Fixed Threshold Research Articles

PI-RADS-Based Segmented Threshold of PSMA-PET SUVmax Is Better than Traditional Fixed Threshold for Diagnosing Clinically Significant Prostate Cancer Especially for PI-RADS 3 Lesions.

Our purpose was to compare the performance of prostate-specific membrane antigen (PSMA)-positron emission tomography (PET) traditional fixed threshold (FT) and newly established Prostate Imaging Reporting and Data System (PI-RADS)-based segmented threshold (ST) for diagnosing clinically significant prostate cancer (csPCa). The study retrospectively included 218 patients who underwent multiparametric magnetic resonance imaging (mpMRI) and PSMA-PET examination for suspected prostate cancer (PCa) from January 2018 to November 2021. Lesions with Gleason score ≥ 3 + 4 were diagnosed as csPCa. In PSMA-PET maximum standardized uptake value (SUVmax), the FT for all the lesions and STs for lesions with different PI-RADS score for diagnosing csPCa were determined by receiver operating characteristic (ROC) curves analysis and compared with Z test. The McNemar test was used to compare sensitivity and specificity. Among the 218 patients, there were 113 csPCa and 105 non-csPCa. The PSMA-PET FT was SUVmax > 5.3 (area under the curve, AUC = 0.842) and STs for PI-RADS 3/4/5 were SUVmax > 4.2/5.7/6.0 (AUCs = 0.870/0.867/0.882), respectively. The AUC of PSMA-PET ST was higher than that of PSMA-PET FT (0.872 vs. 0.842), especially for PI-RADS 3 (0.870 vs. 0.653). Multimodality diagnostic criteria combining PSMA-PET ST and PI-RADS scores of mpMRI was established and its AUC was higher than that of PSMA-PET ST (0.893 vs. 0.872) and significantly higher than that of PSMA-PET FT (0.893 vs. 0.842) with an improvement in sensitivity (93% vs. 78%, p < 0.05) without significantly sacrificing specificity (86% vs. 91%, p > 0.05). For diagnosing csPCa, PI-RADS-based PSMA-PET segmented threshold achieved better performance than traditional fixed threshold, especially for PI-RADS 3 lesions. Multimodality diagnostic criteria demonstrated higher diagnostic performance than segmented threshold and significantly better than PSMA-PET fixed threshold for detecting csPCa.

Investigation and optimization of PET-guided SPECT reconstructions for improved radionuclide therapy dosimetry estimates.

To investigate and optimize the SPECTRE (Single Photon Emission Computed Theranostic REconstruction) reconstruction approach, using the hybrid kernelised expectation maximization (HKEM) algorithm implemented in the software for tomographic image reconstruction (STIR) software library, and to demonstrate the feasibility of performing algorithm exploration and optimization in 2D. Optimal SPECTRE parameters were investigated for the purpose of improving SPECT-based radionuclide therapy (RNT) dosimetry estimates. Using the NEMA IEC body phantom as the test object, SPECT data were simulated to model an early and late imaging time point following a typical therapeutic dose of 8 GBq of 177Lu. A theranostic 68Ga PET-prior was simulated for the SPECTRE reconstructions. The HKEM algorithm parameter space was investigated for SPECT-unique and PET-SPECT mutual features to characterize optimal SPECTRE parameters for the simulated data. Mean and maximum bias, coefficient of variation (COV %), recovery, SNR and root-mean-square error (RMSE) were used to facilitate comparisons between SPECTRE reconstructions and OSEM reconstructions with resolution modelling (OSEM_RM). 2D reconstructions were compared to those performed in 3D in order to evaluate the utility of accelerated algorithm optimization in 2D. Segmentation accuracy was evaluated using a 42% fixed threshold (FT) on the 3D reconstructed data. SPECTRE parameters that demonstrated improved image quality and quantitative accuracy were determined through investigation of the HKEM algorithm parameter space. OSEM_RM and SPECTRE reconstructions performed in 2D and 3D were qualitatively and quantitatively similar, with SPECTRE showing an average reduction in background COV % by a factor of 2.7 and 3.3 for the 2D case and 3D case respectively. The 42% FT analysis produced an average % volume difference from ground truth of 158% and 26%, for the OSEM_RM and SPECTRE reconstructions, respectively. The SPECTRE reconstruction approach demonstrates significant potential for improved SPECT image quality, leading to more accurate RNT dosimetry estimates when conventional segmentation methods are used. Exploration and optimization of SPECTRE benefited from both fast reconstruction times afforded by first considering the 2D case. This is the first in-depth exploration of the SPECTRE reconstruction approach, and as such, it reveals several insights for reconstructing SPECT data using PET side information.

Evolutionary generative adversarial network based end-to-end learning for MIMO molecular communication with drift system

Molecular communication (MC) is a novel paradigm for nano-communication networks. Compared with diffusion-based single-input single-out (SISO) systems, multiple-input multiple-output (MIMO) MC with drift systems can effectively mitigate the negative effects of inter symbol interference (ISI), inter link interference (ILI) and noise, further improving transmission efficiency. The modeling complexity of MIMO MC systems inspires the application of deep learning (DL) techniques to establish end-to-end architectures for signal recovery. However, training of the entire end-to-end system is limited by the unknown channel and small training sample size. In this paper, aiming at signal recovery of the newly developed mathematical MIMO MC with drift system model, a Kullback–Leibler divergence (KLD) evolutionary generative adversarial network (EGAN)-based end-to-end learning method is proposed. The end-to-end architecture can be trained offline with both the sampled and fake signals generated by KLD EGAN, even with a small training sample size, and then used to recover online transmitted signals directly. Besides, two traditional detection algorithms denoted as the maximum a posterior (MAP) detector and fixed threshold (FT) detector, are proposed as well for theoretical comparison. Experiments of the effect of different model parameters on the system performance have been carried out. Results validate the effectiveness and robustness of our proposed method compared to other DL-based methods, including the deep neural networks (DNN)-based, the original GAN-based, and the original EGAN-based, in terms of transmission accuracy.

Use of cardiorespiratory coherence to separate spectral bands of the heart rate variability

Abstract Regulation of heart rate variability (HRV) is dependent on the autonomic nervous system (ANS). The regulation is achieved by the two ANS activity branches distribution, namely the parasympathetic and the sympathetic activities. Their fluctuations can be observed in the HRV signal spectral domain through respective dissociated frequency domains. Power spectrum parameters in low frequency (LF) and high frequency (HF) domains are classically estimated using predetermined fixed frequency ranges which are [0.04–0.15 Hz] band for LF domain and [0.15–0.4 Hz] band for HF domain. However, the 0.15 Hz frequency threshold is controversial in dynamic situations or positions changing. Several studies advanced that the observed cardiac and respiratory oscillation interactions could reflect the functionality of the ANS. These interactions can be estimated by the cardiorespiratory spectral coherence tool which quantifies the existence and strength of linearity between the two modes. We propose in this paper to jointly use the heart rate variability (HRV) and respiration modes by exploiting the cardiorespiratory spectral coherence tool for the time-varying frequency threshold definition between LF and HF bands. The instantaneous center frequency computed on the time-frequency coherence estimator is the proposed variable threshold (VT). The VT method was implemented on both simulated data and real data acquired from the experimental orthostatic test protocol with 10 healthy subjects. The classical 0.15 Hz fixed threshold (FT) and the individual time-dependent spectral boundaries method (AT) using the lower limit of the respiratory HF band as a time-varying threshold are used for comparison. The proposed VT strategy makes it possible to obtain: (i) a strengthened data-dependent definition of boundaries for the HF domain; (ii) instantaneous estimations of the LF and HF band energies; (iii) a better discrimination between the two positions SUPINE and UPRIGHT of the classical orthostatic test.

Impact of tumour motion compensation and delineation methods on FDG PET-based dose painting plan quality for NSCLC radiation therapy.

To quantitatively estimate the impact of different methods for both boost volume delineation and respiratory motion compensation of [18F] FDG PET/CT images on the fidelity of planned non-uniform 'dose painting' plans to the prescribed boost dose distribution. Six locally advanced non-small cell lung cancer (NSCLC) patients were retrospectively reviewed. To assess the impact of respiratory motion, time-averaged (3D AVG), respiratory phase-gated (4D GATED) and motion-encompassing (4D MIP) PET images were used. The boost volumes were defined using manual contour (MANUAL), fixed threshold (FIXED) and gradient search algorithm (GRADIENT). The dose painting prescription of 60Gy base dose to the planning target volume and an integral dose of 14Gy (total 74Gy) was discretized into seven treatment planning substructures and linearly redistributed according to the relative SUV at every voxel in the boost volume. Fifty-four dose painting plan combinations were generated and conformity was evaluated using quality index VQ0.95-1.05, which represents the sum of planned dose voxels within 5% deviation from the prescribed dose. Trends in plan quality and magnitude of achievable dose escalation were recorded. Different segmentation techniques produced statistically significant variations in maximum planned dose (P<0.02), as well as plan quality between segmentation methods for 4D GATED and 4D MIP PET images (P<0.05). No statistically significant differences in plan quality and maximum dose were observed between motion-compensated PET-based plans (P>0.75). Low variability in plan quality was observed for FIXED threshold plans, while MANUAL and GRADIENT plans achieved higher dose with lower plan quality indices. The dose painting plans were more sensitive to segmentation of boost volumes than PET motion compensation in this study sample. Careful consideration of boost target delineation and motion compensation strategies should guide the design of NSCLC dose painting trials.

Reliable spectrum sensing scheme based on dual detector with double-threshold for IEEE 802.22 WRAN

In this paper, a reliable spectrum sensing (SS) scheme using dual detectors for IEEE 802.22 WRAN has been presented. In dual or double detectors, first one detector is energy detector (ED) with fixed threshold (FT), while second one is ED with adaptive double threshold (ADT). Numerical results shows that proposed reliable scheme improves detection performance and outperforms the cyclostationary based sensing method and adaptive SS by 12.9% and 15% at −8 dB signal-to-noise ratio (SNR), respectively. It also shows that the proposed scheme takes smaller detection time period than cyclostationary detection and adaptive SS scheme in the order of 5 ms and 0.8 ms at −20 dB SNR, respectively. Moreover, the scheme analyzes in conjunction with cooperative spectrum sensing (CSS) where each CRs work together in order to take final or global decision. It is observed that the proposed sensing scheme with CSS achieves spectrum detection performance in the order of 0.9 for SNR value of as low as −17.5 dB when numbers of CRs are ten.

Estimating population prevalence of potential airflow obstruction using different spirometric criteria: a pooled cross-sectional analysis of persons aged 40–95 years in England and Wales

ObjectivesConsistent estimation of the burden of chronic obstructive pulmonary disease (COPD) has been hindered by differences in methods, including different spirometric cut-offs for impaired lung function. The impact of different...

OP04 Airway Obstruction and All-Cause and Respiratory Mortality: Exploring the Relationship between three Definitions of Obstruction, Smoking using Healths Survey for England and Scottish Health Survey Data

BackgroundDebate continues about the predictive value of different spirometry based definitions of chronic obstructive pulmonary disease (COPD). We explored the hazard of death for three overlapping definitions, and any significant...

An Automated Cirrus Cloud Detection Method for a Ground-Based Cloud Image

Abstract Cloud detection is a basic research for achieving cloud-cover state and other cloud characteristics. Because of the influence of sunlight, the brightness of sky background on the ground-based cloud image is usually nonuniform, which increases the difficulty for cirrus cloud detection, and few detection methods perform well for thin cirrus clouds. This paper presents an effective background estimation method to eliminate the influence of variable illumination conditions and proposes a background subtraction adaptive threshold method (BSAT) to detect cirrus clouds in visible images for the small field of view and mixed clear–cloud scenes. The BSAT algorithm consists of red-to-blue band operation, background subtraction, adaptive threshold selection, and binarization. The experimental results show that the BSAT algorithm is robust for all types of cirrus clouds, and the quantitative evaluation results demonstrate that the BSAT algorithm outperforms the fixed threshold (FT) and adaptive threshold (AT) methods in cirrus cloud detection.

P3-87: Insertable loop recorder R-wave sensing performance is improved with dynamic threshold adjustment

The fixed-threshold (FT) R-wave sensing used in current Insertable Loop Recorders (ILRs) can sometimes cause false auto-recorded arrhythmic episodes due to R-wave undersensing or T-wave oversensing. Our objective was to compare the automatic trigger performance of a dynamic threshold (DT) R-wave sensing method with the existing FT method.