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

Objective:This study introduces a novel approach utilizing a self-made drug delivery cannula implanted into the cerebellomedullary cistern(CMC)of rats to allow repeated administrations in conscious subjects.Methods:A self-made medication cannula is inserted through a drilled hole at the midpoint of the occipital crest of the rat's skull,de-scending along the inner wall of the occipital bone until reaching the CMC,and securing it in place with skull screws and self-curing resin.Lipopolysaccharide(LPS)is injected into the CMC to induce neuroinflammation,and the feasibility of this method is assessed using X-ray imaging,behavioral testing,and immunofluorescence staining.Results:The place-ment of the brain cannula was confirmed using X-ray film and pontamine sky blue staining.Rats in the LPS group exhib-ited a lower facial mechanical pain threshold compared to the Control group(P＜0.001),along with reduced residence time in the open field center(P＜0.01).Immunofluorescence staining revealed LPS-induced activation of caudal spinal trigeminal nucleus(SpVc)microglia.Conclusion:This method proves to be suitable for multiple administrations to the cerebellomedullary cistern of conscious rats,enabling the study of the SpVc's role in pain modulation.