Objectives: Changes in the microvascular environment are considered crucial in the pathogenesis of compression neuropathies. Several studies have demonstrated elevated intraneural vascularity in severe neuropathy compared with healthy subjects, where intraneural vascularity is considered predominantly undetectable. The aim of this study was to assess and quantify intraneural vasculature by superb microvascular imaging (SMI) in healthy volunteers in the median, ulnar and common peroneal nerve.Methods: Intraneural vascularity was quantified in 26 healthy volunteers (312 segments overall) by SMI sonography using a 22‐MHz linear transducer. Individual nerve segment vascularity was compared with the mean vascularity using one‐way ANOVA and Kruskal–Wallis tests, respectively. Vendor‐provided quantification and manual vessel count were compared by linear regression analysis.Results: Intraneural vascularity was detectable in all nerve segments (100.0%). Vessel density was highest in the median nerve at the wrist (1.54 ± 0.44/mm², P < 0.0001) and lowest in the sulcal ulnar nerve (0.90 ± 0.34/mm², P < 0.0001). Vendor‐provided automated quantification severely overestimated vascular content compared with manual quantification.Conclusion: Superb microvascular imaging can facilitate the visualisation of nerve vascularity and even detect local variations in vessel density. The pathophysiological implications for peripheral neuropathies, especially compression neuropathies, warrant further investigation, but the absence of visible intraneural vasculature as a negative finding in the diagnostic of compression neuropathies should be interpreted with caution, as the intraneural vascularity may lie beyond the 18 MHz resolution power of a transducer.

Background: A better understanding of the peritumoral stroma changes due to tumour invasion using non-invasive diagnostic methods may improve the differentiation between benign and malignant breast lesions. This study aimed to assess the correlation between breast lesion differentiation and intra- and peritumoral shear-wave elastography (SWE) gradients. Methods: A total of 135 patients with newly diagnosed breast lesions were included. Intratumoral, subsurface, and three consecutive peritumoral SWE value measurements (with three repetitions) were performed. Intratumoral, interface, and peritumoral gradients (Gradient 1 and Gradient 2) were calculated using averaged SWE values. Statistical analysis included descriptive statistics and an ordinary one-way ANOVA to compare overall and individual gradients among Breast Imaging-Reporting and Data System (BI-RADS) 2, 3, and 5 groups. Results: Malignant tumours showed higher average SWE velocity values at the tumour centre (BI-RADS 2/3: 4.1 ± 1.8 m/s vs. BI-RADS 5: 4.9 ± 2.0 m/s, p = 0.04) and the first peritumoral area (BI-RADS 2/3: 3.4 ± 1.8 m/s vs. BI-RADS 5: 4.3 ± 1.8 m/s, p = 0.003). No significant difference was found between intratumoral gradients (0.03 ± 0.32 m/s vs. 0.0 ± 0.28 m/s; p > 0.999) or gradients across the tumour–tissue interface (−0.17 ± 0.18 m/s vs. −0.13 ± 0.35 m/s; p = 0.202). However, the first peritumoral gradient (−0.16 ± 0.24 m/s vs. −0.35 ± 0.31 m/s; p < 0.0001) and the second peritumoral gradient (−0.11 ± 0.18 m/s vs. −0.22 ± 0.28 m/s; p = 0.037) were significantly steeper in malignant tumours. The AUC was best for PTG1 (0.7358) and PTG2 (0.7039). A threshold value for peritumoral SWI PT1 above 3.76 m/s and for PTG1 below −0.238 m/s·mm⁻¹ indicated malignancy in 90.6% of cases. Conclusions: Evaluating the peritumoral SWE gradient may improve the diagnostic pre-test probability, as malignant tumours showed a significantly steeper curve of the elasticity values in the peritumoral stroma compared to the linear regression with a relatively flat curve of benign lesions.

Introduction: Aneurysmal wall enhancement (AWE) of non-ruptured sacular intracranial aneurysms (IA) after endovascular treatment (ET) is a frequently observed imaging finding using AWE-sequences in brain magnetic resonance imaging (MRI). So far, its value remains unclear. We aimed to investigate the effect of AWE on aneurysm reperfusion rates in a longitudinal cohort. Methods: This is a retrospective MRI study over the timespan of up to 5 years, assessing the correlation of increased AWE of non-ruptured IAs and events of aneurysm reperfusion and retreatment, PHASES Score and grade of AWE. T1 SPACE fat saturation (FS) and T1 SE FS blood suppression sequences after contrast administration were used for visual interpretation of increased AWE. The IAs’ sizes were assessed via the biggest diameter. The grade of enhancement was defined in a grading system from grade 1 to grade 3. Results: 127 consecutive non ruptured IA-patients (58.9 ± 9.0 years, 94 female, 33 male) who underwent elective aneurysm occlusion were included. AWE was observed in 40.2% of patients (51/127) after ET, 6 patients already showed AWE before treatment. In large IAs (which were defined as a single maximum diameter of over 7.5 mm), AWE was significantly associated with aneurysm reperfusion in contrast to large aneurysm without AWE). All grades of AWE were significantly associated with reperfusion. Conclusions: Our data suggests that in patients with initially large IAs, AWE is correlated with aneurysm reperfusion.

To evaluate the diagnostic utility of the maximum ultrasound strain elastography (SE) halo depth in newly diagnosed and histologically confirmed breast lesions, a retrospective study approval was granted by the local Ethical Review Board. Overall, the maximum strain elastography peritumoural halos (SEPHmax)—the maximum distance between the SE stiffening area and the B-mode lesion size—in 428 cases with newly diagnosed breast lesions were retrospectively analysed alongside patient age, affected quadrant, tumour echogenicity, size, acoustic shadowing, and vascularity. Statistical analysis included an ordinary one-way ANOVA to compare the SEPHmax between BI-RADS 2, 3, and 5 groups and between tumour grades 1, 2, and 3. A binary regression analysis was used to determine the correlation between tumour malignancy and the above-mentioned demographic and imaging factors. SEPHmax was significantly higher in BI-RADS 5 tumours (5.5 ± 3.9 mm) compared to BI-RADS 3 (0.9 ± 1.7 mm, p < 0.0001) and 2 (0.6 ± 1.4 mm, p < 0.0001). The receiver operating characteristic area under the curve was 0.933 for the detection of BI-RADS 5 lesions. Furthermore, tumour grades 2 (5.6 ± 3.6 mm, p = 0.001) and 3 (6.8 ± 4.2 mm, p < 0.0001) exhibited significantly higher SEPHmax than grade 1 tumours (4.0 ± 3.9 mm). Similarly, St. Gallen Ki67-stratified low-risk (p = 0.005) and intermediate-risk (p = 0.013) tumours showed smaller SEPHmax than high-risk tumours. Multivariate analysis revealed a significant correlation between malignant differentiation and SEPHmax (standardized regression coefficient 3.17 [95% confidence interval (CI) 2.42–3.92], p < 0.0001), low tumour echogenicity (1.68 [95% CI 0.41–3.00], p = 0.03), and higher patient age (0.89 [95% CI 0.52–1.26], p < 0.0001). High SEPHmax is a strong predictor for tumour malignancy and a higher tumour grade and can be used to improve tumour characterisation before histopathological evaluation. It may also enable radiologists to identify lesions warranting observation rather than immediate biopsy.

Ultrasound is a highly effective imaging tool for assessing abnormalities within the breast. However, especially the identification of malignant tumors of the breast mimicking fibroadenomas (MTMF) by means of breast ultrasound can be challenging. This study aimed to identify reliable imaging characteristics of MTMF.This retrospective study was approved by the local ethics review board. After screening 623 patients, 421 cases with histologically verified fibroadenomas and MTMF between 2011 and 2021 were included. Sonographic features were compared to histopathological results and an algorithm-based quantitative ranking of predictors contributing most to the correct classification of malignant tumors was conducted.A total of 363 benign, 18 intermediate, and 40 malignant lesions were analyzed. Algorithm-based quantitative ranking showed that the most predictive features indicating malignancy were a hyperechoic rim (gain ratio merit 0.135 ± 0.004), an irregular border (0.057 ± 0.002), perilesional stiffening (0.054 ± 0.002), pectoral contact (0.051 ± 0.003), an irregular shape (0.029 ± 0.001), and irregular vasculature (0.027 ± 0.002).Ultrasound findings for fibroadenomas vary, making identification of MTMF challenging. Features such as indistinct margins and increased perilesional echogenicity are predictors for malignancy and should be considered during sonographic evaluation of fibroadenomas and MTMF.