Differentiation of bone metastases from prostate cancer and benign red marrow depositions of the pelvic bone with multiparametric MRI

PurposeTo investigate the diagnostic utilities of imaging parameters derived from T1-weighted imaging (T1WI), diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to differentiate bone metastases from prostate cancer and benign red marrow depositions of the pelvic bone.Materials and methodsThirty-six lesions from 36 patients with prostate cancer were analyzed with T1WI, DWI, and DCE-MRI. The lesions were classified in the bone metastases (n = 22) and benign red marrow depositions (n = 14). Lesion-muscle ratio (LMR), apparent diffusion coefficient (ADC), volume transfer constant (K^trans), reflux rate (Kep), and volume fraction of the extravascular extracellular matrix (Ve) values were obtained from the lesions. The imaging parameters of the both groups were compared using the Mann-Whitney U test, receiver operating characteristics (ROC) curves were analyzed. For the ROC curves, area under the curves (AUCs) were compared.ResultsThe ADC, K^trans, K_ep, and V_e values of bone metastases were significantly higher than those of benign red marrow depositions (Mann-Whitney U test, p < 0.05). However, there was no significant difference in LMR between the two groups (Mann-Whitney U test, p = 0.360). The AUCs of K^trans_, K_ep, ADC, V_e, and LMR were 0.896, 0.844, 0.812, 0.724, and 0.448, respectively. In the pairwise comparison of ROC curves, the AUCs of K^trans and K_ep was significantly higher than LMR.ConclusionsK^trans, K_ep, V_e, and ADC values can be used as imaging tools to differentiate bone metastases from prostate cancer and benign red marrow depositions of the pelvic bone.     

Dynamic contrast-enhanced MRI with Gd-EOB-DTPA for the quantitative assessment of early-stage liver fibrosis induced by carbon tetrachloride in rabbits

PurposeTo explore quantitative parameters obtained by dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) with Gd-EOB-DTPA in discriminating early-stage liver fibrosis (LF) in a rabbit model.Materials and methodsLF was established in 60 rabbits by the injection of 50% CCl₄ oil solution, whereas 30 rabbits served as the control group. All rabbits underwent pathological examination to determine the LF stage using the METAVIR classification system. DCE MRI was performed, and quantitative parameters, including K^trans, K_ep, V_e, V_p and Re were measured and evaluated among the different LF stages using spearman correlation coefficients and receiver operating characteristic curve.ResultsIn all, 24, 25, and 22 rabbits had stage F0, stage F1, and stage F2 LF, respectively. K^trans (r = 0.803) increased, and K_ep (r = −0.495) and Re (r = −0.701) decreased with LF stage progression (P < 0.001), while no significant correlation was found for V_e or V_p. K^trans and Re were significantly different between all LF stage pairs compared (F0 vs. F1, F0 vs. F2, F1 vs. F2, F0 vs. F1-F2, P < 0.05). With the exception of F0 vs. F1, K_ep differed significantly between stages (P < 0.05). The AUC of K^trans was higher than that of other quantitative parameters, with an AUC of 0.92, 0.99, 0.94 and 0.92 for staging F0 vs. F1, F0 vs. F2, F1 vs. F2, and F0 vs. F1-F2, respectively.ConclusionAmong quantitative parameters of Gd-EOB-DTPA DCE MRI, K^trans was the best predictor for quantitatively differentiating early-stage LF.     

Early responses assessment of neoadjuvant chemotherapy in nasopharyngeal carcinoma by serial dynamic contrast-enhanced MR imaging

PurposeTo evaluate the feasibility of utilizing serial dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) prospectively for early prediction of neoadjuvant chemotherapy (NAC) response in nasopharyngeal carcinoma (NPC) patients.Materials and methodsSixty-three advanced NPC patients were recruited and received three DCE-MRI exams before treatment (Pre-Tx), 3 days (Day3-Tx) and 20 days (Day20-Tx) after initiation of chemotherapy (one NAC cycle). Early response to NAC was determined based on the third MRI scan and classified partial response (PR) as responders and stable disease (SD) as non-responders. After intensity-modulated radiotherapy (IMRT), complete response (CR) patients were classified as responders. The kinetic parameters (K^trans, K_ep, v_e, and v_p) derived from extended Tofts' model analysis and their corresponding changes ΔMetrics_(0–X) (X = 3 or 20 days) were compared between the responders and non-responders using the Student's T-test or Mann–Whitney U test.ResultsCompared to the SD group, the PR group after one NAC cycle presented significantly higher mean K^trans values at baseline (P = 0.011) and larger ΔK^trans_(0–3) and ΔK_ep(0–3) values (P = 0.003 and 0.031). For the above parameters, we gained acceptable sensitivity (range: 66.8–75.0%) and specificity (range: 60.0–66.7%) to distinguish the non-responders from the responders and their corresponding diagnosis efficacy (range: 0.703–0.767). The PR group patients after one NAC cycle showed persistent inhibition of tumor perfusion by NAC as explored by DCE-MRI parameters comparing to the SD group (P < 0.05) and presented a higher cure ratio after IMRT than those who did not (83.3% vs. 73.8%).ConclusionsThis primarily DCE-MRI based study showed that the early changes of the kinetic parameters during therapy were potential imaging markers to predicting response right after one NAC cycle for NPC patients.     

Prediction of early response to concurrent chemoradiotherapy in cervical cancer: Value of multi-parameter MRI combined with clinical prognostic factors

PurposeThis study aimed to investigate the prediction of early response to concurrent chemoradiotherapy (CCRT) through a combination of pretreatment multi-parametric magnetic resonance imaging (MRI) with clinical prognostic factors (CPF) in cervical cancer patients.MethodsEighty-five patients with pathologically confirmed cervical cancer underwent conventional MRI, intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI), and dynamic contrast-enhanced MRI (DCE-MRI) before CCRT. The patients were divided into non- and residual tumor groups according to post-treatment MRI. Univariable and multivariable analyses were performed to pretreatment MRI parameters and CPF between the two groups, and optimal thresholds and predictive performance for post-treatment residual tumor occurrence were estimated by drawing the receiver operating characteristic (ROC) curve.ResultsThere were 52 patients in non- and 33 in residual group. The residual group showed a lower perfusion fraction (f) value and volume transfer constant (K^trans) value, a higher apparent diffusion coefficient (ADC) value, diffusion coefficient (D) value and volume fraction of extravascular extracellular space (V_e) value, and a higher stage than the non-residual tumor group (all P < .05). D, K^trans, V_e and stage were independent prognostic factors. The combination of D, K^trans and V_e improved the diagnostic performance compared with individual MRI parameters. A further combination of these three MRI parameters with stage exhibited the highest predictive performance.ConclusionsPretreatment D, K^trans, V_e and stage were independent prognostic factors for cervical cancer. The predictive capacity of multi-parametric MRI was superior to individual MRI parameters. The combination of multi-parametric MRI with CPF further improved the predictive performance.     

Quantitative diffusion-weighted imaging and dynamic contrast-enhanced MR imaging for assessment of tumor aggressiveness in prostate cancer at 3T

PurposeTo compare diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MR imaging (DCE-MRI) for characterization of prostate cancer (PC).Methods104 PC patients who underwent prostate multiparametric MRI at 3T including DWI and DCE-MRI before MRI-guided biopsy or radical prostatectomy. Apparent diffusion coefficient (ADC) with histogram analysis (mean, 0–25th percentile, skewness, and kurtosis), intravoxel incoherent motion model including D and f; stretched exponential model including distributed diffusion coefficient (DDC) and a; and permeability parameters including K^trans, K_ep, and V_e were obtained from a region of interest placed on the dominant tumor of each patient.ResultsADC_mean, ADC_0–25, D, DDC, and V_e were significantly lower and K_ep was significantly higher in GS ≥ 3 + 4 tumors (n = 89) than in GS = 3 + 3 tumors (n = 15), and also in GS ≥ 4 + 3 tumors (n = 57) than in GS ≤ 3 + 4 tumors (n = 47) (P < 0.001 to P = 0.040). f was significantly lower in GS ≥ 4 + 3 tumors than in GS ≤ 3 + 4 tumors (P = 0.022), but there was no significant difference between GS = 3 + 3 tumors and GS ≥ 3 + 4 tumors, or between the remaining metrics in both comparisons. In metrics with area under the curve (AUC) >0.80, there was a significant difference in AUC between ADC_0–25 and D, and DDC for separating GS ≤ 3 + 4 tumors from GS ≥ 4 + 3 tumors (P = 0.040 and P = 0.022, respectively). There were no significant differences between metrics with AUC > 0.80 for separating GS = 3 + 3 tumors from GS ≥ 3 + 4 tumors. ADC_0–25 had the highest correlation with Gleason grade (ρ = −0.625, P < 0.001).ConclusionsDWI and DCE-MRI showed no apparent clinical superiority of non-Gaussian models or permeability MRI over the mono-exponential model for assessment of tumor aggressiveness in PC.     

Dynamic contrast-enhanced MRI of gastric cancer: Correlations of the pharmacokinetic parameters with histological type,Lauren classification,and angiogenesis

PurposeTo compare the pharmacokinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in gastric cancers of different histological type and Lauren classification, and to investigate whether DCE-MRI parameters correlate with vascular endothelial growth factor (VEGF) expression levels in gastric cancer.MethodsIncluded were 32 patients with gastric cancer who underwent DCE-MRI of the upper abdomen before tumor resection. DCE-MRI parameters including the volume transfer coefficient (K^trans), reverse reflux rate constant (K_ep), and extracellular extravascular volume fraction (V_e) were calculated from the tumor region. Post-operative specimens were used for determination of histological differentiation (i.e., non-mucinous, mucinous, or signet-ring-cell adenocarcinoma) as well as Lauren classification (intestinal type or diffuse type). VEGF expression was examined for assessing angiogenesis. DCE-MRI parameters with different histological type and Lauren classification were compared using independent samples t-test and analysis of variance, respectively. Correlations between DCE-MRI parameters and VEGF expression grades were tested using Spearman correlation analysis.ResultsAmong gastric adenocarcinomas of three different histological types, mucinous adenocarcinomas showed a higher V_e and lower K^trans than the others (P < 0.01). Between the two Lauren classifications, the diffuse type showed a higher V_e than the intestinal type (P < 0.001). The mean K^trans showed a significantly positive correlation with VEGF (r = 0.762, P < 0.001).ConclusionDCE-MRI permits noninvasive prediction of tumor histological type and Lauren classification and estimation of tumor angiogenesis in gastric cancer. DCE-MRI parameters can be used as imaging biomarkers to predict the biologic aggressiveness of a tumor as well as patient prognosis.     

Discrimination between malignant and benign thyroid tumors by diffusion-weighted imaging – A systematic review and meta analysis

PurposeMagnetic resonance imaging is used to stage thyroid tumors. Diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) can be used to reflect tumor microstructure. Our aim was to compare ADC values of malignant and benign thyroid lesions based on a large sample.MethodsMEDLINE library, EMBASE and SCOPUS databases were screened for the associations between ADC values and thyroid lesions up to August 2021. The primary endpoint of the systematic review were ADC values of benign and malignant thyroid lesions. In total, 29 studies were suitable for the analysis and were included into the present study.ResultsThe included studies comprised a total of 2137 lesions, 1118 (52.3%) benign and 1019 (47.7%) malignant lesions. The pooled mean ADC value of the benign thyroid lesions was 1.88 × 10⁻³ mm²/s [95% CI 1.77–2.0] and the pooled mean ADC value of malignant thyroid lesions was 1.15 × 10⁻³ mm²/s [95% CI 1.04–1.25].ConclusionsADC can well discriminate benign and malignant thyroid tumors. Therefore, DWI should be implemented into the presurgical diagnostic work-up in clinical routine.     

Flow versus permeability weighting in estimating the forward volumetric transfer constant (Ktrans) obtained by DCE-MRI with contrast agents of differing molecular sizes

PurposeTo quantify the differential plasma flow- (F_p-) and permeability surface area product per unit mass of tissue- (PS-) weighting in forward volumetric transfer constant (K^trans) estimates by using a low molecular (Gd-DTPA) versus high molecular (Gadomer) weight contrast agent in dynamic contrast enhanced (DCE) MRI.Materials and methodsDCE MRI was performed using a 7T animal scanner in 14 C57BL/6J mice syngeneic for TRAMP tumors, by administering Gd-DTPA (0.9 kD) in eight mice and Gadomer (35 kD) in the remainder. The acquisition time was 10 min with a sampling rate of one image every 2 s. Pharmacokinetic modeling was performed to obtain K^trans by using Extended Tofts model (ETM). In addition, the adiabatic approximation to the tissue homogeneity (AATH) model was employed to obtain the relative contributions of F_p and PS.ResultsThe K^trans values derived from DCE-MRI with Gd-DTPA showed significant correlations with both PS (r² = 0.64, p = 0.009) and F_p (r² = 0.57, p = 0.016), whereas those with Gadomer were found only significantly correlated with PS (r² = 0.96, p = 0.0003) but not with F_p (r² = 0.34, p = 0.111). A voxel-based analysis showed that K^trans approximated PS (< 30% difference) in 78.3% of perfused tumor volume for Gadomer, but only 37.3% for Gd-DTPA.ConclusionsThe differential contributions of F_p and PS in estimating K^trans values vary with the molecular weight of the contrast agent used. The macromolecular contrast agent resulted in K^trans values that were much less dependent on flow. These findings support the use of macromolecular contrast agents for estimating tumor vessel permeability with DCE-MRI.     

A multiparametric approach to diagnosing breast lesions using diffusion-weighted imaging and ultrafast dynamic contrast-enhanced MRI

PurposeTo evaluate the diagnostic performance of a multiparametric approach to breast lesions including apparent diffusion coefficient (ADC) from diffusion-weighted images (DWI), maximum slope (MS) from ultrafast dynamic contrast enhanced (UF-DCE) MRI, lesion size, and patient's age.Materials and methodsIn total, 96 lesions (73 malignant, 23 benign) were evaluated. UF-DCE MRI was acquired using a prototype 3D-gradient-echo volumetric interpolated breath-hold examination (VIBE) with compressed sensing. Images were obtained up to 1 min after gadolinium injection. MS was calculated as the percentage relative enhancement/s. An ADC map was automatically generated from DWI at b = 0 and b = 1000 s/mm². MS and ADC values were measured by two radiologists independently. Interrater agreement was evaluated using intraclass correlation coefficients. Univariate and multivariate logistic regression analyses were performed using MS, ADC, lesion size, and the patient's age. The parameters of the prediction model were generated from the results of the multivariate logistic regression analysis. Area under the curve (AUC) was used to compare diagnostic performance of the prediction model and each parameter.ResultsInterrater agreements on MS and ADC were excellent (ICC 0.99 and 0.88, respectively). MS, ADC, and patient's age remained as significant parameters after univariate and multivariate logistic regression analysis. The prediction model using these significant parameters yielded an AUC of 0.90, significantly higher than that of MS (AUC 0.74, p = 0.01). The AUCs of ADC, MS, patient's age were 0.87, 0.74 and 0.73, respectively.ConclusionsA multiparametric model using ADC from DWI, MS from UF-DCE MRI, and patient's age showed excellent diagnostic performance, with greater contribution of ADC. Combining DWI and UF-DCE MRI might reduce scanning time while preserving diagnostic performance.     

Differentiation of myeloma and metastatic cancer in the spine using dynamic contrast-enhanced MRI

Spinal myeloma and metastatic cancer cause similar symptoms and show similar imaging presentations, thus making them difficult to differentiate. In this study, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was performed to differentiate between 9 myelomas and 22 metastatic cancers that present as focal lesions in the spine. The characteristic DCE parameters, including the peak signal enhancement percentage (SE%), the steepest wash-in SE% during the ascending phase and the wash-out SE%, were calculated by normalizing to the precontrast signal intensity. The two-compartmental pharmacokinetic model was used to obtain K^trans and k_ep. All nine myelomas showed the wash-out DCE pattern. Of the 22 metastatic cancers, 12 showed wash-out, 7 showed plateau, and 3 showed persistent enhancing patterns. The fraction of cases that showed the wash-out pattern was significantly higher in the myeloma group than the metastatic cancer group (9/9 = 100% vs. 12/22 = 55%, P = .03). Compared to the metastatic cancer group, the myeloma group had a higher peak SE% (226% ± 72% vs. 165% ± 60%, P = .044), a higher steepest wash-in SE% (169% ± 51% vs. 111% ± 41%, P = .01), a higher K^trans (0.114 ± 0.036 vs. 0.077 ± 0.028 1/min, P = .016) and a higher k_ep (0.88 ± 0.26 vs. 0.49 ± 0.23 1/min, P = .002). The receiver operating characteristic analysis to differentiate between these two groups showed that the area under the curve was 0.798 for K^trans, 0.864 for k_ep and 0.919 for combined K^trans and k_ep. These results show that DCE-MRI may provide additional information for making differential diagnosis to aid in choosing the optimal subsequent procedures or treatments for spinal lesions.     

Assessment of early response to concurrent chemoradiotherapy in cervical cancer: value of diffusion-weighted and dynamic contrast-enhanced MR imaging

Purpose

To investigate diffusion-weighted (DWI) and dynamic contrast-enhanced MR imaging (DCE-MRI) as early response predictors in cervical cancer patients who received concurrent chemoradiotherapy (CCRT).

Materials and methods

Sixteen patients with cervical cancer underwent DWI and DCE-MRI before CCRT (preTx), at 1 week (postT1) and 4 weeks (postT2) after initiating treatment, and 1 month after the end of treatment (postT3). At each point, apparent diffusion coefficient (ADC) and DCE-MRI parameters were measured in tumors and gluteus muscles (GM). Tumor response was correlated with imaging parameters or changes in imaging parameters at each point.

Results

At each point, ADC, K^trans and V_e in tumors showed significant changes (P < 0.05), as compared with those of GM (P > 0.05). PostT1 tumor ADCs showed a significant correlation with tumor size response at postT2 (P = 0.041), and changes in tumor ADCs at postT1 had a significant correlation with tumor size (P = 0.04) and volume response (P = 0.003) at postT2. In tumors, preTx K^trans and V_e showed significant correlations with tumor size at postT3 (P = 0.011) and tumor size response at postT2 (P = 0.019), respectively.

Conclusion

DWI and DCE-MRI, as early biomarkers, have the potential to evaluate therapeutic responses to CCRT in cervical cancers.     

A comprehensive evaluation and impact of normalization of generalized tracer kinetic model parameters to characterize blood-brain-barrier permeability in normal-appearing and tumor tissue regions of patients with glioma

Rationale and objectivesTo comprehensively evaluate robustness and variations of DCE-MRI derived generalized-tracer-kinetic-model (GTKM) parameters in healthy and tumor tissues and impact of normalization in mitigating these variations on application to glioma.Materials (patients) and methodsA retrospective study included pre-operative 31 high-grade-glioma(HGG), 22 low-grade-glioma(LGG) and 33 follow-up data from 10 patients a prospective study with 4 HGG subjects. Voxel-wise GTKM was fitted to DCE-MRI data to estimate K^trans, v_e, v_b. Simulations were used to evaluate noise sensitivity. Variation of parameters with-respect-to arterial-input-function (AIF) variation and data length were studied. Normalization of parameters with-respect-to mean values in gray-matter (GM) and white-matter (WM) regions (GM-Type-2, WM-Type-2) and mean curves (GM-Type-1, WM-Type-1) were also evaluated. Co-efficient-of-variation(CoV), relative-percentage-error (RPE), Box-Whisker plots, bar graphs and t-test were used for comparison.ResultsGTKM was fitted well in all tissue regions. K^trans and v_e in contrast-enhancing (CE) has shown improved noise sensitivity in longer data. v_b was reliable in all tissues. Mean AIF and C(t) peaks showed ~38% and ~35% variations. During simulation, normalizations have mitigated variations due to changes in AIF amplitude in K^trans and v_b.. v_e was less sensitive to normalizations. CoV of K^trans and v_b has reduced ~70% after GM-Type-1 normalization and ~80% after GM-Type-2 normalization, respectively. GM-Type-1 (p = 0.003) and GM-Type-2 (p = 0.006) normalizations have significantly improved differentiation of HGG and LGG using K^trans.ConclusionK^trans and v_b can be reliably estimated in normal-appearing brain tissues and can be used for normalization of corresponding parameters in tumor tissues for mitigating inter-subject variability due to errors in AIF. Normalized K^trans and v_b provided improved differentiation of HGG and LGG.     

Intravoxel incoherent motion diffusion-weighted imaging as an adjunct to dynamic contrast-enhanced MRI to improve accuracy of the differential diagnosis of benign and malignant breast lesions

PurposeTo investigate the value of use of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) as an adjunct to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to distinguish benign from malignant breast lesions.Materials and methodsRetrospective analysis of data pertaining to 117 patients with breast lesions who underwent DCE-MRI and IVIM-DWI examination with 3.0 T MRI was conducted. A total of 128 lesions were pathologically confirmed (47 benign and 81 malignant). Between-group differences in DCE-MRI parameters (Morphology, enhancement pattern, maximum slope of increase (MSI) and time–signal curve (TIC) type) and IVIM-DWI parameters (f value, D value and D* value) were assessed. Multivariate logistic regression was performed to identify variables that distinguished benign from malignant breast lesions. The diagnostic performance of DCE-MRI and DCE-MRI plus IVIM-DWI, to distinguish benign from malignant breast lesions, was evaluated using pathology results as the gold standard.ResultsLesion morphology, MSI, and TIC type (P < 0.05), but not the enhancement pattern (P > 0.05), were significantly different between the benign and malignant groups. The f (8.53 ± 2.14) and D* (7.64 ± 2.07) values in the malignant group were significantly higher than those in the benign group (7.68 ± 1.97 and 6.83 ± 2.13, respectively), while the D value (0.99 ± 0.22) was significantly lower than that (1.34 ± 0.17) in the benign group (P < 0.05 for all). On logistic regression analysis, the sensitivity, specificity and accuracy of DCE-MRI were 90.1%, 70.2% and 82.8% respectively; the corresponding figures for the combination of IVIM-DWI and DCE-MRI were 88.8%, 85.1%, and 87.5%respectively.ConclusionIVIM-DWI method as an adjunct to DCE-MRI can improve the specificity and accuracy in differential diagnosis of benign and malignant lesions of breast.     

Dynamic contrast-enhanced magnetic resonance imaging parameters independent of baseline T10 values

A baseline T₁₀ value is typically needed for dynamic contrast-enhanced (DCE-) MRI studies. However, an assumed baseline T₁₀ has to be used when T₁₀ measurements for patients are not available. In this work, we systematically investigate the dependence on T₁₀ of the commonly used DCE-MRI parameters (K^trans, k_ep, v_e and IAUC) as well as several newly defined parameters [the normalized ratios (NRs) of k_ep, K^trans and v_e, which are measures of relative changes in these parameters between two time points] for a spoiled gradient-echo pulse sequence using simulations and in vivo studies. Effects of various factors on the T₁₀ dependence, such as the true T₁₀ value, flip angle and the potential changes in T₁₀ due to treatment, were also assessed using simulations. We found that DCE-MRI parameters k_ep and the NR of k_ep are largely independent of T₁₀, especially when larger flip angles are used (e.g., 30–40°). Their estimations therefore do not require any knowledge of T₁₀. The NRs of K^trans, v_e and IAUC also exhibit independence to T₁₀, but only when T₁₀ remains constant between pre- and posttreatment. The estimation of parameters themselves (K^trans, v_e and IAUC) is highly dependent on the T₁₀ value.     

Repeatability of arterial input functions and kinetic parameters in muscle obtained by dynamic contrast enhanced MR imaging of the head and neck

BackgroundQuantification of pharmacokinetic parameters in dynamic contrast enhanced (DCE) MRI is heavily dependent on the arterial input function (AIF). In the present patient study on advanced stage head and neck squamous cell carcinoma (HNSCC) we have acquired DCE-MR images before and during chemo radiotherapy. We determined the repeatability of image-derived AIFs and of the obtained kinetic parameters in muscle and compared the repeatability of muscle kinetic parameters obtained with image-derived AIF's versus a population-based AIF.Materials and methodsWe compared image-derived AIFs obtained from the internal carotid, external carotid and vertebral arteries. Pharmacokinetic parameters (v_e, K^trans, k_ep) in muscle—located outside the radiation area—were obtained using the Tofts model with the image-derived AIFs and a population averaged AIF. Parameter values and repeatability were compared. Repeatability was calculated with the pre- and post-treatment data with the assumption of no DCE-MRI measurable biological changes between the scans.ResultsSeveral parameters describing magnitude and shape of the image-derived AIFs from the different arteries in the head and neck were significantly different. Use of image-derived AIFs led to higher pharmacokinetic parameters compared to use of a population averaged AIF. Median muscle pharmacokinetic parameters values obtained with AIFs in external carotids, internal carotids, vertebral arteries and with a population averaged AIF were respectively: v_e (0.65, 0.74, 0.58, 0.32), K^trans (0.30, 0.21, 0.13, 0.06), k_ep (0.41, 0.32, 0.24, 0.18). Repeatability of pharmacokinetic parameters was highest when a population averaged AIF was used; however, this repeatability was not significantly different from image-derived AIFs.ConclusionImage-derived AIFs in the neck region showed significant variations in the AIFs obtained from different arteries, and did not improve repeatability of the resulting pharmacokinetic parameters compared with the use of a population averaged AIF. Therefore, use of a population averaged AIF seems to be preferable for pharmacokinetic analysis using DCE-MRI in the head and neck area.     

Effects of arterial input function selection on kinetic parameters in brain dynamic contrast-enhanced MRI

PurposeKinetic parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) were suggested as a possible instrument for multi-parametric lesion characterization, but have not found their way into clinical practice yet due to inconsistent results. The quantification is heavily influenced by the definition of an appropriate arterial input functions (AIF). Regarding brain tumor DCE-MRI, there are currently several co-existing methods to determine the AIF frequently including different brain vessels as sources. This study quantitatively and qualitatively analyzes the impact of AIF source selection on kinetic parameters derived from commonly selected AIF source vessels compared to a population-based AIF model.Material and methods74 patients with brain lesions underwent 3D DCE-MRI. Kinetic parameters [transfer constants of contrast agent efflux and reflux K^trans and k_ep and, their ratio, v_e, that is used to measure extravascular-extracellular volume fraction and plasma volume fraction v_p] were determined using extended Tofts model in 821 ROI from 4 AIF sources [the internal carotid artery (ICA), the closest artery to the lesion, the superior sagittal sinus (SSS), the population-based Parker model]. The effect of AIF source alteration on kinetic parameters was evaluated by tissue type selective intra-class correlation (ICC) and capacity to differentiate gliomas by WHO grade [area under the curve analysis (AUC)].ResultsArterial AIF more often led to implausible v_e > 100% values (p < 0.0001). AIF source alteration rendered different absolute kinetic parameters (p < 0.0001), except for k_ep. ICC between kinetic parameters of different AIF sources and tissues were variable (0.08–0.87) and only consistent > 0.5 between arterial AIF derived kinetic parameters. Differentiation between WHO III and II glioma was exclusively possible with v_p derived from an AIF in the SSS (p = 0.03; AUC 0.74).ConclusionThe AIF source has a significant impact on absolute kinetic parameters in DCE-MRI, which limits the comparability of kinetic parameters derived from different AIF sources. The effect is also tissue-dependent. The SSS appears to be the best choice for AIF source vessel selection in brain tumor DCE-MRI as it exclusively allowed for WHO grades II/III and III/IV glioma distinction (by v_p) and showed the least number of implausible v_e values.     

Diagnostic performance of apparent diffusion coefficient and quantitative kinetic parameters for predicting additional malignancy in patients with newly diagnosed breast cancer

Purpose

To evaluate the diagnostic performance of an apparent diffusion coefficient (ADC) and quantitative kinetic parameters in patients with newly diagnosed breast cancer.

Materials and Methods

We enrolled 169 lesions in 89 patients with breast cancer who underwent dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI). Comparisons between benign and malignant lesions were performed for lesion type (mass or nonmass-like enhancement), size (≥ 1 cm or < 1 cm), ADC, kinetic parameters and the presence of a US correlate.

Results

There were 63 benign and 106 malignant lesions. The mean size and initial peak enhancement of the benign lesions were significantly lower than those of malignant lesions (P < 0.001 for both). The ADC of the benign lesions was significantly higher than that of malignant lesions (1.42 × 10^− 3 mm²/sec vs. 1.04 × 10^− 3 mm²/sec; P < 0.001). The area under the receiver operating characteristic curve (AUC) for predicting malignancy was 0.87 for the combined parameters of size, ADC, and initial peak enhancement, which was higher than those of each parameter.

Conclusions

Combination of quantitative kinetic parameters and ADC showed higher diagnostic performance for predicting malignancy than each parameter alone for the evaluation of patients with breast cancer.     

Studies of pathology and VEGF expression in rabbit cerebrospinal fluid metastasis: application of dynamic contrast-enhanced MRI

Objective

The objective was to analyze the correlation of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with vascular endothelial growth factor (VEGF) protein expression and to assess the potential application of DCE-MRI to the rabbit cerebrospinal fluid (CSF) metastasis model.

Methods

Thirty New Zealand rabbits were divided into experimental and control groups. In the experimental group, VX2 tumor cells were injected into the subarachnoid space at the plane of cisterna magna in 24 rabbits. In the control group, physiological saline was injected into the subarachnoid space at the plane of cisterna magna in six rabbits. DCE-MRI was performed at multiple time points, and several pharmacokinetic parameters, including K^trans, K_ep and V_e, were calculated. Also, VEGF levels in plasma and CSF were evaluated by enzyme-linked immunosorbent assay prior to DCE-MRI examination. After DCE-MRI examination, the rabbits were sacrificed, and the corresponding tumor specimens were harvested. Hematoxylin–eosin staining and VEGF immunohistochemical staining were carried out, and VEGF expression in the specimens was evaluated by the immunohistochemical scoring system.

Results

Vascular endothelial growth factor positive staining was localized in the cytoplasm and cell membranes of tumor cells, as well as in a subset of epithelial cells. Both VEGF immunohistochemical scores and VEGF expression in CSF and plasma exhibited positive correlations with K^trans and K_ep values as demonstrated by rank correlation statistical analysis.

Conclusions

Vascular endothelial growth factor expression in plasma and CSF in the CSF metastasis model was higher than in normal tissues. Therefore, DCE-MRI reliably indicated VEGF expression in the rabbit CSF metastasis model.     

Reconstruction of dynamic contrast enhanced magnetic resonance imaging of the breast with temporal constraints

A number of methods using temporal and spatial constraints have been proposed for reconstruction of undersampled dynamic magnetic resonance imaging (MRI) data. The complex data can be constrained or regularized in a number of different ways, for example, the time derivative of the magnitude and phase image voxels can be constrained separately or jointly. Intuitively, the performance of different regularizations will depend on both the data and the chosen temporal constraints. Here, a complex temporal total variation (TV) constraint was compared to the use of separate real and imaginary constraints, and to a magnitude constraint alone. Projection onto Convex Sets (POCS) with a gradient descent method was used to implement the diverse temporal constraints in reconstructions of DCE MRI data. For breast DCE data, serial POCS with separate real and imaginary TV constraints was found to give relatively poor results while serial/parallel POCS with a complex temporal TV constraint and serial POCS with a magnitude-only temporal TV constraint performed well with an acceleration factor as large as R=6. In the tumor area, the best method was found to be parallel POCS with complex temporal TV constraint. This method resulted in estimates for the pharmacokinetic parameters that were linearly correlated to those estimated from the fully-sampled data, with K^trans,R=6=0.97 K^trans,R=1+0.00 with correlation coefficient r=0.98, k_ep,R=6=0.95 k_ep,R=1+0.00 (r=0.85). These results suggest that it is possible to acquire highly undersampled breast DCE-MRI data with improved spatial and/or temporal resolution with minimal loss of image quality.