A study of Docetaxel-induced effects in MCF-7 cells by means of Raman microspectroscopy

Chemotherapies feature a low success rate of about 25%, and therefore, the choice of the most effective cytostatic drug for the individual patient and monitoring the efficiency of an ongoing chemotherapy are important steps towards personalized therapy. Thereby, an objective method able to differentiate between treated and untreated cancer cells would be essential. In this study, we provide molecular insights into Docetaxel-induced effects in MCF-7 cells, as a model system for adenocarcinoma, by means of Raman microspectroscopy combined with powerful chemometric methods. The analysis of the Raman data is divided into two steps. In the first part, the morphology of cell organelles, e.g. the cell nucleus has been visualized by analysing the Raman spectra with k-means cluster analysis and artificial neural networks and compared to the histopathologic gold standard method hematoxylin and eosin staining. This comparison showed that Raman microscopy is capable of displaying the cell morphology; however, this is in contrast to hematoxylin and eosin staining label free and can therefore be applied potentially in vivo. Because Docetaxel is a drug acting within the cell nucleus, Raman spectra originating from the cell nucleus region were further investigated in a next step. Thereby we were able to differentiate treated from untreated MCF-7 cells and to quantify the cell–drug response by utilizing linear discriminant analysis models

MR-based wall shear stress measurements in fully developed turbulent flow using the Clauser plot method

In arterial blood flow wall shear stress (WSS) quantifies the frictional force that flowing blood exerts on a vessel wall. WSS can be directly estimated from phase-contrast (PC) MR velocity measurements and has been suggested as a biomarker in cardio-vascular diseases. We present and investigate the application of the Clauser plot method for estimating WSS in fully developed turbulent stationary flow using PC velocity measurements. The Clauser plot method estimates WSS from the logarithmic region of boundary layer in fully developed turbulent stationary flow. The Clauser plot method was evaluated using 2D PC-MR phantom measurements at 3 T for different in-plane resolutions at various Reynolds numbers. WSS values derived from the Clauser plot were compared to results from Laser Doppler Velocimetry (LDV) measurements and theoretical results calculated using the friction factor formula for smooth pipe flow. For all Reynolds numbers, WSS values derived from the Clauser plot were in good agreement with results from LDV measurements and values using the friction factor formula (relative deviations ∼5%). Furthermore, Clauser plot derived results were almost independent of spatial resolution, in contrast to WSS results obtained with our in-house software tool for MR-based WSS quantification showing relative deviations of more than 100%. In fully developed turbulent flow, the Clauser plot method provides highly consistent WSS independent of the underlying spatial resolution. Therefore, it renders a valuable approach for MR-based WSS estimates in controllable flow settings. Although its direct in vivo applicability is severely limited because of the different flow character, it may serve as helpful approach for validation of MR-based WSS quantification algorithms prior to their clinical application

Ultrashort echo time imaging for quantification of hepatic iron overload: Comparison of acquisition and fitting methods via simulations, phantoms, and in vivo data

Background: Current R2*-MRI techniques for measuring hepatic iron content (HIC) use various acquisition types and fitting models. Purpose: To evaluate the accuracy and precision of R2*-HIC acquisition and fitting methods. Study Type: Signal simulations, phantom study, and prospective in vivo cohort. Population: In all, 132 patients (58/74 male/female, mean age 17.7 years). Field Strength/Sequence: 2D-multiecho gradient-echo (GRE) and ultrashort echo time (UTE) acquisitions at 1.5T. Assessment: Synthetic MR signals were created to mimic published GRE and UTE methods, using different R2* values (25–2000 s −1 ) and signal-to-noise ratios (SNR). Phantoms with varying iron concentrations were scanned at 1.5T. In vivo data were analyzed from 132 patients acquired at 1.5T. R2* was estimated by fitting using three signal models. Accuracy and precision of R2* measurements for UTE acquisition parameters (SNR, echo spacing [ΔTE], maximum echo time [TE max ]) and fitting methods were compared for simulated, phantom, and in vivo datasets. Statistical Tests: R2* accuracy was determined from the relative error and by linear regression analysis. Precision was evaluated using coefficient of variation (CoV) analysis. Results: In simulations, all models had high R2* accuracy (error \u3c5%) and precision (CoV \u3c10%) for all SNRs, shorter ΔTE (≤0.5 msec), and longer TE max (≥10.1 msec); except the constant offset model overestimated R2* at the lowest SNR. In phantoms and in vivo, all models produced similar R2* values for different SNRs and shorter ΔTEs (slopes: 0.99–1.06, R 2 \u3e 0.99, P \u3c 0.001). In all experiments, R2* results degraded for high R2* values with longer ΔTE (≥1 msec). In vivo, shorter and longer TE max gave similar R2* results (slopes: 1.02–1.06, R 2 \u3e 0.99, P \u3c 0.001) for the noise subtraction model for 25≤R2*≤2000 s −1 . However, both quadratic and constant offset models, using shorter TE max (≤4.7 msec) overestimated R2* and yielded high CoVs up to ∼170% for low R2* (\u3c250 s −1 ). Data Conclusion: UTE with TE max ≥ 10.1 msec and ΔTE ≤ 0.5 msec yields accurate R2* estimates over the entire clinical HIC range. Monoexponential fitting with noise subtraction is the most robust signal model to changes in UTE parameters and achieves the highest R2* accuracy and precision. Level of Evidence: 2. Technical Efficacy: Stage 2. J. Magn. Reson. Imaging 2019;49:1475–1488

Autoregressive moving average modeling for hepatic iron quantification in the presence of fat

Background: Measuring hepatic R2* by fitting a monoexponential model to the signal decay of a multigradient-echo (mGRE) sequence noninvasively determines hepatic iron content (HIC). Concurrent hepatic steatosis introduces signal oscillations and confounds R2* quantification with standard monoexponential models. Purpose: To evaluate an autoregressive moving average (ARMA) model for accurate quantification of HIC in the presence of fat using biopsy as the reference. Study Type: Phantom study and in vivo cohort. Population: Twenty iron–fat phantoms covering clinically relevant R2* (30–800 s-1) and fat fraction (FF) ranges (0–40%), and 10 patients (four male, six female, mean age 18.8 years). Field Strength/Sequence: 2D mGRE acquisitions at 1.5 T and 3 T. Assessment: Phantoms were scanned at both field strengths. In vivo data were analyzed using the ARMA model to determine R2* and FF values, and compared with biopsy results. Statistical Tests: Linear regression analysis was used to compare ARMA R2* and FF results with those obtained using a conventional monoexponential model, complex-domain nonlinear least squares (NLSQ) fat–water model, and biopsy. Results: In phantoms and in vivo, all models produced R2* and FF values consistent with expected values in low iron and low/high fat conditions. For high iron and no fat phantoms, monoexponential and ARMA models performed excellently (slopes: 0.89–1.07), but NLSQ overestimated R2* (slopes: 1.14–1.36) and produced false FFs (12–17%) at 1.5 T; in high iron and fat phantoms, NLSQ (slopes: 1.02–1.16) outperformed monoexponential and ARMA models (slopes: 1.23–1.88). The results with NLSQ and ARMA improved in phantoms at 3 T (slopes: 0.96–1.04). In patients, mean R2*-HIC estimates for monoexponential and ARMA models were close to biopsy-HIC values (slopes: 0.90–0.95), whereas NLSQ substantially overestimated HIC (slope 1.4) and produced false FF values (4–28%) with very high SDs (15–222%) in patients with high iron overload and no steatosis. Data Conclusion: ARMA is superior in quantifying R2* and FF under high iron and no fat conditions, whereas NLSQ is superior for high iron and concurrent fat at 1.5 T. Both models give improved R2* and FF results at 3 T. Level of Evidence: 2. Technical Efficacy Stage: 2. J. Magn. Reson. Imaging 2019;50:1620–1632

Autoregressive moving average modeling for hepatic iron quantification in the presence of fat

Background: Measuring hepatic R2* by fitting a monoexponential model to the signal decay of a multigradient-echo (mGRE) sequence noninvasively determines hepatic iron content (HIC). Concurrent hepatic steatosis introduces signal oscillations and confounds R2* quantification with standard monoexponential models. Purpose: To evaluate an autoregressive moving average (ARMA) model for accurate quantification of HIC in the presence of fat using biopsy as the reference. Study Type: Phantom study and in vivo cohort. Population: Twenty iron–fat phantoms covering clinically relevant R2* (30–800 s-1) and fat fraction (FF) ranges (0–40%), and 10 patients (four male, six female, mean age 18.8 years). Field Strength/Sequence: 2D mGRE acquisitions at 1.5 T and 3 T. Assessment: Phantoms were scanned at both field strengths. In vivo data were analyzed using the ARMA model to determine R2* and FF values, and compared with biopsy results. Statistical Tests: Linear regression analysis was used to compare ARMA R2* and FF results with those obtained using a conventional monoexponential model, complex-domain nonlinear least squares (NLSQ) fat–water model, and biopsy. Results: In phantoms and in vivo, all models produced R2* and FF values consistent with expected values in low iron and low/high fat conditions. For high iron and no fat phantoms, monoexponential and ARMA models performed excellently (slopes: 0.89–1.07), but NLSQ overestimated R2* (slopes: 1.14–1.36) and produced false FFs (12–17%) at 1.5 T; in high iron and fat phantoms, NLSQ (slopes: 1.02–1.16) outperformed monoexponential and ARMA models (slopes: 1.23–1.88). The results with NLSQ and ARMA improved in phantoms at 3 T (slopes: 0.96–1.04). In patients, mean R2*-HIC estimates for monoexponential and ARMA models were close to biopsy-HIC values (slopes: 0.90–0.95), whereas NLSQ substantially overestimated HIC (slope 1.4) and produced false FF values (4–28%) with very high SDs (15–222%) in patients with high iron overload and no steatosis. Data Conclusion: ARMA is superior in quantifying R2* and FF under high iron and no fat conditions, whereas NLSQ is superior for high iron and concurrent fat at 1.5 T. Both models give improved R2* and FF results at 3 T. Level of Evidence: 2. Technical Efficacy Stage: 2. J. Magn. Reson. Imaging 2019;50:1620–1632

Spinal Cord Motion in Degenerative Cervical Myelopathy: The Level of the Stenotic Segment and Gender Cause Altered Pathodynamics

In degenerative cervical myelopathy (DCM), focally increased spinal cord motion has been observed for C5/C6, but whether stenoses at other cervical segments lead to similar pathodynamics and how severity of stenosis, age, and gender affect them is still unclear. We report a prospective matched-pair controlled trial on 65 DCM patients. A high-resolution 3D T2 sampling perfection with application-optimized contrasts using different flip angle evolution (SPACE) and a phase-contrast magnetic resonance imaging (MRI) sequence were performed and automatically segmented. Anatomical and spinal cord motion data were assessed per segment from C2/C3 to C7/T1. Spinal cord motion was focally increased at a level of stenosis among patients with stenosis at C4/C5 (n = 14), C5/C6 (n = 33), and C6/C7 (n = 10) (p < 0.033). Patients with stenosis at C2/C3 (n = 2) and C3/C4 (n = 6) presented a similar pattern, not reaching significance. Gender was a significant predictor of higher spinal cord dynamics among men with stenosis at C5/C6 (p = 0.048) and C6/C7 (p = 0.033). Age and severity of stenosis did not relate to spinal cord motion. Thus, the data demonstrates focally increased spinal cord motion depending on the specific level of stenosis. Gender-related effects lead to dynamic alterations among men with stenosis at C5/C6 and C6/C7. The missing relation of motion to severity of stenosis underlines a possible additive diagnostic value of spinal cord motion analysis in DCM

Radial ultrashort TE imaging removes the need for breath-holding in hepatic iron overload quantification by R2∗ MRI

OBJECTIVE. The objective of this study is to evaluate radial free-breathing (FB) multiecho ultrashort TE (UTE) imaging as an alternative to Cartesian FB multiecho gradient-recalled echo (GRE) imaging for quantitative assessment of hepatic iron content (HIC) in sedated patients and subjects unable to perform breath-hold (BH) maneuvers. MATERIALS AND METHODS. FB multiecho GRE imaging and FB multiecho UTE imaging were conducted for 46 test group patients with iron overload who could not complete BH maneuvers (38 patients were sedated, and eight were not sedated) and 16 control patients who could complete BH maneuvers. Control patients also underwent standard BH multiecho GRE imaging. Quantitative R2∗ maps were calculated, and mean liver R2∗ values and coefficients of variation (CVs) for different acquisitions and patient groups were compared using statistical analysis. RESULTS. FB multiecho GRE images displayed motion artifacts and significantly lower R2∗ values, compared with standard BH multiecho GRE images and FB multiecho UTE images in the control cohort and FB multiecho UTE images in the test cohort. In contrast, FB multiecho UTE images produced artifact-free R2∗ maps, and mean R2∗ values were not significantly different from those measured by BH multiecho GRE imaging. Motion artifacts on FB multiecho GRE images resulted in an R2∗ CV that was approximately twofold higher than the R2∗ CV from BH multiecho GRE imaging and FB multiecho UTE imaging. The R2∗ CV was relatively constant over the range of R2∗ values for FB multiecho UTE, but it increased with increases in R2∗ for FB multiecho GRE imaging, reflecting that motion artifacts had a stronger impact on R2∗ estimation with increasing iron burden. CONCLUSION. FB multiecho UTE imaging was less motion sensitive because of radial sampling, produced excellent image quality, and yielded accurate R2∗ estimates within the same acquisition time used for multiaveraged FB multiecho GRE imaging. Thus, FB multiecho UTE imaging is a viable alternative for accurate HIC assessment in sedated children and patients who cannot complete BH maneuvers

Quantitative ultrashort echo time imaging for assessment of massive iron overload at 1.5 and 3 Tesla

Purpose: Hepatic iron content (HIC) quantification via transverse relaxation rate (R2*)-MRI using multi-gradient echo (mGRE) imaging is compromised toward high HIC or at higher fields due to the rapid signal decay. Our study aims at presenting an optimized 2D ultrashort echo time (UTE) sequence for R2* quantification to overcome these limitations. Methods: Two-dimensional UTE imaging was realized via half-pulse excitation and radial center-out sampling. The sequence includes chemically selective saturation pulses to reduce streaking artifacts from subcutaneous fat, and spatial saturation (sSAT) bands to suppress out-of-slice signals. The sequence employs interleaved multi-echo readout trains to achieve dense temporal sampling of rapid signal decays. Evaluation was done at 1.5 Tesla (T) and 3T in phantoms, and clinical applicability was demonstrated in five patients with biopsy-confirmed massively high HIC levels (\u3e25 mg Fe/g dry weight liver tissue). Results: In phantoms, the sSAT pulses were found to remove out-of-slice contamination, and R2* results were in excellent agreement to reference mGRE R2* results (slope of linear regression: 1.02/1.00 for 1.5/3T). UTE-based R2* quantification in patients with massive iron overload proved successful at both field strengths and was consistent with biopsy HIC values. Conclusion: The UTE sequence provides a means to measure R2* in patients with massive iron overload, both at 1.5T and 3T. Magn Reson Med 78:1839–1851, 2017. © 2017 Wiley Periodicals, Inc

Can multi-slice or navigator-gated R2* MRI replace single-slice breath-hold acquisition for hepatic iron quantification?

Background: Liver R2* values calculated from multi-gradient echo (mGRE) magnetic resonance images (MRI) are strongly correlated with hepatic iron concentration (HIC) as shown in several independently derived biopsy calibration studies. These calibrations were established for axial single-slice breath-hold imaging at the location of the portal vein. Scanning in multi-slice mode makes the exam more efficient, since whole-liver coverage can be achieved with two breath-holds and the optimal slice can be selected afterward. Navigator echoes remove the need for breath-holds and allow use in sedated patients. Objective: To evaluate if the existing biopsy calibrations can be applied to multi-slice and navigator-controlled mGRE imaging in children with hepatic iron overload, by testing if there is a bias-free correlation between single-slice R2* and multi-slice or multi-slice navigator controlled R2*. Materials and methods: This study included MRI data from 71 patients with transfusional iron overload, who received an MRI exam to estimate HIC using gradient echo sequences. Patient scans contained 2 or 3 of the following imaging methods used for analysis: single-slice images (n = 71), multi-slice images (n = 69) and navigator-controlled images (n = 17). Small and large blood corrected region of interests were selected on axial images of the liver to obtain R2* values for all data sets. Bland-Altman and linear regression analysis were used to compare R2* values from single-slice images to those of multi-slice images and navigator-controlled images. Results: Bland-Altman analysis showed that all imaging method comparisons were strongly associated with each other and had high correlation coefficients (0.98 ≤ r ≤ 1.00) with P-values ≤0.0001. Linear regression yielded slopes that were close to 1. Conclusion: We found that navigator-gated or breath-held multi-slice R2* MRI for HIC determination measures R2* values comparable to the biopsy-validated single-slice, single breath-hold scan. We conclude that these three R2* methods can be interchangeably used in existing R2*-HIC calibrations