Tinnitus is a pathological event caused by abnormal stimulation of any point along the acoustic pathway. Generally, it produces a sharp tone accompanied by hearing impairment. Currently, no widely used standard protocol for treatment of this condition exists, and vascular microthrombotic factors are considered as the main determinants. Prompted by such observations, we implemented a protocol using an anticoagulant, sodium enoxaparin. It is a kind of heparin with a low molecular weight and is endowed with antithrombotic activity. We studied 40 patients (ages 20-65 years) who had been experiencing tinnitus for at least 2 months. We divided patients into two groups: To the first group, enoxaparin was administered for 10 days; the patients in the second group were treated with traditional therapy (corticosteroids, vasoactive agents, multivitamins, and anticoagulants). At the beginning and at the end of the therapy period, the patients were evaluated by instrumental examinations. All patients treated with anticoagulant therapy have shown an evident abatement of their tinnitus symptom. No patient experienced side effects from this treatment. The results indicate that administration of sodium enoxaparin is an excellent mode of therapy for patients with tinnitus.
Purpose Single‐sided 1 H‐NMR is proposed for the estimation of morphological parameters of trabecular bone, and potentially the detection of pathophysiological alterations of bone structure. In this study, a new methodology was used to estimate such parameters without using an external reference signal, and to study intratrabecular and intertrabecular porosities, with a view to eventually scanning patients. Methods Animal trabecular bone samples were analyzed by a single‐sided device. The Carr‐Purcell‐Meiboom‐Gill sequence of 1 H nuclei of fluids, including marrow, confined inside the bone, was analyzed by quasi‐continuous T 2 distributions and separated into two 1 H pools: short and long T 2 components. The NMR parameters were estimated using models of trabecular bone structure, and compared with the corresponding micro‐CT. Results Without any further assumptions, the internal reference parameter (short T 2 signal intensity fraction) enabled prediction of the micro‐CT parameters BV/TV (volume of the trabeculae/total sample volume) and BS/TV (external surface of the trabeculae/total sample volume) with linear correlation coefficient >0.80. The assignment of the two pools to intratrabecular and intertrabecular components yielded an estimate of average intratrabecular porosity (33 ± 5)%. Using the proposed models, the NMR‐estimated BV/TV and BS/TV were found to be linearly related to the corresponding micro‐CT values with high correlation (>0.90 for BV/TV; >0.80 for BS/TV) and agreement coefficients. Conclusion Low‐field, low‐cost portable devices that rely on intrinsic magnetic field gradients and do not use ionizing radiation are viable tools for in vitro preclinical studies of pathophysiological structural alterations of trabecular bone.
Purpose: To develop and validate a method for B0 mapping for knee imaging using the quantitative Double-Echo in Steady-State (qDESS) exploiting the phase difference (∆θ) between the two echoes acquired. Contrary to a standard two-gradient echo (2-GRE) method, the phase accumulation in qDESS depends only on the first echo time. Methods: Bloch simulations were applied to investigate the robustness to noise of the proposed methodology and all imaging studies were validated with phantoms and in vivo simultaneous bilateral knee acquisitions. Two phantoms and 5 healthy subjects were scanned using qDESS, water saturation shift referencing (WASSR), and multi GRE sequences. ∆B0 maps were calculated with the qDESS and the 2-GRE methods and compared against those obtained with WASSR. The comparison was quantitatively assessed by exploiting pixel-wise difference maps, Bland-Altman (BA) analysis, and Lin’s concordance coefficient (ρc). For in-vivo subjects, the comparison was assessed in cartilage using average values in 6 sub-regions. Results: The proposed method for measuring B0 inhomogeneities in phantom and in-vivo scans from a qDESS acquisition provided ∆B0 maps that were in good agreement with those obtained using WASSR. ∆B0 Lin’s coefficients were greater than or equal to 0.98 and 0.90 in phantoms and in vivo, respectively. The agreement between qDESS and WASSR was comparable to that of a standard 2-GRE method. Conclusion: The proposed method may allow B0 correction for qDESS T2 mapping using an inherently co-registered ∆B0 map without requiring an additional B0 measurement sequence. More generally, the method may help shorten knee imaging protocols that require an auxiliary ∆B0 map by exploiting a qDESS acquisition that also provides T2 measurements and high-quality morphological imaging. Conclusion: The proposed method may allow B0 correction for qDESS T2 mapping using an inherently co-registered ∆B0 map without requiring an additional B0 measurement sequence. More generally, the method may help shorten knee imaging protocols that require an auxiliary ∆B0 map by exploiting a qDESS acquisition that also provides T2 measurements and high-quality morphological imaging. This repository contains the data for reproducing the results reported in the paper. For the in-vivo data, python scripts are provided to perform the data analysis described in the paper. The data are provided in NIFTI format. Please cite the original paper (10.1002/mrm.29465) and this repository if you use any of the data or code contained here.
The HTA Programme was set up in 1993.Its role is to ensure that high-quality research information on the costs, effectiveness and broader impact of health technologies is produced in the most efficient way for those who use, manage and provide care in the NHS.'Health technologies' are broadly defined to include all interventions used to promote health, prevent and treat disease, and improve rehabilitation and long-term care, rather than settings of care.The HTA Programme commissions research only on topics where it has identified key gaps in the evidence needed by the NHS.Suggestions for topics are actively sought
The aim of our study was to analyze factors such as noise, chemical drugs, industrial solvents and radiotherapy, which can cause cochlear lesions with progressive sensorineural hearing loss. Although an acute overstimulation by acoustic energy may induce an irreversible hearing loss, in most cases the noise-induced deafness is related to the duration of the exposure and to the level of the acoustic stimulation. A permanent hearing deficit occurs when the acoustic level exceeds 85 dBs. Also several classes of drugs are described as having ototoxic potential: aminoglycoside antibiotics, loop diuretics, antimalarial drugs such as quinine, salicylates, some chemotherapeutic antineoplastic agents. Their potential ototoxic effect seems to be related not only to the molecule, but also to individual predisposition, dose and route of administration. Regarding the benzene derivatives, there is a relationship between their ototoxicity and factors such as duration of exposure and concentration in the local environment. Finally, radiotherapy to areas near the temporal bone may produce a degenerative insult to the vascular stria and the hair cell causing a progressive sensorineural hearing loss.
The Osteoarthritis Initiative was a longitudinal study of osteoarthritis that prospectively collected a trove of imaging data including Multi-Echo Spin-Echo (MESE) data for cartilage T2 relaxation time assessment in one knee. While this data remains underutilized, several analyses have been performed over the past years to assess T2 sensitivity to OA exploiting the OAI dataset. However, fitting procedures to compute T2 maps from the MESE data in the OAI largely rely on mono-exponential modelling, which is inherently sub-optimal as it does not account for stimulated echoes produced by RF slice-profile and B1 inhomogeneities and it often fails to account for low SNR in longer TEs. To mitigate errors, a common practice is to drop the first echo and fit the remaining 6 echoes at the expense of discarding information and degrading SNR efficiency. T2 fitting of MESE data using Extended phase graph (EPG) modelling, whether based on nonlinear least square (NLSQ) dictionary matching (DM) or deep learning (DL), can account for stimulated echoes, and can potentially provide more accurate and robust fitting for T2 mapping in the OAI. This work proposes to 1) set up three EPG fitting approaches for T2 mapping in the OAI dataset (NLSQ-based, DM-based and DL-based), 2) assess methods for their performance in accuracy and robustness to noise using both simulations and in-vivo data, and 3) compare them against standard fitting methods based on mono-exponential methods. MESE simulations were performed in Matlab (R2022b) using the EPG formalism considering the sequence parameters of OAI data. Hanning-windowed Sinc pulses were used for slice-profile simulations. Three EPG-based fitting methods and three exponential (EXP)-based methods used in prior OAI literature were considered and are summarized in Figure 1. To investigate fitting accuracy and repeatability robustness to noise experiments with simulations as well as using in-vivo data from OAI database were performed. 2000 MESE signals were simulated with T2 ranging from 20 to 80 ms and B1 ranging from 0.9 to 1.1. Each method was used to fit T2 values after adding increasing levels of Gaussian noise. For each SNR, the procedure was repeated 10 times with re-sampling of noise. Accuracy was assessed using the mean percentage error (MPE) and mean absolute percentage error (MAPE), while repeatability was assessed with coefficient of variation (CV). MESE data from 5 subjects in the OAI database (1 in each KLG) were corrupted by injecting Gaussian noise to the MESE images twice with increasing variance. Method repeatability was assessed through Bland-Altman (BA) analysis. To assess agreement among fitting methods and how this affected inference of the presence of OA, 50 subjects were randomly selected from the OAI dataset: 10 subjects (5F & 5M) per KLG (0,1,2,3,4). Patellar (P) and Tibiofemoral (TF) cartilage T2 maps were computed pixel-wise with all the described fitting methods. Mean T2 was computed in 7 ROIs (P, MT, LT, central and posterior regions for the MF and LF) extracted using automatic segmentation of DESS images registered to MESE images. BA analysis was used to asses pair-wise agreement in mean T2 values using Limits of Agreement (LOA) and mean bias. The Lin's concordance coefficient (ρc) and CV were also used as metrics of agreement. A logistic regression model was then performed using OA presence (KLG≥2) as a dependent variable, T2 as independent variable and body mass index as covariate in the MT and the central MF regions. MPE, and CV for different fitting methods from the simulation experiment are reported in Fig. 2 (top panel) as a function of SNR. The EPG methods outperformed the exponential-based methods in terms of accuracy at all SNR levels. The EPG-DL approach had the best overall performance in terms of accuracy and repeatability. In-vivo analysis of LOA and CV as function of SNR (Fig. 2, bottom panel) showed that the EPG-based methods had higher repeatability than EXP-based procedures. The EPG-DL approach also had the best overall performance in in vivo data. T2 pair-wise method comparison in-vivo (Fig. 3) showed that overall, the EPG-based methods had higher inter-method agreement (- 0.1 ms < Bias < 0.05 ms, 0.2 < LOA < 1.13 ms, ρc ∼ 0.99) compared to exponential-based methods (-0.7 ms < Bias < 2 ms, 3.2 ms < LOA < 5.3 ms, 0.86 < ρc < 0.94). Poor agreement was found between EPG-based and exponential-based methods (0.34 < ρc < 0.44, Bias ∼ 10 ms and LOA ∼ 4 ms). With reference to Tab. 1, using the EPG-based methods resulted in higher T2-associated OA odd ratios than EXP-based methods in the MT region (EPG OR ∼ 1.19, 1.13 < EXP OR < 1.18). EPG-based T2 relaxation time fitting methods resulted in more accurate and repeatable T2 estimation than EXP-based approaches in simulations. Preliminary in-vivo experiments also suggest higher robustness to noise of EPG methods compared to EXP-based methods. Furthermore, the EPG-methods showed high inter-method agreement. The lower T2 inter-method agreement of EXP-based approaches greatly affected inference of OA severity. Despite the limited sample size, these results suggest that EPG-based methods to compute T2 maps in the OAI may result in low method-dependent variability. Among the EPG-based methods, the DL approach showed the highest repeatability. The high repeatability of EPG-DL paired with its computational efficiency may allow better exploitation of T2 information in the OAI dataset, especially when longitudinal analysis is involved. We plan to use the EPG-DL approach to compute T2 maps of the entire OAI dataset and make it publicly available for researchers to use it.
Nuclear Magnetic Resonance (NMR) has been a powerful and widespread tool since its birth thanks to its flexibility in assessing properties of physical systems without being invasive and without using ionizing radiations. Although applications of NMR for medical purposes have rapidly developed since the introduction of MR imaging (MRI), most of the clinical protocols retrieve qualitative information about biological tissues. Being able to retrieve also quantitative information with NMR may be beneficial to identify biomarkers for understanding and describing the pathophysiology of complex diseases in many tissues. However, established quantitative MRI (qMRI) methods require long scan times that not only can represent more exposure to image artifacts and more discomfort for the patient, but they also increase the costs of MRI protocols.
To improve the clinical feasibility of quantitative NMR, one can focus on optimizing qMRI protocols to increase data acquisition efficiency, i.e. minimizing the acquisition times and maximising the number of retrieved information. Alternatively, one can focus on the application of low-cost, portable and low maintenance NMR devices in the medical field, such as single-sided devices.
This Ph.D thesis presents studies that aim to advance the role of quantitative NMR in medicine using the two directions stated above.
The first part of the thesis proposes a deep learning approach based on deep Fully Connected Networks (NN), for pixel-wise MR parameter prediction task in Magnetic Resonance Fingerprinting (MRF) as a solution to overcome the curse of dimensionality affecting the gold standard dictionary approach.
The second part proposes a methodology to assess the trabecular bone-volume-to-total-volume (BV/TV) ratio using single-side NMR by means of NMR relaxometry measurements. Nowadays there are not well-established methodologies to assess trabecular BV/TV that are suitable for wide screening campaigns of the population at risk of bone fractures related to diseases such as osteoporosis.
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