Node Mapping Research Articles

Lymphoscintigraphy is frequently recommended but seldom used in a “real world setting”

ObjectiveLymphedema (LED) lacks a standard, simple, guiding noninvasive diagnostic test, unlike the two other circulatory disorders—arterial or venous disease. Lymphoscintigraphy (LSG) has been recommended by several guidelines as the diagnostic test of choice for LED. Several recent expert panels, however, have suggested from anecdotal experience that LSG was used infrequently, and that the diagnosis of LED is usually based on clinical examination. MethodsTo determine the use of LSG in a large real-world LED population, the International Business Machines MarketScan Research Database was examined from April 2012 to March 2020 for patients with a new diagnosis of LED (the index date). Use of LSG (LSG+) was ascertained during the period beginning 12 months prior to the initial coding of a LED diagnosis and ending 12 months after the index date based on the corresponding Current Procedural Terminology code; LSG use for sentinel node mapping at the time of oncologic surgery was excluded. Demographic profiles, comorbidities, and causes of LED among patients with and without evidence of LSG were characterized. ResultsWe identified 57,674 patients, aged ≥18 years, who had a new diagnosis of LED and health care coverage for ≥12 months before and after this index date. Only a small number (1429; 2.5%) of these patients underwent LSG during the study period. The LSG + cohort was younger (53.7 vs 60.7 years), had a higher proportion of women (91.3% vs 73.4%), but a lower percentage of diabetes (12.8% vs 27.5%), heart failure (2.2% vs 8.7%), hypertension (32.4% vs 51.0%), and obesity (15.1% vs 22.2%) compared with the LED population who did not undergo LSG (all P < .001). Most importantly, the use of LSG for diagnosis varied with the etiology of LED (LSG was most frequently utilized among patients with melanoma-LED (9.5%) and patients with breast cancer-LED (6.7%), in contrast to patients with advanced venous disease-related LED (1.1%; P < .05 for both comparisons). ConclusionsDespite four guidelines recommending LSG, including the Guidelines of the American Venous Forum (Handbook of Venous and Lymphatic Disease-4th edition), which recommended LSG “for the initial evaluation of patients with LED” with a 1B recommendation, LSG plays a minor role in establishing the diagnosis of LED in the United States. This underlines the need for a better, simple diagnostic test for LED to complement clinical examination.

Towards learning-based energy-efficient online coordinated virtual network embedding framework

Network virtualization is a highly effective technology for resource sharing within data centers, enabling the coexistence of multiple heterogeneous virtual networks in a shared substrate network, thus achieving resource multiplexing. The efficient embedding of a virtual network onto a substrate network, known as the virtual network embedding (VNE) problem, has been proven to be NP-hard. In response to this challenge, this paper introduces a novel method, named PPO-VNE, which leverages deep reinforcement learning for virtual network embedding. PPO-VNE employs the Proximal Policy Optimization (PPO) algorithm to generate policies and efficiently coordinate node and link mapping. Furthermore, it adopts a hybrid feature extraction approach that combines handcrafted features with features extracted using graph convolutional networks. The proposed reward function takes multiple objectives into account, guiding the learning process. We implemented a prototype of PPO-VNE and conducted experiments based on the simulation environment, in which the substrate network has 100 nodes, with a probability of 0.1 generating edges between any two node, and eventually there will be about 500 physical links. We evaluate the performance of our PPO-VNE approach from the perspective of overall acceptance rate, overall revenue, revenue-to-cost ratio, maximum energy consumption per unit time and revenue-energy consumption coefficient. Comprehensive simulation results in different scenarios show that our PPO-VNE approach achieves the superior performance on most metrics compared with the existing state-of-the-art approaches, where the overall acceptance rate, overall revenue, revenue-energy consumption coefficient are increased by up to 6.4%, 21.3% and 41.4%, respectively, and the maximum energy consumption per unit time are reduced by up to 22.1%.

Let go of the myth: safety of indocyanine green for sentinel lymph node mapping in endometrial cancer

ObjectiveSentinel lymph node mapping by intracervical indocyanine green injection is the preferred method for surgical staging in endometrial cancer. Adverse reactions to indocyanine green are extremely rare, and information about...

Sentinel lymph node mapping in endometrial cancer: Current evidence and practice.

Surgical staging with total hysterectomy, bilateral salpingo-oophorectomy, and lymph node assessment is the standard of care for patients with clinical early-stage endometrial cancer. Traditionally, complete pelvic and para-aortic lymphadenectomy (LND) was performed to assess for nodal metastases; however, numerous prospective studies have demonstrated that sentinel lymph node biopsy has similar diagnostic accuracy, and is an acceptable alternative to complete LND. This has led to a paradigm shift in endometrial cancer staging.

Predictors of Bilateral SLN Radiocolloid Detection in Endometrial Carcinoma.

Introduction Sentinel lymph node (SLN) mapping is an alternative method to conventional lymphadenectomy for nodal status assessment in patients with stage I/II endometrial carcinoma (EC). This study aimed to analyze the potential predictors of unsuccessful bilateral detection of SLN after the application of radiocolloid in EC. Materials and Methods A prospective, observational, cross-sectional study was performed on 41 patients with EC in preoperative stage I, who underwent SLN mapping after cervical application of 4mCi 99m Tc-SENTI-SCINT. The demographic, clinical, and tumor-related data were obtained from the patient's medical records. Univariate analysis was used to analyze the potential factors associated with an unsuccessful bilateral SLN biopsy. Results The bilateral SLN detection rate of planar lymphoscintigraphy, single photon emission computed tomography/computed tomography, and gamma probe was 29.26, 41.46, and 26.82%, correspondingly. None of the 16 analyzed risk factors showed statistical significance for nonconclusive bilateral SLN biopsy. Conclusion Larger scale studies are needed to determine the exact risk factors for unsuccessful bilateral mapping of the lymphatic drainage after cervical application of the radiotracers. This will eventually lead to improvement in bilateral SLN detection in EC patients, so unilateral lymphadenectomy could be avoided.

A SPECT/NIR Fluorescence Dual-Modality Imaging Agent Composed of Drugs and Hospital Available Isotope for Preoperative Sentinel Lymph Node Mapping and Intraoperative Biopsy.

Sentinel lymph node (SLN) mapping-guided biopsy is crucial for cancer staging and treatment. Optical/nuclide dual-modality imaging agents for mapping SLN are ideal for preoperative planning and intraoperative biopsy, which are enabled by penetration-depth unlimited nuclide imaging and dynamic real-time optical imaging, respectively. However, commonly reported dual-modality imaging agents are composed of novel but safety-unproven materials, making their quick clinical translation challenging. Herein, we report a novel nanoparticle composed of facile hospital-available drugs and isotope for single-photon emission computed tomography (SPECT)/near-infrared (NIR) fluorescence imaging to detect SLNs. Indocyanine green-human serum albumin (ICG-HSA) nanoparticles (NPs) were synthesized by ICG-induced HSA self-assembly and further 99mTc-labeling via a one-step, facile hospital-available method. After injecting 99mTc-ICG-HSA into the rats' forepaw pads, the rats' draining axillary lymph nodes were visualized by preoperative mapping with SPECT/CT and intraoperative biopsy with NIR fluorescence. The axillary lymph nodes of rats were identified by pathology and fluorescent staining after execution. Additionally, its toxicity testing and comparison with 99mTc-sulfur colloid imaging were also explored. The study reported a self-assembled 99mTc-ICG-HSA with a high radiochemical yield (85.6 ± 3.8%). Compared with conventional 99mTc-sulfur colloid, 99mTc-ICG-HSA NPs showed faster SLN identification, higher renal clearance, and lower hepatic retention. Furthermore, NIRF imaging allowed for the accurate visualization of the SLN and guided SLN biopsy intraoperatively. Notably, the 99mTc-ICG-HSA NPs were composed of hospital-available drugs and isotope, which are safe for acute toxicity evaluation by a certified institute. The proposed 99mTc-ICG-HSA NPs are safe and capable of noninvasive SLN identification and biopsy guidance with multi-modal imaging strategies and could be a promising tool for clinically assisted SLN biopsy.

The Novel Use of Magtrace in Chest Masculinizing Transgender Top Surgery

Summary: Chest masculinization is the most common surgery performed in transgender men, and although incidence of occult cancer is lower than in cis-gender women receiving mastectomy or reduction mammoplasties, the incidence of high-risk lesions is comparable. In patients with concerns for occult malignancy, Magtrace is a nonradioactive tracer available to assist management for its delayed sentinel lymph node mapping capabilities. We present the first case report using Magtrace before masculinizing mastectomies in a transgender man.

HTA258 A Hospital-Based Health Technology Assessment of Near-Infrared Fluorescence Using Indocyanine Green for Sentinel Lymph Node Mapping for Breast Cancer and Gynecologic Cancer

HTA258 A Hospital-Based Health Technology Assessment of Near-Infrared Fluorescence Using Indocyanine Green for Sentinel Lymph Node Mapping for Breast Cancer and Gynecologic Cancer

Skin Malignancies: Imaging Review with Radiologic-Histopathologic Correlation.

Skin malignancies are commonly encountered as primary or incidental findings. Neoplasms that affect the skin include primary (basal cell carcinoma, squamous cell carcinoma, melanoma, and Merkel cell carcinoma) and secondary (mesenchymal neoplasms, lymphoma, and metastases) tumors. Imaging provides valuable anatomic information (tumor size, depth of involvement, presence of distant metastasis, and data for guiding biopsy) and functional information (metabolic activity and sentinel node mapping data). This information, in addition to biopsy results, improves the histopathologic characterization of tumors and treatment planning. Various histopathologic types of the same entity exhibit different biologic behavior and have different imaging features. Familiarity with the multimodality imaging features, histopathologic characteristics, and various modes of dissemination (direct invasion; perineural, lymphatic, and hematogenous spread) of the most common skin malignancies helps radiologists narrow the differential diagnosis in clinical practice. ©RSNA, 2023 Supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center.

Virtual Network Embedding Over Multi-Band Elastic Optical Network Based on Cross-Matching Mechanism and Hypergraph Theory

The commercialization of 5G and the explosive emergence of new applications stimulate the exponential growth of network traffic and diversification of services. It is promising to integrate multi-band elastic optical network (MBEON) and network virtualization for large volume traffic transmission and highly diverse services. However, performing virtual network embedding (VNE) for network virtualization over MBEON faces the challenge of severe inter-channel stimulated Raman scattering (ISRS) effect, which complicates the underlying physical layer effect in the substrate network. In this paper, we investigate the ISRS-aware VNE over MBEON, where a cross-matching mechanism is proposed for virtual node mapping (VNM) and a hypergraph is introduced for parallel virtual link mapping (VLM). A lightpath-level integer linear programming model is first formulated. To integrate the cost and availability of VLM, which significantly affect the performance of the VNE under the ISRS effect, into the VNM process, the “virtual node-substrate node” mapping pairs are specifically evaluated through the cross-matching mechanism. Moreover, to tackle the couplings among multiple lightpaths induced by the wide spectrum ISRS effect, hypergraphs are used to model the ISRS effect-aware quality of transmission (QoT) constraints among multiple lightpaths. A hypergraph maximal weight independent set heuristic is presented for lightpath selection, which guarantees the obedience of basic constraints and generates near-optimal solutions. Experimental results show that the proposed methods decrease blocking ratio by more than 30% compared with the benchmarks with similar computational complexity.

Setting-up a training programme for intraoperative molecular imaging and sentinel node mapping: how to teach? How to learn?

The current expansion of image-guided surgery is closely related to the role played by radio-guided surgery in supporting the sentinel node (SN) procedure during more than three decades. The so-called triple approach (lymphoscintigraphy, gamma probe detection and blue dye) was not only essential in the seminal validation of the SN procedure but also a first collective learning effort based on skill transfer and outcome-related evaluation which laid the fundaments to delineate the field of intraoperative molecular imaging (IMI) based on a similar multimodality approach and multidisciplinary practice. These elements are also becoming valid in the current incorporation of SPECT/CT and PET/CT to existing and new protocols of IMI procedures and SN mapping concerning other clinical applications. On the other hand, there is a growing tendency to combine novel modern technologies in an allied role with gamma guidance in the operating room following the development of hybrid tracers and multimodal detection approaches. Against this background, learning initiatives are required for professionals working in this area. This objective has led to a group of European practitioners with large experience in SN mapping and IMI applications to give shape to a programme made up out of specific learning modules aimed to be used as a conductive thread in peripherical or centralised training instances concerning the topic. The presented work, written as a tutorial review, is placed in an available prior-art context and is primarily aimed at medical and paramedical practitioners as well as at hardware and software developers.

Digital marketing program design based on abnormal consumer behavior data classification and improved homomorphic encryption algorithm

This article endeavors to delve into the conceptualization of a digital marketing framework grounded in consumer data and homomorphic encryption. The methodology entails employing GridSearch to harmonize and store the leaf nodes acquired post-training of the CatBoost model. These leaf node data subsequently serve as inputs for the radial basis function (RBF) layer, facilitating the mapping of leaf nodes into the hidden layer space. This sequential process culminates in the classification of user online consumption data within the output layer. Furthermore, an enhancement is introduced to the conventional homomorphic encryption algorithm, bolstering privacy preservation throughout the processing of consumption data. This augmentation broadens the applicability of homomorphic encryption to encompass rational numbers. The integration of the Chinese Remainder Theorem is instrumental in the decryption of consumption-related information. Empirical findings unveil the exceptional generalization performance of the amalgamated model, exemplifying an AUC (area under the curve) value of 0.66, a classification accuracy of 98.56% for online consumption data, and an F1-score of 98.41. The enhanced homomorphic encryption algorithm boasts attributes of stability, security, and efficiency, thus fortifying our proposed solution in facilitating companies’ access to precise, real-time market insights. Consequently, this aids in the optimization of digital marketing strategies and enables pinpoint positioning within the target market.

Enhancing NIR-II Imaging and Photothermal Therapy for Improved Oral Cancer Theranostics by Combining TICT and Aggregation-Induced Emission.

In the treatment process of cancers like oral cancer, it is necessary to employ extensive surgical resection to achieve cancer eradication. However, this often results in damage to crucial functions such as chewing and speaking, leading to a poorer prognosis and a reduced quality of life. To address this issue, a multifunctional theranostic agent named MBPN-T-BTD has been developed by precisely modulating the excitation state energy distribution in the radiative/nonradiative decay pathways using the characteristics of twisted intramolecular charge transfer and aggregation-induced emission. This agent outperforms clinically utilized indocyanine green (ICG) in various aspects, including the second near-infrared window (NIR-II, 1000-1700 nm) fluorescence (FL) and photothermal conversion efficiency (PCE). Its nanoparticle form (BTB NPs) can be effectively used for high-contrast delineation of lymph node mapping and tongue and floor of mouth cancers using NIR-II FL, enabling surgeons to achieve more precise and thorough tumor clearance. For tumors located in close proximity to vital organs such as the tongue, the exceptional PCE (71.96%) of BTB NPs allows for targeted photothermal ablation with minimal damage to peripheral healthy tissues. This contribution provides a safer and more effective paradigm for minimally invasive or noninvasive treatment of oral cancer, ensuring the preservation of normal organ functions and showing potential for improving the overall prognosis and quality of life for cancer patients.

The progress and prospect of sentinel lymph node mapping in endometrial carcinoma

Sentinel lymph node (SLN) refers to the initial site of the lymphatic drainage from a primary tumor area. Identifying the SLN and analyzing tumor involvement can predict the status of the remaining lymph nodes. Accordingly, sentinel lymph node mapping (SLN mapping) has been brought up and widely applied to cancer therapy for its illuminating role in clinical lymph node resection. Sufficient information to guide surgical pathological staging and adjuvant treatment in endometrial cancer can be rendered by SLN mapping, hence minimizing surgery injury and reducing the incidence of complications. Evidence suggests that using SLN mapping does not affect progression-free survival (PFS) and overall survival (OS) of endometrial cancer patients. Furthermore, there is increasing evidence that using SLN mapping has a high detection rate (DR), sensitivity, and negative predictive value (NPV) for patients with early-stage lower-risk endometrial cancer. This review aims to systematically summarize the advances and application prospects of SLN mapping in endometrial cancer, with an expectation of furnishing reference for the clinical application.

Multilayer network alignment based on topological assessment via embeddings

BackgroundNetwork graphs allow modelling the real world objects in terms of interactions. In a multilayer network, the interactions are distributed over layers (i.e., intralayer and interlayer edges). Network alignment (NA) is a methodology that allows mapping nodes between two or multiple given networks, by preserving topologically similar regions. For instance, NA can be applied to transfer knowledge from one biological species to another. In this paper, we present DANTEml, a software tool for the Pairwise Global NA (PGNA) of multilayer networks, based on topological assessment. It builds its own similarity matrix by processing the node embeddings computed from two multilayer networks of interest, to evaluate their topological similarities. The proposed solution can be used via a user-friendly command line interface, also having a built-in guided mode (step-by-step) for defining input parameters.ResultsWe investigated the performance of DANTEml based on (i) performance evaluation on synthetic multilayer networks, (ii) statistical assessment of the resulting alignments, and (iii) alignment of real multilayer networks. DANTEml over performed a method that does not consider the distribution of nodes and edges over multiple layers by 1193.62%, and a method for temporal NA by 25.88%; we also performed the statistical assessment, which corroborates the significance of its own node mappings. In addition, we tested the proposed solution by using a real multilayer network in presence of several levels of noise, in accordance with the same outcome pursued for the NA on our dataset of synthetic networks. In this case, the improvement is even more evident: +4008.75% and +111.72%, compared to a method that does not consider the distribution of nodes and edges over multiple layers and a method for temporal NA, respectively.ConclusionsDANTEml is a software tool for the PGNA of multilayer networks based on topological assessment, that is able to provide effective alignments both on synthetic and real multi layer networks, of which node mappings can be validated statistically. Our experimentation reported a high degree of reliability and effectiveness for the proposed solution.

A multicenter prospective study of lateral neck lymph node mapping in papillary thyroid cancer.

Despite the high incidence of lateral neck lymph node (LN) metastasis in papillary thyroid cancer (PTC), the management of the lateral neck remains controversial. We aimed to map the draining LNs in the lateral neck using carbon nanoparticles and explore its potential in neck evaluation. We conducted a multicenter, prospective study in PTC patients who had non-palpable yet suspicious metastatic lateral LNs on ultrasound and/or computed tomography (CT) but could not be confirmed by fine needle aspiration. Carbon nanoparticle suspension was injected peritumorally into the thyroid and modified lateral neck dissection was subsequently performed. A total of 154 patients were enrolled for analysis. And 5,070 lateral LNs were removed, of which 1,079 (21.3%) were dyed. The median of dyed LNs was 6 per case (range, 1-33). The distribution of dyed LNs in neck compartments was IV > III > IIA > IIB/V, independent of tumor size, location, multifocality or microscopic extra-thyroidal extension (ETE). Compared with undyed LNs, the probabilities of metastasis in dyed LNs were significantly increased in compartment III, IV, V, and II-V (III: 29.3% vs. 15.4%, P<0.001; IV: 26.3% vs. 14.5%, P<0.001; V: 16.7% vs. 3.3%, P=0.005; II-V: 26.3% vs. 10.0%, P<0.001). The relative risks of metastasis in dyed LNs compared with undyed LNs were 1.90, 1.82, 5.04 and 2.62 in compartment III, IV, V, and II-V, respectively. It was the first prospective multicenter study to map the lateral neck LNs with carbon nanoparticles, which could help surgeons visualize the suspicious LNs during surgery. Instead of unguided LN biopsy, this method has a potential role in lateral neck assessment for indeterminate lateral LNs in PTC.

Load-Balanced Virtual Network Embedding Based on Deep Reinforcement Learning for 6G Regional Satellite Networks

Regional satellite networks are capable of supporting denser coverage and more reliable communications in the target area and hence have been viewed as an essential part of the sixth generation (6G) communication system. Since satellite networks are time-varying and have limited resources, efficient resource management schemes are needed to accommodate massive and ubiquitous service requests. As a remedy, virtual network embedding (VNE) can enable diverse virtual network requests (VNRs) to share the same substrate network resources to improve resource utilization. However, existing works are few and mainly rely on heuristic methods, whose static embedding strategies cannot be optimized according to the resource state. In this paper, we propose a deep reinforcement learning (DRL) aided load-balanced VNE algorithm (DRL-LBVNE) for the regional satellite networks, where we first build a low-cost regional satellite network scenario and derive its multi-fold coverage constraints. Besides, we design a novel preprocessing scheme to reduce mapping failure, where the satellite network is divided into multiple mapping regions, and VNRs are only deployed in the mapping region with the lowest load. In the node mapping stage, the DRL agent can calculate the embedding probabilities of each physical node based on the environment state. Moreover, a comprehensive metric for path selection is presented in the link mapping stage. Simulation results show that the DRL-LBVNE algorithm outperforms the other five state-of-art algorithms in acceptance rate, resource utilization, and average delay, reflecting better adaptability to dynamic satellite networks.

Sentinel lymph node mapping: current applications and future perspectives in thyroid carcinoma.

Sentinel lymph node (SLN) mapping is a standard, minimally-invasive diagnostic method in the surgical treatment of many solid tumors, as for example melanoma and breast cancer, for detecting the presence of regional nodal metastases. A negative SLN accurately indicates the absence of metastases in the other regional lymph nodes (LN), thus avoiding unnecessary lymph nodal dissection. Papillary thyroid carcinoma (PTC) is the most common type of thyroid carcinoma (TC) with cervical LN metastases at diagnosis in 20-90%, and nodal involvement correlates with local persistence/recurrence. The SLN in PTC is an intraoperative method for staging preoperative N0 patients and for detecting metastatic LNs "in and outside" the cervical LN central compartment; it represents an alternative method to prophylactic central neck node dissection. In this review we summarize different methods and results of the use of SLN in TC. The SLN identification techniques currently used include the selective vital-dye (VD) method, 99mTc-nanocolloid planar lymphoscintigraphy with intraoperative use of a hand-held gamma probe (LS), the combination LS + VD, and the combination LS and preoperative SPECT-CT (LS + SPECT/CT). The application of the SLN procedure in TC has been described in many studies, however, the techniques are heterogeneous, and the role of SLN in TC, with indications, results, advantages and limits, is still debated.

Fault Tolerance and Node Mapping Algorithm Hierarchical Graph HCN

Embedding in an interconnection network maps the interconnection network G to H and analyzes the relationship between G and H. Hypercubes and toruses are widely known as interconnection networks, and various algorithms have been developed. The HCN graph is a network with a hierarchical structure to improve the network cost of hypercube. In this study, we analyze the fault tolerance and embedding properties of HCN graphs. As a result of the research, the HCN graph has the same node connectivity and degree, so it has the maximum fault tolerance property. In addition, an algorithm that can one-to-one node map the HCN structure to the torus structure was proposed. The embedding results showed that it was possible to embed the torus structure in the HCN graph at an extension rate of 3 and dilation of 1. The results of the embedding study mean that various algorithms developed in Torus can be efficiently used in the HCN structure.

Comparing Surgical and Oncological Outcomes between Indocyanine Green (ICG) Sentinel Lymph Node Mapping with Routine Lymphadenectomy in the Surgical Staging of Early-Stage Endometrioid Endometrial Cancer.

A retrospective single-centre cohort study of patients with early-stage endometrioid endometrial cancer undergoing staging surgery (total hysterectomy, bilateral salpingo-oophorectomy with/without pelvic lymph node, and/or para-aortic lymph node dissection (PLND)) with either SLN mapping or routine lymphadenectomy between July 2017 and December 2018. 203 cases with clinical and radiological International Federation of Gynaecology and Obstetrics (FIGO) stage I endometrioid endometrial cancer were included, out of which 109 cases underwent SLN mapping and 94 cases complete lymphadenectomy. Compared to the PLND group, the SLN group had shorter operative time (129 vs. 162 minutes), less blood loss (100 vs. 300 ml), and decreased length of postoperative hospital stay (3 vs. 4 days) (p < 0.001). The lymph node metastases detection rate was 4.6% and 7.4% for the SLN and PLND groups, respectively (p = 0.389). With a median follow-up of 14 months for the SLN and 15 months for the PLND group, the disease-free (DFS) and overall survival (OS) were comparable for both at 13 months (p = 0.538 and p = 0.333, respectively). SLN mapping has been shown to be an acceptable alternative to routine lymphadenectomy in the surgical staging of early-stage endometrial cancer in our centre, with a comparable lymph node metastases detection rate, DFS and OS, and reduction in operative morbidity. Our results with SLN mapping reproduce comparable outcomes to those reported in the literature.