Vessel orientation-dependent sensitivity of optoacoustic imaging using a linear array transducer

For clinical optoacoustic imaging, linear probes are preferably used because they allow versatile imaging of the human body with real-time display and free-hand probe guidance. The two-dimensional (2-D) optoacoustic image obtained with this type of probe is generally interpreted as a 2-D cross-section of the tissue just as is common in echo ultrasound. We demonstrate in three-dimensional simulations, phantom experiments, and in vivo mouse experiments that for vascular imaging this interpretation is often inaccurate. The cylindrical blood vessels emit anisotropic acoustic transients, which can be sensitively detected only if the direction of acoustic radiation coincides with the probe aperture. Our results reveal for this reason that the signal amplitude of different blood vessels may differ even if the vessels have the same diameter and initial pressure distribution but different orientation relative to the imaging plane. This has important implications for the image interpretation, for the probe guidance technique, and especially in cases when a quantitative reconstruction of the optical tissue properties is required.

Fluorescence lifetime imaging of the ocular fundus in mice

PURPOSE Fundus autofluorescence (AF) is characterized not only by its intensity or excitation and emission spectra but also by the lifetimes of the fluorophores. Fluorescence lifetime is influenced by the fluorophore's microenvironment and may provide information about the metabolic tissue state. We report quantitative and qualitative autofluorescence lifetime imaging of the ocular fundus in mice. METHODS A fluorescence lifetime imaging ophthalmoscope (FLIO) was used to measure fluorescence lifetimes of endogenous fluorophores in the murine retina. FLIO imaging was performed in 1-month-old C57BL/6, BALB/c, and C3A.Cg-Pde6b(+)Prph2(Rd2)/J mice. Measurements were repeated at monthly intervals over the course of 6 months. For correlation with structural changes, an optical coherence tomogram was acquired. RESULTS Fundus autofluorescence lifetime images were readily obtained in all mice. In the short spectral channel (498-560 nm), mean ± SEM AF lifetimes were 956 ± 15 picoseconds (ps) in C57BL/6; 801 ± 35 ps in BALB/c mice; and 882 ± 37 ps in C3A.Cg-Pde6b(+)Prph2(Rd2)/J mice. In the long spectral channel (560-720 nm), mean ± SEM AF lifetimes were 298 ± 14 ps in C57BL/6 mice, 241 ± 10 ps in BALB/c mice, and 288 ± 8 ps in C3A.Cg-Pde6b(+)Prph2(Rd2)/J mice. There was a general decrease in mean AF lifetimes with age. CONCLUSIONS Although fluorescence lifetime values differ among mouse strains, we found little variance within the groups. Fundus autofluorescence lifetime imaging in mice may provide additional information for understanding retinal disease processes and may facilitate monitoring of therapeutic effects in preclinical studies.

K-t GRAPPA-accelerated 4D flow MRI of liver hemodynamics: influence of different acceleration factors on qualitative and quantitative assessment of blood flow.

OBJECTIVE We sought to evaluate the feasibility of k-t parallel imaging for accelerated 4D flow MRI in the hepatic vascular system by investigating the impact of different acceleration factors. MATERIALS AND METHODS k-t GRAPPA accelerated 4D flow MRI of the liver vasculature was evaluated in 16 healthy volunteers at 3T with acceleration factors R = 3, R = 5, and R = 8 (2.0 × 2.5 × 2.4 mm(3), TR = 82 ms), and R = 5 (TR = 41 ms); GRAPPA R = 2 was used as the reference standard. Qualitative flow analysis included grading of 3D streamlines and time-resolved particle traces. Quantitative evaluation assessed velocities, net flow, and wall shear stress (WSS). RESULTS Significant scan time savings were realized for all acceleration factors compared to standard GRAPPA R = 2 (21-71 %) (p < 0.001). Quantification of velocities and net flow offered similar results between k-t GRAPPA R = 3 and R = 5 compared to standard GRAPPA R = 2. Significantly increased leakage artifacts and noise were seen between standard GRAPPA R = 2 and k-t GRAPPA R = 8 (p < 0.001) with significant underestimation of peak velocities and WSS of up to 31 % in the hepatic arterial system (p <0.05). WSS was significantly underestimated up to 13 % in all vessels of the portal venous system for k-t GRAPPA R = 5, while significantly higher values were observed for the same acceleration with higher temporal resolution in two veins (p < 0.05). CONCLUSION k-t acceleration of 4D flow MRI is feasible for liver hemodynamic assessment with acceleration factors R = 3 and R = 5 resulting in a scan time reduction of at least 40 % with similar quantitation of liver hemodynamics compared with GRAPPA R = 2.

A g-factor metric for k-t-GRAPPA- and PEAK-GRAPPA-based parallel imaging.

PURPOSE The aim of this work is to derive a theoretical framework for quantitative noise and temporal fidelity analysis of time-resolved k-space-based parallel imaging methods. THEORY An analytical formalism of noise distribution is derived extending the existing g-factor formulation for nontime-resolved generalized autocalibrating partially parallel acquisition (GRAPPA) to time-resolved k-space-based methods. The noise analysis considers temporal noise correlations and is further accompanied by a temporal filtering analysis. METHODS All methods are derived and presented for k-t-GRAPPA and PEAK-GRAPPA. A sliding window reconstruction and nontime-resolved GRAPPA are taken as a reference. Statistical validation is based on series of pseudoreplica images. The analysis is demonstrated on a short-axis cardiac CINE dataset. RESULTS The superior signal-to-noise performance of time-resolved over nontime-resolved parallel imaging methods at the expense of temporal frequency filtering is analytically confirmed. Further, different temporal frequency filter characteristics of k-t-GRAPPA, PEAK-GRAPPA, and sliding window are revealed. CONCLUSION The proposed analysis of noise behavior and temporal fidelity establishes a theoretical basis for a quantitative evaluation of time-resolved reconstruction methods. Therefore, the presented theory allows for comparison between time-resolved parallel imaging methods and also nontime-resolved methods. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

Imaging of the spleen in malaria

Splenomegaly, albeit variably, is a hallmark of malaria; yet, the role of the spleen in Plasmodium infections remains vastly unknown. The implementation of imaging to study the spleen is rapidly advancing our knowledge of this so-called "blackbox" of the abdominal cavity. Not only has ex vivo imaging revealed the complex functional compartmentalization of the organ and immune effector cells, but it has also allowed the observation of major structural remodeling during infections. In vivo imaging, on the other hand, has allowed quantitative measurements of the dynamic passage of the parasite at spatial and temporal resolution. Here, we review imaging techniques used for studying the malarious spleen, from optical microscopy to in vivo imaging, and discuss the bright perspectives of evolving technologies in our present understanding of the role of this organ in infections caused by Plasmodium.

Quantitative microstructure analysis of polymer-modified mortars

Digital light, fluorescence and electron microscopy in combination with wavelength-dispersive spectroscopy were used to visualize individual polymers, air voids, cement phases and filler minerals in a polymer-modified cementitious tile adhesive. In order to investigate the evolution and processes involved in formation of the mortar microstructure, quantifications of the phase distribution in the mortar were performed including phase-specific imaging and digital image analysis. The required sample preparation techniques and imaging related topics are discussed. As a form of case study, the different techniques were applied to obtain a quantitative characterization of a specific mortar mixture. The results indicate that the mortar fractionates during different stages ranging from the early fresh mortar until the final hardened mortar stage. This induces process-dependent enrichments of the phases at specific locations in the mortar. The approach presented provides important information for a comprehensive understanding of the functionality of polymer-modified mortars.

Quantitative Analysis of Mouse Retinal Layers Using Automated Segmentation of Spectral Domain Optical Coherence Tomography Images.

PURPOSE Quantification of retinal layers using automated segmentation of optical coherence tomography (OCT) images allows for longitudinal studies of retinal and neurological disorders in mice. The purpose of this study was to compare the performance of automated retinal layer segmentation algorithms with data from manual segmentation in mice using the Spectralis OCT. METHODS Spectral domain OCT images from 55 mice from three different mouse strains were analyzed in total. The OCT scans from 22 C57Bl/6, 22 BALBc, and 11 C3A.Cg-Pde6b(+)Prph2(Rd2) /J mice were automatically segmented using three commercially available automated retinal segmentation algorithms and compared to manual segmentation. RESULTS Fully automated segmentation performed well in mice and showed coefficients of variation (CV) of below 5% for the total retinal volume. However, all three automated segmentation algorithms yielded much thicker total retinal thickness values compared to manual segmentation data (P < 0.0001) due to segmentation errors in the basement membrane. CONCLUSIONS Whereas the automated retinal segmentation algorithms performed well for the inner layers, the retinal pigmentation epithelium (RPE) was delineated within the sclera, leading to consistently thicker measurements of the photoreceptor layer and the total retina. TRANSLATIONAL RELEVANCE The introduction of spectral domain OCT allows for accurate imaging of the mouse retina. Exact quantification of retinal layer thicknesses in mice is important to study layers of interest under various pathological conditions.

Prediction of Trabecular Bone Anisotropy from Quantitative Computed Tomography using Supervised Learning and a Novel Morphometric Feature Descriptor

Patient-specific biomechanical models including local bone mineral density and anisotropy have gained importance for assessing musculoskeletal disorders. However the trabecular bone anisotropy captured by high-resolution imaging is only available at the peripheral skeleton in clinical practice. In this work, we propose a supervised learning approach to predict trabecular bone anisotropy that builds on a novel set of pose invariant feature descriptors. The statistical relationship between trabecular bone anisotropy and feature descriptors were learned from a database of pairs of high resolution QCT and clinical QCT reconstructions. On a set of leave-one-out experiments, we compared the accuracy of the proposed approach to previous ones, and report a mean prediction error of 6% for the tensor norm, 6% for the degree of anisotropy and 19◦ for the principal tensor direction. These findings show the potential of the proposed approach to predict trabecular bone anisotropy from clinically available QCT images.

Quantitative multi-slice computed tomography assessment of the mitral valvular complex for transcatheter mitral valve interventions part 1: systematic measurement methodology and inter-observer variability

AIMS Transcatheter mitral valve replacement (TMVR) is an emerging technology with the potential to treat patients with severe mitral regurgitation at excessive risk for surgical mitral valve surgery. Multimodal imaging of the mitral valvular complex and surrounding structures will be an important component for patient selection for TMVR. Our aim was to describe and evaluate a systematic multi-slice computed tomography (MSCT) image analysis methodology that provides measurements relevant for transcatheter mitral valve replacement. METHODS AND RESULTS A systematic step-by-step measurement methodology is described for structures of the mitral valvular complex including: the mitral valve annulus, left ventricle, left atrium, papillary muscles and left ventricular outflow tract. To evaluate reproducibility, two observers applied this methodology to a retrospective series of 49 cardiac MSCT scans in patients with heart failure and significant mitral regurgitation. For each of 25 geometrical metrics, we evaluated inter-observer difference and intra-class correlation. The inter-observer difference was below 10% and the intra-class correlation was above 0.81 for measurements of critical importance in the sizing of TMVR devices: the mitral valve annulus diameters, area, perimeter, the inter-trigone distance, and the aorto-mitral angle. CONCLUSIONS MSCT can provide measurements that are important for patient selection and sizing of TMVR devices. These measurements have excellent inter-observer reproducibility in patients with functional mitral regurgitation.

RETICULAR PSEUDODRUSEN ON INFRARED IMAGING ARE TOPOGRAPHICALLY DISTINCT FROM SUBRETINAL DRUSENOID DEPOSITS ON EN FACE OPTICAL COHERENCE TOMOGRAPHY.

PURPOSE: To evaluate the quantitative and topographic relationship between reticular pseudodrusen (RPD) on infrared reflectance (IR) and subretinal drusenoid deposits (SDD) on en face volumetric spectral domain optical coherence tomography. METHODS: Reticular pseudodrusen were marked on IR images by a masked observer. Subretinal drusenoid deposits were visualized on en face sections of spectral domain optical coherence tomography below the external limiting membrane and identified by a semiautomated technique. Control RPD lesions were generated in a random distribution for each IR image. Binary maps of control and experimental RPD and SDD were merged and analyzed in terms of topographic localization and quantitative drusen load comparison. RESULTS: A total of 54 eyes of 41 patients diagnosed with RPD were included in this study. The average number of RPD lesions on IR images was 320 ± 44.62 compared with 127 ± 26.02 SDD lesions on en face (P < 0.001). The majority of RPD lesions did not overlap with SDD lesions and were located >30 μm away (92%). The percentage of total SDD lesions overlapping RPD was 2.91 ± 0.87% compared with 1.73 ± 0.68% overlapping control RPD lesions (P < 0.05). The percentage of total SDD lesions between 1 and 3 pixels of the nearest RPD lesion was 5.08 ± 1.40% compared with 3.33 ± 1.07% between 1 and 3 pixels of the nearest control RPD lesion (P < 0.05). CONCLUSION: This study identified significantly more RPD lesions on IR compared with SDD lesions on en face spectral domain optical coherence tomography and found that a large majority of SDD (>90% of lesions) were >30 μm away from the nearest RPD. Together, our findings indicate that RPD and SDD are two entities that are only occasionally topographically associated, suggesting that at some stage in their development, they may be pathologically related.

Comparison of Routine Brain Imaging at 3 T and 7 T.

OBJECTIVE The aim of this study was to compare quantitative and semiquantitative parameters (signal-to-noise ratio [SNR], contrast-to-noise ratio [CNR], image quality, diagnostic confidence) from a standard brain magnetic resonance imaging examination encompassing common neurological disorders such as demyelinating disease, gliomas, cerebrovascular disease, and epilepsy, with comparable sequence protocols and acquisition times at 3 T and at 7 T. MATERIALS AND METHODS Ten healthy volunteers and 4 subgroups of 40 patients in total underwent comparable magnetic resonance protocols with standard diffusion-weighted imaging, 2D and 3D turbo spin echo, 2D and 3D gradient echo and susceptibility-weighted imaging of the brain (10 sequences) at 3 T and 7 T. The subgroups comprised patients with either lesional (n = 5) or nonlesional (n = 4) epilepsy, intracerebral tumors (n = 11), demyelinating disease (n = 11) (relapsing-remitting multiple sclerosis [MS, n = 9], secondary progressive MS [n = 1], demyelinating disease not further specified [n = 1]), or chronic cerebrovascular disorders [n = 9]). For quantitative analysis, SNR and CNR were determined. For a semiquantitative assessment of the diagnostic confidence, a 10-point scale diagnostic confidence score (DCS) was applied. Two experienced radiologists with additional qualification in neuroradiology independently assessed, blinded to the field strength, 3 pathology-specific imaging criteria in each of the 4 disease groups and rated their diagnostic confidence. The overall image quality was semiquantitatively assessed using a 4-point scale taking into account whether diagnostic decision making was hampered by artifacts or not. RESULTS Without correction for spatial resolution, SNR was higher at 3 T except in the T2 SPACE 3D, DWI single shot, and DIR SPACE 3D sequences. The SNR corrected by the ratio of 3 T/7 T voxel sizes was higher at 7 T than at 3 T in 10 of 11 sequences (all except for T1 MP2RAGE 3D).In CNR, there was a wide variation between sequences and patient cohorts, but average CNR values were broadly similar at 3 T and 7 T.DCS values for all 4 pathologic entities were higher at 7 T than at 3 T. The DCS was significantly higher at 7 T for diagnosis and exclusion of cortical lesions in vascular disease. A tendency to higher DCS at 7 T for cortical lesions in MS was observed, and for the depiction of a central vein and iron deposits within MS lesions. Despite motion artifacts, DCS values were higher at 7 T for the diagnosis and exclusion of hippocampal sclerosis in mesial temporal lobe epilepsy (improved detection of the hippocampal subunits). Interrater agreement was 69.7% at 3 T and 93.3% at 7 T. There was no significant difference in the overall image quality score between 3 T and 7 T taking into account whether diagnostic decision making was hampered by artifacts or not. CONCLUSIONS Ultra-high-field magnetic resonance imaging at 7 T compared with 3 T yielded an improved diagnostic confidence in the most frequently encountered neurologic disorders. Higher spatial resolution and contrast were identified as the main contributory factors.

Fast magnetic resonance temperature imaging for focused ultrasound thermal therapy

The current standard for temperature sensitive imaging using magnetic resonance (MR) is 2-D, spoiled, fast gradient-echo (fGRE) phase-difference imaging exploiting temperature dependent changes in the proton resonance frequency (PRF). The echo-time (TE) for optimal sensitivity is larger than the typical repetition time (TR) of an fGRE sequence. Since TE must be less than TR in the fGRE sequence, this limits the technique's achievable sensitivity, spatial, and temporal resolution. This adversely affects both accuracy and volume coverage of the measurements. Accurate measurement of the rapid temperature changes associated with pulsed thermal therapies, such as high-intensity focused ultrasound (FUS), at optimal temperature sensitivity requires faster acquisition times than those currently available. ^ Use of fast MR acquisition strategies, such as interleaved echo-planar and spiral imaging, can provide the necessary increase in temporal performance and sensitivity while maintaining adequate signal-to-noise and in-plane spatial resolution. This research explored the adaptation and optimization of several fast MR acquisition methods for thermal monitoring of pulsed FUS thermal therapy. Temperature sensitivity, phase-difference noise and phase-difference to phase-difference-to noise ratio for the different pulse sequences were evaluated under varying imaging parameters in an agar gel phantom to establish optimal sequence parameters for temperature monitoring. The temperature sensitivity coefficient of the gel phantom was measured, allowing quantitative temperature extrapolations. ^ Optimized fast sequences were compared based on the ability to accurately monitor temperature changes at the focus of a high-intensity focused ultrasound unit, volume coverage, and contrast-to-noise ratio in the temperature maps. Operating parameters, which minimize complex phase-difference measurement errors introduced by use of the fast-imaging methods, were established. ^

Investigation of arterial spin labeling MRI for quantitative cerebral blood flow measurement

Arterial spin labeling (ASL) is a technique for noninvasively measuring cerebral perfusion using magnetic resonance imaging. Clinical applications of ASL include functional activation studies, evaluation of the effect of pharmaceuticals on perfusion, and assessment of cerebrovascular disease, stroke, and brain tumor. The use of ASL in the clinic has been limited by poor image quality when large anatomic coverage is required and the time required for data acquisition and processing. This research sought to address these difficulties by optimizing the ASL acquisition and processing schemes. To improve data acquisition, optimal acquisition parameters were determined through simulations, phantom studies and in vivo measurements. The scan time for ASL data acquisition was limited to fifteen minutes to reduce potential subject motion. A processing scheme was implemented that rapidly produced regional cerebral blood flow (rCBF) maps with minimal user input. To provide a measure of the precision of the rCBF values produced by ASL, bootstrap analysis was performed on a representative data set. The bootstrap analysis of single gray and white matter voxels yielded a coefficient of variation of 6.7% and 29% respectively, implying that the calculated rCBF value is far more precise for gray matter than white matter. Additionally, bootstrap analysis was performed to investigate the sensitivity of the rCBF data to the input parameters and provide a quantitative comparison of several existing perfusion models. This study guided the selection of the optimum perfusion quantification model for further experiments. The optimized ASL acquisition and processing schemes were evaluated with two ASL acquisitions on each of five normal subjects. The gray-to-white matter rCBF ratios for nine of the ten acquisitions were within ±10% of 2.6 and none were statistically different from 2.6, the typical ratio produced by a variety of quantitative perfusion techniques. Overall, this work produced an ASL data acquisition and processing technique for quantitative perfusion and functional activation studies, while revealing the limitations of the technique through bootstrap analysis. ^

Improved Techniques for Acquisition and Analysis of Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Detecting Vascular Permeability in the Central Nervous System

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a noninvasive technique for quantitative assessment of the integrity of blood-brain barrier and blood-spinal cord barrier (BSCB) in the presence of central nervous system pathologies. However, the results of DCE-MRI show substantial variability. The high variability can be caused by a number of factors including inaccurate T1 estimation, insufficient temporal resolution and poor contrast-to-noise ratio. My thesis work is to develop improved methods to reduce the variability of DCE-MRI results. To obtain fast and accurate T1 map, the Look-Locker acquisition technique was implemented with a novel and truly centric k-space segmentation scheme. In addition, an original multi-step curve fitting procedure was developed to increase the accuracy of T1 estimation. A view sharing acquisition method was implemented to increase temporal resolution, and a novel normalization method was introduced to reduce image artifacts. Finally, a new clustering algorithm was developed to reduce apparent noise in the DCE-MRI data. The performance of these proposed methods was verified by simulations and phantom studies. As part of this work, the proposed techniques were applied to an in vivo DCE-MRI study of experimental spinal cord injury (SCI). These methods have shown robust results and allow quantitative assessment of regions with very low vascular permeability. In conclusion, applications of the improved DCE-MRI acquisition and analysis methods developed in this thesis work can improve the accuracy of the DCE-MRI results.

Radiomics of NSCLC: Quantitative CT Image Feature Characterization and Tumor Shrinkage Prediction

Radiomics is the high-throughput extraction and analysis of quantitative image features. For non-small cell lung cancer (NSCLC) patients, radiomics can be applied to standard of care computed tomography (CT) images to improve tumor diagnosis, staging, and response assessment. The first objective of this work was to show that CT image features extracted from pre-treatment NSCLC tumors could be used to predict tumor shrinkage in response to therapy. This is important since tumor shrinkage is an important cancer treatment endpoint that is correlated with probability of disease progression and overall survival. Accurate prediction of tumor shrinkage could also lead to individually customized treatment plans. To accomplish this objective, 64 stage NSCLC patients with similar treatments were all imaged using the same CT scanner and protocol. Quantitative image features were extracted and principal component regression with simulated annealing subset selection was used to predict shrinkage. Cross validation and permutation tests were used to validate the results. The optimal model gave a strong correlation between the observed and predicted shrinkages with . The second objective of this work was to identify sets of NSCLC CT image features that are reproducible, non-redundant, and informative across multiple machines. Feature sets with these qualities are needed for NSCLC radiomics models to be robust to machine variation and spurious correlation. To accomplish this objective, test-retest CT image pairs were obtained from 56 NSCLC patients imaged on three CT machines from two institutions. For each machine, quantitative image features with concordance correlation coefficient values greater than 0.90 were considered reproducible. Multi-machine reproducible feature sets were created by taking the intersection of individual machine reproducible feature sets. Redundant features were removed through hierarchical clustering. The findings showed that image feature reproducibility and redundancy depended on both the CT machine and the CT image type (average cine 4D-CT imaging vs. end-exhale cine 4D-CT imaging vs. helical inspiratory breath-hold 3D CT). For each image type, a set of cross-machine reproducible, non-redundant, and informative image features was identified. Compared to end-exhale 4D-CT and breath-hold 3D-CT, average 4D-CT derived image features showed superior multi-machine reproducibility and are the best candidates for clinical correlation.