bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unfractionated Heparin Administered Every 8 h Outperforms 12 Hourly Administration for Venous Thromboembolism Prophylaxis in Reconstructive Head and Neck Tumor Patients: A 12 Year Retrospective Cohort Study
Authors: Cevik Jevan , Newland David P. , Cheong Edward , Shadid Omar , Pang Siyuan , Nagpal Sakshar , Cabalag Miguel , Ramakrishnan Anand 
Published: October 2024

ABSTRACTBackgroundVenous thromboembolism (VTE), comprising deep vein thrombosis (DVT) and pulmonary embolism (PE), poses a significant risk of morbidity and mortality in surgical patients, especially those undergoing head and neck cancer surgery with microvascular free flap reconstruction. These patients are at a heightened risk of VTE due to numerous patient and surgical risk factors. VTE chemoprophylaxis guidelines in these patients are limited due to a distinct paucity of research. This study aims to contribute to this scarcity of information, providing guidance for surgeons.MethodsThis retrospective cohort study evaluated the efficacy and safety of subcutaneous unfractionated heparin administered every 8 h versus every 12 h for postoperative VTE prophylaxis in patients undergoing head and neck resections with immediate free flap reconstruction. Data was collected from hospital medical records between January 2010 to December 2021. Patient demographics, operative details, and outcomes, including incidence of VTE and bleeding complications, were analyzed.ResultsAmong 622 patients, those receiving heparin every 8 h (n = 393) demonstrated a significantly lower rate of VTE (0.8%) compared to 12‐hourly group (n = 229; 3.9%) (p = 0.006). Additionally, there were no significant differences in the rates of postoperative hematoma between the two groups (9.4% versus 7.9% respectively, p = 0.510).ConclusionOur study suggests that an increased daily dose of unfractionated heparin every 8 h for VTE chemoprophylaxis is superior to a 12‐hourly regimen with comparable bleeding profiles. Further multicentre, prospective studies are needed to validate these results and compare the efficacy and safety of unfractionated heparin with other agents such as low‐molecular‐weight heparin in this patient group.
Noise‐assisted hybrid attention networks for low‐dose PET and CT denoising
Authors: Xue Hengzhi , Yao Yudong , Teng Yueyang 
Published: October 2024

AbstractBackgroundPositron emission tomography (PET) and computed tomography (CT) play a vital role in tumor‐related medical diagnosis, assessment, and treatment planning. However, full‐dose PET and CT pose the risk of excessive radiation exposure to patients, whereas low‐dose images compromise image quality, impacting subsequent tumor recognition and disease diagnosis.PurposeTo solve such problems, we propose a Noise‐Assisted Hybrid Attention Network (NAHANet) to reconstruct full‐dose PET and CT images from low‐dose PET (LDPET) and CT (LDCT) images to reduce patient radiation risks while ensuring the performance of subsequent tumor recognition.MethodsNAHANet contains two branches: the noise feature prediction branch (NFPB) and the cascaded reconstruction branch. Among them, NFPB providing noise features for the cascade reconstruction branch. The cascaded reconstruction branch comprises a shallow feature extraction module and a reconstruction module which contains a series of cascaded noise feature fusion blocks (NFFBs). Among these, the NFFB fuses the features extracted from low‐dose images with the noise features obtained by NFPB to improve the feature extraction capability. To validate the effectiveness of the NAHANet method, we performed experiments using two public available datasets: the Ultra‐low Dose PET Imaging Challenge dataset and Low Dose CT Grand Challenge dataset.ResultsAs a result, the proposed NAHANet achieved higher performance on common indicators. For example, on the CT dataset, the PSNR and SSIM indicators were improved by 4.1 dB and 0.06 respectively, and the rMSE indicator was reduced by 5.46 compared with the LDCT; on the PET dataset, the PSNR and SSIM was improved by 3.37 dB and 0.02, and the rMSE was reduced by 9.04 compared with the LDPET.ConclusionsThis paper proposes a transformer‐based denoising algorithm, which utilizes hybrid attention to extract high‐level features of low dose images and fuses noise features to optimize the denoising performance of the network, achieving good performance improvements on low‐dose CT and PET datasets.
Performance evaluation of a small‐animal PET scanner with 213 mm axis using NEMA NU 4‐2008
Authors: Wei Qing , Wang Yingjie , Huang Xianchao , Li Daowu , Zheng Yushuang , Wang Peilin , Sun Xiaoli , Chai Pei , Han Xiaorou , Liu Shuangquan , Feng Baotong , Zhou Wei , Zeng Xiangtao , Zhu Meiling , Zhang Zhiming , Wei Long 
Published: October 2024

AbstractBackgroundLong‐axis positron emission tomography (PET) has emerged as one of the recent research directions in PET due to its ability to significantly enhance sensitivity and counting performance for low‐dose imaging, rapid imaging, and whole‐body dynamic imaging.PurposeThe PET system presented in this study is a long‐axis animal PET based on lutetium–yttrium orthosilicate and silicon photomultiplier, designed for whole‐body imaging in rats. It features a diameter of 143 mm and an axial length of 213.3 mm. This study evaluated the performance of this PET system in accordance with the National Electrical Manufacturers Association (NEMA) NU 4‐2008 standards.MethodsThe performance evaluation was conducted according to the NEMA NU 4‐2008 standards in terms of spatial resolution, sensitivity, counting rate performance, scatter fraction (SF) and image quality. In addition, a rat imaging study was conducted to assess the imaging capability of this PET system.ResultsThe average energy resolution of the PET system was 12.87%, the average coincidence timing resolution was 751 ps. The FWHM of spatial resolution reconstructed by filtered back projection and 3D‐OSEM‐PSF algorithm at 5 mm radial offset from the axial center were 1.65 and 0.88 mm. The peak absolute sensitivity measured by a point source at the center of the field of view was evaluated as 6.71% (361–661 keV) and 10.31% (250–750 keV). For the mouse‐like phantom, the SF was 11.0% and the peak noise equivalent counting rate (NECR) was 1193 kcps at 94.2 MBq (2.54 mCi). For the rat‐like phantom, the SF was 26.8% and the NECR was 682.5 kcps at 78.6 MBq (2.12 mCi).ConclusionsThe performance measurement results demonstrate that this PET system exhibits high sensitivity and count rate performance, making it potential for high‐quality whole‐body dynamic imaging of rats.
Necessity and impact of specialization of large foundation model for medical segmentation tasks
Authors: Nguyen Eric , Liu Hengjie , Ruan Dan 
Published: October 2024

AbstractBackgroundLarge foundation models, such as the Segment Anything Model (SAM), have shown remarkable performance in image segmentation tasks. However, the optimal approach to achieve true utility of these models for domain‐specific applications, such as medical image segmentation, remains an open question. Recent studies have released a medical version of the foundation model MedSAM by training on vast medical data, who promised SOTA medical segmentation. Independent community inspection and dissection is needed.PurposeFoundation models are developed for general purposes. On the other hand, stable delivery of reliable performance is key to clinical utility. This study aims at elucidating the potential advantage and limitations of landing the foundation models in clinical use by assessing the performance of off‐the‐shelf medical foundation model MedSAM for the segmentation of anatomical structures in pelvic MR images. We also explore the simple remedies by evaluating the dependency on prompting scheme. Finally, we demonstrate the need and performance gain of further specialized fine‐tuning.MethodsMedSAM and its lightweight version LiteMedSAM were evaluated out‐of‐the‐box on a public MR dataset consisting of 589 pelvic images split 80:20 for training and testing. An nnU‐Net model was trained from scratch to serve as a benchmark and to provide bounding box prompts for MedSAM. MedSAM was evaluated using different quality bounding boxes, those derived from ground truth labels, those derived from nnU‐Net, and those derived from the former two but with 5‐pixel isometric expansion. Lastly, LiteMedSAM was refined on the training set and reevaluated on this task.ResultsOut‐of‐the‐box MedSAM and LiteMedSAM both performed poorly across the structure set, especially for disjoint or non‐convex structures. Varying prompt with different bounding box inputs had minimal effect. For example, the mean Dice score and mean Hausdorff distances (in mm) for obturator internus using MedSAM and LiteMedSAM were {0.251 ± 0.110, 0.101 ± 0.079} and {34.142 ± 5.196, 33.688 ± 5.306}, respectively. Fine‐tuning of LiteMedSAM led to significant performance gain, improving Dice score and Hausdorff distance for the obturator internus to 0.864 ± 0.123 and 5.022 ± 10.684, on par with nnU‐Net with no significant difference in evaluation of most structures. All segmentation structures benefited significantly from specialized refinement, at varying improvement margin.ConclusionWhile our study alludes to the potential of deep learning models like MedSAM and LiteMedSAM for medical segmentation, it highlights the need for specialized refinement and adjudication. Off‐the‐shelf use of such large foundation models is highly likely to be suboptimal, and specialized fine‐tuning is often necessary to achieve clinical desired accuracy and stability.
Algorithms to reduce the edge effect and improve the flood histogram quality of a PET detector consisting of two pixelated crystal arrays
Authors: Cong Longhan , Kuang Zhonghua , Ren Ning , Sang Ziru , Liu Zheng , Niu Ming , Xie Siwei , Peng Qiyu , Yang Yongfeng 
Published: October 2024

AbstractPurposeThe performance of detectors is key for a PET scanner to achieve high spatial resolution and high sensitivity. This work aims to develop flood histogram generating algorithms to reduce the edge effect and improve the crystal identification of a PET detector consisting of two optically coupled pixelated scintillator detectors.MethodsThe PET detector consists of two optically coupled detectors, each consisting of a 23×23 LYSO crystal array with a crystal size of 1.0×1.0×20 mm3 read out by an 8×8 SiPM array with a pixel size of 3.0×3.0 mm2. The SiPM array is read out with a resistor network circuit to obtain four position encoding energy signals. A novel center of gravity (COG) positioning algorithm using six signals from the two detectors was proposed and compared to the traditional COG algorithms using either four or eight signals from the detectors. The raised‐to‐the‐power (RTP) method was applied to the three COG algorithms for the PET detector. Different powers of the RTP from 1.0 to 2.5 were evaluated.ResultsThe proposed COG algorithm significantly improves the crystal identification at the junction of the two detectors as compared to the COG algorithm using four signals of each detector, and improves the crystal identification at the center of the two detectors as compared to the COG algorithm using eight signals from both detectors. The RTP method significantly improves the overall flood histogram qualities of the two COG algorithms using either eight or six signals from the two detectors, and the two COG algorithm provide similar flood histogram quality when a power of 1.5 is used.ConclusionThe novel positioning algorithms reduce the edge effect and improve the flood histogram quality for a PET detector consisting of two optically coupled detectors, each consisting of a pixelated scintillator crystal array and a SiPM array with highly multiplexed four signal readout. The positioning algorithms can be used in a PET scanner to improve the spatial resolution and sensitivity.
Single‐shot echo planar time‐resolved imaging for multi‐echo functional MRI and distortion‐free diffusion imaging
Authors: Dong Zijing , Wald Lawrence L. , Polimeni Jonathan R. , Wang Fuyixue 
Published: October 2024

AbstractPurposeTo develop a single‐shot SNR‐efficient distortion‐free multi‐echo imaging technique for dynamic imaging applications.MethodsEcho planar time‐resolved imaging (EPTI) was first introduced as a multi‐shot technique for distortion‐free multi‐echo imaging. This work aims to develop single‐shot EPTI (ss‐EPTI) to achieve improved robustness to motion/physiological noise, increased temporal resolution, and higher SNR efficiency. A new spatiotemporal encoding that enables reduced phase‐encoding blips and minimized echo spacing under the single‐shot regime was developed, which improves sampling efficiency and enhances spatiotemporal correlation in the k‐TE space for improved reconstruction. A continuous readout with minimized deadtime was employed to optimize SNR efficiency. Moreover, k‐TE partial Fourier and simultaneous multi‐slice acquisition were integrated for further acceleration.Resultsss‐EPTI provided distortion‐free imaging with densely sampled multi‐echo images at standard resolutions (e.g., ˜1.25 to 3 mm) in a single‐shot. Improved SNR efficiency was observed in ss‐EPTI due to improved motion/physiological‐noise robustness and efficient continuous readout. Its ability to eliminate dynamic distortions—geometric changes across dynamics due to field changes induced by physiological variations or eddy currents—further improved the data's temporal stability. For multi‐echo fMRI, ss‐EPTI's multi‐echo images recovered signal dropout in short‐ regions and provided TE‐dependent functional information to distinguish non‐BOLD noise for further tSNR improvement. For diffusion MRI, it achieved shortened TEs for improved SNR and provided images free from both B0‐induced and diffusion‐encoding‐dependent eddy‐current‐induced distortions with multi‐TE diffusion metrics.Conclusionss‐EPTI provides SNR‐efficient distortion‐free multi‐echo imaging with comparable temporal resolutions to ss‐EPI, offering a new acquisition tool for dynamic imaging.
First in‐vivo magic angle directional imaging using dedicated low‐field MRI
Authors: Ristic Mihailo , Chappell Karyn E. , Lanz Harry , McGinley John , Gupte Chinmay , Amiras Dimitris 
Published: October 2024

AbstractPurposeTo report the first in‐vivo results from exploiting the magic angle effect, using a dedicated low‐field MRI scanner that can be rotated about two axes. The magic angle directional imaging (MADI) method is used to depict collagen microstructures with 3D collagen tractography of knee ligaments and the meniscus.MethodsA novel low‐field MRI system was developed, based on a transverse field open magnet, where the magnet can be rotated about two orthogonal axes. Sets of volume scans at various orientations were obtained in healthy volunteers. The experiments focused on the anterior cruciate ligament (ACL) and the meniscus of the knee. The images were co‐registered, anatomical regions of interest (ROIs) were selected and the collagen fiber orientations in each voxel were estimated from the observed image intensity variations. The 3D collagen tractography was superimposed on conventional volume images.ResultsThe MADI method was successfully employed for the first time producing in‐vivo results comparable to those previously reported for excised animal specimens using conventional MRI. Tractography plots were generated for the ACL and the menisci. These results are consistent with the known microstructure of collagen fibers in these tissues.ConclusionImages obtained using low‐field MRI with 1 mm3 resolution were of sufficient quality for the MADI method, which was shown to produce high quality in‐vivo information of collagen microstructures. This was achieved using a cost effective and sustainable low‐field magnet making the technique potentially accessible and scalable, potentially changing the way we image injuries or disease in joints.
Age‐specific optimization of the T2‐weighted MRI contrast in infant and toddler brain
Authors: Wu Jiani , Qin Fenjie , Tian Fengyu , Li Haotian , Yong Xingwang , Liu Tingting , Zhang Hongxi , Wu Dan 
Published: October 2024

AbstractPurposeIn 0–2‐year‐old brains, the T2‐weighted (T2w) contrast between white matter (WM) and gray matter (GM) is weaker compared with that in adult brains and rapidly changes with age. This study aims to design variable‐flip‐angle (VFA) trains in 3D fast spin‐echo sequence that adapt to the dynamically changing relaxation times to improve the contrast in the T2w images of the developing brains.MethodsT1 and T2 relaxation times in 0–2‐year‐old brains were measured, and several age groups were defined according to the age‐dependent pattern of T2 values. Based on the static pseudo‐steady‐state theory and the extended phase graph algorithm, VFA trains were designed for each age group to maximize WM/GM contrast, constrained by the maximum specific absorption rate and overall signal intensity. The optimized VFA trains were compared with the default one used for adult brains based on the relative contrast between WM and GM. Dice coefficient was used to demonstrate the advantage of contrast‐improved images as inputs for automatic tissue segmentation in infant brains.ResultsThe 0–2‐year‐old pool was divided into groups of 0–8 months, 8–12 months, and 12–24 months. The optimal VFA trains were tested in each age group in comparison with the default sequence. Quantitative analyses demonstrated improved relative contrasts in infant and toddler brains by 1.5–2.3‐fold at different ages. The Dice coefficient for contrast‐optimized images was improved compared with default images (p < 0.001).ConclusionAn effective strategy was proposed to improve the 3D T2w contrast in 0–2‐year‐old brains.
Small Strain Stiffness of Sand‐Rubber Mixtures With Particle Size Disparity Effect
Authors: Liu Deyun , Yin Zhen‐Yu 
Published: October 2024

ABSTRACTThis study systematically investigates the small‐strain stiffness of sand‐rubber mixtures, focusing on combined particle disparity—both larger sand with smaller rubber and smaller sand with larger rubber—using the discrete element method. The effectiveness of various state variables in capturing stiffness behavior across different rubber contents and size disparities (SDs) is evaluated. Conventional state variables developed for natural sands, such as void ratio and mechanical void ratio were found to be less effective in describing the small‐strain stiffness characteristics of sand‐rubber mixtures due to distinct properties of rubber. This study then demonstrates that the stiffness contribution of rubber materials could be negligible, emphasizing that particle property disparity is more significant than SD between sand and rubber materials. Therefore, an adapted state variable, considering only active sand particles, shows improved performance for capturing the correlation between small‐strain stiffness with increasing rubber contents, suggesting its potential utility over conventional variables. Additionally, a refined void ratio, including inactive sand particles but excluding rubber, offers a practical alternative for capturing small‐strain stiffness in experimental and engineering practices, aligning with previous experimental observations. These findings underscore the need for developing more effective state variables that accurately reflect the interactions within heterogeneous materials like sand‐rubber mixtures.
Water Intake in Drinks and Food: How Should We Advise Patients With Lower Urinary Tract Dysfunction on Their Water Intake and/or Urine Output, as a Cornerstone of Lifestyle Interventions? ICI‐RS 2024
Authors: Gammie Andrew , Khullar Vik , Rantell Angie , Cotterill Nikki , Abrams Paul , Song Qi‐Xiang , Smith Matthew , Sinha Sanjay 
Published: October 2024

ABSTRACTContextWater intake in drinks and food is essential for life. Multiple guidelines exist to help give recommendations for healthy water intake and urine output, but few of these are specific to patients with lower urinary tract symptoms.MethodsA debate held at the International Consultation on Incontinence—Research Society meeting, held in Bristol in June 2024, considered ways to improve this situation.Results and ConclusionThere are challenges in measuring both total water intake and also urine output, but we suggest that urine output may be the most helpful measure to focus on for future guidelines for patients.
Efficacy of Biofeedback Therapy for Giggle Incontinence in Children: How Many Sessions Are Required?
Authors: Canbaz Furkan Adem , Gerçel Gonca , Sağ Sefa 
Published: October 2024

ABSTRACTIntroductionGiggle incontinence (GI) is characterized by the sudden and involuntary expulsion of urine coinciding with episodes of laughter. The underlying pathophysiology of this condition remains unclear, and various treatment approaches are employed. The objective of this study is to assess the effectiveness of biofeedback (BF) therapy in treating GI and ascertain the requisite number of therapy sessions needed for efficacy.MethodsMedical records of children treated with BF therapy for GI between November 2022 and November 2023 were retrospectively analyzed. The success of treatment was assessed after four and eight sessions, as well as following three maintenance sessions. Treatment outcomes were evaluated using the scoring system recommended by the International Children's Continence Society (ICCS), which categorizes responses into three levels: no response (Score 0), partial response (Score 1), and complete response (Score 2).ResultsThirteen patients were initially diagnosed with GI. Of these, 10 patients were included in the study as three discontinued treatments. The cohort comprised an equal gender distribution with five females (50.0%) and five males (50.0%). The mean age of patients was 8.9 ± 3.3 (range 5–16) years. Two out of ten patients had a history of previous treatment for overactive bladder, while three had received treatment for primary monosymptomatic nocturnal enuresis. Following the completion of all BF sessions, the rate of complete response was observed at 80.0% (n = 8), while the partial response rate accounted for 10.0% (n = 1). Statistical analysis revealed significant differences in response scores after four and eight sessions (p < 0.01) as well as between the results after eight sessions and the completion of maintenance sessions (p < 0.01).ConclusionBF therapy demonstrates a high success rate in managing GI. Completion of at least eight BF therapy sessions enhances the probability of a successful outcome in the treatment of GI. Additionally, it has been observed that maintenance sessions contribute to the increased efficacy of the treatment.
Graph Regularized Sparse L2,1 Semi‐Nonnegative Matrix Factorization for Data Reduction
Authors: Rhodes Anthony , Jiang Bin , Jiang Jenny 
Published: October 2024

ABSTRACTNon‐negative Matrix Factorization (NMF) is an effective algorithm for multivariate data analysis, including applications to feature selection, pattern recognition, and computer vision. Its variant, Semi‐Nonnegative Matrix Factorization (SNF), extends the ability of NMF to render parts‐based data representations to include mixed‐sign data. Graph Regularized SNF builds upon this paradigm by adding a graph regularization term to preserve the local geometrical structure of the data space. Despite their successes, SNF‐related algorithms to date still suffer from instability caused by the Frobenius norm due to the effects of outliers and noise. In this paper, we present a new SNF algorithm that utilizes the noise‐insensitive norm. We provide monotonic convergence analysis of the SNF algorithm. In addition, we conduct numerical experiments on three benchmark mixed‐sign datasets as well as several randomized mixed‐sign matrices to demonstrate the performance superiority of SNF over conventional SNF algorithms under the influence of Gaussian noise at different levels.