A Combination Analysis of IVIM-DWI Biomarkers and T2WI-Based Texture Features for Tumor Differentiation Grade of Cervical Squamous Cell Carcinoma.

Purpose: To explore the value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and texture analysis on T2-weighted imaging (T2WI) for evaluating pathological differentiation of cervical squamous cell carcinoma. Method: This retrospective study included a total of 138 patients with pathologically confirmed poor/moderate/well-differentiated (71/49/18) who underwent conventional MRI and IVIM-DWI scans. The values of ADC, D, D ∗ , and f and 58 T2WI-based texture features (18 histogram features, 24 gray-level co-occurrence matrix features, and 16 gray-level run length matrix features) were obtained. Multiple comparison, correlation, and regression analyses were used. Results: For IVIM-DWI, the ADC, D, D ∗ , and f were significantly different among the three groups (p < 0.05). ADC, D, and D ∗ were positively correlated with pathological differentiation (r = 0.262, 0.401, 0.401; p < 0.05), while the correlation was negative for f (r = -0.221; p < 0.05). The comparison of 52 parameters of texture analysis on T2WI reached statistically significant levels (p < 0.05). Multivariate logistic regression analysis incorporated significant IVIM-DWI, and texture features on T2WI showed good diagnostic performance both in the four differentiation groups (poorly vs. moderately, area under the curve(AUC) = 0.797; moderately vs. well, AUC = 0.954; poorly vs. moderately and well, AUC = 0.795; and well vs. moderately and poorly, AUC = 0.952). The AUCs of each parameters alone were smaller than that of each regression model (0.503∼0.684, 0.547∼0.805, 0.511∼0.712, and 0.636∼0.792, respectively; pairwise comparison of ROC curves between regression model and individual variables, p < 0.05). Conclusions: IVIM-DWI biomarkers and T2WI-based texture features had potential to evaluate the pathological differentiation of cervical squamous cell carcinoma. The combination of IVIM-DWI with texture analysis improved the predictive performance.

Nomogram of Combining CT-Based Body Composition Analyses and Prognostic Inflammation Score: Prediction of Survival in Advanced Epithelial Ovarian Cancer Patients.

PURPOSE: To investigate the value of body composition changes measured by quantitative computer tomography (QCT) in evaluating the prognosis of advanced epithelial ovarian cancer (AEOC) patients who underwent primary debulking surgery (PDS) and adjuvant platinum-based chemotherapy, and constructed a nomogram model for predicting survival in combination with prognostic inflammation score (PIS). METHOD: Fifty-seven patients with AEOC between 2012 and 2016 were retrospectively enrolled. Pre- and post-treatment CT images were used to analyze the body composition biomarkers. The subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), cross-sectional area of paraspinal skeletal muscle area (PMA), skeletal muscle density (SMD), body mineral density (BMD) were measured from two sets of CT images. RESULTS: In multivariate analyses, VFA gain, PMA loss, BMD loss, and PIS were independent risk factors of overall survival (OS) (HR = 3.7, 3.0, 2.8, 1.9, respectively, all p < 0.05). Receiver operating characteristic (ROC) curves showed that the prognostic model combining body composition changes (BCC) and PIS had the highest predictive performance (area under the curve = 0.890). The concordance index (C-index) of the prognostic nomogram was 0.779 (95% CI, 0.673-0.886). Decision curve analysis (DCA) demonstrated the prognostic nomogram had a great distinguishing performance. CONCLUSION: CT-based body composition analyses and PIS were associated with poor OS for AEOC patients who underwent PDS and adjuvant platinum-based chemotherapy. The prognostic nomogram with a combination of BCC and PIS was dependable in predicting survival for AEOC patients during treatment.

The Value of MRI Findings Combined With Texture Analysis in the Differential Diagnosis of Primary Ovarian Granulosa Cell Tumors and Ovarian Thecoma-Fibrothecoma.

OBJECTIVE: This study aims to explore the value of magnetic resonance imaging (MRI) and texture analysis (TA) in the differential diagnosis of ovarian granulosa cell tumors (OGCTs) and thecoma-fibrothecoma (OTCA-FTCA). METHODS: The preoperative MRI data of 32 patients with OTCA-FTCA and 14 patients with OGCTs, confirmed by pathological examination between June 2013 and August 2020, were retrospectively analyzed. The texture data of three-dimensional MRI scans based on T2-weighted imaging and clinical and conventional MRI features were analyzed and compared between tumor types. The Mann-Whitney U-test, χ 2 test/Fisher exact test, and multivariate logistic regression analysis were used to identify differences between the OTCA-FTCA and OGCTs groups. A regression model was established by using binary logistic regression analysis, and receiver operating characteristic curve analysis was carried out to evaluate diagnostic efficiency. RESULTS: A multivariate analysis of the imaging-based features combined with TA revealed that intratumoral hemorrhage (OR = 0.037), log-sigma-20mm-3D_glszm_SmallAreaEmphasis (OR = 4.40), and log-sigma-2-0mm-3D_glszm_SmallAreaHighGrayLevelEmphasis (OR = 1.034) were independent features for discriminating between OGCTs and OTCA-FTCA (P < 0.05). An imaging-based diagnosis model, TA-based model, and combination model were established. The areas under the curve of the three models in predicting OGCTs and OTCA-FTCA were 0.935, 0.944, and 0.969, respectively; the sensitivities were 93.75, 93.75, and 96.87%, respectively; and the specificities were 85.71, 92.86, and 92.86%, respectively. The DeLong test indicated that the combination model had the highest predictive efficiency (P < 0.05), with no significant difference among the three models in differentiating between OGCTs and OTCA-FTCA (P > 0.05). CONCLUSIONS: Compared with OTCA-FTCA, intratumoral hemorrhage may be characteristic MR imaging features with OGCTs. Texture features can reflect the microheterogeneity of OGCTs and OTCA-FTCA. MRI signs and texture features can help differentiate between OGCTs and OTCA-FTCA and provide a more comprehensive and accurate basis for clinical treatment.

Diagnostic Value of Combined Intravoxel Incoherent Motion Diffusion-Weighted Magnetic Resonance Imaging with Diffusion Tensor Imaging in Predicting Parametrial Infiltration in Cervical Cancer.

Objective: This study sought to determine the diagnostic value of combined intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging (MRI) with diffusion tensor imaging (DTI) in predicting parametrial infiltration (PMI) in patients with cervical cancer. Materials and Methods: We enrolled 65 patients with cervical cancer confirmed by radical hysterectomy (25 PMI-negative and 40 PMI-positive) who underwent IVIM and DTI pretreatment. The parameters of IVIM (ADC, D, D ∗ , and f) and DTI (average diffusion coefficient (DCavg) and fractional anisotropy (FA)) were recorded by two observers. All parameter differences were tested, and the receiver operating characteristic (ROC) curves were generated to estimate the diagnostic performance of significant metrics and their combinations. Results: Compared to the PMI-negative group, the PMI-positive group had significantly lower D (0.632 ± 0.017 vs. 0.773 ± 0.024, p < 0.001) and lower FA (0.073 ± 0.002 vs. 0.085 ± 0.003, p=0.003). The area under the ROC curve (AUC) of D and FA was 0.801 and 0.726, respectively, and the combination of D and FA improved the AUC to 0.931, with a sensitivity and specificity of 80.0% and 97.5%, respectively. Conclusion: D and FA values could be used to help diagnose PMI in patients with cervical cancer. The combination of IVIM and DTI was more valuable than either option alone.

Preoperative Prediction of Cervical Nodal Metastasis in Papillary Thyroid Carcinoma: Value of Quantitative Dual-Energy CT Parameters and Qualitative Morphologic Features.

OBJECTIVE. The purpose of our study was to assess the value of combining quantitative dual-energy CT (DECT) parameters with qualitative morphologic parameters for the preoperative prediction of cervical nodal metastasis from papillary thyroid carcinoma (PTC). MATERIALS AND METHODS. Thirty-five patients with pathologically proven PTC underwent single-phase contrast-enhanced DECT before thyroidectomy and cervical lymphadenectomy. Analyses of quantitative DECT parameters and qualitative morphologic features of metastatic and benign lymph nodes (LNs) were independently performed. The diagnostic performances of using only quantitative parameters, only morphologic features, and their combination for predicting cervical nodal metastasis were statistically calculated with ROC curves and logistic regression models. RESULTS. A total of 206 LNs, 80 metastatic and 126 benign, were included. The best single performer in DECT was the normalized iodine concentration in the venous phase, which had low sensitivity (62.5%) but high specificity (85.7%), for diagnosing metastatic cervical LNs. On the other hand, the best single performer in qualitative morphologic parameters was using the criterion of shortest diameter of greater than 5 mm, which had low specificity (69.8%) but high sensitivity (86.3%). Combining these two parameters improved the AUC, sensitivity, and specificity to 0.846, 86.3%, and 72.2%, respectively. The combination of multiple quantitative DECT parameters and all morphologic data further improved AUC, sensitivity, and specificity to 0.878, 87.5%, and 73.8%, respectively, which was significant compared with the use of any single parameter. CONCLUSION. The combination of quantitative DECT parameters with morphologic data improves performance in the preoperative diagnosis of metastatic cervical LNs in patients with PTC.

Diagnostic Performance of MR Imaging-based Features and Texture Analysis in the Differential Diagnosis of Ovarian Thecomas/Fibrothecomas and Uterine Fibroids in the Adnexal Area.

RATIONALE AND OBJECTIVES: To investigate the value of MRI-based features and texture analysis (TA) in the differential diagnosis between ovarian thecomas/fibrothecomas (OTCA/f-TCAs) and uterine fibroids in the adnexal area (UF-iaas). MATERIALS AND METHODS: This retrospective study included 16 OTCA/f-TCA and 37 UF-iaa patients who underwent conventional MRI and DWI between August 2014 and September 2018. Three-dimensional TA was performed with T2-weighted MRI. The clinical, MRI-based and texture features were compared between OTCA/f-TCAs and UF-iaas. Multivariate logistic regression analysis was used for filtering the independent discriminative features and constructing the discriminating model. ROCs were generated to analyse MRI-based features, texture features and their combination for discriminating between the two diseases. RESULTS: Six imaging-based features (ipsilateral ovary detection, arterial period enhancement, lesion components, peripheral cysts, "whorl signs", mean ADCs) and six texture features (Histogram-energy, Histogram-entropy, Histogram-kurtosis, GLCM-energy, GLCM-entropy, and Haralick correlation) were significantly different between OTCA/f-TCAs and UF-iaas (p < 0.05). Multivariate analysis of the MRI-based features revealed that arterial period enhancement (OR = 0.104), peripheral cysts (OR = 16.513), and whorl signs (OR = 0.029) were independent features for discriminating between OTCA/f-TCAs and UF-iaas (p < 0.05). Multivariate analysis of the texture features showed that Histogram-energy and GLCM-energy were independent features for discriminating between OTCA/f-TCAs and UF-iaas (p < 0.05). The area under the curve of imaging-based diagnosis was 0.85, and the combination of imaging-based diagnosis and TA improved the area under the curve to 0.87, with higher accuracy, specificity and sensitivity of 86%, 92%, and 84%, respectively (p < 0.05). CONCLUSIONS: MRI-based features can be useful in differentiating OTCA/f-TCAs from UF-iaas. Furthermore, combining imaging-based diagnosis and TA can improve diagnostic performance.

The predictive value of quantitative DCE metrics for immediate therapeutic response of high-intensity focused ultrasound ablation (HIFU) of symptomatic uterine fibroids.

PURPOSE: The aim of this study was to investigate the value of quantitative DCE-MRI parameters for predicting the immediate non-perfused volume ratio (NPVR) of HIFU therapy in the treatment of symptomatic uterine fibroids. MATERIALS AND METHODS: A total of 78 symptomatic uterine fibroids in 65 female patients were treated with US-HIFU therapy. All patients underwent conventional MRI and DCE-MRI scans 1 day before and 3 days after HIFU treatment. Permeability parameters K trans, K ep, V e, and V p and T1 perfusion parameters BF and BV of pretreatment were measured as a baseline, while NPVR was used to assess immediate ablation efficiency. Data were assigned to NPVR ≧ 70% and NPVR < 70% groups. Then, the predictive performances of different parameters for ablation efficacy were studied to seek the optimal cut-off value, and the length of time to calculate the variable parameters in each case was recorded. RESULTS: (1) It was observed that the pretreatment K trans, K ep, V e, and BF values of the NPVR ≧ 70% group were significantly lower compared to the NPVR < 70% group (p < 0.05). (2) The immediate NPVR was negatively correlated with the K trans, BF, and BV values before HIFU treatment (r = - 0.561, - 0.712, and - 0.528, respectively, p < 0.05 for all). (3) The AUCs of pretreatment K trans, BF, BV values, and K trans combined with BF used to predict the immediate NPVR were 0.810, 0.909, 0.795, and 0.922, respectively (p < 0.05 for all). (4) The mean time to calculate the variable parameters in each case was 7.5 min. CONCLUSION: Higher K trans, BF, and BV values at baseline DCE-MRI suggested a poor ablation efficacy of HIFU therapy for symptomatic uterine fibroids, while the pretreatment DCE-MRI parameters could be useful biomarkers for predicting the ablation efficacy in select cases. The software used to calculate DCE-MRI parameters was simpler, quicker, and easier to incorporate into clinical practice.

Rapid differential detection of classical and highly pathogenic North American Porcine Reproductive and Respiratory Syndrome virus in China by a duplex real-time RT-PCR.

Since the emergence of highly pathogenic North American Porcine Reproductive and Respiratory Syndrome virus (H-US-PRRSV) in 2006, the classical North American PRRSV (C-US-PRRSV) and H-US-PRRSV isolates have coexisted in Chinese swine herds. A duplex real-time RT-PCR assay using minor groove binder (MGB) probes for differential detection of the two US PRRSV isolates was developed. The specificity, sensitivity, reproducibility, and interference test of this assay were validated. The sensitivity of the assay was 3.2TCID(50)/ml or 38 RNA copies/microl for C-US-PRRSV and 0.4 TCID(50)/ml or 14 RNA copies/microl for H-US-PRRSV. Both assays were 10 times more sensitive than the current methods. A total of 302 clinical samples were tested by duplex real-time RT-PCR and conventional RT-PCR assays, and the results showed over 98.7% agreement. In addition, the new assay can be completed in less than 2h. This duplex real-time RT-PCR assay is a promising tool for rapid differential detection and epidemiology of US PRRSV in China.

Molecular mutations associated with the in vitro passage of virulent porcine reproductive and respiratory syndrome virus.

Mutants of a highly pathogenic, porcine reproductive, and respiratory syndrome virus (PRRSV), JXA1 strain, were prepared by continuous in vitro passage. Genomic sequence comparisons were made between mutants obtained at different passages and the parental strain JXA1. The mutant strain obtained at passage 80 contained a 12 nucleotide insertion and 108 nucleotide mutations that resulted in 45 amino acid changes. Most of these changes (89%) occurred between passage 10 and 45 and were genetically stable for the next 35-70 passages. A comparison of the mutants, their parental strain, and several American PRRSV strains, identified 13 characteristic amino acid changes. These sites, as well as the distinct 12 nucleotide insertion, represent possible genetic markers for the evaluation of live vaccine applications, particularly for additional studies of the safety and potency of live PRRSV vaccines.

[Development and characterization of monoclonal antibodies against H7 hemagglutinin of avian influenza virus].

AIM: To prepare monoclonal antibodies (mAbs) against the hemagglutinin protein of H7 subtype of avian influenza virus (AIV). METHODS: (6-8 weeks old) BALB/c mice of were immunized endermicly with H7 subtype of AIV. The splenocytes from the immunized mice were fused with Sp2/0-Ag-14 myeloma cells after the last immunization. Hybridoma cells were screened by hemagglutination (HA) and hemagglutination inhibition (HI) tests. The reactivity and specificity of mAbs were evaluated by HI test and Western blot assay. RESULTS: Four hybridoma cell lines secreting specific mAbs named 2E2, 2A4, 5F5 and 7G5 were developed. The HI titers of these mAbs were 5 x 2(7)-5 x 2(11), and the immunoglobulin subclass of 2E2 was IgM, that of 2A4 was IgG1, and that of 5F5 and 7G5 was IgG2a. Western blot analysis confirmed that the mAbs only reacted with M(r) 75 000 HA protein of H7 subtype of AIV but did not react with the proteins of Newcastle disease virus (NDV). The results of HI reactivity assay suggested that 2E2, 5F5 and 7G5 only reacted with H7 subtype of AIV but did not react with other subtypes of AIV, NDV and infectious bronchitis virus (IBV). However 2A4 reacted not only with H7 subtype of AIV but also with H15N8 reference strain of AIV at low HI level. CONCLUSION: These mAbs can be used as a useful tool to analyze the HA structure of AIV. They also provide the effective reagents for the rapid detection of H7 subtype of AIV.