Quantitative magnetisation transfer imaging in glioma: preliminary results

Multi-pool chemical exchange saturation transfer MRI in glioma grading, molecular subtyping and evaluating tumor proliferation

PURPOSE

To evaluate the performance of multi-pool Chemical exchange saturation transfer (CEST) MRI in prediction of glioma grade, isocitrate dehydrogenase (IDH) mutation, alpha-thalassemia/mental retardation syndrome X-linked (ATRX) loss and Ki-67 labeling index (LI), based on the fifth edition of the World Health Organization classification of central nervous system tumors (WHO CNS5).

METHODS

95 patients with adult-type diffuse gliomas were analyzed. The amide, direct water saturation (DS), nuclear Overhauser enhancement (NOE), semi-solid magnetization transfer (MT) and amine signals were derived using Lorentzian fitting, and asymmetry-based amide proton transfer-weighted (APTwasym) signal was calculated. The mean value of tumor region was measured and intergroup differences were estimated using student-t test. The receiver operating curve (ROC) and area under the curve (AUC) analysis were used to evaluate the diagnostic performance of signals and their combinations. Spearman correlation analysis was performed to evaluate tumor proliferation.

RESULTS

The amide and DS signals were significantly higher in high-grade gliomas compared to low-grade gliomas, as well as in IDH-wildtype gliomas compared to IDH-mutant gliomas (all p < 0.001). The DS, MT and amine signals showed significantly differences between ATRX loss and retention in grade 2/3 IDH-mutant gliomas (all p < 0.05). The combination of signals showed the highest AUC in prediction of grade (0.857), IDH mutation (0.814) and ATRX loss (0.769). Additionally, the amide and DS signals were positively correlated with Ki-67 LI (both p < 0.001).

CONCLUSION

Multi-pool CEST MRI demonstrated good potential to predict glioma grade, IDH mutation, ATRX loss and Ki-67 LI.

Macromolecular Proton Fraction as a Myelin Biomarker: Principles, Validation, and Applications

Macromolecular proton fraction (MPF) is a quantitative MRI parameter describing the magnetization transfer (MT) effect and defined as a relative amount of protons bound to biological macromolecules with restricted molecular motion, which participate in magnetic cross-relaxation with water protons. MPF attracted significant interest during past decade as a biomarker of myelin. The purpose of this mini review is to provide a brief but comprehensive summary of MPF mapping methods, histological validation studies, and MPF applications in neuroscience. Technically, MPF maps can be obtained using a variety of quantitative MT methods. Some of them enable clinically reasonable scan time and resolution. Recent studies demonstrated the feasibility of MPF mapping using standard clinical MRI pulse sequences, thus substantially enhancing the method availability. A number of studies in animal models demonstrated strong correlations between MPF and histological markers of myelin with a minor influence of potential confounders. Histological studies validated the capability of MPF to monitor both demyelination and re-myelination. Clinical applications of MPF have been mainly focused on multiple sclerosis where this method provided new insights into both white and gray matter pathology. Besides, several studies used MPF to investigate myelin role in other neurological and psychiatric conditions. Another promising area of MPF applications is the brain development studies. MPF demonstrated the capabilities to quantitatively characterize the earliest stage of myelination during prenatal brain maturation and protracted myelin development in adolescence. In summary, MPF mapping provides a technically mature and comprehensively validated myelin imaging technology for various preclinical and clinical neuroscience applications.

A Fast Protocol for Multiparametric Characterisation of Diffusion in the Brain and Brain Tumours

Multi-parametric tissue characterisation is demonstrated using a 4-minute protocol based on diffusion trace acquisitions. Three diffusion regimes are covered simultaneously: pseudo-perfusion, Gaussian, and non-Gaussian diffusion. The clinical utility of this method for fast multi-parametric mapping for brain tumours is explored. A cohort of 17 brain tumour patients was measured on a 3T hybrid MR-PET scanner with a standard clinical MRI protocol, to which the proposed multi-parametric diffusion protocol was subsequently added. For comparison purposes, standard perfusion and a full diffusion kurtosis protocol were acquired. Simultaneous amino-acid (¹⁸F-FET) PET enabled the identification of active tumour tissue. The metrics derived from the proposed protocol included perfusion fraction, pseudo-diffusivity, apparent diffusivity, and apparent kurtosis. These metrics were compared to the corresponding metrics from the dedicated acquisitions: cerebral blood volume and flow, mean diffusivity and mean kurtosis. Simulations were carried out to assess the influence of fitting methods and noise levels on the estimation of the parameters. The diffusion and kurtosis metrics obtained from the proposed protocol show strong to very strong correlations with those derived from the conventional protocol. However, a bias towards lower values was observed. The pseudo-perfusion parameters showed very weak to weak correlations compared to their perfusion counterparts. In conclusion, we introduce a clinically applicable protocol for measuring multiple parameters and demonstrate its relevance to pathological tissue characterisation.

Quantitative CEST and MT at 1.5T for monitoring treatment response in glioblastoma: early and late tumor progression during chemoradiation

PURPOSE

Quantitative MRI (qMRI) was performed using a 1.5T protocol that includes a novel chemical exchange saturation transfer/magnetization transfer (CEST/MT) approach. The purpose of this prospective study was to determine if qMRI metrics at baseline, at the 10th and 20th fraction during a 30 fraction/6 week standard chemoradiation (CRT) schedule, and at 1 month following treatment could be an early indicator of response for glioblastoma (GBM).

METHODS

The study included 51 newly diagnosed GBM patients. Four regions-of-interest (ROI) were analyzed: (i) the radiation defined clinical target volume (CTV), (ii) radiation defined gross tumor volume (GTV), (iii) enhancing-tumor regions, and (iv) FLAIR-hyperintense regions. Quantitative CEST, MT, T₁ and T₂ parameters were compared between those patients progressing within 6.9 months (early), and those progressing after CRT (late), using mixed modelling. Exploratory predictive modelling was performed to identify significant predictors of early progression using a multivariable LASSO model.

RESULTS

Results were dependent on the specific tumor ROI analyzed and the imaging time point. The baseline CEST asymmetry within the CTV was significantly higher in the early progression cohort. Other significant predictors included the T₂ of the MT pools (for semi-solid at fraction 20 and water at 1 month after CRT), the exchange rate (at fraction 20) and the MGMT methylation status.

CONCLUSIONS

We observe the potential for multiparametric qMRI, including a novel pulsed CEST/MT approach, to show potential in distinguishing early from late progression GBM cohorts. Ultimately, the goal is to personalize therapeutic decisions and treatment adaptation based on non-invasive imaging-based biomarkers.

Does the magnetization transfer effect bias chemical exchange saturation transfer effects? Quantifying chemical exchange saturation transfer in the presence of magnetization transfer

Purpose

Chemical exchange saturation transfer (CEST) is an MRI technique sensitive to the presence of low‐concentration solute protons exchanging with water. However, magnetization transfer (MT) effects also arise when large semisolid molecules interact with water, which biases CEST parameter estimates if quantitative models do not account for macromolecular effects. This study establishes under what conditions this bias is significant and demonstrates how using an appropriate model provides more accurate quantitative CEST measurements.

Methods

CEST and MT data were acquired in phantoms containing bovine serum albumin and agarose. Several quantitative CEST and MT models were used with the phantom data to demonstrate how underfitting can influence estimates of the CEST effect. CEST and MT data were acquired in healthy volunteers, and a two‐pool model was fit in vivo and in vitro, whereas removing increasing amounts of CEST data to show biases in the CEST analysis also corrupts MT parameter estimates.

Results

When all significant CEST/MT effects were included, the derived parameter estimates for each CEST/MT pool significantly correlated (P < .05) with bovine serum albumin/agarose concentration; minimal or negative correlations were found with underfitted data. Additionally, a bootstrap analysis demonstrated that significant biases occur in MT parameter estimates (P < .001) when unmodeled CEST data are included in the analysis.

Conclusions

These results indicate that current practices of simultaneously fitting both CEST and MT effects in model‐based analyses can lead to significant bias in all parameter estimates unless a sufficiently detailed model is utilized. Therefore, care must be taken when quantifying CEST and MT effects in vivo by properly modeling data to minimize these biases.

Advanced Magnetic Resonance Imaging Techniques in Management of Brain Metastases

Brain metastases are the most common intracranial tumors and occur in 20–40% of all cancer patients. Lung cancer, breast cancer, and melanoma are the most frequent primary cancers to develop brain metastases. Treatment options include surgical resection, whole brain radiotherapy, stereotactic radiosurgery, and systemic treatment such as targeted or immune therapy. Anatomical magnetic resonance imaging (MRI) of the tumor (in particular post-Gadolinium T₁-weighted and T₂-weighted FLAIR) provide information about lesion morphology and structure, and are routinely used in clinical practice for both detection and treatment response evaluation for brain metastases. Advanced MRI biomarkers that characterize the cellular, biophysical, micro-structural and metabolic features of tumors have the potential to improve the management of brain metastases from early detection and diagnosis, to evaluating treatment response. Magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), quantitative magnetization transfer (qMT), diffusion-based tissue microstructure imaging, trans-membrane water exchange mapping, and magnetic susceptibility weighted imaging (SWI) are advanced MRI techniques that will be reviewed in this article as they pertain to brain metastases.

Evaluation of Glioblastoma Response to Therapy With Chemical Exchange Saturation Transfer

PURPOSE

To monitor cellular and metabolic characteristics of glioblastoma (GBM) over the course of standard 6-week chemoradiation treatment with chemical exchange saturation transfer (CEST)-MRI; and to identify the earliest time point CEST could determine subsequent therapeutic response.

METHODS AND MATERIALS

Nineteen patients with newly diagnosed GBM were recruited, and CEST-MRI was acquired immediately before (Day₀), 2 weeks (Day₁₄) and 4 weeks (Day₂₈) into treatment, and 1 month after the end of treatment (Day₇₀). Several CEST metrics, including magnetization transfer ratio and area under the curve of CEST peaks corresponding to nuclear Overhauser effect (NOE) and amide protons (MTR_NOE, MTR_Amide, CEST_NOE, and CEST_Amide respectively), magnetization transfer (MT), and direct water effect were investigated. Lack of early progression was determined as no increase in tumor size or worsening of clinical symptoms according to routine post-chemoradiation serial structural MRI.

RESULTS

Changes in MTR_NOE (nonprogressors = 1.35 ± 0.18, progressors = 0.97 ± 0.22, P = .006) and MTR_Amide (nonprogressors = 1.25 ± 0.17, progressors = 0.99 ± 0.10, P = .017) between baseline (Day₀) and Day₁₄ resulted in the best separation of nonprogressors from progressors. Moreover, the baseline (Day₀) MTR_NOE (nonprogressors = 6.5% ± 1.6%, progressors = 9.1% ± 2.1%, P = .015), MTR_Amide (nonprogressors = 6.7% ± 1.7%, progressors = 8.9% ± 1.9%, P = .028), MT (nonprogressors = 3.8% ± 0.9%, progressors = 5.4% ± 1.4%, P = .019), and CEST_NOE (nonprogressors = 4.1%ċHz ± 1.7%ċHz, progressors = 6.1%ċHz ± 1.9%ċHz, P = .044) were able to identify progressors even before the start of the treatment.

CONCLUSIONS

Chemical exchange saturation transfer (CEST) provides imaging-based biomarkers of GBM response as early as 2 weeks into the treatment. Certain CEST metrics can characterize tumor aggressiveness and identify early progressors even before beginning the treatment. Such an early biomarker of response may allow for adjusting the GBM treatment plan for adaptive radiation therapy in early progressors and more confidently continuing standard adjuvant treatment for nonprogressors.

Glioblastoma (GBM) effects on quantitative MRI of contralateral normal appearing white matter

PURPOSE

The objective was to investigate (with quantitative MRI) whether the normal appearing white matter (NAWM) of glioblastoma (GBM) patients on the contralateral side (cNAWM) was different from NAWM of healthy controls.

METHODS

Thirteen patients with newly diagnosed GBM and nine healthy age-matched controls were MRI-scanned with quantitative magnetization transfer (qMT), chemical exchange saturation transfer (CEST), and transverse relaxation time (T₂)-mapping. MRI scans were performed after surgery and before chemo-radiation treatment. Comprehensive qMT, CEST, T₂ data were acquired. A two-pool MT model was fit to qMT data in transient state, to calculate MT model parameters [Formula: see text]. CEST signal was isolated by removing the contributions from the MT and direct water saturation, and CEST signal was calculated for Amide (CEST_Amide), Amine (CEST_Amine) and nuclear overhauser effect, NOE (CEST_NOE).

RESULTS

There was no difference between GBM patients and normal controls in the qMT properties of the macromolecular pool [Formula: see text]. However, their free water pool spectrum was different (1/R_aT_2a,patient = 28.1 ± 3.9, 1/R_aT_2a,control = 25.0 ± 1.1, p = 0.03). This difference could be attributed to the difference in their T₂ time ([Formula: see text] = 83 ± 4, [Formula: see text] = 88 ± 1, p = 0.004). CEST signals were statistically significantly different with the CEST_Amide having the largest difference between the two cohorts (CEST_{Amide,patient} = 2.8 ± 0.4, CEST_{Amide,control} = 3.4 ± 0.5, p = 0.009).

CONCLUSIONS

CEST in cNAWM of GBM patients was lower than healthy controls which could be caused by modified brain metabolism due to tumor cell infiltration. There was no difference in MT properties of the patients and controls, however, the differences in free water pool properties were mainly due to reduced T₂ in cNAWM of the patients (resulting from structural changes and increased cellularity).

Quantitative Magnetization Transfer in Monitoring Glioblastoma (GBM) Response to Therapy

Quantitative magnetization transfer (qMT) was used as a biomarker to monitor glioblastoma (GBM) response to chemo-radiation and identify the earliest time-point qMT could differentiate progressors from non-progressors. Nineteen GBM patients were recruited and MRI-scanned before (Day0), two weeks (Day14), and four weeks (Day28) into the treatment, and one month after the end of the treatment (Day70). Comprehensive qMT data was acquired, and a two-pool MT model was fit to the data. Response was determined at 3-8 months following the end of chemo-radiation. The amount of magnetization transfer ([Formula: see text]) was significantly lower in GBM compared to normal appearing white matter (p < 0.001). Statistically significant difference was observed in [Formula: see text] at Day0 between non-progressors (1.06 ± 0.24) and progressors (1.64 ± 0.48), with p = 0.006. Changes in several qMT parameters between Day14 and Day0 were able to differentiate the two cohorts with [Formula: see text] providing the best separation (relative [Formula: see text] = 1.34 ± 0.21, relative [Formula: see text] = 1.07 ± 0.08, p = 0.031). Thus, qMT characteristics of GBM are more sensitive to treatment effects compared to clinically used metrics. qMT could assess tumor aggressiveness and identify early progressors even before the treatment. Changes in qMT parameters within the first 14 days of the treatment were capable of separating early progressors from non-progressors, making qMT a promising biomarker to guide adaptive radiotherapy for GBM.

Nuclear Overhauser Enhancement-Mediated Magnetization Transfer Imaging in Glioma with Different Progression at 7 T

Glioma is a malignant neoplasm affecting the central nervous system. The conventional approaches to diagnosis, such as T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and contrast-enhanced T1WI, give an oversimplified representation of anatomic structures. Nuclear Overhauser enhancement (NOE) imaging is a special form of magnetization transfer (MT) that provides a new way to detect small solute pools through indirect measurement of attenuated water signals, and makes it possible to probe semisolid macromolecular protons. In this study, we investigated the correlation between the effect of NOE-mediated imaging and progression of glioma in a rat tumor model. We found that the NOE signal decreased in tumor region, and signal of tumor center and peritumoral normal tissue markedly decreased with growth of the glioma. At the same time, NOE signal in contralateral normal tissue dropped relatively late (at about day 16-20 after implanting the glioma cells). NOE imaging is a new contrast method that may provide helpful insights into the pathophysiology of glioma with regard to mobile proteins, lipids, and other metabolites. Further, NOE images differentiate normal brain tissue from glioma tissue at a molecular level. Our study indicates that NOE-mediated imaging is a new and promising approach for estimation of tumor progression.

Quantitative Magnetization Transfer Imaging of the Breast at 3.0 T: Reproducibility in Healthy Volunteers

Quantitative magnetization transfer magnetic resonance imaging provides a means for indirectly detecting changes in the macromolecular content of tissue noninvasively. A potential application is the diagnosis and assessment of treatment response in breast cancer; however, before quantitative magnetization transfer imaging can be reliably used in such settings, the technique's reproducibility in healthy breast tissue must be established. Thus, this study aims to establish the reproducibility of the measurement of the macromolecular-to-free water proton pool size ratio (PSR) in healthy fibroglandular (FG) breast tissue. Thirteen women with no history of breast disease were scanned twice within a single scanning session, with repositioning between scans. Eleven women had appreciable FG tissue for test–retest measurements. Mean PSR values for the FG tissue ranged from 9.5% to 16.7%. The absolute value of the difference between 2 mean PSR measurements for each volunteer ranged from 0.1% to 2.1%. The 95% confidence interval for the mean difference was ±0.75%, and the repeatability value was 2.39%. These results indicate that the expected measurement variability would be ±0.75% for a cohort of a similar size and would be ±2.39% for an individual, suggesting that future studies of change in PSR in patients with breast cancer are feasible.

Associations between brain white matter integrity and disease severity in obstructive sleep apnea

Obstructive sleep apnea (OSA) is characterized by recurrent upper airway blockage, with continued diaphragmatic efforts to breathe during sleep. Brain structural changes in OSA appear in various regions, including white matter sites that mediate autonomic, mood, cognitive, and respiratory control. However, the relationships between brain white matter changes and disease severity in OSA are unclear. This study examines associations between an index of tissue integrity, magnetization transfer (MT) ratio values (which show MT between free and proton pools associated with tissue membranes and macromolecules), and disease severity (apnea-hypopnea index [AHI]) in OSA subjects. We collected whole-brain MT imaging data from 19 newly diagnosed, treatment-naïve OSA subjects (50.4 ± 8.6 years of age, 13 males, AHI 39.7 ± 24.3 events/hr], using a 3.0-Tesla MRI scanner. With these data, whole-brain MT ratio maps were calculated, normalized to common space, smoothed, and correlated with AHI scores by using partial correlation analyses (covariates, age and gender; P < 0.005). Multiple brain sites in OSA subjects, including superior and inferior frontal regions, ventral medial prefrontal cortex and nearby white matter, midfrontal white matter, insula, cingulate and cingulum bundle, internal and external capsules, caudate nuclei and putamen, basal forebrain, hypothalamus, corpus callosum, and temporal regions, showed principally lateralized negative correlations (P < 0.005). These regions showed significant correlations even with correction for multiple comparisons (cluster-level, family-wise error, P < 0.05), except for a few superior frontal areas. Predominantly negative correlations emerged between local MT values and OSA disease severity, indicating potential usefulness of MT imaging for examining the OSA condition. These findings indicate that OSA severity plays a significant role in white matter injury. © 2016 Wiley Periodicals, Inc.

Rapid measurement of brain macromolecular proton fraction with transient saturation transfer MRI

PURPOSE

To develop an efficient MRI approach to estimate the nonwater proton fraction (f) in human brain.

METHODS

We implement a brief, efficient magnetization transfer (MT) pulse that selectively saturates the magnetization of the (semi-) solid protons, and monitor the transfer of this saturation to the water protons as a function of delay after saturation.

RESULTS

Analysis of the transient MT effect with two-pool model allowed robust extraction of f at both 3 and 7 T. This required estimating the longitudinal relaxation rate constant (R_1,MP and R_1,WP ) for both proton pools, which was achieved with the assumption of uniform R_1,MP and R_1,WP across brain tissues. Resulting values of f were approximately 50% higher than reported previously, which is partly attributed to MT-pulse efficiency and R_1,MP being higher than assumed previously.

CONCLUSION

Experiments performed on human brain in vivo at 3 and 7 T demonstrate the ability of the method to robustly determine f in a scan time of approximately 5 min. Magn Reson Med 77:2174-2185, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Influence of water compartmentation and heterogeneous relaxation on quantitative magnetization transfer imaging in rodent brain tumors

PURPOSE

The goal of this study was to investigate the influence of water compartmentation and heterogeneous relaxation properties on quantitative magnetization transfer (qMT) imaging in tissues, and in particular whether a two-pool model is sufficient to describe qMT data in brain tumors.

METHODS

Computer simulations and in vivo experiments with a series of qMT measurements before and after injection of Gd-DTPA were performed. Both off-resonance pulsed saturation (pulsed) and on-resonance selective inversion recovery (SIR) qMT methods were used, and all data were fit with a two-pool model only.

RESULTS

Simulations indicated that a two-pool fitting of four-pool data yielded accurate measures of pool size ratio (PSR) of macromolecular versus free water protons when there were fast transcytolemmal exchange and slow R1 recovery. The fitted in vivo PSR of both pulsed and SIR qMT methods showed no dependence on R1 variations caused by different concentrations of Gd-DTPA during wash-out, whereas the fitted kex (magnetization transfer exchange rate) changed significantly with R1 .

CONCLUSION

A two-pool model provides reproducible estimates of PSR in brain tumors independent of relaxation properties in the presence of relatively fast transcytolemmal exchange, whereas estimates of kex are biased by relaxation variations. In addition, estimates of PSR in brain tumors using the pulsed and SIR qMT methods agree well with one another. Magn Reson Med 76:635-644, 2016. © 2015 Wiley Periodicals, Inc.

Multiparametric magnetic resonance in the assessment of the gender differences in a high-grade glioma rat model

Background

Glioblastoma, the most frequent and aggressive of all astrocytomas, presents a clear predominance in male humans, but the assessment of sexual differences in its tumourigenesis and growth has received little attention so far. In this study, we aim to identify gender-dependent surrogate markers in an animal model of this cancer by means of magnetic resonance (MR) imaging and biochemical and behavioural studies.

Methods

A high-grade glioma model developed in male and female rats was used. Multiparametric magnetic resonance images and localized spectra were acquired. The MR parameters linked to tumoural features were quantified. Motor and metabolic activity was also assessed. Postmortem analyses were carried out to measure indicators of malignancy, tumoural metabolism and viability of the blood-brain barrier (BBB).

Results

Statistically significant differences dependent on the animal sex were found in the study of pathological indicators like oedema, inflammation, cellularity and microvasculature. Results suggest higher cell proliferative rate, inflammation and vasogenic oedema and or necrosis in glioma-bearing male rats. Haemodynamic parameters measured indicated a major disruption of the BBB, postmortem confirmed, in this sex. Metabolomic and energetic metabolism activity data are in agreement with a major malignancy and aggressiveness of this cancer model on males.

Conclusions

Gender differences should be taken into account in preclinical studies of glioblastoma models, in the characterization of the tumoural behaviour and consequently in the development and validation of new therapeutic approaches. MR imaging and spectroscopy allow to non-invasively monitor this sexual dimorphism in the diagnosis and prognosis of brain cancer.

On the origins of chemical exchange saturation transfer (CEST) contrast in tumors at 9.4 T

Chemical exchange saturation transfer (CEST) provides an indirect means to detect exchangeable protons within tissues through their effects on the water signal. Previous studies have suggested that amide proton transfer (APT) imaging, a specific form of CEST, detects endogenous amide protons with a resonance frequency offset 3.5 ppm downfield from water, and thus may be sensitive to variations in mobile proteins/peptides in tumors. However, as CEST measurements are influenced by various confounding effects, such as spillover saturation, magnetization transfer (MT) and MT asymmetry, the mechanism or degree of increased APT signal in tumors is not certain. In addition to APT, nuclear Overhauser enhancement (NOE) effects upfield from water may also provide distinct information on tissue composition. In the current study, APT, NOE and several other MR parameters were measured and compared comprehensively in order to elucidate the origins of APT and NOE contrasts in tumors at 9.4 T. In addition to conventional CEST methods, a new intrinsic inverse metric was applied to correct for relaxation and other effects. After corrections for spillover, MT and T1 effects, corrected APT in tumors was found not to be significantly different from that in normal tissues, but corrected NOE effects in tumors showed significant decreases compared with those in normal tissues. Biochemical measurements verified that there was no significant enhancement of protein contents in the tumors studied, consistent with the corrected APT measurements and previous literature, whereas quantitative MT data showed decreases in the fractions of immobile macromolecules in tumors. Our results may assist in the better understanding of the contrast depicted by CEST imaging in tumors, and in the development of improved APT and NOE measurements for cancer imaging.

Quantitative magnetization transfer imaging of rodent glioma using selective inversion recovery

Magnetization transfer (MT) provides an indirect means to detect noninvasively variations in macromolecular contents in biological tissues, but, so far, there have been only a few quantitative MT (qMT) studies reported in cancer, all of which used off-resonance pulsed saturation methods. This article describes the first implementation of a different qMT approach, selective inversion recovery (SIR), for the characterization of tumor in vivo using a rodent glioma model. The SIR method is an on-resonance method capable of fitting qMT parameters and T1 relaxation time simultaneously without mapping B0 and B1 , which is very suitable for high-field qMT measurements because of the lower saturation absorption rate. The results show that the average pool size ratio (PSR, the macromolecular pool versus the free water pool) in rat 9 L glioma (5.7%) is significantly lower than that in normal rat gray matter (9.2%) and white matter (17.4%), which suggests that PSR is potentially a sensitive imaging biomarker for the assessment of brain tumor. Despite being less robust, the estimated MT exchange rates also show clear differences from normal tissues (19.7 Hz for tumors versus 14.8 and 10.2 Hz for gray and white mater, respectively). In addition, the influence of confounding effects, e.g. B1 inhomogeneity, on qMT parameter estimates is investigated with numerical simulations. These findings not only help to better understand the changes in the macromolecular contents of tumors, but are also important for the interpretation of other imaging contrasts, such as chemical exchange saturation transfer of tumors.