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Objective: To study the application value of motion-correction phase sensitive inversion recovery (MOCO-PSIR) to evaluate myocardial fibrosis in the patients with heart failure caused by dilated cardiomyopathy (DCM)., Methods: A prospective study included 60 patients who underwent cardiac MRI enhanced scan from June 2017 to November 2018, including 38 patients who were clinically diagnosed with DCM and 22 patients in the normal control group. All patients were scanned with three late gadolinium enhancement (LGE) sequences: segmented-PSIR, single-shot-PSIR, MOCO-PSIR at the same time. The subjective quality score (level 4) and image signal-to-noise ratio (objective evaluation) of normal and abnormal myocardium were analyzed and compared in three scanning technique groups. The detection rate of myocardial fibrosis and image acquisition time of the three scanning techniques were recorded., Results: In the normal control group (sinus rhythm), subjective score showed no statistical significance. Subjective scoring results in the patients with DCM: MOCO-PSIR>single-shot-PSIR> segmented-PSIR ( P < 0.05). SNR results PSIR-LGE images in DCM patients as well as control group: segmented-PSIR>MOCO-PSIR> single-shot-PSIR ( P < 0.05). In the whole 646 segments analysis of DCM patients, the ratio unable to judge in segmented-PSIR was up to 25.5%, but only 1.4% in MOCO-PSIR. Significant difference was found in the three groups. While in the 374 segments of control group, no statistical difference was found in comparison of incapability to judge. Acquisition time covered left ventricular: (5.6±1.7) min in segmented-PSIR, (0.4±0.2) min in single-shot-PSIR and (4.5±1.1) min in MOCO-PSIR. Pairwise comparison of acquisition time among three scanning techniques was statistically significant ( P < 0.001)., Conclusion: MOCO-PSIR-LGE has better clinical significance than conventional delayed enhanced scan sequences in the diagnosis of myocardial fibrosis in the patients with heart failure caused by dilated cardiomyopathy., (Copyright© by Editorial Board of Journal of Sichuan University (Medical Science Edition).)

Aim: This study aims to investigate the manifestation of CT, MRI and dynamic enhanced scans for primary hepatic neuroendocrine cell carcinoma., Methods: CT or MRI arterial and venous phase scan images of 19 cases of pathologically confirmed PHNEC were retrospectively analyzed., Results: 14 cases (73.68%) with single lesion, 5 cases (26.3%) with multiple lesions, with an average diameter of 13.2 cm. Some 12 cases (63.16%) showed inhomogeneous enhancement, seven cases (36.8%) showed homogeneous enhancement, 13 cases (68.4%) demonstrated significant enhancement in the arterial phase, 13 cases (68.4%) had significantly enhanced portal venous phase including 7 cases (36.8 %) with portal venous phase density or signal above the arterial phase and 5 cases (26.3%) with the portal vein density or signal below the arterial phase. Seven cases (36.8%) had continued strengthened separate shadows in the center of the lesion. Thrombosis were not seen in portal veins., Conclusion: CT and MRI images of liver cell neuroendocrine carcinoma have certain characteristics that can provide valuable information for diagnosis and differential diagnosis.

Objective: To determine the diagnostic value of time-signal intensity curve (TIC) in distinguishing breast malignant tumors from benign lesions., Methods: Forty-four patients with 50 breast lesions were recruited in the study, including 24 pathologically confirmed benign lesions and 26 malignant tumors. All patients received dynamic contrast-enhanced breast MRI scanning a week before surgery. The time-signal intensity curves in the regions of interest (ROI) and eight items of TIC including shape, T peak, E peak, Slope(i), E1, E2, W peak-7, and W peak-9 were compared between benign lesions and malignant tumors. The receive operating characteristic curves (ROC) were depicted for those indicators with significant statistical differences., Results: Six items of TIC including shape, T peak, Slope(i), E1, E2, and W peak-9 were significantly different (P<0.05) between malignant tumors and benign lesions. The sensitivities of shape, T peak, Slope(i), E1, E2, and W peak-9 for diagnosing breast malignant tumors were 92.3%, 95.83%, 80.77%, 61.53%, 69.23%, and 69.23% respectively. Their specificities were 87.5%, 92.3%, 95.8%, 87.5%, 79.17%, and 79.17% respectively. TIC curve shape, T peak and Slope(i) were better than E1, E2 and W peak-9 in diagnosing breast malignant lesions (P<0.05)., Conclusion: Benign and malignant breast tumors can be differentiated according to TIC. TIC curve shape, T peak and Slope(i) are better than E1, E2 and W peak-9 in distinguishing malignant breast tumors from benign lesions.