Function Technique Research Articles

Prototype data analysis of the dynamics of the Venice gate-barriers during an extreme storm event

The MoSE barriers system was designed and constructed at the inlets of the Venice Lagoon (Italy) in order to limit and tame the flooding events in the Lagoon areas and in the City. The success of the design and operation of the system has been demonstrated by the significant reduction in the number and intensity of floods in the lagoon since its beginning of operations in 2020. In this study, we investigate the dynamical behavior of the MoSE system at full-scale by analyzing the barriers behavior during the severe storm event of November 22nd, 2022. In particular, the dynamical response of the Chioggia barrier to waves and storm surge is studied in detail. Spectral analysis of field records, barrier and inlet modal analyses and Empirical Orthogonal Functions (EOF) techniques are applied to provide a key for interpreting the actual behavior of such a complex system during a storm event, highlighting dominant frequencies and checking for the occurrence of resonance phenomena. First, a brief review of the experimental and theoretical studies carried out over the past forty years is given. Modal patterns of gates oscillations detected via EOF analysis confirm the presence of the eigenmodes of both the barrier and the inlet; however, the gates oscillations during the considered event are mild and the hydraulic performances of the system are satisfactory for the severe event studied. Further field measurements and future severe events should be studied to reach extended conclusions.

Advancing Oncology through Imaging: Evaluating FDG-PET's Role in Cancer Diagnosis and Staging

Purpose: Fluorine-18 fluorodeoxyglucose positron emission tomography (18F-FDG PET) represents a valuable functional molecular imaging technique. Through non-invasive means, 18F-FDG PET allows for the assessment of glucose metabolic activity in living biological systems. Its utility in oncology is well established, with applications in tumor diagnosis, staging, and treatment monitoring. The purpose of this study is to conduct a systematic review assessing the indicative value and effect on the clinical management of 18F-FDG PET/CT for various cancer types based on the current literature. Materials and Methods: An inclusive search of the PubMed, Google Scholar, and Science Direct databases was performed to identify relevant studies published from 2022 to the present. Records were screened according to predefined inclusion and exclusion criteria. A full-text review of the eligible studies was independently conducted by two reviewers. Results: Twenty-one primary research articles met the inclusion criteria and encompassed several cancer types. Evidence demonstrates superior detection, characterization, and staging compared with anatomical imaging alone. Advantages have been substantiated for head/neck, lung, and brain cancers, as well as lymphomas. The significant associations between 18F-FDG uptake and clinical features validated the molecular profiling capacity. Conclusion: 18F-FDG PET provides crucial metabolic tumor information, augmenting conventional approaches. Specific diagnostic values have been established for diverse oncological applications. While technical refinements are ongoing, 18F-FDG PET plays an expanding role in multimodal cancer algorithms according to guidelines. Continued investigation aims to further optimize these techniques and clarify their comparative effectiveness.

Introductory Review of Soft Implantable Bioelectronics Using Conductive and Functional Hydrogels and Hydrogel Nanocomposites.

Interfaces between implantable bioelectrodes and tissues provide critical insights into the biological and pathological conditions of targeted organs, aiding diagnosis and treatment. While conventional bioelectronics, made from rigid materials like metals and silicon, have been essential for recording signals and delivering electric stimulation, they face limitations due to the mechanical mismatch between rigid devices and soft tissues. Recently, focus has shifted toward soft conductive materials, such as conductive hydrogels and hydrogel nanocomposites, known for their tissue-like softness, biocompatibility, and potential for functionalization. This review introduces these materials and provides an overview of recent advances in soft hydrogel nanocomposites for implantable electronics. It covers material strategies for conductive hydrogels, including both intrinsically conductive hydrogels and hydrogel nanocomposites, and explores key functionalization techniques like biodegradation, bioadhesiveness, injectability, and self-healing. Practical applications of these materials in implantable electronics are also highlighted, showcasing their effectiveness in real-world scenarios. Finally, we discuss emerging technologies and future needs for chronically implantable bioelectronics, offering insights into the evolving landscape of this field.

FAStEN: An Efficient Adaptive Method for Feature Selection and Estimation in High-Dimensional Functional Regressions

Functional regression analysis is an established tool for many contemporary scientific applications. Regression problems involving large and complex data sets are ubiquitous, and feature selection is crucial for avoiding overfitting and achieving accurate predictions. We propose a new, flexible and ultra-efficient approach to perform feature selection in a sparse high dimensional function-on-function regression problem, and we show how to extend it to the scalar-on-function framework. Our method, called FAStEN, combines functional data, optimization, and machine learning techniques to perform feature selection and parameter estimation simultaneously. We exploit the properties of Functional Principal Components and the sparsity inherent to the Dual Augmented Lagrangian problem to significantly reduce computational cost, and we introduce an adaptive scheme to improve selection accuracy. In addition, we derive asymptotic oracle properties, which guarantee estimation and selection consistency for the proposed FAStEN estimator. Through an extensive simulation study, we benchmark our approach to the best existing competitors and demonstrate a massive gain in terms of CPU time and selection performance, without sacrificing the quality of the coefficients’ estimation. The theoretical derivations and the simulation study provide a strong motivation for our approach. Finally, we present an application to brain fMRI data from the AOMIC PIOP1 study. Complete FAStEN code is provided at https://github.com/IBM/funGCN. Supplementary materials for this article are available online.

Advances in Imaging for Metastatic Epidural Spinal Cord Compression: A Comprehensive Review of Detection, Diagnosis, and Treatment Planning.

Metastatic epidural spinal cord compression (MESCC) is a critical oncologic emergency caused by the invasion of metastatic tumors into the spinal epidural space, leading to compression of the spinal cord. If not promptly diagnosed and treated, MESCC can result in irreversible neurological deficits, including paralysis, significantly impacting the patient's quality of life. Early detection and timely intervention are crucial to prevent permanent damage. Imaging modalities play a pivotal role in the diagnosis, assessment of disease extent, and treatment planning for MESCC. Magnetic resonance imaging (MRI) is the current gold standard due to its superior ability to visualize the spinal cord, epidural space, and metastatic lesions. However, recent advances in imaging technologies have enhanced the detection and management of MESCC. Innovations such as functional MRI, diffusion-weighted imaging (DWI), and hybrid techniques like positron emission tomography-computed tomography (PET-CT) and PET-MRI have improved the accuracy of diagnosis, particularly in detecting early metastatic changes and guiding therapeutic interventions. This review provides a comprehensive analysis of the evolution of imaging techniques for MESCC, focusing on their roles in detection, diagnosis, and treatment planning. It also discusses the impact of these advances on clinical outcomes and future research directions in imaging modalities for MESCC. Understanding these advancements is critical for optimizing the management of MESCC and improving patient prognosis.

Asymptotic safe nonassociative quantum gravity with star R-flux products, Goroff–Sagnotti counter-terms, and geometric flows

Nonassociative modifications of general relativity, GR, defined by star products with R-flux deformations in string gravity consist an important subclass of modified gravity theories, MGTs. A longstanding criticism for elaborating quantum gravity, QG, argue that the asymptotic safety does not survive once certain perturbative terms (in general, nonassociative and noncommutative) are included in the projection space. The goal of this work is to prove that a generalized asymptotic safety scenario allows us to formulate physically viable nonassociative QG theories using effective models defined by generic off-diagonal solutions and nonlinear symmetries in nonassociative geometric flow and gravity theories. We elaborate on a new nonholonomic functional renormalization techniques with parametric renormalization group, RG, flow equations for effective actions supplemented by certain canonical two-loop counter-terms. The geometric constructions and quantum deformations are performed for nonassociative phase spaces modelled as R-flux deformed cotangent Lorentz bundles. Our results prove that theories involving nonassociative modifications of GR can be well defined both as classical nonassociative MGTs and QG models. Such theories are characterized by generalized G. Perelman thermodynamic variables which are computed for certain examples of nonassociative geometric and RG flows.

A Novel Directed Seed-Based Connectivity Analysis Toolbox Applied to Human and Marmoset Resting-State fMRI

Estimating the direction of functional connectivity (FC) can help to further elucidate complex brain function. However, the estimation of directed FC at the voxel level in fMRI data, and evaluating its performance, has yet to be done. We therefore developed a novel directed seed-based connectivity analysis (SCA) method based on normalized pairwise Granger causality that provides greater detail and accuracy over ROI-based methods. We evaluated its performance against 145 cortical retrograde tracer injections in male and female marmosets that were used as ground truth cellular connectivity on a voxel-by-voxel basis. The ROC curve was calculated for each injection, and we achieved AUC (Area Under the ROC Curve) of 0.95 for undirected and 0.942 for directed SCA in the case of high cell count threshold. This indicates that SCA can reliably estimate the strong cellular connections between voxels in fMRI data. We then used our directed SCA method to analyze the human default mode network (DMN) and found that dlPFC (dorsolateral prefrontal cortex) and temporal lobe were separated from other DMN regions, forming part of the language-network that works together with the core DMN regions. We also found that the cerebellum (Crus I & II) was strongly targeted by the posterior parietal cortices and dlPFC, but reciprocal connections were not observed. Thus, the cerebellum may not be a part of, but instead a target of, the DMN and language-network. Summarily, our novel directed SCA method, visualized with a new functional flat mapping technique, opens a new paradigm for whole-brain functional analysis.Significant StatementWe developed a novel directed seed-based connectivity analysis (SCA) method. To evaluate its performance, we used 145 retrograde tracer injections into the common marmoset left cortex as ground truth cellular connectivity. These were compared with directed and undirected SCA on a voxel-by-voxel basis. We achieved AUC=0.95 for undirected and AUC=0.942 for directed SCA, thus SCA can estimate strong cellular connections with high accuracy. Then, we analysed the human default mode network (DMN) with directed SCA and found that the dorsolateral prefrontal cortex and temporal lobe were not part of the DMN, but part of the language network. Secondly, our analysis showed that the cerebellum may not be part of, but instead a target of, the DMN and language network.

Blockchain-based conditional privacy-preserving authentication scheme using PUF for vehicular ad hoc networks

Vehicular ad hoc networks (VANET) have been the key indispensable module of the future intelligent transportation system. Security and privacy are two essential attributes that protect the safe driving of vehicles. Over the last two decades, numerous conditional privacy-preserving authentication schemes have been presented for the VANET environment. However, existing schemes have various limitations, including security issues, high storage overhead, and frequent interactions. In order to bridge these difficulties, this work combines physically unclonable function and blockchain technology to construct a conditional privacy-preserving authentication scheme for the VANET environment. Specifically, we combine physical unclonable function and dynamic pseudonym techniques to generate unique pseudonym IDs dynamically and private keys using physical unclonable function to enhance privacy protection and resist physical attack. To reduce the number of communication rounds during the verification process, we deployed lightweight blockchain nodes to avoid direct communication between the receiver and the blockchain network. The proposed scheme demonstrates resilience against various potential attacks through comprehensive security analysis and proof. Furthermore, performance metrics indicate that our scheme outperforms similar schemes, making it suitable for resource-constrained VANET.

The ab initio study of n-type nitrogen and gallium co-doped diamond

Abstract In order to better understand the influence of different complexes on the diamond co-doping system, N and Ga are chosen as co-dopants in diamond. The properties of several substitutional NmGan (m+n <= 3) complexes with vacancy (Va) in the bulk diamond have been investigated by ab initio density functional technique, including their optimized lattice structures, formation energies, binding energies and thermodynamic transition levels. The calculational results show that NmGan complexes in the donor-acceptor-donor (DAD) configuration can provide ionization energies similar to phosphorus-doped diamond. All other complexes provide deep impurity levels. For the DAD configuration, the adsorption process on the diamond surface has been studied to demonstrate the feasibility of growing diamonds containing N-Ga-N in experiments. The desired complex configuration is not uniquely present in the co-doped system. Investigating these properties of different complexes beyond NGaN provides insight into the N and Ga codoped diamond system, yielding a more comprehensive understanding of its potential and limitations. Our research ideas can also be extended to other co-doped systems and help to evaluate other potential co-dopants for diamond.

Simulation and experimental study of tool passivation based on magnetic elastic abrasive particles

The presence of micro-cracks and serrations on the tool often leads to its premature failure. However, these microscopic defects can be mitigated through passivation treatment of the tool. Magnetoelastic abrasive particles are new composite particles formed by using abrasive phase particles, magnetic media phase particles and polymer matrix according to a certain ratio, the abrasive particles have both viscoelasticity and magnetic conductivity. The introduction of magnetoelastic abrasive grains into the dual-disk tool passivation equipment can effectively improve the surface quality of the tool and increase the passivation efficiency. At the outset, a model for tool passivation was crafted employing the ABAQUS simulation software. This model aimed to evaluate the effects of diverse passivation variables on the stress levels, the shape of the impact, and the depth of the impact experienced by the tool. Subsequently, by applying statistical theory combined with fitting function techniques, a mathematical model was constructed to determine the passivation volume of the tool subjected to multiple magnetic elastic abrasive particles. This model was then used to examine the impact count and passivation volume associated with each passivation factor. Finally, a tool passivation experiment was conducted using a dual-disk magnetic tool passivation device. The results showed that the smaller the impact velocity of magnetic elastic abrasive particles, the stress and impact depth of the cutting tool are decreasing, and the deformation of the cutting edge is caused by compressive stress. The error of impact depth calculated by simulation and mathematical model is within 20 %, which proves that the mathematical model can better calculate the impact depth of magnetic elastic abrasive particles on the cutting edge of the tool.

Label-free functional imaging of vagus nerve stimulation-evoked potentials at the cortical surface

Vagus nerve stimulation (VNS) is an FDA-approved stimulation therapy to treat patients with refractory epilepsy. In this work, we use a coherent holographic imaging system to characterize vagus nerve-evoked potentials (VEPs) in the cortex in response to VNS stimulation paradigms without electrode placement or any genetic, structural, or functional labels. We analyze stimulation amplitude up to saturation, pulse width up to 800 μs, and frequency from 10 Hz to 30 Hz, finding that stimulation amplitude strongly modulates VEPs response magnitude (effect size 0.401), while pulse width has a moderate modulatory effect (effect size 0.127) and frequency has almost no modulatory effect (effect size 0.009) on the evoked potential magnitude. We find mild interactions between pulse width and frequency. This non-contact label-free functional imaging technique may serve as a non-invasive rapid-feedback tool to characterize VEPs and may increase the efficacy of VNS in patients with refractory epilepsy.

Propofol disrupts the functional core-matrix architecture of the thalamus in humans

Research into the role of thalamocortical circuits in anesthesia-induced unconsciousness is difficult due to anatomical and functional complexity. Prior neuroimaging studies have examined either the thalamus as a whole or focused on specific subregions, overlooking the distinct neuronal subtypes like core and matrix cells. We conducted a study of heathy volunteers and functional magnetic resonance imaging during conscious baseline, deep sedation, and recovery. We advanced the functional gradient mapping technique to delineate the functional geometry of thalamocortical circuits, within a framework of the unimodal-transmodal functional axis of the cortex. Here we show a significant shift in this geometry during deep sedation, marked by a transmodal-deficient geometry. This alteration is closely linked to the spatial variations in the matrix cell composition within the thalamus. This research bridges cellular and systems-level understanding, highlighting the crucial role of thalamic core–matrix functional architecture in understanding the neural mechanisms of states of consciousness.

The Role of Predictive and Prognostic MRI-Based Biomarkers in the Era of Total Neoadjuvant Treatment in Rectal Cancer.

The role of magnetic resonance imaging (MRI) in rectal cancer management has significantly increased over the last decade, in line with more personalized treatment approaches. Total neoadjuvant treatment (TNT) plays a pivotal role in the shift from traditional surgical approach to non-surgical approaches such as 'watch-and-wait'. MRI plays a central role in this evolving landscape, providing essential morphological and functional data that support clinical decision-making. Key MRI-based biomarkers, including circumferential resection margin (CRM), extramural venous invasion (EMVI), tumour deposits, diffusion-weighted imaging (DWI), and MRI tumour regression grade (mrTRG), have proven valuable for staging, response assessment, and patient prognosis. Functional imaging techniques, such as dynamic contrast-enhanced MRI (DCE-MRI), alongside emerging biomarkers derived from radiomics and artificial intelligence (AI) have the potential to transform rectal cancer management offering data that enhance T and N staging, histopathological characterization, prediction of treatment response, recurrence detection, and identification of genomic features. This review outlines validated morphological and functional MRI-derived biomarkers with both prognostic and predictive significance, while also exploring the potential of radiomics and artificial intelligence in rectal cancer management. Furthermore, we discuss the role of rectal MRI in the 'watch-and-wait' approach, highlighting important practical aspects in selecting patients for non-surgical management.

Research on the application of AHP-FAST-FBS in the design of home entrance disinfection devices in the post-pandemic era

With the outbreak and continued spread of the COVID-19 pandemic, people's demand for daily disinfection products has increased rapidly, and its innovative design has received widespread attention. In this context, this study aims to propose a design methodology for home entrance disinfection devices based on AHP-FAST-FBS. Firstly, the design requirements of the home entrance disinfection device were collected and analyzed through in-depth interviews and the KJ method, and a hierarchical model of design demand indicators was constructed. Secondly, the Analytical Hierarchy Process (AHP) was employed to quantify these design demand indicators, and core design demands for home entrance disinfection devices were identified by weight calculations. On this basis, the Functional Analysis System Technique (FAST) method was combined to rationally transform the design demands into product functional indicators, constructing a functional system model for the home entrance disinfection device through systematic decomposition and categorization. Lastly, based on the Function-Behavior-Structure (FBS) theoretical model, the mapping of each function of the product to its structure was realized, the product structure modules were determined, and the comprehensive design and output of the innovative design scheme for the home entrance disinfection device were completed. The results of this study indicate that the design methodology combining AHP-FAST-FBS can effectively improve the scientific rigor and effectiveness of the home entrance disinfection device design, thereby generating an ideal product design scheme. This study provides systematic theoretical guidance and practical reference for designers of subsequent related disinfection products and also offers a new path for improving social health and safety.

Integrated Fault-Tolerant Control Design With Sampled-Output Measurements for Interval Type-2 Takagi-Sugeno Fuzzy Systems.

This article is concerned with the integrated design of fault estimation (FE) and fault-tolerant control (FTC) for uncertain nonlinear systems suffering from actuator faults and external disturbance. The uncertain nonlinear systems are characterized as the interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy model, and IT2 membership functions are employed to effectively handle uncertainties. A fuzzy observer, utilizing only sampled-output measurements, is applied to simultaneously estimate actuator faults and system states. Based on the estimation, the fault-tolerant controller is designed to ensure the system stability under a predefined H∞ performance. The sampling behavior complicates the system dynamics and makes the integrated FTC design more challenging. To confront this issue, the discontinuous Lyapunov functional technique is exploited to enhance stability results by considering the sampling characteristic, upon which FE and FTC units are co-designed in the linear matrix inequality (LMI) framework. To further relax stability criteria, the analysis process incorporates the bound information of membership functions through the membership-function-dependent (MFD) method. Additionally, the relationship of mismatched premise variables resulting from the sampling scheme is also taken into account. Moreover, considering the imperfect premise matching (IPM) framework, the proposed fault-tolerant controller provides greater flexibility in selecting the shapes of membership functions and number of fuzzy rules that can vary from the counterpart of the fuzzy system. Finally, the efficacy of the proposed FTC technique is validated through a detailed numerical example.

Advancements in optical biosensing techniques: From fundamentals to future prospects

Optical biosensors that consist of a light source, optical elements, and a photodetector are used to detect chemical and biological species and pollutants. This Tutorial discusses the fundamental details of optical biosensing techniques that include materials, working principle, components, sensor configurations, parameters, and future prospects. Optical biosensing techniques include plasmonic [surface plasmon resonance (SPR) and localized SPR], fluorescence, luminescence, Raman scattering, colorimetric, and interferometric methods. Bioreceptor elements play a significant role in detecting the specific analyte that can be synthetic or natural. Surface functionalization techniques to bind the bioreceptor elements on the surface, to control the bioreceptor orientation, have been discussed in detail. The possibility of integration of techniques on a chip, to develop wearable, implantable sensors, and the associated challenges have been fully demonstrated. This Tutorial provides valuable insights into the present state and future directions of optical biosensors for various applications.

ESPRESSO reveals blueshifted neutral iron emission lines on the dayside of WASP-76 b

Context. Ultra hot Jupiters (gas giants with Teq > 2000 K) are intriguing exoplanets due to the extreme physics and chemistry present in their atmospheres. Their torrid daysides can be characterised using ground-based high-resolution emission spectroscopy. Aims. We search for signatures of neutral and singly ionised iron (Fe I and Fe II, respectively) in the dayside of the ultra hot Jupiter WASP-76 b, as these species were detected via transmission spectroscopy in this exoplanet. Furthermore, we aim to confirm the existence of a thermal inversion layer, which has been reported in previous studies, and attempt to constrain its properties. Methods. We observed WASP-76 b on four epochs with ESPRESSO at the VLT, at orbital phases shortly before and after the secondary transit, when the dayside is in view. We present the first analysis of high-resolution optical emission spectra for this exoplanet. We compare the data to synthetic templates created with petitRADTRANS, using cross-correlation function techniques. Results. We detect a blueshifted (−4.7 ± 0.3 km s−1) Fe I emission signature on the dayside of WASP-76 b at 6.0σ. The signal is detected independently both before and after the eclipse, and it is blueshifted in both cases. The presence of iron emission features confirms the existence of a thermal inversion layer. Fe II was not detected, possibly because this species is located in the upper layers of the atmosphere, which are more optically thin. Thus the Fe II signature on the dayside of WASP-76 b is too weak to be detected with emission spectroscopy. Conclusions. We propose that the blueshifted Fe I signature is created by material rising from the hot spot to the upper layers of the atmosphere, and discuss possible scenarios related to the position of the hotspot. This work unveils some of the dynamic processes ongoing on the dayside of the ultra hot Jupiter WASP-76 b through the analysis of the Fe I signature from its atmosphere, and complements previous knowledge obtained from transmission studies. It also highlights the ability of ESPRESSO to probe the dayside of this class of exoplanets.

Resonant tunneling via the corner states in the double-barrier-modulated second-order topological insulator

In this work, we use the Green's function technique and investigate transport properties of the electronic states in the two-dimensional (2D) second-order topological insulator (TI). We calculated the bulk, edge, and corner states corresponding respectively to the infinite plane, one-dimensional nanoribbon, and the square flake geometries of the 2D second-order TI. Existence of the corner states in the square flake is confirmed. In this approach, we considered tunneling via the localized corner states in the double-barrier-modulated 2D second-order TI. Sharp peaks are found in the transmission probability and conductance incurred by the corner states lying within the surrounding energy gap. The relation between transmission peaks and the corner states is confirmed by their energy correspondence. The extremely discrete and sharp resonance might lend insight to experimental observation of the corner states in the 2D second-order TI.

Magnetostrictive assisted free and forced vibration response of layered functionally graded circular plate with effect of prestress

One of the optimization requirements for improving the performance of magnetostrictive materials is prestress, which improves the magnetostriction coefficient. The influence of prestress on the fundamental frequencies and vibration suppression of a smart functionally graded circular plate is examined in the current work. The coupled differential equations regulating the motion are derived using Hamilton’s principle. This paper proposes using Kerr’s foundation as a flexible support structure for the disc braking system assembly. The Dirac-delta function and differential quadrature technique have been used to quantitatively simulate the forced vibration behaviour of a circular plate under moving loads. The accuracy and validity of the method used are tested by comparing numerical results to those that have already been published.

Intravoxel incoherent motion diffusion-weighted imaging in evaluating preoperative staging of esophageal squamous cell carcinoma

BackgroundThe aim of this research is to prospectively investigate the diagnostic performance of intravoxel incoherent motion (IVIM) using the integrated slice-specific dynamic shimming (iShim) technique in staging primary esophageal squamous cell carcinoma (ESCC) and predicting presence of lymph node metastases from ESCC.MethodsSixty-three patients with ESCC were prospectively enrolled from April 2016 to April 2019. MR and IVIM using iShim technique (b = 0, 25, 50, 75, 100, 200, 400, 600, 800 s/mm2) were performed on 3.0T MRI system before operation. Primary tumour apparent diffusion coefficient (ADC) and IVIM parameters, including true diffusion coefficient (D), pseudodiffusion coefficient (D*), pseudodiffusion fraction (f) were measured by two independent radiologists. The differences in D, D*, f and ADC values of different T and N stages were assessed. Intraclass correlation coefficients (ICCs) were calculated to evaluate the interobserver agreement between two readers. The diagnostic performances of D, D*, f and ADC values in primary tumour staging and prediction of lymph node metastasis of ESCC were determined using receiver operating characteristic (ROC) curve analysis.ResultsThe inter-observer consensus was excellent for IVIM parameters and ADC (D: ICC = 0.922; D*: ICC = 0.892; f: ICC = 0.948; ADC: ICC = 0.958). The ADC, D, D* and f values of group T1 + T2 were significantly higher than those of group T3 + T4a [ADC: (2.55 ± 0.43) ×10− 3 mm2/s vs. (2.27 ± 0.40) ×10− 3 mm2/s, t = 2.670, P = 0.010; D: (1.82 ± 0.39) ×10− 3 mm2/s vs. (1.53 ± 0.33) ×10− 3 mm2/s, t = 3.189, P = 0.002; D*: 46.45 (30.30,55.53) ×10− 3 mm2/s vs. 32.30 (18.60,40.95) ×10− 3 mm2/s, z=-2.408, P = 0.016; f: 0.45 ± 0.12 vs. 0.37 ± 0.12, t = 2.538, P = 0.014]. The ADC, D and f values of the lymph nodes-positive (N+) group were significantly lower than those of lymph nodes-negative (N0) group [ADC: (2.10 ± 0.33) ×10− 3 mm2/s vs. (2.55 ± 0.40) ×10− 3 mm2/s, t=-4.564, P < 0.001; D: (1.44 ± 0.30) ×10− 3 mm2/s vs. (1.78 ± 0.37) ×10− 3 mm2/s, t=-3.726, P < 0.001; f: 0.32 ± 0.10 vs. 0.45 ± 0.11, t=-4.524, P < 0.001]. The combination of D, D* and f yielded the highest area under the curve (AUC) (0.814) in distinguishing group T1 + T2 from group T3 + T4a. D combined with f provided the highest diagnostic performance (AUC = 0.849) in identifying group N + and group N0 of ESCC.ConclusionsIVIM may be used as an effective functional imaging technique to evaluate preoperative stage of primary tumour and predict presence of lymph node metastases from ESCC.