Cartilage compositional MRI-a narrative review of technical development and clinical applications over the past three decades.

Articular cartilage damage and degeneration are among hallmark manifestations of joint injuries and arthritis, classically osteoarthritis. Cartilage compositional MRI (Cart-C MRI), a quantitative technique, which aims to detect early-stage cartilage matrix changes that precede macroscopic alterations, began development in the 1990s. However, despite the significant advancements over the past three decades, Cart-C MRI remains predominantly a research tool, hindered by various technical and clinical hurdles. This paper will review the technical evolution of Cart-C MRI, delve into its clinical applications, and conclude by identifying the existing gaps and challenges that need to be addressed to enable even broader clinical application of Cart-C MRI

Quantitative rotating frame relaxometry methods in MRI

Macromolecular degeneration and biochemical changes in tissue can be quantified using rotating frame relaxometry in MRI. It has been shown in several studies that the rotating frame longitudinal relaxation rate constant (R1ρ) and the rotating frame transverse relaxation rate constant (R2ρ) are sensitive biomarkers of phenomena at the cellular level. In this comprehensive review, existing MRI methods for probing the biophysical mechanisms that affect the rotating frame relaxation rates of the tissue (i.e. R1ρ and R2ρ) are presented. Long acquisition times and high radiofrequency (RF) energy deposition into tissue during the process of spin-locking in rotating frame relaxometry are the major barriers to the establishment of these relaxation contrasts at high magnetic fields. Therefore, clinical applications of R1ρ and R2ρ MRI using on- or off-resonance RF excitation methods remain challenging. Accordingly, this review describes the theoretical and experimental approaches to the design of hard RF pulse cluster- and adiabatic RF pulse-based excitation schemes for accurate and precise measurements of R1ρ and R2ρ. The merits and drawbacks of different MRI acquisition strategies for quantitative relaxation rate measurement in the rotating frame regime are reviewed. In addition, this review summarizes current clinical applications of rotating frame MRI sequences. © 2016 John Wiley & Sons, Ltd

Pulse sequences for measuring exchange rates between proton species: From unlocalised NMR spectroscopy to chemical exchange saturation transfer imaging

Within the field of NMR spectroscopy, the study of chemical exchange processes through saturation transfer techniques has a long history. In the context of MRI, chemical exchange techniques have been adapted to increase the sensitivity of imaging to small fractions of exchangeable protons, including the labile protons of amines, amides and hydroxyls. The MR contrast is generated by frequency-selective irradiation of the labile protons, which results in a reduction of the water signal associated with transfer of the labile protons’ saturated magnetization to the protons of the surrounding free water. The signal intensity depends on the rate of chemical exchange and the concentration of labile protons as well as on the properties of the irradiation field. This methodology is referred to as CEST (chemical exchange saturation transfer) imaging. Applications of CEST include imaging of molecules with short transverse relaxation times and mapping of physiological parameters such as pH, temperature, buffer concentration and chemical composition due to the dependency of this chemical exchange effect on all these parameters. This article aims to describe these effects both theoretically and experimentally. In depth analysis and mathematical modelling are provided for all pulse sequences designed to date to measure the chemical exchange rate. Importantly, it has become clear that the background signal from semi-solid protons and the presence of the Nuclear Overhauser Effect (NOE), either through direct dipole-dipole mechanisms or through exchange-relayed signals, complicates the analysis of CEST effects. Therefore, advanced methods to suppress these confounding factors have been developed, and these are also reviewed. Finally, the experimental work conducted both in vitro and in vivo is discussed and the progress of CEST imaging towards clinical practice is presented

Docetaxel chemotherapy response in PC3 prostate cancer mouse model detected by rotating frame relaxations and water diffusion

MRI is a common method of prostate cancer diagnosis. Several MRI-derived markers, including the apparent diffusion coefficient (ADC) based on diffusion-weighted imaging, have been shown to provide values for prostate cancer detection and characterization. The hypothesis of the study was that docetaxel chemotherapy response could be picked up earlier with rotating frame relaxation times TRAFF2 and TRAFF4 than with the continuous wave T1ρ, adiabatic T1ρ, adiabatic T2ρ, T1, T2 or water ADC. Human PC3 prostate cancer cells expressing a red fluorescent protein were implanted in 21 male mice. Docetaxel chemotherapy was given once a week starting 1 week after cell implantation for 10 randomly selected mice, while the rest served as a control group (n = 11). The MRI consisted of relaxation along a fictitious field (RAFF) in the second (RAFF2) and fourth (RAFF4) rotating frames, T1 and T2, continuous wave T1ρ, adiabatic T1ρ and adiabatic T2ρ relaxation time measurements and water ADC. MRI was conducted at 7 T, once a week up to 4 weeks from cell implantation. The tumor volume was monitored using T2-weighted MRI and optical imaging. The histology was evaluated after the last imaging time point. Significantly reduced RAFFn, T1ρ,T2ρ and conventional relaxation times 4 weeks after tumor implantation were observed in the treated tumors compared with the controls. The clearest short- and long-term responses were obtained with T1, while no clear improvement in response to treatment was detected with novel methods compared with conventional methods or with RAFFn compared with all others. The tumor volume decreased after a two-week time point for the treated group and increased significantly in the control group, which was supported by increasing red fluorescent light emission in the control tumors. Decreased relaxation times were associated with successful chemotherapy outcomes. The results indicate altered relaxation mechanisms compared with higher dose chemotherapies previously published

A short & sweet story of CHO

The solid state nuclear magnetic resonance (SSNMR) study of nearly intact plant cell walls along with the computational study of glucose and malonic acid are presented. Previously unassigned 13C chemical shifts are presented for the various carbohydrates in the primary plant cell wall of Arabidopsis thaliana. A continuation of the SSNMR study involved the computational determination of glucose chemical shifts, a model compound for the study of larger carbohydrates. Additional computational studies determined the energy relationship between hydrated tautomers of malonic acid, a commonly occurring atmospheric dicarboxylic acid. In the malonic acid study, agreement between experiment and calculated frequencies verified the presence of the enol form of malonic acid. The development and analysis of a chemical education tool, a quantum chemistry concept inventory, whose aim is to understand misconceptions is also included in this dissertation

Quantitative Magnetic Resonance Imaging and Analysis of Articular Cartilage and Osteoarthritis

MRI plays an important role in the continuing search for a sensitive osteoarthritis (OA) imaging biomarker able to detect early, pre-morphological alterations in cartilage composition. Determining the compositional recovery pattern of cartilage following acute joint loading could potentially present a more sensitive biomarker for defining cartilage health [1]. However, only a limited amount of studies have assessed both the immediate effect of joint loading on cartilage, as well as its post-loading recovery. In addition, when assessing the compositional responses of cartilage to joint loading, previous studies usually did not incorporate the measurement error of the used quantitative MRI technique into their analysis. Therefore, an uncertainty persists whether or not compositional MRI techniques are sensitive enough to measure changes in water and macromolecular content of cartilage, or if previous studies were merely measuring noise. Consequently, an objective of this thesis is to increase our understanding of and reliability in quantitative T2 and T1ρ relaxation time mapping to detect compositional responses of cartilage following a joint loading activity. Furthermore, to obtain the quantitative morphological and compositional measures of cartilage, detailed region-specific delineation of cartilage is required. This delineation (or segmentation) of cartilage is laborious and time-consuming as it is usually performed manually by an expert observer. Many new advances in image analysis, particularly those in convolutional neural networks (CNNs) and deep learning, have enabled a time-efficient semi- or fully-automated alternative to this process [2, 3]. This thesis explores the utility of deep CNNs generated segmentations for accurate surface-based analysis of cartilage morphology and composition from knee MRIs as well as of cortical bone thickness from knee CTs. Chapter 1 will provide an introduction into the structure and biomechanics of articular cartilage and the role of MRI in imaging the degenerative joint disorder, osteoarthritis as well as the effects of different joint loading activities on cartilage morphology and composition. Chapter 2 explains the principle of MRI and the pulse sequences used in the following chapter for the morphometric and compositional assessment of articular cartilage. Chapter 3 describes the use of 3D Cartilage Surface Mapping (3D-CaSM) [3] to assess variations in cartilage T1ρ and T2 relaxation times of young, healthy participants following a mild, unilateral stepping activity. By evaluating and incorporating the intrasessional repeatability of the T1ρ and T2 mapping techniques, I aim to highlight those cartilage areas experiencing exercise-induced compositional changes greater than measurement error. A significant amount of time is needed to manually segment the regions-of-interest required to perform the 3D-CaSM used in Chapter 3. Therefore, in Chapter 4, I assessed the use of deep convolutional neural networks for automating the segmentation process for multiple knee joint tissues simultaneous and increase the time-efficiency for evaluating knee MR datasets. I evaluated the use of a conditional Generative Adversarial Network (cGAN) as a potentially improved method for automated segmentation compared to the widely used convolutional neural network, U-Net. In Chapter 5 I combined the 3D-CaSM and automated segmentation methods presented in Chapters 3 and 4, respectively to assess the use of fully automatic segmentations of femoral and tibial bone-cartilage structures for accurate surface-based analysis of cartilage morphology and composition on knee MR images. This was performed on publicly available data from the Osteoarthritis Initiative, a multicentre observational study with expert manual segmentations provided by the Zuse Institute in Berlin. Chapter 6 describes an automated pipeline for subchondral cortical bone thickness mapping from knee CT data. I developed a method of using automated segmentations of articular cartilage and bone from knee MRI data to determine the periarticular bone surface which is covered by cartilage. This surface was then used to perform cortical bone thickness measurements on corresponding CT data. I validated this pipeline using data from the EU-funded, multi-centre observational study called Applied Private-Public partneRship enabling OsteoArthritis Clinical Headway (APPROACH). Chapter 7 summarises the main conclusions and contributions of the works presented in this thesis as well as providing directions for future work.PhD Studentship funded by GlaxoSmithKlin

NMR investigations of biological and synthetic phosphate-based nanocomposites

The study of complex organic, inorganic and composite systems is greatly facilitated by solid state nuclear magnetic resonance (NMR) spectroscopy. This is especially true for materials lacking crystalline long-range order or having low atomic mass contrast, such as amorphous organic materials, which renders other methods such as x-ray diffraction (XRD) and transmission electron microscopy (TEM) incapable of comprehensive characterization. In this dissertation, a variety of one- and two-dimensional (2D) solid-state NMR measurements are applied to investigate the composition and nanometer-scale structure of a variety of organic-inorganic hybrid systems as well as complex inorganic phases. Bone, which is a natural nanocomposite of an inorganic apatitic phosphate and the organic protein collagen, has been studied by 1H single-resonance, 1H-31P and 1H-13C double-resonance, as well as 1H-13C-31P triple-resonance experiments. Analysis of 31P dephasing by heteronuclear recoupling with dephasing by strong homonuclear interactions of protons (HARDSHIP) has provided information about the size of the apatite nanocrystals. The concentrations of various moieties in the composite, such as the OH-, CO32-,HPO4 2-,H2O-PO43-, and Na in the inorganic apatite, were determined by quantitative spectroscopy via spectral selection of specific chemical moieties. X{lcub} 1H{rcub} HARDSHIP NMR was used to prove their incorporation into the apatite nanocrystals. 31P chemical shift anisotropy (CSA) dephasing experiments as well as 1H{lcub}31P{rcub} rotational echo double resonance (REDOR) experiments have identified and quantified the hydrogen and phosphate species located at the surface and the interior of the apatite crystal. Strongly bound H2O, as well as a layer of viscous water, is present at the organic-inorganic interface, as proven by 1H spin-diffusion detected via 13C and 31P nuclei. Investigation of the proximity of organic moieties to the apatite surface via 13C{lcub}31P{rcub} heteronuclear recoupling experiments provide a structural insight of the organic-inorganic interface.;Biomimetic synthetic organic-inorganic phosphate hybrid materials have been investigated. 31P NMR spectroscopy has enabled identification and quantification of the different types of phosphates in these materials, and the formation of nanocomposites is proven by wideline separation (WISE) NMR with spin diffusion. A bone-replacement material, Si/Zn-doped beta-tricalcium phosphate (TCP), has also been investigated. Spectral selection techniques based on J-modulation and double-quantum filtering have enabled elucidation of the spectrally overlapping silicate Q species. 29Si{lcub} 31P{rcub} REDOR proves that while the silicate is indeed incorporated into the TCP matrix, it is significantly aggregated into ∼7 nm diameter domains. Further, a new class of hybrid systems based on polyamide 6 and phosphate glass was studied, where HARDSHIP has confirmed the formation of nanocomposites of the phosphate glass dispersed in the polyamide matrix. 1H- 31P heteronuclear correlation (HetCor) NMR indicated phosphate-polyamide interactions and alterations of the phosphate glass surface by the polyamide matrix. 13C NMR has also shown that the phosphate glass promotes the crystalline gamma-phase of the polyamide