Longitudinal ultrasound-based AI model predicts axillary lymph node response to neoadjuvant chemotherapy in breast cancer: a multicenter study.

OBJECTIVES: Developing a deep learning radiomics model from longitudinal breast ultrasound and sonographer's axillary ultrasound diagnosis for predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) in breast cancer. METHODS: Breast cancer patients undergoing NAC followed by surgery were recruited from three centers between November 2016 and December 2022. We collected ultrasound images for extracting tumor-derived radiomics and deep learning features, selecting quantitative features through various methods. Two machine learning models based on random forest were developed using pre-NAC and post-NAC features. A support vector machine integrated these data into a fusion model, evaluated via the area under the curve (AUC), decision curve analysis, and calibration curves. We compared the fusion model's performance against sonographer's diagnosis from pre-NAC and post-NAC axillary ultrasonography, referencing histological outcomes from sentinel lymph node biopsy or axillary lymph node dissection. RESULTS: In the validation cohort, the fusion model outperformed both pre-NAC (AUC: 0.899 vs. 0.786, p < 0.001) and post-NAC models (AUC: 0.899 vs. 0.853, p = 0.014), as well as the sonographer's diagnosis of ALN status on pre-NAC and post-NAC axillary ultrasonography (AUC: 0.899 vs. 0.719, p < 0.001). Decision curve analysis revealed patient benefits from the fusion model across threshold probabilities from 0.02 to 0.98. The model also enhanced sonographer's diagnostic ability, increasing accuracy from 71.9% to 79.2%. CONCLUSION: The deep learning radiomics model accurately predicted the ALN response to NAC in breast cancer. Furthermore, the model will assist sonographers to improve their diagnostic ability on ALN status before surgery. CLINICAL RELEVANCE STATEMENT: Our AI model based on pre- and post-neoadjuvant chemotherapy ultrasound can accurately predict axillary lymph node metastasis and assist sonographer's axillary diagnosis. KEY POINTS: Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound. Our AI model outperformed sonographer's visual diagnosis on axillary ultrasound. Our deep learning radiomics model can improve sonographers' diagnosis and might assist in surgical decision-making.

Development of a Novel Contrast-Enhanced Ultrasound-Based Nomogram for Superficial Lymphadenopathy Differentiation: Postvascular Phase Value.

OBJECTIVE: The aim of this study was to develop and prospectively validate a prediction model for superficial lymphadenopathy differentiation using Sonazoid contrast-enhanced ultrasound (CEUS) combined with ultrasound (US) and clinical data. METHODS: The training cohort comprised 260 retrospectively enrolled patients with 260 pathological lymph nodes imaged between January and December 2020. Two clinical US-CEUS models were created using multivariable logistic regression analysis and compared using receiver operating characteristic curve analysis: Model 1 included clinical and US characteristics; Model 2 included all confirmed predictors, including CEUS characteristics. Feature contributions were evaluated using the SHapley Additive exPlanations (SHAP) algorithm. Data from 172 patients were prospectively collected between January and May 2021 for model validation. RESULTS: Age, tumor history, long-axis diameter of lymph node, blood flow distribution, echogenic hilus, and the mean postvascular phase intensity (MPI) were identified as independent predictors for malignant lymphadenopathy. The area under the curve (AUC), sensitivity, specificity, and accuracy of MPI alone was 0.858 (95% confidence interval [CI], 0.817-0.891), 86.47%, 74.55%, and 81.2%, respectively. Model 2 had an AUC of 0.919 (95% CI, 0.879-0.949) and good calibration in training and validation cohorts. The incorporation of MPI significantly enhanced diagnostic capability (p < 0.0001 and p = 0.002 for training and validation cohorts, respectively). Decision curve analysis indicated Model 2 as the superior diagnostic tool. SHAP analysis highlighted MPI as the most pivotal feature in the diagnostic process. CONCLUSION: The employment of our straightforward prediction model has the potential to enhance clinical decision-making and mitigate the need for unwarranted biopsies.

Application of computer-aided diagnosis to predict malignancy in BI-RADS 3 breast lesions.

Purpose: To evaluate the ability of computer-aided diagnosis (CAD) system (S-Detect) to identify malignancy in ultrasound (US) -detected BI-RADS 3 breast lesions. Materials and methods: 148 patients with 148 breast lesions categorized as BI-RADS 3 were included in the study between January 2021 and September 2022. The malignancy rate, accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) were calculated. Results: In this study, 143 breast lesions were found to be benign, and 5 breast lesions were malignant (malignancy rate, 3.4 %, 95 % confidence interval (CI): 0.5-6.3). The malignancy rate rose significantly to 18.2 % (4/22, 95 % CI: 2.1-34.3) in the high-risk group with a "possibly malignant" CAD result (p = 0.017). With a "possibly benign" CAD result, the malignancy rate decreased to 0.8 % (1/126, 95 % CI: 0-2.2) in the low-risk group (p = 0.297). The AUC, sensitivity, specificity, accuracy, PPV, and NPV of the CAD system in BI-RADS 3 breast lesions were 0.837 (95 % CI: 77.7-89.6), 80.0 % (95 % CI: 73.6-86.4), 87.4 % (95 % CI: 82.0-92.7), 87.2 % (95 % CI: 81.8-92.6), 18.2 % (95 % CI: 2.1-34.3) and 99.2 % (95 % CI: 97.8-100.0), respectively. Conclusions: CAD system (S-Detect) enables radiologists to distinguish a high-risk group and a low-risk group among US-detected BI-RADS 3 breast lesions, so that patients in the low-risk group can receive follow-up without anxiety, while those in the high-risk group with a significantly increased malignancy rate should actively receive biopsy to avoid delayed diagnosis of breast cancer.

Sono-anatomy of the middle cervical sympathetic ganglion verified with pathology.

Objectives: Cervical discomfort and other symptoms may be attributable to the middle cervical sympathetic ganglion. The aim of this study was to explore the sonographic features of this ganglion in anatomical specimens and cadavers and evaluate the feasibility of its visualization using high-resolution ultrasonography. Methods: We examined three cervical sympathetic-ganglion specimens and two fresh cadavers using high-resolution ultrasound to explore the sonographic features of this ganglion. Basic imaging characteristics examined included the shape, echo intensity, and location of the ganglion. Core-needle biopsy was performed to examine the suspected middle cervical sympathetic ganglion in the two fresh cadavers and verify the accuracy of the sonographic identification via pathological examination. Results: The middle cervical sympathetic ganglion appeared on high-resolution ultrasonography as an oval-shaped hypoechoic structure, with at least one continuous hypoechoic line connected to each ending in the anatomical specimens and fresh cadavers, and it was distinctly different from the adjacent lymph nodes. Discussion: Based on an adequate understanding of both its location and sonographic features, the direct visualization of the middle cervical sympathetic ganglion using high-resolution ultrasonography is feasible.

Clinical Application of Computer-Aided Diagnosis System in Breast Ultrasound: A Prospective Multicenter Study.

OBJECTIVES: Ultrasound tends to present very high sensitivity but relatively low specificity and positive predictive value (PPV), which would result in unnecessary breast biopsies. The purpose of this study is to analyze the diagnostic performance of computer-aided diagnosis (CAD) (S-Detect) system in differentiating breast lesions and reducing unnecessary biopsies in non-university hospitals in less-developed regions of China. METHODS: The study was a prospective multicenter study from 8 hospitals. The ultrasound images, and cine, CAD analysis, and BI-RADS were recorded. The accuracy, sensitivity, specificity, PPV, negative predictive value (NPV), and area under the curve (AUC) were analyzed and compared between CAD and radiologists. The Youden Index (YI) was used to determine optimal cut-off for the number of planes to downgrade. RESULTS: A total of 491 breast lesions were included in the study. Less-experienced radiologists combined CAD was superior to less-experienced radiologists alone in AUC (0.878 vs 0.712, p < 0.001), and specificity (81.3% vs 44.6%, p < 0.001). There was no statistical difference in AUC (0.891 vs 0.878, p = 0.346), and specificity (82.3% vs 81.3%, p = 0.791) between experienced radiologists and less-experienced radiologists combined CAD. With CAD assistance, the biopsy rate of less-experienced radiologists was significantly decreased (100.0% vs 25.6%, p < 0.001), and malignant rate of biopsy was significantly increased (15.0% vs 43.9%, p < 0.001). CONCLUSIONS: CAD system can be an effective auxiliary tool in differentiating breast lesions and reducing unnecessary biopsies for radiologists from non-university hospitals in less-developed regions of China.

Evaluation of facial artery course variations, diameters, and depth by Doppler ultrasonography.

BACKGROUND: The facial artery (FA) is the main blood vessel supplying blood to the face. It is essential to understand the anatomy of FA around the nasolabial fold (NLF). This study aimed to provide the detailed anatomy and relative positioning of FA to help avoid unexpected complications in plastic surgery. METHODS: FA was observed from the inferior border of the mandible to the end of its terminal branch in 66 hemifaces of 33 patients with Doppler ultrasonography. The evaluation parameters were: (1) location, (2) diameter, (3) FA-skin depth, (4) relationship between the NLF and FA, (5) distance between the FA and significant surgical landmarks, and (6) the running layer. The FA course is classified based on the terminal branch. RESULTS: The most common FA course was Type 1, which had an angular branch as the final branch (59.1%). The most common FA-NLF relationship was that the FA was situated inferior to the NLF (50.0%). The mean FA diameter was 1.56 ± 0.36 mm at the mandibular origin, 1.40 ± 0.37 mm at the cheilion, and 1.32 ± 0.34 mm at the nasal ala. The FA diameter on the right hemiface was thicker than that on the left hemiface (p < 0.05). CONCLUSION: The FA mainly terminates in the angular branch, running in the medial NLF and in dermis and subcutaneous tissue, with a blood supply advantage in the right hemisphere. We suppose that a deep injection into periosteum around the NLF may be safer than an injection into the superficial musculoaponeurotic system (SMAS) layer.

Deep Learning-Based Computer-Aided Diagnosis for Breast Lesion Classification on Ultrasound: A Prospective Multicenter Study of Radiologists Without Breast Ultrasound Expertise.

BACKGROUND. Computer-aided diagnosis (CAD) systems for breast ultrasound interpretation have been primarily evaluated at tertiary and/or urban medical centers by radiologists with breast ultrasound expertise. OBJECTIVE. The purpose of this study was to evaluate the usefulness of deep learning-based CAD software on the diagnostic performance of radiologists without breast ultrasound expertise at secondary or rural hospitals in the differentiation of benign and malignant breast lesions measuring up to 2.0 cm on ultrasound. METHODS. This prospective study included patients scheduled to undergo biopsy or surgical resection at any of eight participating secondary or rural hospitals in China of a breast lesion classified as BI-RADS category 3-5 on prior breast ultrasound from November 2021 to September 2022. Patients underwent an additional investigational breast ultrasound, performed and interpreted by a radiologist without breast ultrasound expertise (hybrid body/breast radiologists, either who lacked breast imaging subspecialty training or for whom the number of breast ultrasounds performed annually accounted for less than 10% of all ultrasounds performed annually by the radiologist), who assigned a BI-RADS category. CAD results were used to upgrade reader-assigned BI-RADS category 3 lesions to category 4A and to downgrade reader-assigned BI-RADS category 4A lesions to category 3. Histologic results of biopsy or resection served as the reference standard. RESULTS. The study included 313 patients (mean age, 47.0 ± 14.0 years) with 313 breast lesions (102 malignant, 211 benign). Of BI-RADS category 3 lesions, 6.0% (6/100) were upgraded by CAD to category 4A, of which 16.7% (1/6) were malignant. Of category 4A lesions, 79.1% (87/110) were downgraded by CAD to category 3, of which 4.6% (4/87) were malignant. Diagnostic performance was significantly better after application of CAD, in comparison with before application of CAD, in terms of accuracy (86.6% vs 62.6%, p < .001), specificity (82.9% vs 46.0%, p < .001), and PPV (72.7% vs 46.5%, p < .001) but not significantly different in terms of sensitivity (94.1% vs 97.1%, p = .38) or NPV (96.7% vs 97.0%, p > .99). CONCLUSION. CAD significantly improved radiologists' diagnostic performance, showing particular potential to reduce the frequency of benign breast biopsies. CLINICAL IMPACT. The findings indicate the ability of CAD to improve patient care in settings with incomplete access to breast imaging expertise.

Can Short-term Follow-up with Ultrasound be Offered as an Acceptable Alternative to Immediate Biopsy or Surgery for Patients with First Ultrasound Diagnosis of BI-RADS 4A Lesions?

OBJECTIVES: To evaluate the relevant factors associated with malignancy in Breast Imaging Reporting and Data System (BI-RADS) 4A and to determine whether it was possible to establish a safe follow-up guideline for lower-risk 4A lesions. METHODS: In this retrospective study, patients categorized as BI-RADS 4A on ultrasound who underwent ultrasound-guided biopsy or/and surgery between June 2014 and April 2020 was analyzed. Classification-tree method and cox regression analysis were used to explore the possible correlation factors of malignancy. RESULTS: Among 9965 patients enrolled, 1211 (mean age, 44.3 ± 13.5 years; range, 18-91 years) patients categorized as BI-RADS 4A were eligible. The result of cox regression analysis revealed the malignant rate was only associated with patient age (hazard ratio (HR) = 1.038, p < 0.001, 95% confidence interval (CI): 1.029-1.048) and the mediolateral diameter of the lesion (HR = 1.261, p < 0.001, 95% CI: 1.159-1.372). The malignant rate for patients (≤ 36 y) with BI-RADS 4A lesions (the mediolateral diameter ≤ 0.9 cm) was 0.0% (0/72). This subgroup included fibrocystic disease and adenosis in 39 patients (54.2%), fibroadenoma in 16 (22.2%), intraductal papilloma in 8 (11.1%), inflammatory lesions in 6 (8.3%), cyst in 2 (2.8%), and hamartoma in 1 (1.4%). CONCLUSIONS: Patient age and lesion size are associated with the rate of malignancy in BI-RADS 4A. For patients with lower-risk BI-RADS 4A lesions (≤ 2% likelihood of malignancy), short-term follow-up with ultrasound may be offered as an acceptable alternative to immediate biopsy or surgery.

High-Risk Breast Lesions Diagnosed by Ultrasound-Guided Vacuum-Assisted Excision.

PURPOSE: The aim of this study was to analyze the role of ultrasound-guided vacuum-assisted excision (US-guided VAE) in the treatment of high-risk breast lesions and to evaluate the clinical and US features of the patients associated with recurrence or development of malignancy. MATERIALS AND METHODS: Between April 2010 and September 2021, 73 lesions of 73 patients underwent US-guided VAE and were diagnosed with high-risk breast lesions. The incidence of recurrence or development of malignancy for high-risk breast lesions was evaluated at follow-up period. The clinical and US features of the patients were analyzed to identify the factors affecting the recurrence or development of malignancy rate. RESULTS: Only benign phyllodes tumors on US-guided VAE showed recurrences, while other high-risk breast lesions that were atypical ductal hyperplasia (ADH), lobular neoplasia (atypical lobular hyperplasia/lobular carcinoma in situ), radial scar, and flat epithelial atypia did not show recurrences or malignant transformation. The recurrence rate of the benign phyllodes tumor was 20.8% (5/24) in a mean follow-up period of 34.3 months. The recurrence rate of benign phyllodes tumor with distance from nipple of less than 1 cm was significantly higher than that of lesions with distance from nipple of more than 1 cm (75% vs. 10%, p < 0.05). CONCLUSIONS: Benign phyllodes tumors without concurrent breast cancer could be safely followed up instead of surgical excision after US-guided VAE when the lesions were classified as BI-RADS 3 or 4A by US.

Ultrasound-Guided Vacuum-Assisted Excision to Treat Intraductal Papilloma.

BACKGROUND: To evaluate the value of ultrasound-guided vacuum-assisted excision (US-guided VAE) in the treatment of intraductal papillomas, including intraductal papillomas with atypical ductal hyperplasia (ADH), and to evaluate the lesion characteristic features affecting the local recurrence rate. MATERIALS AND METHODS: Between August 2011 and December 2020, 91 lesions of 91 patients underwent US-guided VAE and were diagnosed with intraductal papilloma with or without ADH. The recurrence rate of intraductal papilloma was evaluated on follow-up US. The lesion characteristic features were analyzed to identify the factors affecting the local recurrence rate. RESULTS: The local recurrence rate of intraductal papillomas removed by US-guided VAE was 7.7% (7/91), with the follow-up duration 12-92 months (37.4 ± 23.9 months). Of the 91 patients, five cases diagnosed as intraductal papilloma with ADH did not recur, with the follow-up time 12-47 months (26.4 ± 14.4 months). There were no malignant transformation in all 91 cases during the follow-up period. All 7 patients recurred 7-58 months (22.8 ± 19.2 months) after US-guided VAE. There were no significant differences between the non-recurrence and recurrence groups in terms of age, side, distance from nipple, lesion size, BI-RADS category, with ADH, or history of excision (p > 0.05). CONCLUSIONS: US-guided VAE is an effective method for the treatment of intraductal papilloma, including intraductal papilloma with ADH. It avoids invasive surgical excision, but regular follow-up is recommended to prevent recurrence or new onset due to multifocality. Any suspicious lesions during the follow-up should be actively treated.

Evaluation of Supratrochlear, Supraorbital and Angular Artery Course Variations and Depth by Doppler Ultrasound.

BACKGROUND: Supratrochlear (STA), supraorbital (SOA), and dorsal nasal artery (DNA) branches from the ophthalmic artery and angular artery (AA) from the facial artery are the primary suppliers of blood to the upper face. Filler injection without precise knowledge of its vascular topography poses a risk of severe complications. METHODS: Seventy-four hemifaces from 37 subjects with a median age of 25.0 (21.0, 35.0) years and a median body mass index of 21.2 (20.0, 25.4) kg/m2 underwent high-frequency ultrasound tests between March 2022 and April 2022. The bilateral location, depth, peak systolic velocity (PSV), and inner diameter (ID) of the four periorbital arteries (STA, SOA, DNA, AA) were measured. RESULTS: The average ID ranges from 0.6~1.0 mm, and the average PSV ranges from 9.2~24.9 cm/s. All arteries detected passed through the superficial subcutaneous fascia. Most subjects' STAs traveled within 1.0 to 2.0 cm from the midline (left 96.8%, right 93.8%), while SOAs were mainly concentrated within 2.0 to 4.0 cm (left 83.9%, right 81.3%). STAs were more superficial and had a larger internal ID and PSV than SOAs (p<0.001). Except for the ID of the right SOA2 being significantly larger than that of the left SOA2 (p<0.05), no dominant side was found. The depth of STAs and SOAs was moderately correlated with BMI (p<0.05), except for STA1 on the left side. The course of AAs presented a high variability. CONCLUSION: These findings emphasize that the periorbital arteries carry with it a likelihood of ocular complication risks during injection. Targeting the supraperiosteal layer in the STA area and the supramuscular layer in the SOA area of the inferior forehead during injection seems reasonable, and an area within 1.0~2.0 cm from the midline should be avoided. Additionally, the high variability of AAs will enhance the understanding of the anatomy of the facial artery terminals. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Thermal shielding performance of self-healing hydrogel in tumor thermal ablation.

Thermal ablation therapy is widely used in the surgical treatment of tumors. Clinically, normal saline is generally used as an insulator to protect adjacent tissues from local high-temperature burns caused by thermal ablation. However, the flow of saline causes fluid loss, requiring frequent injections and complex operation, which is easy to lead to complications such as secondary injury and hematoma. Here, a self-healing chitosan-PEG (CP) hydrogel was proposed as a protective medium to challenge the clinical preparations. Compared with saline and non-self-healing hydrogel F127, CP hydrogel exhibited outstanding thermal shielding performance in the thermal ablation of thyroid nodule in a Beagle dog model. The transient plane source (TPS) method is used to measure thermal properties, including thermal conductivity, thermal diffusivity and specific heat capacity. The thermal shielding mechanism and clinical advantages including operability, biodegradability, and biological safety of self-healing hydrogel are then revealed in-depth. Therefore, self-healing hydrogel can achieve much better thermal management in tumor thermal ablation.

Artificial intelligence for breast ultrasound: An adjunct tool to reduce excessive lesion biopsy.

PURPOSE: To determine whether adding an artificial intelligence (AI) system to breast ultrasound (US) can reduce unnecessary biopsies. METHODS: Conventional US and AI analyses were prospectively performed on 173 suspicious breast lesions before US-guided core needle biopsy or vacuum-assisted excision. Conventional US images were retrospectively reviewed according to the BI-RADS 2013 lexicon and categories. Two downgrading stratifications based on AI assessments were manually used to downgrade the BI-RADS category 4A lesions to category 3. Stratification A was used to downgrade if the assessments of both orthogonal sections of a lesion from AI were possibly benign. Stratification B was used to downgrade if the assessment of any of the orthogonal sections was possibly benign. The effects of AI-based diagnosis on lesions to reduce unnecessary biopsy were analyzed using histopathological results as reference standards. RESULTS: Forty-three lesions diagnosed as BI-RADS category 4A by conventional US received AI-based hypothetical downgrading. While downgrading with stratification A, 14 biopsies were correctly avoided. The biopsy rate for BI-RADS category 4A lesions decreased from 100 % to 67.4 % (P <  0.001). While downgrading with stratification B, 27 biopsies could be avoided with two malignancies missed, and the biopsy rate would decrease to 37.2 % (P <  0.05, compared with conventional US and stratification A). CONCLUSION: Adding an AI system to breast US could reduce unnecessary lesion biopsies. Downgrading stratification A was recommended for its lower misdiagnosis rate.

Distinguishing a Trichilemmal Cyst From a Pilomatricoma With Ultrasound.

OBJECTIVES: To determine whether ultrasound (US) could distinguish a trichilemmal cyst from a pilomatricoma preoperatively. METHODS: Ultrasound images of 61 pathologically proven trichilemmal cysts and 90 pathologically proven pilomatricomas were analyzed retrospectively. Two radiologists evaluated several US features. The sensitivity, specificity, Youden index, and predictive values of statistically significant US features were assessed. Parallel combined tests, serial combined tests, or both were performed to identify US features with high statistical significance. RESULTS: Results from individual US features were not satisfactory; however, serial combined tests that included absence of complete internal echogenic foci, absence of a hypoechoic rim, absence of peritumoral hyperechogenicity, and absence of vascularity showed higher diagnostic utility. The sensitivity, specificity, Youden index, positive predictive value, and negative predictive value for correctly identifying a trichilemmal cyst were 74%, 88%, 0.62, 80%, and 83%, respectively. If 1 of these 4 US features was not a match for a trichilemmal cyst, pilomatricoma was considered. CONCLUSIONS: It may be possible to distinguish trichilemmal cysts from pilomatricomas preoperatively using US. A combined test is superior to using any individual US feature.

Targeted Biopsy With Reduced Number of Cores: Optimal Sampling Scheme in Patients Undergoing Magnetic Resonance Imaging/Transrectal Ultrasound Fusion Prostate Biopsy.

The 3 Tesla (3T) magnetic resonance imaging (MRI) combined ultrasound (TRUS) targeted biopsy plus 12-core systematic biopsy (TBx + 12-SBx) was considered a reliable method for prostate cancer (PCa) diagnosis. To find another optimal sampling scheme with fewer cores and the same efficiency as TBx + 12-SBx for prostate biopsy, 113 patients who underwent five different hypothetical sampling schemes were analyzed and compared with TBx + 12-SBx. The detection rates of targeted biopsy plus 6-core lateral systematic biopsy (TBx + lateral 6-SBx) for PCa and clinically significant prostate cancer (csPCa) (99.1% and 96.4%, respectively) were higher than other schemes, and the area under the receiver operating characteristic curve of TBx + lateral 6-SBx for PCa and csPCa (0.991 and 0.990, respectively) were also significantly higher than other sampling schemes except TBx plus 6-core ipsilateral systematic biopsy (TBx + ipsilateral 6-SBx). Additionally, TBx + lateral 6-SBx had the lowest missed diagnosis rate. Thus, the TBx + lateral 6-SBx may be the optimal scheme for patients undergoing MRI/TRUS fusion prostate biopsy.

Subcapsular Injection of Ultrasonic Contrast Agent Distinguishes between Benign and Malignant Lymph Node Lesions Exhibiting Homogeneous Enhancement in Intravenous Contrast-Enhanced Ultrasound Images.

We aimed to evaluate whether subcapsular injection of ultrasonic contrast agent (UCA) can distinguish between benign and malignant lymph node (LN) lesions exhibiting homogeneous enhancement in intravenous contrast-enhanced ultrasound (CEUS) images. From November 2012 to July 2015, 32 patients with superficial lymphadenopathy exhibiting homogeneous enhancement after intravenous CEUS were enrolled. A small amount of UCA was injected into LNs using a subcapsular approach, and perfusion characteristics were recorded. Using the pathology identified via core needle biopsy as the gold standard, we calculated the sensitivity, specificity and accuracy of the technique in terms of distinguishing between benign and malignant LN lesions. Pathology revealed 23 cases of true benign and 9 cases of true malignant LN lesions; the former included 2 cases of tuberculosis and 21 cases of reactive hyperplasia, and the latter included 7 lymphomas and 2 metastases. Subcapsular CEUS diagnosed 24 benign and 8 malignant LN lesions. Most lymphomas (6 of 7, 85.7%) exhibited heterogeneous perfusion, with lymphatic tract distortion in the absence of interruption. Reactive hyperplasia LNs manifested as diffuse homogeneous or brush-like perfusion from the subcapsular region to the center, without lymphatic tract distortion. Metastatic LNs had lymphatic tract interruptions. The sensitivity, specificity, consistency and positive and negative predictive values were 77.8%, 95.6%, 90.6%, 87.5% and 91.7%, respectively. For LNs exhibiting uniform enhancement in intravenous CEUS imaging, subcapsular CEUS may help to distinguish between benign and malignant lesions. In particular, lymphatic distortion without interruption may specifically indicate a lymphoma.

The Possible Role of Color Doppler and Pulse Wave Doppler Ultrasound in the Diagnosis of Cutaneous Lymphangioma Circumscriptum.

Cutaneous lymphangioma circumscriptum (CLC) is an uncommon congenital lymphatic malformation. Its dermoscopic features have been reported, however, if blood has infiltrated the lacunas, a pink hue overwhelms the lacunar structures, rendering dermoscopic features indistinguishable. In addition, dermoscopy cannot assess the subcutaneous extent of the lesion before surgery. The high-frequency array transducer Sonography with a high-frequency transducer is excellent in its resolution to evaluate skin lesions and is unaffected by infiltration of blood. Here, the authors report the use of ultrasound (color Doppler and pulse wave Doppler) for the diagnosis and management of CLC.An 18-year-old man presented 10 years previously with an asymptomatic 0.5 × 0.7 cm cluster of dark reddish vesicular lesions on his buttock. The lesions had recently increased in size and number. There was associated pachyderma. The lesions were hyperechoic and well defined on grayscale ultrasound and hypervascular on color Doppler ultrasound. Cluster cystics of lymphatic spaces were found throughout the whole dermis, especially in the papillary dermis. The lymphatic channels extended downwards to the reticular dermis and the superficial layer of the subcutaneous tissue. The pathological findings revealed lymphangiomas invading the subcutaneous tissue. The flat endothelial cells were partly positive for D2-40, which is a marker of lymphatic endothelial cells. Ultrasound was able to delineate the margins of the lesions. Diagnosis of CLC using preoperative color Doppler and pulse wave Doppler could reduce unnecessary repeated pre- and postoperative biopsies.

Automatic Identification of Breast Ultrasound Image Based on Supervised Block-Based Region Segmentation Algorithm and Features Combination Migration Deep Learning Model.

Breast cancer is a high-incidence type of cancer for women. Early diagnosis plays a crucial role in the successful treatment of the disease and the effective reduction of deaths. In this paper, deep learning technology combined with ultrasound imaging diagnosis was used to identify and determine whether the tumors were benign or malignant. First, the tumor regions were segmented from the breast ultrasound (BUS) images using the supervised block-based region segmentation algorithm. Then, a VGG-19 network pretrained on the ImageNet dataset was applied to the segmented BUS images to predict whether the breast tumor was benign or malignant. The benchmark data for bio-validation were obtained from 141 patients with 199 breast tumors, including 69 cases of malignancy and 130 cases of benign tumors. The experiment showed that the accuracy of the supervised block-based region segmentation algorithm was almost the same as that of manual segmentation; therefore, it can replace manual work. The diagnostic effect of the combination feature model established based on the depth feature of the B-mode ultrasonic imaging and strain elastography was better than that of the model established based on these two images alone. The correct recognition rate was 92.95%, and the AUC was 0.98 for the combination feature model.

[Values of Longitudinal and Transverse Plane Ratios in Predicting the Risk of Malignant Thyroid Nodules].

Objective To compare the predictive value of different ratio measurement in predicting the risk of malignant thyroid nodules and to determine the best value of ratio in diagnosing thyroid nodules.Methods The clinical data of 342 thyroid nodules diagnosed by ultrasonography and confirmed by histology in our hospital from January 2018 to August 2018 were analyzed.The ratio of nodules in different sections,including longitudinal plane ratio(A/TL)and transverse plane ratio(A/TC),was obtained through the maximum head-foot diameter(TL),the maximum left-right diameter(TC),and the anterior-posterior diameter(A)of transverse section measured by ultrasonography.The correlation of histological diagnosis of benign or malignant nodule with longitudinal ratio and transverse ratio were analyzed.Results The A/TC and A/TL of malignant nodules were 1.00(0.83,1.17)and 0.81(0.65,1.00),respectively,which were significantly higher than those of benign nodules [0.81(0.67,0.93)(Z=-6.567,P=0.000)and 0.63(0.52,0.75)(Z=-7.239,P=0.000)].The area under the ROC curve of A/TC and A/TL was 0.734 and 0.712,respectively,showing no significant difference(area difference:0.0210,standard error:0.0213,95% CI:-0.0207-0.0627,Z=0.987,P=0.3235).The threshold values of A/TC and A/TL for predicting malignant nodules were 0.784 161 5 and 0.985 714 5,respectively.Conclusions Both A/TL and A/TC has similar diagnostic value in predicting the risk of malignant nodules.The best cutoff value of the above two ratios are 0.78 and 0.99 respectively.