BACKGROUND: Neoadjuvant chemoradiotherapy followed by radical surgery has been a common practice for patients with locally advanced rectal cancer, but the response rate varies among patients. This study aimed to develop a ResNet-Vision Transformer based magnetic resonance imaging (MRI)-endoscopy fusion model to precisely predict treatment response and provide personalized treatment. METHODS: In this multicenter study, 366 eligible patients who had undergone neoadjuvant chemoradiotherapy followed by radical surgery at eight Chinese tertiary hospitals between January 2017 and June 2024 were recruited, with 2928 pretreatment colonic endoscopic images and 366 pelvic MRI images. An MRI-endoscopy fusion model was constructed based on the ResNet backbone and Transformer network using pretreatment MRI and endoscopic images. Treatment response was defined as good response or non-good response based on the tumor regression grade. The Delong test and the Hanley-McNeil test were utilized to compare prediction performance among different models and different subgroups, respectively. The predictive performance of the MRI-endoscopy fusion model was comprehensively validated in the test sets and was further compared to that of the single-modal MRI model and single-modal endoscopy model. RESULTS: The MRI-endoscopy fusion model demonstrated favorable prediction performance. In the internal validation set, the area under the curve (AUC) and accuracy were 0.852 (95% confidence interval [CI]: 0.744-0.940) and 0.737 (95% CI: 0.712-0.844), respectively. Moreover, the AUC and accuracy reached 0.769 (95% CI: 0.678-0.861) and 0.729 (95% CI: 0.628-0.821), respectively, in the external test set. In addition, the MRI-endoscopy fusion model outperformed the single-modal MRI model (AUC: 0.692 [95% CI: 0.609-0.783], accuracy: 0.659 [95% CI: 0.565-0.775]) and the single-modal endoscopy model (AUC: 0.720 [95% CI: 0.617-0.823], accuracy: 0.713 [95% CI: 0.612-0.809]) in the external test set. CONCLUSION The MRI-endoscopy fusion model based on ResNet-Vision Transformer achieved favorable performance in predicting treatment response to neoadjuvant chemoradiotherapy and holds tremendous potential for enabling personalized treatment regimens for locally advanced rectal cancer patients.
Humans ; Rectal Neoplasms/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Middle Aged ; Neoadjuvant Therapy/methods* ; Aged ; Adult ; Chemoradiotherapy/methods* ; Endoscopy/methods* ; Treatment Outcome

Neonatal hypoglycemia is a common clinical disease.Hypoglycemia can lead to severe acute and long-term dysfunction of nervous system.The several aspects of neonatal hypoglyccmia such as the definition,diagnosis of brain injury,risk factors,treatment,detection method and long-term follow-up were reviewed.

Objective To compare the chemical constituents between the dispensing granules and the decoction of Buyanghuanwutang. Methods TLC and HPLC methods were carried out for comparative analysis. Results TLC indicated the chemical constituents were similar between the dispensing granule and the decoction. The HPLC method was successfully established,and used for taking the contents of paeoniflorin in dispensing granule and the decoction of Buyanghuanwutang. The contents of paeoniflorin in dispensing granule were only one sixth of that in the decoction. Conclusion The chemical constituents of the two preparations are similar,but the contents of paeoniflorin are different.

Objective: To study the anti hyperglycemic effect of rubusoside on diabetic rats induced by streptozotocin (STZ)and its mechanism . Methods: The STZ induced diabetic rats were dived into three groups and were given (ig.) saline, rubusoside and Phenformin respectively once a day. After three weeks, the levels of serum glucose, fructosamine, insulin,SOD were assayed. Results: Rubusoside could reduce the level of serum glucose significantly, enhance the ability of anti oxidation and stimulate the secretion of insulin in STZ induced diabetic rats. Conclusion: The action of rubusoside on secretion of insulin can be explained for the anti hyperglycemic effect.