Correlation of Tumor Immunohistochemistry with Dynamic Contrast-Enhanced and DSC-MRI Parameters in Patients with Gliomas.

BACKGROUND AND PURPOSE: Tumor CBV is a prognostic and predictive marker for patients with gliomas. Tumor CBV can be measured noninvasively with different MR imaging techniques; however, it is not clear which of these techniques most closely reflects histologically-measured tumor CBV. Our aim was to investigate the correlations between dynamic contrast-enhanced and DSC-MR imaging parameters and immunohistochemistry in patients with gliomas. MATERIALS AND METHODS: Forty-three patients with a new diagnosis of glioma underwent a preoperative MR imaging examination with dynamic contrast-enhanced and DSC sequences. Unnormalized and normalized cerebral blood volume was obtained from DSC MR imaging. Two sets of plasma volume and volume transfer constant maps were obtained from dynamic contrast-enhanced MR imaging. Plasma volume obtained from the phase-derived vascular input function and bookend T1 mapping (Vp_Φ) and volume transfer constant obtained from phase-derived vascular input function and bookend T1 mapping (Ktrans_Φ) were determined. Plasma volume obtained from magnitude-derived vascular input function (Vp_SI) and volume transfer constant obtained from magnitude-derived vascular input function (Ktrans_SI) were acquired, without T1 mapping. Using CD34 staining, we measured microvessel density and microvessel area within 3 representative areas of the resected tumor specimen. The Mann-Whitney U test was used to test for differences according to grade and degree of enhancement. The Spearman correlation was performed to determine the relationship between dynamic contrast-enhanced and DSC parameters and histopathologic measurements. RESULTS: Microvessel area, microvessel density, dynamic contrast-enhanced, and DSC-MR imaging parameters varied according to the grade and degree of enhancement (P < .05). A strong correlation was found between microvessel area and Vp_Φ and between microvessel area and unnormalized blood volume (rs ≥ 0.61). A moderate correlation was found between microvessel area and normalized blood volume, microvessel area and Vp_SI, microvessel area and Ktrans_Φ, microvessel area and Ktrans_SI, microvessel density and Vp_Φ, microvessel density and unnormalized blood volume, and microvessel density and normalized blood volume (0.44 ≤ rs ≤ 0.57). A weaker correlation was found between microvessel density and Ktrans_Φ and between microvessel density and Ktrans_SI (rs ≤ 0.41). CONCLUSIONS: With dynamic contrast-enhanced MR imaging, use of a phase-derived vascular input function and bookend T1 mapping improves the correlation between immunohistochemistry and plasma volume, but not between immunohistochemistry and the volume transfer constant. With DSC-MR imaging, normalization of tumor CBV could decrease the correlation with microvessel area.

Comparison of the Diagnostic Accuracy of DSC- and Dynamic Contrast-Enhanced MRI in the Preoperative Grading of Astrocytomas.

BACKGROUND AND PURPOSE: Dynamic contrast-enhanced MR imaging parameters can be biased by poor measurement of the vascular input function. We have compared the diagnostic accuracy of dynamic contrast-enhanced MR imaging by using a phase-derived vascular input function and "bookend" T1 measurements with DSC MR imaging for preoperative grading of astrocytomas. MATERIALS AND METHODS: This prospective study included 48 patients with a new pathologic diagnosis of an astrocytoma. Preoperative MR imaging was performed at 3T, which included 2 injections of 5-mL gadobutrol for dynamic contrast-enhanced and DSC MR imaging. During dynamic contrast-enhanced MR imaging, both magnitude and phase images were acquired to estimate plasma volume obtained from phase-derived vascular input function (Vp_Φ) and volume transfer constant obtained from phase-derived vascular input function (K(trans)_Φ) as well as plasma volume obtained from magnitude-derived vascular input function (Vp_SI) and volume transfer constant obtained from magnitude-derived vascular input function (K(trans)_SI). From DSC MR imaging, corrected relative CBV was computed. Four ROIs were placed over the solid part of the tumor, and the highest value among the ROIs was recorded. A Mann-Whitney U test was used to test for difference between grades. Diagnostic accuracy was assessed by using receiver operating characteristic analysis. RESULTS: Vp_ Φ and K(trans)_Φ values were lower for grade II compared with grade III astrocytomas (P < .05). Vp_SI and K(trans)_SI were not significantly different between grade II and grade III astrocytomas (P = .08-0.15). Relative CBV and dynamic contrast-enhanced MR imaging parameters except for K(trans)_SI were lower for grade III compared with grade IV (P ≤ .05). In differentiating low- and high-grade astrocytomas, we found no statistically significant difference in diagnostic accuracy between relative CBV and dynamic contrast-enhanced MR imaging parameters. CONCLUSIONS: In the preoperative grading of astrocytomas, the diagnostic accuracy of dynamic contrast-enhanced MR imaging parameters is similar to that of relative CBV.

Preoperative prognostic value of dynamic contrast-enhanced MRI-derived contrast transfer coefficient and plasma volume in patients with cerebral gliomas.

BACKGROUND AND PURPOSE: The prognostic value of dynamic contrast-enhanced MR imaging-derived plasma volume obtained in tumor and the contrast transfer coefficient has not been well-established in patients with gliomas. We determined whether plasma volume and contrast transfer coefficient in tumor correlated with survival in patients with gliomas in addition to other factors such as age, type of surgery, preoperative Karnofsky score, contrast enhancement, and histopathologic grade. MATERIALS AND METHODS: This prospective study included 46 patients with a new pathologically confirmed diagnosis of glioma. The contrast transfer coefficient and plasma volume obtained in tumor maps were calculated directly from the signal-intensity curve without T1 measurements, and values were obtained from multiple small ROIs placed within tumors. Survival curve analysis was performed by dichotomizing patients into groups of high and low contrast transfer coefficient and plasma volume. Univariate analysis was performed by using dynamic contrast-enhanced parameters and clinical factors. Factors that were significant on univariate analysis were entered into multivariate analysis. RESULTS: For all patients with gliomas, survival was worse for groups of patients with high contrast transfer coefficient and plasma volume obtained in tumor (P < .05). In subgroups of high- and low-grade gliomas, survival was worse for groups of patients with high contrast transfer coefficient and plasma volume obtained in tumor (P < .05). Univariate analysis showed that factors associated with lower survival were age older than 50 years, low Karnofsky score, biopsy-only versus resection, marked contrast enhancement versus no/mild enhancement, high contrast transfer coefficient, and high plasma volume obtained in tumor (P < .05). In multivariate analysis, a low Karnofsky score, biopsy versus resection in combination with marked contrast enhancement, and a high contrast transfer coefficient were associated with lower survival rates (P < .05). CONCLUSIONS: In patients with glioma, those with a high contrast transfer coefficient have lower survival than those with low parameters.

Diagnostic accuracy of dynamic contrast-enhanced MR imaging using a phase-derived vascular input function in the preoperative grading of gliomas.

BACKGROUND AND PURPOSE: The accuracy of tumor plasma volume and K(trans) estimates obtained with DCE MR imaging may have inaccuracies introduced by a poor estimation of the VIF. In this study, we evaluated the diagnostic accuracy of a novel technique by using a phase-derived VIF and "bookend" T1 measurements in the preoperative grading of patients with suspected gliomas. MATERIALS AND METHODS: This prospective study included 46 patients with a new pathologically confirmed diagnosis of glioma. Both magnitude and phase images were acquired during DCE MR imaging for estimates of K(trans)_φ and V(p_)φ (calculated from a phase-derived VIF and bookend T1 measurements) as well as K(trans)_SI and V(p_)SI (calculated from a magnitude-derived VIF without T1 measurements). RESULTS: Median K(trans)_φ values were 0.0041 minutes(-1) (95 CI, 0.00062-0.033), 0.031 minutes(-1) (0.011-0.150), and 0.088 minutes(-1) (0.069-0.110) for grade II, III, and IV gliomas, respectively (P ≤ .05 for each). Median V(p_)φ values were 0.64 mL/100 g (0.06-1.40), 0.98 mL/100 g (0.34-2.20), and 2.16 mL/100 g (1.8-3.1) with P = .15 between grade II and III gliomas and P = .015 between grade III and IV gliomas. In differentiating low-grade from high-grade gliomas, AUCs for K(trans)_φ, V(p_φ), K(trans)_SI, and V(p_)SI were 0.87 (0.73-1), 0.84 (0.69-0.98), 0.81 (0.59-1), and 0.84 (0.66-0.91). The differences between the AUCs were not statistically significant. CONCLUSIONS: K(trans)_φ and V(p_)φ are parameters that can help in differentiating low-grade from high-grade gliomas.

Texture analysis: a review of neurologic MR imaging applications.

Texture analysis describes a variety of image-analysis techniques that quantify the variation in surface intensity or patterns, including some that are imperceptible to the human visual system. Texture analysis may be particularly well-suited for lesion segmentation and characterization and for the longitudinal monitoring of disease or recovery. We begin this review by outlining the general procedure for performing texture analysis, identifying some potential pitfalls and strategies for avoiding them. We then provide an overview of some intriguing neuro-MR imaging applications of texture analysis, particularly in the characterization of brain tumors, prediction of seizures in epilepsy, and a host of applications to MS.

Contrast-enhanced MR imaging in acute ischemic stroke: T2* measures of blood-brain barrier permeability and their relationship to T1 estimates and hemorrhagic transformation.

BACKGROUND AND PURPOSE: rtPA is an effective treatment for AIS, yet it is substantially underused due to the increased risk of HT. Recent work suggests that permeability-related information can be extracted from routine T2*-based perfusion images by measuring the rR of the contrast agent. Given that other T2*-based measures have recently been proposed, the purpose of this study was to evaluate 4 such permeability measures in identifying patients with AIS who will proceed to HT. MATERIALS AND METHODS: Eighteen patients with AIS were examined within a mean of 3.3 +/- 1.4 hours postonset. Dynamic T2*-weighted imaging consisted of a single-shot EPI following a bolus of gadodiamide. HT was determined on follow-up CT or MR imaging at 24-72 hours. Mean values of rR, Peak Height, Recovery, as well as Slope were calculated and analyzed on the basis of follow-up HT status. RESULTS: Eight patients proceeded to HT. The mean rR for patients with HT was significantly greater than that for patients without HT (0.22 +/- 0.06 versus 0.14 +/- 0.06, P = .006), while there was a trend toward decreased %Recovery in patients with HT (76 +/- 6 versus 82 +/- 11%, P = .092). There was a significant negative correlation between %Recovery and rR (r = -0.88, P < .001). No significant differences or trends were detected with respect to Peak Height or Slope. CONCLUSIONS: Both rR and %Recovery can be readily extracted from a routine perfusion MR imaging dataset and show potential for identifying HT during the acute phase poststroke.

Myocardial viability imaging using Gd-DTPA: physiological modeling of infarcted myocardium, and impact on injection strategy and imaging time.

Results of simulations are shown which illustrate how the concentration-time curves of an extravascular extracellular (EVEC) contrast agent, such as Gd-DTPA, vary in myocardial tissue. The simulations show that the variable permeability of dead myocytes within a recent myocardial infarction will significantly alter delayed enhancement patterns following a bolus injection, invariably reducing the sensitivity of this technique for the detection of permanently damaged tissue. It is further predicted that if the bolus injection is followed by a suitably selected constant infusion, the infarct size and infarct volume of distribution may be more accurately determined, even though the degree of enhancement of an infarcted region (with normal flow) above normal tissue is slightly higher for the bolus technique within the first 30 min following the injection. The degree of enhancement of an infarcted region (with normal flow) above normal tissue was comparable between the two techniques at the point in the constant infusion at which the volume of contrast injected was the same as in the bolus case, i.e., at approximately 30 min after the bolus injection. The constant infusion approach became superior thereafter as overall tissue concentrations became greater in both normal and infarcted tissue, and these concentrations remained more stable with the constant infusion approach. Preliminary experimental results in a canine model of infarction/reperfusion illustrated a delayed wash-in of contrast agent in infarcted tissue, which may be explained by a physiological model in which dead myocytes in infarcted myocardium have non-infinite permeability.

Examining a canine model of stunned myocardium with Gd-DTPA-enhanced MRI.

It has previously been shown that the distribution volume of Gd-DTPA (lambda) in infarcted, canine myocardium is higher than that of normal tissue. The purpose of this study was to determine whether stunned myocardium exhibits increased lambda. Stunning was produced in beagles by means of 30 min LAD occlusion followed by 3 weeks (n = 4) reperfusion. Gd-DTPA was infused at each imaging session and lambda determined in vivo using a saturation recovery turboFLASH sequence; cine imaging was used to assess ventricular wall thickening (%WT). (201)Tl uptake was used as an independent assessment of viability. %WT data confirmed that the brief insult caused prolonged, yet reversible, regional contractile dysfunction in each animal. %WT was not significantly different from baseline values by 3 weeks post-reflow. Normal (201)Tl uptake confirmed the absence of infarction. The lambda of stunned tissue (lambda = 0.381 +/- 0.030 ml/g) was not elevated above that of normal tissue (lambda = 0.398 +/- 0.027 ml/g, P = NS), at any time point studied, in vivo. These data suggest that an increase in lambda is a specific indicator of irreversible damage.

T(1) fast acquisition relaxation mapping (T(1)-FARM): optimized data acquisition.

A theoretical procedure for estimating the precision of the T(1) Fast Acquisition Relaxation Mapping sequence as a function of a number of acquisition parameters has been validated by both simulations and experimental results. These results have clarified the selection of sequence parameters to give optimal accuracy and precision in the R(1)* measurements. There is excellent agreement between theory, simulation, and experiment except for flip angles greater than 9 degrees, at which point slice profile imperfections significantly degrade the precision of the technique. The experimental results indicate that over a range of T(1)s that would be seen in a bolus tracking experiment (25-1200 ms), T(1) Fast Acquisition Relaxation Mapping can be used to obtain 64 x 128 R(1)* maps at a rate of 1 map/s, with a precision of 10% or better.