The integration of near-infrared genetically encoded reporters(NIR-GERs)with photoacoustic(PA)imaging enables visualizing deep-seated functions of specific cell populations at high resolution,though the imaging depth ...The integration of near-infrared genetically encoded reporters(NIR-GERs)with photoacoustic(PA)imaging enables visualizing deep-seated functions of specific cell populations at high resolution,though the imaging depth is primarily constrained by reporters’PA response intensity.Directed evolution can optimize NIR-GERs’performance for PA imaging,yet precise quantifying of PA responses in mutant proteins expressed in E.coli colonies across iterative rounds poses challenges to the imaging speed and quantification capabilities of the screening platforms.Here,we present self-calibrated photoacoustic screening(SCAPAS),an imaging-based platform that can detect samples in parallel within 5 s(equivalent to 50 ms per colony),achieving a considerable quantification accuracy of approximately 2.8%and a quantification precision of about 6.47%.SCAPAS incorporates co-expressed reference proteins in sample preparation and employs a ring transducer array with switchable illumination for rapid,wide-field dual-wavelength PA imaging,enabling precisely calculating the PA response using the self-calibration method.Numerical simulations validated the image optimization strategy,quantification process,and noise robustness.Tests with co-expression samples confirmed SCAPAS’s superior screening speed and quantification capabilities.We believe that SCAPAS will facilitate the development of novel NIR-GERs suitable for PA imaging and has the potential to significantly impact the advancement of PA probes and molecular imaging.展开更多
Purpose To investigate the influence of different reconstruction techniques on the quantitative accuracy and image quality of PET/CT.Methods The NEMA NU2-2018 image quality phantom was scanned on a GE Discovery Elite ...Purpose To investigate the influence of different reconstruction techniques on the quantitative accuracy and image quality of PET/CT.Methods The NEMA NU2-2018 image quality phantom was scanned on a GE Discovery Elite PET/CT scanner and the spatial resolution was measured based on NEMA NU2 standard.The same raw data were reconstructed using five different algorithms:ordered subset expectation maximization(OSEM),OSEM with point spread function(PSF)modeling,OSEM with time-of-flight(TOF),OSEM with TOF and PSF,and filtered back-projection(FBP).The recovery coefficient(RC),contrast recovery coefficient(CRC),and contrast-to-noise ratio(CNR)were calculated for the six hot spheres,the percent background variability(PBV)and coefficient of variation(COV)were calculated for the background,and the residual error(RE)was calculated for lung insert in different image slices.Results The incorporation of PSF modeling showed the smallest transverse FWHM and FWTM at both 1 and 10 cm radical offsets.The combination of PSF modeling and TOF improved RC_(mean) and CRC for all spheres and resulted in the highest ratings for the detectability of 10 mm spheres in human observer assessment.PSF modeling played a role in reducing the COV within the background region of interest and increasing the CNR of the spheres,and decreased background noise ratings in human observer assessment.Besides,TOF significantly reduced the RE in lung insert.Neither PSF modeling nor TOF had a significant effect on PBV.Compared to FBP,the OSEM algorithm showed significant advantages in PBV,COV,CNR and RE and human observer ratings of image quality,but worse results for RC_(max),RC_(mean) and CRC.Conclusions The integration of TOF and PSF modeling into the OSEM algorithm achieves improvements in both quantitative accuracy and image quality,providing distinct advantages.PSF modeling improves the spatial resolution and decreases the visual appearance of background noise.The OSEM algorithm shows significantly better image quality than the FBP algorithm but no distinct advantages concerning quantitative accuracy.展开更多
基金STI2030-Major Projects(2022ZD0212000)Key Research and Development Program of Zhejiang(2024SSYS0014)+4 种基金Beijing Natural Science Foundation(Z240009)National Natural Science Foundation of China(2021MG1BI01,62475129,21927813,T2322001)Strategic Precision Surgery Project at the Institute for Intelligent Healthcare(Tsinghua University)Innovation Fund of the Tsinghua-Foshan Institute of Advanced ManufacturingNational Key Research and Development Program of China(2022ZD0211900,2024YFC3406603)。
文摘The integration of near-infrared genetically encoded reporters(NIR-GERs)with photoacoustic(PA)imaging enables visualizing deep-seated functions of specific cell populations at high resolution,though the imaging depth is primarily constrained by reporters’PA response intensity.Directed evolution can optimize NIR-GERs’performance for PA imaging,yet precise quantifying of PA responses in mutant proteins expressed in E.coli colonies across iterative rounds poses challenges to the imaging speed and quantification capabilities of the screening platforms.Here,we present self-calibrated photoacoustic screening(SCAPAS),an imaging-based platform that can detect samples in parallel within 5 s(equivalent to 50 ms per colony),achieving a considerable quantification accuracy of approximately 2.8%and a quantification precision of about 6.47%.SCAPAS incorporates co-expressed reference proteins in sample preparation and employs a ring transducer array with switchable illumination for rapid,wide-field dual-wavelength PA imaging,enabling precisely calculating the PA response using the self-calibration method.Numerical simulations validated the image optimization strategy,quantification process,and noise robustness.Tests with co-expression samples confirmed SCAPAS’s superior screening speed and quantification capabilities.We believe that SCAPAS will facilitate the development of novel NIR-GERs suitable for PA imaging and has the potential to significantly impact the advancement of PA probes and molecular imaging.
文摘Purpose To investigate the influence of different reconstruction techniques on the quantitative accuracy and image quality of PET/CT.Methods The NEMA NU2-2018 image quality phantom was scanned on a GE Discovery Elite PET/CT scanner and the spatial resolution was measured based on NEMA NU2 standard.The same raw data were reconstructed using five different algorithms:ordered subset expectation maximization(OSEM),OSEM with point spread function(PSF)modeling,OSEM with time-of-flight(TOF),OSEM with TOF and PSF,and filtered back-projection(FBP).The recovery coefficient(RC),contrast recovery coefficient(CRC),and contrast-to-noise ratio(CNR)were calculated for the six hot spheres,the percent background variability(PBV)and coefficient of variation(COV)were calculated for the background,and the residual error(RE)was calculated for lung insert in different image slices.Results The incorporation of PSF modeling showed the smallest transverse FWHM and FWTM at both 1 and 10 cm radical offsets.The combination of PSF modeling and TOF improved RC_(mean) and CRC for all spheres and resulted in the highest ratings for the detectability of 10 mm spheres in human observer assessment.PSF modeling played a role in reducing the COV within the background region of interest and increasing the CNR of the spheres,and decreased background noise ratings in human observer assessment.Besides,TOF significantly reduced the RE in lung insert.Neither PSF modeling nor TOF had a significant effect on PBV.Compared to FBP,the OSEM algorithm showed significant advantages in PBV,COV,CNR and RE and human observer ratings of image quality,but worse results for RC_(max),RC_(mean) and CRC.Conclusions The integration of TOF and PSF modeling into the OSEM algorithm achieves improvements in both quantitative accuracy and image quality,providing distinct advantages.PSF modeling improves the spatial resolution and decreases the visual appearance of background noise.The OSEM algorithm shows significantly better image quality than the FBP algorithm but no distinct advantages concerning quantitative accuracy.
