Chemical shift magnetic resonance imaging for distinguishing minimal-fat renal angiomyolipoma from renal cell carcinoma: a meta-analysis.

OBJECTIVES: To determine the performance of chemical shift signal intensity index (CS-SII) values for distinguishing minimal-fat renal angiomyolipoma (mfAML) from renal cell carcinoma (RCC) and to assess RCC subtype characterisation. METHODS: We identified eligible studies on CS magnetic resonance imaging (CS-MRI) of focal renal lesions via PubMed, Embase, and the Cochrane Library. CS-SII values were extracted by lesion type and evaluated using linear mixed model-based meta-regression. RCC subtypes were analysed. Two-sided p value <0.05 indicated statistical significance. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. RESULTS: Eleven articles involving 850 patients were included. Minimal-fat AML had significantly higher CS-SII value than RCC (p < 0.05); there were no significant differences between mfAML and clear cell RCC (cc-RCC) (p = 0.112). Clear cell RCC had a significantly higher CS-SII value than papillary RCC (p-RCC) (p < 0.001) and chromophobe RCC (ch-RCC) (p = 0.045). The methodological quality was relatively high, and Begg's test data points indicated no obvious publication bias. CONCLUSIONS: The CS-SII value for differentiating mfAML from cc-RCC remains unproven, but is a promising method for differentiating cc-RCC from p-RCC and ch-RCC. KEY POINTS: • RCC CS-SII values are significantly lower than those of mfAML overall. • CS-SII values cannot aid differentiation between mfAML and cc-RCC. • CS-SII values might help characterise RCC subtypes.

Atypical choroid plexus papilloma: clinicopathological and neuroradiological features.

Background Atypical choroid plexus papilloma (APP) is a rare, newly introduced entity with intermediate characteristics. To date, few reports have revealed the magnetic resonance (MR) findings. Purpose To analyze the clinicopathological and MR features of APP. Material and Methods The clinicopathological data and preoperative MR images of six patients with pathologically proven APP were retrospectively reviewed. The MR features including tumor location, contour, signal intensity, degree of enhancement, intratumoral cysts, and necrosis; and flow voids, borders, peritumoral edema, and associated hydrocephalus were analyzed. Results The APP were located in the ventricle (n = 4) and cerebellopontine angle (CPA, n = 2). Tumor dissemination along the spinal subarachnoid space was found in one patient. The tumors appeared as milt-lobulated (n = 5) or round mass (n = 1), with slightly heterogeneous signals (n = 5) or mixed signals (n = 1) on T1-weighted and T2-weighted images. Heterogeneous and strong enhancement were found in five cases on contrast-enhanced images. Three of four intraventricular tumors had a partly blurred border with ventricle wall. Four tumors had mild to moderate extent of surrounding edema signals. A slight hydrocephalus was seen in four patients. Incomplete capsule was seen in four tumors at surgery. Histopathologically, mild nuclear atypia was seen in all tumors with a mitotic rate of 2-5 per 10 high-power fields. Conclusion APP should be included in the differential diagnosis when an intraventricular or CPA tumor appearing as a multi-lobulated solid mass with slight heterogeneity, heterogeneous strong enhancement, partly blurred borders, mild to moderate peritumoral edema, or slight hydrocephalus are present.

MR lymphangiography at 3.0 Tesla to assess the function of inguinal lymph node in low extremity lymphedema.

PURPOSE: To assess the function of inguinal lymph node (ILN) in low extremity lymphedema (LEL) with dynamic enhanced MR lymphangiography (MRL). MATERIALS AND METHODS: Sixty-four patients with clinically diagnosed LEL underwent MRL examinations. The lymph drainage patterns were separated into four subtypes. The peak time to enhancement and the contrast ratio of the ILN were calculated 35 min following contrast agent administration. RESULTS: Dilated lymphatic vessels could be observed in all subjects. Type I-IV drainage patterns were observed 25% (16/64), 45.31% (29/64), 17.19% (11/64), and 12.5% (8/64), respectively. The ILN in the edematous limbs could be observed in 93.75% (60/64) of subjects. The peak time to enhancement was correlated with clinical stages (P < 0.001) of the disease, lymph drainage patterns (P < 0.001), and the duration of lymphedema (P < 0.001). The contrast ratios were significantly different at each time point (P < 0.001) and significantly correlated with the lymphatic drainage patterns (P < 0.001). CONCLUSION: MRL could provide useful information for evaluating the functional status of the ILN. Data presented here demonstrate that the functionality of the ILN is related to the clinical stage of the disease, lymphatic drainage patterns, and the duration of lymphedema.

Comparison between solid pseudopapillary neoplasms of the pancreas and pancreatic ductal adenocarcinoma with cystic changes using computed tomography.

BACKGROUND: Solid pseudopapillary neoplasms of the pancreas (SPN) share similar imaging findings with pancreatic ductal adenocarcinoma with cystic changes (PDAC with cystic changes), which may result in unnecessary surgery. AIM: To investigate the value of computed tomography (CT) in differentiation of SPN from PDAC with cystic changes. METHODS: This study retrospectively analyzed the clinical and imaging findings of 32 patients diagnosed with SPN and 14 patients diagnosed with PDAC exhibiting cystic changes, confirmed through pathological diagnosis. Quantitative and qualitative analysis was performed, including assessment of age, sex, tumor size, shape, margin, density, enhancement pattern, CT values of tumors, CT contrast enhancement ratios, "floating cloud sign," calcification, main pancreatic duct dilatation, pancreatic atrophy, and peripancreatic invasion or distal metastasis. Multivariate logistic regression analysis was used to identify relevant features to differentiate between SPN and PDAC with cystic changes, and receiver operating characteristic curves were obtained to evaluate the diagnostic performance of each variable and their combination. RESULTS: When compared to PDAC with cystic changes, SPN had a lower age (32 years vs 64 years, P < 0.05) and a slightly larger size (5.41 cm vs 3.90 cm, P < 0.05). SPN had a higher frequency of "floating cloud sign" and peripancreatic invasion or distal metastasis than PDAC with cystic changes (both P < 0.05). No significant difference was found with respect to sex, tumor location, shape, margin, density, main pancreatic duct dilatation, calcification, pancreatic atrophy, enhancement pattern, CT values of tumors, or CT contrast enhancement ratios between the two groups (all P > 0.05). The area under the receiver operating characteristic curve of the combination was 0.833 (95% confidence interval: 0.708-0.957) with 78.6% sensitivity, 81.3% specificity, and 80.4% accuracy in differentiation of SPN from PDAC with cystic changes. CONCLUSION: A larger tumor size, "floating cloud sign," and peripancreatic invasion or distal metastasis are useful CT imaging features that are more common in SPN and may help discriminate SPN from PDAC with cystic changes.

Computed tomography-based radiomics diagnostic approach for differential diagnosis between early- and late-stage pancreatic ductal adenocarcinoma.

BACKGROUND: One of the primary reasons for the dismal survival rates in pancreatic ductal adenocarcinoma (PDAC) is that most patients are usually diagnosed at late stages. There is an urgent unmet clinical need to identify and develop diagnostic methods that could precisely detect PDAC at its earliest stages. AIM: To evaluate the potential value of radiomics analysis in the differentiation of early-stage PDAC from late-stage PDAC. METHODS: A total of 71 patients with pathologically proved PDAC based on surgical resection who underwent contrast-enhanced computed tomography (CT) within 30 d prior to surgery were included in the study. Tumor staging was performed in accordance with the 8th edition of the American Joint Committee on Cancer staging system. Radiomics features were extracted from the region of interest (ROI) for each patient using Analysis Kit software. The most important and predictive radiomics features were selected using Mann-Whitney U test, univariate logistic regression analysis, and minimum redundancy maximum relevance (MRMR) method. Random forest (RF) method was used to construct the radiomics model, and 10-times leave group out cross-validation (LGOCV) method was used to validate the robustness and reproducibility of the model. RESULTS: A total of 792 radiomics features (396 from late arterial phase and 396 from portal venous phase) were extracted from the ROI for each patient using Analysis Kit software. Nine most important and predictive features were selected using Mann-Whitney U test, univariate logistic regression analysis, and MRMR method. RF method was used to construct the radiomics model with the nine most predictive radiomics features, which showed a high discriminative ability with 97.7% accuracy, 97.6% sensitivity, 97.8% specificity, 98.4% positive predictive value, and 96.8% negative predictive value. The radiomics model was proved to be robust and reproducible using 10-times LGOCV method with an average area under the curve of 0.75 by the average performance of the 10 newly built models. CONCLUSION: The radiomics model based on CT could serve as a promising non-invasive method in differential diagnosis between early and late stage PDAC.

Prevalence and risk factors of depression among patients with perianal fistulizing Crohn's disease.

BACKGROUND: Psychological distress, especially depression, associated with perianal fistulizing Crohn's disease (PFCD) is widespread and refractory. However, there is a surprising paucity of studies to date that have sought to identify the prevalence and risk factors of depression associated with PFCD. AIM: To estimate the prevalence of depressive symptoms and investigate the depression-related risk factors in patients with PFCD. METHODS: The study was conducted in the form of survey and clinical data collection via questionnaire and specialized medical staff. Depressive symptoms, life quality, and fatigue severity of patients with PFCD were assessed by Patient Health Questionnaire-9, Inflammatory Bowel Disease Patient Quality of Life Questionnaire (IBDQ), and Inflammatory Bowel Disease (IBD) Fatigue Patient Self-assessment Scale. The basic demographic information, overall disease features, perianal clinical information, and laboratory inflammation indicators were also gathered. Multivariate regression analysis was ultimately used to ascertain the risk factors of depression associated with PFCD. RESULTS: A total of 123 patients with PFCD were involved, and 56.91% were suffering from depression. According to multivariate logistic regression analysis, Perianal Disease Activity Index (PDAI) score [odds ratio (OR) = 0.69, 95% confidence interval (CI): 0.50 to 0.95], IBDQ score (OR = 0.93, 95%CI: 0.88 to 0.97), modified Van Assche index (OR = 1.24, 95%CI: 1.01 to 1.53), and IBD Fatigue score (OR = 1.72, 95%CI: 1.23 to 2.42) were independent risk factors of depression-related prevalence among patients with PFCD (P < 0.05). Multiple linear regression analysis revealed that the increasing perianal modified Van Assche index (ß value = 0.166, 95%CI: 0.02 to 0.31) and decreasing IBDQ score (ß value = -0.116, 95%CI: -0.14 to -0.09) were independently associated with the severity of depression (P < 0.05). CONCLUSION: Depressive symptoms in PFCD patients have significantly high prevalence. PDAI score, modified Van Assche index, quality of life, and fatigue severity were the main independent risk factors.

The multislice CT findings of renal carcinoma associated with XP11.2 translocation/TFE gene fusion and collecting duct carcinoma.

BACKGROUND: Renal cell carcinoma associated with Xp11.2 translocation and TFE gene fusion (Xp11.2/TFE RCC), and collecting duct carcinoma (CDC) are uncommon subtypes of renal cell carcinomas. PURPOSE: To investigate the multislice CT (MSCT) characteristics of these two tumor types. MATERIAL AND METHODS: Nine patients with Xp11.2/TFE RCC and 10 patients with CDC were studied retrospectively. MSCT was undertaken to investigate differences in tumor characteristics and enhancement patterns. RESULTS: All patients had single tumors centered in the renal medulla. Two patients with each tumor type had lymph node involvement and there was a single case of hepatic metastasis (Xp11.2/TFE RCC). The mean tumor diameter of Xp11.2/TFE RCC tumors was significantly larger than for CDC tumors. Two patients with Xp11.2/TFE RCC had cystic components as did eight patients with CDC (P < 0.05). Calcifications were present in six patients, each with CDC. Clear tumor boundaries were visible in two patients with CDC and in nine with Xp11.2/TFE RCC (P < 0.05). The density of Xp11.2/TFE RCC tumors was greater than that of CDC tumors, normal renal cortex, or medulla on unenhanced CT. Enhancement was higher with Xp11.2/TFE RCC than with CDC tumors during all phases. Xp11.2/TFE RCC enhancement was higher than in the renal medulla during cortical and medullary phase but lower than in normal renal medulla during the delayed phase. CDC tumor enhancement was lower than that for normal renal medulla during all enhanced phases. CONCLUSION: Both tumor types originated from the renal medulla. Distinguishing features included density on unenhanced CT, enhancement patterns, and capsule signs. Identifying these differences may aid diagnosis.

[Application of apparent diffusion coefficient ratio in the diagnosis of bladder cancer grading pre-operation].

OBJECTIVE: To explore the value of apparent diffusion coefficient (ADC) ratio in the diagnosis of bladder cancer pre-operation by analyzing its differences among different grades of bladder cancer. METHODS: A total of 52 cases of bladder cancer were all definitely diagnosed with histological results.Routine examinations of magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) were performed preoperatively on each patient. ADC map was constructed in work station and ADC values of tumor and internal obturator muscle were measured (b = 800 s/mm(2)).Ratio of ADC was calculated with internal obturator muscle as reference site. Then the relationship between ADC ratio and bladder cancer grade was analyzed. RESULTS: Mean ratio of ADC of all tumors was 0.98±0.35, G1 (1.12±0.21) and G2 (0.67±0.29), the sensitivity and specificity of ADC ratio was 90.2% and 85.3% respectively with an optimal threshold of 0.96. The ratios of ADC of low-grade group were significantly higher than those of high-grade group while the values of non-muscle-invasive group were significantly higher than those of muscle-invasive group. The ratios of ADC of tumor were inversely associated with the malignancy degree of bladder cancer (r = -0.845, P < 0.05). CONCLUSION: The ratio of ADC of bladder cancer reflects the lesion tissue properties. And its measurement plays an important role in the diagnosis of bladder cancer grading pre-operation.

Diagnostic accuracy of apparent diffusion coefficient to differentiate intrapancreatic accessory spleen from pancreatic neuroendocrine tumors.

BACKGROUND: Intrapancreatic accessory spleen (IPAS) shares similar imaging findings with hypervascular pancreatic neuroendocrine tumors (PNETs), which may lead to unnecessary surgery. AIM: To investigate and compare the diagnostic performance of absolute apparent diffusion coefficient (ADC) and normalized ADC (lesion-to-spleen ADC ratios) in the differential diagnosis of IPAS from PNETs. METHODS: A retrospective study consisting of 29 patients (16 PNET patients vs 13 IPAS patients) who underwent preoperative contrast-enhanced magnetic resonance imaging together with diffusion-weighted imaging/ADC maps between January 2017 and July 2020 was performed. Two independent reviewers measured ADC on all lesions and spleens, and normalized ADC was calculated for further analysis. The receiver operating characteristics analysis was carried out for evaluating the diagnostic performance of both absolute ADC and normalized ADC values in the differential diagnosis between IPAS and PNETs by clarifying sensitivity, specificity, and accuracy. Inter-reader reliability for the two methods was evaluated. RESULTS: IPAS had a significantly lower absolute ADC (0.931 ± 0.773 × 10-3 mm2/s vs 1.254 ± 0.219 × 10-3 mm2/s) and normalized ADC value (1.154 ± 0.167 vs 1.591 ± 0.364) compared to PNET. A cutoff value of 1.046 × 10-3 mm2/s for absolute ADC was associated with 81.25% sensitivity, 100% specificity, and 89.66% accuracy with an area under the curve of 0.94 (95% confidence interval: 0.8536-1.000) for the differential diagnosis of IPAS from PNET. Similarly, a cutoff value of 1.342 for normalized ADC was associated with 81.25% sensitivity, 92.31% specificity, and 86.21% accuracy with an area under the curve of 0.91 (95% confidence interval: 0.8080-1.000) for the differential diagnosis of IPAS from PNET. Both methods showed excellent inter-reader reliability with intraclass correlation coefficients for absolute ADC and ADC ratio being 0.968 and 0.976, respectively. CONCLUSION: Both absolute ADC and normalized ADC values can facilitate the differentiation between IPAS and PNET.

Untargeted metabolomics characterization of the resectable pancreatic ductal adenocarcinoma.

Background: Diagnosis of pancreatic ductal adenocarcinoma (PDAC) is difficult due to the lack of specific symptoms and screening methods. Only less than 10% of PDAC patients are candidates for surgery at the time of diagnosis. Thus, there is a great global unmet need for valuable biomarkers that could improve the opportunity to detect PDAC at the resectable stage. This study aimed to develop a potential biomarker model for the detection of resectable PDAC by tissue and serum metabolomics. Methods: Ultra-high-performance liquid chromatography and quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS/MS) was performed for metabolome quantification in 98 serum samples (49 PDAC patients and 49 healthy controls (HCs)) and 20 pairs of matched pancreatic cancer tissues (PCTs) and adjacent noncancerous tissues (ANTs) from PDAC patients. Univariate and multivariate analyses were used to profile the differential metabolites between PDAC and HC. Results: A total of 12 differential metabolites were present in both serum and tissue samples of PDAC. Among them, a total of eight differential metabolites showed the same expressional levels, including four upregulated and four downregulated metabolites. Finally, a panel of three metabolites including 16-hydroxypalmitic acid, phenylalanine, and norleucine was constructed by logistic regression analysis. Notably, the panel was capable of distinguishing resectable PDAC from HC with an AUC value of 0.942. Additionally, a multimarker model based on the 3-metabolites-based panel and CA19-9 showed a better performance than the metabolites panel or CA19-9 alone (AUC: 0.968 vs. 0.942, 0.850). Conclusions: Taken together, the resectable early-stage PDAC has unique metabolic features in serum and tissue samples. The defined panel of three metabolites has the potential value for early screening of PDAC at the resectable stage.

XPA A23G polymorphism and susceptibility to cancer: a meta-analysis.

Xeroderma pigmentosum group A (XPA) participates in modulating recognition of DNA damage during the DNA nucleotide excision repair process. The XPA A23G polymorphism has been investigated in case-control studies to evaluate the cancer risk attributed to the variant, but the results were conflicting. To clarify the effect of XPA A23G polymorphism in cancer risk, we conducted a meta-analysis that included 30 published case-control studies. Overall, no significant association of XPA A23G variant with cancer susceptibility was observed for any genetic model. However, significant association was observed for colorectal cancer (GG vs. AA: OR = 1.68, 95% CI = 1.15-2.44; dominant genetic model GG + AG vs. AA: OR = 1.54, 95% CI = 1.08-1.17), for breast cancer an increased but non-significant risk was found (GG vs. AA: OR = 1.27, 95% CI = 0.98-1.66; dominant genetic model GG + AG vs. AA: OR = 1.27, 95% CI = 0.99-1.63), and for head and neck cancer an increased risk was observed in recessive model (OR = 1.19, 95% CI = 1.02-1.38), whereas for lung cancer a significant reduced risk was observed (GG vs. AA: OR = 0.77, 95% CI = 0.66­0.90; dominant genetic model GG + AG vs. AA: OR = 0.76, 95% CI = 0.66-0.87), it's noting that in Asian population the inverse association was more apparent. In addition, in Asian population for esophageal cancer a significant decreased risk was also found in dominant genetic model (OR = 0.55; 95% CI = 0.43-0.70) and for head and neck cancer an increased risk was observed in dominant genetic model (OR = 1.51, 95% CI = 1.03-2.23). The meta-analysis suggested that the XPA A23G G allele is a low-penetrant risk factor for cancer development.

[Multi-slice computed tomography diagnosis of collecting duct carcinoma].

OBJECTIVE: To explore the diagnostic features of collecting duct carcinoma (CDC). METHODS: A total of 7 CDC patients were retrospectively examined by multi-slice computed tomography (MSCT). The relevant diagnostic parameters were assessed. RESULTS: All lesions were located in renal medulla. Among them, infiltrations extended to renal calyx (n = 3) and cortex (n = 5). There were indistinct boundaries (capsule sign) on enhanced phase (n = 6) and pre-capsule (n = 1). On non-enhanced CT, CDC attenuation was greater than normal renal cortex or medulla (43.8 ± 5.3 vs 37.6 ± 5.1 or 32.6 ± 4.1, P < 0.05). The degree of enhancement was less than normal renal cortex and medulla during all enhanced phases (P < 0.05 or 0.01). Excellent consistency existed between CT appearances of CDC and pathological characteristics. CONCLUSION: Dynamic contrast enhanced-CT can show distinct imaging features of CDC correlated with pathological characteristics so as to allow a better differential diagnosis.

Application of Unenhanced Computed Tomography Texture Analysis to Differentiate Pancreatic Adenosquamous Carcinoma from Pancreatic Ductal Adenocarcinoma.

OBJECTIVE: The objective of this study was to investigate the application of unenhanced computed tomography (CT) texture analysis in differentiating pancreatic adenosquamous carcinoma (PASC) from pancreatic ductal adenocarcinoma (PDAC). METHODS: Preoperative CT images of 112 patients (31 with PASC, 81 with PDAC) were retrospectively reviewed. A total of 396 texture parameters were extracted from AnalysisKit software for further texture analysis. Texture features were selected for the differentiation of PASC and PDAC by the Mann-Whitney U test, univariate logistic regression analysis, and the minimum redundancy maximum relevance algorithm. Furthermore, receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of the texture feature-based model by the random forest (RF) method. Finally, the robustness and reproducibility of the predictive model were assessed by the 10-times leave-group-out cross-validation (LGOCV) method. RESULTS: In the present study, 10 texture features to differentiate PASC from PDAC were eventually retained for RF model construction after feature selection. The predictive model had a good classification performance in differentiating PASC from PDAC, with the following characteristics: sensitivity, 95.7%; specificity, 92.5%; accuracy, 94.3%; positive predictive value (PPV), 94.3%; negative predictive value (NPV), 94.3%; and area under the ROC curve (AUC), 0.98. Moreover, the predictive model was proved to be robust and reproducible using the 10-times LGOCV algorithm (sensitivity, 90.0%; specificity, 71.3%; accuracy, 76.8%; PPV, 59.0%; NPV, 95.2%; and AUC, 0.80). CONCLUSION: The unenhanced CT texture analysis has great potential for differentiating PASC from PDAC.

[3.0 T magnetic resonance imaging of pancreatic cancer in an orthotopic nude murine model].

OBJECTIVE: To assess the methods of establishing an orthotopic nude murine model of human pancreatic cancer and explore the manifestations of MRI (magnetic resonance imaging) and its pathological fundamentals so as to provide research rationales for human pancreatic cancer. METHODS: The BXPC-3 cell of human pancreatic cancer was orthotopically planted in nude mice. And the animals were examined by a clinical 3.0 T magnetic resonance imager. The MRI examinations were analyzed along with their pathological findings. RESULTS: Among 18 mice, 15 of them grew tumors with a success ratio of 83.3%. The pathological findings conformed to those of high differentiation pancreatic parenchyma cancer. Comparing with the neighbor muscles, the tumors were homogeneous (66.7%, 10/15) or heterogeneous (33.3%, 5/15) of hypointense on T1-weighted images while homogeneous (26.7%, 4/15) or heterogeneous (73.3%, 11/15) hyperintense on T2-weighted images with heterogeneous enhancement. The border became obviously enhanced and there was mild central enhancement while the necrotic part showed no enhancement. CONCLUSION: 3.0T MRI can detect pancreatic neoplasms ≥ 2 mm and visualize clearly their locations, shapes, dimensions and internal structures in an orthotopic nude murine model. Thus it provides a visible framework for further studies of human pancreatic cancer.

Multi-microphone Complex Spectral Mapping for Utterance-wise and Continuous Speech Separation.

We propose multi-microphone complex spectral mapping, a simple way of applying deep learning for time-varying non-linear beamforming, for speaker separation in reverberant conditions. We aim at both speaker separation and dereverberation. Our study first investigates offline utterance-wise speaker separation and then extends to block-online continuous speech separation (CSS). Assuming a fixed array geometry between training and testing, we train deep neural networks (DNN) to predict the real and imaginary (RI) components of target speech at a reference microphone from the RI components of multiple microphones. We then integrate multi-microphone complex spectral mapping with minimum variance distortionless response (MVDR) beamforming and post-filtering to further improve separation, and combine it with frame-level speaker counting for block-online CSS. Although our system is trained on simulated room impulse responses (RIR) based on a fixed number of microphones arranged in a given geometry, it generalizes well to a real array with the same geometry. State-of-the-art separation performance is obtained on the simulated two-talker SMS-WSJ corpus and the real-recorded LibriCSS dataset.

[Radiographic and computed tomographic manifestations of chest in patients with acute chlorine gas poisoning].

OBJECTIVE: To investigate the radiographic and computerized tomographic features of chest in patients with acute chlorine poisoning and its diagnostic value. METHODS: Twenty-eight cases of chlorine poisoning were reviewed. And their radiographic and computerized tomographic features were compared and analyzed. RESULTS: Radiographic findings: among 28 patients, 9 cases were normal and 2 cases had no abnormalities on the first chest X-ray and became abnormal one or two days later. And there were abnormal findings in first chest X-ray in 17 patients:acute tracheal inflammation of peribronchitis (n = 3), acute chemical bronchopneumonia (n = 6) and diffuse interstitial and central pulmonary edema (n = 8). CT manifestations: At Days 1-3, the patients of mild poisoning had scattered patchy dense shadow; those of moderate to severe poisoning showed multiple patchy or diffuse infiltration (ground-glass opacity). And partial consolidation, air bronchogram and pleural effusion could be observed. At Days 4-10, the manifestations of mild poisoning were largely absorbed; those of moderate to severe poisoning manifested the absorption of diffuse or multiple patchy effusion and a fading of shadow. And the size of lung consolidation became smaller than before. At Day 10 after onset, 4 patients completely recovered. At Days 30-40, 6 cases showed traces of fibrous shadow and one case showed small punctiform opacities in both lungs. And at Day 42, there was slight ground-glass change. CONCLUSION: Acute chlorine gas poisoning in varying degrees may manifest acute bronchial pneumonia and acute pulmonary edema. During treatment, a series of chest X-ray examinations will help to follow the changes of disease. And CT examination can offer a more accurate evaluation of lung lesions.

Deep Learning Based Target Cancellation for Speech Dereverberation.

This study investigates deep learning based single- and multi-channel speech dereverberation. For single-channel processing, we extend magnitude-domain masking and mapping based dereverberation to complex-domain mapping, where deep neural networks (DNNs) are trained to predict the real and imaginary (RI) components of the direct-path signal from reverberant (and noisy) ones. For multi-channel processing, we first compute a minimum variance distortionless response (MVDR) beamformer to cancel the direct-path signal, and then feed the RI components of the cancelled signal, which is expected to be a filtered version of non-target signals, as additional features to perform dereverberation. Trained on a large dataset of simulated room impulse responses, our models show excellent speech dereverberation and recognition performance on the test set of the REVERB challenge, consistently better than single- and multi-channel weighted prediction error (WPE) algorithms.

Complex Spectral Mapping for Single- and Multi-Channel Speech Enhancement and Robust ASR.

This study proposes a complex spectral mapping approach for single- and multi-channel speech enhancement, where deep neural networks (DNNs) are used to predict the real and imaginary (RI) components of the direct-path signal from noisy and reverberant ones. The proposed system contains two DNNs. The first one performs single-channel complex spectral mapping. The estimated complex spectra are used to compute a minimum variance distortion-less response (MVDR) beamformer. The RI components of beamforming results, which encode spatial information, are then combined with the RI components of the mixture to train the second DNN for multi-channel complex spectral mapping. With estimated complex spectra, we also propose a novel method of time-varying beamforming. State-of-the-art performance is obtained on the speech enhancement and recognition tasks of the CHiME-4 corpus. More specifically, our system obtains 6.82%, 3.19% and 2.00% word error rates (WER) respectively on the single-, two-, and six-microphone tasks of CHiME-4, significantly surpassing the current best results of 9.15%, 3.91% and 2.24% WER.

Hysterosalpingo-contrast-sonography vs. magnetic resonance-hysterosalpingography for diagnosing fallopian tubal patency: A systematic review and meta-analysis.

PURPOSE: To compare hysterosalpingo-contrast-sonography (HyCoSy) and magnetic resonance-hysterosalpingography (MR-HSG) in the diagnosis of fallopian tubal patency. MATERIALS AND METHODS: The databases of PubMed, Embase, and the Cochrane Library were searched for records up to November 30, 2019. Studies involved in the diagnostic detection of HyCoSy or MR-HSG for fallopian tubal patency using conventional HSG or laparoscopy as the reference test were included. Data was analyzed by meta-analysis. We compared sensitivity, specificity, positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratio (DOR), and summary receiver operating characteristic (sROC) plots of both HyCoSy and MR-HSG. Quality was assessed using the QUADAS-2 tool. RESULTS: The analysis included 24 articles involving 1340 patients. HyCoSy was studied in 17 studies, and MR-HSG was studied in seven studies. For HyCoSy in diagnosis of fallopian tubal patency, pooled sensitivity was 89 % (95 % confidence interval [CI], 87 %-91 %), and specificity was 93 % (95 % CI, 91 %-94 %). For MR-HSG in diagnosis of fallopian tubal patency, pooled sensitivity was 100 % (95 % CI, 98 %-100 %), and specificity was 82 % (95 % CI, 74 %-89 %). The sROC showed similar diagnostic accuracy for MR-HSG and HyCoSy. 3D/4D HyCoSy with ultrasound microbubbles had equal sensitivity (95 % vs. 100 %, P = 0.186) and significantly higher specificity (94 % vs. 82 %, P = 0.005) compared with MR-HSG. CONCLUSIONS: HyCoSy and MR-HSG showed similar overall diagnostic performance for diagnosing fallopian tubal patency. 3D/4D HyCoSy with ultrasound microbubbles could significantly improve the diagnostic specificity of HyCoSy.

Evidence of motor injury due to damaged corticospinal tract following acute hemorrhage in the basal ganglia region.

The integrity of the corticospinal tract (CST) is significantly affected following basal ganglia haemorrhage. We aimed to assess the local features of CST and to effectively predict motor function by diffusion characteristics of CST in patients with motor injury following acute haemorrhage in the acute basal ganglia region. We recruited 37 patients with paresis of the lateral limbs caused by acute basal ganglia haemorrhage. Based on the automated fiber quantification method to track CST, assessed the character of each CST segment between the affected and contralateral sides, and correlated these with the Fugl-Meyer (FM) and Barthel Index (BI) scores at 6 months after onset. The fractional anisotropy (FA) values of the injured side of CST showed a significantly lower FA than the contralateral side along the tract profiles (p < 0.05, corrections for multiple comparisons). The FA values of each site at the internal capsule, closed corona radiata were positively correlated with the FM and BI score at 6 months after onset (p < 0.001, respectively). Our findings assessed the character of CST vividly in detail and dementated the primary sites of CST can predict the long-term outcome of motor function. This study may facilitate future clinical and cognitive studies of acute haemorrhage.