Congenital anophthalmia and microphthalmia refer to the absence of eyeball and a significantly shortened axial length, respectively.Among them, simple microphthalmia only has a smaller eyeball volume than normal without other eye malformations.The prevalence of congenital anophthalmia and microphthalmia is 1.18/10 000 and the etiology of the diseases are dominated by genetic defects, with common causative genes including SOX2, OTX2, PAX6 and RAX.Recent research results have shown that genetic abnormalities of MAB21L1, EPHA2, VPS35L, FAT1 are also associated with the occurrence and development of the diseases.Advanced childbearing age, gestational diabetes and smoking during pregnancy are risk factors for the diseases.Congenital anophthalmia and microphthalmia can be diagnosed by ocular ultrasound or magnetic resonance imaging measurement of axial length and corneal diameter.At present, congenital anophthalmia and microphthalmia mainly focus on symptomatic treatment.The common complications of congenital anophthalmia and microphthalmia include hyperopia, glaucoma, orbital dysplasia, and uveal effusion.To provide new ideas for the diagnosis and treatment of congenital anophthalmia and microphthalmia, genetic etiology and treatment are reviewed in this article.

Objective:To measure the retinal structural and functional parameters of adult Macaca fascicularis, and explore the similarity of the retinal structural and functional parameters between non-human primates and normal human retinas.Methods:Six eyes of 3 5-year-old adult Macaca fascicularis were examined by in vivo detection including color fundus photography, retinal optical coherence tomography (OCT) and electroretinogram (ERG) to determine the thickness of the inner/outer retina at the fovea and 1 000/2 000 μm away from the nasal, temporal, superior and inferior regions of the fovea, the thickness of the retinal nerve fiber layer (RNFL), the area of optic disc, the area of optic cup, the area ratio of cup to disc and the biological parameters of flash ERG.Differences in the above parameters between left and right eyes were analyzed.The similarity of parameters between Macaca fascicularis and human was compared with reference to published literature.The use and care of animals complied with the Regulation on the Management of Experimental Animals.The study protocol was approved by the Institutional Animal Care and Use Committee of Hubei Topgene Biotechnology (NO.IACUC-2019-012). Results:The foveal thickness, optic disc area, cup-disc area ratio, and average RNFL thickness in normal adult Macaca fascicularis were (252.31±4.79)μm, (1.89±0.05)mm 2, 0.14±0.01, and (103.53±0.58)μm, respectively.The b-wave amplitude of dark-adapted 0.01 ERG was (66.75±7.29)μV.The a- and b-wave amplitudes of dark-adapted 3.0 ERG response were (57.15±15.01) and (122.10±25.51)μV, respectively.The a- and b-wave amplitudes, the amplitude of oscillation potentials, and the latency of dark-adapted 10.0 ERG response were (72.98±20.14)μV, (131.67±13.78)μV, (49.98±10.08)μV, and (30.02±5.76)ms, respectively.The a- and b-wave amplitudes of light-adapted 3.0 ERG were (9.16±2.75) and (40.43±5.57)μV, respectively.The latency and the amplitude of the light-adapted 30 Hz flicker was (26.61±1.19)ms and (24.72±5.10)μV, respectively.There was no significant difference in the parameters between left and right eyes (all at P>0.05). The retinal thickness in central fovea, mean RNFL thickness, waveform and amplitude of ERG of Macaca fascicularis were similar to normal human. Conclusions:The structure and function of the retina of adult Macaca fascicularis are similar to those of normal humans.As a laboratory animal for preclinical drug research, in vivo studies of Macaca fascicularis can refer to normal human retinal parameters.

Objective:To observe and analyze the effect of peripore cavity size on visual function of macular area before and after surgery for idiopathic macular hole (IMH).Methods:A retrospective clinical study. From July 2020 to February 2021, a total of 25 patients with 25 eyes with monocular IMH (operation group) diagnosed by ophthalmology examination in Department of ophthalmology, Fourth Hospital of Hebei Medical University were included in the study. The control group was contralateral healthy eyes. All subjects were examined by best corrected visual acuity (BCVA), microfield of vision, frequency domain optical coherence tomography (SD-OCT), and OCT angiography (OCTA). The diameter of macular hole was measured by SD-OCT. The cystic morphology of deep capillary plexus (DCP) was detected by en face OCT, and the cystic area was measured by Image J software. MP-3 microperimeter was used to measure central macular retinal light sensitivity (MS) and mean macular retinal light sensitivity (MMS). Central macular retinal light sensitivity (CMS), MMS and cystic cavity MS were measured in the operation group. MMS was measured in the control group. The microperimetry images were superimposed on the DCP layer of OCTA to identify and calculate the average MS within the lumen and compare it with the control group. Standard three incisions were performed in all affected eyes by vitrectomy of the flat part of the ciliary body + stripping of the inner boundary membrane + intraocular sterile air filling. Three months after the operation, the same equipment and methods were used to perform relevant examinations. Paired sample t test was used to compare MS between operation group and control group. Pearson correlation analysis was used to analyze the correlation between capsular area, macular hole diameter before and after operation and MS before and after operation. The correlation between BCVA and capsular area before and after surgery was analyzed by Spearman correlation analysis. Results:In the surgical group, the retinal MS was (4.24±3.07) dB. The MMS of control group was (19.08±6.11) dB. The MS in the surgical group was significantly lower than that in the control group, and the difference was statistically significant ( t=10.832, P<0.01). Before operation, the area of cyst was (1.04±0.55) mm 2, and the diameter of macular hole was (564.80±166.59) μm. CMS and MMS were (2.27±2.29) dB and (9.08±3.65) dB, respectively. The diameter of macular hole ( r=0.50, P=0.010) and BCVA before operation ( r=0.57, P<0.001) were positively correlated with peripore cavity area. Before operation, CMS and MMS were negatively correlated with peripore cavity area ( r=-0.53, -0.47; P=0.010, 0.020). At 3 months after surgery, the capsular area was negatively correlated with CMS and MMS ( r=-0.65,-0.76; P=0.020, 0.030). There was no correlation with BCVA ( r=0.23, P=0.470). Conclusions:Retinal MS is decreased in the peri-capsular area of IMH pore. There is a positive correlation between capsule area, BCVA and macular hole diameter before operation. The capsular area is negatively correlated with CMS and MMS before operation.

Objective To differentiate between pulmonary mucosa-associated lymphoid tissue lymphoma (MALT) and adenocarcinoma by radiomics, and then evaluate the diagnostic value of this novel approach. Methods We retrospectively analyzed CT images of pulmonary MALT lymphoma (n=16) and invasive pulmonary adenocarcinoma (n=41) and all these cases were confirmed by pathology in the Second Affiliated Hospital of Zhejiang University School of Medicine from June 2012 to June 2017. After we delineated the lesions as region of interest (ROI), sixty-one radiomics features were extracted from each individual's CT images by Radcloud 1.0. All cases in each group were randomly divided into training set (70％cases) and testing set(30％cases), with 7 features (Wilcoxon test) of which showed group differences and were used to train and validate a support vector machine (SVM) classifier. Results Seven of 61 radiomics features showed differences between the two groups, i.e. 10th percentile, mean, median, minimum, total energy, run length non uniformity, gray level non uniformity. Using these 7 features, the resulted SVM successfully differentiated two diseases. The SVM showed high performance with 90％precision, recall 0.89, F1-score 0.87, ROC 0.75. Conclusions Pulmonary MALT and adenocarcinoma differ in radiomics features and machine learning can utilize these features to differentiate between pulmonary MALT and adenocarcinoma. Combination of radiomics and machine learning is promising in the differential diagnosis of these two diseases.