTA-Gd) or to tamoxifen (TPTA-Gd), were explored as contrast agents for molecular imaging of ER. In solution, both probes exhibited a micromolar ER binding affinity, fast water exchange rate (∼10(7) s(-1)), and water proton-relaxivity of 4.7-6.8 mM(-1) s(-1). In human breast cancer cells, both probes acted as estrogen agonists and enhanced the water protons T1 relaxation rate and relaxivity in ER-positive as compared to ER-negative cells, with EPTA-Gd showing a higher ER-specific relaxivity than TPTA-Gd. In studies of breast cancer tumors in vivo, EPTA-Gd induced the highest enhancement in ER-positive tumors as compared to ER-negative tumors and muscle tissue, enabling in vivo detection of ER. TPTA-Gd demonstrated the highest enhancement in muscle tissue indicating nonspecific interaction of this agent with muscle components. The extracellular contrast agents, PTA-Gd and GdDTPA, showed no difference in the perfusion capacity of ER-positive and -negative tumors confirming the specific interaction of EPTA-Gd with ER. These findings lay a basis for the molecular imaging of the ER using EPTA-Gd as a template for further developments.

Parametric diffusion tensor imaging of the breast.

OBJECTIVES: To investigate the ability of parametric diffusion tensor imaging (DTI), applied at 3 Tesla, to dissect breast tissue architecture and evaluate breast lesions. MATERIALS AND METHODS: All protocols were approved and a signed informed consent was obtained from all subjects. The study included 21 healthy women, 26 women with 33 malignant lesions, and 14 women with 20 benign lesions. Images were recorded at 3 Tesla with a protocol optimized for breast DTI at a spatial resolution of 1.9 × 1.9 × (2-2.5) mm3. Image processing algorithms and software, applied at pixel resolution, yielded vector maps of prime diffusion direction and parametric maps of the 3 orthogonal diffusion coefficients and of the fractional anisotropy and maximal anisotropy. RESULTS: The DTI-derived vector maps and parametric maps revealed the architecture of the entire mammary fibroglandular tissue and allowed a reliable detection of malignant lesions. Cancer lesions exhibited significantly lower values of the orthogonal diffusion coefficients, λ1, λ2, λ3, and of the maximal anisotropy index λ1-λ3 as compared with normal breast tissue (P < 0.0001) and to benign breast lesions (P < 0.0009 and 0.004, respectively). Maps of λ1 exhibited the highest contrast-to-noise ratio enabling delineation of the cancer lesions. These maps also provided high sensitivity/specificity of 95.6%/97.7% for differentiating cancers from benign lesions, which were similar to the sensitivity/specificity of dynamic contrast-enhanced magnetic resonance imaging of 94.8%/92.9%. Maps of λ1-λ3 provided a secondary independent diagnostic parameter with high sensitivity of 92.3%, but low specificity of 69.5% for differentiating cancers from benign lesions. CONCLUSION: Mapping the diffusion tensor parameters at high spatial resolution provides a potential novel means for dissecting breast architecture. Parametric maps of λ1 and λ1-λ3 facilitate the detection and diagnosis of breast cancer.

In vivo magnetic resonance imaging of the estrogen receptor in an orthotopic model of human breast cancer.

Histologic overexpression of the estrogen receptor α (ER) is a well-established prognostic marker in breast cancer. Noninvasive imaging techniques that could detect ER overexpression would be useful in a variety of settings where patients' biopsies are problematic to obtain. This study focused on developing, by in vivo MRI, strategies to measure the level of ER expression in an orthotopic mouse model of human breast cancer. Specifically, novel ER-targeted contrast agents based on pyridine-tetra-acetate-Gd(III) chelate (PTA-Gd) conjugated to 17ß-estradiol (EPTA-Gd) or to tamoxifen (TPTA-Gd) were examined in ER-positive or ER-negative tumors. Detection of specific interactions of EPTA-Gd with ER were documented that could differentiate ER-positive and ER-negative tumors. In vivo competition experiments confirmed that the enhanced detection capability of EPTA-Gd was based specifically on ER targeting. In contrast, PTA-Gd acted as an extracellular probe that enhanced ER detection similarly in either tumor type, confirming a similar vascular perfusion efficiency in ER-positive and ER-negative tumors in the model. Finally, TPTA-Gd accumulated selectively in muscle and could not preferentially identify ER-positive tumors. Together, these results define a novel MRI probe that can permit selective noninvasive imaging of ER-positive tumors in vivo.

Structure of estradiol metal chelate and estrogen receptor complex: the basis for designing a new class of selective estrogen receptor modulators.

Selective estrogen receptor modulators, such as 17ß-estradiol derivatives bound to metal complexes, have been synthesized as targeted probes for the diagnosis and treatment of breast cancer. Here, we report the detailed 3D structure of estrogen receptor α ligand-binding domain (ERα-LBD) bound with a novel estradiol-derived metal complex, estradiol-pyridine tetra acetate europium(III), at 2.6 Å resolution. This structure provides important information pertinent to the design of novel functional ERα targeted probes for clinical applications.

Triple-negative breast cancer: present challenges and new perspectives.

Triple-negative breast cancers (TNBC), characterized by absence of estrogen receptor (ER), progesterone receptor (PR) and lack of overexpression of human epidermal growth factor receptor 2 (HER2), are typically associated with poor prognosis, due to aggressive tumor phenotype(s), only partial response to chemotherapy and present lack of clinically established targeted therapies. Advances in the design of individualized strategies for treatment of TNBC patients require further elucidation, by combined 'omics' approaches, of the molecular mechanisms underlying TNBC phenotypic heterogeneity, and the still poorly understood association of TNBC with BRCA1 mutations. An overview is here presented on TNBC profiling in terms of expression signatures, within the functional genomic breast tumor classification, and ongoing efforts toward identification of new therapy targets and bioimaging markers. Due to the complexity of aberrant molecular patterns involved in expression, pathological progression and biological/clinical heterogeneity, the search for novel TNBC biomarkers and therapy targets requires collection of multi-dimensional data sets, use of robust multivariate data analysis techniques and development of innovative systems biology approaches.

Principal component analysis of dynamic contrast enhanced MRI in human prostate cancer.

OBJECTIVES: To develop and evaluate a fast, objective and standardized method for image processing of dynamic contrast enhanced MRI of the prostate based on principal component analysis (PCA). MATERIALS AND METHODS: The study was approved by the institutional internal review board; signed informed consent was obtained. MRI of the prostate at 3 Tesla was performed in 21 patients with biopsy proven cancers before radical prostatectomy. Seven 3-dimensional gradient echo datesets, 2 pre and 5 post-gadopentetate dimeglumine injection (0.1 mmol/kg), were acquired within 10.5 minutes at high spatial resolution. PCA of dynamic intensity-scaled (IS) and enhancement-scaled (ES) datasets and analysis by the 3-time points (3TP) method were applied using the latter method for adjusting the PCA eigenvectors. RESULTS: PCA of 7 IS datasets and 6 ES datasets yielded their corresponding eigenvectors and eigenvalues. The first IS-eigenvector captured the major part of the signal variance because of a signal change between the precontrast and the first postcontrast arising from the inhomogeneous surface coil reception profile. The next 2 IS-eigenvectors and the 2 dominant ES-eigenvectors captured signal changes because of tissue contrast-enhancement, whereas the remaining eigenvectors captured noise changes. These eigenvectors were adjusted by rotation to reach congruence with the wash-in and wash-out kinetic parameters defined according to the 3TP method. The IS and ES-eigenvectors and rotation angles were highly reproducible across patients enabling the calculation of a general rotated eigenvector base that served to rapidly and objectively calculate diagnostically relevant projection coefficient maps for new cases. We found for the a priori selected prostate cancer patients that the projection coefficients of the IS-2nd eigenvector provided a higher accuracy for detecting biopsy proven cancers (94% sensitivity, 67% specificity, 80% ppv, and 89% npv) than the projection coefficients of the ES-2nd rotated and non rotated eigenvectors. CONCLUSIONS: PCA adjusted to correlate with physiological parameters selects a dominant eigenvector, free of the inhomogeneous radio-frequency field reception-profile and noise-components. Projection coefficient maps of this eigenvector provide a fast, objective, and standardized means for visualizing prostate cancer.

Kinetics of hyperpolarized 13C1-pyruvate transport and metabolism in living human breast cancer cells.

Metabolic fluxes can serve as specific biomarkers for detecting malignant transformations, tumor progression, and response to microenvironmental changes and treatment procedures. We present noninvasive hyperpolarized (13)C NMR investigations on the metabolic flux of pyruvate to lactate, in a well-controlled injection/perfusion system using T47D human breast cancer cells. Initial rates of pyruvate-to-lactate conversion were obtained by fitting the hyperpolarized (13)C and ancillary (31)P NMR data to a model, yielding both kinetic parameters and mechanistic insight into this conversion. Transport was found to be the rate-limiting process for the conversion of extracellular pyruvate to lactate with K(m) = 2.14 +/- 0.03 mM, typical of the monocarboxylate transporter 1 (MCT1), and a V(max) = 27.6 +/- 1.1 fmolxmin(-1).cell(-1), in agreement with the high expression level of this transporter. Modulation of the environment to hypoxic conditions as well as suppression of cells' perfusion enhanced the rate of pyruvate-to-lactate conversion, presumably by up-regulation of the MCT1. Conversely, the addition of quercetin, a flavonoidal MCT1 inhibitor, markedly reduces the apparent rate of pyruvate-to-lactate conversion. These results suggest that hyperpolarized (13)C(1)-pyruvate may be a useful magnetic resonance biomarker of MCT regulation and malignant transformations in breast cancer.