Image Sequences Research Articles

Weld Defect Downscaling Recognition for Phased Array Ultrasonic Data Based on Semantic Segmentation

Phased array ultrasonic testing (PAUT) is one of the most advanced ultrasonic inspection methods, providing inspection data in image sequences with increased resolution and coverage, consequently enhancing inspection efficiency. Due to the inherently abstract nature of ultrasound images, the analysis of PAUT weld data continues to rely on the expertise of experienced inspectors, particularly in the context of shipbuilding welds, which exhibit characteristics such as arbitrary lengths, varying thicknesses, and various weld methods, particularly when associated with hybrid laser-arc welding involving higher caps and narrower fill widths. This paper applies a semantic segmentation architecture to PAUT data for hybrid laser-arc welding to segment defects automatically. A downscaling PAUT image dataset incorporating PAUT imaging principles with scan processes is established. The proposed architecture adopts an encoder-decoder architecture and segments defects downscaling, enabling direct localization and sizing defects in long PAUT data. Meanwhile, it handles PAUT image sequences of arbitrary length, eliminating the need for horizontal scale normalization while preserving the integrity of defect shapes. The proposed architecture was validated in the dataset to demonstrate the superiority of the proposed method in locating and sizing defects in PAUT weld data, offering a promising automated solution to a challenge in ultrasonic inspection methodologies.

Super-Resolution Ultrasound Imaging for Monitoring the Therapeutic Efficacy of a Vascular Disrupting Agent in an Animal Model of Breast Cancer.

Evaluate the use of super-resolution ultrasound (SRUS) imaging for the early detection of tumor response to treatment using a vascular-disrupting agent (VDA). A population of 28 female nude athymic mice (Charles River Laboratories) were implanted with human breast cancer cells (MDA-MB-231, ATCC) in the mammary fat pad and allowed to grow. Ultrasound imaging was performed using a Vevo 3100 scanner (FUJIFILM VisualSonics Inc) equipped with the MX250 linear array transducer immediately before and after receiving bolus injections of a microbubble (MB) contrast agent (Definity, Lantheus Medical Imaging) via the tail vein. Following baseline ultrasound imaging, VDA drug (combretastatin A4 phosphate, CA4P, Sigma Aldrich) or control saline was injected via the placed catheter. After 4 or 24 hours, repeat ultrasound imaging along the same tumor cross-section occurred. Direct intratumoral pressure measurements were obtained using a calibrated sensor. All raw ultrasound data were saved for offline processing and SRUS image reconstruction using custom MATLAB software (MathWorks Inc). From a region encompassing the tumor space and the entire postprocessed ultrasound image sequence, time MB count (TMC) curves were generated in addition to traditional SRUS maps reflecting MB enumeration at each pixel location. Peak enhancement (PE) and wash-in rate (WIR) were extracted from these TMC curves. At termination, intratumoral microvessel density (MVD) was quantified using tomato lectin labeling of patent blood vessels. SRUS images exhibited a clear difference between control and treated tumors. While there was no difference in any group parameters at baseline (0 hour, P > .09), both SRUS-derived PE and WIR measurements in tumors treated with VDA exhibited significant decreases by 4 (P = .03 and P = .05, respectively) and 24 hours (P = .02 and P = .01, respectively), but not in control group tumors (P > .22). Similarly, SRUS derived microvascular maps were not different at baseline (P = .81), but measures of vessel density were lower in treated tumors at both 4 and 24 hours (P < .04). An inverse relationship between intratumoral pressure and both PE and WIR parameters were found in control tumors (R2 > .09, P < .03). SRUS imaging is a new modality for assessing tumor response to treatment using a VDA.

Sequence building block for magnetic resonance spectroscopy on Siemens VE-series scanners.

We present a sequence building block (SBB) that embeds magnetic resonance spectroscopy (MRS) into another sequence on the Siemens VE platform without any custom hardware. This enables dynamic studies such as functional MRS (fMRS), dynamic shimming and frequency correction, and acquisition of navigator images for motion correction. The SBB supports nonlocalised spectroscopy (free induction decay), STimulated Echo Acquisition Mode single voxel spectroscopy, and 1D, 2D and 3D phase-encoded chemical shift imaging. It can embed 1H or X-nuclear MRS into a 1H sequence; and 1H-MRS into an X-nuclear sequence. We demonstrate integration into the vendor's gradient-recalled echo sequence. We acquire test data in phantoms with three coils (31P/1H, 13C/1H and 2H/1H) and in two volunteers on a 7-T Terra MRI scanner. Fifteen lines of code are required to insert the SBB into a sequence. Spectra and images are acquired successfully in all cases in phantoms, and in human abdomen and calf muscle. Phantom comparison of signal-to-noise ratio and linewidth showed that the SBB has negligible effects on image and spectral quality, except that it sometimes produces a nuclear Overhauser effect (NOE) signal enhancement for multinuclear applications in line with conventional 1H NOE pulses. Our new SBB embeds MRS into a host imaging or spectroscopy sequence in 15 lines of code. It allows homonuclear and heteronuclear interleaving. The package is available through the standard C2P procedure. We hope this will lower the barrier for entry to studies applying dynamic fMRS and for online motion correction and B0-shim updating.

Validation of a White Light and Fluorescence Augmented Panoramic Endoscopic Imaging System on a Bimodal Bladder Wall Experimental Model

Background: Fluorescence visualization of pathologies, primarily neoplasms in human internal cavities, is one of the most popular forms of diagnostics during endoscopic examination in medical practice. Currently, visualization can be performed in the augmented reality mode, which allows to observe areas of increased fluorescence directly on top of a usual color image. Another no less informative form of endoscopic visualization in the future can be mapping (creating a mosaic) of the acquired image sequence into a single map covering the area under study. The originality of the present contribution lies in the development of a new 3D bimodal experimental bladder model and its validation as an appropriate phantom for testing the combination of bimodal cystoscopy and image mosaicking. Methods: An original 3D real bladder-based phantom (physical model) including cancer-like fluorescent foci was developed and used to validate the combination of (i) a simultaneous white light and fluorescence cystoscopy imager with augmented reality mode and (ii) an image mosaicking algorithm superimposing both information. Results: Simultaneous registration and real-time visualization of a color image as a reference and a black-and-white fluorescence image with an overlay of the two images was made possible. The panoramic image build allowed to precisely visualize the relative location of the five fluorescent foci along the trajectory of the endoscope tip. Conclusions: The method has broad prospects and opportunities for further developments in bimodal endoscopy instrumentation and automatic image mosaicking.

Temporal compressive edge imaging enabled by a lensless diffuser camera

Lensless imagers based on diffusers or encoding masks enable high-dimensional imaging from a single-shot measurement and have been applied in various applications. However, to further extract image information such as edge detection, conventional post-processing filtering operations are needed after the reconstruction of the original object images in the diffuser imaging systems. Here, we present the concept of a temporal compressive edge detection method based on a lensless diffuser camera, which can directly recover a time sequence of edge images of a moving object from a single-shot measurement, without further post-processing steps. Our approach provides higher image quality during edge detection, compared with the “conventional post-processing method.” We demonstrate the effectiveness of this approach by both numerical simulation and experiments. The proof-of-concept approach can be further developed with other image post-processing operations or versatile computer vision assignments toward task-oriented intelligent lensless imaging systems.

A new framework for quantifying alongshore variability of swash motion using fully convolutional networks

Waves running up and down the beach (‘swash’) at the landward edge of the ocean can cause changes to the beach topology, can erode dunes, and can result in inland flooding. Despite the importance of swash, field observations are difficult to obtain in the thin, bubbly, and potentially sediment laden fluid layers. Here, swash excursions along an Atlantic Ocean beach are estimated with a new framework, V-BeachNet, that uses a fully convolutional network to distinguish between sand and the moving edge of the wave in rapid sequences of images. V-BeachNet is trained with 16 randomly selected and manually segmented images of the swash zone, and is used to estimate swash excursions along 200 m of the shoreline by automatically segmenting four 1-h sequences of images that span a range of incident wave conditions. Data from a scanning lidar system are used to validate the swash estimates along a cross-shore transect within the camera field of view. V-BeachNet estimates of swash spectra, significant wave heights, and wave-driven setup (increases in the mean water level) agree with those estimated from the lidar data.

Near-zero fluoroscopy technique for cardiac electronic device implantation: long-term outcomes

Abstract Introduction Radiation hazards are a major concern for both patients and staff. We have previously described a near-zero fluoroscopy technique for cardiac electronic device implantation. In this study, we aimed to investigate the long-term safety of this technique and compare outcomes and procedural metrics with a conventional approach in a larger population. Methods Low-dose fluoroscopy technique. Radiation exposure during fluoroscopy is directly proportional to the time the unit is activated. Typically, the pedal switch is depressed for at least a few seconds per imaging sequence in order to visualize "live" movements of either the leads during their positioning or the needle during a fluoroscopy-guided puncture of the subclavian vein. Our technique consists of setting a low frame rate per second (0.5-3.75fps) and momentarily triggering the foot pedal switch only to obtain screenshots of the position of the leads/needle. Use of live electrograms to assist spatial awareness of lead position (e.g. Atrial, Coronary Sinus, Ventricular signals) acts as an adjunct to guidance. Study design We included consecutive patients undergoing permanent pacemaker (PPM) or cardiac defibrillator (ICD) implant at our center from July 2018 to December 2022 using the near-zero fluoroscopy technique. Procedures were performed by three operators (AC, MD, MF). Cumulative radiation dose was measured using dose-area product (DAP). We assessed procedure success and complication rate during long-term follow-up. We compared the procedural metrics and outcomes with a cohort of patients with PPM or ICD implanted in our centre by senior operators, using a traditional fluoroscopic approach. Propensity score was adopted to match baseline characteristics between the study and control group. Results The total population consisted of 412 patients (74.2±13.9 years, 60.9% male). We included 206 who underwent PPM or ICD implantation using the low-dose fluoroscopy technique, and 206 matched-control. A PPM or ICD was successfully implanted in all patients. Fluoroscopy time and DAP were significantly lower in the low-dose fluoroscopy group, mean 2.3±2.0 seconds versus 258.4±252.1 seconds (P&amp;lt;0.001) and 3.4±3.5 µGym2 versus 29.8±55.4 µGym2 (P&amp;lt;0.001), respectively. Mean procedure time was 49.0±20.8 minutes in the low fluoroscopy group and 65.7±26.8 minutes in the control group (P&amp;lt;0.001). Median frame per second setting was 0.5 in the low-dose cohort. After a mean follow-up of 441±470 days, the rate of complications was identical across groups (2.4%, p = 1.0). Conclusion This near-zero dose fluoroscopy technique is effective and safe, enabling a 10x reduction in radiation exposure during device implant. Modification of traditional implant and imaging techniques can provide material reductions in fluoroscopy dose to even below that for a standard PA chest radiograph.

A novel transcranial MR Guided focused ultrasound method based on the ultrashort echo time skull acoustic model and phase retrieval techniques

Transcranial ultrasound stimulation (TUS) has been clinically applied as a neuromodulation tool. Particularly, the phase array ultrasound can be applied in TUS to non-invasively focus on the cortex or deep brain. However, the vital phase distortion of the ultrasound induced by the skull limits its clinical application. In the current study, we aimed to develop a hybrid method that combines the ultrashort echo time (UTE) magnetic resonance imaging (MRI) sequences with the prDeep technique to achieve focusing ventral intermediate thalamic nucleus (VIM). The time-reversal (TR) approach of the UTE numerical acoustic model of the skull combined with the prDeep algorithm was used to reduce the number of iterations. The skull acoustic model simulation therapy process was establish to valid this method’s prediction and focus performance, and the classical TR method were considered as the gold standard (GS). Our approach could restore 75% of the GS intensity in 25 iteration steps, with a superior the noise immunity. Our findings demonstrate that the phase aberration caused by the skull can be estimated using phase retrieval techniques to achieve a fast and accurate transcranial focus. The method has excellent adaptability and anti-noise capacity for satisfying complex and changeable scenarios.

A Phase 0 Study to Assess the Biodistribution and Pharmacokinetics of a Radiolabeled Antibody Targeting Human Kallikrein 2 in Participants with Metastatic Castration-Resistant Prostate Cancer.

Despite the inclusion of multiple agents within the prostate cancer treatment landscape, new treatment options are needed to address the unmet need for patients with metastatic castration-resistant prostate cancer (mCRPC). Although prostate-specific membrane antigen is the only cell-surface target to yield clinical benefit in men with advanced prostate cancer, additional targets may further advance targeted immune, cytotoxic, radiopharmaceutical, and other tumor-directed therapies for these patients. Human kallikrein 2 (hK2) is a novel prostate-specific target with little to no expression in nonprostate tissues. This first-in-human phase 0 trial uses an 111In-radiolabeled anti-hK2 monoclonal antibody, [111In]-DOTA-h11B6, to credential hK2 as a potential target for prostate cancer treatment. Methods: Participants with progressive mCRPC received a single infusion of 2 mg of [111In]-DOTA-h11B6 (185 MBq of 111In), with or without 8 mg of unlabeled h11B6 to assess antibody mass effects. Sequential imaging and serial blood samples were collected to determine [111In]-DOTA-h11B6 biodistribution, dosimetry, serum radioactivity, and pharmacokinetics. Safety was assessed within a 2-wk follow-up period from the time of [111In]-DOTA-h11B6 administration. Results: Twenty-two participants received [111In]-DOTA-h11B6 and are included in this analysis. Within 6-8 d of administration, [111In]-DOTA-h11B6 visibly accumulated in known mCRPC lesions, with limited uptake in other organs. Two treatment-emergent adverse events unrelated to treatment occurred, including tumor-related bleeding in 1 patient, which led to early study discontinuation. Serum clearance, biodistribution, and tumor targeting were independent of total antibody mass (2 or 10 mg). Conclusion: This first-in-human study demonstrates that tumor-associated hK2 can be identified and targeted using h11B6 as a platform as the h11B6 antibody selectively accumulated in mCRPC metastases with mass-independent clearance kinetics. These data support the feasibility of hK2 as a target for imaging and hK2-directed agents as potential therapies in patients with mCRPC.

A Technique for In-Situ Displacement and Strain Measurement with Laboratory-Scale X-Ray Computed Tomography

Abstract Purpose: Establish a technique for simultaneous interrupted volumetric imaging of internal structure and time-resolved full-field surface strain measurements during in-situ X-ray micro-computed tomography (XCT) experiments. This enables in-situ testing of stiff materials with large forces relative to the compliance of the in-situ load frame, which might exhibit localization (e.g., necking, compaction banding) and other inhomogeneous behaviors.Methods: The system utilizes a combination of in-situ XCT, 2D X-ray imaging, and particle tracking to conduct volumetric imaging of the internal structure of a specimen with interrupted loading and surface strain mapping during loading. Critically, prior to the laboratory-scale XCT experiments, specimens are speckled with a high-X-ray-contrast powder that is bonded the surface. During in-situ loading, the XCT system is programmed to capture sequential 2D X-ray images orthogonal to the speckled specimen surface. A single particle tracking (SPT) or digital image correlation (DIC) algorithm is used to measure full-field surface strain evolution throughout the time-sequence of images. At specified crosshead displacements, the motion and 2D image sequence is paused for volumetric XCT image collection. Results: We show example results on a micro-tensile demonstration specimen additive manufactured from Inconel 718 nickel-chrome alloy. Results include XCT volume reconstructions, crosshead-based engineering stress, and full-field strain maps. Conclusion: We demonstrate an in-situ technique to obtain surface strain evolution during laboratory-scale XCT testing and interrupted volumetric imaging. This allows closer investigation of, for example, the effect of micro-pores on the strain localization behavior of additive manufactured metal alloys. In addition to describing the method using a representative test piece, the dataset and code are published as open-source resources for the community. Graphical abstract

Estimating Fire Radiative Energy Density with Repeat-Pass Aerial Thermal-Infrared Imaging of Actively Progressing Wildfires

Studies on estimating cumulative fire intensity from spreading wildland fires based on fire radiative energy density (FRED) have primarily been conducted through controlled experiments. The objective of this study was to assess the potential for estimating FRED for freely-burning wildfires at landscape scales. Airborne thermal infrared image sequences collected 8 and 9 December 2017 during the Thomas Fire were used for surface temperature derivation and FRED estimation. Sensitivity of varying ambient temperatures, and a newly developed method that adjusts for ash radiances on fire radiative flux density (FRFD) and FRED estimates were tested. Pixel-level image classification was run to identify FRFD time sequences that were complete or incomplete because of cloud obscuration and provided the basis for an obscuration gap filling technique. Variations in estimated ambient temperature used to estimate FRFD had little impact on FRED estimates, while our ash adjustment led to notable differences. An exponential decay model characterized FRFD time sequences well, providing a basis for gap filling irregular sequences caused by atmospheric obscuration. FRED estimates were regressed on rate of spread (ROS) magnitudes and found to be positively and significantly correlated. FRED magnitudes were higher on 9 December when the Thomas Fire burned under higher wind speeds and lower relative humidity levels (Santa Ana weather conditions) than on 8 December.

Three-dimensional EPI with shot-selective CAIPIRIHANA for rapid high-resolution quantitative susceptibility mapping at 3 T.

QSM provides insight into healthy brain aging and neuropathologies such as multiple sclerosis (MS), traumatic brain injuries, brain tumors, and neurodegenerative diseases. Phase data for QSM are usually acquired from 3D gradient-echo (3D GRE) scans with long acquisition times that are detrimental to patient comfort and susceptible to patient motion. This is particularly true for scans requiring whole-brain coverage and submillimeter resolutions. In this work, we use a multishot 3D echo plannar imaging(3D EPI) sequence with shot-selective 2D CAIPIRIHANA to acquire high-resolution, whole-brain data for QSM with minimal distortion and blurring. To test clinical viability, the 3D EPI sequence was used to image a cohort of MS patients at 1-mm isotropic resolution at 3 T. Additionally, 3D EPI data of healthy subjects were acquired at 1-mm, 0.78-mm, and 0.65-mm isotropic resolution with varying echo train lengths (ETLs) and compared with a reference 3D GRE acquisition. The appearance of the susceptibility maps and the susceptibility values for segmented regions of interest were comparable between 3D EPI and 3D GRE acquisitions for both healthy and MS participants. Additionally, all lesions visible in the MS patients on the 3D GRE susceptibility maps were also visible on the 3D EPI susceptibility maps. The interplay among acquisition time, resolution, echo train length, and the effect of distortion on the calculated susceptibility maps was investigated. We demonstrate that the 3D EPI sequence is capable of rapidly acquiring submillimeter resolutions and providing high-quality, clinically relevant susceptibility maps.

Auditory Effects of Acoustic Noise From 3-T Brain MRI in Neonates With Hearing Protection.

Neonates with immature auditory function (eg, weak/absent middle ear muscle reflex) could conceivably be vulnerable to noise-induced hearing loss; however, it is unclear if neonates show evidence of hearing loss following MRI acoustic noise exposure. To explore the auditory effects of MRI acoustic noise in neonates. Prospective. Two independent cohorts of neonates (N = 19 and N = 18; mean gestational-age, 38.75 ± 2.18 and 39.01 ± 1.83 weeks). T1-weighted three-dimensional gradient-echo sequence, T2-weighted fast spin-echo sequence, single-shot echo-planar imaging-based diffusion-tensor imaging, single-shot echo-planar imaging-based diffusion-kurtosis imaging and T2-weighted fluid-attenuated inversion recovery sequence at 3.0 T. All neonates wore ear protection during scan protocols lasted ~40 minutes. Equivalent sound pressure levels (SPLs) were measured for both cohorts. In cohort1, left- and right-ear auditory brainstem response (ABR) was measured before (baseline) and after (follow-up) MRI, included assessment of ABR threshold, wave I, III and V latencies and interpeak interval to determine the functional status of auditory nerve and brainstem. In cohort2, baseline and follow-up left- and right-ear distortion product otoacoustic emission (DPOAE) amplitudes were assessed at 1.2 to 7.0 kHz to determine cochlear function. Wilcoxon signed-rank or paired t-tests with Bonferroni's correction were used to compare the differences between baseline and follow-up ABR and DPOAE measures. Equivalent SPLs ranged from 103.5 to 113.6 dBA. No significant differences between baseline and follow-up were detected in left- or right-ear ABR measures (P > 0.999, Bonferroni corrected) in cohort1, or in DPOAE levels at 1.2 to 7.0 kHz in cohort2 (all P > 0.999 Bonferroni corrected except for left-ear levels at 3.5 and 7.0 kHz with corrected P = 0.138 and P = 0.533). A single 40-minute 3-T MRI with equivalent SPLs of 103.5-113.6 dBA did not result in significant transient disruption of auditory function, as measured by ABR and DPOAE, in neonates with adequate hearing protection. 2. Stage 5.

A temporal enhanced semi-supervised training framework for needle segmentation in 3D ultrasound images

Objective. Automated biopsy needle segmentation in 3D ultrasound images can be used for biopsy navigation, but it is quite challenging due to the low ultrasound image resolution and interference similar to the needle appearance. For 3D medical image segmentation, such deep learning networks as convolutional neural network and transformer have been investigated. However, these segmentation methods require numerous labeled data for training, have difficulty in meeting the real-time segmentation requirement and involve high memory consumption. Approach. In this paper, we have proposed the temporal information-based semi-supervised training framework for fast and accurate needle segmentation. Firstly, a novel circle transformer module based on the static and dynamic features has been designed after the encoders for extracting and fusing the temporal information. Then, the consistency constraints of the outputs before and after combining temporal information are proposed to provide the semi-supervision for the unlabeled volume. Finally, the model is trained using the loss function which combines the cross-entropy and Dice similarity coefficient (DSC) based segmentation loss with mean square error based consistency loss. The trained model with the single ultrasound volume input is applied to realize the needle segmentation in ultrasound volume. Main results. Experimental results on three needle ultrasound datasets acquired during the beagle biopsy show that our approach is superior to the most competitive mainstream temporal segmentation model and semi-supervised method by providing higher DSC (77.1% versus 76.5%), smaller needle tip position (1.28 mm versus 1.87 mm) and length (1.78 mm versus 2.19 mm) errors on the kidney dataset as well as DSC (78.5% versus 76.9%), needle tip position (0.86 mm versus 1.12 mm) and length (1.01 mm versus 1.26 mm) errors on the prostate dataset. Significance. The proposed method can significantly enhance needle segmentation accuracy by training with sequential images at no additional cost. This enhancement may further improve the effectiveness of biopsy navigation systems.

MR-based radiomics predictive modelling of EGFR mutation and HER2 overexpression in metastatic brain adenocarcinoma: a two-centre study

ObjectivesMagnetic resonance (MR)-based radiomics features of brain metastases are utilised to predict epidermal growth factor receptor (EGFR) mutation and human epidermal growth factor receptor 2 (HER2) overexpression in adenocarcinoma, with the aim to identify the most predictive MR sequence.MethodsA retrospective inclusion of 268 individuals with brain metastases from adenocarcinoma across two institutions was conducted. Utilising T1-weighted imaging (T1 contrast-enhanced [T1-CE]) and T2 fluid-attenuated inversion recovery (T2-FLAIR) sequences, 1,409 radiomics features were extracted. These sequences were randomly divided into training and test sets at a 7:3 ratio. The selection of relevant features was done using the least absolute shrinkage selection operator, and the training cohort’s support vector classifier model was employed to generate the predictive model. The performance of the radiomics features was evaluated using a separate test set.ResultsFor contrast-enhanced T1-CE cohorts, the radiomics features based on 19 selected characteristics exhibited excellent discrimination. No significant differences in age, sex, and time to metastasis were observed between the groups with EGFR mutations or HER2 + and those with wild-type EGFR or HER2 (p > 0.05). Radiomics feature analysis for T1-CE revealed an area under the curve (AUC) of 0.98, classification accuracy of 0.93, sensitivity of 0.92, and specificity of 0.93 in the training cohort. In the test set, the AUC was 0.82. The 19 radiomics features for the T2-FLAIR sequence showed AUCs of 0.86 in the training set and 0.70 in the test set.ConclusionsThis study developed a T1-CE signature that could serve as a non-invasive adjunctive tool to determine the presence of EGFR mutations and HER2 + status in adenocarcinoma, aiding in the direction of treatment plans.Clinical relevance statementWe propose radiomics features based on T1-CE brain MR sequences that are both evidence-based and non-invasive. These can be employed to guide clinical treatment planning in patients with brain metastases from adenocarcinoma.

Changes in the central nervous system in football players: an MRI study.

Football (soccer) is the world's most popular team sport. To comprehensively examine the brain in football (soccer) players, with the use of magnetic resonance imaging (MRI) techniques. The study involved 65 football players and 62 controls. The MR examinations were performed using MR 1.5-T system (Optima MR 360; GE Medical Systems). The examinations were carried out in the 3D Bravo, CUBE, FSEpropeller, and diffusion-weighted imaging (DWI) sequences. The 1HMRS signal was obtained from the volume of interest in the frontal and occipital lobes on both sides. The present study, based on structural MRI, shows some changes in the brains of the group of football players. The findings show asymmetry of the ventricular system in four football players, arachnoid cysts in the parieto-occipital region, and pineal cysts. NAA/Cr concentration in the right frontal lobe was lower in the football players than in the controls, and the Glx/Cr concentration in the right occipital lobe was higher. The apparent diffusion coefficient value is lower in football players in the occipital lobes. Playing football can cause measurable changes in the brain, known to occur in patients diagnosed with traumatic brain injury. The present findings fill the gap in the literature by contributing evidence showing that playing football may lead to changes in the brain, without clinical symptoms of concussion.

The Use of Dixon Magnetic Resonance Imaging Methods for the Quantification of Rotator Cuff Fatty Infiltration: A Systematic Review

Fatty infiltration of the rotator cuff muscles is very common following rotator cuff tears and is one of the most important factors in determining treatment. Current clinical practice relies on subjective evaluation of fatty infiltration through categorical scoring based on the Goutallier classification system. The Dixon magnetic resonance imaging (MRI) sequence provides flexibility in selecting echo times for water–fat separation. The Dixon method, therefore, has the potential to provide robust and high-quality fat quantification that allows for more accurate calculation of fat fraction (%Fat) of the rotator cuff muscles than the Goutallier classification system. However, significant variance exists in sequencing and post-processing methodology within the recent application of Dixon sequences to quantify rotator cuff fatty infiltration. In this paper, we conducted a systematic review to synthesize the relevant literature utilizing Dixon sequencing for the quantification of rotator cuff fatty infiltration. The literature search was extracted from 1094 articles, with 12 studies included in the final review. Regardless of the varying sequencing pattern and post-processing techniques among studies, the findings suggest the Dixon method is reliable for quantitatively calculating the fat fraction of the rotator cuff muscles, even at very low levels of fatty infiltration. In addition, a quantitative difference in fat fraction was observed between participants with different degrees of tear vs. those without any shoulder pathologies. Multi-point Dixon imaging has the potential to be utilized clinically to objectively quantify fatty infiltration and may lead to improved clinical decision making for patients with rotator cuff tears.

The Effect of Battery Configuration on Dendritic Growth: A Magnetic Resonance Microscopy Study on Symmetric Lithium Cells

The potential of metallic lithium to become the anode material for next-generation batteries is hampered by significant challenges, chief among which is dendrite growth during battery charging. These dendritic structures not only impair battery performance but also pose safety risks. Among the non-destructive analytical techniques in battery research, Magnetic Resonance Imaging (MRI) stands out as a promising tool. However, the direct imaging of lithium by 7Li MRI is limited by its low sensitivity and spatial resolution, making it a less effective way of imaging dendrite growth. Instead, a recently introduced indirect imaging approach which is based on 1H MRI of the electrolyte was used in this study. This method was used to sequentially 3D image and thus monitor the charging process of lithium metal symmetric cells in three different electrical circuits, namely those composed of a single cell, four cells in parallel, and four cells in series. The measured sequential images allowed for the measurement of dendrite growth in each cell using volumetric analysis. The growth results confirmed the theoretical prediction that the growth across cells is uneven in a parallel circuit, and even in a series circuit. The methods presented in this study can also be applied to analyze many other dendrite-related issues in batteries.

Self-supervised learning for interventional image analytics: toward robust device trackers.

The accurate detection and tracking of devices, such as guiding catheters in live X-ray image acquisitions, are essential prerequisites for endovascular cardiac interventions. This information is leveraged for procedural guidance, e.g., directing stent placements. To ensure procedural safety and efficacy, there is a need for high robustness/no failures during tracking. To achieve this, one needs to efficiently tackle challenges, such as device obscuration by the contrast agent or other external devices or wires and changes in the field-of-view or acquisition angle, as well as the continuous movement due to cardiac and respiratory motion. To overcome the aforementioned challenges, we propose an approach to learn spatio-temporal features from a very large data cohort of over 16million interventional X-ray frames using self-supervision for image sequence data. Our approach is based on a masked image modeling technique that leverages frame interpolation-based reconstruction to learn fine inter-frame temporal correspondences. The features encoded in the resulting model are fine-tuned downstream in a light-weight model. Our approach achieves state-of-the-art performance, in particular for robustness, compared to ultra optimized reference solutions (that use multi-stage feature fusion or multi-task and flow regularization). The experiments show that our method achieves a 66.31% reduction in the maximum tracking error against the reference solutions (23.20% when flow regularization is used), achieving a success score of 97.95% at a faster inference speed of 42 frames-per-second (on GPU). In addition, we achieve a 20% reduction in the standard deviation of errors, which indicates a much more stable tracking performance. The proposed data-driven approach achieves superior performance, particularly in robustness and speed compared with the frequently used multi-modular approaches for device tracking. The results encourage the use of our approach in various other tasks within interventional image analytics that require effective understanding of spatio-temporal semantics.

Multi-Object Tracking Model Based on Detection Tracking Paradigm in Panoramic Scenes

Multi-Object Tracking Model Based on Detection Tracking Paradigm in Panoramic Scenes