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Objective: Ductal carcinoma in situ (DCIS) of the breast has a wide disease spectrum with risks of progression to invasive cancer linked to pathological factors. High-grade histology, large tumor volume, and comedonecrosis are adverse prognostic factors. This study explores the correlation between conventional ultrasound (Con-US) and shears wave elastography (SWE) features with DCIS prognostic factors and evaluates their predictive efficacy. Methods: A retrospective analysis was conducted on clinical data, Con-US, and SWE imaging features of 83 DCIS patients who underwent surgical resection between June 2018 and December 2022. Binary logistic regression analysis was performed to explore the relationship between sonogram indices and pathological prognostic factors. Results: The results revealed that microcalcification observed on Con-US was an independent risk factor for high-grade DCIS and comedonecrosis [odds ratio (OR): 5.316 and 4.512]. In SWE analysis, the Emax value was significantly different between the non-high-grade and high-grade DCIS groups(P = 0.006), with an Emax value greater than 75.03 kPa identified as an independent risk factor for high-grade DCIS [OR:1.022, the area under the curve (AUC): 0.682, 95% confidence interval (CI): 0.555–0.808]. Additionally, the Ecolor, Emax, Emean, and Emean SD values were statistically different between the groups with and without comedonecrosis (P = 0.049, 0.006, 0.012, 0.022), with an Emean value exceeding 30.45 kPa identified as an independent risk factor for comedonecrosis (OR:1.025, AUC:0.708, 95% CI:0.562–0.854). Furthermore, combining microcalcification on Con-US with specific SWE indicators demonstrated an improved predictive specificity for high-grade DCIS and comedonecrosis (0.902 and 0.889, respectively). No significant difference was found in other indexes on SWE. Conclusions: The microcalcification signs on Con-US, Emax and Emean values on SWE analysis are associated with the high nuclear grade and comedonecrosis of DCIS, the combination of Con-US and SWE can improve the predictive specificity of DCIS-related prognostic factors. [ABSTRACT FROM AUTHOR]

OBJECTIVE: This study aimed to evaluate the clinical characteristics and features of conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) in differentiating between renal urothelial carcinomas (RUC) and endophytic clear cell renal cell carcinomas (EccRCC). METHODS: A total of 72 RUCs and 120 EccRCCs confirmed by pathology were assessed retrospectively. Both CUS and CEUS were performed within 4 weeks before the surgery. Logistic regression analyses were used to select statistically significant variables of clinical, CUS, and CEUS features for the differentiation of RUC and EccRCC. Sensitivity (SEN), specificity (SPE), and the area under the receiver-operating characteristic curve (AUC) were assessed for diagnostic performance. Inter- and intra-observer agreements of CUS and CEUS features were evaluated using the intra-class correlation coefficient(ICC). RESULTS: Multiple logistic regression analysis demonstrated that clinical (age >50 years old and hematuria), CUS (size <4.0 cm, hypo-echogenicity, irregular shape, hydronephrosis) and CEUS (absence of non-enhancement area, iso- /hypo-enhancement in cortical phase and absence of rim-like enhancement) features were independent factors for RUC diagnosis. When combining clinical characters with CUS and CEUS features into an integrated diagnostic criterion, the AUC reached 0.917 (95% CI 0.873–0.961), with a sensitivity of 95.8% and specificity of 87.5%. ICC ranged from 0.756 to 0.907 for inter-observer agreement and 0.791 to 0.934 for intra-observer agreement for CUS and CEUSfeatures. CONCLUSIONS: The combination of clinical features of age and hematuria with imaging features of CUS and CEUS can be useful for the differentiation between RUC and EccRCC. [ABSTRACT FROM AUTHOR]

Aim: To investigate the clinical feasibility of ultra‐high‐frequency abdominal ultrasound (UHFUS) scans of preterm and term infants. Methods: Prospectively, 19 healthy term newborn infants were examined with conventional ultrasound (CUS) (Toshiba, Aplio i700, linear probe 14L5) and UHFUS (Visualsonics VevoMD, linear probes UHF48 and UHF70) according to a standardised protocol. Measurements of wall thickness were performed for; stomach, small intestine, colon and peritoneum. Five preterm infants, with or without suspected necrotising enterocolitis (NEC), were also examined with UHF48. Of these, only one was later diagnosed with NEC. Results: Differences between CUS and UHFUS (UHF48) were found in measurements of thickness; for peritoneum 0.25 versus 0.13 mm (p < 0.001), small intestine 0.76 versus 0.64 mm (p = 0.039) and colon 0.7 versus 0.47 mm (p < 0.001) in healthy term infants. Gaining frequency from 46 to 71 MHz showed a mean reduction in measurements of peritoneum from 0.13 to 0.09 mm (p < 0.001). One preterm infant with NEC showed a fivefold and twofold increase in peritoneal and gastrointestinal wall thickness respectively, compared to healthy preterm infants. Conclusion: UHFUS was a clinically feasible, promising method with potential to improve gastrointestinal diagnostics in infants. Lower peritoneum thickness and gastrointestinal wall thickness were demonstrated with UHFUS compared to CUS, suggesting an overestimation by CUS. [ABSTRACT FROM AUTHOR]

Abstract Objective Ductal carcinoma in situ (DCIS) of the breast has a wide disease spectrum with risks of progression to invasive cancer linked to pathological factors. High-grade histology, large tumor volume, and comedonecrosis are adverse prognostic factors. This study explores the correlation between conventional ultrasound (Con-US) and shears wave elastography (SWE) features with DCIS prognostic factors and evaluates their predictive efficacy. Methods A retrospective analysis was conducted on clinical data, Con-US, and SWE imaging features of 83 DCIS patients who underwent surgical resection between June 2018 and December 2022. Binary logistic regression analysis was performed to explore the relationship between sonogram indices and pathological prognostic factors. Results The results revealed that microcalcification observed on Con-US was an independent risk factor for high-grade DCIS and comedonecrosis [odds ratio (OR): 5.316 and 4.512]. In SWE analysis, the Emax value was significantly different between the non-high-grade and high-grade DCIS groups(P = 0.006), with an Emax value greater than 75.03 kPa identified as an independent risk factor for high-grade DCIS [OR:1.022, the area under the curve (AUC): 0.682, 95% confidence interval (CI): 0.555–0.808]. Additionally, the Ecolor, Emax, Emean, and Emean SD values were statistically different between the groups with and without comedonecrosis (P = 0.049, 0.006, 0.012, 0.022), with an Emean value exceeding 30.45 kPa identified as an independent risk factor for comedonecrosis (OR:1.025, AUC:0.708, 95% CI:0.562–0.854). Furthermore, combining microcalcification on Con-US with specific SWE indicators demonstrated an improved predictive specificity for high-grade DCIS and comedonecrosis (0.902 and 0.889, respectively). No significant difference was found in other indexes on SWE. Conclusions The microcalcification signs on Con-US, Emax and Emean values on SWE analysis are associated with the high nuclear grade and comedonecrosis of DCIS, the combination of Con-US and SWE can improve the predictive specificity of DCIS-related prognostic factors.

Objective: To evaluate accuracy and feasibility of a handheld ultrasound machine for measuring carotid artery intima-media thicknesses (CIMT) and hemodynamic parameters by different expertise levels of ultrasound operators. Methods: The operators were divided into three groups based on the level of their medical expertise: ultrasound technician, sonographer, and nursing staff. Operators from each group measured the CIMT and hemodynamic parameters of 25 volunteers using both handheld ultrasound and a conventional ultrasound machine. The reliability and reproducibility of handheld ultrasound measurements of CIMT and hemodynamic parameters (peak systolic velocity (PSV), end-diastolic velocity (EDV)) in operators were analyzed. Results: After a period of training, there was no statistically significant difference between the mean CIMT measured using handheld ultrasound among the three operators (0.45 ± 0.09 mm, 0.50 ± 0.07 mm, 0.46 ± 0.08 mm, P> 0.05, respectively), as well as PSV (83.30 ± 15.42 cm/s, 76.28 ± 13.26 cm/s, 81.12 ± 21.21 cm/s, P> 0.05, respectively) and EDV (21.04 ± 4.12 cm/s, 21.87 ± 5.05 cm/s, 20.17 ± 5.90 cm/s, respectively, P> 0.05). Furthermore, there was a good repeatability and consistent of handheld ultrasound device in measuring mean CIMT in the ultrasound technician and sonographer groups (r = 0.662, 0.691, respectively, P < 0.01). Conclusions: Under the premise of proper training, handheld ultrasound systems are feasible for rapid and primary assessment of carotid artery by operators with different levels of expertise.

We present a case involving a 71-year-old male with tubulocystic renal cell carcinoma (TRCC), which is a rare entity of renal neoplasm. The patient was admitted for a cystic nodule on the middle pole of the right kidney by urological ultrasound during physical examination. The nodule presented with hyperechoic on conventional ultrasonic and the enhancing intensity of thicken cystic wall at the peak phase in contrast-enhanced ultrasound was similar to that of the renal parenchyma. Findings from computed tomography angiography exhibited heterogeneously contrast enhancing tumor, and magnetic resonance imaging demonstrated hypointense on T1- weighted images (WI) and hyperintense on T2WI. Histologically, the spongy surface was composed of the typical tubular and multiloculated cystic components lined by a single layer of epithelial cells. The final pathological diagnosis was TRCC. The uneventful laparoscopic right radical nephrectomy was conducted. The patient was followed up for 12 months after discharge and no signs of local or distant metastasis were found. In conclusion, TRCC should be accurately diagnosed on the basis of comprehensive radiological and histological findings to ensure a timely surgery and better prognosis. [ABSTRACT FROM AUTHOR]

PurposeThis study aims to assess the diagnostic efficacy of conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) in detecting fat-poor angiomyolipomas(AML) with dimensions less than 5 cm. Additionally, the study seeks to identify independent indicators for predicting the presence of fat-poor AML.MethodsWe conducted a retrospective analysis of patients diagnosed with renal AML and renal cell carcinoma, who were admitted and underwent surgery at Fujian Provincial Hospital from January 2013 to October 2023. A total of 154 renal tumors were included (104 renal cell carcinomas and 50 fat-poor AMLs). Prior to radical or partial nephrectomy, these patients underwent both CUS and CEUS examinations. We systematically analyzed the features observed in CUS and CEUS, identified independent factors through multifactorial regression analysis, and evaluated diagnostic efficacy by calculating the area under the curve (AUC).ResultsUnivariate analysis revealed significant distinctions in fat-poor AML concerning gender, age, morphology, internal hyperechoic features (starry-sky sign, crescent sign), enhancement uniformity, and delayed enhancement, all displaying significance compared to renal cell carcinoma (RCC) (p < 0.05). Multivariate analysis demonstrated that internal hyperechoic features (p < 0.01, Odds Ratio [OR] = 0.003, 95% Confidence Interval [CI]: 0.000-0.0028) and enhancement uniformity (p < 0.01, OR = 0.016, 95% CI: 0.001-0.229) independently predicted fat-poor AML. The Receiver Operating Characteristic (ROC) curve’s area under the curve (AUC) for internal hyperechoic features (starry-sky sign, crescent sign) was 0.88 (95% CI: 0.80–0.95), with a sensitivity of 78.00%, specificity of 97.12%, positive predictive value of 92.85%, and negative predictive value of 90.18%. Conversely, the ROC curve AUC for enhancement uniformity was 0.70 (95% CI: 0.62–0.78), with a sensitivity of 96.00%, specificity of 44.23%, positive predictive value of 45.28%, and negative predictive value of 95.83%.ConclusionThis study suggests that both CUS and CEUS possess discriminative value in differentiating fat-poor AMLs from RCCs. Notably, internal hyperechoic features (starry-sky sign, crescent sign) and uniform enhancement within renal tumors emerge as potential independent indicators for predicting fat-poor AML.

Background: This study aimed to investigate whether quantitative radiomics features extracted from conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) of primary breast lesions can help noninvasively predict axillary lymph nodes metastasis (ALNM) in breast cancer patients. Method: A total of 111 breast cancer patients with 111 breast lesions were prospectively enrolled. All the included patients received presurgical CUS screening and CEUS examination and were randomly assigned to the training and validation sets at a ratio of 7:3 (n = 78 versus 33). Radiomics features were respectively extracted based on CUS and CEUS using the PyRadiomics package. The max-relevance and min-redundancy (MRMR) and least absolute shrinkage and selection operator (LASSO) analyses were used for feature selection and radiomics score calculation in the training set. The variance inflation factor (VIF) was performed to check the multicollinearity among selected predictors. The best performing model was selected to develop a nomogram using binary logistic regression analysis. The calibration and clinical utility of the nomogram were assessed. Results: The model combining CUS reported ALN status, CUS radiomics score (CUS-radscore) and CEUS radiomics score (CEUS-radscore) exhibited the best performance. The areas under the curves (AUC) of our proposed nomogram in the training and external validation sets were 0.845 [95% confidence interval (CI), 0.739-0.950] and 0.901 (95% CI, 0.758-1). The calibration curves and decision curve analysis (DCA) demonstrated the nomogram's robust consistency and clinical utility. Conclusions: The established nomogram is a promising prediction tool for noninvasive prediction of ALN status. The radiomics features based on CUS and CEUS can help improve the predictive performance. [ABSTRACT FROM AUTHOR]

Carbon fiber reinforced polymer (CFRP) composites are popular materials in the aerospace and automotive industries because of their low weight, high strength, and corrosion resistance. However, wrinkles or geometric distortions in the composite layers significantly reduce their mechanical performance and structural integrity. This paper presents a method for non-destructively extracting the three-dimensional geometry, lamina by lamina, of a laminated composite. A method is introduced for fabricating consistent out-of-plane wrinkled CFRP laminate panels, simulating the in-service wrinkle observed in industries that utilize thick structure composites such as the vertical lift or wind power industries. The individual lamina geometries are extracted from the fabricated coupon with an embedded wrinkle from captured ultrasonic waveforms generated from single-element conventional ultrasonic (UT) scan data. From the extracted waveforms, a method is presented to characterize the wrinkle features within each individual lamina, specifically the spatially varying wrinkle height and intensity for the wrinkle. Parts were fabricated with visibly undetectable wrinkles using a wet layup process and a hot press for curing. Scans were performed in a conventional immersion tank scanning system, and the scan data were analyzed for wrinkle detection and characterization. Extraction of the layers was performed based on tracking the voltage peaks from A-scans in the time domain. Spatial Gaussian averaging was performed to smooth the A-scans, from which the surfaces were extracted for each individual lamina. The extracted winkle surface aligned with the anticipated wrinkle geometry, and a single parameter for quantification of the wrinkle intensity for each lamina is presented. [ABSTRACT FROM AUTHOR]

Purpose: Papillary thyroid carcinoma (PTC) with metastatic lymph nodes (LNs) is closely associated with disease recurrence. This study accessed the value of superb microvascular imaging (SMI) in the diagnosis and prediction of metastatic cervical LNs in patients with PTC. Methods: A total of 183 cervical LNs (103 metastatic and 80 reactive) from 116 patients with PTC were analysed. Metastatic cervical LNs were confirmed by pathology or/and cytology; reactive cervical LNs were confirmed by pathology or clinical features. The characteristic of conventional ultrasound (US) was extracted using univariate and multivariate analyses. The diagnostic performance of US and SMI were compared using the area under the receiver operating curve (AUC) with corresponding sensitivity and specificity. A nomogram was developed to predict metastatic LNs in patients with PTC, based on multivariate analyses. Results: L/S < 2, ill-defined border, absence of hilum, isoechoic or hyperechoic, heterogeneous internal echo, peripheral or mixed vascular pattern on color Doppler flow imaging (CDFI) and SMI, and a larger SMI vascular index appeared more frequently in metastatic LNs in the training datasets than in reactive LNs (P < 0.05). The diagnostic sensitivity, specificity and accuracy of SMI vs US are 94.4% and 87.3%, 79.3% and 69.3%, and 87.6% and 79.1%, respectively; SMI combined with US exhibited a higher AUC [0.926 (0.877–0.975)] than US only [0.829 (0.759–0.900)]. L/S < 2, peripheral or mixed vascular type on CDFI, and peripheral or mixed vascular types on SMI were independent predictors of metastatic LNs with PTC. The nomogram based on these three parameters exhibited excellent discrimination, with an AUC of 0.926. Conclusion: SMI was superior to US in diagnosing metastatic LNs in PTC. US combined with SMI significantly improved the diagnostic accuracy of metastatic cervical LNs with PTC. SMI is efficacious for differentiating and predicting metastatic cervical LNs. [ABSTRACT FROM AUTHOR]

Abstract Background Dermatofibrosarcoma protuberans (DFSP) has a high recurrence rate after resection. Because of the lack of specific manifestations, recurrent DFSP is easily misdiagnosed as post-resection scar. A few series have reported ultrasound findings of recurrent DFSP; moreover, the usefulness of contrast-enhanced ultrasound in differentiating recurrent DFSP has not been studied. Objective We investigated conventional and contrast-enhanced ultrasound in the differential diagnosis of recurrent DFSP and post-resection scar. Methods We retrospectively evaluated the findings of conventional and contrast-enhanced ultrasound in 34 cases of recurrent DFSP and 38 postoperative scars examined between January 2018 and December 2022. Results The depth and vascular density of recurrent DFSP were greater than those of postoperative scars (P

BackgroundThis study aimed to investigate whether quantitative radiomics features extracted from conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) of primary breast lesions can help noninvasively predict axillary lymph nodes metastasis (ALNM) in breast cancer patients.MethodA total of 111 breast cancer patients with 111 breast lesions were prospectively enrolled. All the included patients received presurgical CUS screening and CEUS examination and were randomly assigned to the training and validation sets at a ratio of 7:3 (n = 78 versus 33). Radiomics features were respectively extracted based on CUS and CEUS using the PyRadiomics package. The max-relevance and min-redundancy (MRMR) and least absolute shrinkage and selection operator (LASSO) analyses were used for feature selection and radiomics score calculation in the training set. The variance inflation factor (VIF) was performed to check the multicollinearity among selected predictors. The best performing model was selected to develop a nomogram using binary logistic regression analysis. The calibration and clinical utility of the nomogram were assessed.ResultsThe model combining CUS reported ALN status, CUS radiomics score (CUS-radscore) and CEUS radiomics score (CEUS-radscore) exhibited the best performance. The areas under the curves (AUC) of our proposed nomogram in the training and external validation sets were 0.845 [95% confidence interval (CI), 0.739-0.950] and 0.901 (95% CI, 0.758-1). The calibration curves and decision curve analysis (DCA) demonstrated the nomogram’s robust consistency and clinical utility.ConclusionsThe established nomogram is a promising prediction tool for noninvasive prediction of ALN status. The radiomics features based on CUS and CEUS can help improve the predictive performance.

Objective: This study aims to analyse the imaging manifestations of granulomatous mastitis (GM) and invasive ductal carcinoma (IDC) using conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS). The objective is to investigate the clinical value of CEUS in differentiating between GM and IDC., Methods: We retrospectively enrolled 39 GM patients and 64 IDC patients between January 2020 and June 2023. All diagnoses were confirmed via core needle biopsy or surgical pathology. The characteristics of both conventional US and CEUS in these patients were analysed to distinguish GM from IDC., Results: Based on CEUS features, GM lesions most commonly presented as hypoechoic areas (43.6%), followed by pseudocysts (28.2%), hypoechoic nodules (15.4%), and honeycomb cysts (12.8%). The diffuse enhancement pattern was an independent characteristic for distinguishing GM from IDC, with the ROC analysis revealing an area under the curve (AUC) value of 0.794., Conclusion: US is the preferred initial examination for GM, and both its conventional and CEUS features can enhance diagnostic accuracy and guide clinical treatment. CEUS demonstrates high differential diagnostic value in distinguishing GM from IDC., Advances in Knowledge: This study categorizes GM manifestations on CEUS into four types, each corresponding to different pathological stages of GM. We identified that the diffuse enhancement pattern on CEUS is a distinctive characteristic associated with GM, aiding in its differentiation from IDC., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Institute of Radiology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Purpose: Non-invasive tests are increasingly demanded for diagnosing and prognostication of chronic kidney disease (CKD). Shear-wave elastography (SWE), an emerging technique for measuring tissue stiffness, shows promise for distinguishing between individuals with different stages of renal fibrosis. This study aimed to compare the diagnostic accuracy of two-dimensional SWE (2D-SWE) and conventional ultrasound for detecting CKD, employing renal biopsy as the gold standard., Methods: From May 2020 to October 2023, this prospective study included 30 healthy volunteers and 169 patients with CKD who had undergone 2D-SWE and conventional ultrasound of both kidneys. Cortical and medullary stiffness, cortical pixel intensity, renal length, parenchymal and cortical thickness, interlobar artery peak systolic velocity, end-diastolic velocity (EDV), and resistive index were measured. The diagnostic accuracy of 2D-SWE and conventional ultrasound was compared using the receiver operating characteristic curve (ROC) and Delong test., Results: For diagnosing CKD, the area under the ROC (AUC) of cortical stiffness (0.96 [95% CI, 0.93, 0.99]) was significantly higher than that of all conventional ultrasound parameters, including EDV (0.78 [95% CI, 0.71, 0.86]) and cortical thickness (0.74 [95% CI, 0.67, 0.80]). The sensitivity of cortical stiffness (91%) was significantly higher than that of EDV (68%) and cortical thickness (53%). No significant difference was found in the specificity of cortical stiffness (96%) compared to that of EDV (79%) and cortical thickness (100%)., Conclusion: Two-dimensional SWE showed higher diagnostic accuracy than that of conventional ultrasound for detecting CKD., (© 2024 Wiley Periodicals LLC.)

We present a case involving a 71-year-old male with tubulocystic renal cell carcinoma (TRCC), which is a rare entity of renal neoplasm. The patient was admitted for a cystic nodule on the middle pole of the right kidney by urological ultrasound during physical examination. The nodule presented with hyperechoic on conventional ultrasonic and the enhancing intensity of thicken cystic wall at the peak phase in contrast-enhanced ultrasound was similar to that of the renal parenchyma. Findings from computed tomography angiography exhibited heterogeneously contrast enhancing tumor, and magnetic resonance imaging demonstrated hypointense on T1-weighted images (WI) and hyperintense on T2WI. Histologically, the spongy surface was composed of the typical tubular and multiloculated cystic components lined by a single layer of epithelial cells. The final pathological diagnosis was TRCC. The uneventful laparoscopic right radical nephrectomy was conducted. The patient was followed up for 12 months after discharge and no signs of local or distant metastasis were found. In conclusion, TRCC should be accurately diagnosed on the basis of comprehensive radiological and histological findings to ensure a timely surgery and better prognosis., Competing Interests: There are no conflicts of interest., (© 2024 Published by Scientific Scholar on behalf of Journal of Clinical Imaging Science.)

Background: To develop and validate a model based on conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) features to preoperatively predict microinvasion in breast ductal carcinoma in situ (DCIS)., Patients and Methods: Data from 163 patients with DCIS who underwent CUS and CEUS from the internal hospital was retrospectively collected and randomly apportioned into training and internal validation sets in a ratio of 7:3. External validation set included 56 patients with DCIS from the external hospital. Univariate and multivariate logistic regression analysis were performed to determine the independent risk factors associated with microinvasion. These factors were used to develop predictive models. The performance was evaluated through calibration, discrimination, and clinical utility., Results: Multivariate analysis indicated that centripetal enhancement direction (odds ratio [OR], 13.268; 95% confidence interval [CI], 3.687-47.746) and enhancement range enlarged on CEUS (OR, 4.876; 95% CI, 1.470-16.181), lesion size of ≥20 mm (OR, 3.265; 95% CI, 1.230-8.669) and calcification detected on CUS (OR, 5.174; 95% CI, 1.903-14.066) were independent risk factors associated with microinvasion. The nomogram incorporated the CUS and CEUS features achieved favorable discrimination (AUCs of 0.850, 0.848, and 0.879 for the training, internal and external validation datasets), with good calibration. The nomogram outperformed the CUS model and CEUS model (all P < .05). Decision curve analysis confirmed that the predictive nomogram was clinically useful., Conclusion: The nomogram based on CUS and CEUS features showed promising predictive value for the preoperative identification of microinvasion in patients with DCIS., Competing Interests: Disclosure The authors have stated that they have no conflicts of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Ultrasound is widely used in the examination of the parotid gland, but no single ultrasound feature has demonstrated satisfactory diagnostic performance in predicting the nature of parotid nodules. Unlike the established and widely used grading systems for breast and thyroid nodules, a universally adopted and clinically accepted risk stratification system for malignancy in parotid gland nodules remains absent at present. This study aims to establish a malignant risk stratification model for parotid nodules by analyzing patients' clinical features and conventional ultrasound image characteristics., Methods: In this study, clinical data and ultrasound images of 736 patients with parotid nodules were retrospectively analyzed. Pathological results served as the gold standard, and the patients were randomly divided into training and validation groups in a 7:3 ratio. Clinical and ultrasound features of parotid nodules in the training group were compared. Multifactor logistic regression analysis was employed to screen for risk factors of malignant nodules and quantify scores. The probability of malignant risk was assessed and classified into five grades (Grade 1, normal parotid; Grade 2, definitive benign; Grade 3, possibly benign; Grade 4, suspicious malignant; Grade 5, high probability of malignancy). The diagnostic performance of the model was assessed by using calibration curves, receiver operating characteristic curves, decision curves, and clinical impact curves., Results: Facial symptoms, unclear margin, irregular shape, microcalcification, and abnormal cervical lymph nodes were independent risk factors for malignant parotid nodules. The area under the curve of the model was 0.850 [95% confidence interval (CI): 0.816-0.879] in the training group and 0.846 (95% CI: 0.791-0.891) in the validation group., Conclusions: The malignancy risk stratification model based on clinical and ultrasound image features has a good differentiation between benign and malignant parotid nodules, which is helpful for diagnosis and guiding clinical treatment., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://gs.amegroups.com/article/view/10.21037/gs-24-119/coif). The authors have no conflicts of interest to declare., (2024 Gland Surgery. All rights reserved.)

Background: This study aimed to investigate whether quantitative radiomics features extracted from conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) of primary breast lesions can help noninvasively predict axillary lymph nodes metastasis (ALNM) in breast cancer patients., Method: A total of 111 breast cancer patients with 111 breast lesions were prospectively enrolled. All the included patients received presurgical CUS screening and CEUS examination and were randomly assigned to the training and validation sets at a ratio of 7:3 (n = 78 versus 33). Radiomics features were respectively extracted based on CUS and CEUS using the PyRadiomics package. The max-relevance and min-redundancy (MRMR) and least absolute shrinkage and selection operator (LASSO) analyses were used for feature selection and radiomics score calculation in the training set. The variance inflation factor (VIF) was performed to check the multicollinearity among selected predictors. The best performing model was selected to develop a nomogram using binary logistic regression analysis. The calibration and clinical utility of the nomogram were assessed., Results: The model combining CUS reported ALN status, CUS radiomics score (CUS-radscore) and CEUS radiomics score (CEUS-radscore) exhibited the best performance. The areas under the curves (AUC) of our proposed nomogram in the training and external validation sets were 0.845 [95% confidence interval (CI), 0.739-0.950] and 0.901 (95% CI, 0.758-1). The calibration curves and decision curve analysis (DCA) demonstrated the nomogram's robust consistency and clinical utility., Conclusions: The established nomogram is a promising prediction tool for noninvasive prediction of ALN status. The radiomics features based on CUS and CEUS can help improve the predictive performance., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Sun, Gong, Hou, Yang, Li, Li and Wang.)