Scientific Reports 13권, 기사 번호: 8803(2023) 이 기사 인용
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확산 상관 분광법(DCS)은 조직의 혈류를 특성화하는 데 사용할 수 있는 광학 기술입니다. 대뇌 혈역학 측정은 DCS의 유망한 사용 사례로 떠오르고 있지만, DCS의 기존 구현은 성인의 대뇌 혈류를 강력하게 측정하기 위해 최적이 아닌 신호 대 잡음비(SNR)와 대뇌 민감도를 나타냅니다. 이 연구에서는 대뇌 민감도와 SNR을 모두 향상시키기 위해 더 긴 조명 파장(1064nm), 다중 반점 및 간섭계 검출을 결합한 장파장 간섭계 DCS(LW-iDCS)를 제시합니다. 초전도 나노와이어 단일 광자 검출기에 기반한 장파장 DCS와의 직접적인 비교를 통해 우리는 인간 대상에서 측정된 혈류 신호에서 LW-DCS의 단일 채널에 비해 SNR이 약 5배 향상되었음을 보여줍니다. 우리는 LW-DCS와 LW-iDCS 사이의 추출된 혈류의 동등성을 보여주고, 3.5cm의 소스-검출기 분리에서 100Hz에서 측정된 LW-iDCS의 타당성을 입증합니다. 이러한 성능 향상은 대뇌 혈역학의 강력한 측정을 가능하게 하고 확산 상관 분광법에 대한 새로운 사용 사례를 열 수 있는 잠재력을 가지고 있습니다.
확산 상관 분광법(DCS)은 조직 혈류1의 비침습적 측정을 허용하는 확립된 광학 기술입니다. 분산 후방 산란광의 측정을 통해 DCS는 수집된 신호의 시간적 변동을 혈관계를 통한 혈액 세포의 움직임과 연관시킵니다. 병상 임상 혈류 모니터링2, 특히 뇌혈류 모니터링3은 DCS의 사용 사례로 폭발적으로 증가했으며, DCS는 수술 과정 중 뇌 관류의 지표를 추정하는 데 사용되었습니다4,5,6,7,8, 뇌 자동 조절9,10, 뇌혈관 반응성11, 두개내압12,13,14 및 임계 폐쇄 압력15,16. DCS 모니터링을 포함한 많은 연구가 성인 집단에서 입증되었지만 대뇌 민감도 및 신호 대 잡음비17의 한계로 인해 표준 DCS 기술은 신생아 및 어린이의 혈류를 측정하는 데 더 적합합니다. 두피와 두개골)은 성인에 비해 상당히 얇습니다18,19. 성인 인구의 DCS 성능을 향상시키기 위해 많은 그룹에서 대뇌 민감도, 신호 대 잡음비 또는 둘 다를 개선하는 DCS 수정을 개발했습니다. 이러한 방법에는 간섭계 감지20,21,22,23,24,25, 병렬 반점 감지26,27,28, 음향 광학 변조29,30,31, 경로 길이 분해 방법32,33,34,35,36,37, 반점 대비 방법38이 포함됩니다. ,39,40 및 장파장 접근41,42. 우리 그룹의 최근 연구에서는 1064nm에 적용되는 장파장 DCS의 유용성을 보여 주었지만 실제로 임상 측정에서 현재 사용 가능한 상업용 검출기는 깊은 흐름에 민감한 측정에 적합한 노이즈 성능을 갖지 못합니다(InGaAs/InP 단일 -광자 사태 다이오드(SPAD))43 또는 임상적으로 적용하기에는 너무 부피가 크다(초전도 나노와이어 단일 광자 검출기(SNSPD)). 검출기 기술의 이러한 격차를 해결하기 위해 우리는 1064nm에서 작동하는 모든 이점을 활용하고 간섭계를 사용하여 1064nm에서 빛에 민감한 검출기 기술의 부정적인 측면을 피하는 장파장 간섭계 DCS(LW-iDCS)를 개발했습니다. 고도로 평행한 라인 스캔 카메라 센서와 함께 감지합니다(Zhou et al.21,44의 더 짧은 파장에서 수행된 작업에서 영감을 받음). 이 연구에서는 새로운 LW-iDCS 기술에 의한 혈류 추정의 동등성을 검증하고 측정된 신호의 품질을 비교하기 위해 파일럿 인간 대상 연구에서 LW-DCS와 LW-iDCS의 성능을 직접 비교합니다.
3.5 mm center-to-center distance), 1 single mode fiber for short-separation DCS (5 mm) and several co-localized long-separation detection fibers: 4 single mode fibers (LW-DCS), and 7 multimode detection fibers (LW-iDCS). A high coherence (lc > 10 km), fiber (MFD 6.6 µm) laser source emitting ~ 125 mW at 1064 nm (RFLM-125-0-1064, NP Photonics) was fusion spliced (S185HS Fusion Splicer, Fitel) to a 90:10, polarization maintaining fused fiber coupler (MFD 6.6 µm, PN1064R2A1, Thorlabs). The 10% arm of the coupler was used as the input for a fiber amplifier (MAKO-AMP1064, Cybel), and was connected via an FC/APC connector. The amplifier output fiber (MFD 10 µm) was fusion spliced to the input of a 50:50, 105 µm, multimode fused fiber coupler (TW1064R5A1B, Thorlabs). The two outputs of the fiber coupler were spliced to two 105 µm multimode source fibers connected to the probe. The light was amplified to allow for two MPE limited spots54 (1 W/cm2 at 1064 nm, 3.6 mm spot size diameter, 102 mW each spot) to increase the achievable signal-to-noise ratio. The 90% output arm of the polarization maintaining coupler was connected to the reference arm input of the LW-iDCS interferometer. All spliced connections were confirmed by the fusion splicer to have losses less than 0.03 dB./p> 50%. (B) For this maneuver, as expected, the systemic physiology was not significantly affected by the tightening of the tourniquet on the forehead./p> 3.5 mm apart could be used, allowing for an even higher SNR for high quality pulsatile blood flow measurements. The SNR of the LW-iDCS measurement seen in the high-speed pulsatile measurements was 4.5× the SNR of the SNSPD LW-DCS measurement when making single channel comparisons, representing an enabling improvement to the quality of blood flow measured. In the context of the DCS systems currently used for translational research, this improvement is especially significant considering that even the single illumination SNSPD LW-DCS has an SNR gain of 16× over conventional DCS42, and that measurements at 3.5 cm are not feasible with conventional NIR DCS. The use of a camera which is sensitive to light at 1064 nm takes advantage of both the higher number of photons per mode as compared to traditional NIR wavelengths as well as the slower decay of the autocorrelation function. For cerebral blood flow measurements made at long source-detector separations, the autocorrelation decay for traditional NIR DCS can happen in 1–10 s of microseconds, and a significant portion of the decay could be missed if not sampled quickly enough. The use of both heterodyne detection, measuring the slower decaying \({g}_{1}\left(\tau \right)\) as opposed to \({g}_{2}\left(\tau \right)\), and 1064 nm relaxes the sampling rate needed to effectively sample the correlation function. The longer source-detector separation achievable with these advanced DCS systems enables measurements with reduced sensitivity to the upper tissue layers relative to the sensitivity of currently applied DCS systems in the traditional NIR wavelength range (explored in the supplement). The decreased sensitivity to extracerebral signals is greatly beneficial to DCS measurements, especially in clinical applications where systemic physiological fluctuations are more likely to occur and the timing of relevant cerebral hemodynamic changes is not as well defined. We also see good agreement with the estimated noise performance given by Monte Carlo simulation (Figure S3). Additionally, the cost of the system is greatly reduced compared to LW-DCS based on SNSPDs. For this implementation of the LW-iDCS system, the detector used is ~ 7× less expensive (~ $25 k total, camera + frame grabber: ~ $20 k, assorted lenses, opto-mechanics, and fibers: ~ $5 k) as compared to the SNSPDs (~ $180 k total, cryostat: ~ $100 k, individual nanowire detectors: ~ $20 k each). The LW-iDCS cart-based system is also more mobile than the SNSPD based LW-DCS system. These improvements in cost, SNR, and mobility are promising for the clinical usability of LW-iDCS measurements of CBF in adults. The signal processing approach used to extract the correlation function from the raw data stream points to potential pitfalls in the development of iDCS instruments using multimode fiber and free space interferometers though. The motion of fibers and vibrations in the environment have the potential to corrupt the iDCS signals, however, these challenges are manageable, and the use of the custom data analysis pipeline, described in supplementary information, was successful in removing artifacts from the data. The use of a weighted fitting approach allowed for equivalent blood flow indices to be fit from both the LW-DCS and LW-iDCS correlation functions, evidenced by the results shown in Fig. 3C and D. While the results presented matched well, investigation of the generalizability of the weighting factor selected in this study is warranted given the influence that tissue layer thicknesses, optical properties, and ratios of scalp and brain blood flow are known to have on fitting autocorrelation functions67,68. Another challenge posed by the implementation of massively parallel multi-speckle detection is the raw data rate of the instruments. Recent publications on massively parallelized detection have quoted raw data rates between 0.24 GB/s (0.864 TB/hr) and 9.0 GB/s (32.4 TB/hr)22,25,26,27,28,44,69. For clinical blood flow measurements, these data rates could result in untenably large data files, though real time processing utilizing GPUs or FPGAs have been explored as a solution to address this challenge28,69. The increased SNR provided by the LW-iDCS instrument presented here enabled high sensitivity to the cerebral blood flow signal as well as a high rate of BFi calculation. These factors will be highly enabling for the clinical translation of DCS as a noninvasive cerebral blood flow monitor./p>
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