Abstract
Purpose
The blood vessel gives key information for pathological changes in a variety of diseases. In view of the crucial role of blood vessel structure, the present study aims to establish a digital human blood vessel standard model for diagnosing blood vessel-related diseases.
Methods
The present study recruited eight healthy volunteers, and reconstructed their bilateral upper extremity arteries according to CTA. The reconstructed vessels were segmented, registered, and merged into a bunch. After being cut by continuous cut planes, the dispersion of the blood vessel bunches on each cut plane were calculated.
Results
The results demonstrated that the middle segment of the brachial artery, the proximal segment of the ulnar artery, and the middle and distal segments of the radial artery had a low degree of dispersion. A standard blood vessel model was finally established by the integral method using the low-dispersion segments above. The accuracy of the standard blood vessel model was also verified by an actual contralateral vessel, which revealed that the deviation between the model and the actual normal contralateral brachial artery was relatively small.
Conclusion
The structure of the model was highly accordant with the real ones, which can be of great help in evaluating the blood vessel changes in blood vessel-related diseases, bone and soft-tissue tumors, and creating accurate surgical plans.
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1 Introduction
Blood circulation is of critical significance for life maintenance. It is extensively involved in various metabolic functions, such as oxygen and carbon dioxide exchange, digestion and absorption, and urine formation, to name just a few. The blood vessel is the basis of blood circulation, and the pathological changes of blood vessel structure can cause crucial damage of tissues, resulting in a variety of diseases [1,17]. Whereas, thus far, the standardized blood vessel model, which can serve as an essential basis for evaluating 3D blood vessel structural changes and play a critical role in blood vessel disease diagnosis and surgical planning, has not been reported. In view of this, based on the 3D reconstruction, registration, and fitting of CTA images, the present study preliminarily proposed the methods of establishing a standardized blood vessel model.
To reduce the objective influence of somatotype difference on blood vessel structure, adult volunteers with the similar height, weight, and body mass index (BMI) were recruited. In addition, considering the potential differences in structure and location of blood vessels between different genders, only male volunteers were selected in this study to ensure that the standard model established was representative.
Because the CTA data of all eight subjects were in the arterial phase when their image data were collected, the CT value of the artery was significantly higher than that of the vein, nerve, and other surrounding soft tissues, which facilitated the division of the artery structure. As a result of the gap between adjacent cut planes in CTA scanning of artery and bone structure, a morphological interpolation method was used to ensure that the interested structure could be presented stereoscopically according to the 2D image data, relatively consistently with the real structure.
Registration was the basic step of establishing the standardized blood vessel model. Because the upper limbs of different subjects had different bending angles and rotation angles when collecting CTA data, and to make the bones and blood vessels of different volunteers calculable in a unified reference system, it was necessary to align the positions of the bones and blood vessels of the volunteers, that is to say, registration. In addition, because the larger arteries of the human body have relatively uniform trends of location and direction, it is also necessary to eliminate the errors caused by the flexion, extension, and rotation of the upper limbs through segmentation of bones and blood vessels.
It has been reported that active moving anatomical markers, such as the heart surface, or manually installed body surface markers were used as the marker points for registration [18,19,20]. In this study, we used the skeleton as the marker points to ensure that the registration results were more stable and accurate, because the skeleton had no position change during image acquisition. At the same time, there was no need to install additional artificial markers, thus simplifying the operation. In addition, in this study, the registration marker points were all determined manually by senior physicians, because compromising results have been reported after the software automatically selected the marker points for automatic registration [20]. Through the unified registration reference points on the skeleton, the skeleton and the corresponding blood vessels of different positions can be registered, by which the error caused by the limb angle and length can be eliminated, making the data of different volunteers comparable. The blood vessel bundle formed by registration will have a relatively uniform blood vessel direction, which has been delineated in the present study, forming the basis for further blood vessel fitting. For the same marker points, the larger the volume of the holistic matching part, the larger the matching error becomes. In our previous exploration experiment, the whole body skeleton had been registered as a whole with the upper limb skeleton providing the marker points for matching. However, great deviation was found at the shanks and feet, far away from the upper extremity, which undoubtedly could not provide guaranteed accuracy for further blood vessel fitting. In similar studies, there were also reports that the registration employing marker points far from the interested area became ineffective, necessitating manual recalibration [18]. In our study, we used segmental registration, which focused exactly on the local area. Utilizing the nearby bones, the segmented blood vessels of the upper limbs underwent precise registration, improving the accuracy of the subsequent standard blood vessel model fitting.
The processes of dispersion analysis and blood vessel fitting were the next core steps in creating a standardized blood vessel model. The calculation of blood vessel dispersion has been reported, but it was mainly focused on the micro-vessel; moreover, the degree of dispersion was largely estimated using pixel and image processing [21,22,23]. Therefore, in this study, in which we aimed to find the distance between the macro-vessel structure, it was innovative to use the integration method to accurately calculate the dispersion degree and fit the standard vessel model. In the present study, through calculation, it was found that the proximal and distal segments of the brachial artery had high degrees of dispersion, which were not suitable to serve as basic segments for standardized blood vessel model fitting. This high dispersion was particularly obvious in the proximal segments, which might be accounted for by the subclavian artery. During CTA data collection, raising or distaling the shoulder will significantly change the relative position relationship between the humeral head and the sternoclavicular joint, after which the arteries between those two will demonstrate completely different directions. Meanwhile, respiratory movement will also lead to the continuous change of thoracic cavity volume, leading to the relative displacement of the blood vessels close to the thoracic cavity and even motion artifact [18, 19, 24, 25]. By instructing volunteers to take a unified posture for image acquisition, or using some simple fixing stents, this type of dispersion will be reduced. In addition, it is worth mentioning that most blood vessels in the human body will not have such a large, uncorrectable deviation due to the change of posture. Therefore, this method of establishing standard blood vessel model through segmentation, registration, and fitting was valuable and innovative for the evaluation of most of the blood vessels in the human body.
The accordance of the standard blood vessel model was evaluated by actual contralateral blood vessels. And, a high degree of coincidence between them was evident. In view of the symmetry of the blood vessel development in both upper limbs with respect to normal people, the satisfactory accordance has excellent medical value.
There were some limitations in this study. Initially, the calculated standard model can be more accurate and targeted by larger sample size and grou** the subjects by different genders and heights, and calculating the standard model respectively, rather than simply expanding the sample size and trying to use one model to represent all kinds of people. However, the grou** methods were not achievable due to the limited sample size, and the sample size was limited to the difficulty of recruiting healthy volunteers willing to undergo CTA with relatively consistent height, body shape and gender. Second, the blood vessel centerline has been reported to be employed for automatic blood vessel segmentation, while in the present study, the inefficient method of manual segmentation was still in use[20]. Third, the point cloud, iterative-closest-point matching algorithm, and semiautomatic rigid 3D registration have been shown to be capable of registration with promising results [19]. Instead, in this study, a simple point-to-point registration with three marker points was used, potentially causing some imprecision. Finally, the iterative method was demonstrated to be able to achieve optimization of registration through repeated calculation, which can serve as a complement in our follow-up study [26].
5 Conclusion
The present study showed that the human standard blood vessel model based on image registration and fitting technology has promising representativeness for blood vessel structures in the human body, and can further provide a fast, practical, and innovative model for the diagnosis and treatment of relevant diseases.
Data Availability
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Code Availability
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References
Varinska, L., Gal, P., Mojzisova, G., Mirossay, L., & Mojzis, J. (2015). Soy and breast cancer: Focus on angiogenesis. International Journal of Molecular Sciences, 16, 11728–11749.
**g, B. Q., Ou, Y., Zhao, L., **e, Q., & Zhang, Y. X. (2017). Experimental study on the prevention of liver cancer angiogenesis via miR-126. European Review for Medical and Pharmacological Sciences, 21, 5096–5100.
Yeo, D. M., et al. (2015). Correlation of dynamic contrast-enhanced MRI perfusion parameters with angiogenesis and biologic aggressiveness of rectal cancer: Preliminary results. Journal of Magnetic Resonance Imaging: JMRI, 41, 474–480.
**e, L., Ji, T., & Guo, W. (2017). Anti-angiogenesis target therapy for advanced osteosarcoma (Review). Oncology Reports, 38, 625–636.
Leaute-Labreze, C., Harper, J. I., & Hoeger, P. H. (2017). Infantile haemangioma. The Lancet (London, England), 390, 85–94.
Braunagel, M., et al. (2018). Dynamic CTA in native kidneys using a multiphase CT protocol-potential of significant reduction of contrast medium. Academic Radiology, 25, 842–849.
Tuncay, V., et al. (2018). Non-invasive assessment of coronary artery geometry using coronary CTA. Journal of Cardiovascular Computed Tomography, 12, 257–260.
Ibukuro, K., Takeguchi, T., Fukuda, H., Abe, S., Tobe, K., & Tagawa, K. (2013). Spatial relationship between the hepatic artery and portal vein based on the fusion image of CT angiography and CT arterial portography: The left hemiliver. AJR American Journal of Roentgenology, 200, 1160–1166.
Wang, L. H., et al. (2017). CTGF promotes osteosarcoma angiogenesis by regulating miR-543/angiopoietin 2 signaling. Cancer Letters, 391, 28–37.
Lu, Y., et al. (2017). MicroRNA-140-5p inhibits invasion and angiogenesis through targeting VEGF-A in breast cancer. Cancer Gene Therapy, 24, 386–392.
Yang, W., et al. (2017). In vivo inhibitory activity of andrographolide derivative ADN-9 against liver cancer and its mechanisms involved in inhibition of tumor angiogenesis. Toxicology and Applied Pharmacology, 327, 1–12.
Tankova, L., et al. (2019). Endorectal power Doppler ultrasonography is a reliable method for evaluation of rectal cancer angiogenesis. European Review for Medical and Pharmacological Sciences, 23, 1661–1667.
Chaichanyut, M., & Tungjitkusolmun, S. (2016). Microwave ablation using four-tine antenna: Effects of blood flow velocity, vessel location, and total displacement on porous hepatic cancer tissue. Computational and Mathematical Methods in Medicine, 2016, 4846738.
Cheezum, M. K., et al. (2017). Anomalous origin of the coronary artery arising from the opposite sinus: Prevalence and outcomes in patients undergoing coronary CTA. European Heart Journal Cardiovascular Imaging, 18, 224–235.
Zhang, J., Wang, Y., & Geng, D. (2010). Intracranial epithelioid hemangioendothelioma: An unusual CTA finding in one case. British Journal of Neurosurgery, 24, 294–295.
Acar, G., et al. (2015). Relationship of neutrophil-lymphocyte ratio with the presence, severity, and extent of coronary atherosclerosis detected by coronary computed tomography angiography. Angiology, 66, 174–179.
Meng, X., Mi, Q., Fang, S., & Zhong, W. (2015). Preoperative evaluation of renal artery anatomy using computed tomography angiography to guide the superselective clam** of renal arterial branches during a laparoscopic partial nephrectomy. Experimental and Therapeutic Medicine, 10, 139–144.
Vernikouskaya, I., Rottbauer, W., Seeger, J., Gonska, B., Rasche, V., & Wohrle, J. (2018). Patient-specific registration of 3D CT angiography (CTA) with X-ray fluoroscopy for image fusion during transcatheter aortic valve implantation (TAVI) increases performance of the procedure. Clinical Research in Cardiology, 107, 507–516.
Nypan, E., Tangen, G. A., Manstad-Hulaas, F., & Brekken, R. (2019). Vessel-based rigid registration for endovascular therapy of the abdominal aorta. Minimally Invasive Therapy & Allied Technologies: MITAT, 28, 127–133.
von Spiczak, J., et al. (2018). Fusion of CT coronary angiography and whole-heart dynamic 3D cardiac MR perfusion: Building a framework for comprehensive cardiac imaging. The International Journal of Cardiovascular Imaging, 34, 649–660.
Righi, M., Locatelli, S. L., Carlo-Stella, C., Presta, M., & Giacomini, A. (2018). Vascular amounts and dispersion of caliber-classified vessels as key parameters to quantitate 3D micro-angioarchitectures in multiple myeloma experimental tumors. Scientific Reports, 8, 17520.
Righi, M., Giacomini, A., Cleris, L., & Carlo-Stella, C. (2013). (3)D [corrected] quantification of tumor vasculature in lymphoma xenografts in NOD/SCID mice allows to detect differences among vascular-targeted therapies. PLoS ONE, 8, e59691.
Righi, M., Giacomini, A., Lavazza, C., Sia, D., Carlo-Stella, C., & Gianni, A. M. (2009). A computational approach to compare microvessel distributions in tumors following antiangiogenic treatments. Laboratory Investigation, 89, 1063–1070.
Qiu, L., Tan, H., Cheng, D., & Shi, H. (2018). The incremental clinical value of cardiac hybrid SPECT/CTA imaging in coronary artery disease. Nuclear Medicine Communications, 39, 469–478.
Fyrdahl, A., et al. (2018). Pulmonary artery imaging under free-breathing using golden-angle radial bSSFP MRI: A proof of concept. Magnetic Resonance in Medicine, 80, 1847–1856.
Nandish, S., Prabhu, G., & Rajagopal, K. V. (2017). Multiresolution image registration for multimodal brain images and fusion for better neurosurgical planning. Biomedical journal, 40, 329–338.
Acknowledgements
The first three authors (Dinghao Luo, Junxiang Wu, Ning Wang) contributed equally to this manuscript. The authors declare that they have no conflict of interest. This study was supported by grants from National Natural Science Foundation of China (81301546), 3D Snowball Project of Shanghai Jiaotong University School of Medicine (GXQ202009), Clinical Research Project of Multi-Disciplinary Team, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine (201701003), Shanghai Clinical Medical Center (2017ZZ01023), Shanghai Municipal Key Clinical Specialty, the National Key R&D Program of China (2016YFC1100600), General program of NSFC (81972058) and Shanghai Key Clinical Specialty Construction Project - Biomedical Materials (matching funds), Three-year Action Plan of Shenkang Development Center (SHDC2020CR2019B), Huangpu District Industrial Support Fund (XK2020009) and National Key Science and Technology Infrastructure of Translational Medicine (Shanghai) Open Project (TMSZ-2020-207).
Funding
This study was supported by grants from National Natural Science Foundation of China (81301546), 3D Snowball Project of Shanghai Jiaotong University School of Medicine (GXQ202009), Clinical Research Project of Multi-Disciplinary Team, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine (201701003), Shanghai Clinical Medical Center (2017ZZ01023), Shanghai Municipal Key Clinical Specialty, the National Key R&D Program of China (2016YFC1100600), General program of NSFC (81972058) and Shanghai Key Clinical Specialty Construction Project - Biomedical Materials (matching funds), Three-year Action Plan of Shenkang Development Center (SHDC2020CR2019B), Huangpu District Industrial Support Fund (XK2020009) and National Key Science and Technology Infrastructure of Translational Medicine (Shanghai) Open Project (TMSZ-2020-207).
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Luo, D., Wu, J., Wang, N. et al. Establishment of Standard Human Blood Vessel Model Based on Image Registration and Fitting Technology. J. Med. Biol. Eng. 42, 21–28 (2022). https://doi.org/10.1007/s40846-022-00677-9
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DOI: https://doi.org/10.1007/s40846-022-00677-9