Objective:To optimize 3.0T MRI diagnosis indicator in breast cancer and to select the best MRI scan program.
Methods:Totally 45 patients with breast cancers were collected, and another 35 patients with benign breast tumor served as the control group. All patients underwent 3.0T MRI, including T1-weighted imaging (T1WI), fat suppression of the T2-weighted imaging (T2WI), diffusion weighted imaging (DWI), 1H magnetic resonance spectroscopy (1H-MRS) and dynamic contrast enhanced (DCE) sequence. With operation pathology results as the gold standard in the diagnosis of breast diseases, the pathological results of benign and malignant served as dependent variables, and the diagnostic indicators of MRI were taken as independent variables. We put all the indicators of MRI examination under Logistic regression analysis, established the Logistic model, and optimized the diagnosis indicators of MRI examination to further improve MRI scan of breast cancer.
Results:By Logistic regression analysis, some indicators were selected in the equation, including the edge feature of the tumor, the time-signal intensity curve (TIC) type and the apparent diffusion coeffcient (ADC) value when b=500 s/mm2. hTe regression equation was Logit (P)=-21.936+20.478X6+3.267X7+21.488X3.
Conclusion:Valuable indicators in the diagnosis of breast cancer are the edge feature of the tumor, the TIC type and the ADC value when b=500 s/mm2. Combining conventional MRI scan, DWI and dynamic enhanced MRI is a better examination program, while MRS is the complementary program when diagnosis is diffcult.

Objective To explore the values of pixel indexes (PI) with multiple-slice spiral CT low-dose two-phase scanning for assessing the pulmonary function in chronic obstructive pulmonary disease (COPD).Methods Thirty-six patients with COPD (COPD group)and 30 healthy people (control group)underwent pulmonary function test (PFT).Chest 64-MSCT low-dose (50 mAs) scanning at full inspiration and expiration,routine scanning (100 mAs) at inspiration were performed.The effective dose (ED) was calculated.The lung was divided into three regions ( upper,middle,lower).PI of lung were divided into five groups:-960--1024, -910--960, -800--910, -700--800,-400--700.ThePI-910 (sum of the PI under -910 HU) of low-dose scanning at each region were measured and calculated using pulmo software. All PI included PIin-910,PIex-910,PIin-910-PIex-910, PIex-910/PIin-910 and (PIin-910-PIex-910)/PIin-910.All patients underwent PFT within 3 days after 64-MSCT canning,FEV1％ and FEV1/FVC were selected for comparison. Results The PIin in three regions ( - 960 - - 1024,-910 - -960,-800 - -910) were statistically significant between normal and COPD groups( U =0.00,57.00,20.50,P ＜ 0.01 ). The PIex in all regions were statistically significant ( U =0.00,0.00,71.52,191.00,6.00,P ＜ 0.01 ). PI-910--1024 at expiration and inspiration were correlated with FEV1％ and FEV1/FVC( r =- 0.548,- 0.664,- 0.752,- 0.781,P ＜ 0.01 ).PIin -910,PIex -910,PIex-910/PIin -910,( PIin -910-PIex -910 )/PIin -910 had a good correlation with FEV1％ and FEV1/FVC ( r =- 0.548,- 0.664,- 0.752,- 0.781,- 0.674,- 0.642,0.674,0.642,P ＜ 0.01 ).Conclusion Pixel indexes of 64-MSCT low-dose two-phase scanning can be used to evaluate pulmonary function in COPD patients.