Neurodegenerative diseases (NDs) have become a significant threat to an aging human society. Numerous studies have been conducted in the past decades to clarify their pathologic mechanisms and search for reliable biomarkers. Magnetic resonance imaging (MRI) is a powerful tool for investigating structural and functional brain alterations in NDs. With the advantages of being non-invasive and non-radioactive, it has been frequently used in both animal research and large-scale clinical investigations. MRI may serve as a bridge connecting micro- and macro-level analysis and promoting bench-to-bed translational research. Nevertheless, due to the abundance and complexity of MRI techniques, exploiting their potential is not always straightforward. This review aims to briefly introduce research progress in clinical imaging studies and discuss possible strategies for applying MRI in translational ND research.
Animals ; Humans ; Neurodegenerative Diseases/pathology* ; Translational Research, Biomedical ; Magnetic Resonance Imaging/methods* ; Brain/pathology* ; Head/pathology*

Objective To explore the application of PDCA cycle management mode in public health emergencies in gen-eral hospitals.Methods The PDCA cycle management model was carried out.35 medical workers from Shawan People's Hos-pital of Panyu District,Guangzhou from January 2021 to December 2022 were included as research objects and divided according to different time points as cut-off points.The PDCA cycle management model was not implemented from January to December 2021.The PDCA cycle mode management will be implemented from January to December 2022.The treatment time,job burnout and emergency response ability of medical staff before and after PDCA cycle management were compared.Results After the im-plementation of PDCA cycle mode management,the pre-hospital examination,hospital admission,symptom examination and dis-ease diagnosis of medical staff were less than those before the implementation of PDCA cycle mode management,and the differ-ence was significant(P＜0.05).After the implementation of PDCA cycle mode management,the scores of emotional consump-tion and deindividuation tendency of medical staff were lower than those before the implementation of PDCA cycle mode manage-ment,while the scores of low sense of accomplishment after the implementation of PDCA cycle mode management were higher than those before the implementation of PDCA cycle mode management,with significant differences(P＜0.05).After the imple-mentation of PDCA cycle mode management,the emergency ability scores of medical staff were higher than those before the imple-mentation of PDCA cycle mode management,and the difference was significant(P＜0.05).Conclusion PDCA cycle manage-ment mode has a good application effect in public health emergencies in general hospitals,which is conducive to more efficient and successful treatment of public health emergencies.

ObjectiveTo explore the factors affecting neurobehavioral development of 18-month-old infants with low birth weight （LBW）， and to provide scientific basis for early identification of neurobehavioral abnormalities. MethodsThe information of LBW infants who required follow-up in maternal and child health care institutions of 16 districts in Shanghai from January to October 2018 was collected. The subjects who met the inclusion and exclusion criteria were investigated by questionnaire， physical growth measurement and Gesell development diagnosis evaluation. ResultsA total of 885 qualified subjects were included in this study， including 400 boys （45.2%）， 485 girls （54.8%）， 32 cases with birth weight <1 500 g （3.6%）， and 853 cases with birth weight ranging from 1 500 g to 2 500 g （96.4%）. The percentage of abnormalities in the LBW infants at 18 months was 3.3% for gross-motor， 10.3% for fine-motor， 15.7% for adaptive behaviors， 22.1% and 14% for language and personal-social behaviors （DQ≤85）， respectively. Multivariate analysis， with gender， birth weight and gestational age adjusted as confounding factors， showed the following risk factors： male for LBW fine-motor dysplasia （OR=1.86， 95%CI： 1.19‒2.90） and personal-social behavior dysplasia （OR=1.69， 95%CI： 1.14‒2.50）； gestational age less than 32 weeks for personal-social behavior dysplasia （OR=4.95， 95%CI： 2.08‒11.79）； stress during pregnancy for gross- motor dysplasia （OR=3.3， 95%CI： 1.33‒8.21）， language dysplasia （OR=1.72， 95%CI： 1.03‒2.88） and personal-social behavior dysplasia （OR=2.72， 95%CI： 1.56‒4.72）； cigarette smoke exposure during pregnancy for fine-motor dysplasia （OR=5.52， 95%CI： 2.07‒14.70） and adaptive behavior dysplasia （OR=2.88， 95%CI： 1.12‒7.43）； gestational diabetes for language dysplasia （OR=2.22， 95%CI： 1.12‒4.42）； pregnancy induced hypertension （PIH） for abnormal personal-social behavior development （OR=3.57， 95%CI： 1.86‒6.83）； and small head circumference （HCZ<-2） for gross-motor dysplasia （OR=16.15， 95%CI： 3.05‒85.69）， fine-motor dysplasia （OR=11.17， 95%CI： 1.15‒108.83） and language dysplasia （OR=7.86， 95%CI： 1.45‒42.57）. ConclusionThe neurobehavioral development of LBW infants is related to gender， gestational age， mood during pregnancy， cigarette smoke exposure during pregnancy， diseases during pregnancy and head circumference development. Thus， avoiding adverse environmental exposure during pregnancy， actively preventing complications during pregnancy， paying attention to head circumference follow-up and prevention of preterm delivery are of protective significance to the neurobehavioral development of low birth weight infants.

Objective:To optimize the scheme and process of chest CT scanning and control the dose level to the examined individuals by establishing the diagnostic reference level (DRL) and warning dose value from chest CT examinations in our hospital.Methods:The medical records for 205 511 examined individuals, who had undergone chest CT scans in the Second Affiliated Hospital of Zhejiang University Medical College from January 1, 2018 to December 31, 2019, were reviewed consecutively. For the two-year examination periods, these examined individuals were divided into two groups, one for 2018 totalling 90 507 and another for 2019 with a total of 115 004. The mean value of doses from chest CT scans in 2018 was set as the DRL for the hospital, with the 75th and 25th percentiles as the upper and lower limits of diagnostic reference range (DRR) and the 97.5th percentiles as the warning dose values. The doses above the upper limit of DRR were considered to be relatively-high whearas the ones exceeding the warning dose value to be over-high. Based on the analysis of the over high dose in 2018, the scanning scheme and inspection process of the chest CT scans were improved in 2019. The number of examinations were estimated for the 2018 period for chest plain CT scans, chest enhancement CT scans, lung cancer screening low-dose CT scans, and relatively-high and over-high dose CT scans, as well as the single scanning doses to the examined in the two groups. The number of examinations resulting in high dose to the examined due to different reasons before and after the improvement were studied. The various parameters on the examined in the two groups were compared statistically.Results:After the improvement, the average dose from chest plain CT scans decreased by 8.67 %, with the statistically significant difference as compared with before improvement ( t=55.71, P<0.05). The average dose from low-dose chest CT scans fell by 20.13% with statistically significant difference ( t=81.99, P<0.05). The fraction of the examinations with slightly-high doses arising from chest plain CT scans and low dose chest CT scans dropped by 3.66% and 17.15%, respectively. The fraction of the examinations with slightly-high dose from chest enhanced CT increased by 1.7%. The fraction of the examinations with over-high dose from chest plain CT scans, enhanced CT scans and low-dose CT scans decreased by 0.55%, 1.06% and 1.74%, respectively. After improvement, the optimized fraction of the examinations with over-high dose, dropped by 4.72%, 31.49% and 19.18% respectively. Conclusions:The establishment of the DRL and the warming dose value of for chest CT examinations in our hospital is helpful to find out the cause of high dose scanning, promote the optimization of dose, reduce the average dose to the examinedes, and avoid using excessive dose during scanning.

OBJECTIVE: To study the correlation of common cardiovascular risk factors with brain iron deposition. METHODS: Eighty-four elderly subjects without neurological diseases or brain trauma were included in the study. The cardiovascular risk factors were comprehensively assessed. MRI examination was performed to obtain high-resolution T1-weighted images and enhanced susceptibility weighted angiography (ESWAN) images, and R2^* figure was obtained by post-processing the ESWAN sequence. High definition T1 images were segmented using computer segmentation technique. After registration to the ESWAN image, R2^* values of each region of interest were extracted. Multiple linear regression analysis was used to analyze the relationship of R2^* values in each area of interest with gender, age and vascular risk factors. RESULTS Smoking was associated with increased R2^* values in the hippocampus, white matter and cortex (β=0.244, 0.317, 0.277, P<0.05 or P<0.01). Hypertension was correlated with the increase of R2^* in the putamen (β=0.241, P=0.027). Hyperglycemia was associated with the increase of R2^* in the thalamus (β=0.234, P<0.05). In the thalamus, the R2^* value of males was higher than that of females (β=0.320, P<0.05). Age was correlated with the R2^* values of thalamus, caudate nucleus, pallidus, white matter and cortex (β=-0.218、-0.254、0.216、-0.280 and -0.238, P<0.05 or P<0.01). CONCLUSIONS Common cardiovascular risk factors may lead to iron deposition in the brain, and the deposition patterns vary with the gender, age and different risk factors.

Objective: To monitor the WT1 mRNA level and its dynamic changes in patients with myelodysplastic syndromes (MDS) after hypomethylating agents (HMA) , as well as to assess the significance of WT1 mRNA levels and its dynamic changes in evaluating the efficacy of HMA and distinguishing the disease status of heterogeneous patients with stable disease (SD) . Methods: Bone marrow or peripheral blood samples of 56 patients with MDS who underwent hypomethylating agents (≥4 cycles) from November 2009 to March 2018 were tested by real-time quantitative polymerase chain reaction (PCR) to detect the expression of WT1 mRNA, and to observe the correlation between the dynamic changes of WT1 mRNA expression and clinical efficacy and prognosis of patients. Results: WT1 mRNA expression levels of MDS patients decreased significantly after 3 cycles of hypomethylating agent treatment. Besides, the WT1 mRNA expression levels of patients increased significantly after diseases progression. According to the dynamic changes of WT1 mRNA expression levels during SD, 45 cases could be further divided into increased group and non-increased group. In those SD patients with increased WT1 mRNA expression level, the ratio of suffering disease progression or transformation to AML was 95.65% (22/23) , whereas the ratio turned to be 9.09% (2/22) for the non-increased group (χ²=33.852, P<0.001) . Compared with those SD patients reporting no increase in WT1 mRNA expression level, the overall survival[17 (95%CI 11-23) months vs not reached, P<0.001] and progression-free survival [13 (95%CI 8-18) months vs not reached, P<0.001] of those SD patients reporting increase in WT1 mRNA expression level were significantly shorter. Conclusion WT1 mRNA expression level is a useful indicator to assess the efficacy of hypomethylating agents in MDS patients. Especially in patients with SD, detection of the changes in WT1 mRNA expression level is able to predict disease progression and help to make clinical decision.

Objective To differentiate between pulmonary mucosa-associated lymphoid tissue lymphoma (MALT) and adenocarcinoma by radiomics, and then evaluate the diagnostic value of this novel approach. Methods We retrospectively analyzed CT images of pulmonary MALT lymphoma (n=16) and invasive pulmonary adenocarcinoma (n=41) and all these cases were confirmed by pathology in the Second Affiliated Hospital of Zhejiang University School of Medicine from June 2012 to June 2017. After we delineated the lesions as region of interest (ROI), sixty-one radiomics features were extracted from each individual's CT images by Radcloud 1.0. All cases in each group were randomly divided into training set (70％cases) and testing set(30％cases), with 7 features (Wilcoxon test) of which showed group differences and were used to train and validate a support vector machine (SVM) classifier. Results Seven of 61 radiomics features showed differences between the two groups, i.e. 10th percentile, mean, median, minimum, total energy, run length non uniformity, gray level non uniformity. Using these 7 features, the resulted SVM successfully differentiated two diseases. The SVM showed high performance with 90％precision, recall 0.89, F1-score 0.87, ROC 0.75. Conclusions Pulmonary MALT and adenocarcinoma differ in radiomics features and machine learning can utilize these features to differentiate between pulmonary MALT and adenocarcinoma. Combination of radiomics and machine learning is promising in the differential diagnosis of these two diseases.

OBJECTIVE: To evaluate the application of MR diffusion-weighted imaging(DWI) texture features in differentiation of malignant from benign nonpalpable breast lesion for patients with microcalcifications-only in mammography. METHODS: The clinical and MR-DWI data of 61 patients with microcalcifications, who underwent three-dimensional positioning of breast X-ray wire from October 2012 to December 2015 in Zhejiang Cancer Hospital, were retrospectively analyzed, including 38 patients with malignant lesions and 23 patients with benign lesions. Two radiologists independently drew the regions of interest (ROI) on DWI for image segmentation, and 6 histogram features and 16 grayscale symbiosis matrix (GLCM) texture features were extracted on each ROI. The random forest algorithm was applied to select the features and built the classification model. The leave-one-out cross-validation (LOOCV) was used to validate the classifier, and the performance of the classifier was evaluated by ROC curve. RESULTS: Six features were selected, including histogram features of mean, variance, skewness, entropy, as well as contrast (0°) and correlation (45°) in GLCM. The histogram features of mean, variance, skewness and entropy were significantly different between the benign and malignant breast lesions (all <0.05). The AUC of the model was 0.76, and the diagnostic accuracy, sensitivity and specificity were 77.05%, 84.21% and 65.21%, respectively. CONCLUSIONS The texture feature analysis of DWI can improve the diagnostic accuracy of differentiating benign and malignant breast nonpalpable lesions with microcalcifications-only in mammography. Histogram features of mean, variance, skewness, entropy of DWI may be used as important imaging markers.
Breast ; diagnostic imaging ; Breast Neoplasms ; diagnostic imaging ; Calcinosis ; diagnostic imaging ; Diagnosis, Differential ; Diffusion Magnetic Resonance Imaging ; Female ; Humans ; Mammography ; Retrospective Studies ; Sensitivity and Specificity

OBJECTIVETo evaluate the application of CT scan in diagnosis of pathological types and origins of metastatic ovarian tumors.

METHODSClinical data, histopathological results and CT images of 43 patients with pathologically-proved metastatic ovarian tumor were retrospectively analyzed. Diagnostic values of CT imaging for pathological type and origin of metastatic ovarian tumors were evaluated.

RESULTSThe pathological types of metastatic ovarian tumor were related to the size of the lesion (<0.01), while not related to the sites of lesion (unilateral or bilateral), the cystic-solid and mixed lesions with or without separation (all>0.05). Metastatic ovarian tumors of colorectal origin were usually unilateral lesions, and showed cystic or cystic-solid masses, while those of gastric origin were usually bilateral lesions, and showed solid or solid-based masses.

CONCLUSIONSCT imaging may be of value in diagnosis of pathological types and origin of metastatic ovarian tumor.

OBJECTIVETo assess the diagnostic value of dual energy CT for lymph node metastasis in patients with non-small cell lung cancer (NSCLC).

METHODSForty NSCLC patients, including 15 cases of squamous cell carcinoma and 25 cases of adenocarcinoma, underwent dual energy CT examination in pre-contrast and venous phase contrast scans, then the CT attenuation value of the lung cancer lesions and 85 mediastinal enlarged lymph nodes (the short diameter ≥ 5 mm, 53 metastatic and 32 non-metastatic) were measured at different energy levels (40-190 keV, spacing 10 keV) in venous phase contrast. CT spectral curves of the lung cancer lesions, hilus pulmonis and mediastinal enlarged lymph nodes were produced automatically, through comparing their CT spectral curves slope to judge whether or not the lymph nodes were metastatic. Receiver operating characteristic (ROC) curve was used to evaluate the efficiency of CT spectral curve in diagnosis of lymph node metastasis.

RESULTSThe CT spectral curves slopes of the lung cancer, metastatic lymph nodes and non-metastatic lymph nodes were 1.10±0.11, 1.08±0.07 and 1.54±0.17, respectively. There was no significant difference in curve slope between metastatic lymph nodes and lung cancer (=-1.32,>0.05); while there was significant difference between non-metastatic lymph nodes and lung cancer (=-2.58,<0.05). The CT spectral curve slope ratios of metastatic and non-metastatic lymph nodes to lung cancer were 0.98±0.05 and 1.40±0.12, respectively (=-2.86,<0.05). ROC curve showed that taking CT spectral curve slope ratio of 1.15 as cut-off value for the diagnosis of metastatic lymph nodes, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 81.1%, 87.5%, 91.5%, 73.7% and 83.5%, respectively.

CONCLUSIONSDual energy CT is of value in improving the diagnostic accuracy of lymph node metastasis in NSCLC patients before treatment.