1.Effectiveness evaluation of personalized medication for cardiovascular drugs based on the CYP2 C9 protein
Yuefeng TONG ; Shuai YANG ; Zhixing HU ; Yunxiang WANG ; Changchun LAI ; Zhecheng LI ; Qin SU
Military Medical Sciences 2014;(4):294-297
Objective To analyze the effectiveness evaluation of cardiovascular drugs which have been developed on the CYP2C9 target protein by multi-layer fuzzy evaluation technology .Methods The multi-layer fuzzy evaluation method was used to evaluate the effectiveness of cardiovascular drugs interacting with the CYP 2C9 protein and to construct the index system that affects drug efficacy .Results and Conclusion The index system was used to study such cardiovascular drugs as valsartan and to score the drug effectiveness of individual samples .The results were consistent with actual drug treatment and were well confirmed .The results contribute to evaluation of personalized medication .
2.Analysis of variation patterns of focal physiological uptake in the tongue on 18F-FDG PET/CT imaging
Xinzhong HAO ; Zhifang WU ; Min YAN ; Zhixing QIN ; Pengliang CHENG ; Ping WU ; Jianzhong LIU
Chinese Journal of Nuclear Medicine and Molecular Imaging 2020;40(7):415-420
Objective:To analyze variant patterns and characteristics of focal physiological uptake (FPU) in the tongue on 18F-fluorodeoxyglucose (FDG) PET/CT imaging in patients without a history of oral tumor surgery and radiotherapy. Methods:A total of 6 233 consecutive patients who underwent routine whole-body PET/CT scan between January 2013 and December 2017 in the First Hospital of Shanxi Medical University were investigated retrospectively, and 324 patients with a history of oral surgery and radiotherapy were excluded, the remaining 5 909 patients (3 418 males, 2 491 females, age range: 2-95 (average: 58) years) were enrolled. A part of the patients underwent local PET/CT scan and CT scan with diagnostic dose, covering the oral cavity on mouth-opening position. The morphological characteristics of FPU patterns were analyzed, and the maximum standardized uptake value (SUV max) was measured. Results:Seventy-six FPUs in 76 patients (49 males, 27 females, age range: 40-83 (average 64) years) identified by routine whole-body PET/CT scan were confirmed by clinical examination from a specialist in stomatology or follow-up for more than 6 months. Forty-one of the 76 patients subsequently underwent local PET/CT scan and diagnostic CT scan on mouth-opening position. The incidence of FPU in the tongue was 1.29%(76/5 909). The FPU patterns could be classified into three types: type Ⅰ with FDG uptake involved only anterior part of the tongue body in the midline (near the tip of the tongue), which showed as a " dotted" shape( n=68; 1.15%, 68/5 909); type Ⅱ with FDG uptake involved mainly middle part of the genioglossus muscle, which showed as a " bar-shorted" shape ( n=5; 0.08%, 5/5 909); type Ⅲ with FDG uptake involved large part of the tongue body and the genioglossus, which showed as a " T" shape( n=3; 0.05%, 3/5 909). The SUV max in patients with type Ⅰ and type Ⅱ were 5.53(4.53, 7.30), 19.50(17.10, 22.74) respectively. The SUV max in 3 patients with type Ⅲ were 23.34, 27.50 and 35.14, respectively. Conclusion:In patients without a history of oral tumor surgery and radiotherapy, the FPU in the tongue has its specific pattern, and PET/CT scan on mouth-opening position helps to reveal the detailed features.
3.Effects of different reconstruction algorithms on SUV of pulmonary nodules in 18F-FDG PET/CT
Bin ZHAO ; Binwei GUO ; Bin HUANG ; Meng LIANG ; Zhixing QIN ; Xinzhong HAO ; Sijin LI ; Zhifang WU
Chinese Journal of Nuclear Medicine and Molecular Imaging 2020;40(4):224-230
Objective:To compare four reconstruction algorithms of 18F-fluorodeoxyglucose (FDG) PET/CT on standardized uptake value (SUV) of pulmonary nodules. Methods:A total of 46 patients (27 males, 19 females; median age: 66 (range: 44-82) years) with solid pulmonary nodules from February 2018 to July 2019 in the First Hospital of Shanxi Medical University who performed 18F-FDG PET/CT imaging were enrolled. All PET/CT images were retrospectively reconstructed by using four algorithms reconstructions including ordered subset expectation maximization (OSEM), OSEM+ time of flight (TOF), OSEM+ TOF+ point spread function (PSF) and block sequential regularized expectation maximization (BSREM) (G1-G4). Nodule and background parameters were analyzed semi-quantitatively and visually. The maximum of SUV(SUV max), mean of SUV(SUV mean) and peak of SUV (SUV peak) were collected by the region of interest (ROI). Nodules were divided into small nodule group (diameter ≤10 mm) and large nodule group (10 mm < diameter ≤30 mm). Kruskal-Wallis rank sum test and Bonferroni method were performed to compare the differences of SUVs between G1-G4, and Spearman correlation analysis was used to analyze the correlation between the change rate of SUV (%ΔSUV) and the diameter of nodules. The receiver operating characteristic (ROC) curve analysis was used to analyze the diagnostic efficacy of SUV for the differential diagnosis of pulmonary nodules and to get the optimal threshold. Results:There were 114 pulmonary nodules (large nodules, n=55; small nodules, n=59). In visual analysis, the visual detection rates of small nodules in G4 were 55.93%(33/59), 44.07%(26/59), 20.34%(12/59) higher than those in G1-G3. Of 114 pulmonary nodules in 46 patients, there were differences in SUV max and SUV mean between G1-G4 (median SUV max : 2.65-5.29, median SUV mean: 2.05-2.99; H values: 20.628 and 17.749, respectively, both P<0.001), G4 had significant increases compared to G1 in SUV max (median 5.29 and 2.65, P<0.001) and SUV mean (median 2.99 and 2.05, P<0.001). The %ΔSUV max (median: 4.45%-52.96%) and %ΔSUV mean (median: 1.69%-47.56%) were negatively correlated with the diameter of nodules (9.75(6.20, 16.58) mm; r s values: -0.371 to -0.354, -0.371 to -0.320, all P<0.001). In 59 small nodules, G1 significantly increased the SUV max of G4 (median 4.05 and 2.14, H=18.327, P<0.001), while G4 significantly increased the SUV mean of G1 and G3 (median 2.31, 1.26 and 1.53, H=16.808, P<0.05). There was no significant difference in SUVs between G1-G4 in 55 large nodules ( H values: 0.812-7.290, all P>0.05). The optimal threshold values of SUV max in G1-G4 were 4.335, 5.185, 5.410, 5.745 and the area of under curves (AUCs) were 0.747, 0.699, 0.756, 0.778 respectively. The AUC of SUV mean and SUV peak also showed a similar trend. Conclusion:Among the four reconstruction algorithms, BRERM can not only enhance the image quality, but also significantly improve the SUV max and SUV mean of lung nodules diameter below 10 mm, and thus its diagnostic threshold of SUV should be appropriately increased.
4.Clinical study of deep learning reconstruction to improve the quality of rapidly acquired PET images
Linjun HU ; Yiyi HU ; Binwei GUO ; Meng LIANG ; Xinzhong HAO ; Zhixing QIN ; Sijin LI ; Zhifang WU
Chinese Journal of Nuclear Medicine and Molecular Imaging 2021;41(10):602-606
Objective:To improve the quality of 18F-fluorodeoxyglucose (FDG) PET images at different acquisition times through deep learning (DL) PET image reconstruction methods. Methods:A total of 45 patients (20 males, 25 females; age (52.0±13.6) years) with malignant tumors and PET/CT scans from September 2020 to October 2020 in the Department of Nuclear Medicine of the First Hospital of Shanxi Medical University were included in this retrospective study. The short acquisition time 30 s/bed PET images from the raw list mode were selected as the input of DL model. DL image reconstruction model, based on the Unet algorithm, was trained to output imitated PET images with full dose standard acquisition time (3 min). The image quality evaluation and quantitative analysis were carried out for four groups of images: DL images, 30 s, 90 s, and 120 s images, respectively. The quality of PET images in four groups was evaluated using the five-point method. Liver background activities, lesions quantification parameters (maximum standardized uptake value (SUV max), mean standardized uptake value (SUV mean), standard deviation (SD), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)), and first-order texture features (skewness, kurtosis, uniformity, entropy) were measured. Kappa test, χ2 test and one-way analysis of variance (least significant difference t test) were used for data analysis. Results:The image quality scores between four groups were highly consistent ( Kappa=0.799, P<0.001). The number of patients with scores≥3 in DL, 30 s, 90 s and 120 s groups were 6, 4, 7 and 8, respectively ( χ2=125.47, P<0.001). The liver SD of DL group was significantly lower than that of 30 s group (0.26±0.07 vs 0.43±0.11; F=3.58, t=-7.91, P<0.05). The liver SNR of DL group was higher than that of 30 s group (11.04±4.36 vs 5.41±1.41; F=10.22, t=5.40, P<0.05). The liver SD and SNR of DL group were similar to those of 90 s group (0.39±0.16, 8.46±3.34; t values: -0.87 and 2.17, both P>0.05). In 18 tumor lesions with high uptake, SNR and CNR of DL group were significantly higher than those of 30 s group (60.21±29.26 vs 38.38±16.54, 22.26±15.85 vs 15.41±9.51; F values: 13.09 and 7.05; t values: 5.20 and 4.04, both P<0.001). There were statistically significant differences among four groups in the first-order texture features ( F values: 4.30-9.65, all P<0.05), but there was no significant difference between DL group and 120 s group ( t values: from -1.25 to 0.15, all P>0.05). Conclusion:DL reconstruction model can improve the quality of short-frame PET images, which meets the needs of clinical diagnosis, efficacy evaluation and radiomics research.