The role of multimodal ultrasound in diagnosis of fetal bowel dilatation and prediction of adverse neonatal outcomes: A study of 86 cases in a series of 43,562 births

Objective

To investigate the diagnostic utility of multimodal ultrasound for fetal bowel dilatation (FBD) in different parts of the bowel and to examine its prognostic potential in FBD.

Methods

This retrospective study analyzed 86 fetuses with a dilated bowel identified via ultrasound in a 10-month postnatal follow-up. Both two- and three dimensional (2D and 3D, respectively) ultrasound volume imaging were used to characterize dilation across different bowel sections. The optimal intestinal diameter cut-off values for pathological bowel dilatation were determined and a predictive model for neonatal surgery was developed.

Results

The 86 cases of dilatation were distributed as follows: duodenal (n = 36); jejunum/ileum (n = 35); and colonic (n = 15). Duodenal dilatations presented the earliest during pregnancy compared to the other 2 groups (24.4 versus [vs.] 29 vs. 33.7 weeks respectively; p < 0.05). Cases with small intestinal dilatation were delivered earlier than those with colonic dilatation (p < 0.05). Infants with duodenal dilatation had the lowest birth weight and the highest rate of multi-system abnormalities (30.6% vs. 5.7% vs. 20%; p < 0.001). More than one-half of the multi-system abnormalities had chromosomal abnormalities (multiple, 54% vs. single, 12.5%; p = 0.015). There were 2 stillbirths, 24 induced labors, 44 postnatal surgeries, and 18 normal cases after birth. In predicting adverse neonatal outcomes of jejunum/ileum dilatation using a cut-off value of 15.5 mm small intestine diameter, sensitivity was 81.5%, specificity was 62.5%, and the area under the receiver operating characteristic curve (AUC) was 0.762 (p < 0.05). For colonic dilatation, using a cut-off value of 21.5 mm colon diameter: sensitivity was 83.3%, specificity was 77.8%, and AUC was 0.861 (p < 0.05). In detecting jejunum/ileum and colonic obstruction, 3D ultrasound demonstrated significantly better diagnostic efficiency than 2D ultrasound (p < 0.05). Using the backward stepwise selection method, a predictive model for neonatal surgery in patients with jejunum/ileum and colonic dilatation was established: logit (P) = -1.58 + (2.32 × polyhydramnios) +(2.0 × ascites) +(1.14 × hyperechogenic bowel). The AUC for the prediction model was 0.874 (p < 0.05), with 76% sensitivity and 94.1% specificity.

Conclusions

Duodenal dilatation occurred earlier, with a higher incidence of chromosomal abnormalities and multi-system abnormalities than dilatation of other parts of the bowel. 3D ultrasound played an important role in the detection of jejunum/ileum and colon obstructions. Clinical signs, including polyhydramnios, ascites, and strong echoes in the intestine, can be used to predict neonatal surgery.

Application and prospects of AI-based radiomics in ultrasound diagnosis

Artificial intelligence (AI)-based radiomics has attracted considerable research attention in the field of medical imaging, including ultrasound diagnosis. Ultrasound imaging has unique advantages such as high temporal resolution, low cost, and no radiation exposure. This renders it a preferred imaging modality for several clinical scenarios. This review includes a detailed introduction to imaging modalities, including Brightness-mode ultrasound, color Doppler flow imaging, ultrasound elastography, contrast-enhanced ultrasound, and multi-modal fusion analysis. It provides an overview of the current status and prospects of AI-based radiomics in ultrasound diagnosis, highlighting the application of AI-based radiomics to static ultrasound images, dynamic ultrasound videos, and multi-modal ultrasound fusion analysis.

Preoperative prediction of extrathyroidal extension: radiomics signature based on multimodal ultrasound to papillary thyroid carcinoma

BACKGROUND

There is a recognized need for additional approaches to improve the accuracy of extrathyroidal extension (ETE) diagnosis in papillary thyroid carcinoma (PTC) before surgery. Up to now, multimodal ultrasound has been widely applied in disease diagnosis. We investigated the value of radiomic features extracted from multimodal ultrasound in the preoperative prediction of ETE.

METHODS

We retrospectively pathologically confirmed PTC lesions in 235 patients from January 2019 to April 2022 in our hospital, including 45 ETE lesions and 205 non-ETE lesions. MaZda software was employed to obtain radiomics parameters in multimodal sonography. The most valuable radiomics features were selected by the Fisher coefficient, mutual information, probability of classification error and average correlation coefficient methods (F + MI + PA) in combination with the least absolute shrinkage and selection operator (LASSO) method. Finally, the multimodal model was developed by incorporating the clinical records and radiomics features through fivefold cross-validation with a linear support vector machine algorithm. The predictive performance was evaluated by sensitivity, specificity, accuracy, F1 scores and the area under the receiver operating characteristic curve (AUC) in the training and test sets.

RESULTS

A total of 5972 radiomics features were extracted from multimodal sonography, and the 13 most valuable radiomics features were selected from the training set using the F + MI + PA method combined with LASSO regression. The multimodal prediction model yielded AUCs of 0.911 (95% CI 0.866-0.957) and 0.716 (95% CI 0.522-0.910) in the cross-validation and test sets, respectively. The multimodal model and radiomics model showed good discrimination between ETE and non-ETE lesions.

CONCLUSION

Radiomics features based on multimodal ultrasonography could play a promising role in detecting ETE before surgery.

A case report of diagnosis of liver metastasis of medullary thyroid carcinoma by multimodal ultrasound

Medullary thyroid carcinoma is a rare malignant neuroendocrine tumor. Distant metastasis is difficult to detect early. It is most common in lung, liver, bone and brain. This case was reported as liver metastasis of medullary thyroid carcinoma in an elderly woman, but routine ultrasound findings were atypical. After a series of relevant imaging examinations, contrast-enhanced ultrasound and ultrasound-guided puncture biopsy were used to confirm the nature of the intrahepatic lesions. Therefore, we believe that multimodal ultrasound is of great value in the diagnosis of liver metastasis of medullary thyroid carcinoma.

Multimodal ultrasound-based carotid plaque risk biomarkers predict poor functional outcome in patients with ischemic stroke or TIA

BACKGROUND

Carotid vulnerable plaque is an important risk factor for stroke occurrence and recurrence. However, the relationship between risk parameters related to carotid vulnerable plaque (plaque size, echogenicity, intraplaque neovascularization, and plaque stiffness) and neurological outcome after ischemic stroke or TIA is unclear. This study investigates the value of multimodal ultrasound-based carotid plaque risk biomarkers to predict poor short-term functional outcome after ischemic stroke or TIA.

METHODS

This study was a single-center, prospective, continuous, cohort study to observe the occurrence of adverse functional outcomes (mRS 2-6/3-6) 90 days after ischemic stroke or TIA in patients, where the exposure factors in this study were carotid plaque ultrasound risk biomarkers and the risk factors were sex, age, disease history, and medication history. Patients with ischemic stroke or TIA (mRS ≤3) whose ipsilateral internal carotid artery stenosis was ≥50% within 30 days were included. All patients underwent multimodal ultrasound at baseline, including conventional ultrasound, superb microvascular imaging (SMI), and shear wave elastography (SWE). Continuous variables were divided into four groups at interquartile spacing for inclusion in univariate and multifactorial analyses. After completion of a baseline ultrasound, all patients were followed up at 90 days after ultrasound, and patient modified neurological function scores (mRSs) were recorded. Multivariate Cox regression and ROC curves were used to assess the risk factors and predictive power for predicting poor neurological function.

RESULTS

SMI revealed that 20 (30.8%) patients showed extensive neovascularization in the carotid plaque, and 45 (69.2%) patients showed limited neovascularization in the carotid plaque. SWE imaging showed that the mean carotid plaque stiffness was 51.49 ± 18.34 kPa (23.19-111.39 kPa). After a mean follow-up of 90 ± 14 days, a total of 21 (32.3%) patients had a mRS of 2-6, and a total of 10 (15.4%) patients had a mRS of 3-6. Cox regression analysis showed that the level of intraplaque neovascularization and plaque stiffness were independent risk factors for a mRS of 2-6, and the level of intraplaque neovascularization was an independent risk factor for a mRS of 3-6. After correcting for confounders, the HR of intraplaque neovascularization level and plaque stiffness predicting a mRS 2-6 was 3.06 (95% CI 1.05-12.59, P = 0.041) and 0.51 (95% CI 0.31-0.83, P = 0.007), respectively; the HR of intraplaque neovascularization level predicting a mRS 3-6 was 6.11 (95% CI 1.19-31.45, P = 0.031). For ROC curve analysis, the mRSs for intraplaque neovascularization level, plaque stiffness, and combined application to predict 90-day neurological outcome ranged from 2 to 6, with AUCs of 0.73 (95% CI 0.59-0.87), 0.76 (95% CI 0.64-0.89) and 0.85 (95% CI 0.76-0.95), respectively. The mRSs for the intraplaque neovascularization level to predict 90-day neurological outcome ranged from 3 to 6, with AUCs of 0.79 (95% CI 0.63-0.95).

CONCLUSION

Intraplaque neovascularization level and plaque stiffness may be associated with an increased risk of poor short-term functional outcome after stroke in patients with recent anterior circulation ischemic stroke due to carotid atherosclerosis. The combined application of multiple parameters has efficacy in predicting poor short-term functional outcome after stroke.

Update on the use of ultrasound in the diagnosis and monitoring of the critical patient

Hemodynamic and respiratory complications are the main causes of morbidity and mortality in in critical care units (CCU). Imaging techniques are a key tool in differential diagnosis and treatment. In the last decade, ultrasound has shown great potential for bedside diagnosis of respiratory disease, as well as for the hemodynamic assessment of critically ill patients. Ultrasound has proven to be a useful guide for identifying the type of shock, estimating cardiac output, guiding fluid therapy and vasoactive drugs, providing security in the performance of percutaneous techniques (thoracentesis, pericardiocentesis, evacuation of abscesses/hematomas), detecting dynamically in real time pulmonary atelectasis and its response to alveolar recruitment maneuvers, and predicting weaning failure from mechanical ventilation. Due to its dynamic nature, simple learning curve and absence of ionizing radiation, it has been incorporated as an essential tool in daily clinical practice in CCUs. The objective of this review is to offer a global vision of the role of ultrasound and its applications in the critically ill patient.

Multimodal Ultrasound Imaging in Breast Imaging-Reporting and Data System 4 Breast Lesions: A Prediction Model for Malignancy

The purpose of this study was to develop, validate and test a prediction model for discriminating malignant from benign breast lesions using conventional ultrasound (US), US elastography of strain elastography and contrast-enhanced ultrasound (CEUS). The study included 454 patients with breast imaging-reporting and data system (BI-RADS) category 4 breast lesions identified on histologic examinations. Firstly, 228 breast lesions (cohort 1) were analyzed by logistic regression analysis to identify the risk factors, and a breast malignancy prediction model was created. Secondly, the prediction model was validated in cohort 2 (84 patients) and tested in cohort 3 (142 patients) by using analysis of the area under the receiver operating characteristic curve (AUC). Univariate regression indicated that age ≥40 y, taller than wide shape on US, early hyperenhancement on CEUS and enlargement of enhancement area on CEUS were independent risk factors for breast malignancy (all p < 0.05). The logistic regression equation was established as follows: p = 1/1+Exp∑[-5.066 + 3.125 x (if age ≥40 y) + 1.943 x (if taller than wide shape) + 1.479 x (if early hyperenhancement) + 4.167 x (if enlargement of enhancement area). The prediction model showed good discrimination performance with an AUC of 0.967 in cohort 1, 0.948 in cohort 2 and 0.920 in cohort 3. By using the prediction model to selectively downgrade category 4a lesions, the re-rated BI-RADS yield an AUC of 0.880 (95% confidence interval [CI], 0.794-0.965) in cohort 2 and 0.870 (95% CI, 0.801-0.939) in cohort 3. The specificity increased from 0.0% (0/35) to 80.0% (28/35) without loss of sensitivity (from 100.0% to 95.9%, p = 0.153) in cohort 2. Similarly, the specificity increased from 0.0% (0/58) to 77.6% (45/58) without loss of sensitivity (from 100.0% to 96.4%, p = 0.081) in cohort 3. Multimodal US showed good diagnostic performance in predicting breast malignancy of BI-RADS category 4 lesions. Although the loss of sensitivity was existing, the addition of multimodal US to US BI-RADS could improve the specificity in BI-RADS category 4 lesions, which reduced unnecessary biopsies.

Characteristic analysis of Zenker's diverticulum incidentally detected on multimodal neck ultrasound

PURPOSE

Zenker's diverticulum (ZD) incidentally detected on neck ultrasound (US) could be easily misdiagnosed as a thyroid nodule and unnecessarily removed by surgical operation. It is a critical issue to identify the characteristics of ZD in clinical practice.

METHODS

We reported 10 cases of ZD diagnosed using multimodal US, and discussed the features of its multimodal US images extracted from grayscale sonograms, color Doppler flow imaging (CDFI), three-dimensional US (3D-US), and contrast-enhanced US (CEUS).

RESULTS

All lesions were heterogeneous in the posterior of the left thyroid. CDFI showed no blood flow within the lesions. The shapes and internal echoes of the masses changed when patients swallowed or drank. Performing CEUS or 3D-US for those with atypical US findings was complementary to make the final diagnosis. Importantly, multimodal US helped to diagnose suspected small lesions in three cases in which the barium esophagram tests proved negative.

CONCLUSIONS

The US features of ZD detected by multiple modes of US can help in the collection of comprehensive imaging information on ZD, which should be used proactively to facilitate the correct diagnosis and to avoid misdiagnosis of ZD.

[Application of Multimodal Transcranial Ultrasound in SD Rats of Cerebral Ischemic Model at Super Early Stage]

OBJECTIVE

To determine the value of applying multimodal ultrasound (mUS) in SD rats of cerebral ischemic model at super early stage (5-15 min after modeling).

METHODS

Fifteen focal cerebral ischemic models were established in SD rats with thinning skulls using the suture method. Gray-scale ultrasound, contrast-enhanced ultrasound, and enhanced color Doppler (CECDUS) were performed before and immediately after the modeling to observe the location of the in-cranial suture, perfusion of the right hemisphere, and color flow signal of the middle cerebral artery and the anterior cerebral artery, respectively.A modified neurological deficit score (mNSS) and 2, 3, 5-triphenyltetrazolium chloride (TTC) stains were obtained three hours later to confirm the successful modeling as the gold standard. The positive rate detected by mUS was compared with the gold standard using McNemar tests.

RESULTS

One rat died and 14 rats completed the experiment.mUS imaging detected 71% (10/14) positive signals, no significant difference compared with the gold standard (64%, 9/14) ( P>0.05). A hyperechoic double-line at the bottom of the right brain and focal hypoperfused areas in the right hemisphere were observed by gray scale ultrasound and contrast-enhanced ultrasound in the successfully modeled rats, respectively. The CECDUS found no blood flow in the anterior and middle cerebral arteries. Time intensity curve (TIC) analyses indicated significant changes in peak intensity (PI), area under the curve (AUC), wash in slope (WIS), and time to peak (TTP) after successful modeling.

CONCLUSION

Multimodal ultrasound can assess modeling success quickly and accurately immediately after the establishment of ischemic model of SD rats.