Hasil untuk "Surgery"

T. Kajitani, The International Consortium for Outcome Research in H Cancer

R. Rutherford, D. Flanigan, S. Gupta et al.

P. Mcculloch, I. Taylor, M. Sasako et al.

J. Insall, W. Scott

J. Dunning, B. Prendergast, K. Mackway-Jones

H. Buchwald, Stanley E. Williams

B. Whitson, Shawn S. Groth, Susan J. Duval et al.

J. Peters, G. Fried, L. Swanstrom et al.

Junyu Zhou, Yuhao Liu, Ethan Decker et al.

Lattice surgery is a leading approach for implementing fault-tolerant logical operations in surface code quantum computing, but compiling efficient lattice surgery layouts remains challenging. Existing compilers are largely circuit-centric and operate directly on gate sequences, limiting their ability to exploit the topological flexibility of merge-split operations and minimize space--time volume. We present TopoLS, a topology-centric compiler that uses ZX diagrams as an intermediate representation for lattice surgery compilation. TopoLS combines semantic-preserving ZX-level program transformations, including spider fusion and topology-aware slicing, with a Monte Carlo Tree Search (MCTS)-based synthesis procedure that constructs pipe-diagram embeddings by jointly optimizing placement and routing in 3D space--time. To scale to large circuits, TopoLS further introduces topology-aware partitioning that decomposes the compilation task into bounded subproblems and limits the routing frontier during embedding. Across evaluated benchmarks, TopoLS achieves an average $46\%$ reduction in space--time volume over prior circuit-centric compilers, with improvements ranging from $25\%$ to $90\%$, and exhibits strong empirical scalability on large benchmark families. Compared with SAT-based formulations that become intractable on larger instances, TopoLS offers a practical end-to-end solution for optimized lattice surgery compilation. TopoLS has been integrated into the TQEC ecosystem, enabling downstream circuit-level simulation and resource estimation workflows.

M. Chowdhury, H. Dagash, A. Pierro

A. Tsai, T. Wadden

Aditya Dwivedi, Archana Maji, Dmitry Noshchenko et al.

$\rm SL(2,\mathbb{C})$ Chern-Simons theory on a closed 3-manifold is one of the most interesting, yet tractable examples of a QFT. On one hand, its non-perturbative structure is not yet fully understood; on the other, the mathematical structure turns out to be very rich. In this work we explore the new phenomenon of flat connections at infinity on various knot surgery manifolds. Such flat connections can be understood as asymptotic ends in the non-compact moduli space of flat $\rm SL(2,\mathbb{C})$ connections. We focus on the examples of $\pm 1/r$-surgeries on torus, twist and some double twist knot complements in $S^3$. Surprisingly, our findings suggest that flat connections at infinity are abundant even for simple low-crossing knot surgeries. We therefore believe that their presence would shed light on the resurgent nature of the path integral.

Rui Han, Xiaoyu Deng, Hebing Liu et al.

BackgroundAcute pancreatitis (AP) morbidity has been increasing in recent years. Patients with AP exhibit highly variable symptom patterns over time, posting challenges to traditional analytical methods. Dynamic Time Warping (DTW) effectively aligns temporal sequences of different rhythms, offering a novel approach to model these complex dynamics.ObjectiveThis study employs DTW technology to systematically analyze the individualized developmental trajectories of symptom clusters in patients with AP, delving into the heterogeneous characteristics during the process of time series changes.MethodsIn a longitudinal study of 155 patients with AP, 32 symptoms were assessed using the Memorial Symptom Assessment Scale at hospitalization and 1, 3, 6, 9, and 12 months post-discharge. DTW was used to analyze temporal dynamics, generating individual symptom distance matrices. At the group level, these matrices are integrated using Distatis analysis, followed by hierarchical clustering to identify symptom clusters and network analysis to determine central symptoms.ResultsEach patient had unique symptom manifestations and dynamic change patterns. Six major symptom clusters were identified: emotional disorder cluster, appetite disorder cluster, multi-system physical discomfort cluster, localized physiological perception abnormality cluster, functional decline cluster, and abdominal discomfort cluster. Centrality analysis revealed that the appetite domain exhibited high centrality, suggesting that its variation may influence multiple aspects of patient experience.ConclusionDynamic Time Warping provides a novel and effective approach for analyzing the temporal trajectories of symptoms both within and across individuals. The research results provide methodological support and empirical evidence for individualized symptom management, early intervention, and predictive model construction of AP progression.

Jay Lodhia, Mujaheed Suleman, Vanessa Poppe et al.

Abstract Background Mucoepidermoid carcinoma of the skin is an exceedingly rare neoplasm, with only a limited number of cases documented in the literature. Typically, mucoepidermoid carcinoma arises in the salivary glands, where it accounts for 30% of all malignant salivary gland tumors and generally presents as a low-grade malignancy with a low probability of metastasis. Case presentation We report a case of a 49-year-old female patient of African origin who presented to our tertiary center with a longstanding scalp lesion that had been present for approximately 10 years. Initially, the lesion was roughly the size of a tennis ball and remained stable until about 3 months prior to presentation, when it was excised at a peripheral primary health center. Unfortunately, no histological analysis or follow-up was conducted after the excision, and the lesion recurred, progressively increasing in size. The patient reported no cardinal B-symptoms or central nervous system symptoms at any point. Histopathological analysis of the recurrent mass confirmed a diagnosis of mucoepidermoid carcinoma, and a complete surgical excision was subsequently performed. Following surgery, the patient was referred to the national oncology center for radiotherapy as part of her comprehensive oncological management. She is currently 8 months post-excision, receiving radiotherapy, and exhibits no clinical signs of recurrence. Conclusion Mucoepidermoid carcinoma originating in cutaneous sites is particularly unusual and may stem from the embryonic development of ectopic salivary glands within the skin. In this case report, we describe a unique presentation of primary mucoepidermoid carcinoma on the scalp, which demonstrated aggressive characteristics with suspected metastasis to the vertebral body. This case highlights the importance of considering mucoepidermoid carcinoma in the differential diagnosis of scalp masses and underscores the need for further investigation into its pathogenesis and metastatic potential.

Lixue Qiao, Hao Li, Keyu Yin et al.

BackgroundThere is a potential bidirectional pathogenicity between thyroid and breast cancers. The association between sex hormones and two types of malignant tumors has emerged as a topic of intense academic debate in recent years. However, the role of sex hormone metabolism-related genes in thyroid cancer still needs to be further explored.MethodsWe obtained thyroid and breast cancer transcriptome data from the TCGA database and sex hormone metabolism-related gene sets from the MSigDB database, thus screening for sex hormone metabolism-related genes linked to the two malignant tumors. Univariate cox regression analysis was used for the screening of disease-free survival (DFS)-associated genes. The TCGA-THCA patients were classified as two categories via a consistent clustering algorithm, and the differential genes between the two categories were subsequently screened. A sex hormone metabolism-related prognostic model (TBSMRPM) of thyroid cancer versus breast cancer consisting of 10 genes was developed by Cox regression analyses and least absolute shrinkage with selection operator (LASSO) cox regression analysis. Finally, we performed clinicopathological subgroup analyses to analyze the correlation between TBSMRPM and clinical characteristics, immune infiltration, tumor mutation burden (TMB), and chemosensitivity, and verified the expression of TBSMRPM signature genes by qRT-PCR.ResultsWe identified 2 clusters correlated with sex hormone metabolism, and screened 10 prognostic differential genes related to thyroid cancer, breast cancer and sex hormone metabolism. After establishing the two risk groups for thyroid cancer originated from TBSMRPM, the results showed that the high-risk group exhibited the shorter DFS (P<0.05). In further clinical stratification analysis, immune infiltration analysis, TMB and drug sensitivity analysis, the two TBSMRPM groups showed significant differences. The qRT-PCR results showed that C2CD4A, CERS1, MMP9, SLC5A1, HORMAD2 were highly expressed in the IHH4, KTC-1, and TPC-1 cell lines, while SLITRK2, ARHGEF37, PLP1, RNF223, and F3 were lowly expressed.ConclusionThe TBSMRPM established in this study has a certain value for the prognosis of thyroid cancer and contributes to refine clinicians’ treatment protocols.

Yannan Cao, Yixin Wang, Hang Liu et al.

With the development of artificial intelligence (AI), AI-related technologies are being applied in many fields of medicine. Anesthesia is now widely used in surgery, emergency resuscitation, pain treatment and other fields. However, different from some other common biomedical signals, such as the electrocardiogram (ECG), electroencephalogram (EEG), and some other medical imaging or biomarkers could be easily processed and analyzed by AI-related models, how to collect the relevant data in the anesthesia process is still a challenge, that has led to little current work on combining AI and anesthesia. However, it can be foreseen that the combination of AI and anesthesia will become increasingly important. This paper presents a comprehensive review of anesthesia with AI based methods which have been now used in the preoperative phase, intraoperative phase, and postoperative phase. We first overview some crucial concepts of artificial intelligence, then discuss the related applications of artificial intelligence used in different phases of the anesthesia period, finally, we look forward to the future development of intelligent anesthesia. We hope through this review, we can provide comprehensive and objective guidance in AI-related anesthesia process to help anesthesiologists use more advanced AI techniques to diagnose and treat patients during the anesthesia period.

J. Gammie, Shubin Sheng, B. Griffith et al.

F. Carli, P. Charlebois, B. Stein et al.

Ryo Fujii, Masashi Hatano, Hideo Saito et al.

Surgical phase recognition has gained significant attention due to its potential to offer solutions to numerous demands of the modern operating room. However, most existing methods concentrate on minimally invasive surgery (MIS), leaving surgical phase recognition for open surgery understudied. This discrepancy is primarily attributed to the scarcity of publicly available open surgery video datasets for surgical phase recognition. To address this issue, we introduce a new egocentric open surgery video dataset for phase recognition, named EgoSurgery-Phase. This dataset comprises 15 hours of real open surgery videos spanning 9 distinct surgical phases all captured using an egocentric camera attached to the surgeon's head. In addition to video, the EgoSurgery-Phase offers eye gaze. As far as we know, it is the first real open surgery video dataset for surgical phase recognition publicly available. Furthermore, inspired by the notable success of masked autoencoders (MAEs) in video understanding tasks (e.g., action recognition), we propose a gaze-guided masked autoencoder (GGMAE). Considering the regions where surgeons' gaze focuses are often critical for surgical phase recognition (e.g., surgical field), in our GGMAE, the gaze information acts as an empirical semantic richness prior to guiding the masking process, promoting better attention to semantically rich spatial regions. GGMAE significantly improves the previous state-of-the-art recognition method (6.4% in Jaccard) and the masked autoencoder-based method (3.1% in Jaccard) on EgoSurgery-Phase. The dataset is released at https://github.com/Fujiry0/EgoSurgery.

Nitchanant Kitcharanant, Prangmalee Leurcharusmee, Pichitchai Atthakomol et al.

Abstract Background Even with the great advancements in recent years in total knee arthroplasty (TKA), some patients continue to have persistent postsurgical pain (PPSP). The advantages of systemic corticosteroids in the perioperative context have been further supported by previously published trials. However, the impact of dexamethasone on the intensity of post-TKA PPSP is still unclear. We aimed to investigate its effect on the degree of PPSP and compare that with a placebo. Methods In this randomized, double-blind, placebo-controlled study, 48 patients undergoing unilateral TKA were given intravenous dexamethasone 10 mg or saline just before spinal anesthesia was induced, and they also received two additional doses of dexamethasone 10 mg or saline 24 and 48 h after surgery. A standardized, multimodal analgesic regimen was administered to each patient. The modified WOMAC pain scores at 12 weeks postoperative were the main outcome. The secondary outcomes included pain during a walk of five meters, pain during active knee flexion at 45 degrees, maximum pain at rest during the previous 24 h, nausea visual analogue scale values, and use of rescue opioid and antiemetic medications. Results There was no difference in modified WOMAC pain scores 12 weeks after surgery between patients who received and did not receive perioperative dexamethasone. At 24, 30, 48, 54, and 72 h following surgery, the dexamethasone group experienced considerably less pain during a five-meter walk and during 45 degrees active knee flexion (p < 0.01). At postoperative 0–24, 24–48, and 48–72 h, the dexamethasone group experienced less maximal pain at rest (p < 0.01). The dexamethasone group also had less visual analogue scale scores for nausea at 6, 24, 30, 48, and 54 h after surgery (p < 0.02). During the first 0–24 and 24–48 h, the dexamethasone group consumed fewer opioids and antiemetic medications (p < 0.01). All patients showed no signs of wound complications. Conclusions When compared to a placebo at 12 weeks after TKA, intravenous dexamethasone did not reduce PPSP. Nevertheless, early postoperative pain was relieved by perioperative intravenous dexamethasone, which also decreased the need for opioid and antiemetic medications and decreased postoperative nausea and vomiting. Trial registration NCT02760459.