Objective To evaluate MRI diagnostic accuracy and clinical value on the pancreatic carcinoma.Methods 79 patients with suspected pancreatic carcinoma were imaged by T1-weighted spin-echo pulse sequences and T2-weighted fast spin-echo pulse sequences in axial,sagittal and coronal planes with a pelvic phased-array coils.Results 43 patients were diagnosed as pancreatic carcinoma using MR imaging,in which 39 patients were proved pathologically by biopsy.Conclusion MRI is effective diagnostic modality in localizing and staging pancreatic carcinoma and guiding for the choice of pancreatic carcinoma treatment.

Objective:To investigate the clinical characteristics and possible mechanisms of remote intracranial hematoma (RIH) in patients with intracranial aneurysm after interventional embolization.Methods:Six patients with RIH from a series of 58 consecutive patients with intracranial aneurysm, admitted to and performed interventional embolization in our hospital from January 2016 and December 2018, were chosen in our study. Their clinical data were analyzed retrospectively and compared with those without RIH at the same period.Results:In these 6 patients, 4 had history of hypertension, 5 had aneurysm located in the internal carotid artery, 5 were treated with stents combined with postoperative routine anticoagulation treatment. The remote intracranial hematoma occurred within 7 d of interventional embolization, and the hematoma was located in the cerebral hemisphere on the same side of the aneurysm; 4 patients underwent intracranial hematoma puncture catheter drainage; 1 patient was treated conservatively, and one was treated by craniotomy. After treatment, 1 patient recovered (modified Rankin scale [mRS] score of 1), 1 patient had poor prognosis (mRS scores of 5) and discharged automatically, and the rest 4 patients (mRS scores of 3-5) left some degrees of neurological dysfunction. As compared with 52 patients without RIH, 6 patients with RIH had significantly higher percentages of patients used stents and postoperatively used anticoagulation, and higher percentages of patients with poor clinical outcomes at discharge ( P<0.05). Conclusion:Stent-assisted coil embolization in patients with internal carotid artery aneurysm combined with hypertension should be highly vigilant about the possibility of RIH.

Objective:To explore the effectiveness of deep learning image reconstruction (DLIR) algorithm compared to adaptive statistical iterative reconstruction (ASIR-V) algorithm in improving the quality of low-dose brain CT images.Methods:Retrospective inclusion of patients who underwent brain CT examination in the People's Liberation Army General Hospital from November 2021 to August 2022. Four different algorithms were used to reconstruct low-dose CT scans of all patients to obtain 30% intensity ASIR-V (ASIR-V-30%) images, low intensity DLIR (DLIR-L) images, medium intensity DLIR (DLIR-M) images, and high intensity DLIR (DLIR-H) images. The regions of interest were selected from four sets of images, including superficial white matter, superficial gray matter, deep white matter, and deep gray matter, and their CT values and standard deviations were measured for calculating signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR).Subjective evaluation of image quality was conducted by three neuroimaging physicians based on the Likert 5-component scale. The objective and subjective scores of the 4 groups of images were analyzed using ANOVA or Kruskal Wallis. If there are overall differences, pairwise comparisons were conducted within the group.Results:A total of 109 patients were enrolled, including 104 males and 5 females, aged 65-110 years (89.16 ± 9.53) years. The radiation exposure of brain CT low-dose scanning was (0.93 ± 0.01)mSv, significantly lower than that of conventional scanning (2.92 ± 0.01) mSv ( t = 56.15, P < 0.05). The differences in objective image quality analysis of ASIR-V-30%, DLIR-L, DLIR-M, and DLIR-H images of low-dose CT in SNR deep gray matter, SNR deep white matter, SNR superficial gray matter, SNR superficial white matter, CNR deep gray white matter, and CNR superficial gray white matter were statistically significant( F =98.23, 72.95, 68.43, 58.24, 241.13, 289.91, P < 0.05). Among them, DLIR-H images had the lowest noise in deep gray matter, deep white matter, superficial gray matter, and superficial white matter, and had statistically significant differences compared to other image groups ( t = 167.43, 275.46, 182.32, 361.54, P < 0.05). The subjective score of DLIR-H image quality was superior to ASIR-V-30%, DLIR-L, and DLIR-M, with the statistically significant difference ( t = 7.25, 8.32, 9.63, P < 0.05). Conclusions:Compared with ASIR-V, DLIR algorithm can effectively reduce image noise and artifacts in low-dose brain CT, and improve SNR and CNR. The subjective and objective image quality evaluation of DLIR-H is the best.