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First published online February 15, 2007
British Journal of Radiology (2007) 80, 161-168
© 2007 British Institute of Radiology
doi: 10.1259/bjr/17112059
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Full paper

Comparison of cerebral blood volume maps generated from T2* and T1 weighted MRI data in intra-axial cerebral tumours

H A Haroon, PHD 1 T F Patankar, MBBS, FRCR 1 X P Zhu, MD, PHD 2 K L Li, PHD 2 N A Thacker, PHD 1 M J Scott, PHD 1 and A Jackson, PHD, FRCR, FRCP 1

1 Division of Imaging Science and Biomedical Engineering, Faculty of Medical and Human Sciences, The University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, UK, 2 Department of Radiology, School of Medicine, University of California at San Francisco, San Francisco, California 94143, USA

Correspondence: Professor Alan Jackson, Division of Imaging Science and Biomedical Engineering, Faculty of Medical and Human Sciences, The University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, UK. E-mail: alan.jackson{at}man.ac.uk


   Abstract
Top
 Abstract
Introduction
 Methods and materials
 Results
 Discussion
 References
 
We compared parametric maps, measured values and value distributions of cerebral blood volume (CBV) derived from (1) first pass T1 weighted dynamic contrast-enhanced (DCE) data (T1-CBV) using the recently described leakage profile model and (2) conventional T2* weighted DCE data (T2*-CBV) using a conventional curve fitting technique, in nine patients with intraaxial tumours. Regions of interest were defined around enhancing tumour tissue on matched slices. Median tumour values and conspicuity indexes of CBV from the two techniques were compared, demonstrating good correlation (r = 0.667,p<0.05) in enhancing tumour and no significant difference in conspicuity. Pixel-by-pixel scattergrams of values in normal brain in a representative matched slice were produced for each case, which showed excellent correlation (r = 0.96,p<0.001). Distortion of blood vessels around susceptibility interfaces was evident on T2* CBV but not on T1 CBV maps. Leakage-free T1 CBV maps do not suffer from the susceptibility artifacts seen in T2* CBV maps, although they present comparable biological information.


   Introduction
Top
 Abstract
 Introduction
Methods and materials
 Results
 Discussion
 References
 
The development of new blood vessels in tumours depends on the process of angiogenesis [1, 2]. In general terms more aggressive, rapidly growing tumours will provide a stronger angiogenic stimulus and are characterized by increased microvascular density (MVD) on histological examination. A clear relationship between MVD and prognosis has been demonstrated for many tumour types which encouraged the development of non-invasive imaging based techniques that try to duplicate these measurements in vivo [3–5]. The best documented of these is the measurement of regional cerebral blood volume (CBV) using dynamic contrast enhanced MRI. Several groups have demonstrated a clear relationship between CBV and histological grade in cerebral glioma and in a number of other tumour types [6–16]. Areas of increased CBV within the enhancing components of gliomas correspond well with areas of increased fluorodeoxyglucose uptake on positron emission tomography (PET) and with histological evidence of tumoural de-differentiation [17]. As a result CBV maps are increasingly used in clinical assessment of patients with intracerebral tumours and appear to have application in tumour diagnosis, classification and particularly for the targeting of stereotactic surgical biopsy and post-resection radiotherapy [18–22].

The most commonly applied method for mapping CBV is based on dynamic contrast-enhanced imaging using susceptibility (T2*) weighted images (DSCE-MRI) [18, 23, 24]. This approach was first used to study the perfusion of normal cerebral capillary beds in grey and white matter where the blood–brain barrier (BBB) is intact and gadolinium based contrast agents can be assumed to act as purely intravascular markers. In these applications susceptibility based contrast mechanisms have the advantage over other MR techniques of increased signal-to-noise ratio in areas of low blood volume such as capillary beds [24–26]. However, susceptibility based techniques have significant disadvantages related to spatial distortion occurring in areas of paramagnetic variation and residual relaxivity effects in areas of extravascular contrast leakage [27]. This has led several workers to try to derive CBV maps from T1 weighted data [28–32]. Although these methods showed some promise they are not routinely used, largely because of their tendency to give rise to erroneously high estimates of CBV in areas of extravascular contrast leakage.

In 2000, Li et al [33] described a novel method for the analysis of relaxivity (T1) based dynamic contrast enhanced MRI (DRCE-MRI) which uses a shape-based analysis to decompose the dynamic contrast concentration time course data into intravascular and extravascular components. One consequence of this analytical approach is the generation of an estimate of the intravascular contrast concentration time course curve that is free of leakage effects and therefore ideal for the calculation of leakage-free estimates of CBV. Examination of the method using Monte Carlo simulation techniques has shown that the representation of CBV values can be expected to be accurate across a wide range of CBV values [34].

The purpose of the study presented here is to compare this novel DRCE-MRI technique with conventional DSCE-MRI approaches. The CBV maps generated from both methods have been compared in terms of image quality (spatial information, distortions etc.), pixel value distributions within normal brain and measured values within intraaxial cerebral tumours. The aim is to determine the suitability of these CBV maps for diagnosis, grading and the planning and guidance of procedures such as surgery and radiotherapy.


   Methods and materials
Top
 Abstract
 Introduction
 Methods and materials
Results
 Discussion
 References
 
Nine patients (four females and five males; mean age 48.2 years) with intra-axial cerebral neoplasms (see Table 1Go) were recruited into the study. All patients gave informed consent and the Central Manchester Healthcare NHS Trust and Salford Royal Hospitals NHS Trust medical ethics committees approved the protocols.


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  		Table 1. Patient demography

 
Image acquisition
Imaging was performed on a 1.5 Tesla MR system (Philips Medical Systems, Best, The Netherlands) using a birdcage head-coil.

Routine clinical T1 and T2 weighted anatomical imaging was performed in all patients prior to dynamic studies. Post-contrast T1 weighted volume images (TR 24 ms/TE 11 ms) were acquired at the end of the dynamic studies and used for qualitative comparison with parametric maps of CBV.

For acquisition of T1 weighted dynamic contrast-enhanced data, a 3D T1 FFE (T1 fast field echo) scanning sequence was applied, with an image matrix of 128 x 128 pixels and 25 slices in the axial plane. The field of view used was 230 mm (square), with a slice thickness of 6 mm with 3 mm overlap (Fourier interpolation), resulting in an effective slice thickness of 3 mm. TR was set at 4.2 ms, and TE at 1.2 ms. Three pre-contrast data sets were acquired for the baseline T1 calculation using flip angles of 2°, 10° and 35°. This was followed by a dynamic contrast-enhanced acquisition series at a flip angle of 35°, consisting of 120 scans with a temporal spacing of approximately 5 s. Gadolinium-based contrast agent (Gd-DTPA-BMA; OmniscanTM, Amersham Health AS, Oslo, Norway) was injected as a bolus over 4 s at a dose of 0.1 mmol kg–1 of body weight.

Acquisition of T2* weighted data was carried out immediately after completion of T1 weighted data acquisition, with the time delay set at a fixed duration, so that pre-enhancement would minimize residual relaxivity effects ("T1 shine through") in the dynamic data [35]. T2* weighted (T2*W) dynamic contrast-enhanced data were acquired using a multislice 2D T2*W-FEEPI (field echo ({equiv} gradient echo) EPI) multi-shot sequence. The image matrix was 128 x 128 pixels, with nine slices in the axial plane. The field of view was again 230 mm (square), with slice thickness of 5 mm with 1 mm interslice gap, giving an effective slice thickness of 6 mm. TR was set at 440 ms, and TE at 30 ms. The dynamic contrast-enhanced series consisted of 52 scans at a flip angle of 35° and a temporal spacing of 1.8 s. A second dose of contrast agent (Gd-DTPA) was injected after the fifth dynamic scan using the same protocol described above.

For all scans the tumour was centred in the imaging volume, the imaging volume included the superior sagittal sinus to provide a vascular input function for analysis and the geometry of the T2*W acquisitions was selected from the preceding T1W acquisition so that images were spatially coincident with the central images in the T1W dynamic data-set. Due to its volumetric coverage the temporal resolution of the T1W dynamic sequence is almost three times slower than the multi-slice 2D T2*W dynamic sequence. Parallel imaging was not available at the time of these scans. The pre-enhancement required for the T2*W sequence meant that the T1W DCE acquisition was always carried out using the first contrast injection before the T2*W DCE acquisition, and it was therefore not possible to alternate the sequences.

Image analysis
Dynamic contrast-enhanced T1W data were analysed using the First Pass Leakage Profile (FPLP) method described by Li et al [33, 36]. This technique uses a shape analysis to decompose contrast concentration time course data into two separate components representing intravascular and extravascular contrast agent, allowing calculation of CBV free from the effects of contrast leakage (T1 CBV), and of the transfer coefficient (Kfp) for the passage of contrast between the plasma and the extracellular extravascular space (EES).

T2*W dynamic contrast-enhanced data were analysed using the technique described by Zhu et al [14], based on the techniques of Kassner et al [35]. Multi-slice maps of rate of change of T2* ({Delta}R2*) were calculated from the T2*W-FEEPI dynamic data signals for each dynamic phase and a gamma variate model [37] was used to fit the first pass {Delta}R2*(t) data. Relative cerebral blood volume (rCBV) maps were calculated by pixel-by-pixel integration of the resulting gamma variate curves.

Comparison of T1 CBV and T2* CBV
Visual comparison was performed between maps of T1 CBV, T2* CBV and standard post-contrast T1 weighted anatomical images. Qualitative analysis included calculation of lesion conspicuity, a calculation of the correlation coefficient between median CBV values from each technique and an attempt to produce pixel-by-pixel correlation values from one representative case.

Due to spatial distortions resulting from susceptibility effects in the T2*W acquisition it was not possible to reliably apply automated coregistration of T1W and T2*W images. Separate corresponding regions of interest (ROIs) were therefore manually defined on matched T1W and T2*W images. ROIs were drawn by an experienced neuroradiologist (TAP) and were defined on contrast-enhanced images from the late phase dynamic acquisitions. ROI definition included all enhancing components of the tumour but excluded areas of non-enhancement. Calculated values of CBV from T2*W images were normalized to a value of 1 for a group of voxels (to increase signal-to-noise) with an intensity value of greater than 99% of the maximum (assumed to be 100% CBV) to obtain an estimate of absolute CBV. Median tumour CBV values from T1 CBV and T2* CBV were calculated from each ROI, the values were plotted on a scattergram and the correlation between the values tested using Pearson's correlation coefficient. In addition direct subjective visual comparison of T1-CBV and T2*-CBV maps was performed using a standardized colour map to aid comparison.

ROIs were also drawn on normal appearing white matter on both T1 CBV and T2* CBV maps, and the mean (µ) and standard deviation ({sigma}) from these were compared with values from the enhancing tumour ROIs in the same maps, to ascertain an index of tumour conspicuity using the following expression:


Formula 001

Since distortion on T2*W images prevents accurate coregistration with T1W images we compared pixel-by-pixel values of T1 CBV and T2* CBV in non-tumour brain using the following method.

The square-root of the CBV (sqrt (CBV)) maps was taken in order to produce estimates with uniform error and to expand the dynamic range of the data to make it easier to see any trends in the correlation between the two data sets. The volume of T1 sqrt(CBV) maps from a representative case was manually registered, using a linear affine transform, to the corresponding volume of T2* sqrt(CBV) maps. A single T2*W slice was chosen and the T1 sqrt(CBV) volume was resliced using a sinc 5 kernel for interpolation. The T1 sqrt(CBV) map was then normalized to the (already normalized) T2* sqrt(CBV) by finding the peak in the distribution of the logged CBV ratio over all voxels. A scattergram of the sqrt(CBV) of the two data sets in normal vascularized brain only was produced in the range 0–0.6 sqrt(CBV). This range was chosen for clarity, as the majority of sqrt(CBV) values fell within this range. A second scattergram was obtained using data from the same region of interest as the first, by taking the most similar value from the T1 sqrt(CBV) image to the pixel of interest in the T2* sqrt(CBV) image, corresponding to a half pixel linear interpolation in one of four directions (anterior, posterior, left, right) – a pixel shuffle technique, as has previously been used to compare pre- and post-contrast MR images [38]. The technique allows the selection of the most likely match between the two data sets in order to minimize the errors introduced by the non-rigidity between the two volumetric acquisitions and broadening of large blood vessels in T2* data due to susceptibility effects.


   Results
Top
 Abstract
 Introduction
 Methods and materials
 Results
Discussion
 References
 
Parametric images from all patients were of good quality without visual evidence of motion artefacts. There was no evidence of residual relaxivity effects ("T1 shine-through") in the dynamic T2*W data, which was tested as described previously [35].

Figure 1Go shows a typical representative axial slice through the centre of a high grade glioma (patient 8). A standard high resolution T1W volume post-contrast anatomical image showing the enhancing portion of the tumour and enhanced vasculature (Figure 1aGo) is provided for comparison with parametric maps. Figure 1bGo is a T2* CBV map at the same location as that of Figure 1aGo and displays the distribution of CBV values within the brain and tumour tissue (note that the skull and scalp have been stripped from this image during processing). Normal vasculature, such as the branches of the middle cerebral artery and the cerebral veins, show high values of CBV as expected, and the enhancing portion of the tumour shows a heterogeneous distribution of CBV values. There is good differentiation of normal grey and white matter. Note that blood vessels appear much broader and smoother-edged on the T2* CBV map than on the high resolution anatomical image. There is also considerable signal drop-out and distortion in the basal prefrontal cortex due to susceptibility artefact resulting from air in the paranasal sinuses. Figure 1dGo is a T1 CBV map at the same location as Figure 1aGo. In contrast to Figure 1bGo the map shows improved demonstration of high spatial frequency features and anatomical details, particularly vascular structure, corresponding closely to the anatomical image (Figure 1aGo). The signal-to-noise ratio in normal grey and white matter in Figure 1dGo is poorer than in the T2* CBV image but still allows clear subjective visual discrimination. The spatial distribution of CBV values in Figure 1b and 1dGo is similar in normal brain, tumour and vessels. The FPLP method also generates maps of Kfp as shown in Figure 1cGo indicating an intact BBB where Kfp is zero or consistent with noise, and areas of higher Kfp representing contrast leakage only within the tumour and choroid plexus.


Figure 1
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  		Figure 1. (a) High resolution post-contrast T1 weighted (volumetric T1 FFE / TR 24 ms / TE 11 ms) anatomical image showing an enhancing high grade glioma (patient 8). (b) Corresponding cerebral blood volume (CBV) map generated from T2*-weighted EPI dynamic susceptibility-enhanced data (T2* CBV) [values range 0–100%]. Related maps generated from T1 weighted fast field echo contrast-enhanced dynamic data of (c) Kfp [values range 0–1.2 min–1] and (d) T1 CBV (values range 0–100%). ((b),(c) and (d) use the same colour rendering table for display.)

 
Figures 2a and 2bGo are T1 CBV and T2* CBV maps of the tumour and major basal arteries in patient 1. These images have been chosen to show the extent of the broadening of major blood vessels in the T2* CBV map compared with the same vessels in the T1 CBV map and in the high resolution anatomy image (Figure 2cGo), and have been windowed accordingly. Marked distortion and broadening of the main blood vessels in the T2* CBV image is clearly observed, and some detail of vascular structure is obscured in comparison with the T1 CBV map. When compared with the high resolution anatomy image the large vessels seen with the T1 CBV map correspond closely to their true location and size.


Figure 2
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  		Figure 2. Corresponding(a) T1 CBV and a (b) T2* CBV maps showing a high grade glioma, the circle of Willis and middle cerebral arteries (patient 1). (c) High resolution post-contrast T1 weighted (volumetric T1 FFE / TR 24 ms / TE 11 ms) anatomical image showing the same location. ((a) and (b) use the same colour rendering table for display.)

 
Figure 3Go shows a plot of median measurements from the tumour ROIs on T2* CBV and spatially corresponding T1 CBV maps. There is a significant correlation between these median values of T1 CBV and T2* CBV (r = 0.667, p = 0.05). Comparison of tumour conspicuity values between T1 CBV and T2* CBV maps showed no significant difference; hence visual identification of tumour tissue is equally good on both. The scattergram in Figure 4Go shows the pixel-by-pixel variation between T1 CBV and T2* CBV in normal brain. The plot illustrates a strong correlation between CBV estimates from the two techniques (r = 0.92, p<0.001) and three additional features. First, estimates of T1 CBV extend down to zero, whereas those of T2* CBV appear to be restricted to values above 0.01 CBV (0.1 in square root CBV). This is entirely consistent with the expected susceptibility effects of enhancing capillary beds in T2* images. Second, the correlation is strong but with a broad random component. Third, there is some evidence for an excess of large (>0.2 CBV) values in T2*. Figure 5Go is a pixel-by-pixel scattergram representing the same data using the pixel shuffling technique, which is intended to reduce differences due to small local spatial distortions. The results indicate that both approaches to CBV estimation are consistent (r = 0.96, p<0.001) with the exception of spatial distortion effects in T2*-CBV, the differences being due to capillary enhancement occurring only in CBV values below those generally common in brain tissue.


Figure 3
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  		Figure 3. Comparison of the median measurement taken from enhancing tumour tissue ROIs on manually matched slices ofT1-CBV maps against T2*-CBV, for all our tumour cases. (r = 0.667, p<0.05).

 

Figure 4
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  		Figure 4. Pixel-by-pixel scattergram of a visually matched brain slice from the T1-CBV and T2*-CBV maps in patient 7, using a vascular region of normal brain only. The square-root of the values from the two maps is used to ensure uniform error and to expand the dynamic range of data for visualization (see text); (r = 0.92, p<0.001).

 

Figure 5
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  		Figure 5. Pixel-by-pixel scattergram generated from the same data as in Figure 4Go except that this has been produced by a pixel shuffling method between CBV maps to allow for spatial distortions in the T2*-CBV map (see text). (r = 0.96, p<0.001).

 

   Discussion
Top
 Abstract
 Introduction
 Methods and materials
 Results
 Discussion
References
 
Measurements of CBV based on DSCE-MRI (T2* weighted) techniques have been shown to have clinical significance in a range of disease states [39, 40]; however, the use of the techniques to measure CBV in cerebral tumours is associated with a number of inherent disadvantages. High sensitivity to susceptibility effects is associated with distortions around susceptibility interfaces on the acquired image data, which will include the air in the paranasal sinuses and petrous bone and structures containing a high concentration of contrast in enhanced images. Second, leakage of contrast due to BBB breakdown, which is an intrinsic feature of malignant cerebral tumours, will cause competing relaxivity effects on the observed signal changes which will lead to erroneous underestimation of CBV. In practice, these effects are compensated by decreasing the T1 sensitivity of the sequences or by contrast pre-enhancement to saturate T1 based signal change effects as was performed in the current study [35]. Third, T2* weighted images rely on the use of long echo times (TE) to maintain their T2 sensitivity which reduces the size of the sampling matrix and number of slices which can be acquired within the required temporal resolution (approximately 2 s). This can be tackled by the use of echo planar imaging (EPI) acquisitions which greatly enhance acquisition speed but will impose additional spatial distortions into the image making them potentially unsuitable for spatially-sensitive procedures such as surgical planning applications. These effects can be reduced to some extent by the use of segmented EPI acquisitions and temporal resolution can be maintained by the use of echo shifting techniques in sequences such as PRESTO which also uses a volume acquisition to maintain signal-to-noise ratio [41].

Instead of using T2* weighted gradient echo sequences data may also be collected with T2 weighted (T2W) spin echo sequences. T2W spin echo techniques are relatively more sensitive to the small vessels than T2*W gradient-echo imaging techniques [42, 43], while being less prone to the distortion associated with susceptibility effects. On the other hand, T2*W imaging, which represents the effects of total blood volume in capillaries up to large vessels and weights all vessels approximately equally [44], is expected to be more suitable for evaluating brain tumours [45], and more useful for differentiating low-grade from high-grade gliomas than the T2W spin echo techniques [8]. The current study thus focused on the comparison between T2* CBV and T1 CBV in intra-axial cerebral tumours.

In view of the problems associated with DSCE-MRI techniques several groups have attempted to use relaxivity based dynamic images (DRCE-MRI) to derive estimates of CBV. The potential advantages of this approach include the lack of spatial distortion associated with T1W images and the potential for fast 3D imaging approaches without the need for EPI collections. The major problem with DRCE-MRI in enhancing tissues is the inability to separate the effects of intravascular and extravasated contrast on the observed signal change. This means that signal changes in areas of high capillary permeability will result to a large degree from contrast leakage and estimates of CBV will therefore be erroneously high.

Despite this disadvantage, Hacklander's group in the late nineties described the use of DRCE-MRI in cerebral tumours in a series of publications [29–32]. This group dealt with the leakage problem by assuming that contrast leakage is so slow that it can be ignored over the time course of a single passage of a contrast bolus. They stated that: "gadopentate dimeglumine can almost be regarded to be an intravascular contrast agent, even in cases of a disturbed blood brain barrier". They concluded that T1 CBV measurements could be used in enhancing tissues. However, it is interesting to note that they were unable to demonstrate significant differences between grade III and grade IV glioma even though this has been shown by several groups using susceptibility based techniques [10, 14, 28]. In addition, careful comparison of the results from the T2* and T1 based techniques shows systematic overestimation of T1 CBV in tumours with high values (Figure 7 in [32]). Although the authors do not comment on this a similar observation was highlighted by Bruening et al [28], who described areas of apparently very high CBV on T1 CBV maps which were not seen on T2* CBV or T2 CBV. They commented: "In the high grade group, different values between T1 and T2 CBV maps were apparent", concluding: "Theoretically one would anticipate that in settings of blood brain barrier disruption there would be a tendency for T1 rCBV maps to cause elevated rCBV measurements. In contrast T2 rCBV maps tend to underestimate the apparent rCBV values in the presence of a blood brain barrier breakdown and may show false negative findings in the event of an active tumour recurrence."

In practice, as described above, the tendency for T2* CBV maps to underestimate CBV in areas of contrast leakage can be minimized by a variety of acquisition strategies which are discussed in detail by Kassner et al [35], so that the major residual disadvantages of T2* based methods are the distortion associated with susceptibility effects and the restrictions on imaging time. The sequences used here represent a compromise between spatial resolution and susceptibility sensitivity using a segmented EPI acquisition protocol to reduce scan time whilst minimizing the degree of spatial distortion. The use of optimized T2* based sequences such as PRESTO offers the opportunity to improve on this performance by combining echo shifted, segmented EPI collection and volume acquisition techniques in order to maximize temporal and spatial resolution whilst limiting sensitivity to susceptibility artefacts and distortions. Although these sequences are still not widely available and we have not used them in this study our experience with them indicates that the improvements in susceptibility distortion are relatively limited and spatial distortion remains a significant problem [35, 46].

The use of DRCE-MRI avoids problems associated with susceptibility-based spatial distortion and, in addition, it is possible to use reduced contrast doses compared with DSCE-MRI, although we have not explored that aspect in this study [28, 32]. The major problem with DRCE-MRI is that the signal changes resulting from intravascular contrast and from extravasated contrast occur in the same direction and, since they result from the same physical contrast mechanism, they cannot be separated by modifications of the acquisition technique. We have used the first pass leakage profile model described by Li et al [34, 36] to separate these effects and to generate leakage free T1 CBV maps. This analysis technique decomposes the contrast concentration time course data from DRCE-MRI into two components: the first due to intravascular contrast agent, and the second due to contrast agent leakage into the extravascular extracellular space. The technique works by using a constrained shape model of each component and decomposing the data to produce the optimized fit to these constraints. Although the technique was designed to produce estimates of transendothelial contrast transfer coefficient (Ktrans [47], or more specifically Kfp [48]) which are free of intravascular contrast effects, it also allows calculation of leakage-free CBV maps. The theoretical advantages in terms of temporal resolution, tissue coverage and freedom from image distortion have been the subject of the present study. However, it is equally important to know that CBV estimates from DRCE-MRI provide comparable biological information to those derived from conventional DSCE-MRI techniques. This study has confirmed that this is the case with close correlation between median values and also excellent pixel-by-pixel agreement, particularly when spatial distortion effects are reduced. The advantages of T1 techniques allow confident use of parametric maps for image guided surgical procedures and radiotherapy planning without any risk of error due to spatial distortion.

In conclusion we would recommend further investigation of T1-weighted DCE-MRI for the routine measurement of CBV in cerebral tumours. The technique avoids the risk of significant spatial distortion, provides biologically equivalent data to conventional T2* weighted DCE-MRI methods and has the added advantage of providing high-quality maps of the transfer coefficient [48, 49].

Received for publication June 14, 2006. Accepted for publication July 13, 2006.


   References
Top
 Abstract
 Introduction
 Methods and materials
 Results
 Discussion
 References
 

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