Magnetic Field Treatments Improves Sunflower Yield by Inducing Physiological and Biochemical Modulations in Seeds.

Magnetic seed enhancement has been practicing as a promising tool to improve germination and seedling growth of low vigor seeds stored under suboptimal conditions, but there is still ambiguity regarding the prospects for magnetism in oilseeds. Present study elucidates the potential of magnetic seed stimulation to improve sunflower germination, growth and yield. Germination and emergence tests were performed to optimize the strength of the magnetic field to sunflower seed enhancement. The seeds were directly exposed to magnetic field strengths of 50, 100 and 150 millitesla (mT) for 5, 10 and 15 min (min) and then standard germination tests were performed. Secondly, the emergence potential of untreated seeds was compared with seed exposed to hydropriming, priming with 3% moringa leaf extract (MLE), priming with magnetically treated water (MTW) for 10 min and priming with 3% MLE solution prepared in magnetically treated water (MTW + MLE). Germination, emergence, seedling growth and seed biochemical properties were used to select the best treatment for field evaluation. The results of the study revealed that magnetic seed treatment with 100 mT for 10 min and seed priming with 3% MLE solution in magnetically treated water (MTW + MLE) significantly improved emergence, crop growth rate and sunflower yield.

DCE-MRI of hepatocellular carcinoma: perfusion quantification with Tofts model versus shutter-speed model--initial experience.

OBJECTIVE: To quantify hepatocellular carcinoma (HCC) perfusion and flow with the fast exchange regime-allowed Shutter-Speed model (SSM) compared to the Tofts model (TM). MATERIALS AND METHODS: In this prospective study, 25 patients with HCC underwent DCE-MRI. ROIs were placed in liver parenchyma, portal vein, aorta and HCC lesions. Signal intensities were analyzed employing dual-input TM and SSM models. ART (arterial fraction), K (trans) (contrast agent transfer rate constant from plasma to extravascular extracellular space), ve (extravascular extracellular volume fraction), kep (contrast agent intravasation rate constant), and τi (mean intracellular water molecule lifetime) were compared between liver parenchyma and HCC, and ART, K (trans), v e and k ep were compared between models using Wilcoxon tests and limits of agreement. Test-retest reproducibility was assessed in 10 patients. RESULTS: ART and v e obtained with TM; ART, ve, ke and τi obtained with SSM were significantly different between liver parenchyma and HCC (p < 0.04). Parameters showed variable reproducibility (CV range 14.7-66.5% for both models). Liver K (trans) and ve; HCC ve and kep were significantly different when estimated with the two models (p < 0.03). CONCLUSION: Our results show differences when computed between the TM and the SSM. However, these differences are smaller than parameter reproducibilities and may be of limited clinical significance.

Intratumor mapping of intracellular water lifetime: metabolic images of breast cancer?

Shutter-speed pharmacokinetic analysis of dynamic-contrast-enhanced (DCE)-MRI data allows evaluation of equilibrium inter-compartmental water interchange kinetics. The process measured here - transcytolemmal water exchange - is characterized by the mean intracellular water molecule lifetime (τi). The τi biomarker is a true intensive property not accessible by any formulation of the tracer pharmacokinetic paradigm, which inherently assumes it is effectively zero when applied to DCE-MRI. We present population-averaged in vivo human breast whole tumor τi changes induced by therapy, along with those of other pharmacokinetic parameters. In responding patients, the DCE parameters change significantly after only one neoadjuvant chemotherapy cycle: while K(trans) (measuring mostly contrast agent (CA) extravasation) and kep (CA intravasation rate constant) decrease, τi increases. However, high-resolution, (1 mm)(2), parametric maps exhibit significant intratumor heterogeneity, which is lost by averaging. A typical 400 ms τi value means a trans-membrane water cycling flux of 10(13) H2O molecules s(-1)/cell for a 12 µm diameter cell. Analyses of intratumor variations (and therapy-induced changes) of τi in combination with concomitant changes of ve (extracellular volume fraction) indicate that the former are dominated by alterations of the equilibrium cell membrane water permeability coefficient, PW, not of cell size. These can be interpreted in light of literature results showing that τi changes are dominated by a PW (active) component that reciprocally reflects the membrane driving P-type ATPase ion pump turnover. For mammalian cells, this is the Na(+), K(+)-ATPase pump. These results promise the potential to discriminate metabolic and microenvironmental states of regions within tumors in vivo, and their changes with therapy.

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.

The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge, Part II.

This multicenter study evaluated the effect of variations in arterial input function (AIF) determination on pharmacokinetic (PK) analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data using the shutter-speed model (SSM). Data acquired from eleven prostate cancer patients were shared among nine centers. Each center used a site-specific method to measure the individual AIF from each data set and submitted the results to the managing center. These AIFs, their reference tissue-adjusted variants, and a literature population-averaged AIF, were used by the managing center to perform SSM PK analysis to estimate Ktrans (volume transfer rate constant), ve (extravascular, extracellular volume fraction), kep (efflux rate constant), and τi (mean intracellular water lifetime). All other variables, including the definition of the tumor region of interest and precontrast T1 values, were kept the same to evaluate parameter variations caused by variations in only the AIF. Considerable PK parameter variations were observed with within-subject coefficient of variation (wCV) values of 0.58, 0.27, 0.42, and 0.24 for Ktrans, ve, kep, and τi, respectively, using the unadjusted AIFs. Use of the reference tissue-adjusted AIFs reduced variations in Ktrans and ve (wCV = 0.50 and 0.10, respectively), but had smaller effects on kep and τi (wCV = 0.39 and 0.22, respectively). kep is less sensitive to AIF variation than Ktrans, suggesting it may be a more robust imaging biomarker of prostate microvasculature. With low sensitivity to AIF uncertainty, the SSM-unique τi parameter may have advantages over the conventional PK parameters in a longitudinal study.

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.

Evaluation of Soft Tissue Sarcoma Response to Preoperative Chemoradiotherapy Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

This study aims to assess the utility of quantitative dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) parameters in comparison with imaging tumor size for early prediction and evaluation of soft tissue sarcoma response to preoperative chemoradiotherapy. In total, 20 patients with intermediate- to high-grade soft tissue sarcomas received either a phase I trial regimen of sorafenib + chemoradiotherapy (n = 8) or chemoradiotherapy only (n = 12), and underwent DCE-MRI at baseline, after 2 weeks of treatment with sorafenib or after the first chemotherapy cycle, and after therapy completion. MRI tumor size in the longest diameter (LD) was measured according to the RECIST (Response Evaluation Criteria In Solid Tumors) guidelines. Pharmacokinetic analyses of DCE-MRI data were performed using the Shutter-Speed model. After only 2 weeks of treatment with sorafenib or after 1 chemotherapy cycle, Ktrans (rate constant for plasma/interstitium contrast agent transfer) and its percent change were good early predictors of optimal versus suboptimal pathological response with univariate logistic regression C statistics values of 0.90 and 0.80, respectively, whereas RECIST LD percent change was only a fair predictor (C = 0.72). Post-therapy Ktrans, ve (extravascular and extracellular volume fraction), and kep (intravasation rate constant), not RECIST LD, were excellent (C > 0.90) markers of therapy response. Several DCE-MRI parameters before, during, and after therapy showed significant (P < .05) correlations with percent necrosis of resected tumor specimens. In conclusion, absolute values and percent changes of quantitative DCE-MRI parameters provide better early prediction and evaluation of the pathological response of soft tissue sarcoma to preoperative chemoradiotherapy than the conventional measurement of imaging tumor size change.

Early Prediction and Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy Using Quantitative DCE-MRI.

The purpose is to compare quantitative dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) metrics with imaging tumor size for early prediction of breast cancer response to neoadjuvant chemotherapy (NACT) and evaluation of residual cancer burden (RCB). Twenty-eight patients with 29 primary breast tumors underwent DCE-MRI exams before, after one cycle of, at midpoint of, and after NACT. MRI tumor size in the longest diameter (LD) was measured according to the RECIST (Response Evaluation Criteria In Solid Tumors) guidelines. Pharmacokinetic analyses of DCE-MRI data were performed with the standard Tofts and Shutter-Speed models (TM and SSM). After one NACT cycle the percent changes of DCE-MRI parameters K(trans) (contrast agent plasma/interstitium transfer rate constant), ve (extravascular and extracellular volume fraction), kep (intravasation rate constant), and SSM-unique τi (mean intracellular water lifetime) are good to excellent early predictors of pathologic complete response (pCR) vs. non-pCR, with univariate logistic regression C statistics value in the range of 0.804 to 0.967. ve values after one cycle and at NACT midpoint are also good predictors of response, with C ranging 0.845 to 0.897. However, RECIST LD changes are poor predictors with C = 0.609 and 0.673, respectively. Post-NACT K(trans), τi, and RECIST LD show statistically significant (P < .05) correlations with RCB. The performances of TM and SSM analyses for early prediction of response and RCB evaluation are comparable. In conclusion, quantitative DCE-MRI parameters are superior to imaging tumor size for early prediction of therapy response. Both TM and SSM analyses are effective for therapy response evaluation. However, the τi parameter derived only with SSM analysis allows the unique opportunity to potentially quantify therapy-induced changes in tumor energetic metabolism.

The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge.

Dynamic contrast-enhanced MRI (DCE-MRI) has been widely used in tumor detection and therapy response evaluation. Pharmacokinetic analysis of DCE-MRI time-course data allows estimation of quantitative imaging biomarkers such as Ktrans(rate constant for plasma/interstitium contrast reagent (CR) transfer) and ve (extravascular and extracellular volume fraction). However, the use of quantitative DCE-MRI in clinical prostate imaging islimited, with uncertainty in arterial input function (AIF, i.e., the time rate of change of the concentration of CR in the blood plasma) determination being one of the primary reasons. In this multicenter data analysis challenge to assess the effects of variations in AIF quantification on estimation of DCE-MRI parameters, prostate DCE-MRI data acquired at one center from 11 prostate cancer patients were shared among nine centers. Each center used its site-specific method to determine the individual AIF from each data set and submitted the results to the managing center. Along with a literature population averaged AIF, these AIFs and their reference-tissue-adjusted variants were used by the managing center to perform pharmacokinetic analysis of the DCE-MRI data sets using the Tofts model (TM). All other variables including tumor region of interest (ROI) definition and pre-contrast T1 were kept the same to evaluate parameter variations caused by AIF variations only. Considerable pharmacokinetic parameter variations were observed with the within-subject coefficient of variation (wCV) of Ktrans obtained with unadjusted AIFs as high as 0.74. AIF-caused variations were larger in Ktrans than ve and both were reduced when reference-tissue-adjusted AIFs were used. The parameter variations were largely systematic, resulting in nearly unchanged parametric map patterns. The CR intravasation rate constant, kep (= Ktrans/ve), was less sensitive to AIF variation than Ktrans (wCV for unadjusted AIFs: 0.45 for kepvs. 0.74 for Ktrans), suggesting that it might be a more robust imaging biomarker of prostate microvasculature than Ktrans.

Phase I trial of preoperative chemoradiation plus sorafenib for high-risk extremity soft tissue sarcomas with dynamic contrast-enhanced MRI correlates.

PURPOSE: We conducted a phase I trial of the addition of sorafenib to a chemoradiotherapy regimen in patients with high-risk (intermediate/high grade, >5 cm) extremity soft tissue sarcoma undergoing limb salvage surgery. We conducted a correlative study of quantitative dynamic contrast-enhanced MRI (DCE-MRI) to assess response to treatment. EXPERIMENTAL DESIGN: Patients were treated at increasing dose levels of sorafenib (200 mg daily, 400 mg daily, 400 mg twice daily) initiated 14 days before three preoperative and three postoperative cycles of epirubicin/ifosfamide. Radiation (28 Gy) was administered during cycle 2 with epirubicin omitted. The primary objective was to determine the maximum tolerated dose (MTD) of sorafenib. DCE-MRI was conducted at baseline, after 2 weeks of sorafenib, and before surgery. The imaging data were subjected to quantitative pharmacokinetic analyses. RESULTS: Eighteen subjects were enrolled, of which 16 were evaluable. The MTD of sorafenib was 400 mg daily. Common grade 3-4 adverse events included neutropenia (94%), hypophosphatemia (75%), anemia (69%), thrombocytopenia (50%), and neutropenic fever/infection (50%). Of note, 38% developed wound complications requiring surgical intervention. The rate of ≥95% histopathologic tumor necrosis was 44%. Changes in DCE-MRI biomarker ΔK(trans) after 2 weeks of sorafenib correlated with histologic response (R(2) = 0.67, P = 0.012) at surgery. CONCLUSION: The addition of sorafenib to preoperative chemoradiotherapy is feasible and warrants further investigation in a larger trial. DCE-MRI detected changes in tumor perfusion after 2 weeks of sorafenib and may be a minimally invasive tool for rapid assessment of drug effect in soft tissue sarcoma.

A feasible high spatiotemporal resolution breast DCE-MRI protocol for clinical settings.

Three dimensional bilateral imaging is the standard for most clinical breast dynamic contrast-enhanced (DCE) MRI protocols. Because of high spatial resolution (sRes) requirement, the typical 1-2 min temporal resolution (tRes) afforded by a conventional full-k-space-sampling gradient echo (GRE) sequence precludes meaningful and accurate pharmacokinetic analysis of DCE time-course data. The commercially available, GRE-based, k-space undersampling and data sharing TWIST (time-resolved angiography with stochastic trajectories) sequence was used in this study to perform DCE-MRI exams on thirty one patients (with 36 suspicious breast lesions) before their biopsies. The TWIST DCE-MRI was immediately followed by a single-frame conventional GRE acquisition. Blinded from each other, three radiologist readers assessed agreements in multiple lesion morphology categories between the last set of TWIST DCE images and the conventional GRE images. Fleiss' κ test was used to evaluate inter-reader agreement. The TWIST DCE time-course data were subjected to quantitative pharmacokinetic analyses. With a four-channel phased-array breast coil, the TWIST sequence produced DCE images with 20 s or less tRes and ~ 1.0×1.0×1.4 mm(3) sRes. There were no significant differences in signal-to-noise (P=.45) and contrast-to-noise (P=.51) ratios between the TWIST and conventional GRE images. The agreements in morphology evaluations between the two image sets were excellent with the intra-reader agreement ranging from 79% for mass margin to 100% for mammographic density and the inter-reader κ value ranging from 0.54 (P<.0001) for lesion size to 1.00 (P<.0001) for background parenchymal enhancement. Quantitative analyses of the DCE time-course data provided higher breast cancer diagnostic accuracy (91% specificity at 100% sensitivity) than the current clinical practice of morphology and qualitative kinetics assessments. The TWIST sequence may be used in clinical settings to acquire high spatiotemporal resolution breast DCE-MRI images for both precise lesion morphology characterization and accurate pharmacokinetic analysis.