Humans ; Metabolic Syndrome

Objective:To investigate the efficiency of deep learning image reconstruction (DLIR) algorithm in the image quality and detection of hypovascular hepatic metastases under low radiation doses in comparison with adaptive statistical iterative construction-V (ASiR-V).Methods:Fifty-six patients with suspected hypovascular hepatic metastases who needed abdominal enhanced CT scans were collected prospectively in the First Affiliated Hospital of Zhengzhou University from January to April 2021. The patients received conventional radiation dose with tube current-time products of 400 mA CT scans in the first venous phase, low-dose CT scans in the second venous phase, which were set as tube current-time products of 280 mA for group A (19 cases), 200 mA for group B (19 cases) and 120 mA for group C (18 case), respectively. The images of first venous phase and 3 groups of second venous phase were both reconstructed with ASiR-V60% and high-DLIR (DLIR-H). Quantitative parameters [image noise, liver and portal vein signal to noise ratio (SNR), contrast to noise ratio (CNR)] and qualitative parameters (overall image quality, lesion conspicuity, diagnostic confidence) were compared between ASiR-V60% and DLIR-H images, and the effective radiation dose (ED) and the lesion detectability of each group was recorded. The paired t test was used to compare quantitative parameters, whereas the Wilcoxon signed-rank test of paired data was used to compare qualitative parameters. Results:In the second venous phase, ED was (5.56±0.35) mSv in group A, (3.88±0.23) mSv in group B, and (2.42±0.23) mSv in group C, with a decrease of 30%, 50% and 70% compared with the first venous phase, respectively. Moreover, with the decrease of radiation dose, the noise gradually increased, and the CNR lesions, SNR liver and SNR portal vein all gradually decreased. DLIR-H images had statistically better quantitative scores than ASiR-V60% images when the same radiation dose was applied (all P<0.001). Furthermore, the qualitative parameters of each group decreased with the decrease of radiation dose. Under the same radiation dose, the overall image quality, lesion conspicuity and diagnostic confidence of DLIR-H were higher than those of ASiR-V60% (all P<0.001). All lesions [100% (84/84)] were detected by ASIR-V60% and DLIR-H in group A, 92.0% (75/81) in group B, and 88.0% (79/89) in group C. Conclusions:Compared with ASiR-V60%, DLIR-H could reduce image noise, improve overall image quality and lesion conspicuity of hypovascular hepatic metastases as well as increase diagnostic confidence under different radiation doses.

ObjectiveTo compare the diagnostic accuracy of five different weighting methods of Chinese medicine syndrome and then analyze their diagnostic efficacy and characteristics， by taking Diagnostic Standard for Type 2 Diabetes Mellitus （T2DM） with Dampeness-heat Syndrome （abbreviated as diagnostic standard） as an example. MethodsData from expert questionnaire on the diagnostic standard and a cross-sectional survey of 1021 patients were collected. The comparative diagnostic test accuracy （CDTA） method was used to calculate the area under the ROC curve （AUC）， area under the PR curve （AUPR）， accuracy （ACC）， sensitivity， and specificity of five commonly used weighting methods in two categories， including knowledge-driven weighting methods （expert scoring synthesis method， analytic hierarchy process， and precedence chart method） and data-driven weighting methods （logistic regression contribution method and entropy weighting method）. ResultsAmong 1021 patients with T2DM， 389 cases were diagnosed as dampness-heat syndrome. The expert scoring synthesis method， analytic hierarchy process method， and precedence chart method were basically consistent in the weight scores of each item. The expert scoring comprehensive method， analytic hierarchy process method， and entropy weighting method have a smaller difference in the weight scores of each item， while there was larger difference in the weight scores of each item of the precedence chart method and the logistic regression contribution method. The AUC （95% CI）， AUPR， ACC， sensitivity， and specifi-city of the expert scoring synthesis method were 0.913 （0.893， 0.932）， 0.851， 0.870， 0.868 and 0.875， respectively； while those of the analytic hierarchy process method were 0.910 （0.890， 0.930）， 0.838， 0.879， 0.848 and 0.896； of the precedence chart method were 0.919 （0.900， 0.937）， 0.858， 0.875， 0.871 and 0.875； of the logistic regression contribution method were 0.867 （0.842， 0.891）， 0.792， 0.853， 0.769 and 0.898； and of the entropy weighting method were 0.895 （0.873， 0.916）， 0.820， 0.869， 0.802 and 0.908. ConclusionThe knowledge-driven weighting methods are better than the data-driven weighting methods in terms of diagnostic efficacy and reflecting expert experience.