Acquisition Of Maps Research Articles

High dynamic range mapping for the evaluation of parallel transmit arrays.

Demonstration of a high dynamic-range and high SNR method for acquiring absolute maps from a combination of gradient echo and actual-flip-angle measurements that is especially useful during the construction of parallel-transmit arrays. Low flip angle gradient echo images, acquired when transmitting with each channel individually, are used to compute relative maps. Instead of computing these in a conventional manner, the equivalence of the problem to the ESPIRiT parallel image reconstruction method is used to compute maps with a higher SNR. Absolute maps are generated by calibration against a single actual flip-angle acquisition when transmitting on all channels simultaneously. Depending on the number of receiver channels and the location of the receive elements with respect to the subject being investigated, moderate to high gains in the SNR of the acquired maps can be achieved. The proposed method is especially suited for the acquisition of maps during the construction of transceiver arrays. Compared to the original method, maps with higher SNR can be computed without the need for additional measurements, and maps can also be generated using previously acquired data. Furthermore, easy adoption and fast estimation of receiver channels is possible because of existing highly optimized open-source implementations of ESPIRiT, such as in the BART toolbox.

An Indoor-Outdoor Layered HD Map Construction for Unmanned Ground Vehicles

Abstract. High-Definition Maps (HD Maps) are lane-level 3-dimensional road network models that ensure the safe operation of autonomous vehicles and drive the continuous advancement of autonomous driving technology to higher levels. However, HD Maps currently face challenges regarding limited coverage and description of indoor environments (e.g. underground parking), as well as the lack of uniformity between indoor and outdoor map formats. Therefore, this paper proposes a Layered HD Map model for both indoor and outdoor environments. The map model consists of 6 layers, allowing effective representation of indoor and outdoor environments, as well as transitional areas. The paper also establishes an Unmanned Ground Vehicle (UGV) to collect and update map data using LiDAR (Light Detection and Ranging) SLAM (Simultaneous Localization and Mapping) and autonomous exploration technology, aiming to enhance the efficiency and automation of HD Map acquisition. In order to verify the validity of the proposed map model, this paper conducted a navigation experiment in a double decker parking lot containing entrances and exits. The results of the experiments demonstrate that the Layered HD Map generated through autonomous LiDAR SLAM can effectively describe the indoor and outdoor environments, and enable successful navigation of UGVs.

Development of a proton CT imaging system using scintillator-based range detection.

The accuracy of proton therapy and preclinical proton irradiation experiments is susceptible to proton range uncertainties, which partly stem from the inaccurate conversion between CT numbers and relative stopping power (RSP). Proton computed tomography (PCT) can reduce these uncertainties by directly acquiring RSP maps. This study aims to develop a novel PCT imaging system based on scintillator-based proton range detection for accurate RSP reconstruction. The proposed PCT system consists of a pencil-beam brass collimator with a 1mm aperture, an object stage capable of translation and 360° rotation, a plastic scintillator for dose-to-light conversion, and a complementary metal oxide semiconductor (CMOS) camera for light distribution acquisition. A calibration procedure based on Monte Carlo (MC) simulation was implemented to convert the obtained light ranges into water equivalent ranges. The water equivalent path lengths (WEPLs) of the imaged object were determined by calculating the differences in proton ranges obtained with and without the object in the beam path. To validate the WEPL calculation, measurements of WEPLs for eight tissue-equivalent inserts were conducted. PCT imaging was performed on a custom-designed phantom and a mouse, utilizing both 60 and 360 projections. The filtered back projection (FBP) algorithm was employed to reconstruct the RSP from WEPLs. Image quality was assessed based on the reconstructed RSP maps and compared to reference and simulation-based reconstructions. The differences between the calibrated and reference ranges of 110-150 MeV proton beams were within 0.18mm. The WEPLs of eight tissue-equivalent inserts were measured with accuracies better than 1%. Phantom experiments exhibited good agreement with reference and simulation-based reconstructions, demonstrating average RSP errors of 1.26%, 1.38%, and 0.38% for images reconstructed with 60 projections, 60 projections after penalized weighted least-squares algorithm denoising, and 360 projections, respectively. Mouse experiments provided clear observations of mouse contours and major tissue types. MC simulation estimated an imaging dose of 3.44 cGy for decent RSP reconstruction. The proposed PCT imaging system enables RSP map acquisition with high accuracy and has the potential to improve dose calculation accuracy in proton therapy and preclinical proton irradiation experiments.

Dogs with a vocabulary of object labels retain them for at least 2 years.

Long-term memory of words has a crucial role in the developing abilities of young children to acquire language. In dogs, the ability to learn object labels is present in only a small group of uniquely gifted word learner (GWL) dogs. As they are very rare, little is known about the mechanisms through which they acquire such large vocabularies. In the current study, we tested the ability of five GWL dogs to retrieve 12 labelled objects 2 years after the object-label mapping acquisition. The dogs proved to remember the labels of between three and nine objects. The results shed light on the process by which GWL dogs acquire an exceptionally large vocabulary of object names. As memory plays a crucial role in language development, these dogs provide a unique opportunity to study label retention in a non-linguistic species.

Peri-Tumoural Lipid Composition and Hypoxia for Early Immune Response to Neoadjuvant Chemotherapy in Breast Cancer.

The deregulation of monounsaturated, polyunsaturated, and saturated fatty acids (MUFAs, PUFAs, SFAs) from de novo synthesis and hypoxia are central metabolic features of breast tumour. Early response markers for neoadjuvant chemotherapy (NACT) are critical for stratified treatment for patients with breast cancer, and restoration of lipid metabolism and normoxia might precede observable structural change. In this study, we hypothesised that peri-tumoural lipid composition and hypoxia might be predictive and early response markers in patients with breast cancer undergoing NACT. Female patients with breast cancer were scanned on a 3T clinical MRI scanner at baseline and Cycle1, with acquisition of lipid composition maps of MUFAs, PUFAs, and SFAs, and hypoxia maps of effective transverse relaxation rate R2*. The percentage change in lipid composition and hypoxia at Cycle1 was calculated with reference to baseline. Tumour-associated macrophages were analysed based on immunostaining of CD163 from biopsy and resection, with the percentage change in the resected tumour calculated across the entire NACT. We found no significant difference in lipid composition and R2* between good and poor responders at baseline and Cycle1; however, the correlation between the percentage change in MUFAs and PUFAs against CD163 suggested the modulation in lipids with altered immune response might support the development of targeted therapies.

Spatial coding strategy for dual-frequency phase-shifting profilometry

Dual-frequency fringe projection techniques have been broadly utilized for three-dimensional (3D) shape recovery. However, a pervasive challenge across these methodologies lies in the precise implementation of high-speed measurements. This paper explores a spatial coding strategy designed for the dual-frequency phase unwrapping method to tackle this. The strategy mandates the utilization of only four patterns, encapsulating the phase information of both high and low frequencies. The codewords are strategically embedded within the low-frequency phase, facilitating the acquisition of an accurate absolute phase map. A robust decoding algorithm engineered to ensure dependable phase unwrapping, particularly in scenarios characterized by a substantial number of high-frequency cycles. The proposed method exhibits superior noise immunity and enhances accuracy when compared with the previous dual-frequency phase-shifting methodology. Simulations and experiments demonstrate the robustness and efficiency of the proposed strategy.

Application of artificial bee colony algorithm based on homogenization mapping and collaborative acquisition control in network communication security.

In order to optimize the spectrum allocation strategy of existing wireless communication networks and improve information transmission efficiency and data transmission security, this study uses the independent correlation characteristics of chaotic time series to simulate the collection and control strategy of bees, and proposes an artificial bee colony algorithm based on uniform mapping and collaborative collection control. Furthermore, it proposes an artificial bee colony algorithm based on uniform mapping and collaborative collection and control. The method begins by establishing a composite system of uniformly distributed Chebyshev maps. In the neighborhood intervals where the nectar sources are firmly connected and relatively independent, the algorithm then conducts a chaotic traversal search. The research results demonstrated the great performance of the suggested algorithm in each test function as well as the positive effects of the optimization search. The network throughput rate was over 300 kbps, the quantity of security service eavesdropping was below 0.1, and the spectrum utilization rate of the algorithm-based allocation method could be enhanced to 0.8 at the most. Overall, the performance of the proposed algorithm outperformed the comparison algorithm, with high optimization accuracy and a significant amount of optimization. This is favorable for the efficient use of spectrum resources and the secure transmission of communication data, and it encourages the development of spectrum allocation technology in wireless communication networks.

Differential confocal effective measurement region extraction method based on dual measurement

Abstract Aiming at the problem that the existing differential confocal measurement (DCM) method lacks the ability to decouple the differential signals from over-range the depth data, which in turn leads to measurement errors, this study proposes a differential confocal effective measurement region extraction method based on dual measurement (D-DCM). The first measurement is a double blur depth measurement, which is a coarse measurement, and the initial acquisition of the depth map is realized by applying a known Gaussian kernel blurring to the focal plane image and calculating the edge gradient ratios between the original image and the blurred image. This depth map is used to determine whether the depth of the measured sample in the field of view is within the differential confocal range and to segment it. The second measurement is a DCM, which is a fine measurement. The effective measurement area of the segmented image is second measured with high precision depth measurement. It is shown by single and multiple step heights experiments that the proposed D-DCM method can effectively solve the problem of decoupling the differential signal from the axial depth in differential confocal.

Accelerated 3D multi-echo spin-echo sequence with a subspace constrained reconstruction for whole mouse brain mapping.

To accelerate whole-brain quantitative mapping in preclinical imaging setting. A three-dimensional (3D) multi-echo spin echo sequence was highly undersampled with a variable density Poisson distribution to reduce the acquisition time. Advanced iterative reconstruction based on linear subspace constraints was employed to recover high-quality raw images. Different subspaces, generated using exponential or extended-phase graph (EPG) simulations or from low-resolution calibration images, were compared. The subspace dimension was investigated in terms of precision. The method was validated on a phantom containing a wide range of and was then applied to monitor metastasis growth in the mouse brain at 4.7T. Image quality and estimation were assessed for 3 acceleration factors (6/8/10). The EPG-based dictionary gave robust estimations of a large range of . A subspace dimension of 6 was the best compromise between precision and image quality. Combining the subspace constrained reconstruction with a highly undersampled dataset enabled the acquisition of whole-brain maps, the detection and the monitoring of metastasis growth of less than 500 . Subspace-based reconstruction is suitable for 3D mapping. This method can be used to reach an acceleration factor up to 8, corresponding to an acquisition time of 25 min for an isotropic 3D acquisition of 156 m on the mouse brain, used here for monitoring metastases growth.

Two for One-Combined Morphologic and Quantitative Knee Joint MRI Using a Versatile Turbo Spin-Echo Platform.

Quantitative MRI techniques such as T2 and T1ρ mapping are beneficial in evaluating knee joint pathologies; however, long acquisition times limit their clinical adoption. MIXTURE (Multi-Interleaved X-prepared Turbo Spin-Echo with IntUitive RElaxometry) provides a versatile turbo spin-echo (TSE) platform for simultaneous morphologic and quantitative joint imaging. Two MIXTURE sequences were designed along clinical requirements: "MIX1", combining proton density (PD)-weighted fat-saturated (FS) images and T2 mapping (acquisition time: 4:59 min), and "MIX2", combining T1-weighted images and T1ρ mapping (6:38 min). MIXTURE sequences and their reference 2D and 3D TSE counterparts were acquired from ten human cadaveric knee joints at 3.0 T. Contrast, contrast-to-noise ratios, and coefficients of variation were comparatively evaluated using parametric tests. Clinical radiologists (n = 3) assessed diagnostic quality as a function of sequence and anatomic structure using five-point Likert scales and ordinal regression, with a significance level of α = 0.01. MIX1 and MIX2 had at least equal diagnostic quality compared to reference sequences of the same image weighting. Contrast, contrast-to-noise ratios, and coefficients of variation were largely similar for the PD-weighted FS and T1-weighted images. In clinically feasible scan times, MIXTURE sequences yield morphologic, TSE-based images of diagnostic quality and quantitative parameter maps with additional insights on soft tissue composition and ultrastructure.

Phase-sensitive deep reconstruction method for rapid multiparametric MR fingerprinting and quantitative susceptibility mapping in the brain

IntroductionThis study explores the potential of Magnetic Resonance Fingerprinting (MRF) with a novel Phase-Sensitivity Deep Reconstruction Network (PS-DRONE) for simultaneous quantification of T1, T2, Proton Density, B1+, phase and quantitative susceptibility mapping (QSM). MethodsData were acquired at 3 T in vitro and in vivo using an optimized EPI-based MRF sequence. Phantom experiments were conducted using a standardized phantom for T1 and T2 maps and a custom-made agar-based gadolinium phantom for B1 and QSM maps. In vivo experiments included five healthy volunteers and one patient diagnosed with brain metastasis. PSDRONE maps were compared to reference maps obtained through standard imaging sequences. ResultsTotal scan time was 2 min for 32 slices and a resolution of [1 mm, 1 mm, 4.5 mm]. The reconstruction of T1, T2, Proton Density, B1+ and phase maps were reconstructed within 1 s. In the phantoms, PS-DRONE analysis presented accurate and strongly correlated T1 and T2 maps (r = 0.99) compared to the reference maps. B1 maps from PS-DRONE showed slightly higher values, though still correlated (r = 0.6) with the reference. QSM values showed a small bias but were strongly correlated (r = 0.99) with reference data. In the in vivo analysis, PS-DRONE-derived T1 and T2 values for gray and white matter matched reference values in healthy volunteers. PS-DRONE B1 and QSM maps showed strong correlations with reference values. ConclusionThe PS-DRONE network enables concurrent acquisition of T1, T2, PD, B1+, phase and QSM maps, within 2 min of acquisition time and 1 s of reconstruction time.

UV–VIS imaging-based investigation of API concentration fluctuation caused by the sticking behaviour of pharmaceutical powder blends

Surface powder sticking in pharmaceutical mixing vessels poses a risk to the uniformity and quality of drug formulations. This study explores methods for evaluating the amount of pharmaceutical powder mixtures adhering to the metallic surfaces. Binary powder blends consisting of amlodipine and microcrystalline cellulose (MCC) were used to investigate the effect of the mixing order on the adherence to the vessel wall. Elevated API concentrations were measured on the wall and within the dislodged material from the surface, regardless of the mixing order of the components. UV imaging was used to determine the particle size and the distribution of the API on the metallic surface. The results were compared to chemical maps obtained by Raman chemical imaging. The combination of UV and VIS imaging enabled the rapid acquisition of chemical maps, covering a substantially large area representative of the analysed sample. UV imaging was also applied in tablet inspection to detect tablets that fail to meet the content uniformity criteria. The results present powder adherence as a possible source of poor content uniformity, highlighting the need for 100% inspection of pharmaceutical products to ensure product quality and safety.

Methodology of Spatial Data Acquisition and Development of High-Definition Map for Autonomous Vehicles – Case Study from Wrocław, Poland

Autonomous drive systems are a dynamically developed sector of the automotive industry. The key problem in such technological solutions is to provide a reliable navigation system, which is typically based on high-definition (HD) maps supporting the identification of the position of a maneuvering vehicle. HD maps should include possibly up-to-date and detailed information on traffic lanes and on the traffic rules and regulations on such lanes. An effective development of an HD map should be based on the geodetic measurement methods, which ensure efficient and accurate acquisition of spatial data. This article presents the results of an experiment consisting in the manipulation of data obtained with the use of the mobile laser scanning method and further in employing this data in the development of an HD map in an open-source environment. The applied measurement technology and the processing method allowed data of high resolution (frequently above 1000 points per m2) and of high accuracy (3D accuracy down to less than 5 cm). The obtained data were processed in the Vector Map Builder environment (which is accessible from the level of an internet browser) and the final product - HD map was created in the Lanelet2 open-source environment. The above-described experiments allowed two main conclusions. Most importantly, they demonstrate the importance of planning and performing in-field mobile laser scanning measurements. They also point to the important role of the human analyst who needs to manually vectorize the key elements of road infrastructure and to define traffic rules.

Improved diagnostic confidence and tumor type prediction in adult-type diffuse glioma by multimodal imaging including DCE perfusion and diffusion kurtosis mapping – A standardized multicenter study

Background and purposeTo evaluate the feasibility of a multimodal approach involving dynamic contrast-enhanced (DCE) perfusion imaging and diffusion kurtosis imaging (DKI) in the preoperative imaging of brain tumors in a multicenter setting, and to evaluate the effect on diagnostic confidence and accuracy for tumor grade and type prediction. Materials and MethodsOne hundred and thirty-three patients with brain tumors were imaged in six hospitals with a standardized multimodal protocol. Standard imaging and six parameter maps derived from DCE and DKI sequences were reviewed off-site by two independent readers. Image quality and diagnostic confidence were evaluated in qualitative analyses. Quantitative analyses were performed to assess diagnostic accuracy and the performance of DKI and DCE parameters for tumor grade differentiation and molecular tumor type determination. ResultsStandardized acquisition of DCE and DKI maps was feasible with excellent image quality. Diagnostic confidence was significantly improved from 85 % to 96 % (p = 0.0005) by additional review of the DCE and DKI maps. The combination of mean kurtosis and CBV was particularly advantageous for differentiating low-grade and high-grade glioma, oligodendroglial vs. astrocytic, and IDH1/2 wild type vs. mutated tumors. ConclusionA multimodal imaging approach with DCE and DKI improves diagnostic confidence and yields higher diagnostic accuracy for predicting tumor grade and type in adult-type glioma.

SLAMB&MAI: a comprehensive methodology for SLAM benchmark and map accuracy improvement

AbstractSLAM Benchmark plays a pivotal role in the field by providing a common ground for performance evaluation. In this paper, a novel methodology of simultaneous localization and mapping benchmark and map accuracy improvement (SLAMB&MAI) is introduced. It can objectively evaluate errors of localization and mapping, and further improve map accuracy by utilizing evaluation results as feedback. The proposed benchmark transforms all elements into a global frame and measures the errors between them. The comprehensiveness consists in the benchmark of both localization and mapping, and the objectivity consists in the consideration of the correlation between localization and mapping by the preservation of the original pose relations between all reference frames. The map accuracy improvement is realized by first obtaining the optimization that minimizes the errors between the estimated trajectory and ground truth trajectory and then applying it to the estimated map. The experimental results showed that the map accuracy can be improved by an average of 15%. The optimization that yields minimal localization errors is obtained by the proposed Centre Point Registration-Iterative Closest Point (CPR-ICP). This proposed Iterative Closest Point (ICP) variant pre-aligns two point clouds by their centroids and least square planes and then uses traditional ICP to minimize the error between them. The experimental results showed that CPR-ICP outperformed traditional ICP, especially in cases involving large-scale environments. To the extent of our knowledge, this is the first work that can not only objectively benchmark both localization and mapping but also revise the estimated map and increase its accuracy, which provides insights into the acquisition of ground truth map and robot navigation.

Differentiating gallbladder cancer from polyps using non-enhanced magnetic resonance imaging.

This retrospective cohort study assessed the efficiency of non-enhanced magnetic resonance imaging (MRI) for differentiating gallbladder cancer (GBC) from gallbladder polyps (GBPs) measuring ≥ 10 mm. Patients diagnosed with GBCs or GBPs ≥ 10 mm and GBC ≤ T2 stage were eligible for inclusion. Two independent blinded readers assessed the continuity of the mucosal and muscular layers (CMML; present or absent) and normalised signal intensity ratio (NIR) on the apparent diffusion coefficient map (NIR-ADC), T1-weighted image (NIR-T1WI), and T2-weighted half-Fourier acquisition single-shot turbo spin-echo image. Univariate and multivariate logistic regression analyses and interobserver agreement analyses were performed to detect predictive variables differentiating GBCs from GBPs. Receiver operating characteristic (ROC) analysis was performed to evaluate diagnostic performance. A reproducibility test was performed to verify the predictive variables. Multivariate analysis showed significant differences in CMML, NIR-ADC, and NIR-T1WI (p < 0.001). The positive predictive value (PPV) and specificity of the absence of CMML were approximately 100%. The CMML showed the best specificity, accuracy, and PPV in the reproducibility study. The sensitivity of CMML alone was approximately 50%, whereas it increased to approximately 70% when combined with NIR-ADC. The diagnostic performance of the combination, including sensitivity, was almost like that of tumour size. The combined tumour size and CMML assessment showed higher diagnostic performance than tumour size alone. The absence of CMML and NIR-ADC ≤ 1.86 helped in differentiating GBCs from GBPs. Evaluation of the absence of CMML and measurement of tumour size could better aid in determining between the two than measurement of tumour size alone.

Evaluation and Prediction of Post-Hepatectomy Liver Failure Using Imaging Techniques: Value of Gadoxetic Acid-Enhanced Magnetic Resonance Imaging.

Despite improvements in operative techniques and perioperative care, post-hepatectomy liver failure (PHLF) remains the most serious cause of morbidity and mortality after surgery, and several risk factors have been identified to predict PHLF. Although volumetric assessment using imaging contributes to surgical simulation by estimating the function of future liver remnants in predicting PHLF, liver function is assumed to be homogeneous throughout the liver. The combination of volumetric and functional analyses may be more useful for an accurate evaluation of liver function and prediction of PHLF than only volumetric analysis. Gadoxetic acid is a hepatocyte-specific magnetic resonance (MR) contrast agent that is taken up by hepatocytes via the OATP1 transporter after intravenous administration. Gadoxetic acid-enhanced MR imaging (MRI) offers information regarding both global and regional functions, leading to a more precise evaluation even in cases with heterogeneous liver function. Various indices, including signal intensity-based methods and MR relaxometry, have been proposed for the estimation of liver function and prediction of PHLF using gadoxetic acid-enhanced MRI. Recent developments in MR techniques, including high-resolution hepatobiliary phase images using deep learning image reconstruction and whole-liver T1 map acquisition, have enabled a more detailed and accurate estimation of liver function in gadoxetic acid-enhanced MRI.

Hot deformation behavior, superplasticity and microstructure evolution of a new hot isostatic pressed nickel-based superalloy

The new hot isostatically pressed (HIP) superalloy has demonstrated remarkable superplastic characteristics, as evidenced by studying the compression and tensile deformation behavior. To identify the superplastic deformation zone, the instability regions at various strain variables were overlaid onto the strain rate sensitivity index (m) distribution map at a strain of 0.6, resulting in the acquisition of a new hot working map. The tensile test results showed that under the conditions of 1080 °C-10−2.5 s−1 (0.35 < m < 0.43) and 1030 °C-10−3 s−1 (0.66 < m < 0.74) which located in the superplastic deformation zone in the new hot working map, the new HIPed superalloy exhibited superplasticity, and the elongation was 395 % and 410 %, respectively. Considering the hot working map and the microstructure evolution, the suitable hot working window was further optimized to be 1030–1080 °C and 0.001–0.005 s−1. At high strain rate and low temperature conditions, continuous dynamic recrystallization (CDRX) was the primary mechanism for dynamic recrystallization (DRX), while with the gradual decrease of strain rate, discontinuous dynamic recrystallization (DDRX) tended to occur and dominate the process. DDRX dominated under high temperature deformation condition.

Low voltage and low wave speed are rarely present outside the left atrium-pulmonary veins junction in paroxysmal atrial fibrillation but frequently present in persistent forms

Abstract Background and aim Multielectrode high-density catheters have enabled acquisition of comprehensive and dense maps of electrogram’s amplitude and timing. However, automated activation and voltage mapping are flawed by catheter orientation in relation to the wavefront activation. Omnipolar mapping technology (OT) uses both unipolar and bipolar signals to obtain OT signals and increases the accuracy of automatic point acquisition allowing for a high- density map in a quick and efficient way. The aim of this study was to automatically assess with OT, the left atrium (LA) voltage and wave speed propagation map in sinus rhythm (SR) according to the type of atrial fibrillation (AF). Methods We studied 14 consecutive patients referred for ablation of AF, either paroxysmal (PAF) (n=6) or persistent (Pers-AF) (n=8) using catheters with OT. Patients with Pers-AF were cardioverted, and a SR map was obtained before ablation in all patients and voltage and propagation wave speed maps were obtained. The cut-off for low voltage areas (LVAs) was less than 0.1 mV and for low wave speed (LWS) was less than 0.4 mm/ms. Results were compared according to the type of AF. Results The results are depicted in the Table. The median duration of AF in Pers-AF was 18 (5-24) months. Patients with Pers-AF had larger LA volumes and displayed presence of LVAs and LWS areas in 100% of cases in comparison with 17% and 33% of cases respectively for PAF patients (p=0.003 and p=0.015). Also, the total LVAs and LWS areas in cm2 were significantly higher, (p=0.001 and p=0.005)). The LVAs and the LWS areas were more frequently located outside the PV-LA junction in Pers-AF than in PAF, respectively 75% vs 0% and 88% vs 0%, p=0.010 and p=0.005 (Figure). Conclusions Patients with PAF never presented LVAs or LWS outside the PV-LA junction. On the contrary, patients with Pers-AF had frequently anatomical and electrophysiological abnormalities in the LA body. These findings may suggest the need for a wider ablation strategy in Pers-AF.Normal voltage in purple ; LWS in white

Repeatability of Quantitative Knee Cartilage T1, T2, and T1ρ Mapping With 3D-MRI Fingerprinting.

Three-dimensional MR fingerprinting (3D-MRF) techniques have been recently described for simultaneous multiparametric mapping of knee cartilage. However, investigation of repeatability remains limited. To assess the intra-day and inter-day repeatabilities of knee cartilage T1, T2, and T1ρ maps using a 3D-MRF sequence for simultaneous measurement. Prospective. Fourteen healthy subjects (35.4 ± 9.3 years, eight males), scanned on Day 1 and Day 7. 3 T/3D-MRF, T1, T2, and T1ρ maps. The acquisition of 3D-MRF cartilage (simultaneous acquisition of T1, T2, and T1ρ maps) were acquired using a dictionary pattern-matching approach. Conventional cartilage T1, T2, and T1ρ maps were acquired using variable flip angles and a modified 3D-Turbo-Flash sequence with different echo and spin-lock times, respectively, and were fitted using mono-exponential models. Each sequence was acquired on Day 1 and Day 7 with two scans on each day. The mean and SD for cartilage T1, T2, and T1ρ were calculated in five manually segmented regions of interest (ROIs), including lateral femur, lateral tibia, medial femur, medial tibia, and patella cartilages. Intra-subject and inter-subject repeatabilities were assessed using coefficient of variation (CV) and intra-class correlation coefficient (ICC), respectively, on the same day and among different days. Regression and Bland-Altman analysis were performed to compare maps between the conventional and 3D-MRF sequences. The CV in all ROIs was lower than 7.4%, 8.4%, and 7.5% and the ICC was higher than 0.56, 0.51, and 0.52 for cartilage T1, T2, and T1ρ, respectively. The MRF results had a good agreement with the conventional methods with a linear regression slope >0.61 and R2 > 0.59. The 3D-MRF sequence had high intra-subject and inter-subject repeatabilities for simultaneously measuring knee cartilage T1, T2, and T1ρ with good agreement with conventional sequences. 1 TECHNICAL EFFICACY: Stage 1.