Validation of a Multi-Parametric Ultra-High Field MRI Protocol for Central Nervous System Malignancy
Phase: NA
Conditions: Central Nervous System Neoplasm, Glioma, Metastatic Malignant Neoplasm in the Central Nervous System, Metastatic Malignant Solid Neoplasm
Sponsor: M.D. Anderson Cancer Center

Protocol No: 2019-1032 
Version No: 10 
Version Date: August 25, 2023 
1 
PROTOCOL TITLE: Validation of a Multi-Parametric Ultra-high Field MRI Protocol for 
Central Nervous System Malignancy ............................................................................................. 6 
1 
OBJECTIVES ..................................................................................................................... 7 
1.1 
Primary Objectives.......................................................................................................... 7 
1.2 
Secondary Objective ....................................................................................................... 7 
1.3 
Exploratory Objectives ................................................................................................... 7 
1.3.1 To assess patient experience in the 7T MRI system compared to their most recent 
MRI examination. ................................................................................................................... 7 
1.3.2 Functional MRI (fMRI) - To assess the typical significance values seen for areas of 
maximal brain activity associated with each fMRI test. ......................................................... 7 
1.3.3 To assess the geometric distortion of a radiation planning sequence on a ultra-high 
field (UHF) system. ................................................................................................................ 7 
2 
BACKGROUND ................................................................................................................ 7 
2.1 
Primary brain tumors ...................................................................................................... 8 
2.2 
Brain metastasis. ............................................................................................................. 9 
2.3 
Quantitative MRI .......................................................................................................... 10 
2.4 
Multiple B-Value Diffusion Imaging (Adv Diff) ......................................................... 11 
2.5 
Chemical Exchange Saturation Transfer (CEST) MRI ................................................ 12 
2.6 
Multiple inversion time (TI) arterial spin labeling (ASL) “Adv ASL” perfusion 
imaging ...................................................................................................................................... 13 
2.7 
Protocol Particular Disease Description ....................................................................... 13 
3 
ELIGIBILITY ................................................................................................................... 14 
3.1 
Inclusion Criteria .......................................................................................................... 14 
3.2 
Exclusion Criteria ......................................................................................................... 14 
3.3 
NUMBER OF PARTICIPANTS .................................................................................. 15 
4 
STUDY PLAN/DESIGN .................................................................................................. 15 
4.1 
Patient Enrollment: ....................................................................................................... 15 
4.2 
Procedure to Obtain Consent ........................................................................................ 15 
4.3 
Houston Methodist Research Institute (HMRI) Registration ....................................... 16 
4.4 
MR Scanning: ............................................................................................................... 16 
•
Quantitative MRI .......................................................................................................... 16 
•
CEST ............................................................................................................................. 16 
•
Adv Diff ........................................................................................................................ 16 
4.5 
Patient experience survey ............................................................................................. 17 
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4.5.1 Patients will be given a one-page survey regarding their experience in the 7T MRI 
system following their scan. [Appendix A] .......................................................................... 17 
4.6 
Imaging Time Points ..................................................................................................... 17 
4.6.1 A single research imaging session will be planned for each patient.  However, 
patients will still undergo follow-up imaging scans as part of their standard of care.  These 
follow-up scans will serve as the basis for statistical analyses that consider treatment 
response or disease recurrence. ............................................................................................. 17 
4.7 
Conclusion of Study Participation: ............................................................................... 17 
4.7.1 Completion of planned study scan. ........................................................................... 17 
4.7.2 Upon patient request. ................................................................................................ 17 
4.7.3 Death. ........................................................................................................................ 17 
5 
Image Analysis.................................................................................................................. 18 
5.1 
Lesion size evaluation: .................................................................................................. 18 
5.1.1 A patient must have a single intraaxial brain lesion of 5 mm or greater for study 
inclusion as measured on either T2-weighted or T1-post contrast weighted imaging. ........ 18 
5.1.2 Lesions will be measured on either axial T2 FLAIR weighted or T1 post-contrast 
imaging on a slice displaying the maximal lesion size using the longest diameter after 
appropriate magnification on the picture archiving and communicating system (PACS) 
monitors. ............................................................................................................................... 18 
5.1.3 For patients with multiple lesions appropriate for study assessment, the five (5) 
largest lesions will be assessed. ............................................................................................ 18 
5.2 
Lesion CNR evaluation: ................................................................................................ 18 
5.2.1 The largest circular ROI that fits within the lesion on axial T1 post-contrast imaging 
will be placed and will define the lesion ROI. ...................................................................... 18 
5.2.2 The ROI mean signal intensity will be recorded. ..................................................... 18 
5.2.3 A mirror ROI will be placed in the contralateral normal-appearing white matter and 
used as the "background" mean signal intensity measurement. ........................................... 18 
5.2.4 An extracranial ROI without visible artifact will be used as the “noise” mean signal 
intensity measurement. ......................................................................................................... 18 
5.3 
Quantitative MRI .......................................................................................................... 18 
5.3.1 The largest circular ROI that fits within the lesion on axial T1 post-contrast imaging 
will be placed and will define the lesion ROI. ...................................................................... 18 
5.3.2 The T1 and T2 tissue weighting that maximizes the ROI mean signal intensity will 
be identified. ......................................................................................................................... 18 
5.3.3 A mirror ROI will be placed in the contralateral normal-appearing white matter and 
used as the "background" mean signal intensity measurement. ........................................... 18 
5.3.4 An extracranial ROI without visible artifact will be used as the mean “noise” signal 
intensity measurement. ......................................................................................................... 18 
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5.4 
CEST MRI .................................................................................................................... 19 
5.4.1 The largest circular ROI that fits within the lesion on axial T1 post-contrast imaging 
will be placed and will define the lesion ROI. ...................................................................... 19 
5.4.2 The mean signal intensity for a corresponding ROI location on the processed CEST 
data will be recorded. ............................................................................................................ 19 
5.4.3 A mirror ROI will be placed in the contralateral normal-appearing white matter on 
the processed CEST data will be used as the “background” mean signal intensity 
measurement. ........................................................................................................................ 19 
5.4.4 An extracranial ROI without visible artifact will be used as the “noise” mean signal 
intensity measurement. ......................................................................................................... 19 
5.5 
Multiple B Value Diffusion Imaging (Adv Diff) .......................................................... 19 
5.5.1 The largest circular ROI that fits within the lesion on axial T1 post-contrast imaging 
will be placed and will define the lesion ROI. ...................................................................... 19 
5.5.2 The AKC for the lesion will be determined using B-values of 0, 1000, and 2000 
mm2/s. 19 
5.5.3 The ADC of the lesion will also be determined using B-values of 0 and 1000 mm2/s.
 
19 
5.5.4 A mirror ROI will be placed in the contralateral normal-appearing white matter, and 
"background" AKC and ADC measurement will be measured. ........................................... 19 
5.6 
Adv ASL ....................................................................................................................... 19 
5.6.1 The largest circular ROI that fits within the lesion on axial T1 post-contrast imaging 
will be placed and will define the lesion ROI. ...................................................................... 19 
5.6.2 This ROI will be used to assess the cerebral blood flow (CBF) from the processed 
ASL data. .............................................................................................................................. 19 
5.6.3 A mirror ROI will be placed in the contralateral normal-appearing white matter for 
assessment of the “background” CBF................................................................................... 19 
5.6.4 This ROI will be used to assess the bolus arrival time (BAT) from the processed 
ASL data. .............................................................................................................................. 19 
5.7 
Task-based fMRI .......................................................................................................... 20 
5.7.1 fMRI data will be analyzed using custom software, IClinfMRI. .............................. 20 
5.7.2 The general linear model will be used to generate an activation t-value map for each 
task-based fMRI data. The model includes the convolution of the task paradigms with a 
canonical hemodynamic response function. ......................................................................... 20 
5.7.3 Significantly activated areas will be determined by thresholding the t-value map at 
corrected P < .05. .................................................................................................................. 20 
5.8 
Resting-state fMRI ........................................................................................................ 20 
5.8.1 Resting-state datasets will be pre-processed through slice timing, motion correction, 
de-spiking, detrending, regressing out covariates (including six motion parameters and two 
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averaged fluctuations over masks of white matter and cerebrospinal fluid), band-pass 
filtering of 0.01-0.08 Hz, and 4-mm FWHM smoothing. ..................................................... 20 
5.8.2 Functional connectivity maps will be generated by using both seed-based analysis 
and independent component analysis. ................................................................................... 20 
5.8.3 For the seed-based analysis, seed locations will be determined by anatomical motor 
and language areas with the assistance of a regional homogeneity map. ............................. 20 
5.8.4 For the independent component analysis, 30-50 independent components will be 
determined, and the relevant functional connectivity maps will be determined with template 
matching and inspection by neuroradiologists. ..................................................................... 20 
5.9 
Radiation planning validation ....................................................................................... 20 
5.9.1 A 3D T1 SPACE sequence will be obtained to validate the ability of UHF MRI to 
provide acceptable levels of geometric distortion for radiation therapy planning purposes. 20 
5.9.2 The specific parameters of the sequence will be optimized to maximize contrast and 
minimize artifact and distortion. ........................................................................................... 20 
5.9.3 The geometric distortion will be evaluated with a full-field geometric distortion 
phantom to assess the geometric accuracy of the SPACE sequence with its specific 
parameters. ............................................................................................................................ 20 
5.9.4 For radiation therapy purposes, the geometric distortion of less than 1mm is desired 
for the typical head field of view and 2 mm is the targeted limit for the useable field of view
 
20 
6 
Patient Information Confidentiality Plan .......................................................................... 21 
6.1 
Collection of Identifiers: ............................................................................................... 21 
6.2 
Training of personnel: ................................................................................................... 21 
6.3 
Data Storage: ................................................................................................................. 21 
6.4 
Data Sharing: ................................................................................................................ 21 
6.5 
Final Disposition of study records: ............................................................................... 22 
7 
STATISTICAL CONSIDERATIONS.............................................................................. 22 
7.1 
Definitions..................................................................................................................... 22 
7.1.1 Lesion “treatment response” will be defined by size and contrast to noise ratio 
(CNR).  Treatment response will be assessed only in patients with treatment prior to 
enrollment. ............................................................................................................................ 22 
7.1.2 Disease recurrence will be determined by surgical pathology (if available) or at 
least three months of imaging follow-up.  Disease recurrence will be assessed only in 
patients with treatment prior to enrollment. Imaging findings will be considered recurrent 
disease in a lesion if: ............................................................................................................. 22 
7.2 
Overview ....................................................................................................................... 23 
7.3 
Sample Size ................................................................................................................... 23 
7.4 
Analysis Plan ................................................................................................................ 24 
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8 
PROTOCOL MONITORING PLAN ............................................................................... 24 
9 
REFERENCES ................................................................................................................. 25 
10 
APPENDICES .................................................................................................................. 30 
 
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PROTOCOL TITLE: Validation of a Multi-Parametric Ultra-high Field MRI Protocol for 
Central Nervous System Malignancy 
 
 
Principal Investigator: Max Wintermark, MD 
 
Co-Investigators: Maria Gule, MD, Sujit Prabhu, MD, Jason Stafford, MD, Ho-Ling (Anthony) 
Liu, PhD, Ken Hwang, PhD, Mark Pagel, PhD, Jihong Wang, PhD and Jingfei Ma, PhD; Dawid 
Schellingerhout, MDMelissa Chen, MD, Frederick Lang, MD, Jeffrey Weinberg, MD, Ping Ho, 
PhD, Sherise Ferguson, MD, Jing Li, MD, PhD, Vinay Puduvalli, MD, Clifton Fuller, MD, 
Abdallah Mohamed, MD, John Slopis, MD, Chirag Patel, MD, Leomar Ballester, MD 
 
 
Statistician: Roland Bassett, Jr. MS. 
 
 
Outside collaborator:  
*Steve H. Fung, MD (Medical Director, MRI Core & Assistant Clinical Member, Research 
Houston Methodist) 
Robert Rostomily, MD (Neurosurgery, Houston Methodist) 
******************** 
This is an MD Anderson faculty written and supervised research activity. This project is funded 
by the Division of Diagnostic Imaging. Only MD Anderson patients will be recruited for 
enrollment in this study. 
The primary research activity (MRI examination) in this study will take place at the Houston 
Methodist Research Institute.  
*Steve H. Fung, MD, is the Medical Director of the MRI Core at the Houston Methodist 
Research Institute. He will supervise and monitor study activities at the HMRI.  
 
 
 
 
 
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1 
OBJECTIVES 
1.1 
Primary Objectives 
 
1.1.1. To estimate the contrast-to-noise ratio (CNR) for several imaging modalities in brain 
malignancy as compared with normal brain parenchyma separately by type of 
malignancy and treatment status.  The methods to be studied include Quantitative MRI 
(T1 and T2 sequencing), Chemical Exchange Saturation Transfer (CEST) MRI, Multiple 
B-Value Diffusion Imaging (Adv Diff), and Multiple inversion time (TI) arterial spin 
labeling (ASL) perfusion imaging (Adv ASL). 
 
1.2 
Secondary Objective 
 
1.2.1. To assess the conspicuity of each imaging modality to differentiate radiation necrosis 
from progressive disease. 
 
1.3 
Exploratory Objectives 
1.3.1 To assess patient experience in the 7T MRI system compared to their most recent MRI 
examination. 
1.3.2 Functional MRI (fMRI) - To assess the typical significance values seen for areas of 
maximal brain activity associated with each fMRI test. 
1.3.3 To assess the geometric distortion of a radiation planning sequence on a ultra-high field 
(UHF) system. 
 
2 
BACKGROUND  
 
This study is seeking to examine a group of advancing imaging techniques in patients with 
known or suspected brain malignancy to assess whether future clinical and research protocols 
may benefit from their utilization. These advanced imaging techniques, in a limited number of 
publications, have shown improvements at 7T over lower field strengths (detailed below). There 
have additionally been limited applications of these techniques on the Magnetom Terra Siemens 
7T system (FDA approved for brain imaging in 2018 and available at the Houston Methodist 
Research Institute for The University of Texas MD Anderson Cancer Center faculty usage) and 
specifically related to brain cancer. This study seeks to validate these techniques on this specific 
system in a population of patients with known or suspected brain cancer. 
The majority of all malignancies of the central nervous system can be categorized as either 
primary brain neoplasms (such as primary brain tumors) and metastatic disease (such as from 
breast cancer, lung cancer or melanoma). There has been growing recognition of the need for 
novel, effective therapies for brain malignancies. Vice President Joseph Biden in a January 15, 
2016 roundtable at the Abramson Cancer Center stated a goal of catalyzing greater investment, 
coordination, and collaboration in cancer therapy including a specific focus on advances in the 
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treatment of glioblastoma. Currently validated treatments for glioblastoma and other central 
nervous system tumors are few in number and short on proven effectiveness. These treatments 
are also often toxic, threaten neurological function, and hamper the quality of remaining life. The 
Brain Tumor Center at the MD Anderson has defined their Glioblastoma Moon Shot goal as an 
aim for better, safer therapeutics along with quadrupling the five-year survival rate, from 10% to 
40% over the next decade. [1] 
Despite years of scientific work resulting in thousands of publications, there are limited 
advanced MR features that have enough validated evidence to support clinical implementation to 
assist in evaluating tumor response. Techniques including diffusion-weighted imaging (DWI), 
diffusion tensor imaging, perfusion MRI, and magnetic resonance spectroscopy (MRS) allow 
tumor assessment at the metabolic and physiologic level, but they have not yet been able to 
reliably identify tumor volumes or differentiate tumor recurrence from pseudoprogression and 
radiation necrosis. [2] [3] [4] [5] [6] A significant challenge in the field of MRI has been the 
ability to meaningfully compare findings across studies and institutions due to wide variability in 
the image acquisition, post-processing, analysis, and interpretation. 
Ultra-high field (UHF) MRI shows promise to improve detection and characterization of brain 
tumors, preoperative planning for neurosurgical resection, and longitudinal monitoring of the 
effects of radiation and antibody-based therapies. Addition research revealed that the clinical 
advantages of 7T magnets, including higher signal-to-noise ratio, higher contrast-to-noise ratio, 
smaller voxels, and stronger susceptibility contrast, may increase lesion conspicuity, detection 
and characterization compared to lower field 1.5T and 3T. [7] 
2.1 
Primary brain tumors 
 
Primary brain tumors are the most common primary brain tumor in the United States, and despite 
aggressive multimodal therapy with maximum safe resection, radiotherapy in combination with 
concurrent and adjuvant temozolomide, the median survival of the most aggressive form of 
primary brain tumor, glioblastoma, in clinical trial populations is 16 months. There has been an 
unfortunate stagnation in the ability of non-invasive diagnostics to accurately differentiate 
between treatment response and failure. Even under optimal circumstances with the use of ‘state 
of the art' diagnostic and therapeutic interventions, less than 15% of patients will survive five 
years. [8] [9] [10] While the introduction of temozolomide into the first-line standard of care [11] 
achieved some survival improvement, nearly all patients relapse and treatment options for 
recurrent disease remain limited and largely ineffective.  
The ability to measure the response to treatment is a critical component in evaluating the efficacy 
of new therapies. Unfortunately, current diagnostic neuroimaging paradigms fail to evaluate 
treatment response for glioblastoma reliably. The initial landmark imaging evaluation guidelines 
– the Macdonald criteria – were established in 1990 and was based solely on the assessment of 
contrast-enhancement as a surrogate for tumor size. Contrast-enhancement is non-specific and 
reflects the degree of extravasation of a contrast agent across a disrupted blood-brain: changes in 
contrast-enhancement may be attributable to real progression, imaging technique, treatment 
(surgery, radiation, or chemotherapy), steroids and parenchymal changes unrelated to the tumor 
(postsurgical changes, ischemia, seizures). Particularly with the use of multimodal therapy with 
radiation and temozolomide and new systemic therapies such as bevacizumab, new radiological 
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phenomena including pseudoprogression and pseudoresponse have added further complexity to 
assessing treatment response. 
In the context of clinical trials, accurate response assessment is essential. Misclassification of 
patients may lead to premature discontinuation of an actually effective agent, thereby 
withholding a potentially active treatment from the patient or inappropriate continuation of an 
inactive treatment that may have associated toxicities. Moreover, such misclassification may 
confound the data obtained in such studies and may lead to false conclusions with regards to the 
efficacy (or safety) of an investigated drug. An effort to address this challenge to accurately 
evaluate brain tumor response resulted in the formation of the Response Assessment in Neuro-
Oncology (RANO) working group. In 2010, this group published updated guidelines for 
response assessment of high-grade gliomas incorporating additional MRI and clinical 
considerations, which addressed the recognized and accepted limitations of the Macdonald 
Criteria. [12] 
Advanced imaging techniques that provide added value in the evaluation of primary brain tumors 
include MRS for detection of a 2-HG peak which identifies patients at harboring an IDH1/2 gene 
mutation and thus can serve as a non-invasive diagnostic indicator of astrocytoma versus an 
oligodendroglioma. In a study of MRS at 7T, the ability of 2D L-COSY to unambiguously detect 
2HG in addition to other neuro metabolites was demonstrated. [13] 7T MRS has also provided a 
better detection of major neuronal metabolites when there are overlapping peaks. This is a feat 
that is often challenging with technology at 3T and 1.5T imaging systems. [14] 
2.2 
Brain metastasis. 
 
Brain metastases have been reported to occur in up to 30% of patients with cancer, and treatment 
options include supportive care, surgery, and radiotherapy. [15] The incidence of brain 
metastases is increasing, partly because of increase in the incidence of primary cancers and 
partly because improvements in treatment options have prolonged survival of patients with 
cancer, which increases the chance of primary tumors metastasizing. [16] There are very few 
chemotherapy options open to patients with brain metastases.  Stereotactic radiosurgery (SRS) 
has become an increasingly important treatment option for the initial management of patients 
with brain metastases. Early and accurate detection of small metastases is associated with 
improved treatment success. [17] At present, gadolinium-enhanced MRI is considered to be the 
imaging technique of choice in patients suspected of brain metastases. [18] 
Significant limitations to the utilization of gadolinium-enhanced MRI in the screening for brain 
metastasis is cost and the requirement of an intravenous injection of a contrast agent. [19] Some 
patients have claustrophobia requiring sedation. Additionally, underlying conditions, such as 
back pain, may make it hard for the patients to lie still for the duration of the MRI. Achieving 
standard-of-care MR imaging in these populations can be challenging. There is a vital clinical 
necessity for a safe and efficient screening imaging technology to offer patients as risk of brain 
metastases, who have contraindications to gadolinium as well as the ability to tolerate long 
examination times. [20] 
A comparison of brain malignancy at 7T and 3T revealed that routine contrast doses at 7T 
provided higher lesion enhancement than the full dose at 3T, which indicates the possibility of 
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contrast dose reduction at 7T. This could provide particularly useful in pediatric and renal failure 
populations. (Noebauer-Huhmann, 2015)  
This UHF work on patients with multiple sclerosis at 7T revealed the ability of the combination 
of MP2RAGE (magnetization prepared 2 rapid acquisition gradient echoes) and T2*-weighted 
imaging at 7T to improve detection of cortical lesions. This work suggests that similar 
techniques could be used to improve detection of small metastases, including those involving the 
cortical structures. [21] 
2.3 
Quantitative MRI 
 
Intensity values on routine MR imaging are not defined in terms of any consistent scale since the 
signal is dependent on many hardware and patient-specific factors. Hence there is very little 
gained in measuring the “bright” or “dark” pixel values on an MR image, and the images must be 
interpreted subjectively. [22] This would be analogous to subjectively describing “hot” or “cold” 
spots on an infrared heat map image when the absolute temperature scale of the pixels is not 
known. This study proposes to use multi-parameter mapping to quantitatively measure the signal 
changes in the tissues to address these challenges. In MR imaging, hydrogen nuclei or "spins" 
are the sources of the signal. In the strong magnetic field of an MR scanner, these spins emit RF 
signals in response to transmitted RF pulses. Thus, contrast mechanisms in MR imaging are 
highly dependent on the hydrogen spin density or proton density (PD), as well as the longitudinal 
and transverse relaxation times (T1 and T2, respectively), which tend to vary between different 
tissues or fluids. However, measurement of relaxation times requires multiple acquisitions, and 
as a result, measurement or quantitation of these parameters can be excessively long for clinical 
MR exam.   
 
Recent developments in rapid multi-parameter mapping techniques are possible due to advances 
in accelerated imaging and reconstruction techniques. [22, 23] These typically incorporate 
efficient pulse sequence designs and mathematical constraints to assess the desired information 
in each pixel. SyntheticMR developed the first clinically available method and released by GE 
Healthcare as "MAGIC" (MAGnetic resonance Image Compilation), which can achieve whole-
brain quantitation in 5-6 minutes. [24] The SyntheticMR method assumes the process of T1 and 
T2 relaxation times to be monoexponential, whereas it may be multi-exponential for many 
tissues. However, a phantom study has revealed good accuracy and reproducibility for T1, T2, 
and PD measurements by the SyntheticMR method. These measured parameters can also be 
applied to an MR spin model produce images with almost any contrast weighting by virtually 
changing repetition time (TR), echo time (TE), and inversion time (TI). 1 Synthetic MRI is 
particularly useful when many different contrast settings (for example, T1 weighted imaging 
(WI), T2WI, proton density WI) are required. Synthetic MRI of the brain without the use of a 
contrast agent has been reported to produce images that although inferior in image quality the 
diagnostic power of the images was comparable to that of images obtained via conventional MRI 
sequences. [25] Therefore, if the diagnostic power of images obtained via synthetic MRI after 
administration of a contrast agent is also proved to be comparable to that of conventional MRI, 
synthetic MRI could be a useful means of screening for brain metastases, significantly reducing 
scan time and providing quantitative data. [26] 
 
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Multiple investigators have also demonstrated CEST imaging at UHF. These results indicate the 
potential utility of amide proton transfer (APT) at the high field as a noninvasive biomarker of 
white matter pathology, providing complementary information to other MRI methods in current 
clinical use. Also, contrary to results obtained at lower fields, APT imaging at 7T revealed 
significant contrast between white and gray matters, with a higher APT signal apparent within 
the white matter. These findings suggest that UHF CEST imaging would be sensitive to 
alternations in the APT signal related to both malignancies and treatment-related changes. [27] 
 
2.4 
Multiple B-Value Diffusion Imaging (Adv Diff) 
 
Molecular diffusion is a stochastic process, and, as such, it may be described by probability 
distributions. The most basic of these is the probability of a molecule moving a given 
displacement over a given time interval. For pure, homogeneous liquids (e.g., a glass of water), 
this displacement probability distribution function is Gaussian, and the diffusion is referred to as 
Gaussian diffusion. In conventional MR imaging, diffusion of water molecules in the tissues has 
a tiny contribution to the MR signal. In diffusion MRI, powerful magnetic gradients with an 
echo-planar sequence are used. Thus, the measurement of the molecular diffusion of water has 
been possible for decades using MRI, and diffusion-weighted imaging (DWI) with MRI has been 
possible for greater than thirty years. [28] 
 
A diffusion coefficient called apparent diffusion coefficient (ADC) value can be calculated 
within each image voxel, and ADC maps can be generated on a pixel-by-pixel basis. Because 
diffusion coefficients are high in fluids where diffusion is free, a low signal is observed on 
diffusion imaging at b = 1000 mm2/s (high signal on corresponding ADC maps). Normal CSF is 
an example of this. On the other hand, if the mobility of water molecules is restricted such as in 
ischemia (cytotoxic edema) high signal is observed on diffusion imaging at b = 1000 mm2/s (low 
signal on corresponding ADC maps). [29] 
 
Diffusion-weighted imaging has been proposed as a set of tools to improve diagnostic accuracy 
and achieve a better understanding of the pathophysiology of brain cancer. A specialized form of 
DWI is diffusion tensor imaging (DTI) that provides information not only about the random 
displacement, or passive diffusion, of water molecules but also about fiber directionality and 
integrity. DTI can allow visualization of neuronal projections in the central nervous system and 
estimation of the neuronal changes in the white matter of healthy subjects and patients with 
various neurological diseases. [30] 
 
Fractional anisotropy (FA) and mean diffusivity (MD) obtained from diffusion tensor imaging 
(DTI) has been used to assess the nature of brain metastasis and their response to treatment. 
However, FA and MD have limitations in accurately evaluating brain metastasis. New 
technologies, such as diffusion kurtosis imaging (DKI), can provide a more informative insight 
into the biology of tissue, including brain metastasis. [31] An advantage of DKI is that it is 
relatively simple to implement for human imaging on conventional MRI clinical scanners. DKI 
protocols differ from DTI protocols in requiring at least three b-values (as compared to 2 b-
values for DTI) and at least 15 independent diffusion gradient directions (as compared to 6 for 
DTI). Typical protocols for brain have b-values of 0, 1000, 2000 s/mm2 with 30 diffusion 
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directions. The apparent excess kurtosis coefficient (AKC) is a dimensionless metric that 
quantifies the degree of deviation from Gaussian diffusion behavior. [32]  
 
Defining the relationship between DKI and brain metastasis prior, during and following 
treatment can provide more abundant imaging to guide cancer diagnosis and treatment. [33] DKI 
has been used to measure the non-Gaussian nature of water diffusion, which can reveal a more 
complex microstructure in both normal and pathological tissues compared to DTI alone. 
Previous studies have demonstrated that there was a significant difference in mean kurtosis (MK) 
value between high- and low-grade astrocytomas. [34] However, to the best of our knowledge, 
no comparison of different diffusion imaging approaches for assessing brain metastasis has been 
performed. 
 
Early work on DKI at UHF suggests that it is not only feasible but provides improvements over 
diffusion imaging at lower field strengths. Researchers have shown that with modern statistical 
approaches, including an autoregressive model for the inference that ultra-high field functional 
magnetic resonance imaging is successful. [35] Additional research has shown that UHF DKI is 
a viable option for imaging tissue change in MS lesions and normal-appearing WM. [36] 
 
2.5 
Chemical Exchange Saturation Transfer (CEST) MRI 
 
Chemical exchange saturation transfer (CEST) is a promising new MRI contrast mechanism that 
has been used in studying the tumor microenvironment through the detection of mobile proteins 
and peptides. This technique relies on the labeling of endogenous populations of exchanging 
protons by a radiofrequency pulse at a specific frequency. These pools can transfer their 
magnetization to the unbound water (through the exchange), the extent of which constitutes the 
MRI image contrast, and by varying the radiofrequency pulse frequency, a spectrum is 
generated. In the absence of the CEST effect, this spectrum is generally considered to be 
symmetric; however, in its presence, the signal is attenuated at specific frequencies, resulting in 
chemical-specific negative peaks. Two CEST effects apparent in vivo are attributed to protons of 
mobile proteins: backbone amide signals with their base-catalyzed proton transfer (APT), and 
nuclear Overhauser enhancement (NOE) mediated aliphatic proton magnetization transfer (so-
called exchange-relayed NOE. [45]  
 
MRI based on the chemical exchange saturation transfer (CEST) effect from amine, amide, 
sulfhydryl, and hydroxyl protons associated with endogenous metabolites has been shown to 
provide imaging maps of metabolites in tissue noninvasively. [46] Amide proton transfer (APT) 
imaging has been developed, which detects amide protons of low concentration in endogenous 
proteins and peptides in tissue. [47] APT has shown promising results in differentiating radiation 
necrosis from tumor progression in primary brain tumors and necrosis models in rats. [48] APT 
has also been applied to human primary brain tumor patients to differentiate high-grade tumors 
from low-grade ones with encouraging results. [49] 
 
Ten glioblastoma patients were studied in this paper which revealed both that CEST imaging was 
feasible at 7T and also that it appeared to provide superior information to CEST imaging 
performed at lower field strengths (including 3T). Signal and contrast gained in CEST imaging at 
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7T have provided new insights into the conceptualization of CEST imaging in brain tumors. 
Their work also suggests that previous CEST approaches might not have shown pure CEST 
effects, but rather water relaxation shine-through effects. Their insights help to improve 
understanding of the CEST effect changes in tumors and correlations on a cellular and molecular 
level. [45] 
 
2.6 
Multiple inversion time (TI) arterial spin labeling (ASL) “Adv ASL” perfusion 
imaging 
 
Arterial spin labeling (ASL) is an MRI technique that can noninvasively and quantitatively 
determine cerebral blood flow (CBF) by magnetically labeling the arterial water spins with 
radiofrequency pulses. [50] This method takes advantage of the fact that water protons of the 
arterial blood in the feeding vasculature of the brain are magnetically labeled and used as an 
endogenous tracer. After a specific inversion time, the labeled blood arrives at the image plane in 
which the image is acquired. In clinical studies, it has been used to assess perfusion in 
neurodegenerative diseases, epilepsy, central nervous system neoplasms, and vascular 
malformations. [51] However, a disadvantage of ASL-MRI is that in patients with 
cerebrovascular disease, the quantification of CBF is hampered by the recruitment of additional 
blood flow through collateral pathways. [52] These alternative pathways of blood flow lead to 
delayed arrival of the labeled blood bolus to the brain. [53]  
 
As most ASL-MRI techniques acquire the labeled images at a fixed time after the initial labeling 
of arterial blood, it is possible that the magnetic label may not have reached the imaging plane, 
leading to underestimation of CBF. Previous studies reported that tumor-brain blood flow ratios 
determined by arterial spin-labeling were markedly higher than those obtained with dynamic 
susceptibility-weighted contrast-enhanced MR imaging. [54] The underestimation of perfusion 
probably causes this in brain regions with long arterial transit times. The use of higher inversion 
times would overcome these limitations; however, this would conversely lead to a decrease in 
the SNR caused by the rapid decay of the ASL perfusion signal over time. Recently, ASL-MRI 
with the acquisition of a series of images at multiple delay times after the initial labeling has 
been introduced as a method to compensate for these issues and also demonstrated the ability to 
differentiate low-grade and high-grade astrocytomas. [55] 
 
The inherently low contrast-to-noise ratio of ASL techniques is substantially improved when 
scanning at 7T, which allows data to be collected at higher spatial resolution. This work 
demonstrated the ability to quantify the perfusion of small cortical lesions in MS at 7 Tesla, 
demonstrating that an optimized ASL acquisition is sensitive to focal hemodynamic pathology. 
[56] 
 
2.7 
Protocol Particular Disease Description 
 
Brain malignancy will be defined as suspected or pathologically proven space-occupying intra-
axial lesion. Suspected (not pathologically proven) brain malignancy will require confirmed 
suspicion from a neurosurgery and neuroradiology collaborator. 
 
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3 
ELIGIBILITY 
3.1 
Inclusion Criteria 
 
Patients 
• 13 years old and above. 
• Written Informed consent must be obtained by the patient (age 13-17)’s parent or legally 
authorized representative (LAR) 
• Patients must meet one set of inclusion criteria: 
o Newly identified and untreated primary brain tumor or metastasis of at least 5 mm 
or greater in size. 
 Suspected central nervous system neoplasms will require agreement from 
a study neuroradiologist and a study neurosurgeon, neuro-oncologist, or a 
radiation oncology that a lesion exists that is most likely either a primary 
brain tumor or a metastasis. 
 Patients with suspected brain metastasis must also have a history of solid 
organ malignancy. 
o History of primary brain tumor or metastasis treated with surgery, radiation, 
chemotherapy, or immunotherapy with new or increasing signal on MR imaging 
that is suspicious for progressive disease (treatment failure). 
 Suspected recurrent neoplasms will require agreement from a study 
neuroradiologist and a study neurosurgeon, radiation oncologist, or neuro-
oncologist that lesion behavior is suspicious for recurrent disease. 
Healthy Volunteers 
• Volunteers without history of brain cancer. 
• 13 years old and above. 
• No pregnant subjects will be enrolled. 
• No contraindications to MR exam(s) – healthy volunteers will use the same screening 
process utilized for MDACC patients. 
• Written Informed consent must be obtained by the patient (age 13-17)’s parent or legally 
authorized representative (LAR) 
 
3.2 
Exclusion Criteria 
 
Patients 
• Contraindication to MR imaging. 
• Absolute or relative contra-indication to 3T MRI due to metallic foreign bodies and 
devices and/or other conditions that are not MR safe, which include implants with 
unknown behavior in 3T MRI as well as: 
o electronically, magnetically, and mechanically activated implants 
o ferromagnetic or electronically operated active devices like automatic cardioverter 
defibrillators and cardiac pacemakers 
o metallic splinters in the eye 
o ferromagnetic hemostatic clips in the central nervous system (CNS) or body 
o cochlear implants 
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o other pacemakers, e.g., for the carotid sinus 
o insulin pumps and nerve stimulators 
o non-MR safe lead wires 
o prosthetic heart valves (if dehiscence is suspected) 
o non-ferromagnetic stapedial implants 
• pregnancy 
• Claustrophobia that does not readily respond to oral medication 
• Known allergy to gadolinium-based contrast agents. 
• Renal failure as defined by a GFR less than 30 or the use of hemodialysis. 
• Pregnant. 
• Patients less than 13 years of age will be excluded. 
• Interval treatment with radiation or surgery between the diagnostic MRI lesion 
identification and planned study MRI. 
• Wards of the state 
 
3.3 
NUMBER OF PARTICIPANTS 
 
One hundred (100) patients will be studied. Up to twenty (20) healthy volunteers will be studied 
for the purposes of MRI sequence optimization.  
 
4 
STUDY PLAN/DESIGN 
4.1 
Patient Enrollment: 
 
Patients being evaluated for treatment of a suspected brain malignancy at MD Anderson Cancer 
Center will be screened for eligibility based on their screening diagnostic MRI scan and available 
clinical information.  Once eligibility is confirmed, patients will be approached for protocol 
introduction and consenting and enrollment. Attempts will be made to scan patients in the 7T 
system within 30 days of an MRI scan performed at either 3T or 1.5T.   
 
Up to twenty (20) healthy volunteers will be recruited through local advertisement for the 
purposes of MRI sequence optimization. Volunteers will be scanned in accordance with the 
UTMDACC Division of Diagnostic Imaging Policy # 3.00: Imaging of Healthy Volunteers for 
Quality Assurance/Improvement and Technical Development. 
 
4.2 
Procedure to Obtain Consent  
 
The patients and volunteers will be approached in person or using IRB approved remote consent 
procedures by either the Diagnostic Imaging (DI) faculty or Research Staff, including research 
nurses and research coordinators for their approval before their procedure. For subjects’ age 13-
17 years old, a parental or LAR permission must be obtained and documented that the informed 
consent  occurred prior to the study subject’s entry into the study and prior to any study related 
procedures.  During the consenting process, patients will be educated and consented for their 
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research participation in this study. All subjects and volunteers who meet eligibility and 
complete the informed consent process will be registered in UTMDACC CORe system. 
 
4.3 
Houston Methodist Research Institute (HMRI) Registration 
 
If inclusion/exclusion criteria are met and patients agree to participate in the study, the research 
study team will then contact the Houston Methodist Research Institute (HMRI) to register the 
patient and schedule their research MRI scan. Patient information including patient name, date of 
birth, prior allergic reaction to gadolinium based contrast agents, prior surgical history (as it 
pertains to surgical implants which may be a contraindication to MR scanning) which will be 
provided to HMRI as part of the study procedure (Appendix A – MRI Safety Questionnaire) and 
Referral Questionnaire for MDACC (Appendix B).  
   
A copy of the completed MRI safety questionnaire and Referral Questionnaire for MDACC will 
be stored in REDCap and only authorized members of research team from MD Anderson (MDA) 
& HMRI who signed the delegation of authority log will have access to the data.  
 
Research patients and volunteers will be contacted by MDA DI research study staff and given 
instruction for their research MRI scan once it is scheduled at HMRI.    
 
4.4 
MR Scanning: 
 
Patients: 
 
The study MRI will be performed on a 7.0-T MRI system. All patients will undergo 
conventional anatomic MR imaging including 3D T1 pre and post-contrast weighted 
imaging, 3D T2 weighted imaging, 3D T1 SPACE post-contrast, dynamic contrast-enhanced 
perfusion imaging, magnetic resonance spectroscopic imaging, functional magnetic 
resonance imaging (speech and motor paradigm), as well as the study-specific sequences to 
include: 
 
• Quantitative MRI 
• CEST 
• Adv Diff 
 
• Adv ASL 
 
The entire scan time is expected to be approximately sixty (60) minutes. Routine and study 
sequences obtained on the 7T system may be obtained with the system in parallel transmit 
(pTx) scanning mode. Scanning in pTx mode can lead to increases in specific absorption rate 
(SAR) compared to single transmit mode; however, system software controls and sequences 
in both modes adheres to non-significant risk standards as defined by both IEC 60601 and the 
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US Food & Drug Administration including specifically that the SAR for the head will be less 
than 3.2W/kg head. 
 
Volunteers: 
 
 
The study MRI will be performed on a 7.0-T MRI system. Volunteers will not get an IV line 
placed or receive contrast as per UTMDACC Division of Diagnostic Imaging Policy # 3.00: 
Imaging of Healthy Volunteers for Quality Assurance/Improvement and Technical 
Development. 
 
 
Volunteers will undergo a selection of research sequences above for the purposes of 
sequence optimization and quality assurance. The volunteer scan time is expected to be 
approximately sixty (60) minutes. Routine and study sequences obtained on the 7T system 
may be obtained with the system in parallel transmit (pTx) scanning mode. Scanning in pTx 
mode can lead to increases in specific absorption rate (SAR) compared to single transmit 
mode; however, system software controls and sequences in both modes adheres to non-
significant risk standards as defined by both IEC 60601 and the US Food & Drug 
Administration including specifically that the SAR for the head will be less than 3.2W/kg 
head. 
 
4.5 
Patient experience survey 
Patients will be given a one-page survey regarding their experience in the 7T MRI system 
following their scan. For subjects’ age 13-17 years old, Research study staff will review 
questionnaires for completeness and ask subjects with the presence of subject’s parent or LAR to 
complete any missing responses. 
4.5.1 [Appendix A] 
 
4.6 
Imaging Time Points 
4.6.1 A single research imaging session will be planned for each patient.  However, patients 
will still undergo follow-up imaging scans as part of their standard of care.  These follow-
up scans will serve as the basis for statistical analyses that consider treatment response or 
disease recurrence. 
 
4.7 
Conclusion of Study Participation: 
4.7.1 Completion of planned study or volunteer scan. 
4.7.2 Upon patient or volunteer request. 
4.7.3 Death. 
 
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5 
Image Analysis 
5.1 
Lesion size evaluation: 
5.1.1 A patient must have a single intraaxial brain lesion of 5 mm or greater for study inclusion 
as measured on either T2-weighted or T1-post contrast weighted imaging.   
5.1.2 Lesions will be measured on either axial T2 FLAIR weighted or T1 post-contrast imaging 
on a slice displaying the maximal lesion size using the longest diameter after appropriate 
magnification on the picture archiving and communicating system (PACS) monitors.  
5.1.3 For patients with multiple lesions appropriate for study assessment, the five (5) largest 
lesions will be assessed. 
 
5.2 
Lesion CNR evaluation: 
5.2.1 The largest circular ROI that fits within the lesion on axial T1 post-contrast imaging will 
be placed and will define the lesion ROI. 
5.2.2 The ROI mean signal intensity will be recorded. 
5.2.3 A mirror ROI will be placed in the contralateral normal-appearing white matter and used 
as the "background" mean signal intensity measurement.  
5.2.4 An extracranial ROI without visible artifact will be used as the “noise” mean signal 
intensity measurement. 
 
5.3 
Quantitative MRI 
5.3.1 The largest circular ROI that fits within the lesion on axial T1 post-contrast imaging will 
be placed and will define the lesion ROI. 
5.3.2 The T1 and T2 tissue weighting that maximizes the ROI mean signal intensity will be 
identified. 
5.3.3 A mirror ROI will be placed in the contralateral normal-appearing white matter and used 
as the "background" mean signal intensity measurement.  
5.3.4 An extracranial ROI without visible artifact will be used as the mean “noise” signal 
intensity measurement. 
 
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5.4 
CEST MRI 
5.4.1 The largest circular ROI that fits within the lesion on axial T1 post-contrast imaging will 
be placed and will define the lesion ROI. 
5.4.2 The mean signal intensity for a corresponding ROI location on the processed CEST data 
will be recorded. 
5.4.3 A mirror ROI will be placed in the contralateral normal-appearing white matter on the 
processed CEST data will be used as the “background” mean signal intensity 
measurement.  
5.4.4 An extracranial ROI without visible artifact will be used as the “noise” mean signal 
intensity measurement. 
 
5.5 
Multiple B Value Diffusion Imaging (Adv Diff) 
5.5.1 The largest circular ROI that fits within the lesion on axial T1 post-contrast imaging will 
be placed and will define the lesion ROI. 
5.5.2 The AKC for the lesion will be determined using B-values of 0, 1000, and 2000 mm2/s.  
5.5.3 The ADC of the lesion will also be determined using B-values of 0 and 1000 mm2/s. 
5.5.4 A mirror ROI will be placed in the contralateral normal-appearing white matter, and 
"background" AKC and ADC measurement will be measured. 
 
5.6 
Adv ASL 
5.6.1 The largest circular ROI that fits within the lesion on axial T1 post-contrast imaging will 
be placed and will define the lesion ROI. 
5.6.2 This ROI will be used to assess the cerebral blood flow (CBF) from the processed ASL 
data. 
5.6.3 A mirror ROI will be placed in the contralateral normal-appearing white matter for 
assessment of the “background” CBF.  
5.6.4 This ROI will be used to assess the bolus arrival time (BAT) from the processed ASL 
data. 
 
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5.7 
Task-based fMRI 
5.7.1 fMRI data will be analyzed using custom software, IClinfMRI.  
5.7.2 The general linear model will be used to generate an activation t-value map for each task-
based fMRI data. The model includes the convolution of the task paradigms with a 
canonical hemodynamic response function. 
5.7.3 Significantly activated areas will be determined by thresholding the t-value map at 
corrected P < .05. 
 
5.8 
Resting-state fMRI 
5.8.1 Resting-state datasets will be pre-processed through slice timing, motion correction, de-
spiking, detrending, regressing out covariates (including six motion parameters and two 
averaged fluctuations over masks of white matter and cerebrospinal fluid), band-pass 
filtering of 0.01-0.08 Hz, and 4-mm FWHM smoothing.  
5.8.2 Functional connectivity maps will be generated by using both seed-based analysis and 
independent component analysis.  
5.8.3 For the seed-based analysis, seed locations will be determined by anatomical motor and 
language areas with the assistance of a regional homogeneity map.   
5.8.4 For the independent component analysis, 30-50 independent components will be 
determined, and the relevant functional connectivity maps will be determined with 
template matching and inspection by neuroradiologists.  
 
5.9 
Radiation planning validation 
5.9.1 A 3D T1 SPACE sequence will be obtained to validate the ability of UHF MRI to 
provide acceptable levels of geometric distortion for radiation therapy planning purposes. 
5.9.2 The specific parameters of the sequence will be optimized to maximize contrast and 
minimize artifact and distortion.  
5.9.3 The geometric distortion will be evaluated with a full-field geometric distortion phantom 
to assess the geometric accuracy of the SPACE sequence with its specific parameters.  
5.9.4 For radiation therapy purposes, the geometric distortion of less than 1mm is desired for 
the typical head field of view and 2 mm is the targeted limit for the useable field of view 
 
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6 
Patient Information Confidentiality Plan 
6.1 
Collection of Identifiers:   
The patient identifiers that will be collected in this study consist of patient medical record numbers 
and dates. Electronic data will be kept securely at MD Anderson (password protected behind the 
institution firewall). 
 
The study will be performed following institutional policies for the use of existing medical 
information for research. Confidentiality will be maintained throughout the study. No identifying 
information will be used in any publication from this study. Electronic study data will be stored 
on password-protected institution computers behind the institution firewall. Only the PI and 
collaborators who have completed Human Subject Protection Training (HSPT) will have access 
to the study data. 
 
6.2 
Training of personnel:  
Only MDACC personnel designated by the PI who have completed HSPT training will have 
access to study records.  These personnel will be fully trained to maintain patient health 
information confidentiality. 
 
6.3 
Data Storage: 
Electronic study data will be kept on password-protected computers behind the institution 
firewall.  Paper records (data forms, and unique identifiers, etc.) will be kept in a locked file 
cabinet with access granted only to study investigators and research staff. 
 
6.4 
Data Sharing: 
Study will utilize REDCap to store and share data with study collaborators and research staff 
with HMRI.  Only authorized members of research team from MDA & HMRI who signed the 
delegation of authority log will have access to the data in REDCap. 
 
Study data will be collected and managed using the REDCap (Research Electronic Data Capture) 
system hosted at MD Anderson. REDCap (www.project-redcap.org) is a secure, web-based 
application with controlled access designed to support data capture for research studies, 
providing: 1) an intuitive interface for validated data entry; 2) audit trails for tracking data 
manipulation and export procedures; 3) automated export procedures for seamless downloads to 
common statistical packages; and 4) procedures for importing data from external sources. 
REDCap (https://redcap.mdanderson.org) is hosted on a secure server by MD Anderson Cancer 
Center's Department of Oncology Care & Research Information Systems. REDCap has 
undergone an annual Governance Risk & Compliance Assessment (since May 2014) by MD 
Anderson's Information Security Office and found to be compliant with HIPAA, Texas 
Administrative Codes 202-203, University of Texas Policy 165, federal regulations outlined in 
21CFR Part 11, and UTMDACC Institutional Policy #ADM0335. 
 
Those having access to the data include the study PI and research team personnel at MDA & 
HMRI. Internal users are authenticated against MDACC's Active Directory system. External 
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users will be granted access to the study.  The application is accessed through Secure Socket 
Layer (SSL). The linking of patient protected health information (PHI) will be removed from the 
data when it is exported from REDCap for final analysis. All dates for a given subject will be 
shifted by a randomly generated number between 0 and 364, thus preserving the distance 
between dates. Dates for each subject will be shifted by a different randomly generated number. 
 
The digital imaging data will be stored on secure servers held by HMRI. Access to these research 
images in the HMRI will be restricted to Dr. Steven Fung, Dr. Robert Rostomily or the 
authorized research personnel at HMRI who will oversee the release of research MRI images of 
this IRB protocol and shared with Dr. Max Wintermark, Principal Investigator of this IRB 
protocol: 2019-1032. Complete confidentiality will be maintained; the investigators will be 
responsible for the transmission, sharing and storage of research imaging data.  
 
6.5 
Final Disposition of study records: 
After publication, any printed paper records will be placed into the Shred-it confidential waste bins 
for disposition. The study will be performed following current institutional standards for the use 
of existing medical information, banking the data, and identifiers for research. There will be no 
further use of the study data without prior review and approval by the IRB. 
 
7 
STATISTICAL CONSIDERATIONS   
7.1 
Definitions 
7.1.1 Lesion “treatment response” will be defined by size and contrast to noise ratio (CNR).  
Treatment response will be assessed only in patients with treatment prior to enrollment. 
7.1.1.1 Size – treatment response in a single lesion will be considered as a decrease in size of 
30%. (see section 5.1) 
7.1.1.2 CNR—treatment response will be considered as a decrease in T1 post-contrast CNR of 
at least 20%. (see section 5.2) by standard T1 post-contrast imaging.  
7.1.1.3 Lesions that do not meet these criteria for treatment response will be considered 
treatment failure. 
7.1.2 Disease recurrence will be determined by surgical pathology (if available) or at least 
three months of imaging follow-up.  Disease recurrence will be assessed only in patients 
with treatment prior to enrollment. Imaging findings will be considered recurrent disease 
in a lesion if: 
7.1.2.1 The lesion was initially considered to be a treatment responder. 
7.1.2.2 The lesion showed a successive increase in the size of 25% from nadir or a single 
imaging time point increase of 40%. (see section 5.1) 
7.1.2.3 Lesions that do not meet these criteria will be considered radiation necrosis. 
 
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7.2 
Overview 
 
Patients with untreated disease (new lesions) will be categorized as having brain metastasis, 
primary brain tumor, or non-tumor based upon the following: 
 
1. Patients with well-defined intra-axial lesions seen in the setting of pathology-proven solid 
organ malignancy will be considered metastasis. 
2. Patients without history of a primary malignancy and agreement on a likely diagnosis of 
primary brain tumor by both a neurosurgical and neuroradiology co-investigator will be 
considered primary brain tumor. 
3. Patients that do not the above criteria will be categorized as having non-tumor. 
 
Patients in categories 1 and 2 will be further classified as having received treatment and not 
having received treatment. 
 
 
 
 
7.3 
Sample Size 
 
The healthy volunteers’ data will only be used for fMRI sequence optimization, quality 
assurance and will not yield data for the study.  The optimization scans on healthy volunteers 
will not affect the statistical results. 
 
Patients will be divided into 5 groups as discussed above.  It is assumed that 90% of patients 
enrolled will represent either brain metastasis or primary brain tumor, approximately half in each 
category. We also expect approximately half of each group to have received treatment.  We thus 
expect to have approximately 20-25 patients in each of the first four groups (metastasis with and 
without treatment and primary brain tumor with and without treatment).  The other 10% will be 
in group 5 and are assumed to be non-tumor mimics of malignancy (for example, stroke, 
demyelinating disease).  
 
For the primary endpoints, the objective is to calculate the contrast-to-noise ratio (CNR) or 
equivalent parameter for each method for both primary brain tumors and metastases separately 
by whether the patient has received treatment.  For each imaging modality, we will calculate the 
CNR separately in the largest lesion/metastasis per patient as well as in all study lesions (see 
5.1.3).  As an example, for CEST, under the assumption of only a single lesion per patient and an 
expected mean CEST CNR of 14.9 and corresponding standard deviation of 3.0, 20 patients in a 
group will give a 95% confidence interval between 13.6 and 16.2. [40] Similar calculations apply 
for the CNR for each of the other imaging modalities. 
 
We may also combine groups for the purpose of analysis.  Continuing the above example, with 
45 patients in a group, and the same assumed mean and standard deviation, a 95% confidence 
interval around the CEST CNR will range from 14.0 to 15.8.  Again, similar calculations apply 
for other imaging modalities. 
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7.4 
Analysis Plan 
 
Patients with metastasis are expected to have on average 2-3 detectable brain lesions each. 
Patients with primary brain tumors are expected to have a single lesion.  All analyses will be 
performed on the largest lesion within patients, and some analyses will be repeated on a per-
lesion basis.  
 
The CNR for each imaging method will be determined and reported along with the 
corresponding 95% confidence interval.  In secondary analyses, for the conspicuity endpoints, 
the T1 sequence by MRI will be considered the gold standard, and we will compare the 
conspicuity of each of the other methods to that of T1 sequencing by using McNemar’s test.  
This analysis will first be performed in the largest lesion per patient, and then analyses will be 
repeated using all lesions. 
 
If enough follow-up images are obtained (see section 4.5), we will compare the CNR in lesions 
that respond to treatment to those that do not by using a Wilcoxon rank-sum test.  We will 
compare the CNR between baseline and follow-up within patient by using a Wilcoxon signed-
rank test.  Also, for those lesions that initially respond, some will subsequently grow in size after 
the initial response.  Of these, some will be considered radiation necrosis and some progressive 
disease.  The CNR will be compared between lesions with necrosis and those that are progressive 
disease using a Wilcoxon rank-sum test. 
 
Exploratory aims will be analyzed with descriptive statistics. fMRI paradigms will be 
summarized by the group mean and standard deviation.  Patient satisfaction will be reported on a 
five-point Likert scale and compared between the 7T scan and the most recent clinical scan by 
using a Wilcoxon rank-sum test. 
 
8 
PROTOCOL MONITORING PLAN 
 
This is not a treatment study, and no adverse effects are anticipated related to contrast-enhanced 
MR imaging. There is a tiny risk of an allergic reaction to the gadolinium-based contrast agent 
for which the patient will go through regular Departmental screening. 
 
The principal investigator is responsible for monitoring the study and the safety of patients who 
enroll in the study.  Approval is required to share study data and images with individuals or 
entities specified in a data or material transfer agreement. 
 
Reports will be provided to the IRB as per current institutional policies for the use of existing 
medical information for research. This study will be approved by the Institutional Review Board 
at MD Anderson and Houston Methodist Research Institute for the Protection of Human 
Subjects. Participants will be protected according to the processes outlined by the MD Anderson 
IRB.  
 
Personal information will be protected by taking the following measures:  
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• All HIPAA identifiers including names and medical records will be kept in a confidential 
manner, stored behind the institutional firewall.  Paper copy will be stored in locked file 
in the office of a study investigators and authorized research staff.    
• Data will be shared with HMRI investigators and staff and only as required to fulfill this 
research goals and objectives.  
• Study data will be stored into REDCap. Access will be granted to HMRI and MDA study 
investigators and research staff authorized by the PI. 
• A study code number rather than the participants’ real names will be used on the research 
transcribed documents. This code linking the participants’ demographic information will 
be known only to the study staff and will be kept in a separate locked cabinet in the 
locked PI’s office at MD Anderson.  
• Study data will be stored permanently on a secure institutional computer behind the 
institutional firewall in the office of the PI.  
• REDCap will be utilized to store study data, forms, questionnaires and research MRI 
images.  
• Only the study investigators and authorized research study staff who signed the 
delegation of authority log will have access to the study data.  
• Study data will be collected and managed using an UT MD Anderson Cancer 
Center – approved database. The investigators will be responsible for data 
processing, in accordance with the institution`s data management procedures. 
 
 
9 
REFERENCES 
 
1. 
Glioblastoma. In: http://www.cancermoonshots.org/cancer-types glioblastoma. Accessed 
13 Jul 2019 
2. 
Hamstra DA, Galbán CJ, Meyer CR, et al (2008) Functional diffusion map as an early 
imaging biomarker for high-grade glioma: correlation with conventional radiologic 
response and overall survival. Journal of Clinical Oncology 26:3387–3394. doi: 
10.1200/JCO.2007.15.2363 
3. 
Hu LS, Baxter LC, Pinnaduwage DS, et al (2010) Optimized Preload Leakage-Correction 
Methods to Improve the Diagnostic Accuracy of Dynamic Susceptibility-Weighted 
Contrast-Enhanced Perfusion MR Imaging in Posttreatment Gliomas. AJNR Am J 
Neuroradiol 31:40–48. doi: 10.3174/ajnr.A1787 
4. 
Bobek-Billewicz B, Stasik-Pres G, Majchrzak H, Zarudzki L (2010) Differentiation 
between brain tumor recurrence and radiation injury using perfusion, diffusion-weighted 
imaging and MR spectroscopy. Folia Neuropathol 48:81–92. 
5. 
Hygino da Cruz LC, Rodriguez I, Domingues RC, et al (2011) Pseudoprogression and 
pseudoresponse: imaging challenges in the assessment of posttreatment glioma. AJNR 
Am J Neuroradiol 32:1978–1985. doi: 10.3174/ajnr.A2397 
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6. 
Vöglein J, Tüttenberg J, Weimer M, et al (2011) Treatment monitoring in gliomas: 
comparison of dynamic susceptibility-weighted contrast-enhanced and spectroscopic MRI 
techniques for identifying treatment failure. Invest Radiol 46:390–400. doi: 
10.1097/RLI.0b013e31820e1511 
7. 
Obusez EC, Lowe M, Oh S-H, et al (2018) 7T MR of intracranial pathology: Preliminary 
observations and comparisons to 3T and 1.5T. NeuroImage 168:459–476. doi: 
10.1016/j.neuroimage.2016.11.030 
8. 
Stupp R, Hegi ME, Mason WP, et al (2009) Effects of radiotherapy with concomitant and 
adjuvant temozolomide versus radiotherapy alone on survival in glioblastoma in a 
randomised phase III study: 5-year analysis of the EORTC-NCIC trial. The Lancet 
Oncology 10:459–466. doi: 10.1016/S1470-2045(09)70025-7 
9. 
Ostrom QT, Gittleman H, Liao P, et al (2014) CBTRUS statistical report: primary brain 
and central nervous system tumors diagnosed in the United States in 2007-2011. Neuro-
oncology 16 Suppl 4:iv1–63. doi: 10.1093/neuonc/nou223 
10. 
Ostrom QT, Gittleman H, Xu J, et al (2016) CBTRUS Statistical Report: Primary Brain 
and Other Central Nervous System Tumors Diagnosed in the United States in 2009-2013. 
Neuro-oncology 18:v1–v75. doi: 10.1093/neuonc/now207 
11. 
Stupp R, Mason WP, van den Bent MJ, et al (2005) Radiotherapy plus concomitant and 
adjuvant temozolomide for glioblastoma. N Engl J Med 352:987–996. doi: 
10.1056/NEJMoa043330 
12. 
van den Bent MJ, Vogelbaum MA, Wen PY, et al (2009) End point assessment in 
gliomas: novel treatments limit usefulness of classical Macdonald's Criteria. Journal of 
Clinical Oncology 27:2905–2908. doi: 10.1200/JCO.2009.22.4998 
13. 
Verma G, Mohan S, Nasrallah MP, et al (2016) Non-invasive detection of 2-
hydroxyglutarate in IDH-mutated gliomas using two-dimensional localized correlation 
spectroscopy (2D L-COSY) at 7 Tesla. J Transl Med 14:274. doi: 10.1186/s12967-016-
1035-1 
14. 
Li Y, Lafontaine M, Chang S, Nelson SJ (2018) Comparison between Short and Long 
Echo Time Magnetic Resonance Spectroscopic Imaging at 3T and 7T for Evaluating Brain 
Metabolites in Patients with Glioma. ACS Chem Neurosci 9:130–137. doi: 
10.1021/acschemneuro.7b00286 
15. 
Patel AJ, Suki D, Hatiboglu MA, et al (2010) Factors influencing the risk of local 
recurrence after resection of a single brain metastasis. J Neurosurg 113:181–189. doi: 
10.3171/2009.11.JNS09659 
16. 
Kaye AH, Laws ER (2001) Brain Tumors. Gulf Professional Publishing 
Proprietary Information of MD Anderson

Protocol No: 2019-1032 
Version No: 10 
Version Date: August 25, 2023 
27 
 
17. 
Mayr NA, Yuh WT, Muhonen MG, et al (1994) Cost-effectiveness of high-dose MR 
contrast studies in the evaluation of brain metastases. AJNR Am J Neuroradiol 15:1053–
1061. 
18. 
Barajas RF, Cha S (2012) Imaging diagnosis of brain metastasis. Prog Neurol Surg 25:55–
73. doi: 10.1159/000331174 
19. 
Smith TE, Steven A, Bagert BA (2019) Gadolinium Deposition in Neurology Clinical 
Practice. Ochsner J 19:17–25. doi: 10.31486/toj.18.0111 
20. 
Caraiani C, Dong Y, Rudd AG, Dietrich CF (2018) Reasons for inadequate or incomplete 
imaging techniques. Med Ultrason 20:498–507. doi: 10.11152/mu-1736 
21. 
Beck ES, Sati P, Sethi V, et al (2018) Improved Visualization of Cortical Lesions in 
Multiple Sclerosis Using 7T MP2RAGE. AJNR Am J Neuroradiol 39:459–466. doi: 
10.3174/ajnr.A5534 
22. 
Warntjes JBM, Leinhard OD, West J, Lundberg P (2008) Rapid magnetic resonance 
quantification on the brain: Optimization for clinical usage. Magn Reson Med 60:320–
329. doi: 10.1002/mrm.21635 
23. 
Kvernby S, Warntjes MJB, Haraldsson H, et al (2014) Simultaneous three-dimensional 
myocardial T1 and T2 mapping in one breath hold with 3D-QALAS. J Cardiovasc Magn 
Reson 16:102. doi: 10.1186/s12968-014-0102-0 
24. 
Tanenbaum LN, Tsiouris AJ, Johnson AN, et al (2017) Synthetic MRI for Clinical 
Neuroimaging: Results of the Magnetic Resonance Image Compilation (MAGiC) 
Prospective, Multicenter, Multireader Trial. AJNR Am J Neuroradiol 38:1103–1110. doi: 
10.3174/ajnr.A5227 
25. 
Blystad I, Warntjes JBM, Smedby O, et al (2012) Synthetic MRI of the brain in a clinical 
setting. Acta Radiol 53:1158–1163. doi: 10.1258/ar.2012.120195 
26. 
Hagiwara A, Hori M, Suzuki M, et al (2016) Contrast-enhanced synthetic MRI for the 
detection of brain metastases. Acta Radiol Open 5:2058460115626757. doi: 
10.1177/2058460115626757 
27. 
Dula AN, Asche EM, Landman BA, et al (2011) Development of chemical exchange 
saturation transfer at 7 T. Magn Reson Med 66:831–838. doi: 10.1002/mrm.22862 
28. 
Moseley ME, Kucharczyk J, Mintorovitch J, et al (1990) Diffusion-weighted MR imaging 
of acute stroke: correlation with T2-weighted and magnetic susceptibility-enhanced MR 
imaging in cats. AJNR Am J Neuroradiol 11:423–429. 
29. 
Sener RN (2001) Diffusion MRI: apparent diffusion coefficient (ADC) values in the 
normal brain and a classification of brain disorders based on ADC values. Computerized 
Medical Imaging and Graphics 25:299–326. doi: 10.1016/S0895-6111(00)00083-5 
Proprietary Information of MD Anderson

Protocol No: 2019-1032 
Version No: 10 
Version Date: August 25, 2023 
28 
 
30. 
Taylor W (2003) Diffusion tensor imaging: background, potential, and utility in 
psychiatric research. Biological Psychiatry. doi: 10.1016/S0006-3223(03)00813-8 
31. 
Wang X-C, Lei Y, Wang L, et al (2018) Diffusion Kurtosis Imaging Reflects Glial 
Fibrillary Acidic Protein (GFAP), Topo IIα, and O⁶-Methylguanine-DNA 
Methyltransferase (MGMT) Expression in Astrocytomas. Med Sci Monit 24:8822–8830. 
doi: 10.12659/MSM.911631 
32. 
Jensen JH, Helpern JA (2010) MRI quantification of non-Gaussian water diffusion by 
kurtosis analysis. NMR Biomed 23:698–710. doi: 10.1002/nbm.1518 
33. 
Fujima N, Sakashita T, Homma A, et al (2018) Utility of a Hybrid IVIM-DKI Model to 
Predict the Development of Distant Metastasis in Head and Neck Squamous Cell 
Carcinoma Patients. Magn Reson Med Sci 17:21–27. doi: 10.2463/mrms.mp.2016-0136 
34. 
Falk Delgado A, Nilsson M, van Westen D, Falk Delgado A (2018) Glioma Grade 
Discrimination with MR Diffusion Kurtosis Imaging: A Meta-Analysis of Diagnostic 
Accuracy. Radiology 287:119–127. doi: 10.1148/radiol.2017171315 
35. 
Yang X, Holmes MJ, Newton AT, et al (2012) A Comparison of Distributional 
Considerations with Statistical Analysis of Resting State fMRI at 3T and 7T. Proc SPIE 
Int Soc Opt Eng 8314:831416. doi: 10.1117/12.911307 
36. 
(2019) Characterizing Microstructural Tissue Properties in Multiple Sclerosis with 
Diffusion MRI at 7 T and 3 T: The Impact of the Experimental Design. Neuroscience 
403:17–26. doi: 10.1016/j.neuroscience.2018.03.048 
37. 
Fink JR, Muzi M, Peck M, Krohn KA (2015) Multimodality Brain Tumor Imaging: MR 
Imaging, PET, and PET/MR Imaging. J Nucl Med 56:1554–1561. doi: 
10.2967/jnumed.113.131516 
38. 
Boxerman JL, Ellingson BM, Jeyapalan S, et al (2017) Longitudinal DSC-MRI for 
Distinguishing Tumor Recurrence From Pseudoprogression in Patients With a High-grade 
Glioma. Am J Clin Oncol 40:228–234. doi: 10.1097/COC.0000000000000156 
39. 
Chaskis C, Stadnik T, Michotte A, et al (2006) Prognostic value of perfusion-weighted 
imaging in brain glioma: a prospective study. Acta Neurochir 148:277–85– discussion 
285. doi: 10.1007/s00701-005-0718-9 
40. 
Barajas RF Jr, Chang JS, Segal MR, et al (2009) Differentiation of Recurrent 
Glioblastoma Multiforme from Radiation Necrosis after External Beam Radiation 
Therapy with Dynamic Susceptibility-weighted Contrast-enhanced Perfusion MR Imaging 
1. Radiology 253:486–496. doi: 10.1148/radiol.2532090007 
41. 
Boxerman JL, Zhang Z, Safriel Y, et al (2013) Early post-bevacizumab progression on 
contrast-enhanced MRI as a prognostic marker for overall survival in recurrent 
glioblastoma: results from the ACRIN 6677/RTOG 0625 Central Reader Study. Neuro-
oncology 15:945–954. doi: 10.1093/neuonc/not049 
Proprietary Information of MD Anderson

Protocol No: 2019-1032 
Version No: 10 
Version Date: August 25, 2023 
29 
 
42. 
Boxerman JL, Hamberg LM, Rosen BR, Weisskoff RM (1995) MR contrast due to 
intravascular magnetic susceptibility perturbations. Magn Reson Med 34:555–566. 
43. 
Kiselev VG, Strecker R, Ziyeh S, et al (2005) Vessel size imaging in humans. Magn 
Reson Med 53:553–563. doi: 10.1002/mrm.20383 
44. 
Kang H-Y, Xiao H-L, Chen J-H, et al (2016) Comparison of the Effect of Vessel Size 
Imaging and Cerebral Blood Volume Derived from Perfusion MR Imaging on Glioma 
Grading. AJNR Am J Neuroradiol 37:51–57. doi: 10.3174/ajnr.A4477 
45. 
Zaiss M, Windschuh J, Paech D, et al (2015) Relaxation-compensated CEST-MRI of the 
human brain at 7T: Unbiased insight into NOE and amide signal changes in human 
glioblastoma. NeuroImage 112:180–188. doi: 10.1016/j.neuroimage.2015.02.040 
46. 
Cai K, Singh A, Poptani H, et al (2015) CEST signal at 2ppm (CEST@2ppm) from Z-
spectral fitting correlates with creatine distribution in brain tumor. NMR Biomed 28:1–8. 
doi: 10.1002/nbm.3216 
47. 
Zhou J, Payen J-F, Wilson DA, et al (2003) Using the amide proton signals of intracellular 
proteins and peptides to detect pH effects in MRI. Nat Med 9:1085–1090. doi: 
10.1038/nm907 
48. 
Zhou J, Tryggestad E, Wen Z, et al (2011) Differentiation between glioma and radiation 
necrosis using molecular magnetic resonance imaging of endogenous proteins and 
peptides. Nat Med 17:130–134. doi: 10.1038/nm.2268 
49. 
Togao O, Yoshiura T, Keupp J, et al (2014) Amide proton transfer imaging of adult 
diffuse gliomas: correlation with histopathological grades. Neuro-oncology 16:441–448. 
doi: 10.1093/neuonc/not158 
50. 
Williams DS, Detre JA, Leigh JS, Koretsky AP (1992) Magnetic resonance imaging of 
perfusion using spin inversion of arterial water. Proc Natl Acad Sci USA 89:212–216. doi: 
10.1073/pnas.89.1.212 
51. 
Wolf RL, Detre JA (2007) Clinical Neuroimaging Using Arterial Spin-Labeled Perfusion 
Magnetic Resonance Imaging. Neurotherapeutics 4:346–359. doi: 
10.1016/j.nurt.2007.04.005 
52. 
Liebeskind DS (2003) Collateral Circulation. Stroke 34:2279–2284. doi: 
10.1161/01.STR.0000086465.41263.06 
53. 
Calamante F, Williams SR, van Bruggen N, et al (1996) A Model for Quantification of 
Perfusion in Pulsed Labelling Techniques. NMR Biomed 9:79–83. doi: 
10.1002/(SICI)1099-1492(199604)9:2<79::AID-NBM399>3.0.CO;2-4 
54. 
Warmuth C, Günther M, Zimmer C (2003) Quantification of Blood Flow in Brain 
Tumors: Comparison of Arterial Spin Labeling and Dynamic Susceptibility-weighted 
Proprietary Information of MD Anderson

Protocol No: 2019-1032 
Version No: 10 
Version Date: August 25, 2023 
30 
 
Contrast-enhanced MR Imaging1. Radiology 228:523–532. doi: 
10.1148/radiol.2282020409 
55. 
Bokkers RP, Bremmer JP, van Berckel BN, et al (2009) Arterial Spin Labeling Perfusion 
MRI at Multiple Delay Times: A Correlative Study with H215O Positron Emission 
Tomography in Patients with Symptomatic Carotid Artery Occlusion:. Journal of Cerebral 
Blood Flow & Metabolism 30:222–229. doi: 10.1038/jcbfm.2009.204 
56. 
Dury RJ, Falah Y, Gowland PA, et al (2019) Ultra-high-field arterial spin labelling MRI 
for non-contrast assessment of cortical lesion perfusion in multiple sclerosis. Eur Radiol 
29:2027–2033. doi: 10.1007/s00330-018-5707-5 
 
10 APPENDICES 
 
Appendix A - MRI Safety Questionnaire)  
Appendix B - Referral Questionnaire for MDACC 
Appendix C - UTMDACC Division of Diagnostic Imaging Policy # 3.00: Imaging of Healthy 
Volunteers for Quality Assurance/Improvement and Technical Development. 
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