Accurate diagnosis of severe coronary stenosis based on resting magnetocardiography: a prospective, single-center, cross-sectional analysis.

OBJECTIVE: To evaluate the role of resting magnetocardiography in identifying severe coronary artery stenosis in patients with suspected coronary artery disease. METHODS: A total of 513 patients with angina symptoms were included and divided into two groups based on the extent of coronary artery disease determined by angiography: the non-severe coronary stenosis group (< 70% stenosis) and the severe coronary stenosis group (≥ 70% stenosis). The diagnostic model was constructed using magnetic field map (MFM) parameters, either individually or in combination with clinical indicators. The performance of the models was evaluated using receiver operating characteristic curves, accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Calibration plots and decision curve analysis were performed to investigate the clinical utility and performance of the models, respectively. RESULTS: In the severe coronary stenosis group, QR_MCTDd, S_MDp, and TT_MAC50 were significantly higher than those in the non-severe coronary stenosis group (10.46 ± 10.66 vs. 5.11 ± 6.07, P < 0.001; 7.2 ± 8.64 vs. 4.68 ± 6.95, P = 0.003; 0.32 ± 57.29 vs. 0.26 ± 57.29, P < 0.001). While, QR_MVamp, R_MA, and T_MA in the severe coronary stenosis group were lower (0.23 ± 0.16 vs. 0.28 ± 0.16, P < 0.001; 55.06 ± 48.68 vs. 59.24 ± 53.01, P < 0.001; 51.67 ± 39.32 vs. 60.45 ± 51.33, P < 0.001). Seven MFM parameters were integrated into the model, resulting in an area under the curve of 0.810 (95% CI: 0.765-0.855). The sensitivity, specificity, PPV, NPV, and accuracy were 71.7%, 80.4%, 93.3%, 42.8%, and 73.5%; respectively. The combined model exhibited an area under the curve of 0.845 (95% CI: 0.798-0.892). The sensitivity, specificity, PPV, NPV, and accuracy were 84.3%, 73.8%, 92.6%, 54.6%, and 82.1%; respectively. Calibration curves demonstrated excellent agreement between the nomogram prediction and actual observation. The decision curve analysis showed that the combined model provided greater net benefit compared to the magnetocardiography model. CONCLUSIONS: The novel quantitative MFM parameters, whether used individually or in combination with clinical indicators, have been shown to effectively predict the risk of severe coronary stenosis in patients presenting with angina-like symptoms. Magnetocardiography, an emerging non-invasive diagnostic tool, warrants further exploration for its potential in diagnosing coronary heart disease.

US Contrast Agent Arrival Time Difference Ratio for Benign versus Malignant Subpleural Pulmonary Lesions.

Background US has proven valuable in the diagnosis of subpleural pulmonary lesions (SPLs); however, existing US indicators have limitations. Purpose To propose and validate a revised contrast-enhanced (CE) US indicator for differential diagnosis of benign and malignant SPLs and to compare its performance with existing CE US diagnostic criteria. Materials and Methods This prospective study (Chinese clinical trial registry, ChiCTR1800019828) enrolled patients with SPLs between May 2019 and August 2020. They were divided into a developmental cohort (DC) and a validation cohort (VC). In the DC, the optimal indicator was selected from five CE US indicators. In the VC, the selected indicator was compared with existing CE US diagnostic criteria using the area under the receiver operating characteristic curve (AUC). Pathologic analysis, microbial evidence, and clinical follow-up were used as reference standards for all SPLs. Results A total of 902 participants (DC, 424 participants; VC, 478 participants) with SPLs (mean age, 56 years ± 17; 593 men) were evaluated. The arrival time (AT) difference ratio proved to be the optimal indicator to distinguish benign from malignant SPLs. In the overall (regardless of lesion size), large (vertical diameter >3 cm), and small (vertical diameter ≤3 cm) lesion groups, the cutoff values of the AT difference ratio were 43%, 42%, and 50% and the AUCs obtained from the VC were 0.91 (95% CI: 0.88, 0.93), 0.97 (95% CI: 0.94, 0.98), and 0.77 (95% CI: 0.71, 0.83) respectively, which were higher than those of lesion-lung AT difference greater than 2.5 seconds (0.81 [P < .001], 0.85 [P < .001], and 0.7 [P = .005], respectively), lesion AT greater than 7.5 seconds (0.65 [P < .001], 0.64 [P < .001], and 0.63 [P < .001], respectively), and lesion AT greater than 10 seconds (0.67 [P < .001], 0.68 [P < .001], and 0.64 [P < .001] respectively). Conclusion The US contrast agent arrival time difference ratio enables better differentiation of benign and malignant subpleural lesions when compared with existing diagnostic criteria. Online supplemental material is available for this article. Published under a CC BY 4.0 license.

Development and Prospective Validation of an Ultrasound Prediction Model for the Differential Diagnosis of Benign and Malignant Subpleural Pulmonary Lesions: A Large Ambispective Cohort Study.

OBJECTIVE: To develop and prospective validate an ultrasound (US) prediction model to differentiate between benign and malignant subpleural pulmonary lesions (SPLs). METHODS: This study was conducted retrospectively from July 2017 to December 2018 (development cohort [DC], n = 592) and prospectively from January to April 2019 (validation cohort [VC], n = 220). A total of 18 parameters of B-mode US and contrast-enhanced US (CEUS) were acquired. Based on the DC, a model was developed using binary logistic regression. Then its discrimination and calibration were verified internally in the DC and externally in the VC, and its diagnostic performance was compared with those of the existing US diagnostic criteria in the two cohorts. The reference criteria were from the comprehensive diagnosis of clinical-radiological-pathological made by two senior respiratory physicians. RESULTS: The model was eventually constructed with 6 parameters: the angle between lesion border and thoracic wall, basic intensity, lung-lesion arrival time difference, ratio of arrival time difference, vascular sign, and non-enhancing region type. In both internal and external validation, the model provided excellent discrimination of benign and malignant SPLs (C-statistic: 0.974 and 0.980 respectively), which is higher than that of "lesion-lung AT difference ≥ 2.5 s" (C-statistic: 0.842 and 0.777 respectively, P <0.001) and "AT ≥ 10 s" (C-statistic: 0.688 and 0.641 respectively, P <0.001) and the calibration curves of the model showed good agreement between actual and predictive malignancy probabilities. As for the diagnosis performance, the sensitivity and specificity of the model [sensitivity: 94.82% (DC) and 92.86% (VC); specificity: 92.42% (DC) and 92.59% (VC)] were higher than those of "lesion-lung AT difference ≥ 2.5 s" [sensitivity: 88.11% (DC) and 80.36% (VC); specificity: 80.30% (DC) and 75.00% (VC)] and "AT ≥ 10 s" [sensitivity: 64.94% (DC) and 61.61% (VC); specificity: 72.73% (DC) and 66.67% (VC)]. CONCLUSION: The prediction model integrating multiple parameters of B-mode US and CEUS can accurately predict the malignancy probability, so as to effectively differentiate between benign and malignant SPLs, and has better diagnostic performance than the existing US diagnostic criteria. CLINICAL TRIAL REGISTRATION: www.chictr.org.cn, identifier ChiCTR1800019828.

Contrast-Enhanced Ultrasound of the Pleural Cavity: A Method to Locate Pleural Catheters and Identify Fibrous Septa.

We aimed to explore the value of contrast-enhanced ultrasound (CEUS) of the pleural cavity in locating catheters and identifying fibrous septa and to compare CEUS with multiple existing methods. We included 304 participants whose pleural effusion could not continue to be drained and compared the catheter-localization capabilities of empirical diagnosis, B-mode ultrasound with normal saline and CEUS, with computed tomography as the reference standard. CEUS performed the best (accuracy, 100%; sensitivity, 100%; specificity, 100%), followed by B-mode ultrasound with normal saline (accuracy, 77.78%; sensitivity, 62.5%; specificity, 100%), and finally empirical diagnosis (accuracy, 54.17%; sensitivity, 66.67%; specificity, 33.33%). The capabilities of CEUS and computed tomography to identify fibrous septa were evaluated, with B-mode ultrasound as the reference, and CEUS (accuracy, 100%; sensitivity, 100%; specificity, 100%) was superior to computed tomography (accuracy, 82.41%; sensitivity, 26.09%; specificity, 97.65%). Overall, CEUS can accurately locate catheters and identify fibrous septa, with performance superior to existing methods.

Clinical performance of Xpert MTB/RIF on contrast-enhanced ultrasound-guided core biopsy specimens for rapid diagnosis of superficial tuberculous lymphadenitis in high TB burden settings.

OBJECTIVE: The diagnosis of superficial tuberculous lymphadenitis (TBLN) remains difficult due to low detection rate of etiology. To increase the diagnostic value for TBLN, contrast-enhanced ultrasound (CEUS) guided core biopsy was introduced to obtain the specimen followed by Xpert MTB/RIF (Xpert) and other methods testing and to explore the optimum diagnostic pattern for TBLN in China. METHODS: A prospective study was performed on patients with suspected superficial TBLN. All patients underwent CEUS-guided core biopsy from which specimens were tested by histopathology, Xpert, acid-fast bacilli (AFB), and MGIT960 culture (MGIT960), respectively. The diagnostic values were calculated and compared. RESULTS: A total of 328 patients were included the study, 272 were diagnosed as TBLN (254 definite TB, 18 probable TB) and 56 cases with Non-TBLN, and 100% (272/272) of TBLN patients obtained diagnosis sampled by CEUS-guided core biopsy. The overall sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of comprehensive diagnosis on the specimens by CEUS-guided core biopsy for TBLN were 100% ( 272/272, 95% CI 98.26-100.00), 94.64% (53/56, 95% CI 84.20-98.61), 98.91% (272/275, 95% CI 96.58-99.72), and 100% (53/53, 95% CI 91.58-100%), respectively. Xpert obtained 93.31% (237/254) of etiology detection rate on the specimens sampling by CEUS-guided biopsy. The etiology detection rate was associated with histopathological caseous necrosis. CONCLUSIONS: Current examinations on specimens by CEUS-guided core biopsy can achieve a high diagnostic efficacy for TBLN. Pathological differentiation of CEUS-guided biopsy tissue, then followed by Xpert, may be the best pattern for the diagnosis of TBLN in high TB burden areas.