UNASSIGNED: Desmoid tumor (DT) is a rare locally aggressive but non-metastatic mesenchymal soft tissue neoplasm that predominantly occurs in the abdominal wall, abdominal cavity, and extremities. Its occurrence in the mesentery is relatively uncommon.
UNASSIGNED: This article reports two cases of desmoid tumor treated at the Department of Gastrointestinal Surgery, Weifang People\'s Hospital. The first case was a 59-year-old male patient who had previously undergone surgery for esophagogastric junction cancer. Postoperatively, he developed an intra-abdominal mass that rapidly increased in size within three months. The second case was a 60-year-old male patient who incidentally discovered a mass in the left lower abdomen. Both patients underwent surgical treatment, and the postoperative pathological diagnosis was mesenteric desmoid tumor.
UNASSIGNED: The treatment of desmoid tumor remains challenging. Simple surgical resection often yields unsatisfactory outcomes, and the efficacy of adjuvant radiotherapy and chemotherapy is also limited. Further research and clinical practice are necessary to improve diagnostic and therapeutic strategies, aiming to enhance patient survival and quality of life.

BACKGROUND: To explore the potential of different quantitative dynamic contrast-enhanced (qDCE)-MRI tracer kinetic (TK) models and qDCE parameters in discriminating benign from malignant soft tissue tumors (STTs).
METHODS: This research included 92 patients (41females, 51 males; age range 16-86 years, mean age 51.24 years) with STTs. The qDCE parameters (Ktrans, Kep, Ve, Vp, F, PS, MTT and E) for regions of interest of STTs were estimated by using the following TK models: Tofts (TOFTS), Extended Tofts (EXTOFTS), adiabatic tissue homogeneity (ATH), conventional compartmental (CC), and distributed parameter (DP). We established a comprehensive model combining the morphologic features, time-signal intensity curve shape, and optimal qDCE parameters. The capacities to identify benign and malignant STTs was evaluated using the area under the curve (AUC), degree of accuracy, and the analysis of the decision curve.
RESULTS: TOFTS-Ktrans, EXTOFTS-Ktrans, EXTOFTS-Vp, CC-Vp and DP-Vp demonstrated good diagnostic performance among the qDCE parameters. Compared with the other TK models, the DP model has a higher AUC and a greater level of accuracy. The comprehensive model (AUC, 0.936, 0.884-0.988) demonstrated superiority in discriminating benign and malignant STTs, outperforming the qDCE models (AUC, 0.899-0.915) and the traditional imaging model (AUC, 0.802, 0.712-0.891) alone.
CONCLUSIONS: Various TK models successfully distinguish benign from malignant STTs. The comprehensive model is a noninvasive approach incorporating morphological imaging aspects and qDCE parameters, and shows significant potential for further development.

OBJECTIVE: To systematically evaluate the application value of radiomics and deep learning (DL) in the differential diagnosis of benign and malignant soft tissue tumors (STTs).
METHODS: A systematic review was conducted on studies published up to December 11, 2023, that utilized radiomics and DL methods for the diagnosis of STTs. The methodological quality and risk of bias were evaluated using the Radiomics Quality Score (RQS) 2.0 system and Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool, respectively. A bivariate random-effects model was used to calculate the summarized sensitivity and specificity. To identify factors contributing to heterogeneity, meta-regression and subgroup analyses were performed to assess the following covariates: diagnostic modality, region/volume of interest, imaging examination, study design, and pathology type. The asymmetry of Deeks\' funnel plot was used to assess publication bias.
RESULTS: A total of 21 studies involving 3866 patients were included, with 13 studies using independent test/validation sets included in the quantitative statistical analysis. The average RQS was 21.31, with substantial or near-perfect inter-rater agreement. The combined sensitivity and specificity were 0.84 (95% CI: 0.76-0.89) and 0.88 (95% CI: 0.69-0.96), respectively. Meta-regression and subgroup analyses showed that study design and the region/volume of interest were significant factors affecting study heterogeneity (P < 0.05). No publication bias was observed.
CONCLUSIONS: Radiomics and DL can accurately distinguish between benign and malignant STTs. Future research should concentrate on enhancing the rigor of study designs, conducting multicenter prospective validations, amplifying the interpretability of DL models, and integrating multimodal data to elevate the diagnostic accuracy and clinical utility of soft tissue tumor assessments.

BACKGROUND: Recently, a novel group of CD34 and S100 co-expression spindle cell tumors with distinctive stromal and perivascular hyalinization harboring recurrent gene fusions involving RET, RAF1, BRAF, and NTRK1/2 gene has been identified.
METHODS: In this study, we reported two Chinese male patients with soft tissue tumors presenting in the right knee joint and the left thigh, respectively. For both patients, the tumors were completely excised with clear margin. Microscopically, case 1showed morphological overlap with neurofibroma, and case 2 showed overlap with lipomatous solitary fibrous tumor. Both tumors showed co-expression of S100 and CD34, and absence of SOX10. Genomic profiling with DNA-based next-generation sequencing (NGS) assay was performed and revealed KIF5B-RAF1 (K16:R8) and TLN2-RAF1 (T54:R8) rearrangements. RNA-based NGS and RT-PCR were performed to confirm the gene fusion.
CONCLUSIONS: Though systemic therapy was not indicated in these two patients, identification of targetable kinase fusions may help to refine tumors with an ambiguous immunoprofile, and provides suggestions for targeted therapy in rare aggressive cases.

Objective: To evaluate the diagnostic performance of standard diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI), for differentiating benign and malignant soft tissue tumors (STTs). Materials and methods: A thorough search was carried out to identify suitable studies published up to September 2020. The quality of the studies involved was evaluated using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The pooled sensitivity (SEN), specificity (SPE), and summary receiver operating characteristic (SROC) curve were calculated using bivariate mixed effects models. A subgroup analysis was also performed to explore the heterogeneity. Results: Eighteen studies investigating 1319 patients with musculoskeletal STTs (malignant, n=623; benign, n=696) were enrolled. Thirteen standard DWI studies using the apparent diffusion coefficient (ADC) showed that the pooled SEN and SPE of ADC were 0.80 (95% CI: 0.77-0.82) and 0.63 (95% CI: 0.60-0.67), respectively. The area under the curve (AUC) calculated from the SROC curve was 0.806. The subgroup analysis indicated that the percentage of myxoid malignant tumors, magnet strength, study design, and ROI placement were significant factors affecting heterogeneity. Four IVIM studies showed that the AUCs calculated from the SROC curves of the parameters ADC and D were 0.859 and 0.874, respectively. The AUCs for the IVIM parameters pseudo diffusion coefficient (D*) and perfusion fraction (f) calculated from the SROC curve were 0.736 and 0.573, respectively. Two DKI studies showed that the AUCs of the DKI parameter mean kurtosis (MK) were 0.97 and 0.89, respectively. Conclusion: The DWI-derived ADC value and the IVIM DWI-derived D value might be accurate tools for discriminating musculoskeletal STTs, especially for non-myxoid SSTs, using more than two b values, with maximal b value ranging from 600 to 800 s/mm2, additionally, a high-field strength (3.0 T) optimizes the diagnostic performance.

UNASSIGNED: The objective of this study was to establish a predictive nomogram based on ultrasound (US) and clinical features for patients with soft tissue tumors (STTs).
UNASSIGNED: A total of 260 patients with STTs were enrolled in this retrospective study and were divided into a training cohort (n=200, including 110 malignant and 90 benign masses) and a validation cohort (n=60, including 30 malignant and 30 benign masses). Multivariate analysis was performed by binary logistic regression analysis to determine the significant factors predictive of malignancy. A simple nomogram was established based on these independent risk factors including US and clinical features. The predictive accuracy and discriminative ability of the nomogram were measured by the calibration curve and the concordance index (C-index).
UNASSIGNED: The nomogram, comprising US features (maximum diameter, margin and vascular density) and clinical features (sex, age, and duration of disease), showed a favorable performance for predicting malignancy, with a sensitivity of 88.2% and a specificity of 78.7%. The calibration curve for malignancy probability in the training cohort showed good agreement between the nomogram predictions and actual observations. The C-indexes of the training cohort and validation cohort for predicting malignancy were 0.89 (95% CI: 0.85-0.94) and 0.83 (95% CI: 0.73-0.94), respectively.
UNASSIGNED: The nomogram based on US and clinical features could be a simple, intuitive and reliable tool to individually predict malignancy in patients with STTs.

OBJECTIVE: To investigate the diagnostic value of conventional ultrasound (US) and strain elastography (SE) in malignant soft tissue tumors.
METHODS: A total of 83 soft tissue masses were included prospectively. US and SE imaging were performed at the same time. Two observers assessed the B mode, color Doppler, elastic scores (ES), strain ratio (SR), and SE size to B mode size (EI/B) ratio and compared the consistency of the data between the observers. According to the pathological diagnosis of resection, the cases were divided into malignant and nonmalignant groups. The diagnostic value of conventional US and SE in the prediction of malignant soft tissue tumors was assessed.
RESULTS: The pathology results divided cases into 36 malignant lesions and 47 nonmalignant lesions. There was no statistically significant difference in gender, location, maximum diameter, echo, tail sign, cystic component, Doppler scores, or SR between the two groups (p > 0.05). However, significant differences between the two groups were found in age, depth, heterogeneity, edge, ES, and EI/B (p < 0.05). The biggest area under the receiver operating characteristics curve (0.934) was the combination model of age, heterogeneity, edge, ES, and EI/B, and the sensitivity and specificity were 0.861 and 0.957, respectively.
CONCLUSIONS: Conventional US and SE are significant for the diagnosis of malignant soft tissue tumors, and SE can be used as a complementary technique to the characterization of STTs using conventional US.

This meta-analysis was aimed at investigating the value of using contrast-enhanced ultrasound (CEUS) in the differential diagnosis of benign and malignant soft tissue masses (STMs). Relevant studies published before March 24, 2020 were identified through a comprehensive search of PubMed, Ovid, Cochrane and Web of Science. According to the inclusion criteria, five studies were selected comprising 746 patients. In the differential diagnosis of benign and malignant STMs, the pooled sensitivity and specificity of CEUS were 76% (95% confidence interval [CI]: 71%-81%; heterogeneity [I2] = 74.5%) and 67% (95% CI: 62%-71%; I2 = 36.5%), respectively. The diagnostic odds ratio was 7.37 (95% CI: 3.78%-14.35; I2 = 66.6%). The overall area under the curve was 0.77 (standard error: 0.0392). Subgroup analysis revealed that different index tests of CEUS resulted in different diagnostic performance. Importantly, CEUS is an effective method for the differential diagnosis between benign and malignant STMs.

To investigate the correlation between dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) parameters and angiogenesis and to explore prospectively the feasibility of using DSC-MRI to differentiate malignant from benign soft tissue tumors (STTs) in limbs.
This prospective study included 33 patients with STTs in limbs who underwent DSC-MRI after bolus Gd-DTPA infusion. All STTs were confirmed by pathological examination after surgery and microvessel density (MVD), vascular endothelial growth factor (VEGF) expression, were evaluated by immune-histochemical analysis. Semiquantitative DSC-MRI parameters, including negative enhancement integral (NEI), maximum slopes of decrease (MSD) and increase (MSI), and mean time to enhancement were calculated by postprocessing in workstation. The correlation was analyzed between DSC-MRI parameters and angiogenesis factors. Then, the DSC-MRI parameters were compared between benign and malignant STTs and evaluated for diagnostic efficiency by receiver operating characteristic.
The 33 evaluated tumors were consisted of 13 benign and 20 malignant STTs in limbs. Significant positive correlations were observed between NEI, MSD, MSI and MVD, VEGF (p < 0.05). However, mean time to enhancement had no correlation with MVD and VEGF. The benign and malignant STTs differed significantly in terms of NEI, MSD, and MSI (p < 0.05). The areas under the curve (AUC) of NEI, MSD, and MSI were 0.915, 0.862, and 0.815 for discriminating between benign and malignant STTs, respectively.
DSC-MRI parameters are positively correlated with MVD and VEGF, which can evaluate angiogenesis indirectly. Furthermore, DSC-MRI can be considered as one of assistant noninvasive MR imaging technique in differentiation between benign and malignant STTs in limbs.

Epithelioid angiosarcomas are extremely rare malignant tumors formed from endothelial cells. The majority of studies reporting these tumors have been concerned with the clinical and pathological aspects, with limited reporting of radiological diagnosis. The aim of the present study was to provide a reference to improve understanding of diagnosis, treatment choice and prognosis assessment of epithelioid angiosarcoma. The current study reports the case of a 44-year-old woman with epithelioid angiosarcoma located in the deep soft tissue of the lower extremities. Physical examination of the right thigh revealed a palpable hard mass and movement was clearly restricted and painful. X-ray, computed tomography (CT) scans and magnetic resonance imaging (MRI) were used to evaluate the imaging features of the tumor. Using X-ray and CT scanning, an inhomogenous tumor with osteolytic osseous destruction was observed. MRI revealed that the bordering skeletal muscles were infiltrated. The patient was treated with palliative surgery and chemotherapy, but succumbed to disease 1 year later.