3D 1H MRSI of brain tumors at 3.0 Tesla using an eight-channel phased-array head coil

Translating preclinical MRI methods to clinical oncology

The complexity of modern in vivo magnetic resonance imaging (MRI) methods in oncology has dramatically changed in the last 10 years. The field has long since moved passed its (unparalleled) ability to form images with exquisite soft-tissue contrast and morphology, allowing for the enhanced identification of primary tumors and metastatic disease. Currently, it is not uncommon to acquire images related to blood flow, cellularity, and macromolecular content in the clinical setting. The acquisition of images related to metabolism, hypoxia, pH, and tissue stiffness are also becoming common. All of these techniques have had some component of their invention, development, refinement, validation, and initial applications in the preclinical setting using in vivo animal models of cancer. In this review, we discuss the genesis of quantitative MRI methods that have been successfully translated from preclinical research and developed into clinical applications. These include methods that interrogate perfusion, diffusion, pH, hypoxia, macromolecular content, and tissue mechanical properties for improving detection, staging, and response monitoring of cancer. For each of these techniques, we summarize the 1) underlying biological mechanism(s); 2) preclinical applications; 3) available repeatability and reproducibility data; 4) clinical applications; and 5) limitations of the technique. We conclude with a discussion of lessons learned from translating MRI methods from the preclinical to clinical setting, and a presentation of four fundamental problems in cancer imaging that, if solved, would result in a profound improvement in the lives of oncology patients. Level of Evidence: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:1377-1392.

In vivo MR spectroscopy predicts high tumor grade in endometrial cancer

Background In vivo magnetic resonance spectroscopy (MRS) enables non-invasive measurements of tumor metabolites. Choline-containing metabolites play a key role in tumor metabolism. Purpose To explore whether preoperative MRS-derived tumor choline levels are associated with clinical and histological features in endometrial carcinomas. Material and Methods Preoperative pelvic magnetic resonance imaging (MRI) (1.5T), including structural and diffusion-weighted imaging and localized multivoxel proton MR (1H-MR) spectroscopy, was performed in 77 prospectively included patients with histologically confirmed endometrial carcinomas. Relative levels of total choline-containing metabolites (tCho) in tumor and myometrium were measured using the ratios: tCho/Creatine; tCho/Water; and tCho/Noise. MRS parameters were analyzed in relation to histological subtype and grade, surgicopathological staging parameters, MRI-measured tumor volume, and tumor apparent diffusion coefficient (ADC) value and clinical outcome. Results Tumor tissue had significantly higher ratios for tCho/Creatine, tCho/Water, and tCho/Noise than normal myometrial tissue ( P < 0.001 for all). High tumor tCho/Water ratio was significantly associated with high tumor grade in endometrioid tumors ( P = 0.02). Tumor tCho/Creatine ratio was positively correlated to MRI-measured tumor volume (r_s = 0.25; P = 0.03). Conclusion High choline levels in tumor are associated with high-risk features. In vivo MRS may potentially aid in the preoperative risk stratification in endometrial cancer.

Combining Functional Studies with Intraoperative MRI in Glioma Surgery

Maximal safe resection is the cornerstone of treatment for low-grade and high-grade gliomas. In addition to high-resolution anatomic MRI studies that highlight tumor architecture, it is important to determine the relationship of the tumor to the eloquent cortical and subcortical areas to avoid introducing or exacerbating a neurologic deficit. The goal of this review was to highlight imaging modalities that provide functional information and can be integrated with intraoperative MRI navigation to maximize the extent of resection while preserving a patient's neurologic function.

Impacts of MR spectroscopic imaging on glioma patient management

Magnetic resonance (MR) modalities are routine imaging tools in the diagnosis and management of gliomas. MR spectroscopic imaging (MRSI), which relies on the metabolic characteristics of tissues, has been developed to accelerate the understanding of gliomas and to aid in effective clinical decision making and development of targeted therapies. In this review, the potentials and practical challenges to frequently use this technique in clinical management of gliomas are discussed. The applications of new biomarkers detectable by MRSI in differential glioma diagnosis, pre- and post-treatment evaluations, and neurosurgery are also addressed.

Strategies for rapid in vivo 1H and hyperpolarized 13C MR spectroscopic imaging

In vivo MRSI is an important imaging modality that has been shown in numerous research studies to give biologically relevant information for assessing the underlying mechanisms of disease and for monitoring response to therapy. The increasing availability of high field scanners and multichannel radiofrequency coils has provided the opportunity to acquire in vivo data with significant improvements in sensitivity and signal to noise ratio. These capabilities may be used to shorten acquisition time and provide increased coverage. The ability to acquire rapid, volumetric MRSI data is critical for examining heterogeneity in metabolic profiles and for relating serial changes in metabolism within the same individual during the course of the disease. In this review we discuss the implementation of strategies that use alternative k-space sampling trajectories and parallel imaging methods in order to speed up data acquisition. The impact of such methods is demonstrated using three recent examples of how these methods have been applied. These are to the acquisition of robust 3D (1)H MRSI data within 5-10 min at a field strength of 3 T, to obtaining higher sensitivity for (1)H MRSI at 7 T and to using ultrafast volumetric and dynamic (13)C MRSI for monitoring the changes in signals that occur following the injection of hyperpolarized (13)C agents.

Automated prescription of oblique brain 3D magnetic resonance spectroscopic imaging

Two major difficulties encountered in implementing Magnetic Resonance Spectroscopic Imaging (MRSI) in a clinical setting are limited coverage and difficulty in prescription. The goal of this project was to automate completely the process of 3D PRESS MRSI prescription, including placement of the selection box, saturation bands and shim volume, while maximizing the coverage of the brain. The automated prescription technique included acquisition of an anatomical MRI image, optimization of the oblique selection box parameters, optimization of the placement of outer-volume suppression saturation bands, and loading of the calculated parameters into a customized 3D MRSI pulse sequence. To validate the technique and compare its performance with existing protocols, 3D MRSI data were acquired from six exams from three healthy volunteers. To assess the performance of the automated 3D MRSI prescription for patients with brain tumors, the data were collected from 16 exams from 8 subjects with gliomas. This technique demonstrated robust coverage of the tumor, high consistency of prescription and very good data quality within the T2 lesion.

Improved spatial coverage for brain 3D PRESS MRSI by automatic placement of outer-volume suppression saturation bands

PURPOSE

To develop a technique for optimizing coverage of brain 3D (1) H magnetic resonance spectroscopic imaging (MRSI) by automatic placement of outer-volume suppression (OVS) saturation bands (sat bands) and to compare the performance for point-resolved spectroscopic sequence (PRESS) MRSI protocols with manual and automatic placement of sat bands.

MATERIALS AND METHODS

The automated OVS procedure includes the acquisition of anatomic images from the head, obtaining brain and lipid tissue maps, calculating optimal sat band placement, and then using those optimized parameters during the MRSI acquisition. The data were analyzed to quantify brain coverage volume and data quality.

RESULTS

3D PRESS MRSI data were acquired from three healthy volunteers and 29 patients using protocols that included either manual or automatic sat band placement. On average, the automatic sat band placement allowed the acquisition of PRESS MRSI data from 2.7 times larger brain volumes than the conventional method while maintaining data quality.

CONCLUSION

The technique developed helps solve two of the most significant problems with brain PRESS MRSI acquisitions: limited brain coverage and difficulty in prescription. This new method will facilitate routine clinical brain 3D MRSI exams and will be important for performing serial evaluation of response to therapy in patients with brain tumors and other neurological diseases.

Assessment of therapeutic response and treatment planning for brain tumors using metabolic and physiological MRI

MRI is routinely used for diagnosis, treatment planning and assessment of response to therapy for patients with glioma. Gliomas are spatially heterogeneous and infiltrative lesions that are quite variable in terms of their response to therapy. Patients classified as having low-grade histology have a median overall survival of 7 years or more, but need to be monitored carefully to make sure that their tumor does not upgrade to a more malignant phenotype. Patients with the most aggressive grade IV histology have a median overall survival of 12-15 months and often undergo multiple surgeries and adjuvant therapies in an attempt to control their disease. Despite improvements in the spatial resolution and sensitivity of anatomic images, there remain considerable ambiguities in the interpretation of changes in the size of the gadolinium-enhancing lesion on T(1) -weighted images as a measure of treatment response, and in differentiating between treatment effects and infiltrating tumor within the larger T(2) lesion. The planning of focal therapies, such as surgery, radiation and targeted drug delivery, as well as a more reliable assessment of the response to therapy, would benefit considerably from the integration of metabolic and physiological imaging techniques into routine clinical MR examinations. Advanced methods that have been shown to provide valuable data for patients with glioma are diffusion, perfusion and spectroscopic imaging. Multiparametric examinations that include the acquisition of such data are able to assess tumor cellularity, hypoxia, disruption of normal tissue architecture, changes in vascular density and vessel permeability, in addition to the standard measures of changes in the volume of enhancing and nonenhancing anatomic lesions. This is particularly critical for the interpretation of the results of Phase I and Phase II clinical trials of novel therapies, which are increasingly including agents that are designed to have anti-angiogenic and anti-proliferative properties as opposed to having a direct effect on tumor cell viability.

Magnetic resonance in the era of molecular imaging of cancer

Magnetic resonance imaging (MRI) has played an important role in the diagnosis and management of cancer since it was first developed, but other modalities also continue to advance and provide complementary information on the status of tumors. In the future, there will be a major continuing role for noninvasive imaging in order to obtain information on the location and extent of cancer, as well as assessments of tissue characteristics that can monitor and predict treatment response and guide patient management. Developments are currently being undertaken that aim to provide improved imaging methods for the detection and evaluation of tumors, for identifying important characteristics of tumors such as the expression levels of cell surface receptors that may dictate what types of therapy will be effective and for evaluating their response to treatments. Molecular imaging techniques based mainly on radionuclide imaging can depict numerous, specific, cellular and molecular markers of disease and have unique potential to address important clinical and research challenges. In this review, we consider what continuing and evolving roles will be played by MRI in this era of molecular imaging. We discuss some of the challenges for MRI of detecting imaging agents that report on molecular events, but highlight also the ability of MRI to assess other features such as cell density, blood flow and metabolism which are not specific hallmarks of cancer but which reflect molecular changes. We discuss the future role of MRI in cancer and describe the use of selected quantitative imaging techniques for characterizing tumors that can be translated to clinical applications, particularly in the context of evaluating novel treatments.

Post-processing correction of the endorectal coil reception effects in MR spectroscopic imaging of the prostate

PURPOSE

To develop and validate a post-processing correction algorithm to remove the effect of the inhomogeneous reception profile of the endorectal coil on MR spectroscopic imaging (MRSI) data.

MATERIALS AND METHODS

A post-processing algorithm to correct for the endorectal coil reception effects on MRSI data was developed based upon theoretical modeling of the endorectal coil reception profile and of the spatial saturation pulse profiles. This algorithm was evaluated on three-dimensional (3D) MRSI data acquired at 3T from a uniform phantom and from 18 patients with known or suspected prostate cancer.

RESULTS

For the phantom data, the coefficient of variation of metabolite peak areas decreased 16% to 46% and the peak area distributions became more Gaussian with correction, as demonstrated by higher Q-Q plot linear correlations (R(2) = 0.98 +/- 0.007 vs. R(2) = 0.89 +/- 0.066). Across the 18 patients, the mean coefficient of variation for suppressed water decreased significantly, from 0.95 +/- 0.18, to 0.66 +/- 0.11, (P < 10(-6), paired t-test) and the linear correlations of the Q-Q plots for the suppressed water increased from R(2) = 0.91 to R(2) = 0.95 (P = 0.0083, paired t-test) with correction.

CONCLUSION

An algorithm for reducing the effect of the inhomogeneous reception profile in endorectal coil acquired 3D MRSI prostate data was demonstrated, illustrating increased homogeneity and more Gaussian peak area distributions.

First intraoperative, shared-resource, ultrahigh-field 3-Tesla magnetic resonance imaging system and its application in low-grade glioma resection

OBJECT

The authors describe the first shared-resource, 3-T intraoperative MR (ioMR) imaging system and analyze its impact on low-grade glioma (LGG) resection with an emphasis on the use of intraoperative proton MR spectroscopy.

METHODS

The Acibadem University ioMR imaging facility houses a 3-T Siemens Trio system and consists of interconnected but independent MR imaging and surgical suites. Neurosurgery is performed using regular ferromagnetic equipment, and a patient can be transferred to the ioMR imaging system within 1.5 minutes by using a floating table. The ioMR imaging protocol takes < 10 minutes including the transfer, and the authors obtain very high-resolution T2-weighted MR images without the use of intravenous contrast. Functional sequences are performed when needed. A new 5-pin headrest-head coil combination and floating transfer table were specifically designed for this system.

RESULTS

Since the facility became operational in June 2004, 56 LGG resections have been performed using ioMR imaging, and > 19,000 outpatient MR imaging procedures have been conducted. First-look MR imaging studies led to further resection attempts in 37.5% of cases as well as a 32.3% increase in the number of gross-total resections. Intraoperative ultrasonography detected 16% of the tumor remnants. Intraoperative proton MR spectroscopy and diffusion weighted MR imaging were used to differentiate residual tumor tissue from peritumoral parenchymal changes. Functional and diffusion tensor MR imaging sequences were used both pre- and postoperatively but not intraoperatively. No infections or other procedure-related complications were encountered.

CONCLUSIONS

This novel, shared-resource, ultrahigh-field, 3-T ioMR imaging system is a cost-effective means of affording a highly capable ioMR imaging system and increases the efficiency of LGG resections.

(1)H spectroscopic imaging of human brain at 3 Tesla: comparison of fast three-dimensional magnetic resonance spectroscopic imaging techniques

PURPOSE

To investigate the signal-to-noise-ratio (SNR) and data quality of time-reduced three-dimensional (3D) proton magnetic resonance spectroscopic imaging ((1)H MRSI) techniques in the human brain at 3 Tesla.

MATERIALS AND METHODS

Techniques that were investigated included ellipsoidal k-space sampling, parallel imaging, and echo-planar spectroscopic imaging (EPSI). The SNR values for N-acetyl aspartate, choline, creatine, and lactate or lipid peaks were compared after correcting for effective spatial resolution and acquisition time in a phantom and in the brains of human volunteers. Other factors considered were linewidths, metabolite ratios, partial volume effects, and subcutaneous lipid contamination.

RESULTS

In volunteers, the median normalized SNR for parallel imaging data decreased by 34-42%, but could be significantly improved using regularization. The normalized signal to noise loss in flyback EPSI data was 11-18%. The effective spatial resolutions of the traditional, ellipsoidal, sensitivity encoding (SENSE) sampling scheme, and EPSI data were 1.02, 2.43, 1.03, and 1.01 cm(3), respectively. As expected, lipid contamination was variable between subjects but was highest for the SENSE data. Patient data obtained using the flyback EPSI method were of excellent quality.

CONCLUSION

Data from all (1)H 3D-MRSI techniques were qualitatively acceptable, based upon SNR, linewidths, and metabolite ratios. The larger field of view obtained with the EPSI methods showed negligible lipid aliasing with acceptable SNR values in less than 9.5 min without compromising the point-spread function.

3D sensitivity encoded ellipsoidal MR spectroscopic imaging of gliomas at 3T

PURPOSE

The goal of this study was to implement time efficient data acquisition and reconstruction methods for 3D magnetic resonance spectroscopic imaging (MRSI) of gliomas at a field strength of 3T using parallel imaging techniques.

METHODS

The point spread functions, signal to noise ratio (SNR), spatial resolution, metabolite intensity distributions and Cho:NAA ratio of 3D ellipsoidal, 3D sensitivity encoding (SENSE) and 3D combined ellipsoidal and SENSE (e-SENSE) k-space sampling schemes were compared with conventional k-space data acquisition methods.

RESULTS

The 3D SENSE and e-SENSE methods resulted in similar spectral patterns as the conventional MRSI methods. The Cho:NAA ratios were highly correlated (P<.05 for SENSE and P<.001 for e-SENSE) with the ellipsoidal method and all methods exhibited significantly different spectral patterns in tumor regions compared to normal appearing white matter. The geometry factors ranged between 1.2 and 1.3 for both the SENSE and e-SENSE spectra. When corrected for these factors and for differences in data acquisition times, the empirical SNRs were similar to values expected based upon theoretical grounds. The effective spatial resolution of the SENSE spectra was estimated to be same as the corresponding fully sampled k-space data, while the spectra acquired with ellipsoidal and e-SENSE k-space samplings were estimated to have a 2.36-2.47-fold loss in spatial resolution due to the differences in their point spread functions.

CONCLUSION

The 3D SENSE method retained the same spatial resolution as full k-space sampling but with a 4-fold reduction in scan time and an acquisition time of 9.28 min. The 3D e-SENSE method had a similar spatial resolution as the corresponding ellipsoidal sampling with a scan time of 4:36 min. Both parallel imaging methods provided clinically interpretable spectra with volumetric coverage and adequate SNR for evaluating Cho, Cr and NAA.

Quantitative proton magnetic resonance spectroscopy detects abnormalities in dorsolateral prefrontal cortex and motor cortex of patients with frontotemporal lobar degeneration

Frontotemporal lobar degeneration (FTLD) is a neurodegenerative disease of the frontal and temporal neocortex. The single most common pathology underlying FTLD is neuronal degeneration with ubiquitin-positive but tau-negative inclusions consisting of Tar DNA binding proteins (TDP-43). Inclusions containing TDP-43 in neurons are also the most common pathology underlying motor neuron disease (MND). The present study tested the hypothesis that abnormal metabolite patterns within the dorsolateral prefrontal cortex (DLPFC) as well as the motor cortex (MC) may be observed in FTLD patients without motor disorders, using proton magnetic resonance spectroscopy ((1)H MRS). Twenty-six FTLD patients with cognitive damage and ten controls underwent multivoxel (1)H MRS. Absolute concentrations of N-acetyl aspartate (NAA), creatine (Cr), choline (Cho) and myo-inositol (mI) were measured from the DLPFC, the MC and the parietal cortex (PC, an internal control). Statistical analyses were performed for group differences between FTLD patients and controls. Comparisons were also made across brain regions (PC and DLPFC; PC and MC) within FTLD patients. Significant reductions in NAA and Cr along with increased Cho and mI were observed in the DLPFC of FTLD patients compared to controls. Significantly lower NAA and higher Cho were also observed in the MCs of patients as compared to controls. Within the FTLD patients, both the MC and the DLPFC exhibited significantly decreased NAA and elevated Cho compared to the PC. However, only the DLPFC had significantly lower Cr and higher mI. Abnormal metabolite pattern from the MC supports the hypothesis that FTLD and MND may be closely linked.

Elliptical magnetic resonance spectroscopic imaging with GRAPPA for imaging brain tumors at 3 T

Magnetic Resonance Spectroscopic Imaging (MRSI) is a technique for imaging spatial variation of metabolites and has been very useful in characterizing biochemical changes associated with disease as well as response to therapy in malignant pathologies. This work presents a self-calibrated undersampling to accelerate 3D elliptical MRSI and an extrapolation-reconstruction algorithm based on the GRAPPA method. The accelerated MRSI technique was tested in three volunteers and five brain tumor patients. Acceleration allowed larger spatial coverage and consequently, less lipid contamination in spectra, compared to fully sampled acquisition within the same scantime. Metabolite concentrations measured from the accelerated acquisitions were in good agreement with measurements obtained from fully sampled MRSI scans.

Design of cosine modulated very selective suppression pulses for MR spectroscopic imaging at 3T

The advantages of using a 3 Tesla (T) scanner for MR spectroscopic imaging (MRSI) of brain tissue include improved spectral resolution and increased sensitivity. Very selective saturation (VSS) pulses are important for maximizing selectivity for PRESS MRSI and minimizing chemical shift misregistration by saturating signals from outside the selected region. Although three-dimensional (3D) PRESS MRSI is able to provide excellent quality metabolic data for patients with brain tumors and has been shown to be important for defining tumor burden, the method is currently limited by how much of the anatomic lesion can be covered within a single examination. In this study we designed and implemented cosine modulated VSS pulses that were optimized for 3T MRSI acquisitions. This provided improved coverage and suppression of unwanted lipid signals with a smaller number of pulses. The use of the improved pulse sequence was validated in volunteer studies, and in clinical 3D MRSI exams of brain tumors.

Molecular imaging without radiopharmaceuticals?

The limitations on the sensitivity for detecting small changes in MRI, CT, and ultrasound pulse-echo images are used to estimate the practical requirements for molecular imaging and targeted contrast enhancement for these modalities. These types of imaging are highly unlikely to approach the sensitivity for detecting molecular processes of radionuclear methods, and the prospects for achieving sufficient concentrations of appropriate agents in vivo are poor for several types of applications such as small-molecule targeting of specific receptors. However, using relatively large carrier systems such as particles and liposomes, sufficient concentrations of paramagnetic agents may be delivered to achieve MR-signal changes adequate for detection. The use of higher-resolution MR images will aid the prospects for molecular imaging in small animals. Theoretic considerations also predict that a similar approach, using rather large particles or carriers of materials with a high atomic number, may also be successful for CT, especially with additional developments such as the use of monochromatic x-rays. The prospects of molecular imaging by x-ray imaging may not be as bleak as has been predicted. For ultrasound detection, gas-filled bubbles can provide a sufficient backscattered sound intensity to be detectable at concentrations and sizes not much different from agents designed for these other modalities.

Relative cerebral blood volume values to differentiate high-grade glioma recurrence from posttreatment radiation effect: direct correlation between image-guided tissue histopathology and localized dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging measurements

BACKGROUND AND PURPOSE

Differentiating tumor growth from posttreatment radiation effect (PTRE) remains a common problem in neuro-oncology practice. To our knowledge, useful threshold relative cerebral blood volume (rCBV) values that accurately distinguish the 2 entities do not exist. Our prospective study uses image-guided neuronavigation during surgical resection of MR imaging lesions to correlate directly specimen histopathology with localized dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging (DSC) measurements and to establish accurate rCBV threshold values, which differentiate PTRE from tumor recurrence.

MATERIALS AND METHODS

Preoperative 3T gradient-echo DSC and contrast-enhanced stereotactic T1-weighted images were obtained in patients with high-grade glioma (HGG) previously treated with multimodality therapy. Intraoperative neuronavigation documented the stereotactic location of multiple tissue specimens taken randomly from the periphery of enhancing MR imaging lesions. Coregistration of DSC and stereotactic images enabled calculation of localized rCBV within the previously recorded specimen locations. All tissue specimens were histopathologically categorized as tumor or PTRE and were correlated with corresponding rCBV values. All rCBV values were T1-weighted leakage-corrected with preload contrast-bolus administration and T2/T2*-weighted leakage-corrected with baseline subtraction integration.

RESULTS

Forty tissue specimens were collected from 13 subjects. The PTRE group (n = 16) rCBV values ranged from 0.21 to 0.71, tumor (n = 24) values ranged from 0.55 to 4.64, and 8.3% of tumor rCBV values fell within the PTRE group range. A threshold value of 0.71 optimized differentiation of the histopathologic groups with a sensitivity of 91.7% and a specificity of 100%.

CONCLUSIONS

rCBV measurements obtained by using DSC and the protocol we have described can differentiate HGG recurrence from PTRE with a high degree of accuracy.