Research ArticleOpen Access

In vivo label-free measurement of blood flow velocity symmetry based on dual line scanning third-harmonic generation microscopy excited at the 1700 nm window

Key Laboratory of Optoelectronic Devices, and Systems of Ministry of Education and Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060 P. R. China

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Jincheng Zhong

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Ping Qiu

https://orcid.org/0000-0002-2114-5909

E-mail Address: pingqiu@szu.edu.cn

Corresponding authors.

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, and

Ke Wang

E-mail Address: kewangfs@szu.edu.cn

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https://doi.org/10.1142/S1793545823500116Cited by:2 (Source: Crossref)

Abstract

Measurement of blood flow velocity is key to understanding physiology and pathology in vivo. While most measurements are performed at the middle of the blood vessel, little research has been done on characterizing the instantaneous blood flow velocity distribution. This is mainly due to the lack of measurement technology with high spatial and temporal resolution. Here, we tackle this problem with our recently developed dual-wavelength line-scan third-harmonic generation (THG) imaging technology. Simultaneous acquisition of dual-wavelength THG line-scanning signals enables measurement of blood flow velocities at two radially symmetric positions in both venules and arterioles in mouse brain in vivo. Our results clearly show that the instantaneous blood flow velocity is not symmetric under general conditions.

Keywords:

1. Introduction

For animals and human beings, blood vessels are critical for the circulation and efficient transport of nutrients, fluids, and signaling molecules between cellular tissues and organs.^1,2 Abnormal vascular development may contribute to the pathogenesis of many diseases, such as excessive angiogenesis, abnormal remodeling, and insufficiency or regression of vascular growth.^3,4,5 It has long been recognized that hemodynamics plays a decisive role in shaping blood vessels and mediating vascular disease. Brain is the one of most important organs and relies almost entirely on blood for the delivery of essential nutrients and energy. Besides, blood flow velocity in the cerebral vasculature can quantitatively reflect the physiological and pathological conditions, such as dynamic activity of nerve cells, cerebrovascular embolism, and peripheral blood flow abnormalities due to Alzheimer’s disease.^6,7,8 Therefore, the blood flow velocity is an important parameter of the blood supply to the brain.

Besides the blood flow velocity itself, an interesting and unanswered question is: Is the blood flow velocity symmetric in brain blood vessels? Theoretically, for simplicity, it is often assumed that blood vessels are cylinders with radially symmetric velocity distribution.^9,10 However, this assumption is apparently not valid from a practical point of view. The measurement of the intravascular distribution of blood flow velocity is essential for answering this question and may be of significance for the study of cerebrovascular development, physiology and pathology. Many methods have been proposed to measure the blood flow velocity in vivo. Intrinsic optical imaging and laser scatter imaging can yield information about changes in oxygenation and/or blood flow, but are not suitable for high-resolution measurements of flow below the cortical surface.^11,12,13,14 Laser doppler imaging and blood oxygenation level-dependent functional magnetic resonance imaging (BLOD fMRI) measure deep into the brain surface but with lower temporal and spatial resolution.^15,16,17 Though single-photon imaging using confocal laser scanning microscopy is feasible for blood flow analysis at the single-vessel level, it has relatively poor spatial resolution in the z direction (along the light path) and its imaging depth is limited.^18,19,20 Moreover, for studies of vascular structure and blood flow, fluorescent dyes or beads are typically injected into the bloodstream to label the blood plasma.^21,22,23,24 However, the flow of fluorescent beads through the field of view is random, as is the position of measurement. In other words, this technology cannot measure instantaneous values at a designated position. Besides, these methods can only measure velocity at one position, and the blood flow velocity at different radial positions cannot be measured simultaneously, so, the above problem cannot be solved.

Multiphoton microscopy (MPM) is well known for its 3D sectioning capability, which enables locating to the equatorial plane of the blood vessel for velocity measurement. Third-harmonic generation (THG) is one of the frequent imaging modalities of MPM.^{25,26,27,28,29} Red blood cells (RBCs) can produce THG signal under excitation at the appropriate wavelength.^30,31 Compared with other methods, THG imaging combines the advantages of a label-free technology with sub-micron spatial resolution and intrinsic 3D sectioning capability. Besides, excited at the 1700nm window, it is an ideal method for continuously measuring blood flow velocity in vivo. Recently, we have demonstrated that THG imaging excited at the 1700nm window can be applied to measuring blood flow velocity and even wall shear rate (i.e., velocity gradient) in animal models in vivo.^30,32

In order to answer the key question of brain blood flow symmetry, here, we use a recently developed dual-wavelength label-free THG line-scanning technology³² to measure the flow velocity at symmetric positions along both venules and arterioles in mouse brains in vivo. Using this technique, we can simultaneously extract the THG line-scanning traces at two radially symmetric positions within the vessel to calculate the flow velocities. Our results show the general asymmetric distribution of blood flow velocity at high spatial and temporal resolution in practical conditions which cannot be accounted for by the simple theoretical assumption of symmetry.

2. Materials and Methods

2.1. Dual-wavelength third-harmonic-generation imaging system

In order to obtain the blood flow velocity at two radially symmetric positions simultaneously, we use the dual-wavelength third-harmonic-generation line-scanning imaging system.³² The experimental step is shown in Fig. 1(a). We used a half-wave plate to adjust the polarization angle of the 1550nm, 6.25MHz, and 527fs pump laser (FLCPA-02CSZU, Calmar) output into a 3m LMA fiber (LMA-PM-35, NKT Photonics). The soliton self-frequency shift (SSFS) effect in the fiber yielded two orthogonally-polarized laser pulses with two wavelengths simultaneously. Then, a customized 1650nm long-pass filter (1650lpf, Yi Zhao Photonics Technology) was used to remove the residual pump at the output end of the fiber. After separating these two wavelengths (1680nm and 1780nm) spatially using a polarization beam splitter (PBS104, Thorlabs), the measured spectra of these two solitons are shown in Fig. 1(b). The pulse widths of the 1680nm and 1780nm solitons are 146fs and 151fs, respectively. Moreover, the two beams were offset at an angle on the scan mirror of a multiphoton microscope (MOM, Sutter), in order to separate them when focusing on the sample. Through a water-immersion objective lens (XPLN25XSVMP2, Olympus) with D₂O immersion, the optical power on the sample surface was 20 and 22mW for 1680 and 1780nm excitations, respectively. The scanning parameters of the system are as follows: The line-scanning speed was 1ms/line, the pixel size of the two-dimensional image was $512 \times 512$ $512 \times 512$ pixels, and the scanning line size of 50 $μ$ $μ$ m. For signal collection, THG signals excited at 1780nm were detected by a GaAs PMT (H7422-50, Hamamatsu) with a 630/92 bandpass filter (FF01-630/92-25, Semrock). A GaAsP PMT (H7422-40, Hamamatsu) with a 540/80 bandpass filter (FF01-540/80-25, Semrock) was used to collect THG signal from 1680nm excitation laser. The two channels of THG signals were simultaneously acquired.

Fig. 1. (a) Experimental setup of dual-wavelength third-harmonic-generation line-scanning imaging system. HWP: Half-wave plate; L1 and L2: Focusing and collimating lens; SL and TL: Scan lens and tube lens; F1: Long-pass filter; F2 and F3: Band-pass filter; M: Mirror; DM: Dichroic mirror; PBS: Polarization beam splitter. Zooming in on the objective section, the red box indicates the schematic of the radial symmetric position of the dual-line scan within the vessel. (b) Measured optical spectra of the 1680nm (red) and 1780nm (purple) femtosecond solitons.

2.2. Animal procedures

All the mice were from Guangdong Medical Animal Experimental Center, China. The protocols and handling of the animals had been approved by the Animal Ethics Committee of Shenzhen University Medical College.

In mice (C57, female, 7–8 weeks, ∼18g), craniotomy was performed for imaging. Before the experiment, all instruments were sterilized with alcohol, including forceps, scissors, drill and glass coverslips. First, the scalp and periosteum of anesthetized mice were removed with scissors. Second, a home-made head ring was attached to the skull with dental cement. Then, we found suitable target blood vessels with the skull infiltrated with saline. Next, the skull was slowly polished with a drill in a circular motion, centered on target blood vessel, until the skull was about to fall off. Then, the skull was removed with tweezers to create a cranial window about 3mm in diameter. At this time, the brain was exposed to air and washed with saline. After that, the cranial window was sealed with a cover glass (5mm diameter) using dental cement. Finally, the mouse was placed in the microscope for in vivo imaging. The mouse was kept anesthetized with isoflurane air anesthesia and their body temperature was maintained with a heating pad during the entire experiment.

2.3. Measurement of blood flow velocity and relative difference analysis

RBCs can generate third-harmonic signals without labeling. Line scanning is a well-established technique for measuring blood flow velocity. Here, we first moved two scan-lines to radially symmetric positions in the target vessel with the dual-wavelength THG microscopy. The steps are as follows: (1) Move the objective lens so that the equatorial surface of the vessels in one of the channels is in the center of the field of view, and at the same time, the vessels in both channels can be seen to be deviated in radial position. (2) After measuring the distance difference between the radial positions of the two channels, the scan line of the channel moves half the distance of the distance difference, and the other channel moves simultaneously, so that the scan lines of the two channels are in a symmetrical position. (3) After measuring a set of data, adjust the optical path, so that the two scan lines spacing changes, and then repeat the above operation, you can get another set of radial symmetric position of the data and so on to obtain multiple sets of radially symmetric position of the line scan results.

Then, under the simultaneous excitation of two different wavelengths, continuous line-scanning was carried out along a straight line, and two-dimensional time-space images are recorded in two channels. As RBCs flowed in the blood vessels, a series of oblique stripes were acquired in the 2D images. These streaks can be used to measure flow velocity. We used this method to measure blood flow velocity in four groups of radially symmetric positions within a single vessel with 1KHz scan rate.

Next, we converted the pixel value generated by RBCs movement in the time-space image into microns ( $Δ x$ $Δ x$ ) and calculated the velocity using Eq. (1), where $Δ t$ $Δ t$ is the time between line-scans.³³ We used an established algorithm to calculate the blood flow velocity³⁴ with our own imaging parameters. From this, we obtained instantaneous velocity versus time at the radially symmetric positions in the target vessel.

v=ΔxΔt.<math display="block" altimg="eq-00031.gif"><mi>v</mi><mo>=</mo><mfrac><mrow><mi mathvariant="normal">Δ</mi><mi>x</mi></mrow><mrow><mi mathvariant="normal">Δ</mi><mi>t</mi></mrow></mfrac><mo>.</mo></math>(1)

To quantitatively determine the symmetry of the blood flow velocity, we used Eq. (2) to calculate the relative difference ( $δ$ $δ$ ), where $v_{1}$ $v_{1}$ and $v_{2}$ $v_{2}$ denote the velocity obtained from line-scan at 1780nm and 1680nm wavelengths at radially symmetric positions, respectively. Here, we consider a relative difference within $\pm 10$ $\pm 10$ % as good symmetry of blood flow velocity, otherwise poor.

δ=v1−v2v1+v22×100%.<math display="block" altimg="eq-00038.gif"><mi>δ</mi><mo>=</mo><mfrac><mrow><msub><mrow><mi>v</mi></mrow><mrow><mn>1</mn></mrow></msub><mo>−</mo><msub><mrow><mi>v</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow><mrow><mfrac><mrow><msub><mrow><mi>v</mi></mrow><mrow><mn>1</mn></mrow></msub><mo>+</mo><msub><mrow><mi>v</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow><mrow><mn>2</mn></mrow></mfrac></mrow></mfrac><mo>×</mo><mn>1</mn><mn>0</mn><mn>0</mn><mi>%</mi><mo>.</mo></math>(2)

3. Results

Venules and arterioles were first identified by their flow direction and general appearance.³⁵ Then, we performed dual-wavelength THG imaging and simultaneously measured the instantaneous velocities at two radially symmetric positions in the vessel. Figure 2(A(a)) shows the THG imaging results of a target venule in the brain excited at 1780nm, and the white arrows indicate the direction of blood flow from right to left. Zooming onto the blood vessel in the yellow box (Fig. 2(A(b))), the white dashed line indicates the center of the equatorial plane of blood vessels, and the “×” marks with the same color on both sides indicate a set of radially symmetrical line scan positions. The upper half of the blood vessel was imaged by 1680nm, and the corresponding line-scanning results are shown in Fig. 2(C). Likewise, the lower half was imaged by 1780nm with the line-scanning results shown in Fig. 2(B).

The velocities at the symmetrical position of the venules were calculated and statistically analyzed over time, as shown in Fig. 2(D). The velocity and relative difference results at the radial symmetrical position of the venules were obtained in four groups. The four groups of velocity data (Figs. 2(D)(a)–(d)) correspond to the four groups of symmetric positions in Fig. 2(A)(b). The mean velocities of the venule are summarized in Table 1. Furthermore, the relative difference of the first two groups (Figs. 2(D)(a) and 2(b)) is within 10% (Figs. 2(D)(e) and 2(f)), indicating that the flow velocity at the position of venules near the center of blood vessels has good symmetry. The relative difference for the latter two groups (Figs. 2(D)(g) and 2(h)) exceeds 10%, indicating poor symmetry of flow velocity near the vessel wall.

For arteriole with a diameter of 40 $μ$ $μ$ m, the measured results are shown in Fig. 3, with white arrows indicating the direction of blood flow. Compared with the venule in Fig. 2, the blood flow velocities are faster with almost horizontal stripes (Figs. 3(B) and 3(C)). The mean velocities of the arteriole are also summarized in Table 1. In addition to this, it can be seen from Figs. 3(D(e)–(h)) that the symmetry of the arterial blood flow velocity is better near the middle than near the vessel wall, but significantly worse than the radial symmetry of the venule.

**Table 1. Measured mean velocities of the venule and arteriole at different positions.^a**
Type	Wavelength	Position 1 (mm/s)	Position 2 (mm/s)	Position 3 (mm/s)	Position 4 (mm/s)
Venule	1680nm	3.31	2.95	2.20	2.91
	1780nm	3.32	3.00	2.03	3.25
Arteriole	1680nm	−12.94	−8.58	−5.30	−3.08
	1780nm	−13.12	−9.11	−6.52	−4.09

Notes: ^aPositions 1–4 represent four groups of radially symmetric blood flow velocity measurement positions, with directions from the middle to the walls. Negative sign indicates different direction of blood flow.

4. Discussion

According to Table 1, we can know that the blood flow velocity is fast in the middle of the vessel and decreases gradually in the direction of the vessel wall on both sides. We have done measurements on five blood vessels (two arterioles and three venules) from five different mice (including those in Figs. 2 and 3), all of which show the same trend of velocity symmetry, which are summarized in Table 2. We also performed statistical analysis of the measured mean relative velocity differences for venules. The measured mean±standard deviation (SD) values for position 1, 2, 3, and 4 are $2.3 \pm 2.3$ $2.3 \pm 2.3$ %, $2.9 \pm 2.8$ $2.9 \pm 2.8$ %, $5.5 \pm 3.0$ $5.5 \pm 3.0$ %, and $12.5 \pm 5.4$ $12.5 \pm 5.4$ %, respectively. For this statistical analysis, we took the absolute values of the relative velocity difference, since we were only concerned with their magnitude rather than the sign.

**Table 2. The mean relative velocity differences of the venules and arterioles.**
Type	Blood vessel #	Position 1	Position 2	Position 3	Position 4
Venule	1	0.3%	1.6%	−8%	11.3%
	2	1.0%	1.1%	−2.1%	−7.8%
	3	−5.7%	−6.1%	−6.3%	−18.4%
Arteriole	1	−1.6%	−4.9%	−23.6%	−52.4%
	2	1.2%	6.0%	20.5%	28.7%

5. Conclusions

Theoretical analysis for blood flow often assumes for simplicity that the flow velocity is radially symmetric. However, this oversimplified assumption may not be valid under practical conditions and needs experimental verification. Previous measurement technologies lack high spatial and temporal resolution. To address these issues, here, we demonstrate a label-free measurement technique based on MPM with a nonlinear optical signal purely from an intrinsic origin (RBCs). Moreover, this technology can be used to measure instantaneous blood flow velocities in a vessel at two radially symmetric positions simultaneously.

Through our measurement, we show that the radial symmetry of blood flow velocity in venules and arterioles is different from the simplified symmetric model. We measured the blood flow speed of arterioles and venules using line scans in mouse brain in vivo, and indicated a distribution of rapid flow in the middle and slow flow on both sides. For venules and arteriole, the symmetry of blood flow velocity is good near the middle of the vessel (relative velocity difference $δ < 10$ $δ < 10$ %), while the symmetry of blood flow velocity becomes worse and not so symmetric close to the vessel wall ( $δ > 10$ $δ > 10$ %). Furthermore, the symmetry of arterial flow velocity is poorer than the venule. Our more accurate results may provide guidelines for designing fluidic devices to more accurately mimic blood flow in real blood vessels.

Acknowledgments

This work is funded by the National Natural Science Foundation of China (Grant/Award Numbers 62075135 and 61975126), the Science and Technology Innovation Commission of Shenzhen (Grant/Award Numbers JCYJ20190808174819083 and JCYJ20190808175201640), Shenzhen Science and Technology Planning Project (ZDSYS 20210623092006020).

Conflicts of Interest

The authors declare that there are no conflicts of interest relevant to this paper.

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Received 10 March 2023

Accepted 11 April 2023

Published: 20 May 2023

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