Publications by authors named "Manushka Vaidya"

Purpose: Metabolite-specific balanced SSFP (MS-bSSFP) sequences are increasingly used in hyperpolarized [1-C]Pyruvate (HP C) MRI studies as they improve SNR by refocusing the magnetization each TR. Currently, pharmacokinetic models used to fit conversion rate constants, k and k, and rate constant maps do not account for differences in the signal evolution of MS-bSSFP acquisitions.

Methods: In this work, a flexible MS-bSSFP model was built that can be used to fit conversion rate constants for these experiments.

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Purpose: We constructed a C/P surface coil at 3 T for studying cancer metabolism and bioenergetics. In a single scan session, hyperpolarized C-pyruvate MRS and P MRS was carried out for a healthy rat brain.

Methods: All experiments were carried out at 3 Tesla.

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Purpose: The goal of this study was to combine a specialized acquisition method with a new quantification pipeline to accurately and efficiently probe the metabolism of hyperpolarized C-labeled compounds in vivo. In this study, we tested our approach on [2- C]pyruvate and [1- C]α-ketoglutarate data in rat orthotopic brain tumor models at 3T.

Methods: We used a multiband metabolite-specific radiofrequency (RF) excitation in combination with a variable flip angle scheme to minimize substrate polarization loss and measure fast metabolic processes.

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In many tumors, cancer cells take up large quantities of glucose and metabolize it into lactate, even in the presence of sufficient oxygen to support oxidative metabolism. It has been hypothesized that this malignant metabolic phenotype supports cancer growth and metastasis, and that reversal of this so-called "Warburg effect" may selectively harm cancer cells. Conversion of glucose to lactate can be reduced by ablation or inhibition of lactate dehydrogenase (LDH), the enzyme responsible for conversion of pyruvate to lactate at the endpoint of glycolysis.

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Purpose: To investigate how high-permittivity materials (HPMs) can improve SNR when placed between MR detectors and the imaged body.

Methods: We used a simulation framework based on dyadic Green's functions to calculate the electromagnetic field inside a uniform dielectric sphere at 7 Tesla, with and without a surrounding layer of HPM. SNR-optimizing (ideal) current patterns were expressed as the sum of signal-optimizing (signal-only) current patterns and dark mode current patterns that minimize sample noise while contributing nothing to signal.

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Background: There is growing interest in detecting cerebro-cerebellar circuits, which requires adequate blood oxygenation level dependent contrast and signal-to-noise ratio (SNR) throughout the brain. Although 7T scanners offer increased SNR, coverage of commercial head coils is currently limited to the cerebrum.

Purpose: To improve cerebellar functional MRI (fMRI) at 7T with high permittivity material (HPM) pads extending the sensitivity of a commercial coil.

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Purpose: The aim of this study was to evaluate the effect of integrated high-permittivity materials (HPMs) on excitation homogeneity and global specific absorption rate (SAR) for transmit arrays at 7T.

Methods: A rapid electrodynamic simulation framework was used to calculate L-curves associated with excitation of a uniform 2D profile in a dielectric sphere. We used ultimate intrinsic SAR as an absolute performance reference to compare different transmit arrays in the presence and absence of a layer of HPM.

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Objective: To use high-permittivity materials (HPM) positioned near radiofrequency (RF) surface coils to manipulate transmit/receive field patterns.

Materials And Methods: A large HPM pad was placed below the RF coil to extend the field of view (FOV). The resulting signal-to-noise ratio (SNR) was compared with that of other coil configurations covering the same FOV in simulations and experiments at 7 T.

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In high field MRI, the spatial distribution of the radiofrequency magnetic ( ) field is usually affected by the presence of the sample. For hardware design and to aid interpretation of experimental results, it is important both to anticipate and to accurately simulate the behavior of these fields. Fields generated by a radiofrequency surface coil were simulated using dyadic Green's functions, or experimentally measured over a range of frequencies inside an object whose electrical properties were varied to illustrate a variety of transmit [Formula: see text] and receive [Formula: see text] field patterns.

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We investigated to what degree and at what rate the ultimate intrinsic (UI) signal-to-noise ratio (SNR) may be approached using finite radiofrequency detector arrays. We used full-wave electromagnetic field simulations based on dyadic Green's functions to compare the SNR of arrays of loops surrounding a uniform sphere with the ultimate intrinsic SNR (UISNR), for increasing numbers of elements over a range of magnetic field strengths, voxel positions, sphere sizes, and acceleration factors. We evaluated the effect of coil conductor losses and the performance of a variety of distinct geometrical arrangements such as "helmet" and "open-pole" configurations in multiple imaging planes.

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Purpose: We investigated global specific absorption rate (SAR) and radiofrequency (RF) power requirements in parallel transmission as the distance between the transmit coils and the sample was increased.

Methods: We calculated ultimate intrinsic SAR (UISAR), which depends on object geometry and electrical properties but not on coil design, and we used it as the reference to compare the performance of various transmit arrays. We investigated the case of fixing coil size and increasing the number of coils while moving the array away from the sample, as well as the case of fixing coil number and scaling coil dimensions.

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Background And Purpose: Prediction of local failure in radiotherapy patients with non-small cell lung cancer (NSCLC) remains a challenging task. Recent evidence suggests that FDG-PET images can be used to predict outcomes. We investigate an alternative multimodality image-feature approach for predicting post-radiotherapy tumor progression in NSCLC.

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Locally advanced non-small cell lung cancer (NSCLC) patients suffer from a high local failure rate following radiotherapy. Despite many efforts to develop new dose-volume models for early detection of tumor local failure, there was no reported significant improvement in their application prospectively. Based on recent studies of biomarker proteins' role in hypoxia and inflammation in predicting tumor response to radiotherapy, we hypothesize that combining physical and biological factors with a suitable framework could improve the overall prediction.

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