Validation of the vault prediction model based on the sulcus-to-sulcus diameter and lens thickness: a 925-eye prospective study.

BACKGROUND: To verify the accuracy and stability of the prediction formula based on the ciliary sulcus diameter and lens thickness and to analyse factors influencing the prediction results. METHODS: In total, 925 eyes from 506 subjects were enrolled in this prospective study between July 1, 2020, and June 30, 2021. Subjects were divided into four seasons, each spanning three months. The target vault was set to be between 300 µm and 700 µm according the prediction formula. The actual vault was measured one month postoperatively. The Bland-Altman test, 95% confidence intervals (95% CI) and 95% limits of agreement (95% LoA) were used to evaluate the agreement between the predicted vault and the actual vault. Eyes with absolute prediction errors greater than 300 µm were further analysed. RESULTS: The mean predicted vaults for the four seasons were 503 ± 99, 494 ± 96, 481 ± 92 and 502 ± 93 µm, while the mean actual vaults were 531 ± 189, 491 ± 179, 464 ± 179 and 529 ± 162 µm, respectively. The predicted and actual vaults of the overall subjects were 493 ± 95 and 500 ± 180 µm, respectively. Of the 925 eyes, 861 eyes (93.08%), 42 eyes (4.54%), and 22 eyes (2.38%) showed a normal vault, high vault, and low vault, respectively. Bland-Altman plots showed that the mean difference between the actual vault and predicted vault overall (± 95% LoA) was 6.43 ± 176.2 µm (-339 to 352 µm). Three UBM features may lead to large prediction errors (more than 300 µm): wide iris-ciliary angle (ICA), iris concavity and anteriorly positioned ciliary body. CONCLUSIONS: This study demonstrated the accuracy and stability of the prediction formula through the validation of a large sample size and a long time span. Wide ICA, iris concavity and anteriorly positioned ciliary body may have an effect on vault.

BgNet: Classification of benign and malignant tumors with MRI multi-plane attention learning.

Objectives: To propose a deep learning-based classification framework, which can carry out patient-level benign and malignant tumors classification according to the patient's multi-plane images and clinical information. Methods: A total of 430 cases of spinal tumor, including axial and sagittal plane images by MRI, of which 297 cases for training (14072 images), and 133 cases for testing (6161 images) were included. Based on the bipartite graph and attention learning, this study proposed a multi-plane attention learning framework, BgNet, for benign and malignant tumor diagnosis. In a bipartite graph structure, the tumor area in each plane is used as the vertex of the graph, and the matching between different planes is used as the edge of the graph. The tumor areas from different plane images are spliced at the input layer. And based on the convolutional neural network ResNet and visual attention learning model Swin-Transformer, this study proposed a feature fusion model named ResNetST for combining both global and local information to extract the correlation features of multiple planes. The proposed BgNet consists of five modules including a multi-plane fusion module based on the bipartite graph, input layer fusion module, feature layer fusion module, decision layer fusion module, and output module. These modules are respectively used for multi-level fusion of patient multi-plane image data to realize the comprehensive diagnosis of benign and malignant tumors at the patient level. Results: The accuracy (ACC: 79.7%) of the proposed BgNet with multi-plane was higher than that with a single plane, and higher than or equal to the four doctors' ACC (D1: 70.7%, p=0.219; D2: 54.1%, p<0.005; D3: 79.7%, p=0.006; D4: 72.9%, p=0.178). Moreover, the diagnostic accuracy and speed of doctors can be further improved with the aid of BgNet, the ACC of D1, D2, D3, and D4 improved by 4.5%, 21.8%, 0.8%, and 3.8%, respectively. Conclusions: The proposed deep learning framework BgNet can classify benign and malignant tumors effectively, and can help doctors improve their diagnostic efficiency and accuracy. The code is available at https://github.com/research-med/BgNet.

Clinical Significance of Preoperative CT and MR Imaging Findings in the Prediction of Postoperative Recurrence of Spinal Giant Cell Tumor of Bone.

OBJECTIVES: To explore the predictive value of preoperative imaging in patients with spinal giant cell tumor of bone (GCTB) for postoperative recurrence and risk stratification. METHODS: Clinical data for 62 cases of spinal GCTB diagnosed and treated at our hospital from 2008 to 2018 were identified. All patients were followed up for more than 2 years according to the clinical guidelines after surgery. Medical history data including baseline demographic and clinical characteristics, computed tomography (CT) and magnetic resonance imaging (MRI) findings of recurrent and non-recurrent patients were compared. Two musculoskeletal radiologists read the images and were blinded to the clinical data. The imaging features associated with postoperative recurrence were analyzed by multivariate logistic regression, and receiver operating characteristic (ROC) curve analysis was performed to determine the optimal cutoff value of the largest lesion diameter predicting recurrence after surgery. RESULTS: According to whether the disease recurred within the follow-up period, patients were divided into the recurrence group and the non-recurrence group. Of 62 patients (29 males and 33 females), 17 had recurrence and 45 did not. The recurrence rate was 27.4%. The mean follow-up time was 73.66 (± 32.92) months. The three major treatments were total en bloc spondylectomy (n = 26), intralesional spondylectomy (n = 20), and curettage(n = 16). A total of 16 CT and MRI features were analyzed. A univariate analysis showed no significant difference in age, sex, treatment, multi-vertebral body involvement, location, boundary, expansile mass, residual bone crest, paravertebral soft tissue mass, CT value, and MRI signal on T1-weighted imaging (WI), T2-WI, and T2-WI fat suppression (FS) sequences (P > 0.05). The largest lesion diameter [(4.68 ± 1.79) vs (5.92 ± 2.17) cm, t = 2.287, P = 0.026] and the vertebral compression fracture (51% vs 82%, χ2  = 5.005, P = 0.025) were significantly different between the non-recurrence and recurrence groups. Logistic regression analysis showed that both largest lesion diameter (odds ratio [OR], 1.584; 95% confidence interval [CI], 1.108-2.264; P = 0.012) and compression fracture (OR, 8.073; 95%CI, 1.481-11.003; P = 0.016) were independent predictors of postoperative recurrence. When we set the cutoff value for the largest lesion diameter at 4.2 cm, the sensitivity and specificity for distinguishing the recurrence and non-recurrence of GCTB were 94.1% and 42.2%, respectively, and the area under the curve (AUC) was 0.671. The combined model achieved a sensitivity, specificity and accuracy of 47.1%, 97.8% and 83.9%, respectively. CONCLUSIONS: In spinal GCTB, maximum lesion diameter and the vertebral compression fracture are associated with tumor recurrence after surgery, which may provide helpful information for planning personalized treatment.

[Comparison of effects of secondary in-the-bag and sulcus intraocular lens implantation in pediatric aphakia after congenital cataract operation].

OBJECTIVE: To compare the results of secondary in-the-bag intraocular lens (IOL) implantation with secondary sulcus IOL implantation in the eyes which received cataract extraction during early infancy. METHODS: A case control study. We selected 60 eyes of 44 patients with pediatric aphakia that meet the inclusion criterion in Affiliated Eye Hospital of Wenzhou Medical College from September 2005 to August, 2011. Thirty eyes received in-the-bag secondary IOL implantation and were compared with 30 eyes that received secondary sulcus IOL implantation. Data were collected for the ages at cataract extraction and at secondary IOL implantation, the preoperative axial length, the length of follow-up, postoperative complications, postoperative best-corrected visual acuity (BCVA) and refraction. When sufficient capsular opening was possible or capsular support deemed adequate, an IOL was placed within the capsular bag, otherwise the IOL was implanted in the sulcus. The χ(2) test or Fisher exact test was used to compare complications between the in-the-bag and sulcus groups. The independent-samples t test or Wilcoxon rank sum test was used to compare demographic, preoperative and postoperative refractive relevant data between the in-the-bag and sulcus groups. RESULTS: The median of 1-week-postoperative spherical equivalent clustered 1.00 D (range, -2.13 to 3.38 D) for in-the-bag group and 0.69 D (range, -2.25 to 2.38 D) for the sulcus group (Z = -1.01, P = 0.31). The median of 1-year-postoperative spherical equivalent clustered 0.00 D (range, -3.50 to 3.00 D) for in-the-bag and -0.50 D (range, -3.25 to 2.50 D) for the sulcus (Z = -0.53, P = 0.60). The last follow-up BCVA was available in 23 of 30 eyes in the in-the-bag group and 22 of 30 eyes in the sulcus group. The median of visual outcome clustered around 0.20 D (range, 0.05 to 0.70 D) for in-the-bag and 0.20 D (range, 0.05 to 0.60 D) for the sulcus (Z = -1.06, P = 0.29). The rate of nystagmus was significantly greater in the sulcus group (63.3%) than in the in-the-bag group (33.3%) (χ(2) = 5.41, P = 0.02). The incidence of strabismus, glaucoma and corneal calcific band keratopathy in the in-the-bag group were 36.7% (11/30), 3.0% (1/30) and 10.0% (3/30); 23.3% (7/30), 3.0% (1/30) and 13.3% (4/30) in the sulcus group, respectively. There were no significant differences between the two groups (Strabismus: χ(2) = 1.27, P = 0.26; Glaucoma: χ(2) = 0.16, P = 0.69; corneal calcific band keratopathy: P = 1.00). CONCLUSIONS: For children who have been aphakic due to receiving cataract extraction during their early infancy, there was no significant difference in both postoperative complications and visual acuity between the secondary in-the-bag IOL implantation and secondary sulcus IOL implantation during 1 year to 6 years follow-up time after the implantation surgery.