Prediction of intraoperative cerebrospinal fluid leaks in endoscopic endonasal transsphenoidal pituitary surgery based on a deep neural network model trained with MRI images: a pilot study.

Objective: This study aimed to investigate the reliability of a deep neural network (DNN) model trained only on contrast-enhanced T1 (T1CE) images for predicting intraoperative cerebrospinal fluid (ioCSF) leaks in endoscopic transsphenoidal surgery (EETS). Methods: 396 pituitary adenoma (PA) cases were reviewed, only primary PAs with Hardy suprasellar Stages A, B, and C were included in this study. The T1CE images of these patients were collected, and sagittal and coronal T1CE slices were selected for training the DNN model. The model performance was evaluated and tested, and its interpretability was explored. Results: A total of 102 PA cases were enrolled in this study, 51 from the ioCSF leakage group, and 51 from the non-ioCSF leakage group. 306 sagittal and 306 coronal T1CE slices were collected as the original dataset, and data augmentation was applied before model training and testing. In the test dataset, the DNN model provided a single-slice prediction accuracy of 97.29%, a sensitivity of 98.25%, and a specificity of 96.35%. In clinical test, the accuracy of the DNN model in predicting ioCSF leaks in patients reached 84.6%. The feature maps of the model were visualized and the regions of interest for prediction were the tumor roof and suprasellar region. Conclusion: In this study, the DNN model could predict ioCSF leaks based on preoperative T1CE images, especially in PAs in Hardy Stages A, B, and C. The region of interest in the model prediction-making process is similar to that of humans. DNN models trained with preoperative MRI images may provide a novel tool for predicting ioCSF leak risk for PA patients.

Deep Learning model-based approach for preoperative prediction of Ki67 labeling index status in a noninvasive way using magnetic resonance images: A single-center study.

OBJECTIVES: Ki67 is an important biomarker of pituitary adenoma (PA) aggressiveness. In this study, PA invasion of surrounding structures is investigated and deep learning (DL) models are established for preoperative prediction of Ki67 labeling index (Ki67LI) status using conventional magnetic resonance (MR) images. METHODS: We reviewed 362 consecutive patients with PAs who underwent endoscopic transsphenoidal surgery, of which 246 patients with primary PA are selected for PA invasion analysis. MRI data from 234 of these PA patients are collected to develop DL models to predict Ki67LI status, and DL models were tested on 27 PA patients in the clinical setting. RESULTS: PA invasion is observed in 46.8% of cases in the Ki67 ≥ 3% group and 33.3% of cases in the Ki67 < 3% group. Three deep-learning models are developed using contrast-enhanced T1-weighted images (ceT1WI), T2-weighted images (T2WI), and multimodal images (ceT1WI+T2WI), respectively. On the validation dataset, the prediction accuracy of the ceT1WI model, T2WI model, and multimodal model were 87.4%, 89.4%, and 89.2%, respectively. In the clinical test, 27 MR slices with the largest tumors from 27 PA patients were tested using the ceT1WI model, T2WI model, and multimodal model, the average accuracy of Ki67LI status prediction was 63%, 77.8%, and 70.4%, respectively. CONCLUSION: Preoperative prediction of PA Ki67LI status in a noninvasive way was realized with the DL model by using MRI. T2WI model outperformed the ceT1WI model and multimodal model. This end-to-end model-based approach only requires a single slice of T2WI to predict Ki67LI status and provides a new tool to help clinicians make better PA treatment decisions.

A comparative study of clinical effect of total knee arthroplasty in the treatment of primary osteoarthritis and osteoarthritis of Kashin-Beck disease.

OBJECTIVE: To evaluate the clinical efficacy of total knee arthroplasty (TKA) in the treatment of primary osteoarthritis (OA) and osteoarthritis of Kashin-Beck disease (KBD). METHODS: This study enrolled 77 KBD patients (77 knees, KBD-TKA) and 75 OA patients (75 knees, OA-TKA) who underwent TKA from September 2008 to June 2018. Clinical assessments for each patient were performed pre-operatively and last follow-up. The efficacy measures included the visual analogue scale (VAS) pain score, range of motion (ROM), Hospital for Special Surgery (HSS) score, and short form 36 Health Survey (SF-36) as well as related influencing factors between the two groups. RESULTS: All patients were followed up; the follow-up time of KBD-TKA was 14-132 months, with an average of 72.68 ± 37.55 months; OA-TKA was 15-120 months, with an average of 49.2 ± 28.91 months. There was no difference in pre-operative VAS score (7.29 vs. 7.24) and SF-36 (PCS) score (4.87 vs. 5.49) between KBD-TKA and OA-TKA (P > 0.05), while compared with OA, KBD-TKA had significantly worse pre-operative ROM (75.48° vs. 82.87°), HSS score (36.40 vs. 41.84), and SF-36 (MCS) score (26.28 vs. 28.73) (P < 0.05). At the final follow-up, there was no significant difference in VAS score (1.13 vs. 1.16), ROM (105.79 vs. 105.79), and HSS score (92.06 vs. 92.25) between KBD-TKA and OA-TKA (P > 0.05), while compared with OA, KBD-TKA had significantly worse SF-36 (PCS) score (36.90 vs. 42.00) and SF-36 (MCS) score (55.16 vs. 59.70) (P < 0.05). In a multivariate regression, controlling for multiple potential confounders, diagnosis of KBD was associated with poor quality of life after surgery, whereas pre-operative pain was specifically associated with post-operative pain. However, preoperative gender, age, BMI, and the angles of knee prosthesis (before and after surgery) were not associated with post-operative outcome. CONCLUSION: Patients with KBD undergoing primary TKA have excellent outcomes, comparable with OA at the final follow-up, in spite of worse pre-operative ROM, HSS score, and SF-36(MCS) score. However, KBD patients are worse than OA in terms of general health. Pre-operative age, gender, BMI, and the angles of knee prosthesis were not the factors influencing the clinical efficacy of TKA. The diagnosis of KBD was an independent risk factor for poor quality of life after TKA. Pre-operative pain was a clinically important predictor of outcome.

Isolated elliptically polarized attosecond soft X-ray with high-brilliance using polarization gating of harmonics from relativistic plasmas at oblique incidence.

The production of intense isolated attosecond pulse is a major goal in ultrafast research. Recent advances in high harmonic generation from relativistic plasma mirrors under oblique incidence interactions gave rise to photon-rich attosecond pulses with circular or elliptical polarization. However, to achieve an isolated elliptical attosecond pulse via polarization gating using currently available long driving pulses remains a challenge, because polarization gating of high harmonics from relativistic plasmas is assumed only possible at normal or near-normal incidence. Here we numerically demonstrate a scheme around this problem. We show that via control of plasma dynamics by managing laser polarization, it is possible to gate an intense single attosecond pulse with high ellipticity extending to the soft X-ray regime at oblique incidence. This approach thus paves the way towards a powerful tool enabling high-time-resolution probe of dynamics of chiral systems and magnetic materials with current laser technology.

Application of the burned bone morphology and DNA technology in human identification / 法医学杂志

Burned bones have their unique characteristics in investigation of fire disaster/crimes, airplane disaster, explosion and other accidents. To study the morphological changes of skeletal tissue and DNA changes at different incinerating temperature might provide precise standard means to determine genera, sex, and age. Genetic locus was also applied in the above fields. The techniques to extract and detect of DNA in burning bones have been improved in recent years. In this article investigation advancement of analysis of burned bones with the morphology, histology, and molecular biology as well as the latest methods and techniques were reviewed. These results provide a new approach for further research and practice in forensic medicine.