OBJECTIVETo assess the clinical value of three-dimensional contrast-enhanced magnetic resonance angiography (3D-CE-MRA) in the diagnosis of mesenteric arteriosclerosis.

METHODS3D-CE-MRA of the mesenteric arteries was performed in 21 patients with 23 healthy subjects as the control. After 3D image reconstruction and maxi intense projection, and the abnormalities of the mesenteric arteries were observed and analyzed. The diameter and number of the arterial branches were compared between the patients and the control subjects.

RESULTSAll the 21 patients suffered arteriosclerosis in the arteries other than the mesenteric arteries. On 3D-CE-MRA, mesenteric arteriosclerosis was characterized by thinning of the arterial trunk, luminal stenosis, irregular arterial margins and homo- or heterogeneous thickening of vascular walls. Multiple filling defects were found in the mesenteric artery lumens with reduced second order branches, which showed rigid lining with dashed line appearance or disappeared in some cases. The inferior mesenteric arteries were seen in only 2 patients. The diameters of superior and inferior mesenteric arteries were 3.8-/+0.32 mm and 1.20-/+0.12 mm in the patients, significantly smaller than those of in the control subjects (6.51-/+1.01 mm and 2.90-/+0.90 mm, respectively, P<0.01). The number of the mesenteric artery branch of the patients was also significantly reduced as compared with that in the control subjects (P<0.05). In som cases, the intestinal enhancement was attenuated with the intestinal contraction, dilatation and lowering of the intestinal tension.

CONCLUSION3D-CE-MRA can clearly display mesenteric arteriosclerosis and secondary intestinal changes, and provides a useful means for the diagnosis and assisting the therapy of mesenteric arteriosclerosis.

Aged ; Aged, 80 and over ; Arteriosclerosis ; diagnosis ; pathology ; Case-Control Studies ; Contrast Media ; Female ; Humans ; Image Enhancement ; Imaging, Three-Dimensional ; Magnetic Resonance Angiography ; methods ; Male ; Mesenteric Arteries ; pathology ; Middle Aged

Objective To construct an artificial intelligence assisted diagnosis model based on deep learning for dynamically recognizing gastric lesions and their locations under gastroscopy in real time,and to evaluate its ability to detect and recognize gastric lesions and their locations.Methods The gastroscopy videos of 104 patients in our hospital was retrospectively analyzed,and the video frames were manually annotated.The annotated picture frames of lesion category were divided into the training set and the validation set according to the ratio of 8∶2,and the annotated picture frames of location category were divided into the training set and the validation set according to the patient sources at the ratio of 8∶2.These sets were utilized for training and validating the respective models.YoloV4 model was used for the training of lesion recognition,and ResNet152 model was used for the training of location recognition.The accuracy,sensitivity,specificity,positive predictive value,negative predictive value and location recognition accuracy of the auxiliary diagnostic model were evaluated.Results A total of 68 351 image frames were annotated,with 54 872 frames used as the training set,including 41 692 frames for lesion categories and 13 180 frames for location categories.The validation set consisted of 13 479 frames,comprising 10 422 frames for lesion categories and 3 057 frames for location categories.The lesion recognition model achieved an overall accuracy of 98.8%,with a sensitivity of 96.6%,specificity of 99.3%,positive predictive value of 96.3%,and negative predictive value of 99.3% in validation set.Meanwhile,the location recognition model demonstrated an top-5 accuracy of 87.1% .Conclusion The artificial intelligence assisted diagnosis model based on deep learning for real-time dynamic recognition of gastric lesions and their locations under gastroscopy has good ability in lesion detection and location recognition,and has great clinical application prospects.

Brain Mapping ; Cognitive Dysfunction ; Humans ; Magnetic Resonance Imaging ; Schizophrenia/therapy* ; Transcranial Magnetic Stimulation

During coronavirus disease 2019 epidemic, the treatment of severe trauma has been impacted. The Consensus on emergency surgery and infection prevention and control for severe trauma patients with 2019 novel corona virus pneumonia was published online on February 12, 2020, providing a strong guidance for the emergency treatment of severe trauma and the self-protection of medical staffs in the early stage of the epidemic. With the Joint Prevention and Control Mechanism of the State Council renaming "novel coronavirus pneumonia" to "novel coronavirus infection" and the infection being managed with measures against class B infectious diseases since January 8, 2023, the consensus published in 2020 is no longer applicable to the emergency treatment of severe trauma in the new stage of epidemic prevention and control. In this context, led by the Chinese Traumatology Association, Chinese Trauma Surgeon Association, Trauma Medicine Branch of Chinese International Exchange and Promotive Association for Medical and Health Care, and Editorial Board of Chinese Journal of Traumatology, the Chinese expert consensus on emergency surgery for severe trauma and infection prevention during coronavirus disease 2019 epidemic ( version 2023) is formulated to ensure the effectiveness and safety in the treatment of severe trauma in the new stage. Based on the policy of the Joint Prevention and Control Mechanism of the State Council and by using evidence-based medical evidence as well as Delphi expert consultation and voting, 16 recommendations are put forward from the four aspects of the related definitions, infection prevention, preoperative assessment and preparation, emergency operation and postoperative management, hoping to provide a reference for severe trauma care in the new stage of the epidemic prevention and control.