A practical risk stratification system based on ultrasonography and clinical characteristics for predicting the malignancy of soft tissue masses.

OBJECTIVE: To establish a practical risk stratification system (RSS) based on ultrasonography (US) and clinical characteristics for predicting soft tissue masses (STMs) malignancy. METHODS: This retrospective multicenter study included patients with STMs who underwent US and pathological examinations between April 2018 and April 2023. Chi-square tests and multivariable logistic regression analyses were performed to assess the association of US and clinical characteristics with the malignancy of STMs in the training set. The RSS was constructed based on the scores of risk factors and validated externally. RESULTS: The training and validation sets included 1027 STMs (mean age, 50.90 ± 16.64, 442 benign and 585 malignant) and 120 STMs (mean age, 51.93 ± 17.90, 69 benign and 51 malignant), respectively. The RSS was constructed based on three clinical characteristics (age, duration, and history of malignancy) and six US characteristics (size, shape, margin, echogenicity, bone invasion, and vascularity). STMs were assigned to six categories in the RSS, including no abnormal findings, benign, probably benign (fitted probabilities [FP] for malignancy: 0.001-0.008), low suspicion (FP: 0.008-0.365), moderate suspicion (FP: 0.189-0.911), and high suspicion (FP: 0.798-0.999) for malignancy. The RSS displayed good diagnostic performance in the training and validation sets with area under the receiver operating characteristic curve (AUC) values of 0.883 and 0.849, respectively. CONCLUSION: The practical RSS based on US and clinical characteristics could be useful for predicting STM malignancy, thereby providing the benefit of timely treatment strategy management to STM patients. CRITICAL RELEVANCE STATEMENT: With the help of the RSS, better communication between radiologists and clinicians can be realized, thus facilitating tumor management. KEY POINTS: There is no recognized grading system for STM management. A stratification system based on US and clinical features was built. The system realized great communication between radiologists and clinicians in tumor management.

Contrast-enhanced ultrasound guided core needle biopsy for soft tissue tumors: Accuracy and applicability.

OBJECTIVE: To evaluate the effectiveness of contrast-enhanced ultrasound (CEUS) guided core needle biopsy (CNB) in diagnosing soft tissue tumors (STTs) and to identify the conventional ultrasonography (US) features of STTs that are recommended for CEUS-guided CNB. MATERIALS AND METHODS: A retrospective study was conducted on 123 patients with surgically confirmed STTs. Before surgeries, all subjects underwent CNB under the guidance of US or CEUS. The histopathological results of surgical specimens were considered as the gold standards. A successful biopsy diagnosis was defined as the pathological subtypes obtained by biopsy consistent with the gold standard. The diagnostic yields were compared between the US and CEUS groups, and the diagnostic yields based on various conventional US features of STTs were also compared between the two groups. RESULTS: Sixty-seven cases underwent US-guided CNB and fifty-six cases underwent CEUS-guided CNB. The clinical, biopsy, and conventional US characteristics revealed no significant difference between the two groups. The diagnostic yield of the CEUS group was statistically higher than that of the US group (p = 0.011). In the CEUS group, more STTs with the anechoic areas were identified after CEUS examination (p = 0.031). Furthermore, the diagnostic yields based on the conventional US features of STTs, including deep fascia layer (p = 0.010), a maximum diameter ≥5 cm (p = 0.037), rough margin (p = 0.016), heterogeneous echotexture (p = 0.017), and absence of anechoic area (p = 0.013), were significantly different between the two groups, and the CEUS group exhibited higher diagnostic yields. CONCLUSION: CEUS-guided CNB was found to be an efficient method for STTs diagnosis. It is particularly recommended for STTs with the following conventional US features, including location in deep fascia layer, a maximum diameter ≥5 cm, rough margin, heterogeneous echotexture, or absence of anechoic area.

A multiparametric clinic-ultrasomics nomogram for predicting extremity soft-tissue tumor malignancy: a combined retrospective and prospective bicentric study.

OBJECTIVE: We aimed at building and testing a multiparametric clinic-ultrasomics nomogram for prediction of malignant extremity soft-tissue tumors (ESTTs). MATERIALS AND METHODS: This combined retrospective and prospective bicentric study assessed the performance of the multiparametric clinic-ultrasomics nomogram to predict the malignancy of ESTTs, when compared with a conventional clinic-radiologic nomogram. A dataset of grayscale ultrasound (US), color Doppler flow imaging (CDFI), and elastography images for 209 ESTTs were retrospectively enrolled from one hospital, and divided into the training and validation cohorts. A multiparametric ultrasomics signature was built based on multimodal ultrasomic features extracted from the grayscale US, CDFI, and elastography images of ESTTs in the training cohort. Another conventional radiologic score was built based on multimodal US features as interpreted by two experienced radiologists. Two nomograms that integrated clinical risk factors and the multiparameter ultrasomics signature or conventional radiologic score were respectively developed. Performance of the two nomograms was validated in the retrospective validation cohort, and tested in a prospective dataset of 51 ESTTs from the second hospital. RESULTS: The multiparametric ultrasomics signature was built based on seven grayscale ultrasomic features, three CDFI ultrasomic features, and one elastography ultrasomic feature. The conventional radiologic score was built based on five multimodal US characteristics. Predictive performance of the multiparametric clinic-ultrasomics nomogram was superior to that of the conventional clinic-radiologic nomogram in the training (area under the receiver operating characteristic curve [AUC] 0.970 vs. 0.890, p = 0.006), validation (AUC: 0.946 vs. 0.828, p = 0.047) and test (AUC: 0.934 vs. 0.842, p = 0.040) cohorts, respectively. Decision curve analysis of combined training, validation and test cohorts revealed that the multiparametric clinic-ultrasomics nomogram had a higher overall net benefit than the conventional clinic-radiologic model. CONCLUSION: The multiparametric clinic-ultrasomics nomogram can accurately predict the malignancy of ESTTs.

Analysis on diagnostic failure of US-guided core needle biopsy for soft tissue tumors.

Purpose: To evaluate the diagnostic yield of ultrasonography (US)-guided core needle biopsy (CNB) in the diagnosis of soft tissue tumors (STTs) and to analyze the failure factors. Methods: 139 patients with STTs that underwent both US-guided CNB and surgical resection were collected retrospectively. Compared with the histopathological results of surgical resection, the biopsy failure was defined as the following conditions: indefinitive diagnosis, including insufficient samples and unknown subtypes with correct biological potential classification; wrong diagnosis, including wrong biological potential classification and wrong subtypes with correct biological potential classification. Univariate and multivariate analyses from the perspectives of histopathological, demographic and US features together with biopsy procedures were performed to determine risk factors for diagnostic failure. Results: The diagnostic yield of US-guided CNB for STTs in our study was 78.4%, but when only considering the correct biological potential classification of STTs, the diagnostic yield was 80.6%. The multivariate analysis showed that adipocytic tumors (odds ratio (OR) = 10.195, 95% confidence interval (CI): 1.062 - 97.861, p = 0.044), vascular tumors (OR = 41.710, 95% CI: 3.126 - 556.581, p = 0.005) and indeterminate US diagnosis (OR = 8.641, 95% CI: 1.852 - 40.303, p = 0.006) were correlated with the diagnostic failure. The grade III vascular density (OR = 0.019, 95% CI: 0.001 - 0.273, p = 0.007) enabled a higher diagnostic accuracy. Conclusion: US-guided CNB can be an effective modality for the diagnosis of STTs. The diagnostic yield can be increased when the tumor vascular density was grade III in Color Doppler US, but can be decreased in adipocytic tumors, vascular tumors and masses with indeterminate US diagnosis.