Search tips
Search criteria 


Logo of springeropenLink to Publisher's site
Applied Magnetic Resonance
Appl Magn Reson. 2010 June; 38(3): 349–360.
Published online 2010 March 28. doi:  10.1007/s00723-010-0124-1
PMCID: PMC2866959

Assessment of Blood Hemodynamics by USPIO-Induced R1 Changes in MRI of Murine Colon Carcinoma


The objective of this study is to assess whether ultrasmall superparamagnetic iron oxide (USPIO)-induced changes of the water proton longitudinal relaxation rate (R1) provide a means to assess blood hemodynamics of tumors. Two types of murine colon tumors (C26a and C38) were investigated prior to and following administration of USPIO blood-pool contrast agent with fast R1 measurements. In a subpopulation of mice, R1 was measured following administration of hydralazine, a well-known blood hemodynamic modifier. USPIO-induced R1 increase in C38 tumors (ΔR1 = 0.072 ± 0.0081 s−1) was significantly larger than in C26a tumors (ΔR1 = 0.032 ± 0.0018 s−1, N = 9, t test, P < 0.001). This was in agreement with the immunohistochemical data that showed higher values of relative vascular area (RVA) in C38 tumors than in C26a tumors (RVA = 0.059 ± 0.015 vs. 0.020 ± 0.011; P < 0.05). Following administration of hydralazine, a decrease in R1 value was observed. This was consistent with the vasoconstriction induced by the steal effect mechanism. In conclusion, R1 changes induced by USPIO are sensitive to tumor vascular morphology and to blood hemodynamics. Thus, R1 measurements following USPIO administration can give novel insight into the effects of blood hemodynamic modifiers, non-invasively and with a high temporal resolution.


It is well established that tumor vasculature plays a key role in tumor growth [1]. Tumor vessels are not only morphologically, but also physiologically distinct from host vessels [2]. Knowledge about these aspects of tumor vasculature is critical to tumor therapy, both in novel anti-angiogenesis therapeutic treatments and in conventional cytotoxic therapy. Moreover, in recent studies, blood hemodynamic modifiers have been employed to enhance the effects of treatment [3]. However, the exact mechanism by which blood hemodynamic modifiers act is still not well understood [4] and their effects on tumor hemodynamics remain unclear [5]. It is crucial, therefore, to characterize the tumor vasculature and its response to blood hemodynamic modifiers in order to assess and improve the effectiveness of current therapeutic treatments.

Magnetic resonance imaging (MRI), in combination with contrast agent administration, has proven useful in the characterization of tumor vasculature. Several studies have shown that magnetic susceptibility effects, caused by blood-pool contrast agents that consist of ultrasmall superparamagnetic particles of iron oxide (USPIO), can be used to assess blood volume and vessel sizes within tumors. USPIOs have been mostly employed in combination with quantitative and/or qualitative T2 and T2* measurements [612]. In particular, the enhancement in the transverse relaxation rates R2 (=1/T2) and R2* (=1/T2*), after administration of USPIO, provides an index proportional to the blood volume of the microvasculature and macrovasculature, respectively. However, quantitative ΔR2 and ΔR2* measurements are characterized by relatively long acquisition times, due to the long repetition time TR needed to minimize T1 effects.

Quantitative T1 MRI, in combination with USPIO administration, represents an alternative approach to T2/T2* USPIO contrast-enhanced MRI, in particular, when fast assessment (i.e., on the order of seconds) of blood hemodynamics is needed. In this study, detailed measurements of changes in longitudinal relaxation rate R1 (=1/T1), following USPIO administration were performed within in vivo tumor tissue. R1 was measured with the inversion–recovery snapshot fast low-angle shot (IR-FLASH) imaging sequence pre- and post-USPIO administration, in two different types of murine colon carcinoma (C26a, C38). The findings were compared with the vascularity of these tumor types as determined by immunohistochemistry. To assess whether USPIO-induced R1 changes provide a means to assess blood hemodynamics with high temporal resolution, we administered hydralazine—a central vasodilator which induces vasoconstriction in subcutaneous tumors by the steal effect mechanism [13]—and monitored R1 changes in time.

Materials and Methods


All procedures were approved by the Radboud University Nijmegen Medical Center Animal Care and Use Committee. C26a (n = 9) and C38 (n = 9) murine colon tumor tissue fragments were implanted subcutaneously in female Balb/C and C57/Bl6 mice, respectively, of 8–12 weeks of age. Experiments were performed when tumors reached the diameter of approximately 0.8 cm. Mice were anesthetized with isoflurane inhalation (1.5–2%); in each mouse, a catheter was inserted in the tail vein for the administration of the contrast agent and the tumor was positioned in the center of a 10-mm diameter surface radio-frequency (RF) coil used as a transmitter/receiver. During the measurements, the body temperature was monitored with a rectal fluoroptic probe (Luxtron 712, Luxtron Corporation, California, USA) and maintained at a constant temperature of 37 ± 1°C with a warm water pad.

MRI experiments were performed on a 7T/200 mm horizontal-bore MR spectrometer interfaced to a SMIS console and equipped with a gradient insert with a gradient strength of 150 mT/m and rise time of 150 μs. The image acquisition protocol started with three-gradient echo scout images followed by multislice gradient echo images for anatomical localization of the tumor. Imaging parameters were: repetition time (TR) = 400 ms, echo time (TE) = 10 ms, image matrix size of 128 × 128, field of view (FOV) of 5.8 cm × 5.8 cm, slice thickness (SLT) of 0.7 mm and 1 excitation per phase-encoding step. IR-FLASH imaging [14, 15] was then performed on a slice through the center of the tumor, prior to and following administration of an USPIO blood-pool contrast agent (Sinerem®, Guerbet, France; 150 μmol Fe/kg). Imaging parameters were: TR/TE = 5 ms/2.7 ms, image matrix size of 64 × 64, FOV of 3 cm × 3 cm, SLT of 1.6 mm. In this sequence, the longitudinal magnetization is first inverted by a hyperbolic secant adiabatic inversion pulse and then repeatedly sampled by a train of small flip-angle (5°) read-out Gaussian pulses to generate multiple images at different time points on the T1 water proton recovery curve. Digitized RF spoiling pulses with phase angle increments of 117° [16], and a gradient spoiling were applied in order to spoil the transverse steady-state magnetization prior to each read-out pulse. The time interval between the inversion pulse and the first image was 52 ms. Ten dummy scans were applied prior to each image acquisition so that the total acquisition time per image was 370 ms. The lines in the k-space were acquired with a centric profile order to generate 16 images, which sampled the recovery of the longitudinal magnetization over ca. 5 s, at intervals of 370 ms.

To assess the precision of the R1 measurement, in order to determine whether the changes in R1 induced by the contrast agent are greater than the measurement error, four repeated R1 measurements were performed prior to and following administration of USPIO on a group of mice (n = 5, C26a tumors and n = 5, C38 tumors). Further, in a group of mice with C38 tumors (n = 3), an intraperitoneal catheter was inserted for hydralazine injection. Hydralazine was dissolved in NaCl 0.9% to a concentration of 0.33 mg/ml and intraperitoneally injected at a dose of 2.5 mg/kg of mouse weight. The MRI protocol was as before with the only difference that after the post-USPIO R1 measurement, hydralazine was injected, and the R1 value was measured 5 min thereafter.

Data Analysis

The Levenberg–Marquardt non-linear least squares algorithm was used to analyze the R1 relaxation data. R1 maps were obtained from the entire set of 16 images. Voxel-by-voxel R1 maps, pre- and post-USPIO, and after hydralazine, were generated from a three-parameter fit of the image intensities according to the equation: S(TI) = A + B exp(−TI/T1*) and the value of the corrected R1 was calculated from the formula: R1 = (T1*(B/A − 1))−1 which is valid in the small flip-angle limit. Pixel-by-pixel T1 maps were calculated using an algorithm described elsewhere [17]. First, for each pixel, the signal intensity of the 16 magnitude images was evaluated and the minimum value (Smin) was determined. Second, an inversion–recovery curve (i.e., with negative and positive values) was generated by inverting all the data on the left of the minimum value Smin. The fit was determined, as well as the coefficient of determination (R2), which is a measure of the goodness of the fit. Third, the same procedure was repeated choosing one point on the left (Smin−1) and one point on the right (Smin+1) of Smin, so that two additional inversion–recovery curves were generated by inverting all the data on the left of (Smin−1) and of (Smin+1), respectively. The fit was determined, as well as R2. Thus, in total, three inversion–recovery curves were generated. The inversion–recovery which displayed the best fit (i.e., highest R2) was chosen for calculating the T1 relaxation time. The fitting algorithm is further described in Ref. [17]. From the voxel-by-voxel R1 maps, ΔR1 maps (ΔR1 = R1post − R1pre, where R1post and R1pre are the R1 post- and pre-USPIO, respectively) were calculated. For each tumor, the mean ΔR1 was then calculated by drawing a region-of-interest (ROI)—which included the tumor core—on the ΔR1 map and averaging the ΔR1 values of all voxels within the ROI.

To assess the precision of the measured R1 values, we performed four repeated measurements of R1 prior to and following administration of USPIO. For each tumor, four R1 maps pre-USPIO and four R1 maps post-USPIO were generated as described in the previous paragraph. From each R1 map, the mean R1 was calculated by averaging the R1 values of all voxels within an ROI which included the tumor core. The standard deviation (SD) over four repeated R1 measurements, pre-USPIO and post-USPIO was calculated [18]. All data are expressed as mean ± SD. The Levenberg–Marquardt non-linear least squares algorithms were implemented in MatLab (Mathworks, Natick, MA, USA).

In order to compare the changes in the R1 relaxation time (ΔR1) in the C26a tumor with the ΔR1 value in the C38 tumor line, the data were further analyzed with the software package Prism (GraphPad Software Inc., CA, USA). The statistical significance (P < 0.001) of differences between the ΔR1 value in the C26a and C38 tumors was determined by means of a two-tailed Student’s t test.


Since the USPIO remains intravascular, modeling of the effects of the USPIO on the R1 relaxation rate requires the framework of a two-compartment exchange model, where the two compartments are the intra- and extravascular space. The relaxation behavior of the two-compartment exchange model depends on the exchange rate τ−1, defined as the sum of equation M1 and equation M2, where τi and τe are the water proton lifetimes in the intra- and extravascular compartment, respectively, and on the absolute value of the difference between the water proton relaxation rates of the intra- and extravascular space (R1i and R1e, respectively). The precise value of τ−1 is not exactly known [19]; however, the reported values are ca. 1 Hz [2023]. The two-compartment model is in slow exchange when the condition τ−1 [double less-than sign] |R1i − R1e| is satisfied. Schwarzbauer et al. [24] showed that, following contrast agent administration, in the case of slow exchange the observed change in relaxation rate ΔR1 is equal to PS/(λ − RBV), where PS is the permeability-surface area product for water across blood vessel walls, λ is the tissue-to-blood partition coefficient and RBV is the regional blood volume. For typical values of λ and RBV [24], RBV [double less-than sign] λ and therefore, after Taylor series expansion (1/[1 − x] ~ [1 + x], for |x[double less-than sign] 1), ΔR1 ~ (PS/λ)(1 + RBV/λ).


In two separate groups of mice (n = 6 for C38 and n = 5 for C26a) with tumors of approximately the same size as used for the MR experiments, tumor vascularity was determined by immunohistochemistry. After the animals were killed by cervical dislocation, their tumors were excised immediately and stored under liquid nitrogen. Frozen tumor sections of 5 μm thickness were cut for staining and further analysis of vasculature. After thawing, the sections were fixed in cold (4°C) acetone for 10 min. Between all consecutive steps of the staining procedure, sections were rinsed three times for 2 min in phosphate buffered saline. Sections were mounted in Fluorostab (Organon, Boxtel, The Netherlands). Endothelial structures were stained with 9F1, which is a rat monoclonal antibody to mouse endothelium (Department of Pathology, University Medical Centre Nijmegen, The Netherlands) [25]. Then sections were incubated for 30 min at 37°C with goat anti-rat-Alexa546 (Molecular Probes, Leiden, The Netherlands) and diluted 1:200 in polyclonal liquid diluent (Euro-DPC, Breda, The Netherlands). Quantitative data for tumor vascularity were acquired by a semiautomatic method based on a computerized digital image analysis system, as described previously [26, 27]. Whole tumor sections were scanned for 9F1 positive structures and a contour line was drawn to delineate the tumor area thereby excluding non-tumor tissue from the analyses. Consecutive hematoxylin and eosin-stained tumor sections were employed to distinguish parenchyma from non-tumor tissue. The resulting composite image was divided into smaller ROIs (230 × 230 μm). In each ROI the relative vascular area (RVA: 9F1 positive area divided by the viable tumor area) was calculated. From this, a new image map was created in which the voxels had values of the RVA values in the corresponding ROIs.


The IR-FLASH provided a fast method for measuring the water proton R1 relaxation rate in murine colon carcinoma. Figure 1 shows the sixteen IR-FLASH images of a central slice through a C26a murine colon carcinoma. The acquisition time for the whole set of images was ca. 5 s. The combination of RF and gradient spoiling implemented in the IR-FLASH measurements provided images virtually free from artifacts. The signal intensity of the last image (image 16) was typically less than the signal intensity of the first image, due to small saturating effect originating from the read-out pulses. At the inversion time of approximately 1,000 ms, the longitudinal magnetization goes through the null point. The signal intensity changes from a single voxel within the tumor, as well as the fit of the signal recovery to a monoexponential function are illustrated in Fig. 1 (right). The R2 value of 0.9996 indicates the excellent agreement between data points and fit.

Fig. 1
IR-FLASH measurements of the R1 relaxation rate in a C26a murine colon carcinoma. The sixteen IR-FLASH images of a C26a murine colon carcinoma (left). Plot of signal amplitudes from a single voxel within the tumor (right). The dashed line indicates the ...

To estimate the precision of the measured R1 values of each tumor, four repeated measurements were performed prior to and following USPIO administration (Fig. 2). The column graph shows the values of R1 obtained from the four repeated measurements prior to and following administration of USPIO, in a C26a and a C38 tumor. The horizontal line indicates the mean of the four measurements, while each point represents the value of one measurement. Prior to USPIO administration, R1 = 0.5467 ± 0.0024 s−1 in the C26a and R1 = 0.5791 ± 0.0029 s−1 in the C38. Following USPIO administration, R1 = 0.5692 ± 0.0013 s−1 in the C26a and R1 = 0.6596 ± 0.0030 s−1 in the C38. As a result, in both tumors, the USPIO-induced change ΔR1 was greater than the SD value. The repeated measurements were performed in ten tumors. The results of the data analysis for all tumors are given in Table 1. The SD pre- and post-USPIO administration was typically ca. 1–3 10−3 s−1. A small increase in SD in the post-USPIO measurements was observed. On the other hand, changes in R1 induced by USPIO (third row in Table Table1)1) were well above SD values in all cases.

Fig. 2
Column graph of the changes in the R1 relaxation rate following USPIO administration in a C26a and a C38 colon carcinoma. Symbols indicate the values of R1 from four repeated measurements performed prior to and following USPIO administration. Prior to ...
Table 1
SD of R1 calculated from four repeated measurements, performed in ten tumors and the change in R1 induced by the USPIO

In Fig. 3, a column graph of the changes in the R1 relaxation rate following USPIO administration in all tumors showed a clear difference between C38 and C26a tumors. The R1 increase in the C38 tumors (ΔR1 = 0.072 ± 0.0081 s−1) was significantly larger than in the C26a tumors (ΔR1 = 0.032 ± 0.0018 s−1, P < 0.001). Among the C26a tumors, changes in R1 were very similar, while the C38 tumors displayed a broader range of changes in R1. It should be noted that the smallest ΔR1 observed in the C38 group was greater than the largest ΔR1 of the C26a group.

Fig. 3
Column graph of the changes in water proton R1 relaxation rate (ΔR1) following USPIO administration in the C26a and C38 colon carcinoma. The R1 increase in the C38 (ΔR1 = 0.072 ± 0.0081 s ...

The immunohistochemically determined RVA of the C38 tumors was larger than the RVA of the C26a tumors (0.059 ± 0.015 vs. 0.020 ± 0.011; P = 0.0013). This is illustrated in Fig. 4, which shows an RVA map, as well as the vascular structure, of a typical C38 and C26a tumor. The photomicrograph clearly shows the substantial difference in vascular volume and morphology between the C26a and C38 tumors.

Fig. 4
RVA maps of the C26a (a) and C38 (b) tumor section. Each pixel represents a 0.23 × 0.23 mm ROI. Maps are scaled to 100% which corresponds to an RVA value of 21%. c and d Detailed photomicrographs of the tumors in a and ...

Figure 5 shows the R1 relaxation rate before USPIO administration and changes in the R1 relaxation rate after USPIO and hydralazine administration. The increase in R1 after USPIO administration was then followed by a decrease in R1, after hydralazine administration.

Fig. 5
Graph of normalized R1 prior to USPIO administration (first time point), following USPIO administration (second time point) and 5 min after hydralazine administration (third time point) in three C38 colon carcinomas. Following hydralazine administration, ...


In the current study, we propose a method which uses fast R1 measurements on tumors prior to and following USPIO administration in order to monitor the tumor hemodynamics. While USPIO-induced changes in the transverse relaxation rates R2 and R2* within tumors have been experimentally investigated in a number of studies, less attention has been paid to quantitative measurements of R1 changes [28]. Here, we first performed detailed measurements of R1, to assess the precision of our experimental setup, in order to evaluate the significance of the R1 changes. The high signal-to-noise ratio, achieved by (i) the use of a small surface coil, (ii) the positioning of the imaged slice in the plane of the coil itself and (iii) the high field strength, results in a reliable and precise measure of R1. As a consequence, R1 changes following USPIO are significantly larger than the experimental error associated with the R1 measurement.

The USPIO-induced increase in R1 may be attributed to the exchange of water protons between the intra- and extravascular space [19]. Following administration of USPIO, R1 of the intravascular water protons in blood significantly increases (i.e., T1 decreases from a value of ca. 2 s to a value below 200 ms [28]), whereas the extravascular water protons affected by the contrast agent are only those which are in exchange with the intravascular space. As a result, following USPIO administration, the value of |R1i − R1e| increases to a value of ca. 5 Hz, which is greater than the suggested values of τ (~1 Hz [2023]). Thus, USPIO administration drives the system towards slow exchange. In the limit of slow exchange, two decaying components are expected. However, since only about 5% of the water signal can be attributed to intravascular water protons and since the T1 relaxation time of the intravascular component is very short, MRI using the inversion–recovery imaging sequences cannot resolve the two decaying components, that is, it cannot detect the fast-decaying component. The measured T1 is therefore representative of the extravascular component. In the case of slow exchange, as pointed out in Sect. 2, ΔR1 is proportional to the blood volume and to the PS product. Therefore, differences in ΔR1 between various tumor lines may be due to differences in blood volume, PS product or both. In our study, there was a statistically significant difference (P < 0.001) between ΔR1 in the C26a and C38 colon carcinoma, with ΔR1 being larger in the C38 than in the C26a colon carcinoma. This result indicates a difference in tumor vascular morphology between the two tumor lines, which is attributed either to differences in the PS product or in blood volume. The results from the immunohistochemistry, which was performed in the current study on the same tumor lines, indicate that there was a difference in RVA between the two tumor lines, with the C38 colon carcinoma exhibiting a higher RVA.

More relevant and of immediate interpretation are the R1 changes for investigating hemodynamic effects in tumors. In fact, in case of vasoconstriction or vasodilation within the same tumor, ΔR1 can be strictly related to vasoconstriction or vasodilation effects. In other words, if—as a response to a blood hemodynamic modifier—vasoconstriction (or vasodilation) occurs within the tumor, there will be a decrease (or increase) of both surface area and blood volume. Therefore, any vasoconstriction (or vasodilation) is reflected in a decrease (or increase) of R1. The decrease in R1 after hydralazine administration, which is a well-known central vasodilator, suggested a hydralazine-induced vasoconstriction in tumors. This is in line with the observation of vasoconstriction by the steal effect mechanism [29] due to hydralazine reported in other studies of subcutaneous tumors utilizing fluorescent staining [30] and contrast-enhanced MRI [31]. The ‘paradoxical’ vasoconstrictor effect (the ‘steal effect’) in tumor vasculature, as a result of administration of vasodilator agents, such as hydralazine for instance [2931], can be explained in the following way: the systemic vasodilation of all ‘healthy’ blood vessels in the body takes away blood (“steal” the blood) from the tumor vasculature. In fact, since the tumor vasculature itself does not respond directly to the vasoactive agent, as it has a minimal capability of blood flow autoregulation [13], a reduction in tumor blood flow/volume is observed. Tumors have developed a number of ways to ensure a proper blood supply, such as incorporation of pre-existent vessels (also referred to as vessel co-option), vessel modulation (e.g., dilatation and intussusception) and angiogenesis [1, 8]. The ability to monitor tumor blood volume with a high temporal resolution in vivo will provide essential insight into tumor physiology and is a prerequisite to evaluate tumor response to therapy. It will further improve our knowledge of a tumor vasculature response to vasoactive agents (such as in serial measurements of CO2/O2 breathing experiments, for instance), tumor capability for blood flow autoregulation, and transient hemodynamic effects in tumors.

The most significant advantage of quantitative R1 over quantitative R2*/R2 measurements is the temporal resolution: a few seconds for R1 measurements versus minutes in R2 measurements. It should be noted that a temporal resolution of seconds could be also achieved with T2*/T2-weighted imaging; on the other hand, measurement of relative changes in the signal intensity makes interindividual comparison less reliable. With respect to fast quantitative T2*/T2 measurements, based on a steady-state free precession type of acquisition [32], for instance, they suffer from B1 inhomogeneties and artifacts due to off-resonance (B0 inhomogeneities), in particular, at high fields. Quantitative R1 measurements could be an interesting alternative to T2*/T2-weighted images and quantitative R2*/R2 measurements in assessing changes in blood hemodynamics and thus can give novel insight into the effects of blood hemodynamic modifiers on tumor vasculature, non-invasively and with a high temporal resolution.


We thank A. Veltien and B. Lemmers for technical assistance with the MRI measurements and animal handling. We also thank J. Lok, from the Department of Radiation Oncology for providing us with the photomicrographs of tumor vasculature. This work is supported by Dutch Cancer Society, grant KUN 2000-2307 and NWO-ZONWM investment grant 902-37-088.

Open Access This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.


1. Folkman J. Semin. Cancer Biol. 1992;3(2):65–71. [PubMed]
2. Jain RK. Cancer. Res. 1988;48(10):2641–2658. [PubMed]
3. Kaanders JH, Bussink J, Kogel AJ. Lancet Oncol. 2002;3(12):728–737. doi: 10.1016/S1470-2045(02)00929-4. [PubMed] [Cross Ref]
4. Kelleher DK, Vaupel PW. Radiother. Oncol. 1994;32(1):47–53. doi: 10.1016/0167-8140(94)90448-0. [PubMed] [Cross Ref]
5. Hulshof MC, Rehmann CJ, Booij J, Royen EA, Bosch DA, Gonzalez Gonzalez D. Radiother. Oncol. 1998;48(2):135–142. doi: 10.1016/S0167-8140(98)00053-X. [PubMed] [Cross Ref]
6. Bremer C, Mustafa M, Bogdanov A, Jr, Ntziachristos V, Petrovsky A, Weissleder R. Radiology. 2003;226(1):214–220. doi: 10.1148/radiol.2261012140. [PubMed] [Cross Ref]
7. Dennie J, Mandeville JB, Boxerman JL, Packard SD, Rosen BR, Weisskoff RM. Magn. Reson. Med. 1998;40(6):793–799. doi: 10.1002/mrm.1910400602. [PubMed] [Cross Ref]
8. Gambarota G, Leenders W, Maass C, Wesseling P, Kogel B, Tellingen O, Heerschap A. Br. J. Cancer. 2008;98(11):1784–1789. doi: 10.1038/sj.bjc.6604389. [PMC free article] [PubMed] [Cross Ref]
9. Gambarota G, Laarhoven HW, Philippens M, Lok J, Kogel A, Punt CJ, Heerschap A. Magn. Reson. Imaging. 2006;24(3):279–286. doi: 10.1016/j.mri.2005.12.003. [PubMed] [Cross Ref]
10. Le Duc G, Peoc’h M, Remy C, Charpy O, Muller RN, Le Bas JF, Decorps M. Magn. Reson. Med. 1999;42(4):754–761. doi: 10.1002/(SICI)1522-2594(199910)42:4<754::AID-MRM18>3.0.CO;2-Q. [PubMed] [Cross Ref]
11. Robinson SP, Rijken PF, Howe FA, McSheehy PM, Sanden BP, Heerschap A, Stubbs M, Kogel AJ, Griffiths JR. J. Magn. Reson. Imaging. 2003;17(4):445–454. doi: 10.1002/jmri.10274. [PubMed] [Cross Ref]
12. Tropres I, Grimault S, Vaeth A, Grillon E, Julien C, Payen JF, Lamalle L, Decorps M. Magn. Reson. Med. 2001;45(3):397–408. doi: 10.1002/1522-2594(200103)45:3<397::AID-MRM1052>3.0.CO;2-3. [PubMed] [Cross Ref]
13. Jirtle RL. Int. J. Hyperthermia. 1988;4(4):355–371. doi: 10.3109/02656738809016490. [PubMed] [Cross Ref]
14. Deichmann R, Haase A. J. Magn. Reson. 1992;96(1):608–612.
15. Haase A, Matthaei D, Bartkowski R, Duhmke E, Leibfritz D. J. Comput. Assist. Tomogr. 1989;13(6):1036–1040. doi: 10.1097/00004728-198911000-00016. [PubMed] [Cross Ref]
16. Zur Y, Wood ML, Neuringer LJ. Magn. Reson. Med. 1991;21(2):251–263. doi: 10.1002/mrm.1910210210. [PubMed] [Cross Ref]
17. Nekolla S, Gneiting T, Syha J, Deichmann R, Haase A. J. Comput. Assist. Tomogr. 1992;16(2):327–332. doi: 10.1097/00004728-199203000-00031. [PubMed] [Cross Ref]
18. Bland JM, Altman DG. BMJ. 1996;312(7047):1654. [PMC free article] [PubMed]
19. Donahue KM, Weisskoff RM, Burstein D. J. Magn. Reson. Imaging. 1997;7(1):102–110. doi: 10.1002/jmri.1880070114. [PubMed] [Cross Ref]
20. Landis CS, Li X, Telang FW, Molina PE, Palyka I, Vetek G, Springer CS., Jr Magn. Reson. Med. 1999;42(3):467–478. doi: 10.1002/(SICI)1522-2594(199909)42:3<467::AID-MRM9>3.0.CO;2-0. [PubMed] [Cross Ref]
21. Larsson HB, Rosenbaum S, Fritz-Hansen T. Magn. Reson. Med. 2001;46(2):272–281. doi: 10.1002/mrm.1188. [PubMed] [Cross Ref]
22. Paulson OB, Hertz MM, Bolwig TG, Lassen NA. Acta Neurol. Scand. Suppl. 1977;64:492–493. [PubMed]
23. Wacker CM, Wiesmann F, Bock M, Jakob P, Sandstede JJ, Lehning A, Ertl G, Schad LR, Haase A, Bauer WR. Magn. Reson. Med. 2002;47(5):1013–1016. doi: 10.1002/mrm.10125. [PubMed] [Cross Ref]
24. Schwarzbauer C, Morrissey SP, Deichmann R, Hillenbrand C, Syha J, Adolf H, Noth U, Haase A. Magn. Reson. Med. 1997;37(5):769–777. doi: 10.1002/mrm.1910370521. [PubMed] [Cross Ref]
25. Westphal JR, van’t Hullenaar RG, Laak JA, Cornelissen IM, Schalkwijk LJ, Muijen GN, Wesseling P, Wilde PC, Ruiter DJ, Waal RM. Br. J. Cancer. 1997;76(5):561–570. [PMC free article] [PubMed]
26. Bussink J, Kaanders JH, Rijken PF, Martindale CA, Kogel AJ. Br. J. Cancer. 1998;77(1):57–64. [PMC free article] [PubMed]
27. Rijken PF, Bernsen HJ, Kogel AJ. Microvasc. Res. 1995;50(2):141–153. doi: 10.1006/mvre.1995.1048. [PubMed] [Cross Ref]
28. Barbier EL, St Lawrence KS, Grillon E, Koretsky AP, Decorps M. Magn. Reson. Med. 2002;47(6):1100–1109. doi: 10.1002/mrm.10158. [PubMed] [Cross Ref]
29. Voorhees WD, 3rd, Babbs CF. Eur. J. Cancer Clin. Oncol. 1982;18(10):1027–1033. doi: 10.1016/0277-5379(82)90252-8. [PubMed] [Cross Ref]
30. Trotter MJ, Acker BD, Chaplin DJ. Int. J. Radiat. Oncol. Biol. Phys. 1989;17(4):785–789. [PubMed]
31. Belfi CA, Ting LL, Hassenbusch SJ, Tefft M, Ngo FQ. Int. J. Radiat. Oncol. Biol. Phys. 1992;22(3):477–482. [PubMed]
32. Deoni SC, Peters TM, Rutt BK. Magn. Reson. Med. 2005;53(1):237–241. doi: 10.1002/mrm.20314. [PubMed] [Cross Ref]

Articles from Springer Open Choice are provided here courtesy of Springer