ALOS-PALSAR datasets used in the experiment and their characteristics.
\r\n\tHydrogen gas is the key energy source for hydrogen-based society. Ozone dissolved water is expected as the sterilization and cleaning agent that can comply with the new law enacted by the US Food and Drug Administration (FDA). The law “FDA Food Safety Modernization Act” requires sterilization and washing of foods to prevent food poisoning and has a strict provision that vegetables, meat, and fish must be washed with non-chlorine cleaning agents to make E. coli adhering to food down to “zero”. If ozone dissolved water could be successively applied in this field, electrochemistry would make a significant contribution to society.
\r\n\r\n\t
\r\n\tOxygen-enriched water is said to promote the growth of farmed fish. Hydrogen dissolved water is said to be able to efficiently remove minute dust on the silicon wafer when used in combination with ultrasonic irradiation.
\r\n\tAt present researches on direct water electrolysis have shown significant progress. For example, boron-doped diamonds and complex metal oxides are widely used as an electrode, and the interposing polymer electrolyte membrane (PEM) between electrodes has become one of the major processes of water electrolysis.
\r\n\t
\r\n\tThe purpose of this book is to show the latest water electrolysis technology and the future of society applying it.
Tsunami and earthquake seriously endanger people’s lives and properties. Efficient and accurate monitoring and assessment are of crucial importance for the fast response, management, and mitigation of the disasters [1, 2, 3]. Compared with the optical remote sensing, microwave remote sensing technology such as synthetic aperture radar (SAR) has been widely applied to monitoring natural and human-induced disasters for its all-day and all-weather working capacity [4].
Polarization is an essential property of the electromagnetic wave [5, 6, 7, 8]. The polarization state of wave will change when interacting with ground object. For example, rough natural surface such as land and water often induces the strong Bragg surface scattering, while building often presents the dominant double-bounce scattering because of the dihedral corner reflectors formed by ground and the vertical wall of building. Therefore, by analyzing the polarization of the scattering wave, we can acquire the physical and geometrical information regarding the object. This is the main task of SAR polarimetry (PolSAR) [9, 10, 11].
Tsunami is often accompanied by earthquake and flooding [1, 2, 3]. It damages and inundates the buildings and causes the collapse of the ground-wall dihedral structures as well as the enhancement of the direct surface scatterers. Therefore, by analyzing the power of double-bounce scattering and surface scattering before and after the event, we can achieve an efficient monitoring of the disasters. This simple strategy has been successfully adopted in the polarimetric microwave remote sensing of tsunami/earthquake [12, 13, 14, 15, 16, 17, 18, 19, 20, 21].
Nonetheless, the extraction of double-bounce scattering and surface scattering from PolSAR image is not so straightforward because each pixel in PolSAR is a
This chapter is dedicated to enable an extension to G4U for better monitoring of tsunami/earthquake disaster. It is indicated that the unitary transformation in G4U adds a
The remainder of this chapter is arranged as follows. Section 2 presents the basic principle of PolSAR and the polarization descriptors first. The advanced four-component scattering power decompositions are then described in Section 3 to develop the EG4U. By decomposing the ALOS-PALSAR datasets of the 2011 great Tohoku tsunami/earthquake using EG4U, Section 4 evaluates and analyzes the polarimetric monitoring of disaster damages further. The chapter is eventually concluded in Section 5.
SAR is an active microwave remote sensing technique dedicated to acquire the large-scaled 2D coherent image of the earth’s surface reflectivity [9]. It transmits microwave pulses and receives the backscattering from the illuminated terrain to synthesize a high spatial resolution image. Such an active operation enables SAR an all-day working capacity independent of solar illumination. In addition, operating in the microwave region of electromagnetic spectrum avoids the effects of rain and clouds, which allows SAR an almost all-weather continuous monitoring of the earth surface [9].
Polarization characterizes the vector state of the electromagnetic wave. The polarization state of wave will change when interacting with a ground object. By processing and analyzing such change of polarization, we can obtain the material, roughness, shape, and orientation information regarding the object. The core of this change is the (Sinclair) scattering matrix
where
Generally, almost all the ground scatterers are situated in the dynamically changing environment and subjected to spatial and/or temporal variations [32]. Such scatterer is called the distributed target, and we can no longer model its scattering with a determined scattering matrix
where
The coherency matrix
where
Combining Eq. (4) into Eq. (3), the deoriented coherency matrix
Deorientation makes
A coherency matrix
Polarimetric incoherent decomposition plays an important role in the discrimination and recognition of the distributed target [22]. It pursues the scattering mechanism of the unknown target by extracting the dominant or average target (such as the Huynen-type phenomenological dichotomies [7, 32] and the eigenvalue/eigenvector-based target decompositions [9, 33]) from
Y4R and S4R decompose the target by linearly expanding matrix
The canonical models involved in the four-component model-based scattering power decompositions.
where
Parameters
Nevertheless, we obtain no scattering balance equation on
To model
Comparing Eq. (11) with Eq. (10), we can find that Eq. (11–2) gives a dichotomy to Eq. (10–2). The redundancy makes Eq. (11) have no such exact solution like Eq. (10) but some approximate ones. In G4U, Singh et al. preferred the first equation of (11–2) only.
Obviously, Eq. (11) provides us a generalized G4U (GG4U). Here we focus on the general solution to (11) for the unknowns
where
Eq. (13) comprises of five equations and six unknowns. Following Freeman-Durden [23] and Yamaguchi et al. [24], we can fix
where BC
where
By taking appropriate value to
Case (1):
This is just the parameter
Case (2):
This acts as the complement of case (1); thus we name it the dual G4U (DG4U).
Case (3):
This is the parameter
S4R can improve Y4R by strengthening the double-bounce scattering in urban area [27]. Singh et al. [28] indicated that G4U could further improve S4R in this aspect by strengthening surface scattering in the area where surface scattering is preferable to double-bounce scattering, while increasing the double-bounce scattering in the urban area where the double-bounce scattering is preferable to surface scattering. By combining the ruling in Eq. (14), we can formulate these observations as
In terms of the general expression of
From Eq. (20) we have
Then Eq. (19) will hold if
Combining
Combining Eqs. (20) and (22), after some simple deduction, we obtain
We can immediately obtain from Eq. (23) that
From Eq. (24) we obtain
where
As the adaptive combination of G4U and DG4U, EG4U is also a special case of GG4U. So we denote it as
Compared with S4R and G4U, EG4U increases surface scattering in area where surface scattering is superior to double-bounce scattering and strengthens double-bounce scattering in area where double-bounce scattering is preferable to surface scattering. Therefore, EG4U achieves not only a nice improvement to S4R, but also an effective extension to G4U. This may make EG4U more suitable to the remote sensing of tsunami/earthquake. We will investigate this in Section 4. The procedure of EG4U is outlined in Algorithm 1.
Algorithm 1: EG4U
01: Input:
02: Conduct deorientation to
03: Compute helix power
04: Calculate branch condition
05: Determine volume scattering model based on branch condition
06: Obtain volume scattering power
07: Compute parameters
08: Implement
09: if
10: Adaptively select between G4U and DG4U based on
11: if
12:
13: else
14:
15: end if
16: Calculate surface scattering power
17: if
18:
19: else
20:
21: end if
22: Implement nonnegative
23: else
24:
25: end if
26: Output:
As indicated in Subsection 3.4, G4U and S4R represent two special forms of GG4U of equal status. Hence, G4U cannot fully improve S4R only if we ascend the status of G4U by combining the duality of G4U, i.e., DG4U and G4U together for EG4U. EG4U can adaptively strengthen the surface scattering and double-bounce scattering. Therefore, it may improve the competence and performance of G4U in the remote sensing of damages caused by earthquake/tsunami disaster. We demonstrate these in the following by decomposing the ALOS-PALSAR images of the 2011 great Tohoku tsunami/earthquake using EG4U.
The great Tohoku earthquake is also known as the great Sendai earthquake or the great East Japan earthquake, which was a magnitude 9.0–9.1 (Mw) undersea megathrust earthquake off the coast of northeast Japan (the epicenter is shown in Figure 2 as “
Location of the great Tohoku tsunami/earthquake epicenter () and the ALOS-PALSAR footprint of the two selected fully polarimetric datasets (red rectangle, pre-event; blue rectangle, post-event).
The Advanced Land Observing Satellite (ALOS) was launched in 2006 by the Japanese Space Agency (JAXA). It has three remote sensing payloads, i.e., the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) for digital elevation mapping, the Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) for precise land coverage observation, and the Phased Array type L-band SAR (PALSAR) for all-day/all-weather land observation [36].
To demonstrate the capability of polarimetric remote sensing for damage monitoring, we choose two quad-polarization single-look complex-level 1.1 (ascending orbit) datasets acquired around Miyagi Prefecture, Japan, before and after the earthquake/tsunami with 138 days’ temporal baseline, as summarized in Table 1. The ALOS-PALSAR footprint of the two datasets is shown in Figure 2.
Scene ID | Acquire data | Incidence angle1 | Azimuth resolution | Ground-range resolution2 |
---|---|---|---|---|
ALPSRP257090760 | 2010-11-21 | 23.802° | 4.5 m | 23.5 m |
ALPSRP277220760 | 2011-04-08 | 23.836° | 4.5 m | 23.5 m |
ALOS-PALSAR datasets used in the experiment and their characteristics.
The incidence angle here indicates the incidence angle at the scene center.
The ground-range resolution is defined as the slant-range resolution/sin(incidence angle) [9], while the slant-range resolution of the two datasets is both 9.5 m.
The flowchart of EG4U-based monitoring and evaluation of damages caused by tsunami/earthquake disaster is illustrated in Figure 3. We first co-register the two datasets based on the image features [37, 38, 39, 40]. The boxcar filtering [9] is then carried out to both datasets to suppress the speckles. To ensure the pixel size in both image directions comparable, the window size for ensemble average is chosen as 2 pixels in ground-range direction and 12 pixels in azimuth direction, i.e., we integrate the scattering matrix
Flowchart of EG4U-based monitoring of tsunami/earthquake disaster.
Color-coded scattering power image of the study area (a) before and (b) after the great Tohoku tsunami/earthquake disaster. The framed patch regions A, B, and C are extracted for particular analysis.
For better comparison and analysis, we also display the optical image of the study area obtained from ©Google Earth in Figure 5. Our intuitive impression of Figure 4(a) and (b) is their consistency and nice correspondence to the optical image. The blue color mainly appears in the water and land areas because of the dominant surface scattering there. The red color mainly arises in the urban area, such as the Ishinomaki City and Higashi-Matsushima City, with a large number of buildings. The ground and the vertical walls of buildings constitute the dihedral corner structures, which generally reflect the dominant double-bounce scattering. Mountain presents the green color, i.e., the dominant volume scattering. The well-developed branch and crown structures of trees on the mountain complicate the scattering process, depolarize the scattering wave, and show themselves as the complex mixed volume scattering in PolSAR image. Therefore, by color-coding the scattering powers obtained by EG4U, we can achieve a nice discrimination of the ground objects.
Optical image of the study area obtained from ©Google earth. Particular attention is paid to the framed patch regions A, B, and C.
Despite the consistency, we can also observe the obvious difference between the pre- and post-event scattering power images. A lot of red pixels in Figure 4(a) change to blue pixels in Figure 4(b), particularly in the urban areas of Ishinomaki and Higashi-Matsushima, which illustrate the change from the dominant double-bounce scattering to the dominant surface scattering, denote the decrease of the dihedral structures, and indicate the collapse of buildings. Take Ishinomaki City framed in Patch A for instance; it is interesting to observe that the strong change mainly arises in the area by the seaside, while tiny change occurs in the area away from the coast. This finding is also validated by the corresponding optical images acquired before and after the event shown in Figure 6(a) and (b). Therefore, the severe damages brought by the Tohoku tsunami/earthquake are probably mainly due to the flooding rather than the earthquake. Flooding from the Onagawa Bay and the Mangokuura Sea also swept the town of Onagawa framed in Patch B, as shown in Figure 6(c) and (d) in terms of the pre- and post-event optical images. A large majority of red pixels of Patch B in Figure 4(a) change to blue pixels or even green pixels in Figure 4(b), which indicates that nearly all the buildings in Onagawa were badly damaged by the flooding except for a few buildings constructed in high elevation. The collapsed buildings not only present the dominant surface scattering here, but also the dominant volume scattering because of the complex scattering in such mountain area. The biggest change caused by flooding appears in the area along the Kitakami River. Take the town of Kamaya framed in Patch C, for example, as shown in Figure 6(e), besides several buildings, the most part of Kamaya is farmland. This area can be clearly distinguished from the Kitakami River in Figure 4(a) before the disaster. However, after the disaster, nearly all the land and buildings in Kamaya are flooded by the water from Kitakami River as shown in Figure 6(f), which present in Figure 4(b) as the wide distribution of blue pixels and show the dominant surface scattering here. Therefore, by decomposing the pre- and post-event PolSAR datasets with EG4U to construct the color-coded scattering power images, we can achieve a simple but accurate monitoring of the damages caused by tsunami/earthquake disaster.
Optical images of (first row, i.e. (a) and (b)) patch A, (second row, i.e. (c) and (d)) patch B, and (third row, i.e. (e) and (f)) patch C obtained from ©Google earth (first column, i.e. (a), (c), and (e)) before and (second column, i.e. (b), (d), and (f)) after the 3.11 great Tohoku tsunami/earthquake.
From the above analysis, we can obtain that flooding which resulted from tsunami is the main contributor to the severe damages in the 3.11 great Tohoku earthquake. The flooding destroyed the buildings and inundated the lands. All these damages present themselves in the polarization domain as the change of the dominant scattering mechanism from double-bounce scattering to surface scattering and in the image domain as the change of pixel color from red to blue. The boundary condition
Binary display of the branch condition BC extracted from (a) pre- and (b) post-event ALOS-PALSAR datasets. The white pixels correspond to BC>0, while the black pixels denote BC≤0.
Singh et al. [28] indicated that G4U could enhance double-bounce scattering over urban area while strengthen surface scattering contribution over water and land area. This establishes G4U the state-of-the-art four-component scattering power decomposition and enables its wide application to the remote sensing of forestry, agriculture, wetland, snow, glaciated terrain, earth surface, manmade target, environment, and damages caused by earthquake, tsunami, and landslide [29, 30]. Nevertheless, the rigorous derivation in Eq. (21) validates that G4U cannot always enhance the double-bounce scattering nor strengthen the surface scattering power unless we adaptively integrate G4U and its duality, i.e., DG4U, for EG4U based on another boundary condition
Binary display of the branch condition BC1 extracted from (a) pre- and (b) post-event ALOS-PALSAR datasets. The white pixels correspond to BC1>0, while the black pixels denote BC1≤0.
Flooding is the main contributor to the severe damages in the great Tohoku tsunami/earthquake. It destroyed the buildings and inundated the lands by the seaside. All these damages present themselves in the polarization domain as the change of the dominant scattering mechanism from double-bounce scattering to surface scattering and in the image domain as the change of pixel color from red to blue. The color-coded scattering power image is very useful and powerful in the qualitative evaluation of damages. The boundary condition
This work was supported in part by the National Natural Science Foundation of China under Grant No. 41871274 and No. 61971402 and by the Strategic High-Tech Innovation Fund of Chinese Academy of Sciences under Grant CXJJ19B10.
The authors declare no conflict of interest.
Sections 2 and 3 of this chapter are extracted from a journal paper of the authors submitted to IEEE Transactions on Geoscience and Remote Sensing on June 07, 2017. The paper is still under review at the time of publication of this chapter. For more details about the paper, please refer to Reference [30].
Dry eye is a type of disease caused by tear film instability and/or ocular surface damage, which results in eye discomfort and visual dysfunction [1]. The etiology and pathogenesis of dry eye are complicated. Epidemiological studies have shown that there is a positive correlation between pterygium and dry eye [2], and usually accompanied with tear film dysfunction, which is associated with pterygium hyperplasia, irregular, and non-smooth ocular surface. Surgical resection is the main treatment for pterygium which can repair the ocular surface and improve tear film function and reduce dry eye symptoms [3]. It found that different surgical methods of pterygium have different recurrence rates and different tear film function changes [4]. Now, we will summarize the changes of tear film function after different surgical methods of pterygium.
It reported that the stability of the tear film after pterygium resection is reduced, and dry eye syndrome occurs in severe cases [5]. Compared with preoperative, the tear break-up time (BUT) was significantly prolonged for 1 month after scleral exposure with simple pterygium excision. Tear-ferning test showed a significant increase in normal crystallization ratio, and conjunctival imprint cytology showed a significant increase in goblet cell density. Therefore, they thought that tear function in patients with primary pterygium improves after pterygium excision, which indicates that pterygium has a close relationship with dry eye [6]. However, there was other studies concluded that pterygium removal may not have any effect on Schirmer’s test results and tear BUT 1-month post- surgery [7]. Paton observed that a pterygium is further exacerbated by elevation of the pterygium head, dryness, and delle formation [8]. Pterygium excision can partly restore the tear functions into normal state in patients with pterygium which may be due to the increasing density of the conjunctival goblet cell and the recovery of mucus secretion [9]. Simple excision of pterygium is a traditional surgical method, but the recurrence rate is as high as 24–89% [10], and it is currently less applied.
Kilic et al. [11] investigated the effects of pterygium excision using the limbal conjunctival autografting technique on the tear function tests in 14 eyes of 13 patients. Since no difference was found in the Schirmer and tear BUT tests at 1 and 6 months postoperative versus preoperative. Shortened BUT and the reduced length of Schirmer test after the removal of pterygium combined with autologous conjunctival transplantation are related to the number of operations, the size of the scleral exposed surface, the thickness of the graft, and the location of the graft. Large removal of the nasal conjunctiva intraoperatively, too large conjunctival graft, and the location too close to the dome or too deep can all lead to shortened BUT, reduced tear secretion test length, and prone to dry eye syndrome [12]. Some authors [13] have found that compared with the opposite healthy eyes, the BUT and mucus fern test (MFT) in the eyes with pterygium were significantly different before the operation (p < 0.05). The results of the BUT and MFT in the eyes with pterygium were significantly different before and 4 weeks after the operation (p < 0.05). The BUT was prolonged and the ratio of normal crystallization in the MFT increased. Tear functions were abnormal in the eyes with pterygium. Pterygium excision combined with conjunctival autograft transplantation can partially restore the tear film function into normal state, and the tear film function was stable 4 weeks after surgery. Zeng et al. [14] compared the recurrence rates after pterygium excision combined with autologous conjunctiva and amniotic membrane transplantation. After 1 year follow-up, the results showed that the combined autologous conjunctival transplantation group was lower than the amniotic membrane transplantation group, and the difference was statistically significant (p < 0.05). No statistically significant difference was observed between the two groups in postoperative tear film BUT (p > 0.05).
The lack of stem cells at the neck of pterygium [15] provides a theoretical basis for the treatment of pterygium excision combined with limbal stem cell transplantation. Because of the low recurrence rate after excision of pterygium combined with autologous limbal stem cell transplantation [16], it is widely used. Zhang et al. [17] compared the therapeutic effects of recurrent pterygium treated by limbal stem cell autograft transplantation and amniotic membrane transplantation. After the follow-up of 6–24 months, the recurrence rate was 3.03% in limbal stem cell autograft transplantation group, and 22.86% in amniotic membrane transplantation group. There was statistical significant difference between two groups (p < 0.05). The average epithelial recovering time of corneal wound was 4.73 and 6.38 days in two groups, the difference was significant (p < 0.05). Limbal stem cells autograft transplantation can decrease the recurrent rate and improve epithelial recovering time of corneal wound. It is an ideal method of recurrent pterygium surgery. It was shown that pterygium excision combined with limbal stem cell transplantation has less effect on tear film function than traditional pterygium excision, and the incidence of dry eye is lower [18]. Other authors [19] compared the incidence of dry eye after the operation of pterygium excision combined with autologous limbal stem cell transplantation and amniotic membrane transplantation. They showed that patients with primary pterygium treated with autologous limbal stem cell transplantation can improve the tear film stability in the early postoperative period and reduce the incidence of dry eye. However, the long-term effects of the two surgical methods and the dry eye are not obvious. Clinically, the surgical method should be reasonably selected according to the actual situation of the patient. Tear film stability of pterygium excision combined with limbal stem cell transplantation is better compared with pterygium excision combined with amniotic membrane transplantation at early postoperative. Patients bear mild symptoms of dry eye [20]. Deng et al. [21] observed the situations of different surgical methods on dry eyes in patients with pterygium excision combined transplantation. Group A underwent pterygium excision combined large autologous conjunctival flap transplantation; group B underwent pterygium excision combined with small conjunctival flap; and group C underwent pterygium excision combined with small conjunctival flap with autologous limbal stem cell. Repair of postoperative corneal epithelium, tear film BUT, and questionnaire of ocular surface disease index (OSDl) preoperation and 1, 3 months postoperation were observed among three groups, which caused the situation of dry eyes by pterygium and pterygium excision were evaluated. They concluded that pterygium excision combined with small conjunctival flap and autologous limbal stem cell shows quickly corneal epithelium recover and low dry eye ratio. Jin et al. [22] investigated the effect of pterygium excision combined with autologous corneal limbus stem cells transplantation on lacrimal film recovery between primary and recurrent pterygium. About 1 week after operation, both groups appeared dryness and shortened BUT, which was more serious in recurrent pterygium group (p < 0.05); there was no significant difference in Schirmer I test between two groups. One month after operation only recurrent pterygium group appeared dryness and shortened BUT compared with primary pterygium group, which was nearly recovered (p < 0.05). Results showed that the recovery of tear stability and lacrimal secretion was poorer in recurrent pterygium than in primary pterygium, which partly explains high recurrence rate of recurrent pterygium. A study [23] suggested that pterygium excision combined with limbal stem cell transplantation can provide a healthy source of epithelial cells. The damaged corneal epithelial surface is repaired, and the limbal anatomy and physiological reconstruction are obtained by the proliferation and differentiation of stem cells and the centripetal repair of cells. Flatter graft makes smoother surface, and the tear film stability is better. In contrast, other authors [24] suggest corneal limbal conjunctival autograft combined with pterygium excision yields sound long-term efficacy and a low recurrence rate than pterygium excision with exposed sclera, and induces only mild damage on the ocular surface. No statistically significant differences are observed between the two groups regarding postoperative tear film BUT.
Amniotic membrane is a thin and transparent membrane in the placenta. It has no blood vessels and lymphatic vessels. It contains a variety of cytokines, which can effectively reduce inflammation, promote wound healing, and anti-fibrosis [25]. The recurrence rate of pterygium excision combined with amniotic membrane transplantation was significantly lower than that of single pterygium excision group [26]. Pterygium excision combined with amniotic membrane transplantation mainly inhibits fibroplasia in the operation area, inhibits leukocyte activation, reduces inflammatory reaction, reduces scar formation, inhibits vascularization, and prevents recurrence of pterygium [27]. Yao [28] compared tear BUT and Schirmer I test at preoperatively, 1, 3 months postoperatively between simple pterygium excision group and pterygium excision combined with amniotic membrane transplantation group, and ocular surface temperature and dry eye symptom score were taken at 2 months after operation. Pterygium excision combined with amniotic membrane transplantation can effectively improve the dry eye, which is conducive to the stability of tear film function. Some authors [29] compared two surgical methods (pterygium excision combined with conjunctival flap transplantation and pterygium excision combined with amniotic membrane transplantation) on tear function. BUT and Schirmer I were shortened on both groups at 1 and 3 months postoperation, and the differences were significant (p < 0.05). Pterygium excision affects tear film function at the early postoperative stage. Tear film function returns to preoperative levels 3 months after surgery. Influence of pterygium excision combined with amniotic membrane transplantation on function of the tear film is less than that of pterygium excision combined with conjunctival flap transplantation at early postoperative stage. Amniotic membrane transplantation can limit fibrosis of the sub-conjunctival tissue, improve the success rate of surgery, and reduce the incidence of postoperative dry eye. The reason is the basement membrane surface of the amniotic membrane and the fibroblasts of the conjunctiva stimulate the differentiation of conjunctival goblet cells, keeping the conjunctiva and cornea of the postoperative patients moist, reducing the incidence of dry eye [30].
MMC is an anti-tumor antibiotic isolated from the filtrate of Streptomyces cephalosporin. It inhibits the synthesis of DNA, RNA, and protein and is radiomimetic in many of its actions [31]. It could reduce tissue adhesions and scar formation that has been widely adopted in pterygium surgery to lower the recurrence rate [32]. The purpose of the use of MMC as an adjunctive treatment is to prevent the recurrence of pterygium after the surgery [33]. It has been reported that the wound tissue has not been completely repaired within 2 weeks after pterygium resection. Local use of MMC is prone to lead to ischemic necrosis of wound tissue, especially for patients with bulbar conjunctival flap transplantation [34]. Research [35] has shown that pterygium excision with a free conjunctival autograft combined with intraoperative low-dose MMC is a safe and effective technique in pterygium surgery. MMC can prevent vascular regeneration in the surgical field, prevent fibroblast proliferation and scar formation, and reduce the recurrence rate after pterygium surgery. Intraoperative administration of mitomycin C at 0.05% is safe and effective in preventing pterygium recurrences [36]. Gao et al. [37] compared the clinical efficacy of treatment on recurrent pterygium using different concentration MMC in the pterygium excision operation combined with the corneal limbal stem cell autografting. In their study, complications are corneal edema, corneal ulcer, and conjunctival flap infection. Scleral necrosis occurs in 0.2–4.5% of patients, and higher risk is linked to adjunctive use of MMC, especially more concentrated or repeated doses [38]. It was reported that a case of corneoscleral melt that occurred 50 years after resection of pterygium with postoperative administration of MMC [39]. The application of 0.2 mg/ml MMC during operation for 3 minutes could effectively control fiber hyperplasia of conjunctivas and there are no complications on cornea and sclera [40]. Study [41] shows that the dry eye symptoms, basic tear secretion and BUT values of the MMC group are significantly better than the simple pterygium excision group. The difference between the two groups is statistically significant (p < 0.05). Therefore, it is believed that the treatment of pterygium excision combined with MMC has little effect on the stability of tear film and the secretion of basic tears, and the cure rate is high, which is an effective method for treating pterygium [42]. There is no significant difference in the cure rate and recurrence rate between pterygium excision combined with MMC and pterygium excision combined with autologous limbal stem cell transplantation (p > 0.05), both of which can effectively treat primary pterygium, but pterygium excision combined with MMC treatment will not destroy the ocular surface microenvironment, and the operation is easy to master, which is worthy of clinical promotion [43]. However, some studies have shown that the use of 0.2 g/L MMC in the treatment of simple pterygium excision showed signs of significant improvement in ocular surface environment early after surgery, and patients who use 0.29/L MMC are observed obvious ocular surface damage, keratinization of epithelial cells, loss of normal cuboid morphology, loose connection between cells, increased cell gap, increased nuclear-to-plasma ratio, and marked decrease in goblet cell density in analyzed area 3 months after surgery [44].
By combining autologous corneal limbal stem cell transplantation with conjunctival flap and amnion transplantation, the barrier between corneal epithelium and conjunctival epithelium is maintained and the invasion of foreign conjunctival tissue is prevented, so that the recurrence of pterygium and relevant complications are reduced [45]. The operation of transplantation of amniotic membrane and limbal stem cells can further reduce the postoperative recurrence rate [46]. Tear function is abnormal in patients with recurrent pterygium. The tear functions in patients with recurrent pterygium can improve significantly after combined surgery, restore the cornea stem cells and cohesion margin health conjunctival, and promote the ocular surface reconstruction perfect [47]. Tear film stability of pterygium excision combined with limbal stem cell and amniotic membrane transplantation is better than that of pterygium excision combined with limbal stem cell transplantation or amniotic membrane transplantation in early postoperative stage, but the forward performance and severity of xerophthalmia after surgical treatment of pterygium are about the same. Operation method should be chosen according to the patient’s condition [48].
Pterygium is a common ocular surface disease, and the prevalence rate is high. The main treatment method is surgical resection. The recurrence rate and incidence of postoperative dry eye after traditional simple pterygium resection is high. The recurrence rate and the incidence of dry eye of pterygium excision combined with autologous limbal stem cell transplantation is low, so it is most widely used currently. The healthy conjunctival tissue will not be damaged in combined amniotic membrane transplantation which provides conditions for glaucoma filtration surgery. Combined use of low concentration of MMC can effectively reduce the recurrence rate of pterygium, easy to operate, but there are risks of long-term complications such as scleral lysis. Amniotic membrane transplantation combined with autologous limbal stem cell transplantation can reduce the recurrence rate of pterygium and recurrent pterygium, and has little effect on the tear film. The surgical method can be selected according to the actual situation of pterygium patients.
Authors are listed below with their open access chapters linked via author name:
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\\n\\n\\n\\n\\n\\n\\n\\n\\n\\nJocelyn Chanussot (chapter to be published soon...)
\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\nYuekun Lai
\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\nPrevious years (alphabetically by surname)
\\n\\nAbdul Latif Ahmad 2016-18
\\n\\nKhalil Amine 2017, 2018
\\n\\nEwan Birney 2015-18
\\n\\nFrede Blaabjerg 2015-18
\\n\\nGang Chen 2016-18
\\n\\nJunhong Chen 2017, 2018
\\n\\nZhigang Chen 2016, 2018
\\n\\nMyung-Haing Cho 2016, 2018
\\n\\nMark Connors 2015-18
\\n\\nCyrus Cooper 2017, 2018
\\n\\nLiming Dai 2015-18
\\n\\nWeihua Deng 2017, 2018
\\n\\nVincenzo Fogliano 2017, 2018
\\n\\nRon de Graaf 2014-18
\\n\\nHarald Haas 2017, 2018
\\n\\nFrancisco Herrera 2017, 2018
\\n\\nJaakko Kangasjärvi 2015-18
\\n\\nHamid Reza Karimi 2016-18
\\n\\nJunji Kido 2014-18
\\n\\nJose Luiszamorano 2015-18
\\n\\nYiqi Luo 2016-18
\\n\\nJoachim Maier 2014-18
\\n\\nAndrea Natale 2017, 2018
\\n\\nAlberto Mantovani 2014-18
\\n\\nMarjan Mernik 2017, 2018
\\n\\nSandra Orchard 2014, 2016-18
\\n\\nMohamed Oukka 2016-18
\\n\\nBiswajeet Pradhan 2016-18
\\n\\nDirk Raes 2017, 2018
\\n\\nUlrike Ravens-Sieberer 2016-18
\\n\\nYexiang Tong 2017, 2018
\\n\\nJim Van Os 2015-18
\\n\\nLong Wang 2017, 2018
\\n\\nFei Wei 2016-18
\\n\\nIoannis Xenarios 2017, 2018
\\n\\nQi Xie 2016-18
\\n\\nXin-She Yang 2017, 2018
\\n\\nYulong Yin 2015, 2017, 2018
\\n"}]'},components:[{type:"htmlEditorComponent",content:'New for 2018 (alphabetically by surname).
\n\n\n\n\n\n\n\n\n\nJocelyn Chanussot (chapter to be published soon...)
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nYuekun Lai
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\n\nAbdul Latif Ahmad 2016-18
\n\nKhalil Amine 2017, 2018
\n\nEwan Birney 2015-18
\n\nFrede Blaabjerg 2015-18
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\n\nCyrus Cooper 2017, 2018
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\n\nVincenzo Fogliano 2017, 2018
\n\nRon de Graaf 2014-18
\n\nHarald Haas 2017, 2018
\n\nFrancisco Herrera 2017, 2018
\n\nJaakko Kangasjärvi 2015-18
\n\nHamid Reza Karimi 2016-18
\n\nJunji Kido 2014-18
\n\nJose Luiszamorano 2015-18
\n\nYiqi Luo 2016-18
\n\nJoachim Maier 2014-18
\n\nAndrea Natale 2017, 2018
\n\nAlberto Mantovani 2014-18
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\n\nMohamed Oukka 2016-18
\n\nBiswajeet Pradhan 2016-18
\n\nDirk Raes 2017, 2018
\n\nUlrike Ravens-Sieberer 2016-18
\n\nYexiang Tong 2017, 2018
\n\nJim Van Os 2015-18
\n\nLong Wang 2017, 2018
\n\nFei Wei 2016-18
\n\nIoannis Xenarios 2017, 2018
\n\nQi Xie 2016-18
\n\nXin-She Yang 2017, 2018
\n\nYulong Yin 2015, 2017, 2018
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