The discriminatory diagnostic value of multimodal ultrasound combined with blood cell analysis for granulomatous lobular mastitis and invasive ductal carcinoma of the breast.

OBJECTIVE: To explore the discriminatory diagnostic value of multimodal ultrasound(US) combined with blood cell analysis(BCA) for Granulomatous Lobular Mastitis (GLM) and Invasive Ductal Carcinoma(IDC) of the breast. METHODS: A total of 157 breast disease patients were collected and divided into two groups based on postoperative pathological results: the GLM group(57 cases with 57 lesions) and the IDC group(100 cases with 100 lesions). Differences in multimodal ultrasound features and the presence of BCA were compared between the two groups. The receiver operating characteristic(ROC) curve was used to calculate the optimal cutoff values, sensitivity, specificity, 95% confidence interval(CI), and the area under the curve(AUC) for patient age, lesion size, lesion resistive index(RI), and white blood cell(WBC) count in BCA. Sensitivity, specificity, positive predictive value, negative predictive value, diagnostic accuracy, and AUC were calculated for different diagnostic methods. RESULTS: There were statistically significant differences(P <  0.05) observed between GLM and IDC patients in terms of age, breast pain, the factors in Conventional US(lesion size, RI, nipple delineation, solitary/multiple lesions, margin, liquefaction area, growth direction, microcalcifications, posterior echogenicity and abnormal axillary lymph nodes), the factors in CEUS(contrast agent enhancement intensity, enhancement pattern, enhancement range, and crab-like enhancement) and the factors in BCA(white blood cells, neutrophils, lymphocytes and monocytes). ROC curve analysis results showed that the optimal cutoff values for distinguishing GLM from IDC were 40.5 years for age, 7.15 cm for lesion size, 0.655 for lesion RI, and 10.525*109/L for white blood cells. The diagnostic accuracy of conventional US combined with CEUS(US-CEUS) was the highest(97.45%). The diagnostic performance AUCs for US-CEUS, CEUS, and US were 0.965, 0.921 and 0.832, respectively. CONCLUSION: Multifactorial analysis of multimodal ultrasound features and BCA had high clinical application value in the differential diagnosis of GLM and IDC.

Comparison of the diagnostic performance of three ultrasound thyroid nodule risk stratification systems for follicular thyroid neoplasm: K-TIRADS, ACR -TIRADS and C-TIRADS.

OBJECTIVE: To explore the diagnostic performance of the currently used ultrasound-based thyroid nodule risk stratification systems (K-TIRADS, ACR -TIRADS, and C-TIRADS) in differentiating follicular thyroid adenoma (FTA) from follicular thyroid carcinoma (FTC). METHODS: Clinical data and preoperative ultrasonographic images of 269 follicular thyroid neoplasms were retrospectively analyzed. All of them were detected by Color Doppler ultrasound instruments equipped with high-frequency liner array probes (e.g. Toshiba Apoli500 with L5-14MHZ; Philips IU22 with L5-12MHZ; GE LOGIQ E9 with L9-12MHZ and MyLab Class C with L9-14MHZ). The diagnostic performance of three TIRADS classifications for differentiating FTA from FTC was evaluated by drawing the receiver operating characteristic (ROC) curves and calculating the cut-off values. RESULTS: Of the 269 follicular neoplasms (mean size, 3.67±1.53 cm), 209 were FTAs (mean size, 3.56±1.38 cm) and 60 were FTCs (mean size, 4.07±1.93 cm). There were significant differences in ultrasound features such as margins, calcifications, and vascularity of thyroid nodules between the FTA and FTC groups (P < 0.05). According to the ROC curve comparison analysis, the diagnostic cut-off values of K-TIRADS, ACR-TIRADS, and C-TIRADS for identifying FTA and FTC were K-TR4, ACR-TR4, and C-TR4B, respectively, and the areas under the curves were 0.676, 0.728, and 0.719, respectively. The difference between ACR-TIRADS and K-TIRADS classification was statistically significant (P = 0.0241), whereas the differences between ACR-TIRADS and C-TIRADS classification and between K-TIRADS and C-TIRADS classification were not statistically significant (P > 0.05). CONCLUSION: The three TIRADS classifications were not conducive to distinguishing FTA from FTC. It is necessary to develop a novel malignant risk stratification system specifically for the identification of follicular thyroid neoplasms.

Chlorpromazine confers neuroprotection against brain ischemia by activating BKCa channel.

Chlorpromazine (CPZ) is a well-known antipsychotic drug, still widely being used to treat symptoms of schizophrenia, psychotic depression and organic psychoses. We have previously reported that CPZ activates the BKCa (KCa1.1) channel at whole cell level. In the present study, we demonstrated that CPZ increased the single channel open probability of the BKCa channels without changing its single channel amplitude. As BKCa channel is one of the molecular targets of brain ischemia, we explored a possible new use of this old drug on ischemic brain injury. In middle cerebral artery occlusion (MCAO) focal cerebral ischemia, a single intraperitoneal injection of CPZ at several dosages (5mg/kg, 10mg/kg and 20mg/kg) could exert a significant neuroprotective effect on the brain damage in a dose- and time-dependent manner. Furthermore, blockade of BKCa channels abolished the neuroprotective effect of CPZ on MCAO, suggesting that the effect of CPZ is mediated by activation of the BKCa channel. These results demonstrate that CPZ could reduce focal cerebral ischemic damage through activating BKCa channels and merits exploration as a potential therapeutic agent for treating ischemic stroke.