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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

A computer aided thermodynamic approach for predicting the formation of Z-DNA in naturally occurring sequences

The ease with which a particular DNA segment adopts the left-handed Z-conformation depends largely on the sequence and on the degree of negative supercoiling to which it is subjected. We describe a computer program (Z-hunt) that is designed to search long sequences of naturally occurring DNA and retrieve those nucleotide combinations of up to 24 bp in length which show a strong propensity for Z-DNA formation. Incorporated into Z-hunt is a statistical mechanical model based on empirically determined energetic parameters for the B to Z transition accumulated to date. The Z-forming potential of a sequence is assessed by ranking its behavior as a function of negative superhelicity relative to the behavior of similar sized randomly generated nucleotide sequences assembled from over 80,000 combinations. The program makes it possible to compare directly the Z-forming potential of sequences with different base compositions and different sequence lengths. Using Z-hunt, we have analyzed the DNA sequences of the bacteriophage phi X174, plasmid pBR322, the animal virus SV40 and the replicative form of the eukaryotic adenovirus-2. The results are compared with those previously obtained by others from experiments designed to locate Z-DNA forming regions in these sequences using probes which show specificity for the left-handed DNA conformation.

Non-NASA Center↗
DOE OSTI2015

Primer and platform effects on 16S rRNA tag sequencing

Sequencing of 16S rRNA gene tags is a popular method for profiling and comparing microbial communities. The protocols and methods used, however, vary considerably with regard to amplification primers, sequencing primers, sequencing technologies; as well as quality filtering and clustering. How results are affected by these choices, and whether data produced with different protocols can be meaningfully compared, is often unknown. Here we compare results obtained using three different amplification primer sets (targeting V4, V6–V8, and V7–V8) and two sequencing technologies (454 pyrosequencing and Illumina MiSeq) using DNA from a mock community containing a known number of species as well as complex environmental samples whose PCR-independent profiles were estimated using shotgun sequencing. We find that paired-end MiSeq reads produce higher quality data and enabled the use of more aggressive quality control parameters over 454, resulting in a higher retention rate of high quality reads for downstream data analysis. While primer choice considerably influences quantitative abundance estimations, sequencing platform has relatively minor effects when matched primers are used. In conclusion, beta diversity metrics are surprisingly robust to both primer and sequencing platform biases.

16S rRNA gene sequencing↗
DOE OSTI2018

In vivo gene correction with targeted sequence substitution through microhomology-mediated end joining

Highlights: • A novel microhomology mediated end joining (MMEJ) gene correction method was tested. • MMEJ resulted in precise targeted sequence substitution (TSS) in vitro and in vivo. • MMEJ-TSS showed superior efficiency than homology-directed repair (HDR) in vitro. • MMEJ-TSS resulted in the survival of mice model of hereditary tyrosinemia in vivo. • MMEJ-TSS could overcome the limitations of HDR for gene therapy. Genome editing technology using programmable nucleases has rapidly evolved in recent years. The primary mechanism to achieve precise integration of a transgene is mainly based on homology-directed repair (HDR). However, an HDR-based genome-editing approach is less efficient than non-homologous end-joining (NHEJ). Recently, a microhomology-mediated end-joining (MMEJ)-based transgene integration approach was developed, showing feasibility both in vitro and in vivo. We expanded this method to achieve targeted sequence substitution (TSS) of mutated sequences with normal sequences using double-guide RNAs (gRNAs), and a donor template flanking the microhomologies and target sequence of the gRNAs in vitro and in vivo. Our method could realize more efficient sequence substitution than the HDR-based method in vitro using a reporter cell line, and led to the survival of a hereditary tyrosinemia mouse model in vivo. The proposed MMEJ-based TSS approach could provide a novel therapeutic strategy, in addition to HDR, to achieve gene correction from a mutated sequence to a normal sequence.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Bottom-Up Simulation, Reconstruction, and Quantification of Macromolecule Sequences from Experimental Polymerizations

Motivated by the canonical sequence–structure–function paradigm, tools to characterize chemical patterning in natural biomacromolecules, from proteins to nucleic acids, have grown exponentially in recent years. However, analogous strategies for synthetic macromolecules remain in nascent stages, complicated by sequence polydispersity and analytical limitations. To address this, we have developed a comprehensive and open-source Python package, PRISM (polymer rate insights and sequence modeling), an end-to-end workflow that provides a path from experimental kinetics measurements to quantitative and qualitative metrics for describing chemical patterning in stochastic polymers. First, a numerical integration strategy was constructed to simulate and fit experimental data from reversible addition–fragmentation chain transfer (RAFT) polymerization kinetics, enabling the facile estimation of relevant reactivity ratios. These ratios were then used in a mechanism-specific stochastic kinetic simulation strategy to simulate sequence ensembles corresponding to model systems spanning experimental copolymers, classes of statistical polymers (e.g., alternating, block, and gradient), and multiblock copolymers. Lastly, inspired by sequence homology metrics from bioinformatics, we introduce visualization strategies and quantitative metrics to facilitate comparisons of different sequence ensembles. As the sequence–structure–function paradigm becomes increasingly central in de novo design of synthetic macromolecules, this toolkit provides a first step toward accurate and representative sequence description and featurization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Sequence-defined structural transitions by calcium-responsive proteins

Biopolymer sequences dictate their functions, and protein-based polymers are a promising platform to establish sequence–function relationships for novel biopolymers. To efficiently explore vast sequence spaces of natural proteins, sequence repetition is a common strategy to tune and amplify specific functions. This strategy is applied to repeats-in-toxin (RTX) proteins with calcium-responsive folding behavior, which stems from tandem repeats of the nonapeptide GGXGXDXUX in which X can be any amino acid and U is a hydrophobic amino acid. To determine the functional range of this nonapeptide, we modified a naturally occurring RTX protein that forms β-roll structures in the presence of calcium. Sequence modifications focused on calcium-binding turns within the repetitive region, including either global substitution of nonconserved residues or complete replacement with tandem repeats of a consensus nonapeptide GGAGXDTLY. Some sequence modifications disrupted the typical transition from intrinsically disordered random coils to folded β rolls, despite conservation of the underlying nonapeptide sequence. Proteins enriched with smaller, hydrophobic amino acids adopted secondary structures in the absence of calcium and underwent structural rearrangements in calcium-rich environments. In contrast, proteins with bulkier, hydrophilic amino acids maintained intrinsic disorder in the absence of calcium. In conclusion, these results indicate a significant role of nonconserved amino acids in calcium-responsive folding, thereby revealing a strategy to leverage sequences in the design of tunable, calcium-responsive biopolymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

A theoretical method to compute sequence dependent configurational properties in charged polymers and proteins

A general formalism to compute configurational properties of proteins and other heteropolymers with an arbitrary sequence of charges and non-uniform excluded volume interaction is presented. A variational approach is utilized to predict average distance between any two monomers in the chain. The presented analytical model, for the first time, explicitly incorporates the role of sequence charge distribution to determine relative sizes between two sequences that vary not only in total charge composition but also in charge decoration (even when charge composition is fixed). Furthermore, the formalism is general enough to allow variation in excluded volume interactions between two monomers. Model predictions are benchmarked against the all-atom Monte Carlo studies of Das and Pappu [Proc. Natl. Acad. Sci. U. S. A. 110, 13392 (2013)] for 30 different synthetic sequences of polyampholytes. These sequences possess an equal number of glutamic acid (E) and lysine (K) residues but differ in the patterning within the sequence. Without any fit parameter, the model captures the strong sequence dependence of the simulated values of the radius of gyration with a correlation coefficient of R{sup 2} = 0.9. The model is then applied to real proteins to compare the unfolded state dimensions of 540 orthologous pairs of thermophilic and mesophilic proteins. The excluded volume parameters are assumed similar under denatured conditions, and only electrostatic effects encoded in the sequence are accounted for. With these assumptions, thermophilic proteins are found—with high statistical significance—to have more compact disordered ensemble compared to their mesophilic counterparts. The method presented here, due to its analytical nature, is capable of making such high throughput analysis of multiple proteins and will have broad applications in proteomic studies as well as in other heteropolymeric systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Optimization of micropillar sequences for fluid flow sculpting

Inertial fluid flow deformation around pillars in a microchannel is a new method for controlling fluid flow. Sequences of pillars have been shown to produce a rich phase space with a wide variety of flow transformations. Previous work has successfully demonstrated manual design of pillar sequences to achieve desired transformations of the flow cross section, with experimental validation. However, such a method is not ideal for seeking out complex sculpted shapes as the search space quickly becomes too large for efficient manual discovery. We explore fast, automated optimization methods to solve this problem. We formulate the inertial flow physics in microchannels with different micropillar configurations as a set of state transition matrix operations. These state transition matrices are constructed from experimentally validated streamtraces for a fixed channel length per pillar. This facilitates modeling the effect of a sequence of micropillars as nested matrix-matrix products, which have very efficient numerical implementations. With this new forward model, arbitrary micropillar sequences can be rapidly simulated with various inlet configurations, allowing optimization routines quick access to a large search space. We integrate this framework with the genetic algorithm and showcase its applicability by designing micropillar sequences for various useful transformations. We computationally discover micropillar sequences for complex transformations that are substantially shorter than manually designed sequences. We also determine sequences for novel transformations that were difficult to manually design. Finally, we experimentally validate these computational designs by fabricating devices and comparing predictions with the results from confocal microscopy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

From sequence to protein structure and conformational dynamics with artificial intelligence/machine learning

The 2024 Nobel Prize in Chemistry was awarded in part for de novo protein structure prediction using AlphaFold2, an artificial intelligence/machine learning (AI/ML) model trained on vast amounts of sequence and three-dimensional structure data. AlphaFold2 and related models, including RoseTTAFold and ESMFold, employ specialized neural network architectures driven by attention mechanisms to infer relationships between sequence and structure. At a fundamental level, these AI/ML models operate on the long-standing hypothesis that the structure of a protein is determined by its amino acid sequence. More recently, AlphaFold2 has been adapted for the prediction of multiple protein conformations by subsampling multiple sequence alignments. Herein, we provide an overview of the deterministic relationship between sequence and structure, which was hypothesized over half a century ago with profound implications for the biological sciences ever since. We postulate that protein conformational dynamics are also determined, at least in part, by amino acid sequence and that this relationship may be leveraged for construction of AI/ML models dedicated to predicting protein conformational ensembles. Accordingly, we describe a conceptual model architecture, which may be trained on sequence data in combination with conformationally sensitive structural information, coming primarily from nuclear magnetic resonance (NMR) spectroscopy. Notwithstanding certain limitations in this context, NMR offers abundant structural heterogeneity conducive to conformational ensemble prediction. As NMR and other data continue to accumulate, sequence-informed prediction of protein structural dynamics with AI/ML has the potential to emerge as a transformative capability across the biological sciences.

Artificial intelligence↗
DOE OSTI2012

A TALE OF DWARFS AND GIANTS: USING A z = 1.62 CLUSTER TO UNDERSTAND HOW THE RED SEQUENCE GREW OVER THE LAST 9.5 BILLION YEARS

We study the red sequence in a cluster of galaxies at z = 1.62 and follow its evolution over the intervening 9.5 Gyr to the present day. Using deep YJK{sub s} imaging with the HAWK-I instrument on the Very Large Telescope, we identify a tight red sequence and construct its rest-frame i-band luminosity function (LF). There is a marked deficit of faint red galaxies in the cluster that causes a turnover in the LF. We compare the red-sequence LF to that for clusters at z < 0.8, correcting the luminosities for passive evolution. The shape of the cluster red-sequence LF does not evolve between z = 1.62 and z = 0.6 but at z < 0.6 the faint population builds up significantly. Meanwhile, between z = 1.62 and 0.6 the inferred total light on the red sequence grows by a factor of {approx}2 and the bright end of the LF becomes more populated. We construct a simple model for red-sequence evolution that grows the red sequence in total luminosity and matches the constant LF shape at z > 0.6. In this model the cluster accretes blue galaxies from the field whose star formation is quenched and who are subsequently allowed to merge. We find that three to four mergers among cluster galaxies during the 4 Gyr between z = 1.62 and z = 0.6 match the observed LF evolution between the two redshifts. The inferred merger rate is consistent with other studies of this cluster. Our result supports the picture that galaxy merging during the major growth phase of massive clusters is an important process in shaping the red-sequence population at all luminosities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

A REVISED PARALLEL-SEQUENCE MORPHOLOGICAL CLASSIFICATION OF GALAXIES: STRUCTURE AND FORMATION OF S0 AND SPHEROIDAL GALAXIES

We update van den Bergh's parallel-sequence galaxy classification in which S0 galaxies form a sequence S0a-S0b-S0c that parallels the sequence Sa-Sb-Sc of spiral galaxies. The ratio B/T of bulge-to-total light defines the position of a galaxy in this tuning-fork diagram. Our classification makes one major improvement. We extend the S0a-S0b-S0c sequence to spheroidal ('Sph') galaxies that are positioned in parallel to irregular galaxies in a similarly extended Sa-Sb-Sc-Im sequence. This provides a natural 'home' for spheroidals, which previously were omitted from galaxy classification schemes or inappropriately combined with ellipticals. To motivate our juxtaposition of Sph and Im galaxies, we present photometry and bulge-disk decompositions of four rare, late-type S0s that bridge the gap between the more common S0b and Sph galaxies. NGC 4762 is an edge-on SB0bc galaxy with a very small classical-bulge-to-total ratio of B/T = 0.13 {+-} 0.02. NGC 4452 is an edge-on SB0 galaxy with an even tinier pseudobulge-to-total ratio of PB/T = 0.017 {+-} 0.004. It is therefore an SB0c. VCC 2048, whose published classification is S0, contains an edge-on disk, but its 'bulge' plots in the structural parameter sequence of spheroidals. It is therefore a disky Sph. And NGC 4638 is similarly a 'missing link' between S0s and Sphs-it has a tiny bulge and an edge-on disk embedded in an Sph halo. In the Appendix, we present photometry and bulge-disk decompositions of all Hubble Space Telescope Advanced Camera for Surveys Virgo Cluster Survey S0s that do not have published decompositions. We use these data to update the structural parameter correlations of Sph, S+Im, and E galaxies. We show that Sph galaxies of increasing luminosity form a continuous sequence with the disks (but not bulges) of S0c-S0b-S0a galaxies. Remarkably, the Sph-S0-disk sequence is almost identical to that of Im galaxies and spiral galaxy disks. We review published observations for galaxy transformation processes, particularly ram-pressure stripping of cold gas. We suggest that Sph galaxies are transformed, 'red and dead' Scd-Im galaxies in the same way that many S0 galaxies are transformed, red and dead Sa-Sc spiral galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Combining protein sequences and structures with transformers and equivariant graph neural networks to predict protein function

Abstract Motivation Millions of protein sequences have been generated by numerous genome and transcriptome sequencing projects. However, experimentally determining the function of the proteins is still a time consuming, low-throughput, and expensive process, leading to a large protein sequence-function gap. Therefore, it is important to develop computational methods to accurately predict protein function to fill the gap. Even though many methods have been developed to use protein sequences as input to predict function, much fewer methods leverage protein structures in protein function prediction because there was lack of accurate protein structures for most proteins until recently. Results We developed TransFun—a method using a transformer-based protein language model and 3D-equivariant graph neural networks to distill information from both protein sequences and structures to predict protein function. It extracts feature embeddings from protein sequences using a pre-trained protein language model (ESM) via transfer learning and combines them with 3D structures of proteins predicted by AlphaFold2 through equivariant graph neural networks. Benchmarked on the CAFA3 test dataset and a new test dataset, TransFun outperforms several state-of-the-art methods, indicating that the language model and 3D-equivariant graph neural networks are effective methods to leverage protein sequences and structures to improve protein function prediction. Combining TransFun predictions and sequence similarity-based predictions can further increase prediction accuracy. Availability and implementation The source code of TransFun is available at https://github.com/jianlin-cheng/TransFun.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Evaluation of earthquake stress parameters and its scaling during the 2016-2017 Amatrice-Norcia-Visso sequence -- Part I

The Amatrice–Norcia–Visso sequence is distinguished by complex behaviour that is somewhat atypical of main-shock–aftershock sequences, as there were multiple large main shocks that continued for months. Here, we focus on the Amatrice sequence (main shock 2016 August 24, M w = 5.97) to evaluate the apparent stress values and magnitude-dependent scaling in order to improve our knowledge of processes that control small and large earthquakes within this active region of Italy. Apparent stress is proportional to the ratio of radiated seismic energy and seismic moment, and as such, these stress parameters play an important role in hazard prediction as they have a strong effect on the observed and predicted ground shaking. We analyse 83 events of the sequence from 2016 August 24 to October 16, within a radius of 20 km from the main shock and with an M w ranging between 5.97 and 2.72. Taking advantage of the averaging nature of coda waves, we analyse coda-envelope-based spectral ratios between neighbouring event pairs. We use equations proposed by Walter et al. to consider stable, low-frequency and high-frequency spectral ratio levels which provide measures of the corner frequency and apparent stress ratios of the events within the sequence. The results demonstrate non-self-similar behaviour within the sequence, indicating a change in dynamics between the largest events and the smaller aftershocks. The apparent stress and corner frequency estimates are compared to those obtained by Malagnini and Munafò who utilized hundreds of direct S-wave spectral ratio measurements to obtain their results. Although our analysis is based only on 83 events, our results are in very good agreement, demonstrating once more that the use of coda waves is very stable and provides lower variance measures than those using direct waves. A comparison with recent Central Apennines source scaling models derived from various seismic sequences (1997–1998 Colfiorito, 2002 San Giuliano di Puglia, 2009 L'Aquila) shows that the Amatrice sequence source scaling in this study is well represented by the models proposed by Pacor et al. and Malagnini and Mayeda.

58 GEOSCIENCES↗
DOE OSTI2021

A minimal motif for sequence recognition by mitochondrial transcription factor A (TFAM)

Abstract Mitochondrial transcription factor A (TFAM) plays a critical role in mitochondrial transcription initiation and mitochondrial DNA (mtDNA) packaging. Both functions require DNA binding, but in one case TFAM must recognize a specific promoter sequence, while packaging requires coating of mtDNA by association with non sequence-specific regions. The mechanisms by which TFAM achieves both sequence-specific and non sequence-specific recognition have not yet been determined. Existing crystal structures of TFAM bound to DNA allowed us to identify two guanine-specific interactions that are established between TFAM and the bound DNA. These interactions are observed when TFAM is bound to both specific promoter sequences and non-sequence specific DNA. These interactions are established with two guanine bases separated by 10 random nucleotides (GN10G). Our biochemical results demonstrate that the GN10G consensus is essential for transcriptional initiation and contributes to facilitating TFAM binding to DNA substrates. Furthermore, we report a crystal structure of TFAM in complex with a non sequence-specific sequence containing a GN10G consensus. The structure reveals a unique arrangement in which TFAM bridges two DNA substrates while maintaining the GN10G interactions. We propose that the GN10G consensus is key to facilitate the interaction of TFAM with DNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Arrayed in vivo barcoding for multiplexed sequence verification of plasmid DNA and demultiplexing of pooled libraries

Sequence verification of plasmid DNA is critical for many cloning and molecular biology workflows. To leverage high-throughput sequencing, several methods have been developed that add a unique DNA barcode to individual samples prior to pooling and sequencing. However, these methods require an individual plasmid extraction and/or in vitro barcoding reaction for each sample processed, limiting throughput and adding cost. Here, we develop an arrayed in vivo plasmid barcoding platform that enables pooled plasmid extraction and library preparation for Oxford Nanopore sequencing. This method has a high accuracy and recovery rate, and greatly increases throughput and reduces cost relative to other plasmid barcoding methods or Sanger sequencing. We use in vivo barcoding to sequence verify >45 000 plasmids and show that the method can be used to transform error-containing dispersed plasmid pools into sequence-perfect arrays or well-balanced pools. In vivo barcoding does not require any specialized equipment beyond a low-overhead Oxford Nanopore sequencer, enabling most labs to flexibly process hundreds to thousands of plasmids in parallel.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Estimating Protistan Diversity Using High‐Throughput Sequencing

Abstract Sequencing hypervariable regions from the 18S rRNA gene is commonly employed to characterize protistan biodiversity, yet there are concerns that short reads do not provide the same taxonomic resolution as full‐length sequences. A total of 7,432 full‐length sequences were used to perform an in silico analysis of how sequences of various lengths and target regions impact downstream ecological interpretations. Sequences that were longer than 400 nucleotides and included the V4 hypervariable region generated results similar to those derived from full‐length 18S rRNA gene sequences. Present high‐throughput sequencing capabilities are approaching protistan diversity estimation comparable to whole gene sequences.

Hu, Sarah K.↗
DOE OSTI2015

SU-E-J-216: A Sequence Independent Approach for Quantification of MR Image Deformations From Brachytherapy Applicators

Purpose: MRI is increasingly used as a single imaging modality for brachytherapy treatment planning. The presence of a brachytherapy applicator may cause distortions in the images, especially at higher field strengths. Our aim is to develop a procedure to quantify these distortions theoretically for any MR-sequence and to verify the estimated deformations for clinical sequences. Methods: Image distortions due to perturbation of the B0-field are proportional to the ratio of the induced frequency shift and the read-out bandwidth of the applied sequence. By reconstructing a frequency-shift map from the phase data from a multi-echo sequence, distortions can be calculated for any MR-sequence. Verification of this method for estimating distortions was performed by acquiring images with opposing read-out directions and consequently opposing distortions. The applicator shift can be determined by rigidly matching these images. Clinically, T2W-TSE-images are used for this purpose. For pre-clinical tests, EPI-sequences with narrow read-out bandwidth (19.5–47.5Hz), consequently large distortions, were added to the set of clinical MRsequences. To quantify deformations of the Utrecht Interstitial CT/MR applicator (Elekta Brachytherapy) on a Philips Ingenia 3T MRI, pre-clinical tests were performed in a phantom with the applicator in water, followed by clinical validation. Results: Deformations observed in the narrow bandwidth EPI-images were well predicted using the frequency-shift, the latter giving an overestimation up to 30%/up to 1 voxel. For clinically applied MR-sequences distortions were well below the voxel size. In patient setup distortions determined from the frequency-shift map were at sub-voxel level (<0.7mm). Using T2W-images larger distortions were found (1–2mm). This discrepancy was caused by patient movement between/during acquisition of the T2W-images with opposing read-out directions. Conclusion: Phantom experiments demonstrated the feasibility of a clinical procedure for quantification of MR-image distortions for any MR-sequence. In a clinical set-up the distortions from a Utrecht interstitial CT/MR applicator are sub-voxel level. This work was partially funded by Elekta Brachytherpy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-231: Comparison of Delineation Variability of Soft Tissue Volume and Position in Head-And-Neck Between Two T1-Weighted Pulse Sequences Using An MR-Simulator with Immobilization

Purpose: There is growing interests in applying MR-simulator(MR-sim) in radiotherapy but MR images subject to hardware, patient and pulse sequence dependent geometric distortion that may potentially influence target definition. This study aimed to evaluate the influence on head-and-neck tissue delineation, in terms of positional and volumetric variability, of two T1-weighted(T1w) MR sequences on a 1.5T MR-sim Methods: Four healthy volunteers were scanned (4 scans for each on different days) using both spin-echo (3DCUBE, TR/TE=500/14ms, TA=183s) and gradient-echo sequences (3DFSPGR, TE/TR=7/4ms, TA=173s) with identical coverage, voxel-size(0.8×0.8×1.0mm3), receiver-bandwidth(62.5kHz/pix) and geometric correction on a 1.5T MR-sim immobilized with personalized thermoplastic cast and head-rest. Under this setting, similar T1w contrast and signal-to-noise ratio were obtained, and factors other than sequence that might bias image distortion and tissue delineation were minimized. VOIs of parotid gland(PGR, PGL), pituitary gland(PIT) and eyeballs(EyeL, EyeR) were carefully drawn, and inter-scan coefficient-of-variation(CV) of VOI centroid position and volume were calculated for each subject. Mean and standard deviation(SD) of the CVs for four subjects were compared between sequences using Wilcoxon ranksum test. Results: The mean positional(<4%) and volumetric(<7%) CVs varied between tissues, majorly dependent on tissue inherent properties like volume, location, mobility and deformability. Smaller mean volumetric CV was found in 3DCUBE, probably due to its less proneness to tissue susceptibility, but only PGL showed significant difference(P<0.05). Positional CVs had no significant differences for all VOIs(P>0.05) between sequences, suggesting volumetric variation might be more sensitive to sequence-dependent delineation difference. Conclusion: Although 3DCUBE is considered less prone to tissue susceptibility-induced artifact and distortion, our preliminary data showed that both sequences had insignificant differences on positional and volumetric CV in most head-and-neck tissues except for PGL. This study is majorly limited in its small sample size. Influences of image contrasts(T1w v.s. T2w) and inter-observer difference have to be further investigated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-IeP1-08: MR Geometric Distortion Dependency On Imaging Sequence, Acquisition Orientation and Receiver Bandwidth of a Dedicated 1.5T MR-Simulator

Purpose: To investigate the 3D geometric distortion of four potential MR sequences for radiotheraptic applications, and its dependency on sequence-type, acquisition-orientation and receiver-bandwidth from a dedicated 1.5T 700mm-wide bore MR-simulator (Magnetom-Aera, Sienmens Healthcare, Erlangen, Germany), using a large customized geometric accuracy phantom. Methods: This work studied 3D gradient-echo (VIBE) and spin-echo (SPACE) sequences for anatomical imaging; a specific ultra-short-TE sequence (PETRA) potentially for bone imaging and MR-based dosimetry; and a motion-insensitive sequence (BLADE) for dynamic applications like 4D-MRI. Integrated geometric-correction was employed, three orthogonal acquisition-orientations and up to three receiver-bandwidths were used, yielding 27 acquisitions for testing (Table 1a).A customized geometric accuracy phantom (polyurethane, MR/CT invisible, W×L×H:55×55×32.5cm3) was constructed and filled with 3892 spherical markers (6mm diameter, MR/CT visible) arranged on a 25mm-interval 3D isotropic-grid (Fig.1). The marker positions in MR images were quantitatively calculated and compared against those in the CT-reference using customized MatLab scripts. Results: The average distortion within various diameter-of-spherical-volumes (DSVs) and the usable DSVs under various distortion limits were measured (Tables 1b-c). It was observed that distortions fluctuated when sequence-type, acquisition-orientation or receiver-bandwidth changed (e.g. within 300mm-DSV, the lowest/highest average distortions of VIBE were 0.40mm/0.59mm, a 47.5% difference). According to AAPM-TG66 (<1mm distortion, left-most column of Table 1c), PETRA (Largest-DSV:253.9mm) has the potential on brain treatment, while BLADE (Largest-DSV:207.2mm) may need improvement for thoracic/abdominal applications. The results of VIBE (Largest-DSVs:294.3mm, the best among tested acquisitions) and SPACE (Largest-DSVs:267.7mm) suggests their potentials on head and neck applications. These Largest-DSVs were attained on different acquisition-orientations and receiver-bandwidths. Conclusion: Geometric distortion was shown to be dependent on sequence-type, acquisition-orientation and receiver-bandwidth. In the experiment, no configuration in any one of these factors could consistently reduce distortion while the others were varying. The distortion analysis result is a valuable guideline for sequence selection and optimization for MR-aided radiotherapy applications.

60 APPLIED LIFE SCIENCES↗