Dataset Information

DNA hybridization detection with 100 zM sensitivity using piezoelectric plate sensors with an improved noise-reduction algorithm.

ABSTRACT: We have examined real-time, in situ hybridization detection of target DNA (tDNA) in a buffer solution and in urine using 8 ?m-thick lead magnesium niobate-lead titanate (PMN-PT) piezoelectric plate sensors (PEPSs) about 1.1-1.2 mm long and 0.45 mm wide with improved 3-mercaptopropyltrimethoxysilane (MPS) insulation and a new multiple-parabola (>50) resonance peak position fitting algorithm. With probe DNA (pDNA) immobilized on the PEPS surface and by monitoring the first width extension mode (WEM) resonance frequency shift we detected tDNA in real time at concentration as low as 1 × 10(-19) M in urine (100 zM) with a signal to noise ratio (SNR) of 13 without DNA isolation and amplification at room temperature in 30 min. The present multiple-parabola fitting algorithm increased the detection of SNR by about 10 times compared to those obtained using the raw data and by about 5 times compared to those obtained using single parabola fitting. The detection was validated by in situ follow-up detection and subsequent visualization of fluorescent reporter microspheres (FRMs) coated with reporter DNA complementary to the tDNA but different from the probe pDNA.

SUBMITTER: Kirimli CE

PROVIDER: S-EPMC4971884 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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DNA hybridization detection with 100 zM sensitivity using piezoelectric plate sensors with an improved noise-reduction algorithm.

Kirimli Ceyhun E CE Shih Wei-Heng WH Shih Wan Y WY

The Analyst 20140601 11

We have examined real-time, in situ hybridization detection of target DNA (tDNA) in a buffer solution and in urine using 8 μm-thick lead magnesium niobate-lead titanate (PMN-PT) piezoelectric plate sensors (PEPSs) about 1.1-1.2 mm long and 0.45 mm wide with improved 3-mercaptopropyltrimethoxysilane (MPS) insulation and a new multiple-parabola (>50) resonance peak position fitting algorithm. With probe DNA (pDNA) immobilized on the PEPS surface and by monitoring the first width extension mode (WE ...[more]

PMID: 24759937

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Project description:BackgroundQuantum noise intrinsically limits the quality of fluoroscopic images. The lower is the X-ray dose the higher is the noise. Fluoroscopy video processing can enhance image quality and allows further patient's dose lowering. This study aims to assess the performances achieved by a Noise Variance Conditioned Average (NVCA) spatio-temporal filter for real-time denoising of fluoroscopic sequences. The filter is specifically designed for quantum noise suppression and edge preservation. It is an average filter that excludes neighborhood pixel values exceeding noise statistic limits, by means of a threshold which depends on the local noise standard deviation, to preserve the image spatial resolution. The performances were evaluated in terms of contrast-to-noise-ratio (CNR) increment, image blurring (full width of the half maximum of the line spread function) and computational time. The NVCA filter performances were compared to those achieved by simple moving average filters and the state-of-the-art video denoising block matching-4D (VBM4D) algorithm. The influence of the NVCA filter size and threshold on the final image quality was evaluated too.ResultsFor NVCA filter mask size of 5 × 5 × 5 pixels (the third dimension represents the temporal extent of the filter) and a threshold level equal to 2 times the local noise standard deviation, the NVCA filter achieved a 10% increase of the CNR with respect to the unfiltered sequence, while the VBM4D achieved a 14% increase. In the case of NVCA, the edge blurring did not depend on the speed of the moving objects; on the other hand, the spatial resolution worsened of about 2.2 times by doubling the objects speed with VBM4D. The NVCA mask size and the local noise-threshold level are critical for final image quality. The computational time of the NVCA filter was found to be just few percentages of that required for the VBM4D filter.ConclusionsThe NVCA filter obtained a better image quality compared to simple moving average filters, and a lower but comparable quality when compared with the VBM4D filter. The NVCA filter showed to preserve edge sharpness, in particular in the case of moving objects (performing even better than VBM4D). The simplicity of the NVCA filter and its low computational burden make this filter suitable for real-time video processing and its hardware implementation is ready to be included in future fluoroscopy devices, offering further lowering of patient's X-ray dose.

Project description:PURPOSE:To evaluate the image quality of low-dose chest digital radiographic images obtained with a new spatial noise reduction algorithm, compared to a conventional de-noising technique. MATERIALS AND METHODS:In 69 patients, the dose reduction protocol was divided into A, B, and C test groups- 60% (n = 22), 50% (n = 23), and 40% (n = 24) of the baseline dose. In each patient, baseline dose radiographs were obtained with conventional image processing while low-dose images were acquired with new image processing. A set of baseline and low-dose radiographic images per patient was evaluated and scored on a 5-point scale over seven anatomical landmarks (radiolucency of unobscured lung, pulmonary vascularity, trachea, edge of rib, heart border, intervertebral disc space, and pulmonary vessels in the retrocardiac area) and three representative abnormal findings (nodule, consolidation, and interstitial marking) by two thoracic radiologists. A comparison of paired baseline and low-dose images was statistically analyzed using a non-inferiority test based on the paired t-test or the Wilcoxon signed-rank test. RESULTS:In A, B, and C test groups, the mean dose reduction rate of the baseline radiation dose was 63.4%, 53.9%, and 47.8%, respectively. In all test groups, the upper limit of the 95% confidence interval was less than the non-inferiority margin of 0.5 every seven anatomical landmarks and three representative abnormal findings, which suggested that the image quality of the low-dose image was not inferior to that of the baseline dose image even if the maximum average dose reduction rate was reduced to 47.8% of the baseline dose. CONCLUSION:In our study, an image processing technique integrating a new noise reduction algorithm achieved dose reductions of approximately half without compromising image quality for abnormal lung findings and anatomical landmarks seen on chest radiographs. This feature-preserving, noise reduction algorithm adopted in the proposed engine enables a lower radiation dose boundary for the sake of patient's and radiography technologist's radiation safety in routine clinical practice, in compliance with regulatory guidelines.

Dataset Information

DNA hybridization detection with 100 zM sensitivity using piezoelectric plate sensors with an improved noise-reduction algorithm.

Publications

DNA hybridization detection with 100 zM sensitivity using piezoelectric plate sensors with an improved noise-reduction algorithm.

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