Published: Jan. 1, 2024
Language: Английский
Photoacoustics, Journal Year: 2023, Volume and Issue: 35, P. 100579 - 100579
Published: Dec. 2, 2023
Peripheral arterial disease (PAD) leads to chronic vascular occlusion and results in end organ damage critically perfused limbs. There are currently no clinical methods available determine the muscular induced by mal-perfusion. This monocentric prospective cross-sectional study investigated n = 193 adults, healthy severe PAD, order quantify degree of calf muscle degeneration caused PAD using a non-invasive hybrid ultrasound single wavelength optoacoustic imaging (US/SWL-OAI) approach. While US provides morphologic information, SWL-OAI visualizes absorption pulsed laser light resulting sound waves from molecules undergoing thermoelastic expansion. US/SWL-OAI was compared multispectral data, severity, angiographic findings, phantom experiments, histological examinations biopsies. We were able show that synergistic use is most likely map progressive PAD.
Language: Английский
Citations
10
Communications Medicine, Journal Year: 2025, Volume and Issue: 5(1)
Published: March 25, 2025
Abstract Background Peripheral arterial disease (PAD) affects more than 200 million people worldwide, with symptoms ranging from none to severe. Despite these different diagnostic options, patients unclear leg pain remain challenging diagnose. The primary objective of this study was evaluate whether multispectral optoacoustic tomography (MSOT) can discriminate between healthy volunteers (HV) and intermittent claudication (IC) by assessing hemoglobin-related biomarkers in calf muscle tissue. Method In monocentric, cross-sectional, observational trial (NCT05373927) n = 102 were included two independent derivation (DC, 51) validation cohorts (VC, 51). MSOT performed before after standardized heel raise provocation compared PAD diagnostics including pulse palpation, ankle brachial index (ABI), duplex sonography, 6-minute walk test (6MWT), assessment health-related quality life (VASCUQOL-6), angiography (aggregated TransAtlantic Inter-Society Consensus classification, aTASC). Results Here we show that is capable differentiating IC HV an area under the receiver operator characteristics curve (AUROC) DC 0.99 (sensitivity: 100%, specificity: 95.8%) VC 0.95 96.2%, 96.0%). MSOT-derived oxygenation positively correlates ABI post-exercise (R 0.83, P 2.31 × 10 −26 ), absolute walking distance 6MWT 0.77, 3.40 −21 VASCUQOL-6 0.79, 4.82 −23 ) negatively aTASC classification -0.80, 2.92 −24 ). Conclusions Post-exercise saturation validated as a non-invasive imaging biomarker distinguish yielding high sensitivity specificity.
Language: Английский
Citations
0
Lecture notes in electrical engineering, Journal Year: 2025, Volume and Issue: unknown, P. 451 - 462
Published: Jan. 1, 2025
Language: Английский
Citations
0
Photoacoustics, Journal Year: 2025, Volume and Issue: 43, P. 100723 - 100723
Published: April 18, 2025
Three-dimensional (3D) photoacoustic imaging (PAI) with detector arrays has shown superior capabilities in biomedical applications. However, the quality of 3D PAI is often degraded due to reconstruction artifacts caused by sparse detectors. Existing iterative or deep learning-based methods are either time-consuming require large training datasets, limiting their practical application. Here, we propose Zero-Shot Artifact2Artifact (ZS-A2A), a zero-shot self-supervised artifact removal method based on super-lightweight network, which leverages fact that patterns more sensitive sensor data loss. By randomly dropping acquired PA data, it spontaneously generates subset reconstruct images, turn stimulates network learn results, thus enabling removal. This approach requires neither nor prior knowledge artifacts, making suitable for arbitrary array configurations. We validated ZS-A2A both simulation study and invivo animal experiments. Results demonstrate achieves high performance compared existing methods.
Language: Английский
Citations
0
European Journal of Nuclear Medicine and Molecular Imaging, Journal Year: 2024, Volume and Issue: unknown
Published: June 4, 2024
Language: Английский
Citations
2
Journal of Biomedical Optics, Journal Year: 2024, Volume and Issue: 29(S3)
Published: June 5, 2024
SignificancePhotoacoustic imaging (PAI) promises to measure spatially resolved blood oxygen saturation but suffers from a lack of accurate and robust spectral unmixing methods deliver on this promise. Accurate oxygenation estimation could have important clinical applications cancer detection quantifying inflammation.AimWe address the inflexibility existing data-driven for estimating in PAI by introducing recurrent neural network architecture.ApproachWe created 25 simulated training dataset variations assess performance. We used long short-term memory implement wavelength-flexible architecture proposed Jensen–Shannon divergence predict most suitable dataset.ResultsThe can flexibly handle input wavelengths outperforms linear previously learned decoloring method. Small changes data significantly affect accuracy our method, we find that correlates with error is thus predicting appropriate datasets any given application.ConclusionsA flexible combined best set provides promising direction might enable photoacoustic oximetry use cases.
Language: Английский
Citations
2
Advanced Science, Journal Year: 2024, Volume and Issue: 11(32)
Published: June 23, 2024
Mesoscopic photoacoustic imaging (PAI) enables label-free visualization of vascular networks in tissues with high contrast and resolution. Segmenting these from 3D PAI data interpreting their physiological pathological significance is crucial yet challenging due to the time-consuming error-prone nature current methods. Deep learning offers a potential solution; however, supervised analysis frameworks typically require human-annotated ground-truth labels. To address this, an unsupervised image-to-image translation deep model introduced, Vessel Segmentation Generative Adversarial Network (VAN-GAN). VAN-GAN integrates synthetic blood vessel that closely resemble real-life anatomy into its training process learns replicate underlying physics system order learn how segment vasculature images. Applied diverse range silico, vitro, vivo data, including patient-derived breast cancer xenograft models clinical angiograms, demonstrates capability facilitate accurate unbiased segmentation networks. By leveraging reduces reliance on manual labeling, thus lowering barrier entry for high-quality (F1 score: vs. U-Net = 0.84 0.87) enhancing preclinical research structure function.
Language: Английский
Citations
2
Biomedical Optics Express, Journal Year: 2024, Volume and Issue: 15(8), P. 4689 - 4689
Published: July 10, 2024
Accurate prediction of breast cancer (BC) is essential for effective treatment planning and improving patient outcomes. This study proposes a novel deep learning (DL) approach using photoacoustic (PA) imaging to enhance BC accuracy. We enrolled 334 patients with lesions from Shenzhen People's Hospital between January 2022 2024. Our method employs ResNet50-based model combined attention mechanisms analyze ultrasound (PA-US) images. Experiments demonstrated that the PAUS-ResAM50 achieved superior performance, an AUC 0.917 (95% CI: 0.884 -0.951), sensitivity 0.750, accuracy 0.854, specificity 0.920 in training set. In testing set, maintained high performance 0.870 0.778-0.962), 0.786, 0.872, 0.836. significantly outperformed other models, including PAUS-ResNet50, BMUS-ResAM50, BMUS-ResNet50, as validated by DeLong test (p < 0.05 all comparisons). Additionally, improved radiologists' diagnostic without reducing sensitivity, highlighting its potential clinical application. conclusion, demonstrates substantial promise optimizing diagnosis aiding radiologists early detection BC.
Language: Английский
Citations
2
Biomedical Optics Express, Journal Year: 2024, Volume and Issue: 15(9), P. 5479 - 5479
Published: Aug. 15, 2024
Dental caries cause pain and if not diagnosed, it may lead to the loss of teeth in extreme cases. X-ray imaging is gold standard for detection; however, cannot detect hidden caries. In addition, ionizing nature radiation another concern. Hence, other alternate modalities like photoacoustic (PA) are being explored dental imaging. Here, we demonstrate feasibility acoustic resolution microscopy (ARPAM) image a tooth with metal filling, circular computed tomography (cPACT) acquire images pigmentation, linear array-based (lPACT) pigmentation. The cavity measured lPACT compared image. filling its boundaries clearly seen ARPAM cPACT at 1064 nm were better representative surface acquired 532 nm. It was possible cavities present dentine when used. PA signal from pigmented on lateral (occlusion view) high imaged using system.
Language: Английский
Citations
2
Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)
Published: Sept. 8, 2024
Abstract Pompe disease (PD) is a rare autosomal recessive glycogen storage disorder that causes proximal muscle weakness and loss of respiratory function. While enzyme replacement therapy (ERT) the only effective treatment, biomarkers for monitoring are scarce. Following ex vivo biomarker validation in phantom studies, we apply multispectral optoacoustic tomography (MSOT), laser- ultrasound-based non-invasive imaging approach, clinical trial (NCT05083806) to image biceps muscles 10 late-onset PD (LOPD) patients matched healthy controls. MSOT compared with magnetic resonance (MRI), ultrasound, spirometry, testing quality life scores. Next, results validated an independent LOPD patient cohort from second site. Our study demonstrates enables subcellular pathology increases glycogen/water, collagen lipid signals, providing higher sensitivity detecting degeneration than current methods. This translational approach suggests implementation complex care these patients.
Language: Английский
Citations
2