Deep learning-based automatic scoring models for the disease activity of rheumatoid arthritis based on multimodal ultrasound images.

OBJECTIVES: We aimed to investigate the value of deep learning (DL) models based on multimodal ultrasonographic (US) images to quantify RA activity. METHODS: Static greyscale (SGS), dynamic greyscale (DGS), static power Doppler (SPD) and dynamic power Doppler (DPD) US images were collected and evaluated by two expert radiologists according to the EULAR-OMERACT Synovitis Scoring system. Four DL models were developed based on the ResNet-type structure, evaluated on two separate test cohorts, and finally compared with the performance of 12 radiologists with different levels of experience. RESULTS: In total, 1244 images were used for the model training, and 152 and 354 for testing (cohort 1 and 2, respectively). The best-performing models for the scores of 0/1/2/3 were the DPD, SGS, DGS and SPD models, respectively (Area Under the receiver operating characteristic Curve [AUC] = 0.87/0.95/0.74/0.95; no significant differences). All the DL models provided results comparable to the experienced radiologists on a per-image basis (intraclass correlation coefficient: 0.239-0.756, P < 0.05). The SPD model performed better than the SGS one on test cohort 1 (score of 0/2/3: AUC = 0.82/0.67/0.95 vs 0.66/0.66/0.75, respectively) and test cohort 2 (score of 0: AUC = 0.89 vs 0.81). The dynamic DL models performed better than the static ones in most of the scoring processes and were more accurate than the most of senior radiologists, especially the DPD model. CONCLUSION: DL models based on multimodal US images allow a quantitative and objective assessment of RA activity. Dynamic DL models in particular have potential value in assisting radiologists to improve the accuracy of RA US-based grading.

Localization of Ectopic Hyperparathyroidism: Ultrasound Versus 99mTc-sestamibi, 4-Dimensional Computed Tomography, and 11C-choline Positron Emission Tomography/Computed Tomography.

OBJECTIVE: To investigate the usefulness of ultrasound (US) for the localization of ectopic hyperparathyroidism and compare it with 99mTc-sestamibi (99mTc-MIBI), 4-dimensional computed tomography (4D-CT), and 11C-choline positron emission tomography/ computed tomography (PET/CT). METHODS: Of the 527 patients with surgically confirmed primary hyperparathyroidism, 79 patients with ectopic hyperparathyroidism were enrolled. The diagnostic performance of US, 99mTc-MIBI, US + MIBI, 4D-CT, and 11C-choline PET/CT was calculated, and the factors affecting the sensitivity of US and 99mTc-MIBI were analyzed. RESULTS: Eighty-three ectopic parathyroid lesions were found in 79 patients. The sensitivity was 75.9%, 81.7%, 95.1%, 83.3%, and 100% for US, 99mTc-MIBI, US + MIBI, 4D-CT, and 11C-choline PET/CT, respectively. The difference in sensitivity among these different modalities did not achieve statistical significance (P > .05). The US sensitivity was significantly higher for ectopic lesions in the neck region than for those in the anterior mediastinum/chest wall (85.9% vs. 42.1%, P < .001). The 99mTc-MIBI and 4D-CT sensitivity was not significantly different between these two groups (84.1% vs. 94.6%, P = .193 and 81.3% vs. 85.7%, P = 1). The 11C-choline PET/CT sensitivity was 100% in both groups. CONCLUSIONS: US is a valuable tool for the localization of ectopic hyperparathyroidism, especially for ectopic lesions in the neck region.

Clinical application of intraoperative ultrasound superb microvascular imaging in brain tumors resections: contributing to the achievement of total tumoral resection.

BACKGROUND: To investigate whether the intraoperative superb microvascular imaging(SMI) technique helps evaluate lesion boundaries compared with conventional grayscale ultrasound in brain tumor surgery and to explore factors that may be associated with complete radiographic resection. METHODS: This study enrolled 57 consecutive brain tumor patients undergoing surgery. During the operation, B-mode and SMI ultrasound evaluated the boundaries of brain tumors. MRI before and within 48h after surgery was used as the gold standard to evaluate gross-total resection(GTR). The ultrasound findings and GTR results were analyzed to determine the imaging factors related to GTR. RESULTS: A total of 57 patients were enrolled in the study, including 32 males and 25 females, with an average age of 53.4 ± 14.1 years old(range 19 ~ 80). According to the assessment criteria of MRI, before and within 48 h after the operation, 37(63.9%) cases were classified as GTR, and 20(35.1%) cases were classified as GTR. In comparing tumor interface definition between B-mode and SMI mode, SMI improved HGG boundary recognition in 5 cases(P = 0.033). The results showed that the tumor size ≥ 5 cm and unclear ultrasonic boundary were independent risk factors for nGTR (OR>1, P<0.05). CONCLUSIONS: As an innovative intraoperative doppler technique in neurosurgery, SMI can effectively demarcate the tumor's boundary and help achieve GTR as much as possible.

How to identify juxtaglomerular cell tumor by ultrasound: a case series and review of the literature.

PURPOSE: To study the value of ultrasound in the diagnosis of juxtaglomerular cell tumor (JGCT). METHODS: From January 2005 to July 2020, fifteen patients diagnosed as JGCT by surgical pathology in Peking Union Medical College Hospital were collected. All patients underwent preoperative ultrasound examination. The clinical, laboratory, ultrasound, computed tomography (CT), surgical, and pathological features of the patients were analyzed retrospectively. RESULTS: The 15 patients were 5 males and 10 females with a median age of 29 years (10∼72 years). 14 of them had hypertension and one had normal blood pressure. The tumors were all solitary, with a median diameter of 1.5 cm (0.9-5.9 cm). Among the fifteen patients, eleven were correctly detected by preoperative ultrasound, and four were missed. There was a significant difference in tumor size (2.64 ± 1.48 cm vs. 1.23 ± 0.21 cm) and whether the tumor protruded outward (9/11 vs. 0/4) between the ultrasound-detected group and the ultrasound-missed group (p = 0.010, p = 0.011). Of the 11 tumors detected by ultrasound, four were extremely hypoechoic, two were hypoechoic, three were isoechoic, and two were hyperechoic. Color Doppler showed no blood flow in five tumors with the size range from 0.9 to 2.0 cm, and mild blood flow in six tumors with the size range from 2.8 to 5.9 cm. CONCLUSIONS: JGCT is rare, and has characteristic clinical manifestations. Diagnosis should be suspected in case of secondary hypertension, particularly in young women, if no renal vascular cause was found. Ultrasound, combined with clinical manifestations, was helpful for the diagnosis.

Deep-learning-based renal artery stenosis diagnosis via multimodal fusion.

PURPOSE: Diagnosing Renal artery stenosis (RAS) presents challenges. This research aimed to develop a deep learning model for the computer-aided diagnosis of RAS, utilizing multimodal fusion technology based on ultrasound scanning images, spectral waveforms, and clinical information. METHODS: A total of 1485 patients received renal artery ultrasonography from Peking Union Medical College Hospital were included and their color doppler sonography (CDS) images were classified according to anatomical site and left-right orientation. The RAS diagnosis was modeled as a process involving feature extraction and multimodal fusion. Three deep learning (DL) models (ResNeSt, ResNet, and XCiT) were trained on a multimodal dataset consisted of CDS images, spectrum waveform images, and individual basic information. Predicted performance of different models were compared with senior physician and evaluated on a test dataset (N = 117 patients) with renal artery angiography results. RESULTS: Sample sizes of training and validation datasets were 3292 and 169 respectively. On test data (N = 676 samples), predicted accuracies of three DL models were more than 80% and the ResNeSt achieved the accuracy 83.49% ± 0.45%, precision 81.89% ± 3.00%, and recall 76.97% ± 3.7%. There was no significant difference between the accuracy of ResNeSt and ResNet (82.84% ± 1.52%), and the ResNeSt was higher than the XCiT (80.71% ± 2.23%, p < 0.05). Compared to the gold standard, renal artery angiography, the accuracy of ResNest model was 78.25% ± 1.62%, which was inferior to the senior physician (90.09%). Besides, compared to the multimodal fusion model, the performance of single-modal model on spectrum waveform images was relatively lower. CONCLUSION: The DL multimodal fusion model shows promising results in assisting RAS diagnosis.

Pitfalls of ultrasound for deep vein thrombosis of the lower extremities.

Venous ultrasound is the primary, widely accepted diagnostic tool to assess deep vein thrombosis (DVT) in the lower extremities. However, other focal lesions in the lower extremities can be identified on ultrasound. The sonographic appearance of these abnormalities may overlap the thrombosis, which included vascular tumors, Baker's cyst, hematoma, cancer thrombosis, and peripheral nerve tumors. This essay derives from cases diagnosed in our centers and published literature, with images available for illustrations, which may help to improve the clinical management of these findings.

Synovial Oxygenation at Photoacoustic Imaging to Assess Rheumatoid Arthritis Disease Activity.

Background Synovial hypoxia is a hallmark of rheumatoid arthritis (RA). Photoacoustic (PA) imaging, based on the use of laser-generated US, can detect the oxygenation status of tissue in individuals with RA. However, large studies are lacking, with few investigating the correlation between oxygenation status and disease activity. Purpose To measure synovial oxygenation status in participants with RA by using a multimodal PA US imaging system and to determine the correlation between PA imaging-measured oxygen saturation (SO2) and disease activity. Materials and Methods In this prospective observational cohort study, multimodal PA US imaging examinations were performed on small joints of consecutive participants with RA, who were treated at two outpatient rheumatology clinics from 2019 to 2021, and healthy controls. The SO2 values of the synovium were measured with dual-wavelength PA imaging and classified into three categories-hyperoxia, intermediate oxygenation status, or hypoxia-based on the signal coloration and clustering analysis of the SO2 values. The correlations of oxygenation status with power Doppler US (PDUS) scoring and clinical disease activity index were evaluated with one-way analysis of variance and the Kruskal-Wallis test with Bonferroni correction. Results A total of 118 participants with RA (median age, 55 years [IQR, 41-62 years]; 92 women) and 15 healthy control participants (median age, 37 years [IQR, 33-41 years]; 11 women) were included. The wrist synovium was categorized as hyperoxic in 36 participants with RA, of intermediate oxygenation status in 48 participants, and hypoxic in 34 participants. All control participants had hyperoxic synovial tissues. For participants with RA, hyperoxic synovium had more affluent Doppler US-depicted vasculature than those with hypoxia and intermediate oxygenation status (mean PDUS grade: hyperoxia, 2.7 ± 0.6 [SD]; intermediate, 1.3 ± 0.7; hypoxia, 1.1 ± 0.8; P < .001). Participants with intermediate status synovium had a lower clinical disease activity index than those with hypoxia (intermediate, 11.0 [IQR, 5.0-21.5] vs hypoxia, 26.0 [IQR, 18.0-39.0]; P = .001). Conclusion Photoacoustic imaging-detected hypoxia in thickened synovium correlated with less vascularization and higher disease activity in participants with rheumatoid arthritis. Clinical trial registration no. NCT04297475 © RSNA, 2022 Online supplemental material is available for this article.

Ultrasound-based deep learning in the establishment of a breast lesion risk stratification system: a multicenter study.

OBJECTIVES: To establish a breast lesion risk stratification system using ultrasound images to predict breast malignancy and assess Breast Imaging Reporting and Data System (BI-RADS) categories simultaneously. METHODS: This multicenter study prospectively collected a dataset of ultrasound images for 5012 patients at thirty-two hospitals from December 2018 to December 2020. A deep learning (DL) model was developed to conduct binary categorization (benign and malignant) and BI-RADS categories (2, 3, 4a, 4b, 4c, and 5) simultaneously. The training set of 4212 patients and the internal test set of 416 patients were from thirty hospitals. The remaining two hospitals with 384 patients were used as an external test set. Three experienced radiologists performed a reader study on 324 patients randomly selected from the test sets. We compared the performance of the DL model with that of three radiologists and the consensus of the three radiologists. RESULTS: In the external test set, the DL model achieved areas under the receiver operating characteristic curve (AUCs) of 0.980 and 0.945 for the binary categorization and six-way categorizations, respectively. In the reader study set, the DL BI-RADS categories achieved a similar AUC (0.901 vs. 0.933, p = 0.0632), sensitivity (90.98% vs. 95.90%, p = 0.1094), and accuracy (83.33% vs. 79.01%, p = 0.0541), but higher specificity (78.71% vs. 68.81%, p = 0.0012) than those of the consensus of the three radiologists. CONCLUSIONS: The DL model performed well in distinguishing benign from malignant breast lesions and yielded outcomes similar to experienced radiologists. This indicates the potential applicability of the DL model in clinical diagnosis. KEY POINTS: • The DL model can achieve binary categorization for benign and malignant breast lesions and six-way BI-RADS categorizations for categories 2, 3, 4a, 4b, 4c, and 5, simultaneously. • The DL model showed acceptable agreement with radiologists for the classification of breast lesions. • The DL model performed well in distinguishing benign from malignant breast lesions and had promise in helping reduce unnecessary biopsies of BI-RADS 4a lesions.

Sonographic prediction of intraductal papillary carcinoma with partially cystic breast lesions.

BACKGROUND: Intraductal papillary carcinoma (IDPC) is a rare but fatal disease. Preoperative ultrasound diagnosis of IDPC remains challenging and meaningful. The aim of the study was to determine an effective ultrasound model to predict intraductal papillary carcinoma (IDPC) in patients with partially cystic breast lesions on ultrasound. METHODS: We reviewed female patients with breast nodules who underwent biopsy or surgery between 2004 and 2019, and pathological results were used as the reference standard. We finally included 21 IDPC patients with partially cystic lesions on preoperative ultrasound matched to 40 patients with intraductal papilloma. The association of ultrasound features with IDPC was analysed. RESULTS: Posterior echo enhancement (P < 0.001), tumour size (P = 0.002), irregular shape (P = 0.003), wide base (P = 0.003), solid-mainly component (P = 0.013), rich Doppler flow (P < 0.001) and multiple lesions (P = 0.044) were associated with IDPC by univariate analysis. Based on univariate analysis, variables were included in the regression analysis to obtain independent factors. The regression analysis showed that microcalcification, multiple lesions, posterior echo enhancement, wide base of solid components and rich colour Doppler flow were predictors for IDPC (P < 0.001). The collective model of the independent factors (microcalcification, multiple lesions, posterior echo enhancement, wide base of solid components and rich colour Doppler flow) could predict IDPC with an area under the curve (AUC) of 0.99 (95% CI 0.95-1.00). The collective model had a better net benefit demonstrated by the decision curve. CONCLUSION: Ultrasonic features may be an applicable model for predicting IDPC with partially cystic breast lesions on ultrasound and has a better potential to facilitate decision-making preoperatively.

Real-time carotid plaque recognition from dynamic ultrasound videos based on artificial neural network.

PURPOSE: Carotid ultrasound allows noninvasive assessment of vascular anatomy and function with real-time display. Based on the transfer learning method, a series of research results have been obtained on the optimal image recognition and analysis of static images. However, for carotid plaque recognition, there are high requirements for self-developed algorithms in real-time ultrasound detection. This study aims to establish an automatic recognition system, Be Easy to Use (BETU), for the real-time and synchronous diagnosis of carotid plaque from ultrasound videos based on an artificial neural network. MATERIALS AND METHODS: 445 participants (mean age, 54.6±7.8 years; 227 men) were evaluated. Radiologists labeled a total of 3259 segmented ultrasound images from 445 videos with the diagnosis of carotid plaque, 2725 images were collected as a training dataset, and 554 images as a testing dataset. The automatic plaque recognition system BETU was established based on an artificial neural network, and remote application on a 5G environment was performed to test its diagnostic performance. RESULTS: The diagnostic accuracy of BETU (98.5%) was consistent with the radiologist's (Kappa = 0.967, P < 0.001). Remote diagnostic feedback based on BETU-processed ultrasound videos could be obtained in 150ms across a distance of 1023 km between the ultrasound/BETU station and the consultation workstation. CONCLUSION: Based on the good performance of BETU in real-time plaque recognition from ultrasound videos, 5G plus Artificial intelligence (AI)-assisted ultrasound real-time carotid plaque screening was achieved, and the diagnosis was made.

Ultrasonography and contrast-enhanced ultrasound for activity assessment in 115 patients with carotid involvement of Takayasu arteritis.

OBJECTIVES: To evaluate the efficacy of ultrasound and contrast-enhanced ultrasound (CEUS) in disease activity assessment of Takayasu arteritis (TA) with carotid involvement. METHODS: This is a cohort study of 115 patients of TA with carotid involvement. We investigated correlations between clinical data, sonographic features, and CEUS enhancement at the site most prominent lesion of each patient. Disease activity was assessed by the National Institute of Health Kerr criteria. Sonographic findings were compared with follow-up examinations. CEUS was repeated after a 3-7 months interval in 35 patients to evaluate change of CEUS enhancement after treatment. RESULTS: Extensiveness of CEUS enhancement at most prominent carotid lesions had significant correlations with disease activity by the Kerr criteria (P < .001). The specificity of extensive enhancement for indicating active disease was 95%, while sensitivity was 67%. Patients with active disease showed greater arterial wall thickness and more prominent reduction of arterial wall thickness after treatment. Most of the patients (68%) with subsided active disease after treatment featured decrease of CEUS enhancement. CONCLUSIONS: Extensiveness of enhancement by CEUS and arterial wall thickness by ultrasonography may be useful markers for initial and follow-up assessment of disease activity of TA with common carotid artery involvement.

[Performance of Contrast-enhanced Ultrasound Liver Imaging Reporting and Data System LR-5 in the Diagnosis of Hepatocellular Carcinoma:A Meta-analysis].

Objective To evaluate the performance of contrast-enhanced ultrasound (CEUS) liver imaging reporting and data system (LI-RADS) LR-5 in the diagnosis of hepatocellular carcinoma (HCC). Methods The clinical research reports with the application of CEUS LI-RADS in the diagnosis of HCC were collected from PubMed,Embase,Cochrane Library,CNKI,and Wanfang Data from inception to November 14,2021.Two researchers respectively screened the literature and extracted relevant information.The Quality Assessment of Diagnostic Accuracy Studies (QUADAS) was used to evaluate the quality of all the included articles.RevMan 5.4,Meta disc 1.4,and Stata 16.0 were employed to analyze the diagnostic performance of LR-5 for HCC in high-risk patients. Results Twenty original studies were included,involving a total of 6131 lesions,of which 5142 were HCC.The results of meta-analysis showed that the LR-5 in CEUS LI-RADS for diagnosing HCC in the high-risk population had the overall sensitivity of 0.72 (95%CI=0.66-0.77),the overall specificity of 0.93 (95%CI=0.87-0.96),the overall positive likelihood ratio of 9.89 (95%CI=5.31-18.41),the overall negative likelihood ratio of 0.30 (95%CI=0.25-0.37),and the area under the summary receiver operating characteristic curve of 0.88 (95%CI=0.85-0.91).There was heterogeneity among the included studies (I2=95.31,P<0.001).The funnel plot indicated the existence of publication bias (P=0.04). Conclusion The CEUS LI-RADS can effectively diagnose HCC in high-risk patients based on the LR-5 criteria.

Determine independent gut microbiota-diseases association by eliminating the effects of human lifestyle factors.

Lifestyle and physiological variables on human disease risk have been revealed to be mediated by gut microbiota. Low concordance between case-control studies for detecting disease-associated microbe existed due to limited sample size and population-wide bias in lifestyle and physiological variables. To infer gut microbiota-disease associations accurately, we propose to build machine learning models by including both human variables and gut microbiota. When the model's performance with both gut microbiota and human variables is better than the model with just human variables, the independent gut microbiota -disease associations will be confirmed. By building models on the American Gut Project dataset, we found that gut microbiota showed distinct association strengths with different diseases. Adding gut microbiota into human variables enhanced the classification performance of IBD significantly; independent associations between occurrence information of gut microbiota and irritable bowel syndrome, C. difficile infection, and unhealthy status were found; adding gut microbiota showed no improvement on models' performance for diabetes, small intestinal bacterial overgrowth, lactose intolerance, cardiovascular disease. Our results suggested that although gut microbiota was reported to be associated with many diseases, a considerable proportion of these associations may be very weak. We proposed a list of microbes as biomarkers to classify IBD and unhealthy status. Further functional investigations of these microbes will improve understanding of the molecular mechanism of human diseases.

Evaluation of the diagnostic performance of the EFSUMB CEUS Pancreatic Applications guidelines (2017 version): a retrospective single-center analysis of 455 solid pancreatic masses.

OBJECTIVES: To explore the diagnostic performance of EFSUMB CEUS Pancreatic Applications guidelines (version 2017) before and after the addition of iso-enhancement and very fast/fast washout as supplementary diagnostic criteria for PDAC. METHODS: In this retrospective study, patients diagnosed with solid pancreatic lesions from January 2017 to December 2020 were evaluated. Pancreatic ductal adenocarcinoma (PDAC) is reported to show hypo-enhancement in all phases according to the EFSUMB guidelines. First, based on this definition, all lesions were categorized as PDAC and non-PDAC. Then, iso-enhancement and very fast/fast washout were added as supplementary diagnostic criteria, and all lesions were recategorized. The diagnostic performance was assessed in terms of the accuracy (ACC), sensitivity (SEN), specificity (SPE), positive predictive value (PPV), and negative predictive value (NPV). The reference standard consisted of histologic evaluation or composite imaging and clinical follow-up findings. RESULTS: A total of 455 nodules in 450 patients (median age, 58.37 years; 250 men) were included. The diagnostic performance using the EFSUMB CEUS guidelines for PDAC had an ACC of 69.5%, SEN of 65.4%, SPE of 84%, PPV of 93.5%, NPV of 40.6%, and ROC of 0.747. After recategorization according to the supplementary diagnostic criteria, the diagnostic performance for PDAC had an ACC of 95.8%, SEN of 99.2%, SPE of 84%, PPV of 95.7%, NPV of 96.6%, and ROC of 0.916. CONCLUSION: The EFSUMB guidelines and recommendations for pancreatic lesions can effectively identify PDAC via hypo-enhancement on CEUS. However, the diagnostic performance may be further improved by the reclassification of PDAC lesions after adding iso-enhancement and very fast/fast washout mode. KEY POINTS: • In the EFSUMB guidelines, the only diagnostic criterion for PDAC is hypo-enhancement, to which iso-enhancement and very fast/fast washout mode were added in our research. • Using hypo-enhancement/iso-enhancement with very fast/fast washout patterns as the diagnostic criteria for PDAC for solid pancreatic masses on CEUS has high diagnostic accuracy. • The blood supply pattern of PDAC can provide important information, and CEUS has unique advantages in this respect due to its real-time dynamic attenuation ability.

Evaluation of Appendicular Muscle Mass in Sarcopenia in Older Adults Using Ultrasonography: A Systematic Review and Meta-Analysis.

BACKGROUND: The measurement of appendicular muscle mass is essential for the diagnosis of sarcopenia. Ultrasonography is an accurate and convenient method used to evaluate muscle mass. OBJECTIVE: The aim of the study was to evaluate the diagnostic value of ultrasonography for appendicular muscle mass in sarcopenia in older adults and find out proper ultrasound parameters. METHODS: Medline, Embase, Cochrane, and Web of Science databases were searched for relevant articles. Published studies on the validity and/or reliability of ultrasonography for quantifying muscle mass of the limbs in sarcopenia in the older population were included. A systematic review was conducted based on specific muscles and reference methods. A meta-analysis was conducted to assess the validity and reliability of the ultrasonography. RESULTS: Forty articles were included in this review. There were nine, nine, nine, and four studies included in the qualitative synthesis for a diagnostic test, correlation coefficient, intra-class reliability, and inter-class reliability, respectively. The diagnostic value of rectus femoris (RF) or gastrocnemius (GM) thickness on ultrasonography for sarcopenia or low muscle mass was moderate (the area under summary receiver operating characteristic curve [SROC] = 0.76, 95% confidence interval [CI]: 0.72-0.79, SROC = 0.80, 95% CI: 0.76-0.83, respectively). The pooled correlation between muscle mass on dual-energy X-ray (DXA) or bioelectrical impedance analysis (BIA) and muscle thickness (MT) on ultrasound was moderate (r = 0.56, 95% CI: 0.49-0.62). There was a low-to-moderate correlation between muscle mass on DXA or BIA and cross-sectional area (CSA) on ultrasound (r = 0.267-0.584). The correlation was high to very high between muscle mass from DXA and the ultrasound-predicted formula (r = 0.85-0.963). The CSA from ultrasound had a high or very high correlation with that from computed tomography or magnetic resonance imaging (r = 0.826, intra (inter)-correlation coefficient [ICC] = 0.998-0.999). The respective meta-analyses showed good inter-rater and intra-rater reliabilities (ICC > 0.9). CONCLUSION: Ultrasonography is a reliable and valid diagnostic method for the quantitative assessment of appendicular muscle mass in sarcopenia in older people. The thickness and CSA of the RF or GM seem to be proper ultrasound parameters to predict muscle mass in sarcopenia. Multicenter studies with large samples and the application of new ultrasonic techniques will be the future research directions.

[Research Progress of Targeted Ultrasound Contrast Agent BR55].

BR55 is an ultrasound contrast agent targeting vascular endothelial growth factor receptor 2,which can be used to detect tumor neovascularization and improve the diagnostic accuracy.Overseas researchers have used BR55 for human ultrasound molecular imaging,which showed good safety and tolerance.We reviewed the research progress on BR55 applied in the evaluation of tumor neovascularization from the composition,characteristics,animal experiments,and clinical studies of BR55.

Multimodal photoacoustic/ultrasonic imaging system: a promising imaging method for the evaluation of disease activity in rheumatoid arthritis.

OBJECTIVES: We aimed to assess the clinical value of multimodal photoacoustic/ultrasound (PA/US) articular imaging scores, a novel imaging method which can reflect the micro-vessels and oxygenation level of inflamed joints of rheumatoid arthritis (RA). METHODS: Seven small joints were examined by the PA/US imaging system. A 0-3 scoring system was used to semi-quantify the PA and power-Doppler (PD) signals, and the sums of PA and PD scores (PA-sum and PD-sum scores) of the seven joints were calculated. The relative oxygen saturation (SO2) values of the inflamed joints were measured and classified into 3 PA+SO2 patterns. The correlations between the PA/US imaging scores and the disease activity scores were assessed. RESULTS: Thirty-one patients of RA and a total of 217 joints were examined using the PA/US system. The PA-sum had high positive correlations with the standard clinical scores of RA (DAS28 [ESR] ρ = 0.754, DAS28 [CRP] ρ = 0.796, SDAI ρ = 0.836, CDAI ρ = 0.837, p < 0.001), which were superior to the PD-sum (DAS28 [ESR] ρ = 0.651, DAS28 [CRP] ρ = 0.676, SDAI ρ = 0.716, CDAI ρ = 0.709, p < 0.001). For the patients with high PA-sum scores, significant differences between hypoxia and hyperoxia were identified in pain visual analog score (p = 0.020) and patient's global assessment (p = 0.026). The PA+SO2 patterns presented moderate and high correlation with PGA (ρ = 0.477, p = 0.0077) and VAS pain score (ρ = 0.717, p < 0.001). CONCLUSION: The PA scores have significant correlations with standard clinical scores for RA, and the PA+SO2 patterns are also related with clinical scores that reflect pain severity. PA may have clinical potential in evaluating RA. KEY POINTS: • Multimodal photoacoustic/ultrasound imaging is a novel method to assess micro-vessels and oxygenation of local lesions. • Significant correlations between multimodal imaging parameters and clinical scores of RA patients were verified. • The multimodal PA/US system can provide objective imaging parameters, including PA scores of micro-vessels and relative SO2 value, as a supplementary to disease activity evaluation.

A Retrospective Study of Ultrasonography in the Investigation of Primary Hyperparathyroidism: A New Perspective for Ultrasound Echogenicity Features of Parathyroid Nodules.

OBJECTIVE: To identify and understand parathyroid lesions of patients with primary hyperparathyroidism (PHPT) more accurately under ultrasound. METHODS: This retrospective study involved 423 adult patients with PHPT with a single parathyroid nodule and positive parathyroid ultrasonography between 2018 and 2019. The clinical characteristics of the study patients and histopathologic sections were reviewed. RESULTS: According to the main grayscale echogenicity features of parathyroid nodules, 423 cases were divided into groups: iso-hyperechogenicity solid (61/423), hypoechogenicity solid (304/423), and mixed-echogenicity cyst-solid (58/423) groups. Comparison among the 3 groups showed that the iso-hyperechogenicity group included more asymptomatic patients with PHPT and fewer patients with severe symptoms like bone fractures (P < .05). The mixed-echogenicity group showed higher median serum parathyroid hormone (PTH) and serum calcium levels and larger lesion sizes (P < .05), and the iso-hyperechogenicity group showed the lowest median serum PTH level. No difference in lesion size was noted between the 2 solid groups, but the median serum PTH level in the hypoechogenicity group was higher than that in the iso-hyperechogenicity group (P < .05). According to histopathology, the hypoechogenic area of the samples may contain more functional components (chief cells), whereas the iso-hyperechogenic area has more nonfunctional components (eg, lipocytes and connective tissues). CONCLUSION: The PHPT nodules distinguished by ultrasound echogenicity features showed different histopathologic components, reflected by different clinical characteristics of the patients with PHPT.

Neovascularization in carotid atherosclerotic plaques can be effectively evaluated by superb microvascular imaging (SMI): Initial experience.

The objective of this study was to investigate the correlation between the amount of blood flow in the area of neovascularization within a carotid atherosclerotic plaque by superb microvascular imaging (SMI) and the microvessel density (MVD) determined by histopathological staining. Twenty-eight carotid atherosclerotic plaques were detected by SMI in 28 patients who underwent carotid endarterectomy. SMI was graded according to the visual methods as follows: grade I: no appearance of neovascularization within the plaque; grade II: punctate neovascularization; grade III: one or two linear neovascularizations within the plaque; and grade IV: multiple (> 2) linear neovascularizations throughout the plaque. The neovascularization density was determined by the CD31 complex staining method. There was a significant correlation between the density of neovascularization in histopathologic plaques and the blood flow grade found by SMI (r = 0.788, p < 0.001). A significant difference was observed in SMI blood flow grade between the symptomatic and asymptomatic groups (χ2 = 2.634, p = 0.036). The MVD of plaques in the symptomatic group was significantly higher than that in the asymptomatic group (t = 2.530, p = 0.018). The SMI-based classification was positively correlated with plaque thickness. SMI, which is a new nonultrasound contrast-enhanced imaging method, can effectively evaluate neovascularization in carotid atherosclerotic plaques and can be used as a novel method for the clinical prediction of stroke risk.