Using Apparent Diffusion Coefficient (ADC) of Endometrial Cancer MRI to Determine P53 Molecular Subtypes.

BACKGROUND: Endometrial Cancer (EC) is a highly heterogeneous cancer comprising both histological and molecular subtypes. Using a non-invasive modality method to trigger these subtypes as early as possible can aid clinicians in establishing individualized treatment. PURPOSE: The study aimed to clarify the value of the Apparent Diffusion Coefficient (ADC) of EC MRI in determining molecular subtypes. MATERIAL AND METHODS: We retrospectively recruited 109 patients with pathologically proven EC (78 endometrioid cancers and 31 non-endometrioid cancers) with available molecular classification from a tertiary centre. MRI was prospectively performed a month prior to surgery; images were blindly interpreted by two experienced radiologists with consensus reading. The ADC value was measured by an experienced radiologist on the commercially available processing workstation. Interoperator measurement consistency was calculated. RESULTS: Our sample comprised 17 PLOE, 32 MSI-H, 31 NSMP, and 29 P53abn ECs. Clinical information did not differ significantly among the groups. The maximum diameter and volume of the lesions differed among the groups. The ADC value in the maximal area (ADCarea) or region of interest (ROI, ADCroi) in the P53abn group was higher than that in the other groups (894.0 ±12.6 and 817.5 ± 83.3 x10-6 mm2/s). The ADC mean values were significantly different between the P53abn group and the other groups (P = 0.000). The nomogram showed the highest discriminative ability to distinguish P53abn EC from other types (AUC: 0.859). CONCLUSION: Our results have suggested the quantitative MR characteristics (ADC values) derived from preoperative EC MRI to provide useful information in preoperatively determining P53abn cancer.

Determination of p53abn endometrial cancer: a multitask analysis using radiological-clinical nomogram on MRI.

OBJECTIVES: We aimed to differentiate endometrial cancer (EC) between TP53mutation (P53abn) and Non-P53abn subtypes using radiological-clinical nomogram on EC body volume MRI. METHODS: We retrospectively recruited 227 patients with pathologically proven EC from our institution. All these patients have undergone molecular pathology diagnosis based on the Cancer Genome Atlas. Clinical characteristics and histological diagnosis were recorded from the hospital information system. Radiomics features were extracted from online Pyradiomics processors. The diagnostic performance across different acquisition protocols was calculated and compared. The radiological-clinical nomogram was established to determine the nonendometrioid, high-risk, and P53abn EC group. RESULTS: The best MRI sequence for differentiation P53abn from the non-P53abn group was contrast-enhanced T1WI (test AUC: 0.8). The best MRI sequence both for differentiation endometrioid cancer from nonendometrioid cancer and high-risk from low- and intermediate-risk groups was apparent diffusion coefficient map (test AUC: 0.665 and 0.690). For all 3 tasks, the combined model incorporating all the best discriminative features from each sequence yielded the best performance. The combined model achieved an AUC of 0.845 in the testing cohorts for P53abn cancer identification. The MR-based radiomics diagnostic model performed better than the clinical-based model in determining P53abn EC (AUC: 0.834 vs 0.682). CONCLUSION: In the present study, the diagnostic model based on the combination of both radiomics and clinical features yielded a higher performance in differentiating nonendometrioid and P53abn cancer from other EC molecular subgroups, which might help design a tailed treatment, especially for patients with high-risk EC. ADVANCES IN KNOWLEDGE: (1) The contrast-enhanced T1WI was the best MRI sequence for differentiation P53abn from the non-P53abn group (test AUC: 0.8). (2) The radiomics-based diagnostic model performed better than the clinical-based model in determining P53abn EC (AUC: 0.834 vs 0.682). (3) The proposed model derived from multi-parametric MRI images achieved a higher accuracy in P53abn EC identification (AUC: 0.845).

Histogram Feature Analysis of Tumor Body on Diffusion-weighted MR Imaging in Differentiation between Granulosa Cell Tumors and Other Sex-cord Tumors in Ovary: Comparison with Histological Results.

OBJECTIVE: We aimed to differentiate granulosa cell tumors (GCT) from other ovarian sex-cord tumors (OSCs) based on feature analysis of the tumor body on MR imaging. METHODS: We retrospectively enrolled 27 patients with pathologically proven sex-cord tumours (14 GSTs, 8 fibromas, 4 fibrothecomas, and 1 sclerosing stromal tumour) from our institution. All MRI examinations were performed at least one month prior to surgery. MR image features were recorded by two radiologists with consensus readings. Histogram analysis was performed using FeAture Explorer software. The differences in histogram parameters between GCT (38.1 ± 14.6 years) and OSC (43.7 ± 18.0 years) groups were compared. Fourteen randomly selected cellular-type myomas who also underwent MRI in our hospital were considered as the control group. The intra-operator consistency of ADC value was evaluated across measurements twice. RESULTS: The repeatability of conventional ADC measurements on the tumor body was good. The values of ADC-mean, ADC-min, and ADC-max significantly differed across three groups (p < 0.001). The histogram variance on DWI, histogram percentage on T2WI, and ADC min showed the best discriminative performance in determining GCTs from other OSCs with an area under the receiver operator curve (AUC) of 0.997, 0.882, and 0.795, respectively. The histogram variance on DWI yielded a sensitivity of 92.3%, a specificity of 100%, and an accuracy of 96.6% in discriminating GSTs from other OSCs. CONCLUSION: In the present study, feature analysis of tumor body MR imaging has helped to differentiate GST from OSC with better performance than conventional ADC measurements.

Dynamic contrast-enhanced magnetic resonance imaging in epithelial ovarian tumor categorization: comparison with apparent diffusion coefficient histogram analysis and the tumor cell proliferation marker.

OBJECTIVE: To compare the capability of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and apparent diffusion coefficient (ADC) histogram analysis in epithelial ovarian tumor categorization. METHODS: We retrospectively recruited 52 patients with pathologically proven ovarian serous epithelial cancer from our institution. ADC histogram analysis was performed using FeAture Explorer software after outlining the whole lesion area on the ADC map. The ADC histogram parameter difference between subgroups was compared; the correlation between the quantitative parameters on MRI and Ki-67 expression was calculated for both groups. RESULTS: The repeatability of ADC measurements across the two methods was good; the area method (ADCarea) had better performance in repeatability than the ROI method (ADCroi). The ADCroi, ADCarea, Ktrans, and Kep values significantly differed between the groups (P < 0.05). The histogram parameters (percent10, entropy, minimum, range and variance) and DCE parameter (Ktrans) were strongly correlated with Ki-67 expression (P = 0.000), while the conventional ADC measurements were not significantly correlated with Ki-67 expression (P > 0.05). Overall, Ktrans had the best diagnostic performance for discriminating type I with type II ovarian cancers (AUC = 0.826). CONCLUSION: In the present study, both diffusion-weighted imaging (DWI) and DCE MRI could help classify ovarian cancer patients with high accuracy. ADC histogram analysis could accurately reflect the proliferative capability of tumor cells to some extent.

Deep learning for the ovarian lesion localization and discrimination between borderline and malignant ovarian tumors based on routine MR imaging.

To establish a deep learning (DL) model in differentiating borderline ovarian tumor (BOT) from epithelial ovarian cancer (EOC) on conventional MR imaging. We retrospectively enrolled 201 patients of 102 pathologically proven BOTs and 99 EOCs at OB/GYN hospital Fudan University, between January 2015 and December 2017. All imaging data were reviewed on picture archiving and communication systems (PACS) server. Both T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI) MR images were used for lesion area determination. We trained a U-net++ model with deep supervision to segment the lesion area on MR images. Then, the segmented regions were fed into a classification model based on DL network to categorize ovarian masses automatically. For ovarian lesion segmentation, the mean dice similarity coefficient (DSC) of the trained U-net++ model in the testing dataset achieved 0.73 [Formula: see text] 0.25, 0.76 [Formula: see text] 0.18, and 0.60 [Formula: see text] 0.24 in the sagittal T2WI, coronal T2WI, and axial T1WI images, respectively. The DL model by combined T2WI computerized network could differentiate BOT from EOC with a significantly higher AUC of 0.87, an accuracy of 83.7%, a sensitivity of 75.0% and a specificity of 87.5%. In comparison, the AUC yielded by radiologist was only 0.75, with an accuracy of 75.5%, a sensitivity of 96.0% and specificity of 54.2% (P < 0.001).The trained DL network model derived from routine MR imaging could help to distinguish BOT from EOC with a high accuracy, which was superior to radiologists' assessment.

Histogram Analysis of Apparent Diffusion Coefficient on Diffusion Weighted Magnetic Resonance Imaging in Differentiation between Low and High Grade Serous Ovarian Cancer.

BACKGROUND: Ovarian cancer is a leading cause of death in gynecological malignancies. Being the most common subtype in OEC, ovarian serous cancer also includes two subtypes: low grade serous ovarian cancer (LGSC) and high grade serous ovarian cancer (HGSC) (1). PURPOSE: The study aims to assess the capability of apparent diffusion coefficient (ADC) histogram analysis and conventional measurements on magnetic resonance imaging (MRI) in differentiating between LGSC and HGSC. METHODS: We retrospectively recruited 38 patients with pathologically proven ovarian serous epithelial cancer. The mean ADC value was measured by one technician using two methods on post-processed workstation. The ADC value and histogram parameter difference between LGSC and HGSC groups were compared. The correlation between the ADC value and the Ki-67 expression was calculated across both groups. RESULTS: The repeatability of ADC measurements across two methods was good; the ROI method (ADC-roi) had better performance repeatability than the area method (ADC-area). The value of ADC-mean , ADC-min, ADC-max, and ADC-area significantly differed between both groups (p < 0.001). The value of ADC-area correlated inversely with ki-67 expression in the whole group (Pearson coefficient = -0.382, p = 0.02). The 3D computerized-diagnostic model had the best discriminative performance in determining HGSC than 2D and conventional ADC measurements. The 3D model yielded a sensitivity of 100%, a specificity of 95.45%, and an accuracy of 97.73%. CONCLUSION: In the present study, the 3D ADC histogram model help differentiate HGSC from LGSC with a better performance than conventional ADC measurements.

Two-dimensional and three-dimensional T2 weighted imaging-based radiomic signatures for the preoperative discrimination of ovarian borderline tumors and malignant tumors.

BACKGROUND: Ovarian cancer is the most women malignancy in the whole world. It is difficult to differentiate ovarian cancers from ovarian borderline tumors because of some similar imaging findings.Radiomics study may help clinicians to make a proper diagnosis before invasive surgery. PURPOSE: To evaluate the ability of T2-weighted imaging (T2WI)-based radiomics to discriminate ovarian borderline tumors (BOTs) from malignancies based on two-dimensional (2D) and three-dimensional (3D) lesion segmentation methods. METHODS: A total of 95 patients with pathologically proven ovarian BOTs and 101 patients with malignancies were retrospectively included in this study. We evaluated the diagnostic performance of the signatures derived from T2WI-based radiomics in their ability to differentiate between BOTs and malignancies and compared the performance differences in the 2D and 3D segmentation models. The least absolute shrinkage and selection operator method (Lasso) was used for radiomics feature selection and machine learning processing. RESULTS: The radiomics score between BOTs and malignancies in four types of selected T2WI-based radiomics models differed significantly at the statistical level (p < 0.0001). For the classification between BOTs and malignant masses, the 2D and 3D coronal T2WI-based radiomics models yielded accuracy values of 0.79 and 0.83 in the testing group, respectively; the 2D and 3D sagittal fat-suppressed (fs) T2WI-based radiomics models yielded an accuracy of 0.78 and 0.99, respectively. CONCLUSIONS: Our results suggest that T2WI-based radiomic features were highly correlated with ovarian tumor subtype classification. 3D-sagittal MRI radiomics features may help clinicians differentiate ovarian BOTs from malignancies with high ACC.

MR-based radiomics-clinical nomogram in epithelial ovarian tumor prognosis prediction: tumor body texture analysis across various acquisition protocols.

BACKGROUND: Epithelial ovarian cancer (EOC) is the most malignant gynecological tumor in women. This study aimed to construct and compare radiomics-clinical nomograms based on MR images in EOC prognosis prediction. METHODS: A total of 186 patients with pathologically proven EOC were enrolled and randomly divided into a training cohort (n = 130) and a validation cohort (n = 56). Clinical characteristics of each patient were retrieved from the hospital information system. A total of 1116 radiomics features were extracted from tumor body on T2-weighted imaging (T2WI), T1-weighted imaging (T1WI), diffusion weighted imaging (DWI) and contrast-enhanced T1-weighted imaging (CE-T1WI). Paired sequence signatures were constructed, selected and trained to build a prognosis prediction model. Radiomic-clinical nomogram was constructed based on multivariate logistic regression analysis with radiomics score and clinical features. The predictive performance was evaluated by receiver operating characteristic curve (ROC) analysis, decision curve analysis (DCA) and calibration curve. RESULTS: The T2WI radiomic-clinical nomogram achieved a favorable prediction performance in the training and validation cohort with an area under ROC curve (AUC) of 0.866 and 0.818, respectively. The DCA showed that the T2WI radiomic-clinical nomogram was better than other models with a greater clinical net benefit. CONCLUSION: MR-based radiomics analysis showed the high accuracy in prognostic estimation of EOC patients and could help to predict therapeutic outcome before treatment.

Treatment of early brain injury after subarachnoid hemorrhage in the rat model by inhibiting p53-induced ferroptosis.

Post-subarachnoid hemorrhage (SAH) survivors experience severe neurological disability. Previous studies implicate that ferroptosis is involved in SAH. Ferroptosis is an iron-dependent form of regulated cell death caused by the accumulation of lipid peroxidation. However, the role and the mechanism of ferroptosis in SAH are still uncertain and need further study. Thus, we investigated the effect of ferroptosis on early brain injury (EBI) after SAH and further clarified its mechanism. The results showed ferroptosis characteristics appeared in the cerebral cortex of rats with SAH after 24 h. However, ferroptosis could be rescued by Ferrostatin-1 (Fer-1). Treatment with Fer-1 could increase SLc7a11 and GPx4, and alleviated damage-associated molecular pattern molecules and inflammatory cytokines. Similarly, blood-brain barrier impairment, brain edema, behavioral deficits and neuronal damage were reduced by inhibiting ferroptosis. More importantly, the p53 inhibitor pifithrin-α could significantly block cortical SAH-induced ferroptosis. Collectively, these results indicated that ferroptosis aggravated EBI after SAH was partly dependent on p53, and inhibiting ferroptosis might be an effective therapeutic target for EBI.

Diffusion-Weighted Magnetic Resonance Imaging (DWI) Parameters in Benign and Malignant Ovarian Tumors with Solid and Cystic Components.

OBJECTIVE: To determine the values of diffusion-weighted magnetic resonance imaging (DWI) parameters on differential diagnosis of benign and malignant ovarian tumours with solid and cystic components. STUDY DESIGN: An observational study. PLACE AND DURATION OF STUDY: Department of Radiology, Obstetrics and Gynecology Hospital of Fudan University, China, from January to December 2017. METHODOLOGY: Forty-four cases of malignant and benign ovarian tumours were selected as respective groups. Inclusion criteria were ovarian masses found by pelvic and abdominal imaging examination. Exclusion criteria of two groups were endometriosis and pelvic inflammatory diseases found by relevant examination, those with chronic diseases, tumors in other organs found by relevant examination, and those with family cancer history. Conventional MRI plain scans, enhanced scans and DWI scans, were performed after admission. Apparent diffusion coefficient (ADC) and exponential apparent diffusion imaging (eADC) of solid lesions of two groups were recorded and compared. RESULTS: Solid ADC in malignant group was lower than that in benign group (p<0.001). Solid eADC in malignant group was higher than that in benign group (p<0.001). CONCLUSION: Diffusion-weighted magnetic resonance imaging is of high application value in the differential diagnosis of benign and malignant ovarian tumours with solid and cystic components, and it is worthy of promotion and application.

Value of 3.0 T diffusion-weighted imaging in discriminating thecoma and fibrothecoma from other adnexal solid masses.

BACKGROUND: To investigate the value of diffusion-weighted imaging (DWI) at 3.0 T (3T), and especially the apparent diffusion coefficient (ADC), in discriminating ovarian thecoma from other adnexal solid masses. METHODS: Eighteen thecomas or fibrothecomas, 14 ligamentous leiomyomas, and 24 other ovarian solid tumors underwent prospective DWI magnetic resonance imaging (MRI) in addition to routine MRI on a 3T MRI machine. The baseline characteristics, components, and conventional MRI and DWI-MRI signals for the thecomas were recorded. The ADC values (ADCs) were measured for each group and compared. RESULTS: The thecomas often appeared as homogeneous isointensity (17/18) on T1-weighted images (T1WI; 11/18) or T2WI (11/18) on DWI-MRI, with minor (9/18) or mild (6/18) enhancement. The mean ADC value for thecoma (1.20 ± 0.45 × 10-3 mm2/s) was almost equal to that of the other solid ovarian masses (1.26 ± 0.51 × 10-3 mm2/s), but lower than that for leiomyoma (1.48 ± 0.42 × 10-3 mm2/s), although not significantly so. There was a significant difference (p = 0.043) in the ADCs of the benign ovarian solid masses (1.16 ± 0.47 × 10-3 mm2/s) and leiomyomas (1.48 ± 0.42 × 10-3 mm2/s). CONCLUSIONS: There is no significant difference in ADC between thecoma and other adnexal solid masses, but the ADCs of thecomas are lower than those of leiomyomas.

HIV and intestinal parasite co-infections among a Chinese population: an immunological profile.

BACKGROUND: Parasite infections often result in a switch of the human body's predominant immune reaction from T-helper 1 (Th1)-type to Th2-type. Hence, parasite infections are widely expected to accelerate the progression of human immunodeficiency virus (HIV) infections to acquired immunodeficiency syndrome (AIDS). In the People's Republic of China, both parasitic diseases and AIDS are epidemic in certain rural areas, and co-infections are relatively common. However, no population-based studies have yet investigated the frequency of HIV and parasite co-infections, and its effects on immune responses. We studied (1) the immune status of an HIV-infected population, and (2) the effect of co-infection of HIV and intestinal parasites on selected parameters of the human immune system. METHODS: A total of 309 HIV-infected individuals were recruited and compared to an age-matched and sex-matched control group of 315 local HIV-negative individuals. Questionnaires were administered to all participants to obtain information on sociodemographic characteristics, sanitation habits, family income, and recent clinical manifestations. Two consecutive stool samples and 10 ml samples of venous blood were also collected from each individual for the diagnosis of parasite infections and quantitative measurements of selected cytokines and CD4+ T-lymphocytes, respectively. RESULTS: During the study period, 79 HIV-infected individuals were not under highly active antiretroviral therapy (HAART) and were thus included in our analysis; the prevalence of intestinal helminth infections was 6.3% and that of protozoa was 22.8%. The most common protozoan infections were Blastocystis hominis (B. hominis) (13.9%) and Cryptosporidium spp. (10.1%). The prevalence of Cryptosporidium spp. in HIV-infected individuals was significantly higher than that in HIV negative individuals (P < 0.05). Compared to the non-co-infected population, no significant difference was found for any of the measured immunological indicators (P > 0.05). However, the following trends were observed: IFN-γ levels were lower, but the IL-4 level was higher, in the population co-infected with HIV and helminths. In the population co-infected with HIV and B. hominis, the IL-2 level was higher. The population co-infected with HIV and Cryptosporidium spp. had markedly lower CD4+ T-lymphocyte counts. CONCLUSION: According to the immunologic profile, co-infection with helminths is disadvantageous to HIV-infected individuals. It was associated with a shift in the Th1/Th2 balance in the same direction as that caused by the virus itself, which might indicate an acceleration of the progress from an HIV infection to AIDS. Co-infection with Cryptosporidium spp. was not associated with a significant change in immune factors but co-infection with Cryptosporidium spp. was associated with a reduced level of CD4 + T-lymphocytes, confirming the opportunistic nature of such infections. Co-infection with B. hominis, on the other hand, was associated with an antagonistic shift in the immunological profile compared to an HIV infection.

Five-year longitudinal assessment of the downstream impact on schistosomiasis transmission following closure of the Three Gorges Dam.

BACKGROUND: Schistosoma japonicum is a major public health concern in the Peoples' Republic of China (PRC), with about 800,000 people infected and another 50 million living in areas at risk of infection. Based on ecological, environmental, population genetic and molecular factors, schistosomiasis transmission in PRC can be categorised into four discrete ecosystems or transmission modes. It is predicted that, long-term, the Three Gorges Dam (TGD) will impact upon the transmission of schistosomiasis in the PRC, with varying degree across the four transmission modes. METHODOLOGY/PRINCIPAL FINDINGS: We undertook longitudinal surveillance from 2002 to 2006 in sentinel villages of the three transmission modes below the TGD across four provinces (Hunan, Jiangxi, Hubei and Anhui) to determine whether there was any immediate impact of the TGD on schistosomiasis transmission. Eight sentinel villages were selected to represent both province and transmission mode. The primary end point measured was human incidence. Here we present the results of this five-year longitudinal cohort study. Results showed that the incidence of human S. japonicum infection declined considerably within individual villages and overall mode over the course of the study. This is also reflected in the yearly odds ratios (adjusted) for infection risk that showed significant (P<0.01) downward trends in all modes over the follow-up period. CONCLUSIONS/SIGNIFICANCE: The decrease in human S. japonicum incidence observed across all transmission modes in this study can probably be attributed to the annual human and bovine PZQ chemotherapy. If an increase in schistosome transmission had occurred as a result of the TGD, it would be of negligible size compared to the treatment induced decline seen here. It appears therefore that there has been virtually no immediate impact of the TGD on schistosomiasis transmission downstream of the dam.

Co-infection of HIV and intestinal parasites in rural area of China.

BACKGROUND: Intestinal parasite infections (IPIs) are among the most significant causes of illness and disease of socially and economically disadvantaged populations in developing countries, including rural areas of the People's Republic of China. With the spread of the human immunodeficiency virus (HIV) among rural Chinese populations, there is ample scope for co-infections and there have been increasing fears about their effects. However, hardly any relevant epidemiological studies have been carried out in the country. The aim of the present survey was to assess the IPI infection status among a representative sample of HIV-positive Chinese in rural Anhui province, and compare the findings with those from a cohort of non-infected individuals. METHODS: A case control study was carried out in a rural village of Fuyang, Anhui province, China. Stool samples of all participants were examined for the presence of intestinal parasites. Blood examination was performed for the HIV infection detection and anemia test. A questionnaire was administered to all study participants. RESULTS: A total of 302 HIV positive and 303 HIV negative individuals provided one stool sample for examination. The overall IPI prevalence of intestinal helminth infections among HIV positives was 4.3% (13/302) while it was 5.6% (17/303) among HIV negatives, a non-significant difference. The prevalence of protozoa infections among HIV positives was 23.2% while the rate was 25.8% among HIV negatives. The species-specific prevalences among HIV positives were as follows: 3.6% for hookworm, 0.7% for Trichuris trichiura, zero for Ascaris lumbricoides, 0.3% for Clonorchis sinensis, 1.3% for Giardia intestinalis, 16.2% for Blastocystis hominis, 1.7% for Entamoeba spp. and 8.3% for Cryptosporidium spp.. Cryptosporidium spp. infections were significantly more prevalent among HIV positives (8.3%) compared to the HIV negative group (3.0%; P < 0.05). Among people infected with HIV, Cryptosporidium spp. was significantly more prevalent among males (12.6%) than females (4.4%; P < 0.05). According to multivariate logistic regression, the factors significantly associated with parasite infections of the people who were HIV positive included sex (male: OR = 6.70, 95% CI: 2.030, 22.114), younger age (less than 42 years old: OR = 4.148, 95% CI: 1.348, 12.761), and poor personal hygiene habits (OR = 0.324, 95% CI: 0.105, 0.994). CONCLUSIONS: HIV positive individuals are more susceptible to co-infections with Cryptosporidium spp. than HIV negative people, particularly younger males with poor personal hygiene habits, indicating a need for targeted hygiene promotion, IPI surveillance and treatment.

Treatment and reinfection of water buffaloes and cattle infected with Schistosoma japonicum in Yangtze River Valley, Anhui province, China.

The aim of the present study was to evaluate the efficacy of praziquantel treatment of Schistosoma japonicum infections in cattle and water buffaloes and to assess the natural rate of reinfection after treatment. The studies were conducted on 2 islands in the Yangtze River, Anhui province, China, from March 2003 to January 2004. The efficacy of praziquantel was 97% when applied orally wrapped in tree leaves at the recommended doses. The efficacy was measured using a miracidium hatching technique on fecal samples collected 20 days after treatment. The treatment did not give rise to any major side effects. Reinfection after treatment was high and occurred throughout the year in both cattle and water buffaloes. Age-related resistance was only observed in water buffaloes. It is concluded that although praziquantel is highly effective against S. japonicum in cattle and water buffaloes, a single annual treatment strategy does not effectively control transmission. New strategies for integrated control of animal schistosomiasis are needed to control schistosomiasis transmission more effectively in farm areas of China.

Field evaluation of a rapid, visually-read colloidal dye immunofiltration assay for Schistosoma japonicum for screening in areas of low transmission.

OBJECTIVE: To determine the validity of a recently developed rapid test--a colloidal dye immunofiltration assay (CDIFA)--used by health workers in field settings to identify villagers infected with Schistosoma japonicum. METHODS: Health workers in the field used CDIFA to test samples from 1553 villagers in two areas of low endemicity and an area where S. japonicum was not endemic in Anhui, China. All the samples were then tested in the laboratory by laboratory staff using a standard parasitological method (Kato-Katz), an indirect haemagglutination assay (IHA), and CDIFA. The results of CDIFA performed by health workers were compared with those obtained by Kato-Katz and IHA. FINDINGS: Concordance between the results of CDIFA performed in field settings and in the laboratory was high (kappa index, 0.95; 95% confidence interval, 0.93-0.97). When Kato-Katz was used as the reference test, the overall sensitivity and specificity of CDIFA were 98.5% and 83.6%, respectively in the two villages in areas of low endemicity, while the specificity was 99.8% in the nonendemic village. Compared with IHA, the overall specificity and sensitivity of CDIFA were greater than 99% and 96%, respectively. With the combination of Kato-Katz and IHA as the reference standard, CDIFA had a sensitivity of 95.8% and a specificity of 99.5%, and an accuracy of 98.6% in the two areas of low endemicity. CONCLUSION: CDIFA is a specific, sensitive, and reliable test that can be used for rapid screening for schistosomiasis by health workers in field settings.

In vivo and in vitro encystment of Echinochasmus liliputanus cercariae and biological activity of the metacercariae.

In vivo and in vitro encystment of the cercariae of Echinochasmus liliputanus and biological activity of the metacercariae were studied. In vivo encystment of cercariae occurred in the gills of goldfish, the second intermediate host. However, the cercariae also encysted in vitro in Locke solution (0.6x to 1.2x strength), 0.7-1.2% NaCI, artificial gastric juice, and human gastric juice. Locke or NaCI solutions were shown to be appropriate for in vitro encystment to occur within 24 hr; however, full-strength Locke solution was shown to be optimal. The 1-day-old metacercariae formed in vivo and treated in 0.1% sodium deoxycholate excystation medium at 37 C for 1 hr showed 88.5% excystation. The metacercariae formed in vitro, however, showed 88.6% and 85.0% excystation for normal and abnormal ones, respectively. Abnormal cysts at room temperature usually die within 10 days. About 70% of the normal cysts, both in vivo and in vitro, can still excyst after being stored in Locke 0.5x solution at 4 C for 3 mo. Cysts formed in vivo and in vitro were equally infective. The encystment of the cercariae in vitro could be inhibited when the cercariae were treated with 1 micromol silver nitrate. Because silver nitrate binds to the papillae, especially to the ciliated papillae, on the cercaria surface, it is suggested that papillary chemoreceptors may be involved in encystment of the cercariae. The finding of E. liliputanus cercariae encysting in vitro, especially in human gastric juice, might be helpful in elucidating mechanisms of the definitive hosts that are directly infected by the cercariae.

[The current status of schistosomiasis epidemics in China].

OBJECTIVE: To analyze the change of tendency on schistosomiasis epidemics in China in the last 5 years. METHODS: Data on schistosomiasis epidemics in the history and particularly in the last 5 years were collected. Tendency and the re-emerging status after 1998 were analyzed. RESULTS: Data in 2003 showed that in 42%, 40% and 53% of the provinces, counties and townships with epidemics, the transmission of the disease has been interrupted or controlled. The number of estimated patients of schistosomiasis and areas with snails were also reduced by 92.74% and 73.56%, in 2003. The annual estimated number of chronic cases was around 800 000 and 31 321.5 hectare of snail infested areas were newly identified in recent 5 years. Among 20 national villages under longitudinal surveillance, 30%, 70% and 35% of the villages were presented a tendency of increase in the rates of human infection, bovine infection and Oncomelania snails infection, respectively. A total of 38 counties from 7 provinces have re-emerged in schistosomiasis transmission after those counties having reached criteria of transmission under control or interrupted. In 6 non-endemic counties, snails were presented, and 16 marshlands in Xan river were found with appearance of acute cases of schistosomiasis. More snail infested areas were found in Shanghai, Zhejiang, and Fujian. Both snail infested areas and newly infected cases were occurred in urban areas along the Yangtze River. CONCLUSION: The tendency of increase was presented in focal areas along the Yangtze River, due to changes of environmental, ecological, societal and economic status, as well as on the forces of control.

[Establishment of minimum medical geographic information systems database in China].

OBJECTIVE: To establish a minimum medical geographic information systems (GIS) database as a spatial decision supporting system (SDSS), and to use the database into public health practice in China. METHODS: Spatial data collected from different sources were standardized as decimal degree format, including: (1) satellite images covering areas of China; (2) digital maps of China in vector files; (3) diseases database and relevant models. RESULTS: Necessary satellite images for the database have been collected from NOAA AVHRR, Landsat TM, etc., including the normalized difference vegetation index (NDVI) images from AVHRR, earth surface temperature images from AVHRR, GTOPO30 DEM images from USGS and landuse images from USGS. The digital vector files for GIS analysis were collected including political (county, provinces, country) boundaries file, environmental (drainage, land cover, soil type) vector file, population data and climate data; Data on diseases mainly generated from survey or case reporting. Relevant models on transmission of Schistosoma japonicum and Plasmodium vivax, and models of Oncomelania hupensis and Anophores sinansis were developed, and the relevant environmental factors related to incidence of cancers were mapped, to test and verify those database. CONCLUSION: The database unified the data from different sources for users. Minimum medical data included in the database could be used in the practice of public health. It is expected that this database be used in a wider range.