Characteristics of detection accuracy of the patient setup using InBore optical patient positioning system

This study aimed to evaluate the detection accuracy of the AlignRT-InBore system in surface-guided radiation therapy using a phantom and to determine the feasibility of the system by conducting a comparative analysis with cone-beam computed tomography (CBCT) registration. The AlignRT-InBore system integrated with the ETHOS Therapy was used. A phantom and a QUASAR phantom were employed to examine the specific areas of interest relevant to clinical cases. The evaluation involved monitoring translations for approximately 30 min and assessing the position detection accuracy for static and moving objects. Fifty clinical cases were used to evaluate the position detection accuracy and its relationship with the localization accuracy of CBCT before treatment. The detection accuracy of static and moving objects was within 1.0 mm using the phantom. However, the longitudinal direction tended to be larger than the other directions. Regarding the accuracy of localization in clinical cases, a strong and statistically significant (p < 0.01) correlation was observed in each direction. A detection accuracy within 1.0 mm is possible for static and moving objects. The detection accuracy of the patient setup using the InBore optical patient positioning system was extremely high, and the patient could be detected with high precision, suggesting its usefulness.

Detection of Clinically Significant Prostate Cancer Using Targeted Biopsy with Four Cores Versus Target Saturation Biopsy with Nine Cores in Transperineal Prostate Fusion Biopsy: A Prospective Randomized Trial

BACKGROUND

Multiparametric magnetic resonance imaging (mpMRI) and targeted biopsy (TB) facilitate accurate detection of clinically significant prostate cancer (csPC). However, it remains unclear how targeted cores should be applied for accurate diagnosis of csPC.

OBJECTIVE

To assess csPC detection rates for two target-directed MRI/transrectal ultrasonography (TRUS) fusion biopsy approaches, conventional TB and target saturation biopsy (TS).

DESIGN, SETTING, AND PARTICIPANTS

This was a prospective single-center study of outcomes for transperineal MRI/TRUS fusion biopsies for 170 men. Half of the men (n = 85) were randomized to conventional TB with four cores per lesion and half (n = 85) to TS with nine cores. Biopsies were performed by three experienced board-certified urologists.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

PC and csPC (International Society of Urological Pathology grade group ≥2) detection rates for systematic biopsy (SB), TB, and TS were analyzed using McNemar's test for intrapatient comparisons and Fisher's exact test for TS versus TB. A combination of targeted biopsy (TS or TB) and SB served as the reference.

RESULTS AND LIMITATIONS

According to the reference, csPC was diagnosed for 57 men in the TS group and 36 men in the TB group. Of these, TS detected 57/57 csPC cases and TB detected 33/36 csPC cases (p = 0.058). Detection of Gleason grade group 1 disease was 10/12 cases with TS and 8/17 cases with TB (p = 0.055). In addition, TS detected 97% of 63 csPC lesions, compared to 86% with TB (p = 0.1). Limitations include the single-center design, the limited generalizability owing to the transperineal biopsy route, the lack of central review of pathology and radical prostatectomy correlation, and uneven distributions of csPC prevalence, Prostate Imaging-Reporting and Data System (PI-RADS) 5 lesions, men with two or more PI-RADS ≥3 lesions, and prostate-specific antigen density between the groups, which may have affected the results.

CONCLUSIONS

In our study, rates of csPC detection did not significantly differ between TS and TB.

PATIENT SUMMARY

In this study, we investigated two targeted approaches for taking prostate biopsy samples after observation of suspicious lesions on prostate scans. We found that the rates of detection of prostate cancer did not significantly differ between the two approaches.

Dysgraphia disorder forecasting and classification technique using intelligent deep learning approaches

Writing abilities are impacted by dysgraphia, a condition of learning disability. It might be challenging to diagnose dysgraphia at an initial point of a child's upbringing. Problematic abilities linked to Dysgraphia difficulties that is utilized in detecting the learning disorder. The features used in this research to identify dysgraphia include handwriting and geometric features that is reclaimed using kekre-discrete cosine mathematical model. The feature learning step of deep transfer learning makes good use of the obtained features to identify dysgraphia. The results of the data collection indicate that this study can use handwritten images to detect children who have dysgraphia. Compared to past investigations, this experiment has shown a significant improvement in the capacity to identify dysgraphia using handwritten drawings. The proposed approach is compared with the machine learning and deep learning approaches where the Kekre-Discrete Cosine Transform with Deep Transfer Learning (K-DCT-DTL) outperforms the existing approaches. The proposed K-DCT-DTL approach attains 99.75% of highest accuracy that exhibits the efficiency of the proposed method.

An optofluidic Bragg fiber sensor for estimating adulterants in a temperature-dependent molar fraction of hydrated mono-alcohol fuels

Since, chemically complex environments, the aroma has been a difficult task so far. Therefore, in the present communication, an optofluidic Bragg fiber artificial nose for perceiving the temperature-functional molar fraction of an adulterated binary composition of hydrated mono-alcohols is optimized and reported. The task is theoretically predicted over an optofluidic Bragg fiber sensor having geometrical defects by creating an asymmetry in mid of periodic cylindrical Bragg reflectors. In a cylindrical coordinate system, Henkel function (HF) and transfer matrix technique (TMT) are used to simulate a multilayer concentric hollow-core Bragg fiber (HCBF). The variation in refractive index (RI) of the adulterated binary mono-alcohol fuel is connected to the temperature-functional molar concentration, which is again anticipated by making use of several models, including the most suitable Dale-Gladstone, Lorentz-Lorenz, etc. A prominent sensing signal of which has the full width at half maximum (FWHM) equal to 0.1 nm is observed in the examined photonic bandgap (PBG). The signal is responsive to fluctuations in optofluidic core RI in the vicinity of a structural defect layer. The suggested sensor's temperature-dependent maximum sensitivity (due to varied weather circumstances) for ethanol fuel rather than methanol fuel is 1057.32 nm/RIU. Furthermore, the surface plasmon-based static temperature sensor is compared. Due to the smallest FWHM of output signal around 0.1 nm, other sensing performance metrics such as detection accuracy and quality parameters are also enhanced in the proposed sensor device.

Displacement detection with sub-pixel accuracy and high spatial resolution using deep learning

PURPOSE

The purpose of this study was to detect two dimensional and sub-pixel displacement with high spatial resolution using an ultrasonic diagnostic apparatus. Conventional displacement detection methods assume neighborhood uniformity and cannot achieve both high spatial resolution and sub-pixel displacement detection.

METHODS

A deep-learning network that utilizes ultrasound images and output displacement distribution was developed. The network structure was constructed by modifying FlowNet2, a widely used network for optical flow estimation, and a training dataset was developed using ultrasound image simulation. Detection accuracy and spatial resolution were evaluated via simulated ultrasound images, and the clinical usefulness was evaluated with ultrasound images of the liver exposed to high-intensity-focused ultrasound (HIFU). These results were compared to the Lucas-Kanade method, a conventional sub-pixel displacement detection method.

RESULTS

For a displacement within ± 40 µm (± 0.6 pixels), a pixel size of 67 µm, and signal noise of 1%, the accuracy was above 0.5 µm and 0.2 µm, the precision was above 0.4 µm and 0.3 µm, and the spatial resolution was 1.1 mm and 0.8 mm for the lateral and axial displacements, respectively. These improvements were also observed in the experimental data. Visualization of the lateral displacement distribution, which determines the edge of the treated lesion using HIFU, was also realized.

CONCLUSION

Two-dimensional and sub-pixel displacement detection with high spatial resolution was realized using a deep-learning methodology. The proposed method enabled the monitoring of small and local tissue deformations induced by HIFU exposure.

Silicon Nitride-BP-Based Surface Plasmon Resonance Highly Sensitive Biosensor for Virus SARS-CoV-2 Detection

In this study, we propose a surface plasmon resonance (SPR)-based biosensor using silicon nitride (Si₃N₄), black phosphorous (BP), and thiol-tethered DNA as a ligand for fast detection of the SARS-CoV-2 virus. In the proposed biosensor, we have deposited silver (Ag), Si₃N₄, and BP on the base of the BK-7 prism and investigated the performance parameters on the probe in different combinations of the mentioned materials. Herein, three (Ag, Si₃N₄, and BP) different configurations are introduced and compared for the detection of SARS-CoV-2. Furthermore, with the help of the transfer matrix method (TMM), all the three configurations have been analyzed. Notably, the combination of Ag, Si₃N₄, and BP shows better sensitivity (154°/RIU) when compared with other configurations for the detection of SARS-CoV-2. This work may facilitate a new sensing device to detect SARS-CoV-2, based on the hybrid materials.

Recent progress in surface plasmon resonance based sensors: A comprehensive review

In the recent years, researchers have contributed substantially in the field of Surface Plasmon Resonance (SPR) sensors and its applications. SPR sensors show the salient features, such as label-free detection, real-time monitoring, small sample size, furnish accurate outcomes at low cost, and smooth handling. Moreover, the SPR sensors are also well-known because of its quantitative and qualitative excellent performance in real-time applications, including drug discovery, environment monitoring, food safety, medical diagnosis, clinical diagnosis, biological studies, and biomolecule interactions. This paper exhibits a comprehensive review of SPR based sensors, such as prism-based SPR with the applications (e.g., biomolecule interaction, medical diagnostic, etc.), fiber-based SPR, and waveguide-based SPR. Furthermore, we summarized the modern designs and techniques with their limitations and challenges in detail. The erudition outlined in this paper can be given an exceptional benefit for the researchers and industry people in the field of SPR based sensors.

Numerical and analytical study for ultrasonic testing of internal delamination defects considering surface roughness

The improvement of detection accuracy and reliability of micro delamination defect is restricted by the rough surface. The flat bottom holes (FBHs) are frequently employed as reference targets to evaluate the sensitivity of ultrasonic testing for internal defects. A roughness-modified analytical model for ultrasonic testing of FBHs is established based on the principle of multi-Gaussian beam and phase-screen approximation. The signal of reference reflector is obtained from two-dimensional ultrasonic simulation model. The amplitude changes of echo signals and noises of FBHs with different diameters and depths under rough surfaces are presented. The analyses results indicate that the root-mean-square (rms) height plays a dominant role in the amplitude change of signals compared with the correlation length. The reflected wave amplitude of FBHs decreases nonlinearly with an increase of roughness whereas the amplitude of noise increases slightly. Subsequently, a method is proposed further combining the noise amplitude acquired from numerical simulation and the echo signal amplitude obtained by the analytical model, which is to predict and estimate the detection accuracy of internal defects under different surface roughness. The parallel experiments are performed on several samples with different roughness to validate the evaluation method.

Nationwide carrier detection and molecular characterization of β-thalassemia and hemoglobin E variants in Bangladeshi population

Background

ß-thalassemia is one of the most common inherited blood disorders in the world and a major deterrent to the public health of Bangladesh. The management of thalassemia patients requires lifelong frequent blood transfusion and the available treatment options are unsatisfactory. A national policy on thalassemia prevention is mandatory in Bangladesh. However, precise and up-to-date information on the frequency of ß-thalassemia carriers are missing due to lack of accurate diagnostic approaches, limited access to information and absence of national screening program. This study aims to determine the nationwide carrier frequency of hemoglobin E (HbE) and β- thalassemia and mutation spectrum among the carriers using molecular, hematological and biochemical methods.

Methods

The study enrolled a total of 1877 individuals (60.1% male and 39.9% female) aged between 18 and 35 years. Total sample size and its division-wise breakdown were calculated in proportion to national and division-wise population. Venous blood was collected and subjected to CBC analysis and Hb-electrophoresis for each participant. Serum ferritin was measured to detect coexistence of iron deficiency anemia with thalassemia carrier. DNA-based High Resolution Melting (HRM) curve analysis was performed for confirmation of carrier status by mutation detection.

Results

Of 11.89% (95% CI, 10.43–13.35) carriers of β-globin gene mutations, 8.68% (95% CI, 7.41–9.95) had HbE trait (ETT) and 2.24% (95% CI, 1.57–2.91) had beta-thalassemia trait (BTT). Among eight divisions, Rangpur had the highest carrier frequency of 27.1% (ETT-25%, BTT-2.1%), whereas Khulna had the lowest frequency of 4.2% (ETT-4.2% only). Moreover, α- thalassemia, HbD trait, HbE disease, hereditary persistence of HbF were detected in 0.11, 0.16, 0.43 and 0.16% participants, respectively. HRM could identify two individuals with reported pathogenic mutations in both alleles who were erroneously interpreted as carriers by hematological indices. Finally, a total of nine different mutations including a novel mutation (c.151A > G) were detected in the β-globin gene.

Conclusions

Since carrier frequency for both HbE and β-thalassemia is alarmingly high in Bangladesh, a nationwide awareness and prevention program should be made mandatory to halt the current deteriorating situations. Mutation-based confirmation is highly recommended for the inconclusive cases with conventional carrier screening methods to avoid any faulty detection of thalassemia carriers.

Accuracy in Detecting Artificial Root Resorption in Panoramic Radiography versus Tomosynthetic Panoramic Radiographs

INTRODUCTION

The aim of this study was to compare the detection accuracy of panoramic radiography (PAN) and tomosynthetically reconstructed panoramic radiography (TPAN) for the detection of artificial external root resorption in a multiobserver approach.

METHODS

Thirty-six teeth in 5 dry human mandibles were prepared with artificial root resorption by means of diamond bur defects (0.8, 1.0, and 1.2 mm). The samples were exposed in a digital panoramic radiographic unit in a predetermined appropriate position using a wax layer (6.25 mm thickness) as soft tissue scatter equivalent and a water-filled plastic bottle to mimic the absorption of the cervical spine. This resulted in 5 panoramic radiographs and 5 tomosynthetically reconstructed panoramic radiographs, which were evaluated by 13 observers regarding the visibility of artificial root resorption by means of a 5-point confidence scale. Seven of these observers repeated the process after a minimum interval of 30 days. A receiver operating characteristic analysis was conducted with the area beneath the receiver operating characteristic curves (Az) as the main accuracy parameter. Inter- and intrarater reproducibility were calculated by means of the intraclass coefficient using a 2-way random effects model.

RESULTS

The mean Az for TPAN (0.76; median = 0.77; range, 0.70-0.85) was slightly yet significantly higher (P < .05, Wilcoxon test) than for PAN (0.75; median = 0.75; range, 0.69-0.82). The Az values for both methods were highest in the premolar and lowest in the molar region. The mean sensitivity for TPAN was 0.54 (specificity = 0.96) and 0.50 (specificity = 0.96) for PAN. Intraclass coefficient values indicated that intra- (PAN: mean = 0.53 ± 0.088; TPAN: mean = 0.55 ± 0.102; P < .05,Wilcoxon test) and interrater (PAN: mean = 0.47 [0.43-0.51], TPAN: mean = 0.47 [0.42-0.51]) reproducibility were both moderate.

CONCLUSIONS

From our ex vivo study, we observed slightly higher accuracy in the detection of artificial root resorption from tomosynthetically reconstructed panoramic radiographs compared with conventional digital panoramic radiographs.

Improving the signal detection accuracy of functional Magnetic Resonance Imaging

A major drawback of functional Magnetic Resonance Imaging (fMRI) concerns the lack of detection accuracy of the measured signal. Although this limitation stems in part from the neuro-vascular nature of the fMRI signal, it also reflects particular methodological decisions in the fMRI data analysis pathway. Here we show that the signal detection accuracy of fMRI is affected by the specific way in which whole-brain volumes are created from individually acquired brain slices, and by the method of statistically extracting signals from the sampled data. To address these limitations, we propose a new framework for fMRI data analysis. The new framework creates whole-brain volumes from individual brain slices that are all acquired at the same point in time relative to a presented stimulus. These whole-brain volumes contain minimal temporal distortions, and are available at a high temporal resolution. In addition, statistical signal extraction occurred on the basis of a non-standard time point-by-time point approach. We evaluated the detection accuracy of the extracted signal in the standard and new framework with simulated and real-world fMRI data. The new slice-based data-analytic framework yields greatly improved signal detection accuracy of fMRI signals.