Ensuring Safe Exploration: Ares Launch Vehicle Integrated Vehicle Ground Vibration Testing

Ground vibration testing has been an integral tool for developing new launch vehicles throughout the space age. Several launch vehicles have been lost due to problems that would have been detected by early vibration testing, including Ariane 5, Delta III, and Falcon 1. NASA will leverage experience and testing hardware developed during the Saturn and Shuttle programs to perform ground vibration testing (GVT) on the Ares I crew launch vehicle and Ares V cargo launch vehicle stacks. NASA performed dynamic vehicle testing (DVT) for Saturn and mated vehicle ground vibration testing (MVGVT) for Shuttle at the Dynamic Test Stand (Test Stand 4550) at Marshall Space Flight Center (MSFC) in Huntsville, Alabama, and is now modifying that facility to support Ares I integrated vehicle ground vibration testing (IVGVT) beginning in 2012. The Ares IVGVT schedule shows most of its work being completed between 2010 and 2014. Integrated 2nd Stage Ares IVGVT will begin in 2012 and IVGVT of the entire Ares launch stack will begin in 2013. The IVGVT data is needed for the human-rated Orion launch vehicle's Design Certification Review (DCR) in early 2015. During the Apollo program, GVT detected several serious design concerns, which NASA was able to address before Saturn V flew, eliminating costly failures and potential losses of mission or crew. During the late 1970s, Test Stand 4550 was modified to support the four-body structure of the Space Shuttle. Vibration testing confirmed that the vehicle's mode shapes and frequencies were better than analytical models suggested, however, the testing also identified challenges with the rate gyro assemblies, which could have created flight instability and possibly resulted in loss of the vehicle. Today, NASA has begun modifying Test Stand 4550 to accommodate Ares I, including removing platforms needed for Shuttle testing and upgrading the dynamic test facilities to characterize the mode shapes and resonant frequencies of the vehicle. The IVGVT team expects to collect important information about the new launch vehicles, greatly increasing astronaut safety as NASA prepares to explore the Moon and beyond

Diffusion MRI in early cancer therapeutic response assessment

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136261/1/nbm3458_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136261/2/nbm3458.pd

Development of a multiparametric voxel-based magnetic resonance imaging biomarker for early cancer therapeutic response assessment

Quantitative magnetic resonance imaging (MRI)-based biomarkers, which capture physiological and functional tumor processes, were evaluated as imaging surrogates of early tumor response following chemoradiotherapy in glioma patients. A multiparametric extension of a voxel-based analysis, referred as the parametric response map (PRM), was applied to quantitative MRI maps to test the predictive potential of this metric for detecting response. Fifty-six subjects with newly diagnosed high-grade gliomas treated with radiation and concurrent temozolomide were enrolled in a single-site prospective institutional review board-approved MRI study. Apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps were acquired before therapy and 3 weeks after therapy was initiated. Multiparametric PRM (mPRM) was applied to both physiological MRI maps and evaluated as an imaging biomarker of patient survival. For comparison, single-biomarker PRMs were also evaluated in this study. The simultaneous analysis of ADC and rCBV by the mPRM approach was found to improve the predictive potential for patient survival over single PRM measures. With an array of quantitative imaging parameters being evaluated as biomarkers of therapeutic response, mPRM shows promise as a new methodology for consolidating physiologically distinct imaging parameters into a single interpretable and quantitative metric

Comparison of voxel-wise and histogram analyses of glioma ADC maps for prediction of early therapeutic change

Noninvasive imaging methods are sought to objectively predict early response to therapy for high-grade glioma tumors. Quantitative metrics derived from diffusion-weighted imaging, such as apparent diffusion coefficient (ADC), have previously shown promise when used in combination with voxel-based analysis reflecting regional changes. The functional diffusion mapping (fDM) metric is hypothesized to be associated with volume of tumor exhibiting an increasing ADC owing to effective therapeutic action. In this work, the reference fDM-predicted survival (from previous study) for 3 weeks from treatment initiation (midtreatment) is compared to multiple histogram-based metrics using Kaplan-Meier estimator for 80 glioma patients stratified to responders and nonresponders based on the population median value for the given metric. The ADC histogram metric reflecting reduction in midtreatment volume of solid tumor (ADC 8% population-median with respect to pretreatment is found to have the same predictive power as the reference fDM of increasing midtreatment ADC volume above 4%. This study establishes the level of correlation between fDM increase and low-ADC tumor volume shrinkage for prediction of early response to radiation therapy in patients with glioma malignancies

Diffusion imaging for evaluation of tumor therapies in preclinical animal models

The increasing development of novel targeted therapies for treating solid tumors has necessitated the development of technology to determine their efficacy in preclinical animal models. One such technology that can non-invasively quantify early changes in tumor cellularity as a result of an efficacious therapy is diffusion MRI. In this overview we present some theories as to the origin of diffusion changes as a result of tumor therapy, a robust methodology for acquisition of apparent diffusion coefficient maps and some applications of determining therapeutic efficacy in a variety therapeutic regimens and animal models.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47951/1/10334_2004_Article_79.pd

Intravoxel water diffusion heterogeneity imaging of human high-grade gliomas

This study aimed to determine the potential value of intravoxel water diffusion heterogeneity imaging for brain tumor characterization and evaluation of high-grade gliomas, by comparing an established heterogeneity index ( Α value) measured in human high-grade gliomas to those of normal appearing white and grey matter landmarks. Twenty patients with high-grade gliomas prospectively underwent diffusion-weighted magnetic resonance imaging using multiple b-values. The stretched-exponential model was used to generate Α and distributed diffusion coefficient (DDC) maps. The Α values and DDCs of the tumor and contralateral anatomic landmarks were measured in each patient. Differences between Α values of tumors and landmark tissues were assessed using paired t- tests. Correlation between tumor Α and tumor DDC was assessed using Pearson's correlation coefficient. Mean Α of tumors was significantly lower than that of contralateral frontal white matter ( p  = 0.0249), basal ganglia ( p  < 0.0001), cortical grey matter ( p  < 0.0001), and centrum semiovale ( p  = 0.0497). Correlation between tumor Α and tumor DDC was strongly negative (Pearson correlation coefficient, −0.8493; p  < 0.0001). The heterogeneity index Α of human high-grade gliomas is significantly different from those of normal brain structures, which potentially offers a new method for evaluating brain tumors. The observed negative correlation between tumor Α and tumor DDC requires further investigation. Copyright © 2009 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65045/1/1441_ftp.pd

Image Registration for Quantitative Parametric Response Mapping of Cancer Treatment Response

AbstractImaging biomarkers capable of early quantification of tumor response to therapy would provide an opportunity to individualize patient care. Image registration of longitudinal scans provides a method of detecting treatment-associated changes within heterogeneous tumors by monitoring alterations in the quantitative value of individual voxels over time, which is unattainable by traditional volumetric-based histogram methods. The concepts involved in the use of image registration for tracking and quantifying breast cancer treatment response using parametric response mapping (PRM), a voxel-based analysis of diffusion-weighted magnetic resonance imaging (DW-MRI) scans, are presented. Application of PRM to breast tumor response detection is described, wherein robust registration solutions for tracking small changes in water diffusivity in breast tumors during therapy are required. Methodologies that employ simulations are presented for measuring expected statistical accuracy of PRM for response assessment. Test-retest clinical scans are used to yield estimates of system noise to indicate significant changes in voxel-based changes in water diffusivity. Overall, registration-based PRM image analysis provides significant opportunities for voxel-based image analysis to provide the required accuracy for early assessment of response to treatment in breast cancer patients receiving neoadjuvant chemotherapy

DW-MRI as a Biomarker to Compare Therapeutic Outcomes in Radiotherapy Regimens Incorporating Temozolomide or Gemcitabine in Glioblastoma

The effectiveness of the radiosensitizer gemcitabine (GEM) was evaluated in a mouse glioma along with the imaging biomarker diffusion-weighted magnetic resonance imaging (DW-MRI) for early detection of treatment effects. A genetically engineered murine GBM model [Ink4a-Arf−/− PtenloxP/loxP/Ntv-a RCAS/PDGF(+)/Cre(+)] was treated with gemcitabine (GEM), temozolomide (TMZ) +/− ionizing radiation (IR). Therapeutic efficacy was quantified by contrast-enhanced MRI and DW-MRI for growth rate and tumor cellularity, respectively. Mice treated with GEM, TMZ and radiation showed a significant reduction in growth rates as early as three days post-treatment initiation. Both combination treatments (GEM/IR and TMZ/IR) resulted in improved survival over single therapies. Tumor diffusion values increased prior to detectable changes in tumor volume growth rates following administration of therapies. Concomitant GEM/IR and TMZ/IR was active and well tolerated in this GBM model and similarly prolonged median survival of tumor bearing mice. DW-MRI provided early changes to radiosensitization treatment warranting evaluation of this imaging biomarker in clinical trials

In-Vivo Visualization of Tumor Microvessel Density and Response to Anti-Angiogenic Treatment by High Resolution MRI in Mice

Purpose: Inhibition of angiogenesis has shown clinical success in patients with cancer. Thus, imaging approaches that allow for the identification of angiogenic tumors and the detection of response to anti-angiogenic treatment are of high clinical relevance. Experimental Design: We established an in vivo magnetic resonance imaging (MRI) approach that allows us to simultaneously image tumor microvessel density and tumor vessel size in a NSCLC model in mice. Results: Using microvessel density imaging we demonstrated an increase in microvessel density within 8 days after tumor implantation, while tumor vessel size decreased indicating a switch from macro- to microvessels during tumor growth. Moreover, we could monitor in vivo inhibition of angiogenesis induced by the angiogenesis inhibitor PTK787, resulting in a decrease of microvessel density and a slight increase in tumor vessel size. Conclusions: We present an in vivo imaging approach that allows us to monitor both tumor microvessel density and tumor vessel size in the tumor. Moreover, this approach enables us to assess, early-on, treatment effects on tumor microvessel density as well as on tumor vessel size. Thus, this imaging-based strategy of validating anti-angiogenic treatment effects ha

Animal Models and Their Role in Imaging-Assisted Co-Clinical Trials

The availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunities to conduct co-clinical trials, which are studies on patients that are carried out parallel to or sequentially with animal models of cancer that mirror the biology of the patients\u27 tumors. Patient-derived xenografts (PDX) and genetically engineered mouse models (GEMM) are considered to be the models that best represent human disease and have high translational value. Notably, one element of co-clinical trials that still needs significant optimization is quantitative imaging. The National Cancer Institute has organized a Co-Clinical Imaging Resource Program (CIRP) network to establish best practices for co-clinical imaging and to optimize translational quantitative imaging methodologies. This overview describes the ten co-clinical trials of investigators from eleven institutions who are currently supported by the CIRP initiative and are members of the Animal Models and Co-clinical Trials (AMCT) Working Group. Each team describes their corresponding clinical trial, type of cancer targeted, rationale for choice of animal models, therapy, and imaging modalities. The strengths and weaknesses of the co-clinical trial design and the challenges encountered are considered. The rich research resources generated by the members of the AMCT Working Group will benefit the broad research community and improve the quality and translational impact of imaging in co-clinical trials