Simultaneous automatic arteries-veins separation and cerebral blood flow imaging with single-wavelength laser speckle imaging

Identification of cortical arteries and veins in awake mice using two-photon microscopy

Distinguishing arteries from veins in the cerebral cortex is critical for studying hemodynamics under pathophysiological conditions, which plays an important role in the diagnosis and treatment of various vessel-related diseases. However, due to the complexity of the cerebral vascular network, it is challenging to identify arteries and veins in vivo. Here, we demonstrate an artery-vein separation method that employs a combination of multiple scanning modes of two-photon microscopy and a custom-designed stereoscopic fixation device for mice. In this process, we propose a novel method for determining the line scanning direction, which allows us to determine the blood flow directions. The vasculature branches have been identified using an optimized z-stack scanning mode, followed by the separation of blood vessel types according to the directions of blood flow and branching patterns. Using this strategy, the penetrating arterioles and penetrating venules in awake mice could be accurately identified and the type of cerebral thrombus has been also successfully isolated without any empirical knowledge or algorithms. Our research presents a new, more accurate, and efficient method for cortical artery-vein separation in awake mice, providing a useful strategy for the application of two-photon microscopy in the study of cerebrovascular pathophysiology.

Statistical modeling and knowledge-based segmentation of cerebral artery based on TOF-MRA and MR-T1

BACKGROUND AND OBJECTIVE

For cerebrovascular segmentation from time-of-flight (TOF) magnetic resonance angiography (MRA), the focused issues are segmentation accuracy, vascular network coverage ratio, and cerebral artery and vein (CA/CV) separation. Therefore, cerebral artery segmentation is a challenging work, while a complete solution is lacking so far.

METHODS

The preprocessing of skull-stripping and Hessian-based feature extraction is first implemented to acquire an indirect prior knowledge of vascular distribution and shape. Then, a novel intensity- and shape-based Markov statistical modeling is proposed for complete cerebrovascular segmentation, where our low-level process employs a Gaussian mixture model to fit the intensity histogram of the skull-stripped TOF-MRA data, while our high-level process employs the vascular shape prior to construct the energy function. To regularize the individual data processes, Markov regularization parameter is automatically estimated by using a machine-learning algorithm. Further, cerebral artery and vein (CA/CV) separation is explored with a series of morphological logic operations, which are based on a direct priori knowledge on the relationship of arteriovenous topology and brain tissues in between TOF-MRA and MR-T1.

RESULTS

We employed 109 sets of public datasets from MIDAS for qualitative and quantitative assessment. The Dice similarity coefficient, false negative rate (FNR), and false positive rate (FPR) of 0.933, 0.158, and 0.091% on average, as well as CA/CV separation results with the agreement, FNR, and FPR of 0.976, 0.041, and 0.022 on average. For clinical visual assessment, our methods can segment various sizes of the vessel in different contrast region, especially performs better on vessels of small size in low contrast region.

CONCLUSION

Our methods obtained satisfying results in visual and quantitative evaluation. The proposed method is capable of accurate cerebrovascular segmentation and efficient CA/CV separation. Further, it can stimulate valuable clinical applications on the computer-assisted cerebrovascular intervention according to the neurosurgeon's recommendation.

In vivo identification of arteries and veins using two-photon excitation elastin autofluorescence

Distinguishing arteries from veins in vivo has a great significance in clinical practices and preclinical studies. Optical imaging methods such as two-photon microscopy can provide high-resolution morphological information of tissue and are therefore extremely suitable for imaging small blood vessels. However, few optical imaging methods allow in vivo identification of arteries and veins merely utilizing the autofluorescence signal of blood vessels. In this report, we found the arterial wall generates a remarkably stronger two-photon excitation autofluorescence (TPEA) signal compared with the venous wall based on BALB/c mice. According to histological analysis and fluorescence characteristic measurement, the contrast signal is confirmed to be from elastin fibers. Employing this unique feature, we propose an objective and effective artery-vein separation strategy that considers the presence of the elastin-TPEA border as the indicator of arteries. Using this strategy, the arterial and venous networks of the dorsal skin and cerebral cortex of BALB/c mice are demonstrated to be excellently mapped and accurately separated in vivo without depending on any exogenous contrast agent, empirical knowledge, and algorithm. This study may provide a novel technique for mapping arterial and venous networks for anatomic research as well as an extra aid to basic researches on the mechanism, diagnosis, and treatment of blood vessel-related diseases.

A Robust Method for Adjustment of Laser Speckle Contrast Imaging during Transcranial Mouse Brain Visualization

Laser speckle imaging (LSI) is a well-known and useful approach for the non-invasive visualization of flows and microcirculation localized in turbid scattering media, including biological tissues (such as brain vasculature, skin capillaries etc.). Despite an extensive use of LSI for brain imaging, the LSI technique has several critical limitations. One of them is associated with inability to resolve a functionality of vessels. This limitation also leads to the systematic error in the quantitative interpretation of values of speckle contrast obtained for different vessel types, such as sagittal sinus, arteries, and veins. Here, utilizing a combined use of LSI and fluorescent intravital microscopy (FIM), we present a simple and robust method to overcome the limitations mentioned above for the LSI approach. The proposed technique provides more relevant, abundant, and valuable information regarding perfusion rate ration between different types of vessels that makes this method highly useful for in vivo brain surgical operations.

Manhattan Distance-Based Adaptive 3D Transform-Domain Collaborative Filtering for Laser Speckle Imaging of Blood Flow

Laser speckle contrast imaging (LSCI) is a full-field, noncontact imaging technology for mapping blood flow with high spatio-temporal resolution, in which the speckle contrast can be estimated either in spatial domain or temporal domain. Temporal LSCI (tLSCI) provides higher spatial resolution than spatial domain does. However, when the number of sampling frames is limited, it is difficult to obtain accurate blood flow velocity owing to the significant statistical noise. The widely used spatially averaged tLSCI (savg-tLSCI) usually requires a large number of sampling frames to obtain acceptable denoising performance. Here, based on the nonlocal filtering strategy of block-matching and three-dimensional transform-domain collaborative filtering (BM3D), Manhattan distance-based adaptive BM3D (MD-ABM3D) is proposed to effectively manage the complicated inhomogeneous noise in tLSCI image and improve the signal-to-noise ratio. Manhattan distance improves the accuracy of the block matching in strong noise, and the adaptive algorithm adapts to the inhomogeneous noise and estimates suitable parameters for improved denoising. MD-ABM3D improves 4.91 dB in peak signal-to-noise ratio relative to savg-tLSCI. It achieves stability for denoising tLSCI image with different temporal windows. The image-quality evaluation of MD-ABM3D for tLSCI (t = 20 frames) equals that of savg-tLSCI (t = 60 frames). It achieves high signal-to-noise ratio with a reduced number of sampling frames. A reduced number of sampling frames are more practical for biomedical applications. It also offers higher temporal resolution and less disturbance from the motion of the moving object.

Optical Access to Arteriovenous Cerebral Microcirculation Through a Transparent Cranial Implant

BACKGROUND AND OBJECTIVE

Microcirculation plays a critical role in physiologic processes and several disease states. Laser speckle imaging (LSI) is a full-field, real-time imaging technique capable of mapping microvessel networks and providing relative flow velocity within the vessels. In this study, we demonstrate that LSI combine with multispectral reflectance imaging (MSRI), which allows for distinction between veins and arteries in the vascular flow maps produced by LSI. We apply this combined technique to mouse cerebral vascular network in vivo, comparing imaging through the skull, to the dura mater and brain directly through a craniectomy, and through a transparent cranial "Window to the Brain" (WttB) implant.

STUDY DESIGN/MATERIALS AND METHODS

The WttB implant used in this study is made of a nanocrystalline Yttria-Stabilized-Zirconia ceramic. MSRI was conducted using white-light illumination and filtering the reflected light for 560, 570, 580, 590, 600, and 610 nm. LSI was conducted using an 810 nm continuous wave near-infrared laser with incident power of 100 mW, and the reflected speckle pattern was captured by a complementary metal-oxide-semiconductor (CMOS) camera.

RESULTS

Seven vessel branches were analyzed and comparison was made between imaging through the skull, craniectomy, and WttB implant. Through the skull, MSRI did not detect any vessels, and LSI could not image microvessels. Imaging through the WttB implant, MSRI was able to identify veins versus arteries, and LSI was able to image microvessels with only slightly higher signal-to-noise ratio and lower sharpness than imaging the brain through a craniectomy.

CONCLUSIONS

This study demonstrates the ability to perform MSRI-LSI across a transparent cranial implant, to allow for cerebral vascular networks to be mapped, including microvessels. These images contain additional information such as vein-artery separation and relative blood flow velocities, information which is of value scientifically and medically. The WttB implant provides substantial improvements over imaging through the murine cranial bone, where microvessels are not visible and MSRI cannot be performed. Lasers Surg. Med. © 2019 Wiley Periodicals, Inc.

Cardiac pulsatility mapping and vessel type identification using laser speckle contrast imaging

Systemic flow variations caused by the cardiac cycle can play a role or be an important marker in both normal and pathological conditions. The shape, magnitude and propagation speed of the flow pulse reflect mechanical properties of the vasculature and are known to vary significantly with vascular diseases. Most conventional techniques are not capable of imaging cardiac activity in the microcirculation due to spatial and/or temporal resolution limitations and instead make inferences about propagation speed by making measurements at two points along an artery. Here, we apply laser speckle contrast imaging to images with high spatial resolution in the high frequency harmonics of cardiac activity in the cerebral cortex of a mouse. We reveal vessel dependent variation in the cardiac pulse activity and use this information to automatically identify arteries and veins.

Real-time, label-free, intraoperative visualization of peripheral nerves and micro-vasculatures using multimodal optical imaging techniques

Accurate, real-time identification and display of critical anatomic structures, such as the nerve and vasculature structures, are critical for reducing complications and improving surgical outcomes. Human vision is frequently limited in clearly distinguishing and contrasting these structures. We present a novel imaging system, which enables noninvasive visualization of critical anatomic structures during surgical dissection. Peripheral nerves are visualized by a snapshot polarimetry that calculates the anisotropic optical properties. Vascular structures, both venous and arterial, are identified and monitored in real-time using a near-infrared laser-speckle-contrast imaging. We evaluate the system by performing in vivo animal studies with qualitative comparison by contrast-agent-aided fluorescence imaging.

Accessing to arteriovenous blood flow dynamics response using combined laser speckle contrast imaging and skin optical clearing

Laser speckle contrast imaging (LSCI) shows a great potential for monitoring blood flow, but the spatial resolution suffers from the scattering of tissue. Here, we demonstrate the capability of a combination method of LSCI and skin optical clearing to describe in detail the dynamic response of cutaneous vasculature to vasoactive noradrenaline injection. Moreover, the superior resolution, contrast and sensitivity make it possible to rebuild arteries-veins separation and quantitatively assess the blood flow dynamical changes in terms of flow velocity and vascular diameter at single artery or vein level.

'Go with the flow ': a review of methods and advancements in blood flow imaging

Physics has delivered extraordinary developments in almost every facet of modern life. From the humble thermometer and stethoscope to X-Ray, CT, MRI, ultrasound, PET and radiotherapy, our health has been transformed by these advances yielding both morphological and functional metrics. Recently high resolution label-free imaging of the microcirculation at clinically relevant depths has become available in the research domain. In this paper, we present a comprehensive review on current imaging techniques, state-of-the-art advancements and applications, and general perspectives on the prospects for these modalities in the clinical realm.