Journal of Ultrasound in Medicine最新文献

This systematic review aimed to identify studies that have created ultrasound-able models for resident procedural training by means of 3D-printing techniques and examine their tissue specific properties. There were 456 articles identified from 3 databases, of which, 35 studies were assessed for eligibility, and 11 total studies were included. All qualitative studies showed improvements in procedural skills and 89% of the quantitative studies showed significant results. Studies that documented modeling price showed a 90% reduction in fabrication cost compared to commercial models. Three-dimensional-printed, ultrasound-able models have the potential to provide trainees with low-cost, high-fidelity training opportunities.

Objectives: This study aimed to develop a nomogram for predicting intrauterine pregnancy after an in vitro frozen embryo transfer cycle using endometrial ultrasound radiomics.

Methods: A total of 211 patients who underwent ultrasound examination on the day of endometrial transformation before the frozen embryo transfer cycle were enrolled. The patients were divided into an intrauterine pregnancy group and a pregnancy failure group based on ultrasound results. Clinical characteristics and radiomic features were analyzed using univariate and multivariate logistic regression analyses. A nomogram prediction model was established based on radiomic signatures and significant clinical factors. The model's robustness was assessed in training and external validation cohorts.

Results: Nine radiomic features were selected using least absolute shrinkage and selection operator (LASSO), and the radiomics score (Rad-score) was calculated as the sum of each feature multiplied by the nonzero coefficient from LASSO. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve based on the Rad-score was 0.72, 0.65, and 0.69 in the training, validation, and combined cohorts, respectively. To improve diagnostic efficiency, the Rad-score was further integrated with clinical factors to form a novel predictive nomogram. The results indicated that the AUC increased to 0.81, 0.67, and 0.77 in the training, validation, and combined cohorts, respectively. Decision curve analysis showed that the radiomics nomogram was clinically useful.

Conclusion: The radiomics and clinical predictive nomogram can effectively predict intrauterine pregnancy after in vitro frozen embryo transfer and can be further applied in clinical strategy.

Objectives: Advances in diagnosing carpal tunnel syndrome (CTS) using ultrasonography (US) and artificial intelligence (AI) aim to replace nerve conduction studies. However, a method for accurate severity diagnosis remains unachieved. We explored the potential of comprehensive video data formats for constructing an effective model for diagnosing CTS severity.

Methods: We studied 75 individuals (52 with CTS) from 2019 to 2022, categorizing them into 3 groups based on disease severity. We recorded 132 US videos of carpal tunnel during finger movement. Features of the median nerve (MN) were extracted from automatically segmented US video frames, from which 3 datasets were created: a comprehensive video dataset with full information, a key metrics dataset, and an initial frame dataset with the least information. We compared the accuracy of machine learning algorithms for classifying CTS severity into 3 groups across these datasets using 63-fold cross-validation.

Results: The cross-sectional area of the MN correlated with severity (P < .05) but MN displacement did not. The algorithm using the comprehensive video dataset exhibited the highest sensitivity (1.00) and accuracy (0.75).

Conclusions: Our study demonstrated that utilizing comprehensive video data enables a more accurate US-based diagnosis of CTS severity. This underscores the value of capturing the patterns of MN deformation and movement, which cannot be captured by representative metrics such as medians or maximums. By further developing an AI model based on our findings, a simpler and painless method for assessing CTS severity can be achieved.

Objective: This study aims to describe the ultrasound characteristics of keratoacanthoma (KA), providing valuable insights for non-invasive diagnosis and differentiation from well-differentiated cutaneous squamous cell carcinoma (wcSCC).

Methods: Ultrasound characteristics of 16 KA and 13 wcSCC conformed by surgical pathology were retrospective analyzed.

Results: KA patients were younger (mean age 63.13 years) compared with wcSCC patients (mean age 76.23 years). Ultrasound characteristics revealed that KA lesions were generally smaller, more frequently domed-shaped (87.50 vs 38.46%), exophytic (93.75 vs 30.77%), and well-defined (93.75 vs 53.85%) compared with wcSCC. Both lesion types predominantly showed hypoechoic internal echoes and inhomogeneous echotexture. The prevalence of hyperechoic superficial area was notably high in both groups (93.75 vs 84.62%), precluding the reliable use of this feature as a discriminatory marker between these two distinct neoplastic entities. KA lesions were mostly confined to the epidermis and superficial dermis (87.50%), while wcSCC cases frequently infiltrated into the subcutaneous fat layer (84.62%). Color Doppler imaging demonstrated higher vascularity in wcSCC lesions, with 61.5% showing Grade 3 flow, compared with KA lesions, where 62.5% exhibited Grade 2 flow.

Conclusions: High-frequency ultrasound reveals distinct ultrasound characteristics differentiating KA from wcSCC, offering a promising non-invasive tool for preliminary diagnosis and treatment planning.

Objective: We sought to assess whether the presence and extent of lung ultrasound (LUS) findings were associated with asthma exacerbation severity in children.

Methods: We enrolled a convenience sample of patients aged 5-18 years presenting with acute asthma exacerbation to a tertiary care pediatric emergency department. Severity of an asthma exacerbation (mild, moderate, severe) was assessed within 1 hour of the LUS using the Hospital Asthma Severity Score, a validated asthma assessment tool. LUS was performed by trained pediatric emergency providers. The presence of LUS findings (B-lines, consolidations, pleural effusion, and pleural line abnormalities) was assessed using a standardized criterion based on consensus guidelines.

Results: A total of 111 patients with a median age of 8 years (interquartile range 6-12) were enrolled. LUS was positive in 57% of patients. Pleural line abnormalities were observed in 34%, B-lines in 29%, consolidations <1 cm in 24%, and consolidations ≥1 cm in 7%. Patients with moderate and severe asthma exacerbations were more likely to have any B-lines (31% and 43%, respectively) than patients with mild exacerbations (12%; P = .021); however, the presence of ≥3 B-lines or confluent B-lines did not differ across severity groups. The presence of other findings did not differ based on asthma severity.

Conclusions: LUS findings are observed in a substantial portion of children presenting with asthma exacerbations. B-lines were the only LUS finding significantly associated with asthma severity, while lung consolidations <1 cm and >1 cm were not correlated with severity. These findings provide valuable information for the diagnostic use of LUS in pediatric patients with asthma exacerbation.

Objectives: To evaluate the value of radiomics based on ultrasonography in differentiating follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA) and construct a tool for preoperative noninvasive predicting FTC and FTA.

Methods: The clinical data and ultrasound images of 389 patients diagnosed with FTC or FTA postoperatively were retrospectively analyzed at 3 institutions from January 2017 to December 2023. Patients in our hospital were randomly assigned in a 7:3 ratio to training cohort and validation cohort. External test cohort consisted of data collected from other 2 hospitals. Radiomics features were used to develop models based on different machine learning classifiers. A combined model was developed combining radiomics features with clinical characteristics and a nomogram was depicted. The performance of the models was assessed by area under the receiver operating characteristic curve (AUC), calibration curve and decision curve.

Results: Radiomics model based on random forest showed best performance in discriminating FTC and FTA, with AUCs 0.880 (95% confidence interval [CI]: 0.8290-0.9308), 0.871 (95% CI: 0.7690-0.9734), and 0.821 (95% CI: 0.7036-0.9389) in training, validation, and test cohort, respectively. The combined model presented better efficacy comparing with clinical model and radiomics model, with AUCs 0.883 (95% CI: 0.8359-0.9295), 0.874 (95% CI: 0.7873-0.9615), and 0.876 (0.7809-0.9714) in training, validation, and test cohort, respectively. The calibration curves suggested good consistency and decision curves showed the highest overall clinical benefit for the combined model.

Conclusions: Ultrasound radiomics model based on random forest is feasible to differentiate FTC and FTA, and the combined model is an intuitively noninvasive tool for FTC and FTA preoperative identification.

Objectives: The aim of this study was to use quantitative ultrasound (QUS) parameters to assess the muscle mass and quality in patients with lymphoma. Additionally, the study aimed to investigate the relationship between these QUS parameters and post-chemotherapy myelosuppression.

Methods: The study cohort comprised 202 patients diagnosed with lymphoma (105 males, 97 females; mean age 57.0 ± 14.9 years). The skeletal muscle index (SMI) and mean skeletal muscle density (SMD) were measured on CT and used as the gold standards to evaluate low skeletal muscle mass and quality. The muscle thickness (MT) of the forearm flexor and extensor muscles was measured in both the relaxed and contracted states, while the normalized non-linear parameter B/A (MusQBOX.NLP) and normalized mean intensity (MusQBOX.NMI) were extracted from retained ultrasound radiofrequency signals. The correlations between the QUS parameters and grip strength were assessed. Models were constructed using these QUS parameters to predict low SMI and SMD, and to evaluate whether these factors were independently associated with post-chemotherapy myelosuppression.

Results: The MT in both the relaxed and contracted states exhibited the strongest correlations with grip strength, while the MusQBOX.NLP and MusQBOX.NMI were only weakly correlated with grip strength. Models incorporating QUS parameters to predict low SMI and SMD achieved high area under the receiver operating characteristic curve values. The MT, MusQBOX.NLP, and MusQBOX.NMI were independent factors associated with post-chemotherapy myelosuppression.

Conclusions: QUS parameters show promise in characterizing muscle strength, mass, and quality. They are also independent factors influencing post-chemotherapy myelosuppression.

Objectives: The aim of the present study was to assess the reliability of aponeurosis and muscle thickness of the hamstrings using ultrasound (US).

Methods: US images were captured from the semitendinosus (ST) and biceps femoris long head (BFlh) of 30 individuals (15 females), undergoing two testing sessions with a 24-hour interval. Measurements were taken at six sites along the thigh at two knee angles (0° = full extension and 90°) in prone position. Aponeurosis and muscle thickness across the entire length of ST and BFlh were evaluated using computational image segmentation which generated ~360 data points per participant.

Results: The intraclass correlation coefficients ranged from 0.937 to 0.998 while the standard error of measurement varied from 0.88 to 2.72% for superficial aponeurosis, from 1.41 to 2.29% for deep aponeurosis, and from 1.50 to 4.22% for muscle thickness. The minimal detectable change ranged from 2.44 to 7.56% for the superficial aponeurosis, from 3.57 to 6.27% for deep aponeurosis, and from 4.17 to 11.70% for BF and ST muscle thickness.

Conclusions: Evaluation of hamstring aponeurosis and muscle thickness measurements at rest displayed very high reliability and, hence, such measurements can be used to diagnose changes in thickness due to injury or exercise interventions.

Management of suspected large for gestational age (LGA) fetuses remains unclear because ultrasound-estimated fetal weight (EFW) is not accurate. This was a systematic review of observational studies on fetal soft tissues measurements used alone or in combination to create a new EFW formula, to improve the screening for LGA fetuses. Studies were scored using a predefined set of independently agreed methodological criteria and an overall quality score was assigned for study design, statistical analysis, and reporting methods. There is a need to standardize methodologies for soft fetal tissue measurements. We propose a set of suggestions for this purpose.