OBJECTIVE: To explore the prenatal and postnatal phenotypes of 22q11.2 microdeletion syndrome (22q11.2DS) and enhance clinical understanding of this condition. METHODS: Data were collected from 86 fetuses diagnosed with 22q11.2DS at four prenatal diagnostic centers across China between January 2014 and August 2025. Prenatal imaging findings, pregnancy outcomes, and postnatal conditions were analyzed. RESULTS: Among the 86 fetuses, complete ultrasound data were available for 65 cases. Cardiovascular abnormalities were observed in 42 cases, thymic hypoplasia or aplasia in 7 cases, urinary system anomalies in 6 cases, nuchal translucency (NT) thickening in 7 cases, butterfly vertebrae, clubfoot, omphalocele and diaphragmatic hernia in 1 case each, cleft lip and palate in 2 cases, and ultrasound soft markers in 13 cases. The parents of 9 fetuses opted to continue with the pregnancy. Among these, 6 showed no significant ultrasound abnormalities and no related phenotypes postnatally, while the remaining 3 exhibited ultrasound anomalies with postnatal manifestations including developmental delay, immunodeficiency, and cardiac defects. CONCLUSION Fetuses with 22q11.2DS may exhibit various ultrasound abnormalities in multiple systems before and after birth. In addition to cardiovascular anomalies, they may also present with thymic hypoplasia or aplasia, thickened NT, and urinary abnormalities. Fetuses with thickened NT or thymic anomalies should be closely monitored, and thymic assessment should be included in routine prenatal imaging evaluations. For fetuses with 22q11.2DS who show no ultrasound abnormalities, the risk of developing severe phenotypes after birth is relatively low, but occult palate clefts and psychiatric disorders cannot be ruled out. Due to limitations in sample size and follow-up duration, above conclusions require further validation through large-scale prospective studies.
Humans ; Female ; Pregnancy ; Ultrasonography, Prenatal ; DiGeorge Syndrome/genetics* ; Adult ; Male ; Follow-Up Studies ; Fetus/diagnostic imaging* ; Phenotype ; Infant, Newborn

OBJECTIVE: To investigate the genetic etiology of a fetus diagnosed with Mandibulofacial dysostosis with microcephaly (MFDM). METHODS: A fetus that underwent prenatal diagnosis at Beijing Obstetrics and Gynecology Hospital, Capital Medical University, on May 19, 2025 was selected for analysis. Results of fetal ultrasound findings, chromosomal karyotyping, copy number variation sequencing (CNV-seq), and whole-exome sequencing (WES) were collected. Sanger sequencing was performed for familial validation of the pathogenic variant. The Human Protein Atlas (HPA), STRING, and Simple ClinVar databases were queried to characterize the biological features of the candidate gene. Three-dimensional structures of the wild-type and variant proteins were modeled and analyzed, and the evolutionary conservation of the affected amino acid was assessed using UGENE. Prenatal phenotypes associated with EFTUD2 variants were summarized through a review of the literature. This study was approved by the Ethics Committee of Beijing Obstetrics and Gynecology Hospital, Capital Medical University (Ethics No.: 2025-KY-029-01). RESULTS: At 23⁺² weeks of gestation, ultrasound examination revealed bilateral microtia with low-set ears, mild micrognathia with a reduced mandibular-facial angle, a single umbilical artery, a slightly narrow aortic diameter, and trivial mitral regurgitation. Amniotic fluid karyotyping and CNV-seq showed no abnormalities. WES identified a de novo, previously unreported EFTUD2 variant, c.698dupA (p.V235Gfs*27), in the fetus. This frameshift variant is predicted to alter the structural integrity of the EFTUD2 protein. Literature review indicated that micrognathia and microtia or low-set ears are the most common sonographic features in fetuses with EFTUD2 variants, while secondary findings may include abnormal stomach bubble, cleft palate, single umbilical artery, gastrointestinal atresia, polyhydramnios, and reduced aortic diameter. CONCLUSION The EFTUD2: c.698dupA (p.V235Gfs*27) variant is likely the genetic cause underlying MFDM in this fetus.
Humans ; Mandibulofacial Dysostosis/diagnostic imaging* ; Microcephaly/diagnostic imaging* ; Female ; Pregnancy ; Ribonucleoprotein, U5 Small Nuclear/chemistry* ; Peptide Elongation Factors/chemistry* ; Fetus ; DNA Copy Number Variations/genetics* ; Adult ; Ultrasonography, Prenatal

The accurate segmentation of breast ultrasound images is an important precondition for the lesion determination. The existing segmentation approaches embrace massive parameters, sluggish inference speed, and huge memory consumption. To tackle this problem, we propose T ²KD Attention U-Net (dual-Teacher Knowledge Distillation Attention U-Net), a lightweight semantic segmentation method combined double-path joint distillation in breast ultrasound images. Primarily, we designed two teacher models to learn the fine-grained features from each class of images according to different feature representation and semantic information of benign and malignant breast lesions. Then we leveraged the joint distillation to train a lightweight student model. Finally, we constructed a novel weight balance loss to focus on the semantic feature of small objection, solving the unbalance problem of tumor and background. Specifically, the extensive experiments conducted on Dataset BUSI and Dataset B demonstrated that the T ²KD Attention U-Net outperformed various knowledge distillation counterparts. Concretely, the accuracy, recall, precision, Dice, and mIoU of proposed method were 95.26%, 86.23%, 85.09%, 83.59%and 77.78% on Dataset BUSI, respectively. And these performance indexes were 97.95%, 92.80%, 88.33%, 88.40% and 82.42% on Dataset B, respectively. Compared with other models, the performance of this model was significantly improved. Meanwhile, compared with the teacher model, the number, size, and complexity of student model were significantly reduced (2.2×10 ⁶ vs. 106.1×10 ⁶, 8.4 MB vs. 414 MB, 16.59 GFLOPs vs. 205.98 GFLOPs, respectively). Indeedy, the proposed model guarantees the performances while greatly decreasing the amount of computation, which provides a new method for the deployment of clinical medical scenarios.
Humans ; Breast Neoplasms/diagnostic imaging* ; Female ; Ultrasonography, Mammary/methods* ; Image Processing, Computer-Assisted/methods* ; Algorithms ; Neural Networks, Computer ; Breast/diagnostic imaging*

Medical cross-modal retrieval aims to achieve semantic similarity search between different modalities of medical cases, such as quickly locating relevant ultrasound images through ultrasound reports, or using ultrasound images to retrieve matching reports. However, existing medical cross-modal hash retrieval methods face significant challenges, including semantic and visual differences between modalities and the scalability issues of hash algorithms in handling large-scale data. To address these challenges, this paper proposes a Medical image Semantic Alignment Cross-modal Hashing based on Transformer (MSACH). The algorithm employed a segmented training strategy, combining modality feature extraction and hash function learning, effectively extracting low-dimensional features containing important semantic information. A Transformer encoder was used for cross-modal semantic learning. By introducing manifold similarity constraints, balance constraints, and a linear classification network constraint, the algorithm enhanced the discriminability of the hash codes. Experimental results demonstrated that the MSACH algorithm improved the mean average precision (MAP) by 11.8% and 12.8% on two datasets compared to traditional methods. The algorithm exhibits outstanding performance in enhancing retrieval accuracy and handling large-scale medical data, showing promising potential for practical applications.
Algorithms ; Semantics ; Humans ; Ultrasonography ; Information Storage and Retrieval/methods* ; Image Processing, Computer-Assisted/methods*

To address the high computational complexity of the Transformer in the segmentation of ultrasound thyroid nodules and the loss of image details or omission of key spatial information caused by traditional image sampling techniques when dealing with high-resolution, complex texture or uneven density two-dimensional ultrasound images, this paper proposes a thyroid nodule segmentation method that integrates the receiving weighted key-value (RWKV) architecture and spherical geometry feature (SGF) sampling technology. This method effectively captures the details of adjacent regions through two-dimensional offset prediction and pixel-level sampling position adjustment, achieving precise segmentation. Additionally, this study introduces a patch attention module (PAM) to optimize the decoder feature map using a regional cross-attention mechanism, enabling it to focus more precisely on the high-resolution features of the encoder. Experiments on the thyroid nodule segmentation dataset (TN3K) and the digital database for thyroid images (DDTI) show that the proposed method achieves dice similarity coefficients (DSC) of 87.24% and 80.79% respectively, outperforming existing models while maintaining a lower computational complexity. This approach may provide an efficient solution for the precise segmentation of thyroid nodules.
Thyroid Nodule/diagnostic imaging* ; Humans ; Ultrasonography/methods* ; Algorithms ; Image Processing, Computer-Assisted/methods* ; Thyroid Gland/diagnostic imaging*

Thyroid nodules are a common endocrine disorder, and their early detection and accurate diagnosis are crucial for the prevention of thyroid cancer. However, the highly heterogeneous morphology and boundaries of thyroid nodules pose significant challenges to their precise identification and classification. Traditional diagnostic approaches rely heavily on physicians' experience, which increases the risk of misdiagnosis and missed diagnoses. With the rapid advancement of computer-aided diagnosis (CAD) technologies, applying deep learning algorithms to the analysis of thyroid nodule ultrasound images has shown great potential. This paper reviews the latest research progress on deep learning-based CAD methods for thyroid nodules, with a focus on their applications in image preprocessing, segmentation and classification. The advantages and limitations of current techniques are analyzed, and potential future directions are discussed. This review aims to highlight the potential of deep learning in thyroid nodule diagnosis and to provide a foundation for selecting feasible pathways for future clinical applications.
Humans ; Thyroid Nodule/diagnostic imaging* ; Deep Learning ; Ultrasonography/methods* ; Diagnosis, Computer-Assisted/methods* ; Algorithms ; Thyroid Neoplasms/diagnostic imaging* ; Image Processing, Computer-Assisted/methods*

INTRODUCTION

Left ventricular remodeling is an adaptive response to aging and cumulative exposure to risk factors for cardiovascular disease. With the rising prevalence of cardiovascular disease in the younger population, a timely risk identification is warranted.

This study aims to determine the prevalence of LV remodeling in young patients using transthoracic echocardiography, and to determine the association of their clinical profiles with LV remodeling.

A retrospective cross-sectional design was utilized. Descriptive statistics using frequency and percentages was employed to describe the clinical profiles of patients; chi-square tests to assess the significance of associations of patients’ clinical profile with the LV remodeling patterns; and One-way Analysis of Variance (ANOVA) followed by post-hoc tests for significant F values to provide insights into the differences of means across various cardiac parameters.

Our study included 208 patients who had thoracic echocardiography from January 2021 to December 2022 at our institution. Majority were aged 31-40 years (64.4%), female (54.8%), and under the BMI classification of obese (52.9%). There were varying percentages per comorbidity, with hypertension (HPN) being the most prevalent. The presence of symptoms was also examined; however, it was not statistically significant. Age, sex, comorbidities, and presence of symptoms were not significantly associated with LV remodeling while BMI classification demonstrated a significant association (χ2 = 25.457, p = 0.003**). In this study, LV remodeling is already prevalent at 32.21% in young adults aged 18-40 years old. BMI classification demonstrated a significant association with LV remodeling pattern. Obesity showed a significant association with concentric remodeling pattern.

We found that LV remodeling is already prevalent in young adults aged 18-40 years old. BMI classification demonstrated a significant association with LV remodeling pattern. Obesity showed a significant association with concentric remodeling pattern.

Objective:To describe a low-cost, reproducible phantom model for training medical practitioners in ultrasound-guided ethanol ablation (EA) of a cystic thyroid nodule.

Methods:The model of cyst contents was created using a mixture of coffee powder, cornstarch and water to mimic colloidal contents. This was injected into the finger of a cut surgical glove secured with transparent tape to serve as an inflatable capsule and placed inside a chicken breast. This setup allows practitioners to perform key ultrasound-guided ethanol ablation techniques including spinal needle insertion, cyst aspiration, saline flushing, re-aspiration and ethanol injection.

Results:The phantom model was assembled for PhP 150.30 per unit and took approximately 5 minutes to construct. This model was demonstrated to be a cost-effective and simple method for enabling specialists to practice and enhance their skills in ultrasound-guided ethanol ablation of a cystic thyroid nodule.

Conclusion:The described phantom model provides an accessible and practical training tool for healthcare providers to gain proficiency in ultrasound-guided ethanol ablation of a cystic thyroid nodule in a safe and controlled setting prior to actual patient handling.

OBJECTIVE: To investigate the accuracy of color Doppler ultrasound (CDU) and CT angiography (CTA) in the preoperative evaluation of perforator vessels in free posterior interosseous artery perforator (PIAP) flaps. METHODS: Between January 2020 and December 2023, 19 patients with hand skin and soft tissue defects caused by trauma were admitted. There were 11 males and 8 females, with a median age of 45 years (range, 26-54 years). The interval between injury and admission was 5-11 days (mean, 7.2 days). The skin and soft tissue defects were located on the dorsum of the hand in 8 cases and on the fingers in 11 cases. The size of defect ranged from 4.0 cm×2.5 cm to 7.5 cm×3.5 cm. After locating the perforator vessels through CDU and CTA before operation, the free PIAP flaps were designed to repair hand defects, with the size of 4.5 cm×3.0 cm-7.5 cm×4.0 cm. The defects of donor sites were directly sutured. The number and diameter of perforator vessels in the posterior interosseous artery detected by CDU and CTA were compared. The differences in localization of perforator vessels using CDU and CTA and their clinical effects were also compared to calculate the accuracy and recognition rate. During follow-up, the survival of the skin flap was observed, and the Vancouver scar scale (VSS) score was used to evaluate the healing of the donor site, while the visual analogue scale (VAS) score was used to evaluate the patient's satisfaction with the appearance of the skin flap. RESULTS: The number and the diameter of PIAP vessels was 5.8±1.2 and (0.62±0.08) mm assessed by CDU and 5.2±1.0 and (0.60±0.07) mm by CTA, showing no significant difference between the two methods ( P>0.05). The number, course, and distribution of perforator vessels of the PIAP vessels observed during operation were basically consistent with those detected by preoperative CDU and CTA. Compared with intraoperative observation results, the recognition rates of dominant perforating vessels by CDU and CTA were 95.0% (18/19) and 89.5% (17/19), respectively, and the accuracy rates were 100% (19/19) and 84.2% (16/19), with no significant difference between the two methods ( P>0.05). All flaps survived after operation, and all wounds and incisions at donor sites healed by first intention. All patients were followed up 6-13 months (mean, 8.2 months). At last follow-up, the skin flaps had elasticity and soft texture，with the patient satisfaction VAS score of 9.2±0.8. The donor sites had no obvious scar hyperplasia with the VSS score of 11.7±0.9. CONCLUSION CDU and CTA accurately identify the dominant perforator vessels and provide reliable information for vessel localization, facilitating precise flap harvesting and minimizing donor site injury. However, CDU offers superior visualization of distal end of perforator vessels in the forearm compared to CTA.
Humans ; Female ; Male ; Adult ; Perforator Flap/blood supply* ; Middle Aged ; Ultrasonography, Doppler, Color/methods* ; Computed Tomography Angiography/methods* ; Soft Tissue Injuries/diagnostic imaging* ; Hand Injuries/diagnostic imaging* ; Plastic Surgery Procedures/methods* ; Hand/surgery* ; Preoperative Care ; Arteries/diagnostic imaging*

OBJECTIVE: To evaluate the analgesic efficacy of ultrasound-guided high fascia iliaca compartment block (HFICB) in managing tourniquet-related pain following total knee arthroplasty (TKA). METHODS: A prospective randomized controlled trial was conducted involving 84 patients with severe knee osteoarthritis or rheumatoid arthritis who underwent unilateral TKA between March 2024 and December 2024. Patients were randomly assigned to two groups ( n=42) using a random number table. In the trial group, ultrasound-guided HFICB was performed preoperatively, with 0.2% ropivacaine injected into the fascia iliaca compartment. No intervention was administered in the control group. Baseline characteristics, including gender, age, surgical side, body mass index, and preoperative visual analogue scale (VAS) scores at rest and during movement, showed no significant difference between the two groups ( P>0.05). In both groups, a tourniquet was applied after osteotomy and before pulsed lavage, and removed after the closure of the first layer of the joint capsule. Postoperative assessments were conducted at 6, 12, 24, and 48 hours, including VAS scores at the tourniquet site (at rest and during movement), Bromage motor block scores, Ramsay sedation scores, and Bruggrmann comfort scale (BCS) scores to evaluate patient comfort. Additionally, the average tramadol consumption and incidence of nausea and vomiting within 48 hours postoperatively were recorded and compared. RESULTS: In the trial group and control group, VAS scores during movement at the tourniquet site significantly improved at all postoperative time points compared to preoperative levels ( P<0.05). VAS scores at rest increased transiently at 6 hours after operation in both groups, and then gradually decreased to the preoperative level. Except that there was no significant difference at 48 hours after operation in the trial group ( P>0.05), there were significant differences at other time points of two groups compared to preoperative score ( P<0.05). Except for VAS score at rest at 6 hours, VAS score during movement at 48 hours, and BCS comfort score at 48 hours ( P>0.05), the trial group showed significantly better outcomes than the control group in terms of VAS score at rest, VAS score during movement, Ramsay sedation scores, and BCS comfort scores at all other time points ( P<0.05). No significant difference was found in Bromage motor block scores between the groups ( P>0.05). Tramadol was used in 3 patients in the trial group and 7 patients in the control group within 48 hours after operation, the dosage was (133.30±14.19) mg and (172.40±22.29) mg, showing significant difference ( P<0.05). Nausea and vomiting occurred in 4 patients (9.5%) in the trial group and 3 patients (7.1%) in the control group, with no significant difference in incidence between groups ( P>0.05). CONCLUSION Ultrasound-guided HFICB provides effective analgesia for tourniquet-related pain following TKA, facilitates early postoperative functional recovery of the knee joint, and may serve as a valuable clinical option for postoperative pain management in TKA patients.
Humans ; Arthroplasty, Replacement, Knee/adverse effects* ; Nerve Block/methods* ; Male ; Female ; Pain, Postoperative/etiology* ; Tourniquets/adverse effects* ; Prospective Studies ; Middle Aged ; Ropivacaine/administration & dosage* ; Aged ; Ultrasonography, Interventional ; Anesthetics, Local/administration & dosage* ; Pain Measurement ; Fascia ; Osteoarthritis, Knee/surgery* ; Treatment Outcome ; Arthritis, Rheumatoid/surgery*