Dynamic Contrast-enhanced Perfusion MR Imaging Research Articles

Differentiating Low-Grade from High-Grade Intracranial Ependymomas: Comparison of Dynamic Contrast-Enhanced MRI and Diffusion-Weighted Imaging.

The aim of this study was to determine the diagnostic value of fractional plasma volume derived from dynamic contrast-enhanced perfusion MR imaging versus ADC, obtained from DWI in differentiating between grade 2 (low-grade) and grade 3 (high-grade) intracranial ependymomas. A hospital database was created for the period from January 2013 through June 2022, including patients with histologically-proved ependymoma diagnosis with available dynamic contrast-enhanced MR imaging. Both dynamic contrast-enhanced perfusion and DWI were performed on each patient using 1.5T and 3T scanners. Fractional plasma volume maps and ADC maps were calculated. ROIs were defined by a senior neuroradiologist manually by including the enhancing tumor on every section and conforming a VOI to obtain the maximum value of fractional plasma volume (Vpmax) and the minimum value of ADC (ADCmin). A Mann-Whitney U test at a significance level of corrected P = .01 was used to evaluate the differences. Additionally, receiver operating characteristic curve analysis was applied to assess the sensitivity and specificity of Vpmax and ADCmin values. A total of 20 patients with ependymomas (10 grade 2 tumors and 10 grade 3 tumors) were included. Vpmax values for grade 3 ependymomas were significantly higher (P < .002) than those for grade 2. ADCmin values were overall lower in high-grade lesions. However, no statistically significant differences were found (P = .12114). As a dynamic contrast-enhanced perfusion MR imaging metric, fractional plasma volume can be used as an indicator to differentiate grade 2 and grade 3 ependymomas. Dynamic contrast-enhanced perfusion MR imaging plays an important role with high diagnostic value in differentiating low- and high-grade ependymoma.

Looking through the imaging perspective: the importance of imaging necrosis in glioma diagnosis and prognostic prediction - single centre experience.

The aim of the study was to investigate the diagnostic value of imaging necrosis (Imnecrosis) in grading, predict the genotype and prognosis of gliomas, and further assess tumor necrosis by dynamic contrast-enhanced MR perfusion imaging (DCE-MRI). We retrospectively included 150 patients (104 males, mean age: 46 years old) pathologically proved as adult diffuse gliomas and all diagnosis was based on the 2021 WHO central nervous system (CNS) classification. The pathological necrosis (Panecrosis) and gene mutation information were collected. All patients underwent conventional and DCE-MRI examinations and had been followed until May 31, 2021. The Imnecrosis was determined by two experienced neuroradiologists. DCE-MRI derived metric maps have been post-processed, and the mean value of each metric in the tumor parenchyma, peritumoral and contralateral area were recorded. There was a strong degree of inter-observer agreement in defining Imnecrosis (Kappa = 0.668, p < 0.001) and a strong degree of agreement between Imnecrosis and Panecrosis (Kappa = 0.767, p < 0.001). Compared to low-grade gliomas, high-grade gliomas had more Imnecrosis (85.37%, p < 0.001), and Imnecrosis significantly increased with the grade of gliomas increasing. And Imnecrosis was significantly more identified in IDH-wildtype, 1p19q-non-codeletion, and CDKN2A/B-homozygous-deletion gliomas. Using multivariate Cox regression analysis, Imnecrosis was an independent and unfavorable prognosis factor (Hazard Ratio = 2.113, p = 0.046) in gliomas. Additionally, extravascular extracellular volume fraction (ve) in tumor parenchyma derived from DCE-MRI demonstrated the highest diagnostic efficiency in identifying Panecrosis and Imnecrosis with high specificity (83.3% and 91.9%, respectively). Imnecrosis can provide supplementary evidence beyond Panecrosis in grading, predicting the genotype and prognosis of gliomas, and ve in tumor parenchyma can help to predict tumor necrosis with high specificity.

T1-Weighted, Dynamic Contrast-Enhanced MR Perfusion Imaging Can Differentiate between Treatment Success and Failure in Spine Metastases Undergoing Radiation Therapy.

Current imaging techniques have difficulty differentiating treatment success and failure in spinal metastases undergoing radiation therapy. This study investigated the correlation between changes in dynamic contrast-enhanced MR imaging perfusion parameters and clinical outcomes following radiation therapy for spinal metastases. We hypothesized that perfusion parameters will outperform traditional size measurements in discriminating treatment success and failure. This retrospective study included 49 patients (mean age, 63 [SD, 13] years; 29 men) with metastatic lesions treated with radiation therapy who underwent dynamic contrast-enhanced MR imaging. The median time between radiation therapy and follow-up dynamic contrast-enhanced MR imaging was 62 days. We divided patients into 2 groups: clinical success (n = 38) and failure (n = 11). Failure was defined as PET recurrence (n = 5), biopsy-proved (n = 1) recurrence, or an increase in tumor size (n = 7), while their absence defined clinical success. A Mann-Whitney U test was performed to assess differences between groups. The reduction in plasma volume was greater in the success group than in the failure group (-57.3% versus +88.2%, respectively; P < .001). When we assessed the success of treatment, the sensitivity of plasma volume was 91% (10 of 11; 95% CI, 82%-97%) and the specificity was 87% (33 of 38; 95% CI, 73%-94%). The sensitivity of size measurements was 82% (9 of 11; 95% CI, 67%-90%) and the specificity was 47% (18 of 38; 95% CI, 37%-67%). The specificity of plasma volume was higher than that of conventional size measurements, suggesting that dynamic contrast-enhanced MR imaging is a powerful tool to discriminate between treatment success and failure.

Differentiation of Skull Base Chondrosarcomas, Chordomas, and Metastases: Utility of DWI and Dynamic Contrast-Enhanced Perfusion MR Imaging.

Differentiation of skull base tumors, including chondrosarcomas, chordomas, and metastases, on conventional imaging remains a challenge. We aimed to test the utility of DWI and dynamic contrast-enhanced MR imaging for skull base tumors. Fifty-nine patients with chondrosarcomas, chordomas, or metastases between January 2015 and October 2021 were included in this retrospective study. Pretreatment normalized mean ADC and dynamic contrast-enhanced MR imaging parameters were calculated. The Kruskal-Wallis H test for all tumor types and the Mann-Whitney U test for each pair of tumors were used. Fifteen chondrosarcomas (9 men; median age, 62 years), 14 chordomas (6 men; median age, 47 years), and 30 metastases (11 men; median age, 61 years) were included in this study. Fractional plasma volume helped distinguish all 3 tumor types (P = .003, <.001, and <.001, respectively), whereas the normalized mean ADC was useful in distinguishing chondrosarcomas from chordomas and metastases (P < .001 and P < .001, respectively); fractional volume of extracellular space, in distinguishing chondrosarcomas from metastases (P = .02); and forward volume transfer constant, in distinguishing metastases from chondrosarcomas/chondroma (P = .002 and .002, respectively) using the Kruskal-Wallis H test. The diagnostic performances of fractional plasma volume for each pair of tumors showed areas under curve of 0.86-0.99 (95% CI, 0.70-1.0); the forward volume transfer constant differentiated metastases from chondrosarcomas/chordomas with areas under curve of 0.82 and 0.82 (95% CI, 0.67-0.98), respectively; and the normalized mean ADC distinguished chondrosarcomas from chordomas/metastases with areas under curve of 0.96 and 0.95 (95% CI, 0.88-1.0), respectively. DWI and dynamic contrast-enhanced MR imaging sequences can be beneficial for differentiating the 3 common skull base tumors.

Diagnostic Role of Diffusion-Weighted and Dynamic Contrast-Enhanced Perfusion MR Imaging in Paragangliomas and Schwannomas in the Head and Neck.

Distinguishing schwannomas from paragangliomas in the head and neck and determining succinate dehydrogenase (SDH) mutation status in paragangliomas are clinically important. We aimed to assess the clinical usefulness of DWI and dynamic contrast-enhanced MR imaging in differentiating these 2 types of tumors, as well as the SDH mutation status of paragangliomas. This retrospective study from June 2016 to June 2020 included 42 patients with 15 schwannomas and 27 paragangliomas (10 SDH mutation-positive and 17 SDH mutation-negative). ADC values, dynamic contrast-enhanced MRI parameters, and tumor imaging characteristics were compared between the 2 tumors and between the mutation statuses of paragangliomas as appropriate. Multivariate stepwise logistic regression analysis was performed to identify significant differences in these parameters. Fractional plasma volume (P ≤ .001), rate transfer constant (P = .038), time-to-maximum enhancement (P < .001), maximum signal-enhancement ratio (P < .001) and maximum concentration of contrast agent (P < .001), velocity of enhancement (P = .002), and tumor characteristics including the presence of flow voids (P = .001) and enhancement patterns (P = .027) showed significant differences between schwannomas and paragangliomas, though there was no significant difference in ADC values. In the multivariate logistic regression analysis, fractional plasma volume was identified as the most significant value for differentiation of the 2 tumor types (P = .014). ADC values were significantly higher in nonhereditary than in hereditary paragangliomas, while there was no difference in dynamic contrast-enhanced MR imaging parameters. Dynamic contrast-enhanced MR imaging parameters show promise in differentiating head and neck schwannomas and paragangliomas, while DWI can be useful in detecting SDH mutation status in paragangliomas.

T1-Weighted Dynamic Contrast-Enhanced MR Perfusion Imaging Characterizes Tumor Response to Radiation Therapy in Chordoma.

Chordomas notoriously demonstrate a paucity of changes following radiation therapy on conventional MR imaging. We hypothesized that dynamic contrast-enhanced MR perfusion imaging parameters of chordomas would change significantly following radiation therapy. Eleven patients with pathology-proved chordoma who completed dynamic contrast-enhanced MR perfusion imaging pre- and postradiation therapy were enrolled. Quantitative tumor measurements were obtained by 2 attending neuroradiologists. ROIs were used to calculate vascular permeability and plasma volume and generate dynamic contrast-enhancement curves. Quantitative analysis was performed to determine mean and maximum plasma volume and vascular permeability values, while semiquantitative analysis on averaged concentration curves was used to determine the area under the curve. A Mann-Whitney U test at a significance level of P < .05 was used to assess differences of the above parameters between pre- and postradiation therapy. Plasma volume mean (pretreatment mean = 0.82; posttreatment mean = 0.42), plasma volume maximum (pretreatment mean = 3.56; posttreatment mean = 2.27), and vascular permeability mean (pretreatment mean = 0.046; posttreatment mean = 0.028) in the ROIs significantly decreased after radiation therapy (P < .05); this change thereby demonstrated the potential for assessing tumor response. Area under the curve values also demonstrated significant differences (P < .05). Plasma volume and vascular permeability decreased after radiation therapy, suggesting that these dynamic contrast-enhanced MR perfusion parameters may be useful for monitoring chordoma growth and response to radiation therapy. Additionally, the characteristic dynamic MR signal intensity-time curve of chordoma may provide a radiographic means of distinguishing chordoma from other spinal lesions.

Assessment of Semiquantitative Parameters of Dynamic Contrast-Enhanced Perfusion MR Imaging in Differentiation of Subtypes of Renal Cell Carcinoma.

SummaryBackgroundTo assess semiquantitative parameters of dynamic contrast-enhanced perfusion MR imaging (DCE) in differentiation of subtypes of renal cell carcinoma (RCC).Material/MethodsProspective study conducted upon 34 patients (27 M, 7 F, aged 25–72 ys: mean 45 ys) with RCC. Abdominal dynamic contrast-enhanced gradient-recalled echo MR sequence after administration of gadopentetate dimeglumine was obtained. The time signal intensity curve (TIC) of the lesion was created with calculation of enhancement ratio (ER), and washout ratio (WR).ResultsThe subtypes of RCC were as follows: clear cell carcinomas (n=23), papillary carcinomas (n=6), and chromophobe carcinomas (n=5). The mean ER of clear cell, papillary and chromophobe RCC were 188±49.7, 35±8.9, and 120±41.6 respectively. The mean WR of clear cell, papillary and chromophobe RCCs were 28.6±6.8, 47.6±5.7 and 42.7±10, respectively. There was a significant difference in ER (P=0.001) and WR (P=0.001) between clear cell RCC and other subtypes of RCC. The threshold values of ER and WR used for differentiating clear cell RCC from other subtypes of RCC were 142 and 38 with areas under the curve of 0.937 and 0.895, respectively.ConclusionsWe concluded that ER and WR are semiquantitative perfusion parameters useful in differentiation of clear cell RCC from chromophobe and papillary RCCs.

Clinical utility of multimodality imaging with dynamic contrast-enhanced MRI, diffusion-weighted MRI, and 18F-FDG PET/CT for the prediction of neck control in oropharyngeal or hypopharyngeal squamous cell carcinoma treated with chemoradiation.

The clinical usefulness of pretreatment imaging techniques for predicting neck control in patients with oropharyngeal or hypopharyngeal squamous cell carcinoma (OHSCC) treated with chemoradiation remains unclear. In this prospective study, we investigated the role of pretreatment dynamic contrast-enhanced perfusion MR imaging (DCE-PWI), diffusion-weighted MR imaging (DWI), and [18F]fluorodeoxyglucose-positron emission tomography (18F-FDG PET)/CT derived imaging markers for the prediction of neck control in OHSCC patients treated with chemoradiation. Patients with untreated OHSCC scheduled for chemoradiation between August, 2010 and July, 2012 were eligible for the study. Clinical variables and the following imaging parameters of metastatic neck lymph nodes were examined in relation to neck control: transfer constant, volume of blood plasma, and volume of extracellular extravascular space (Ve) on DCE-PWI; apparent diffusion coefficient (ADC) on DWI; maximum standardized uptake value, metabolic tumor volume, and total lesion glycolysis on 18F-FDG PET/CT. There were 69 patients (37 with oropharynx SCC and 32 with hypopharynx SCC) with successful pretreatment DCE-PWI and DWI available for analysis. After a median follow-up of 31 months, 25 (36.2%) participants had neck failure. Multivariate analysis identified hemoglobin level <14.3 g/dL (P = 0.019), Ve <0.23 (P = 0.040), and ADC >1.14×10−3 mm2/s (P = 0.003) as independent prognostic factors for 3-year neck control. A prognostic scoring system was formulated by summing up the three significant predictors of neck control. Patients with scores of 2–3 had significantly poorer neck control and overall survival rates than patients with scores of 0–1. We conclude that hemoglobin levels, Ve, and ADC are independent pretreatment prognostic factors for neck control in OHSCC treated with chemoradiation. Their combination may identify a subgroup of patients at high risk of developing neck failure.

Dynamic contrast-enhanced perfusion processing for neuroradiologists: model-dependent analysis may not be necessary for determining recurrent high-grade glioma versus treatment effect.

Dynamic contrast-enhanced perfusion MR imaging has proved useful in determining whether a contrast-enhancing lesion is secondary to recurrent glial tumor or is treatment-related. In this article, we explore the best method for dynamic contrast-enhanced data analysis. We retrospectively reviewed 24 patients who met the following conditions: 1) had at least an initial treatment of a glioma, 2) underwent a half-dose contrast agent (0.05-mmol/kg) diagnostic-quality dynamic contrast-enhanced perfusion study for an enhancing lesion, and 3) had a diagnosis by pathology within 30 days of imaging. The dynamic contrast-enhanced data were processed by using model-dependent analysis (nordicICE) using a 2-compartment model and model-independent signal intensity with time. Multiple methods of determining the vascular input function and numerous perfusion parameters were tested in comparison with a pathologic diagnosis. The best accuracy (88%) with good correlation compared with pathology (P = .005) was obtained by using a novel, model-independent signal-intensity measurement derived from a brief integration beginning after the initial washout and by using the vascular input function from the superior sagittal sinus for normalization. Modeled parameters, such as mean endothelial transfer constant > 0.05 minutes(-1), correlated (P = .002) but did not reach a diagnostic accuracy equivalent to the model-independent parameter. A novel model-independent dynamic contrast-enhanced analysis method showed diagnostic equivalency to more complex model-dependent methods. Having a brief integration after the first pass of contrast may diminish the effects of partial volume macroscopic vessels and slow progressive enhancement characteristic of necrosis. The simple modeling is technique- and observer-dependent but is less time-consuming.

Glioma: Application of Histogram Analysis of Pharmacokinetic Parameters from T1-Weighted Dynamic Contrast-Enhanced MR Imaging to Tumor Grading

The usefulness of pharmacokinetic parameters for glioma grading has been reported based on the perfusion data from parts of entire-tumor volumes. However, the perfusion values may not reflect the entire-tumor characteristics. Our aim was to investigate the feasibility of glioma grading by using histogram analyses of pharmacokinetic parameters including the volume transfer constant, extravascular extracellular space volume per unit volume of tissue, and blood plasma volume per unit volume of tissue from T1-weighted dynamic contrast-enhanced perfusion MR imaging. Twenty-eight patients (14 men, 14 women; mean age, 49.75 years; age range, 25-72 years) with histopathologically confirmed gliomas (World Health Organization grade II, n = 7; grade III, n = 8; grade IV, n = 13) were examined before surgery or biopsy with conventional MR imaging and T1-weighted dynamic contrast-enhanced perfusion MR imaging at 3T. Volume transfer constant, extravascular extracellular space volume per unit volume of tissue, and blood plasma volume per unit volume of tissue were calculated from the entire-tumor volume. Histogram analyses from these parameters were correlated with glioma grades. The parameters with the best percentile from cumulative histograms were identified by analysis of the area under the curve of the receiver operating characteristic analysis and were compared by using multivariable stepwise logistic regression analysis for distinguishing high- from low-grade gliomas. All parametric values increased with increasing glioma grade. There were significant differences among the 3 grades in all parameters (P < .01). For the differentiation of high- and low-grade gliomas, the highest area under the curve values were found at the 98th percentile of the volume transfer constant (area under the curve, 0.912; cutoff value, 0.277), the 90th percentile of extravascular extracellular space volume per unit volume of tissue (area under the curve, 0.939; cutoff value, 19.70), and the 84th percentile of blood plasma volume per unit volume of tissue (area under the curve, 0.769; cutoff value, 11.71). The 98th percentile volume transfer constant value was the only variable that could be used to independently differentiate high- and low-grade gliomas in multivariable stepwise logistic regression analysis. Histogram analysis of pharmacokinetic parameters from whole-tumor volume data can be a useful method for glioma grading. The 98th percentile value of the volume transfer constant was the most significant measure.

Dynamic Contrast-Enhanced MR Imaging Predicts Local Control in Oropharyngeal or Hypopharyngeal Squamous Cell Carcinoma Treated with Chemoradiotherapy

The role of pretreatment dynamic contrast-enhanced perfusion MR imaging (DCE-PWI) and diffusion-weighted MR imaging (DWI) in predicting the treatment response of oropharyngeal or hypopharyngeal squamous cell carcinoma (OHSCC) to chemoradiation remains unclear. We prospectively investigated the ability of pharmacokinetic parameters derived from pretreatment DCE-PWI and DWI to predict the local control of OHSCC patients treated with chemoradiation. Between August, 2010 and March, 2012, patients with untreated OHSCC scheduled for chemoradiation were eligible for this prospective study. DCE-PWI and DWI were performed in addition to conventional MRI. The relationship of local control with the following clinical and imaging variables was analyzed: the hemoglobin level, T-stage, tumor location, gross tumor volume, maximum standardized uptake value, metabolic tumor volume and total lesion glycolysis on FDG PET/CT, transfer constant (K trans), volume of blood plasma and volume of extracellular extravascular space on DCE-PWI, and apparent diffusion coefficient on DWI of the primary tumor. The patients were also divided into a local control group and a local failure group, and their clinical and imaging parameters were compared. There were 58 patients (29 with oropharynx squamous cell carcinoma [SCC] and 29 with hypopharynx SCC) with successful pretreatment DCE-PWI and DWI available for analysis. After a median follow-up of 18.2 months, 17 (29.3%) participants had local failure, whereas the remaining 41 patients achieved local control. Univariate analysis revealed that only the K trans value was significantly associated with local control (P = 0.03). When the local control and local failure groups were compared, significant differences were observed in K trans and the tumor location (P = 0.01 and P = 0.04, respectively). In the multivariable analysis, only K trans was statistically significant (P = 0.04). Our results suggest that pretreatment K trans may help predict the local control in OHSCC patients treated with chemoradiation.

Comparative study of three dimensional dynamic contrast-enhanced MR perfusion imaging in healthy volunteers and patients with chronic obstructive pulmonary disease

Objective To prospectively compare MR pulmonary perfusion imaging with quantitative HRCT for the detection of mild chronic obstructive pulmonary disease (COPD) and classification of COPD. Methods Sixty-two consecutive patients with COPD and 17 healthy volunteers underwent pulmonary function test (PFT),HRCT and MR perfusion imaging on the same day.According to the Global Initiative for Chronic Obstructive Lung Disease (GOLD),all COPD patients were classified into 4 stages:stageⅠ (n=19),stageⅡ (n=17),stageⅢ (n=14),stageⅣ Key words: Pulmonary disease,chronic obstructive; Respiratory function tests; Magnetic resonance imaging; Tomography,X-ray computed

Prediction of Pseudoprogression in Patients with Glioblastomas Using the Initial and Final Area Under the Curves Ratio Derived from Dynamic Contrast-Enhanced T1-Weighted Perfusion MR Imaging

Dynamic contrast-enhanced T1-weighted perfusion MR imaging is much less susceptible to artifacts, and its high spatial resolution allows accurate characterization of the vascular microenvironment of the lesion. The purpose of this study was to test the predictive value of the initial and final area under the time signal-intensity curves ratio derived from dynamic contrast-enhanced perfusion MR imaging to differentiate pseudoprogression from early tumor progression in patients with glioblastomas. Seventy-nine consecutive patients who showed new or enlarged, contrast-enhancing lesions within the radiation field after concurrent chemoradiotherapy were assessed by use of conventional and dynamic contrast-enhanced perfusion MR imaging. The bimodal histogram parameters of the area under the time signal-intensity curves ratio, which included the mean area under the time signal-intensity curves ratio at a higher curve (mAUCRH), 3 cumulative histogram parameters (AUCR50, AUCR75, and AUCR90), and the area under the time signal-intensity curves ratio at mode (AUCRmode), were calculated and correlated with the final pathologic or clinical diagnosis. The best predictor for differentiation of pseudoprogression from early tumor progression was determined by receiver operating characteristic curve analyses. Seventy-nine study patients were subsequently classified as having pseudoprogression (n=37, 46.8%) or early tumor progression (n=42, 53.2%). There were statistically significant differences of mAUCRH, AUCR50, AUCR75, AUCR90, and AUCRmode between the 2 groups (P < .0001, each). Receiver operating characteristic curve analyses showed the mAUCRH to be the best single predictor of pseudoprogression, with a sensitivity of 90.1% and a specificity of 82.9%. AUCR50 was found to be the most specific predictor of pseudoprogression, with a sensitivity of 87.2% and a specificity of 83.1%. A bimodal histogram analysis of the area under the time signal-intensity curves ratio derived from dynamic contrast-enhanced perfusion MR imaging can be a potential, noninvasive imaging biomarker for monitoring early treatment response in patients with glioblastomas.

Dynamic contrast‐enhanced MR perfusion imaging of head and neck tumors at 3 Tesla

Dynamic contrast-enhanced (DCE) MR perfusion imaging allows assessment of vascular density and integrity of tumors. The purpose of this study was to determine the diagnostic efficacy of time intensity curve analysis on DCE MRI for characterization of head and neck tumors. Twenty patients underwent T1-weighted fast field echo DCE MRI with temporal resolution of 2.6 seconds. In total, 100 dynamic phases covering 20 slices were obtained in 4.5 minutes. Time to peak (TTP), relative maximum enhancement (RME) ratio, and relative washout ratio (RWO) were calculated. Malignant tumors had a significantly lower RME (p = .025) and prolonged TTP with lower RWO than benign lesions. Postradiation changes had a significantly longer TTP (p = .024) and lower RWO (p = .007) than did postradiation recurrent tumors. Receiver operating characteristic (ROC) analysis revealed RWO had highest accuracy (area under the curve [AUC] = 1.0). DCE MR perfusion imaging provides pivotal information regarding microcirculation, potentially improves differentiation of malignant tumor from postradiation changes.

Dynamic Contrast-Enhanced Perfusion MR Imaging With SPIO

To investigate the feasibility of dynamic susceptibility-weighted contrast material-enhanced (DSC) perfusion imaging with ferucarbotran at 3.0 T, and to assess the impact of the different characteristics of gadolinium (Gd)- and ferucarbotran-based agent in rCBV measurement under pathologic condition with BBB disruption. Nine patients with suspected meningioma (4 men and 5 women; age range, 27-79 years; mean age, 61.6 +/- 17.9 years) were eligible for the study. Approval was obtained from the institutional review board. All participants provided signed informed consent prior to the study. DSC perfusion images were acquired with a T2*-weighted echo-planar imaging sequence during the first pass of a standard-dose of Gd-based agent, and of 4, 8, or 16 micromol Fe/kg of ferucarbotran-based agent in 3 patients for each dose respectively. Pre- and postenhanced T1-weighted images were obtained in all. Ferucarbotran decreased the signal intensity in both gray and white matter in a dose-dependent fashion. Differences regarding the DeltaSI between the 4 and 8 or 8 and 16 micromol Fe/kg groups were statistically significant (P < 0.05, 1-way analysis of variance, Tukey-Kramer method) in any region. No effect of leakage of ferucarbotran was demonstrated in the intensity-time curves or in the postenhanced T1-weighted images. Relative CBV in tumor area obtained with Gd was reduced to 37.6%-86.5% compared with that obtained with ferucarbotran. T2*-weighted DSC perfusion imaging with ferucarbotran is feasible at 3.0 T. Compared with Gd-based agent, larger particle size of ferucarbotran can diminish the effect of contrast leakage during the first pass under pathologic conditions with BBB disruption.

Comparison of three physiologically‐based pharmacokinetic models for the prediction of contrast agent distribution measured by dynamic MR imaging

To compare the performance of three physiologically-based pharmacokinetic (PBPK) models for predicting gadolinium contrast agent concentration-time curves (Gd-CTCs) obtained in superior sagittal sinus (SSS), cerebral cortex, and psoas muscle. Three published whole-body PBPK models were modified to predict Gd-CTCs in normal-appearing tissue. The models differed in the number of organs modeled and total number of compartments, and were designated as the "well-mixed," "delay," and "dispersion" models. The suitability of the three models to predict Gd-CTC was studied using data from dynamic contrast-enhanced MR perfusion imaging obtained at 1.5T from 10 patients with glioblastoma multiforme and at 3.0T from five patients with liver metastases. The dispersion model produced better fits than the delay model in the SSS (P < 0.0001) and cerebral cortex (P < 0.0001), and better fits than the well-mixed model in psoas muscle (P < 0.005). No model produced better fits than the dispersion model at any of the three locations. In this evaluation, the dispersion model was most robust for prediction of Gd-CTCs derived from dynamic contrast-enhanced (DCE)-MRI. This represents a preliminary step in the development of a PBPK model useful for predicting Gd-CTCs at a time resolution appropriate for dynamic MRI applications.

Dynamic contrast-enhanced perfusion MR imaging of diseased vertebrae: analysis of three parameters and the distribution of the time-intensity curve patterns

To assess the diagnostic value of perfusion MR imaging of diseased vertebrae by analysis of three parameters and the distribution of the time-intensity curve (TIC) patterns. Dynamic MR imaging was performed on 34 patients with 48 lesions. All lesions were assigned to one of four groups: osteoporotic compression fracture, benign lesion without compression fracture, pathologic compression fracture, or metastatic lesion without fracture. Peak enhancement, steepest slope, and slope value were calculated from the TIC of diseased vertebrae. TICs were classified into five types. Comparisons were made among groups by analysis of the three parameters and the distributions of the TICs pattern. All parameters of pathologic compression fracture were significantly higher than those of osteoporotic compression fracture (P<0.05). The steepest slopes of metastatic lesions with and without pathologic compression fracture were significantly higher than those of benign lesions without compression fracture (P<0.05). No characteristic distribution of the TIC pattern helpful for the differentiation of benign and metastatic lesions was found. In distinguishing osteoporotic from pathologic compression fractures, semiquantitative analysis of the perfusion MR imaging may be useful. However, the analysis of the TIC patterns can not significantly contribute to the differential diagnosis.