Quantitative photoacoustic elastography of Young’s modulus in humans

Elastography can noninvasively map the elasticity distribution of biological tissue, which is often altered in pathological states. In this work, we report quantitative photoacoustic elastography (QPAE), capable of measuring Young’s modulus of human tissue in vivo. By combining photoacoustic elastography with a stress sensor having known stress-strain behavior, QPAE can simultaneously measure strain and stress, from which Young’s modulus is calculated. We first applied QPAE to quantify the Young’s modulus of tissue-mimicking agar phantoms with different concentrations. The measured values fitted well with both the empirical expectations based on the agar concentrations and those measured in independent standard compression tests. We then demonstrated the feasibility of QPAE by measuring the Young’s modulus of human skeletal muscle in vivo. The data showed a linear relationship between muscle stiffness and loading. The results proved that QPAE can noninvasively quantify the absolute elasticity of biological tissue, thus enabling longitudinal imaging of tissue elasticity. QPAE can be exploited for both preclinical biomechanics studies and clinical applications

Quantitative photoacoustic elastography in humans

We report quantitative photoacoustic elastography (QPAE) capable of measuring Young’s modulus of biological tissue in vivo in humans. By combining conventional PAE with a stress sensor having known stress–strain behavior, QPAE can simultaneously measure strain and stress, from which Young’s modulus is calculated. We first demonstrate the feasibility of QPAE in agar phantoms with different concentrations. The measured Young’s modulus values fit well with both the empirical expectation based on the agar concentrations and those measured in an independent standard compression test. Next, QPAE was applied to quantify the Young’s modulus of skeletal muscle in vivo in humans, showing a linear relationship between muscle stiffness and loading. The results demonstrated the capability of QPAE to assess the absolute elasticity of biological tissue noninvasively in vivo in humans, indicating its potential for tissue biomechanics studies and clinical applications

Synthetic Bessel light needle for extended depth-of-field microscopy

An ultra-long light needle is highly desired in optical microscopy for its ability to improve the lateral resolution over a large depth of field (DOF). However, its use in image acquisition usually relies on mechanical raster scanning, which compromises between imaging speed and stability and thereby restricts imaging performance. Here, we propose a synthetic Bessel light needle (SBLN) that can be generated and scanned digitally by complex field modulation using a digital micromirror device. In particular, the SBLN achieves a 45-fold improvement in DOF over its counterpart Gaussian focus. Further, we apply the SBLN to perform motionless two-dimensional and three-dimensional microscopic imaging, achieving both improved resolution and extended DOF. Our work is expected to open up opportunities for potential biomedical applications

Quantitative photoacoustic elastography in humans

We report quantitative photoacoustic elastography (QPAE) capable of measuring Young’s modulus of biological tissue in vivo in humans. By combining conventional PAE with a stress sensor having known stress–strain behavior, QPAE can simultaneously measure strain and stress, from which Young’s modulus is calculated. We first demonstrate the feasibility of QPAE in agar phantoms with different concentrations. The measured Young’s modulus values fit well with both the empirical expectation based on the agar concentrations and those measured in an independent standard compression test. Next, QPAE was applied to quantify the Young’s modulus of skeletal muscle in vivo in humans, showing a linear relationship between muscle stiffness and loading. The results demonstrated the capability of QPAE to assess the absolute elasticity of biological tissue noninvasively in vivo in humans, indicating its potential for tissue biomechanics studies and clinical applications

Dictionary learning sparse-sampling reconstruction method for in-vivo 3D photoacoustic computed tomography

The sparse transforms currently used in the model-based reconstruction method for photoacoustic computed tomography (PACT) are predefined and they typically cannot capture the underlying features of the specific data sets adequately, thus limiting the high-quality recovery of photoacoustic images. In this work, we present an advanced reconstruction model using the K-VSD dictionary learning technique and present the in vivo results after adapting the model into the 3D PACT system. The in vivo experiments were performed on an IRB approved human hand and two rats. When compared to the traditional sparse transform, experimental results using our proposed method improved accuracy and contrast to noise ration of the reconstructed photoacoustic images, on average, by 3.7 and 1.8 times in the case of 50% sparse-sampling rate, respectively. We also compared the performance of our algorithm against other techniques, and imaging speed was 60% faster than other approaches. Our system would require sparse-transducer array and lower number of data acquisition hardware (DAQs) potentially reducing the cost of the system. Thus, our work provides a new way for reconstructing photoacoustic images, and it would enable the development of new high-speed low-cost 3D PACT for various biomedical applications

Comparative Diagnostic Accuracy of Contrast-Enhanced Ultrasound and Shear Wave Elastography in Differentiating Benign and Malignant Lesions: A Network Meta-Analysis

Background: We performed a network meta-analysis to compare the diagnostic accuracy of contrast-enhanced ultrasound (CEUS) and shear wave elastography (SWE) in differentiating benign and malignant lesions in different body sites.Methods: A computerized literature search of Medline, Embase, SCOPUS, and Web of Science was performed using relevant keywords. Following data extraction, we calculated sensitivity, specificity, positive likelihood ratio (LR), negative LR, and diagnostic odds ratio (DOR) for CEUS, and SWE compared to histopathology as a reference standard. Statistical analyses were conducted by MetaDiSc (version 1.4) and R software (version 3.4.3).Results: One hundred and fourteen studies (15,926 patients) were pooled in the final analyses. Network meta-analysis showed that CEUS had significantly higher DOR than SWE (DOR = 27.14, 95%CI [2.30, 51.97]) in breast cancer detection. However, there were no significant differences between CEUS and SWE in hepatic (DOR = −6.67, 95%CI [−15.08, 1.74]) and thyroid cancer detection (DOR = 3.79, 95%CI [−3.10, 10.68]). Interestingly, ranking analysis showed that CEUS achieved higher DOR in detecting breast and thyroid cancer, while SWE achieved higher DOR in detecting hepatic cancer. The overall DOR for CEUS in detecting renal cancer was 53.44, 95%CI [29.89, 95.56] with an AUROC of 0.95, while the overall DOR for SWE in detecting prostate cancer was 25.35, 95%CI [7.15, 89.89] with an AUROC of 0.89.Conclusion: Both diagnostic tests showed relatively high sensitivity and specificity in detecting malignant tumors in different organs. Network meta-analysis showed that CEUS had higher diagnostic accuracy than SWE in detecting breast and thyroid cancer, while SWE had higher accuracy in detecting hepatic cancer. However, the results were not statistically significant in hepatic and thyroid malignancies. Further head-to-head comparisons are needed to confirm the optimal imaging technique to differentiate each cancer type

Motionless volumetric photoacoustic microscopy with spatially invariant resolution

Photoacoustic microscopy (PAM) is uniquely positioned for biomedical applications because of its ability to visualize optical absorption contrast in vivo in three dimensions. Here we propose motionless volumetric spatially invariant resolution photoacoustic microscopy (SIR-PAM). To realize motionless volumetric imaging, SIR-PAM combines two-dimensional Fourier-spectrum optical excitation with single-element depth-resolved photoacoustic detection. To achieve spatially invariant lateral resolution, propagation-invariant sinusoidal fringes are generated by a digital micromirror device. Further, SIR-PAM achieves 1.5 times finer lateral resolution than conventional PAM. The superior performance was demonstrated in imaging both inanimate objects and animals in vivo with a resolution-invariant axial range of 1.8 mm, 33 times the depth of field of the conventional PAM counterpart. Our work opens new perspectives for PAM in biomedical sciences

Motionless volumetric photoacoustic microscopy with spatially invariant resolution

Photoacoustic microscopy (PAM) is uniquely positioned for biomedical applications because of its ability to visualize optical absorption contrast in vivo in three dimensions. Here we propose motionless volumetric spatially invariant resolution photoacoustic microscopy (SIR-PAM). To realize motionless volumetric imaging, SIR-PAM combines two-dimensional Fourier-spectrum optical excitation with single-element depth-resolved photoacoustic detection. To achieve spatially invariant lateral resolution, propagation-invariant sinusoidal fringes are generated by a digital micromirror device. Further, SIR-PAM achieves 1.5 times finer lateral resolution than conventional PAM. The superior performance was demonstrated in imaging both inanimate objects and animals in vivo with a resolution-invariant axial range of 1.8 mm, 33 times the depth of field of the conventional PAM counterpart. Our work opens new perspectives for PAM in biomedical sciences