JSQE: Joint Surveillance Quality and Energy Conservation for Barrier Coverage in WSNs.

Barrier coverage is a fundamental issue in wireless sensor networks (WSNs). Most existing works have developed centralized algorithms and applied the Boolean Sensing Model (BSM). However, the critical characteristics of sensors and environmental conditions have been neglected, which leads to the problem that the developed mechanisms are not practical, and their performance shows a large difference in real applications. On the other hand, the centralized algorithms also lack scalability and flexibility when the topologies of WSNs are dynamically changed. Based on the Elfes Sensing Model (ESM), this paper proposes a distributed Joint Surveillance Quality and Energy Conservation mechanism (JSQE), which aims to satisfy the requirements of the desired surveillance quality and minimize the number of working sensors. The proposed JSQE first evaluates the sensing probability of each sensor and identifies the location of the weakest surveillance quality. Then, the JSQE further schedules the sensor with the maximum contribution to the bottleneck location to improve the overall surveillance quality. Extensive experiment results show that our proposed JSQE outperforms the existing studies in terms of surveillance quality, the number of working sensors, and the efficiency and fairness of surveillance quality. In particular, the JSQE improves the surveillance quality by 15% and reduces the number of awake sensors by 22% compared with the relevant TOBA.

2021 Advocacy Statements for the Role of 99mTc-Pyrophosphate Scintigraphy in the Diagnosis of Transthyretin Cardiac Amyloidosis: A Report of the Taiwan Society of Cardiology and the Society of Nuclear Medicine of the Republic of China.

Transthyretin cardiac amyloidosis (ATTR-CM) is an increasingly recognized cause of heart failure with preserved ejection fraction. Favorable prognosis depends on early diagnosis and correct treatment strategy. Among patients for whom there is a high clinical suspicion of cardiac amyloidosis, 99mTc-labeled bone avid scintigraphy including 99mTc-pyrophosphate (PYP) scintigraphy may be of diagnostic and prognostic importance. Various international guidelines support the non-biopsy diagnosis of ATTR-CM using 99mTc-PYP scintigraphy, yet emphasize the gap in standardization of acquisition and imaging analysis protocols, as well as the appropriateness of its clinical use. Therefore, a joint expert consensus has been reached by the Taiwan Society of Cardiology and the Society of Nuclear Medicine of the Republic of China, to advocate for the application of 99mTc-PYP scintigraphy in the diagnosis of ATTR-CM. This article aims to highlight the recommendations on image acquisition, qualitative and quantitative assessments of cardiac 99mTc-PYP uptake, and diagnostic algorithms. We hope the implementation of these recommendations in Taiwan will facilitate the process and enhance the diagnostic rate of ATTR-CM.

Simplified quantification of 13N-ammonia PET myocardial blood flow: A comparative study with the standard compartment model to facilitate clinical use.

BACKGROUND: Short imaging protocol to quantify myocardial blood flow (MBF) and myocardial flow reserve (MFR) may enhance the clinical application of 13N-ammonia cardiac PET. We assessed the flow quantitation of 13N-ammonia PET implementing simple retention model and two-compartment model. METHODS: Fourteen healthy volunteers (HVT) and twenty-three clinical patients received 13N-ammonia PET/CT. The simple retention model used the first 7-minute image to quantify MBF. Global and regional MBF and MFR of the two models were compared. RESULTS: Global and regional MBF and MFR of these two models were highly correlated with mildly inferior correlation in RCA territory (global R2: rest MBF = 0.79, stress MBF = 0.65, MFR = 0.77; regional R2: rest MBF ≥ 0.72, stress MBF ≥ 0.52, MFR ≥ 0.68). There were significant differences for MFR (4.04 ± 0.72, 3.66 ± 0.48, p = .02) and rest MBF (0.69 ± 0.12, 0.78 ± 0.12, p = .02) between the two models in the HVT group. CONCLUSIONS: 13N-ammonia global and regional MBF and MFR from the simple retention model demonstrate strong correlations with that from the two-compartment model. Significant differences of MFR and rest MBF are noted in the HVT group, with a proposed normal reference value for the 13N-ammonia short simple retention protocol.

Cooperative Data Collection Mechanism Using Multiple Mobile Sinks in Wireless Sensor Networks.

Data collection problems have received much attention in recent years. Many data collection algorithms that constructed a path and adopted one or more mobile sinks to collect data along the paths have been proposed in wireless sensor networks (WSNs). However, the efficiency of the established paths still can be improved. This paper proposes a cooperative data collection algorithm (CDCA), which aims to prolong the network lifetime of the given WSNs. The CDCA initially partitions the n sensor nodes into k groups and assigns each mobile sink acting as the local mobile sink to collect data generated by the sensors of each group. Then the CDCA selects an appropriate set of data collection points in each group and establishes a separate path passing through all the data collection points in each group. Finally, a global path is constructed and the rendezvous time points and the speed of each mobile sink are arranged for collecting data from k local mobile sinks to the global mobile sink. Performance evaluations reveal that the proposed CDCA outperforms the related works in terms of rendezvous time, network lifetime, fairness index as well as efficiency index.

Towards Human Activity Recognition: A Hierarchical Feature Selection Framework.

The inherent complexity of human physical activities makes it difficult to accurately recognize activities with wearable sensors. To this end, this paper proposes a hierarchical activity recognition framework and two different feature selection methods to improve the recognition performance. Specifically, according to the characteristics of human activities, predefined activities of interest are organized into a hierarchical tree structure, where each internal node represents different groups of activities and each leaf node represents a specific activity label. Then, the proposed feature selection methods are appropriately integrated to optimize the feature space of each node. Finally, we train corresponding classifiers to distinguish different activity groups and to classify a new unseen sample into one of the leaf-nodes in a top-down fashion to predict its activity label. To evaluate the performance of the proposed framework and feature selection methods, we conduct extensive comparative experiments on publicly available datasets and analyze the model complexity. Experimental results show that the proposed method reduces the dimensionality of original feature space and contributes to enhancement of the overall recognition accuracy. In addition, for feature selection, returning multiple activity-specific feature subsets generally outperforms the case of returning a common subset of features for all activities.

An Efficient Wireless Recharging Mechanism for Achieving Perpetual Lifetime of Wireless Sensor Networks.

Energy recharging has received much attention in recent years. Several recharging mechanisms were proposed for achieving perpetual lifetime of a given Wireless Sensor Network (WSN). However, most of them require a mobile recharger to visit each sensor and then perform the recharging task, which increases the length of the recharging path. Another common weakness of these works is the requirement for the mobile recharger to stop at the location of each sensor. As a result, it is impossible for recharger to move with a constant speed, leading to inefficient movement. To improve the recharging efficiency, this paper takes "recharging while moving" into consideration when constructing the recharging path. We propose a Recharging Path Construction (RPC) mechanism, which enables the mobile recharger to recharge all sensors using a constant speed, aiming to minimize the length of recharging path and improve the recharging efficiency while achieving the requirement of perpetual network lifetime of a given WSN. Performance studies reveal that the proposed RPC outperforms existing proposals in terms of path length and energy utilization index, as well as visiting cycle.

Multiantenna relay beamforming design for QoS discrimination in two-way relay networks.

This paper investigates the relay beamforming design for quality of service (QoS) discrimination in two-way relay networks. The purpose is to keep legitimate two-way relay users exchange their information via a helping multiantenna relay with QoS guarantee while avoiding the exchanged information overhearing by unauthorized receiver. To this end, we propose a physical layer method, where the relay beamforming is jointly designed with artificial noise (AN) which is used to interfere in the unauthorized user's reception. We formulate the joint beamforming and AN (BFA) design into an optimization problem such that the received signal-to-interference-ratio (SINR) at the two legitimate users is over a predefined QoS threshold while limiting the received SINR at the unauthorized user which is under a certain secure threshold. The objective of the optimization problem is to seek the optimal AN and beamforming vectors to minimize the total power consumed by the relay node. Since the optimization problem is nonconvex, we solve it by using semidefinite program (SDP) relaxation. For comparison, we also study the optimal relay beamforming without using AN (BFO) under the same QoS discrimination constraints. Simulation results show that both the proposed BFA and BFO can achieve the QoS discrimination of the two-way transmission. However, the proposed BFA yields significant power savings and lower infeasible rates compared with the BFO method.

Follow-up Tc-99 m pyrophosphate cardiac scan for patients with transthyretin cardiac amyloidosis treated with tafamidis.

BACKGROUND: Tafamidis has been used for treatment of transthyretin cardiac amyloidosis (ATTR-CA). However, Tc-99 m pyrophosphate (PYP) cardiac scan for follow-up after tafamidis therapy has not been reported. METHODS: From May 2017 to March 2022, five patients with or without tafamidis therapy had received two Tc-99 m PYP cardiac scans. Tc-99 m PYP cardiac scan was performed with planar image and single photon emission computed tomography/computed tomography (SPECT/CT) 3 h after administration of Tc-99 m PYP. Perugini grading system was applied to determine positive or negative result of the scan. Heart to contralateral lung (H/CL) ratio as well as the difference of H/CL ratio between first and second Tc-99 m PYP cardiac scans (ΔH/CL ratio) was calculated. RESULTS: In the five patients participated in this study, three received tafamidis therapy and H/CL ratio was significantly decreased (p = 0.02) after tafamidis therapy. Besides, the ΔH/CL ratio was larger in patients with tafamidis therapy than that in those without tafamidis therapy, albeit not reaching statistical significance (p = 0.2). CONCLUSION: A decrease in H/CL ratio was found after tafamidis therapy in patients with ATTR-CA, albeit the magnitude of changes in the H/CL ratio (ΔH/CL ratio) was not significantly different from that of patients without tafamidis therapy. Future study with larger population might be required to further clarify the effect of tafamidis therapy on myocardial uptake of Tc-99 m PYP. CLINICAL TRIAL REGISTRATION: No clinical trial was conducted in our retrospective study.

EBDC: an energy-balanced data collection mechanism using a mobile data collector in WSNs.

The data collection problem is one of the most important issues in Wireless Sensor Networks (WSNs). Constructing a tree from all sensor nodes to the sink node is the simplest way, but this raises the problem of energy unbalance since the sensors closer to the sink node would have much higher workloads from relaying data. To cope with the energy unbalance problem, a number of mobile-sink mechanisms have been proposed in recent years. This paper proposes an Energy-Balanced Data Collection mechanism, called EBDC, which determines the trajectory of a mobile data collector (or mobile sink) such that the data-relaying workloads of all sensors can be totally balanced. Theoretical analysis and performance evaluation reveal that the proposed EBDC mechanism outperforms the existing approaches in terms of network lifetime and the degree of energy balancing.

Detection of coronary lesions in Kawasaki disease by Scaled-YOLOv4 with HarDNet backbone.

Introduction: Kawasaki disease (KD) may increase the risk of myocardial infarction or sudden death. In children, delayed KD diagnosis and treatment can increase coronary lesions (CLs) incidence by 25% and mortality by approximately 1%. This study focuses on the use of deep learning algorithm-based KD detection from cardiac ultrasound images. Methods: Specifically, object detection for the identification of coronary artery dilatation and brightness of left and right coronary artery is proposed and different AI algorithms were compared. In infants and young children, a dilated coronary artery is only 1-2 mm in diameter than a normal one, and its ultrasound images demonstrate a large amount of noise background-this can be a considerable challenge for image recognition. This study proposes a framework, named Scaled-YOLOv4-HarDNet, integrating the recent Scaled-YOLOv4 but with the CSPDarkNet backbone replaced by the CSPHarDNet framework. Results: The experimental result demonstrated that the mean average precision (mAP) of Scaled-YOLOv4-HarDNet was 72.63%, higher than that of Scaled YOLOv4 and YOLOv5 (70.05% and 69.79% respectively). In addition, it could detect small objects significantly better than Scaled-YOLOv4 and YOLOv5. Conclusions: Scaled-YOLOv4-HarDNet may aid physicians in detecting KD and determining the treatment approach. Because relatively few artificial intelligence solutions about images for KD detection have been reported thus far, this paper is expected to make a substantial academic and clinical contribution.

MOS photodetectors based on Au-nanorod doped graphene electrodes.

By using Au-nanorod (Au-NR) doped graphene as a transparent conducting electrode, Si-based metal-oxide-semiconductor (MOS) photodetectors (PDs) exhibit high external quantum efficiency (EQE) and fast response time. It is found that upon adding Au-NRs to the graphene, a significant increase in EQE is observed for both planar and Si-nanotip (Si-NT) MOS PDs. The planar Si-based MOS PDs reveal a notable photoresponse with an EQE of 49% at the peak wavelength of 530 nm under zero bias and an EQE of 66% at the peak wavelength of 600 nm under - 0.4 V bias. For the Si-NTs MOS PD, it exhibits a relatively high EQE of 71% under - 4 V bias due to the effect of light trapping arising from the nature of the Si-NT array.

Different Pattern of Bone Scintigraphy in Mandibular Osteosarcoma Arising From Fibrous Dysplasia in a Patient With McCune-Albright Syndrome.

McCune-Albright syndrome is a rare condition consisting of triad of fibrous dysplasia, hyperfunctioning endocrinopathy, and café au lait macules of skin. A 31-year-old man was diagnosed with fibrous dysplasia 18 years before presenting with pathologic fracture. No workup for polyostotic fibrous dysplasia was performed at that time. He now presented with left facial swelling and skeletal features of acromegaly. MRI revealed a 15-cm enhancing tumor diagnosed histopathologically as high-grade osteosarcoma. Tc-methylene diphosphonate bone scintigraphy revealed decreased uptake at the tumor site contrary to the usual finding of avid uptake by the neoplastic bone forming tumor.

Fractionated deep-inspiration breath-hold ZTE Compared with Free-breathing four-dimensional ZTE for detecting pulmonary nodules in oncological patients underwent PET/MRI.

The zero echo time (ZTE) technique has improved the detection of lung nodules in PET/MRI but respiratory motion remains a challenge in lung scan. We investigated the feasibility and performance of fractionated deep-inspiration breath-hold (FDIBH) three-dimensional (3D) ZTE FDG PET/MRI for assessing lung nodules in patients with proved malignancy. Sixty patients who had undergone ZTE FDG PET/MRI and chest CT within a three-day interval were retrospectively included. Lung nodules less than 2 mm were excluded for analysis. Two physicians checked the adequacy of FDIBH ZTE and compared the lung nodule detection rates of FDIBH 3D ZTE and free-breathing (FB) four-dimensional (4D) ZTE, with chest CT as the reference standard. FDIBH resolved the effect of respiratory motion in 49 patients. The mean number and size of the pulmonary nodules identified in CT were 15 ± 31.3 per patient and 5.9 ± 4.6 mm in diameter. The overall nodule detection rate was 71% for FDIBH 3D ZTE and 70% for FB 4D ZTE (p = 0.73). FDIBH 3D ZTE significantly outperformed FB 4DZTE in detecting lung base nodules (72% and 68%; p = 0.03), especially for detecting those less than 6 mm (61% and 55%; p = 0.03). High inter-rater reliability for FDIBH 3D ZTE and FB 4D ZTE (k = 0.9 and 0.92) was noted. In conclusion, the capability of FDIBH 3D ZTE in respiratory motion resolution was limited with a technical failure rate of 18%. However, it could provide full expansion of the lung in a shorter scan time which enabled better detection of nodules (< 6 mm) in basal lungs, compared to FB 4D ZTE.

Implicit Irregularity Detection Using Unsupervised Learning on Daily Behaviors.

The irregularity detection of daily behaviors for the elderly is an important issue in homecare. Plenty of mechanisms have been developed to detect the health condition of the elderly based on the explicit irregularity of several biomedical parameters or some specific behaviors. However, few research works focus on detecting the implicit irregularity involving the combination of diverse behaviors, which can assess the cognitive and physical wellbeing of elders but cannot be directly identified based on sensor data. This paper proposes an Implicit IRregularity Detection (IIRD) mechanism that aims to detect the implicit irregularity by developing the unsupervised learning algorithm based on daily behaviors. The proposed IIRD mechanism identifies the distance and similarity between daily behaviors, which are important features to distinguish the regular and irregular daily behaviors and detect the implicit irregularity of elderly health condition. Performance results show that the proposed IIRD outperforms the existing unsupervised machine-learning mechanisms in terms of the detection accuracy and irregularity recall.

BIA: Behavior Identification Algorithm Using Unsupervised Learning Based on Sensor Data for Home Elderly.

Behavior identification plays an important role in supporting homecare for the elderly living alone. In literature, plenty of algorithms have been designed to identify behaviors of the elderly by learning features or extracting patterns from sensor data. However, most of them adopted probabilistic models or supervised learning to identify behaviors based on labeled sensor data. This paper proposes a behavior identification algorithm (BIA) using unsupervised learning based on unlabeled sensor data for the elderly living alone in smart home. This paper presents the observation of elder behaviors with three features: Event Order, Time Length Similarity and Time Interval Similarity features. Based on these features of behavior observations, two properties of behaviors, including the Event Shift and Histogram Shape Similarity properties, are presented. According to these properties, the proposed BIA is developed. Finally, performance results show that the proposed BIA outperforms the existing unsupervised machine learning mechanisms in terms of the behavior identification precision and recall.

Granulomatous disease: is it a nuisance or an asset during PET/computed tomography evaluation of lung cancers?

OBJECTIVES: To evaluate combined PET-computed tomography (CT) criteria for differentiating between granulomatous disease (GD) and malignancy (CA) in oncologic PET-CT studies. METHODS: Sixty-two patients who were referred for fluoro-2-deoxyglucose (FDG) PET-CT evaluation of pulmonary lesion(s) without a history of concurrent infection were studied. PET-CT was performed 1.5 h after intravenous administration of 555 MBq 18F-FDG in the fasting state with oral contrast. Combined PET-CT criteria including (i) calcifications (Ca2+) within lymph nodes, (ii) Ca2+ in lung nodules, (iii) liver and/or spleen Ca2+, (iv) locations of lung lesion(s), (v) hilar FDG uptake, (vi) comparison of lung versus maximum mediastinal FDG uptake, (vii) lymph node uptake not in the most probable lymphatic drainage pathway from a particular lung lesion, and (viii) extra pulmonary abnormal FDG uptake were each assigned a numerical score (0-3) with progressively higher score and sum of scores toward the increasing likelihood of GD. These patients either had pathological confirmation by biopsy/resection or were followed radiographically for a period of 2 years (CA=13; GD=49). Discriminant analysis was performed on all the above criteria with this gold standard. Simple t-test and box plot analysis were also performed on the summation of the scores (from 0 in CA to 13 in GD). RESULTS: When all eight criteria were entered into discriminant analysis, the combined PET-CT criteria classified correctly 71% of patients with a sensitivity of 65% and specificity of 92% for GD. The most significant discriminating criterion was FDG uptake in the lung lesion(s) less than maximum mediastinal uptake (P=0.01). The sum scores in GD and CA were significantly different (4.9+/-2.4 vs. 3.2+/-1.5, respectively, P=0.014). Box plots showed a clear separation at a cut-off value of around 3.5. CONCLUSION: Results show that the set of combined PET-CT criteria are highly specific for GD, which is not necessarily a nuisance during oncologic evaluation. Knowledge of these criteria may attribute some of the abnormal PET findings to GD, which is a useful asset for quick recognition and clinical interpretation.

Detection of multiple myeloma by PET/CT in a patient with colon cancer.

A 76-year-old man with previous sigmoid colon resection for adenocarcinoma had low back pain for 2 months. Whole-body bone scintigraphy showed multiple focal Tc-99m methylene diphosphonate (MDP)-avid lesions in both rib cages and 3 lumbar vertebrae, indicating metastases. F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) imaging was performed for further evaluation of this possible metastatic disease and demonstrated the lumbar and costal metastases and several hypermetabolic areas in the pelvic bones, multiple thoracic vertebrae, both shoulders, and the right femur. Histopathologic examination of the right-sided iliac crest, however, revealed multiple myeloma.

The prognostic value of tumor shadow disappearance rate on integrated PET/CT evaluation of solitary pulmonary nodules with low glucose metabolism.

OBJECTIVE: This study aimed to determine the prognostic value of the tumor shadow disappearance rate (TDR) on integrated PET/computed tomography (PET/CT) evaluation of solitary pulmonary nodules (SPNs) with low glucose uptake. MATERIALS AND METHODS: From January 2008 to September 2010, 99 patients who underwent fluorine-18 fluorodeoxyglucose PET (F-FDG-PET)/CT scanning for the evaluation of SPNs with a maximum standardized uptake value (SUVmax) below 2.75 (2.5+10%) were retrospectively reviewed. Among the 99 SPNs from these patients, 67 were malignant and 32 were benign, based on surgical pathology. Differences in baseline characteristics between the two groups were examined by means of the independent t-test, the Mann-Whitney U-test, and the χ-test. To test the efficacy of TDR for determining malignancy, the sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and positive and negative likelihood ratios (LR+ and LR-, respectively) with 95% confidence intervals were calculated using the pathological test as the gold standard. RESULTS: Patients with malignant nodules were older than those with benign nodules (64.5 vs. 55.1 years, respectively, P<0.001) and had higher TDRs (0.8 vs. 0.3, respectively, P<0.001). The optimal cutoff point for the TDR was 0.4886 where the sensitivity, specificity, positive predictive value, and negative predictive value were 0.851, 0.844, 0.919, and 0.730, respectively, and the LR+ and LR- were 5.443 and 0177, respectively. A significant negative correlation between TDR and SUVmax was found only in the malignant group. CONCLUSION: The diagnostic value of TDR complements the PET/CT evaluation of SPNs with a low F-FDG uptake.

Added Value of Dual-Time-Point 18F-FDG PET/CT With Delayed Imaging for Detecting Aortic Graft Infection: An Observational Study.

F-FDG PET/CT is a promising tool in detecting aortic graft infection. Present study investigated the value of dual-time-point F-FDG PET/CT imaging (DTPI) with delayed imaging in assessing aortic graft infection.Twenty-nine patients with suspected aortic graft infection were prospectively enrolled in this DTPI study. Two nuclear medicine physicians read all the images and achieved consensus about the measurement of maximal standardized uptake value (SUVmax) and grading of image quality. The percentages of SUVmax change between initial and delayed images were recorded as retention index (RI); sensitivity, specificity, and accuracy were calculated based on reference standard.All the 5 infected aortic grafts had positive RIs, which were generally higher than that of noninfected grafts. Those noninfected grafts had variable RIs. Seven patients had improved image quality in delayed imaging. DTPI with delayed image detected all the infected grafts with improved specificity (88%) and accuracy (90%), providing conspicuous delineation of the infected graft extent.In conclusion, noninfected aortic grafts had more variable RIs than infected ones. DTPI might be useful for detecting aortic graft infection, improving image quality, and enhancing delineation of the infected aortic grafts.

Feasibility and incremental benefit of puffed-cheek 18F-FDG PET/CT on oral cancer patients.

PURPOSE: The complexity of small oral cavity and intimate apposition of the oral cavity mucosal surfaces make CT identification of obvious masses difficult. Puffed-cheek CT improves the evaluation of oral cavity lesions. We used the puffed-cheek maneuver with 18F-FDG PET/CT scans to determine the feasibility and accuracy in clinical practice and to identify any benefits. PATIENTS AND METHODS: Twenty-two patients with oral cancer were included. They were instructed to perform the puffed-cheek maneuver after a conventional 18F-FDG PET/CT scan. Two physicians reviewed the puffed-cheek and conventional 18F-FDG PET/CT images and achieved consensus about the cancer extent, location, and dental artifacts before classifying and grading the oral cancers. Dichotomous results of localized or extended cancer and artifact grading scores from the puffed-cheek and conventional 18F-FDG PET/CT methods were compared using McNemar test and the Wilcoxon signed-rank test. P < 0.05 was considered significant. RESULTS: The puffed-cheek maneuver with 18F-FDG PET/CT was practical and had incremental benefits. The conventional 18F-FDG PET/CT classified 12 patients correctly as having localized or extended cancer, and the puffed-cheek 18F-FDG PET/CT classified 21 patients correctly. Puffed-cheek 18F-FDG PET/CT found a synchronous skip cancer and provided detailed cancer delineation. This method might reduce the effects of dental artifacts without undesirable muscular FDG uptake. CONCLUSIONS: Puffed-cheek PET/CT is feasible in the current clinical setting and can improve the delineation of oral cancer extent and location, with a potential benefit of reducing dental artifacts.