Atherosclerotic disease of the carotid arteries is a crucial risk factor in predicting the likelihood of future stroke events. In addition, emerging studies suggest that carotid stenosis may also be an indicator of plaque load on coronary arteries and thus have a correlation with the risk of acute cardiovascular events. Furthermore, although in symptomatic patients the degree of stenosis is the main morphological parameter studied, recent evidence suggests, especially in asymptomatic patients, that plaque vulnerability should also be evaluated as an emerging and significant imaging parameter. The reference diagnostic methods for the evaluation of carotid stenosis are currently ultrasonography, magnetic resonance imaging (MRI), and computed tomography angiography (CTA). In addition, other more invasive methods such as 123I-metaiodobenzylguanidine (MIBG) scintigraphy and PET-CT, as well as digital subtraction angiography, can be used. Each method has advantages and disadvantages, and there is often some confusion in their use. For example, the usefulness of MRI is often underestimated. In addition, implementations for each method have been developed over the years and are already enabling a significant increase in diagnostic accuracy. The purpose of our study is to make an in-depth analysis of all the methods in use and in particular their role in the diagnostic procedure of carotid stenosis, also discussing new technologies.

OBJECTIVE: A deep neural network (DNN) was trained to generate a multiparametric ultrasound (mpUS) volume from four input ultrasound-based modalities (acoustic radiation force impulse [ARFI] imaging, shear wave elasticity imaging [SWEI], quantitative ultrasound-midband fit [QUS-MF], and B-mode) for the detection of prostate cancer.
METHODS: A DNN was trained using co-registered ARFI, SWEI, MF, and B-mode data obtained in men with biopsy-confirmed prostate cancer prior to radical prostatectomy (15 subjects, comprising 980,620 voxels). Data were obtained using a commercial scanner that was modified to allow user control of the acoustic beam sequences and provide access to the raw image data. For each subject, the index lesion and a non-cancerous region were manually segmented using visual confirmation based on whole-mount histopathology data.
RESULTS: In a prostate phantom, the DNN increased lesion contrast-to-noise ratio (CNR) compared to a previous approach that used a linear support vector machine (SVM). In the in vivo test datasets (n = 15), the DNN-based mpUS volumes clearly portrayed histopathology-confirmed prostate cancer and significantly improved CNR compared to the linear SVM (2.79 ± 0.88 vs. 1.98 ± 0.73, paired-sample t-test p < 0.001). In a sub-analysis in which the input modalities to the DNN were selectively omitted, the CNR decreased with fewer inputs; both stiffness- and echogenicity-based modalities were important contributors to the multiparametric model.
CONCLUSIONS: The findings from this study indicate that a DNN can be optimized to generate mpUS prostate volumes with high CNR from ARFI, SWEI, MF, and B-mode and that this approach outperforms a linear SVM approach.

OBJECTIVE: To assess the value of 3D multiparametric ultrasound imaging, combining hemodynamic and tissue stiffness quantifications by machine learning, for the prediction of prostate biopsy outcomes.
METHODS: After signing informed consent, 54 biopsy-naïve patients underwent a 3D dynamic contrast-enhanced ultrasound (DCE-US) recording, a multi-plane 2D shear-wave elastography (SWE) scan with manual sweeping from base to apex of the prostate, and received 12-core systematic biopsies (SBx). 3D maps of 18 hemodynamic parameters were extracted from the 3D DCE-US quantification and a 3D SWE elasticity map was reconstructed based on the multi-plane 2D SWE acquisitions. Subsequently, all the 3D maps were segmented and subdivided into 12 regions corresponding to the SBx locations. Per region, the set of 19 computed parameters was further extended by derivation of eight radiomic features per parameter. Based on this feature set, a multiparametric ultrasound approach was implemented using five different classifiers together with a sequential floating forward selection method and hyperparameter tuning. The classification accuracy with respect to the biopsy reference was assessed by a group-k-fold cross-validation procedure, and the performance was evaluated by the Area Under the Receiver Operating Characteristics Curve (AUC).
RESULTS: Of the 54 patients, 20 were found with clinically significant prostate cancer (csPCa) based on SBx. The 18 hemodynamic parameters showed mean AUC values varying from 0.63 to 0.75, and SWE elasticity showed an AUC of 0.66. The multiparametric approach using radiomic features derived from hemodynamic parameters only produced an AUC of 0.81, while the combination of hemodynamic and tissue-stiffness quantifications yielded a significantly improved AUC of 0.85 for csPCa detection (p-value < 0.05) using the Gradient Boosting classifier.
CONCLUSIONS: Our results suggest 3D multiparametric ultrasound imaging combining hemodynamic and tissue-stiffness features to represent a promising diagnostic tool for biopsy outcome prediction, aiding in csPCa localization.

BACKGROUND: Prostate cancer is a prevalent cancer among men. Multiparametric ultrasound [mpUS] is a diagnostic instrument that uses various types of ultrasounds to diagnose it. This systematic review aims to evaluate the performance of different parametric ultrasounds in diagnosing prostate cancer by associating with radical prostatectomy specimens.
METHODS: A review was performed on various ultrasound parameters using five databases. Systematic review tools were utilized to eliminate duplicates and identify relevant results. Reviewers used the Quality Assessment of Diagnostic Accuracy Results [QUADAS-2] to evaluate the bias and applicability of the study outcomes.
RESULTS: Between 2012 and 2023, eleven studies were conducted to evaluate the performance of the different ultrasound parametric procedures in detecting prostate cancer using grayscale TRUS, SWE, CEUS, and mpUS. The high sensitivity of these procedures was found at 55%, 88.6%, 81%, and 74%, respectively. The specificity of these procedures was found to be 93.4%, 97%, 88%, and 59%, respectively. This high sensitivity and specificity may be associated with the large lesion size. The studies revealed that the sensitivity of these procedures in diagnosing clinically significant prostate cancer was 55%, 73%, 70%, and 74%, respectively, while the specificity was 61%, 78.2%, 62%, and 59%, respectively.
CONCLUSIONS: The mpUS procedure provides high sensitivity and specificity in PCa detection, especially for clinically significant prostate cancer.

Hyperthyroidismis a prevalent condition affecting global populations, with an overall prevalence of 1.2%. Our research aimed to establish a systematic diagnostic approach using multiparametric ultrasound (MPUS) to diagnose hyperthyroid diffuse thyroid disease (DTD).
We conducted a retrospective study from June 2021 to June 2023 at a specialized endocrinology center in Timisoara, Romania, enrolling subjects presenting with clinical hyperthyroidism. Using the Mach 30 Aixplorer ultrasound equipment, evaluations were performed initially in B-mode US, followed by Color Doppler and Spectral Doppler measurements, and finally, 2D Shear wave elastography (SWE).
From the 218 patients analyzed, the diagnosis of DTD with hyperthyroidism was confirmed through biochemical assessment, subgrouping various pathologies such as subacute thyroiditis, Graves\' disease, painless thyroiditis, Hashimoto\'s thyroiditis, iatrogenic, as well as healthy controls. In the first step, B-mode hypoechogenicity had an AUC of 0.951 for DTD detection. In the second step, the peak systolic velocity differentiated Graves\' disease with a median of 42.4 cm/s and an AUC of 1. Lastly, the third step consisted of SWE evaluation, revealing a mean elasticity index in the SAT subgroup significantly higher from other subgroups (p<0.001) with an AUC of 1.
Our study offers a step-by-step evaluation algorithm for DTD diagnosis, with a very good overall diagnostic performance (AUC of 0.946).

OBJECTIVE: Ultrasound (US) technology has recently made advances that have led to the development of modalities including elastography and contrast-enhanced ultrasound. The use of different US modalities in combination may increase the accuracy of PCa diagnosis. This study aims to assess the diagnostic accuracy of multiparametric ultrasound (mpUS) in the PCa diagnosis.
METHODS: Through September 2023, we searched through Cochrane CENTRAL, PubMed, Embase, Scopus, Web of Science, ClinicalTrial.gov, and Google Scholar for relevant studies. We used standard methods recommended for meta-analyses of diagnostic evaluation. We plot the SROC curve, which stands for summary receiver operating characteristic. To determine how confounding factors affected the results, meta-regression analysis was used.
RESULTS: Finally, 1004 patients from 8 studies that were included in this research were examined. The diagnostic odds ratio for PCa was 20 (95% confidence interval (CI), 8-49) and the pooled estimates of mpUS for diagnosis were as follows: sensitivity, 0.88 (95% CI, 0.81-0.93); specificity, 0.72 (95% CI, 0.59-0.83); positive predictive value, 0.75 (95% CI, 0.63-0.87); and negative predictive value, 0.82 (95% CI, 0.71-0.93). The area under the SROC curve was 0.89 (95% CI, 0.86-0.92). There was a significant heterogeneity among the studies (p < 0.01). According to meta-regression, both the sensitivity and specificity of mpUS in the diagnosis of clinically significant PCa (csPCa) were inferior to any PCa.
CONCLUSIONS: The diagnostic accuracy of mpUS in the diagnosis of PCa is moderate, but the accuracy in the diagnosis of csPCa is significantly lower than any PCa. More relevant research is needed in the future.
UNASSIGNED: This study provides urologists and sonographers with useful data by summarizing the accuracy of multiparametric ultrasound in the detection of prostate cancer.
CONCLUSIONS: • Recent studies focused on the role of multiparametric ultrasound in the diagnosis of prostate cancer. • This meta-analysis revealed that multiparametric ultrasound has moderate diagnostic accuracy for prostate cancer. • The diagnostic accuracy of multiparametric ultrasound in the diagnosis of clinically significant prostate cancer is significantly lower than any prostate cancer.

BACKGROUND: Enlarged cervical lymph nodes (CLNs) can result from infection or malignancies, and a definitive diagnosis requires histological examination. Ultrasound (US) remains the first-line imaging modality for detection, and new US techniques may improve characterization. The aim of our study was to investigate whether the qualitative assessment of multiparametric US (mpUS) can improve diagnostic performance in the differentiation of benign and malignant CLNs.
METHODS: 107 CLNs in 105 patients were examined by preoperative mpUS consisting of B-mode US, color-coded duplex sonography (CCDS), shear wave elastography (SWE) and contrast-enhanced US (CEUS). US images were evaluated in consensus by two experienced US operators. Histopathological examination was used as reference standard.
RESULTS: SWE and CEUS combined showed the highest overall diagnostic performance (91% sensitivity, 77% specificity, 87% positive predictive value (PPV), 83% negative predictive value (NPV), 90% accuracy, χ2 (1) = 51.485, p < 0.001) compared to B-mode US and CCDS (87% sensitivity, 44% specificity, 73% PPV, 65% NPV, 73% accuracy χ2 (1) = 12.415, p < 0.001). In terms of individual techniques, SWE had higher specificity than B-mode and CCDS (71% sensitivity, 90% specificity, 92% PPV, 64% NPV, 78% accuracy, χ2 (1) = 36.115, p < 0.001), while qualitative CEUS showed the best diagnostic performance of all investigated US techniques (93% sensitivity, 85% specificity, 91% PPV, 87% NPV, 90% accuracy, χ2 (1) = 13.219, p < 0.001). Perfusion patterns, homogeneity, presence of necrosis, and malignancy differed significantly between malignant and benign CLNs (p < 0.001).
CONCLUSIONS: SWE and CEUS can facilitate the differentiation of inconclusive CLNs when performed to supplement B-mode US and CCDS. MpUS may thus aid the decision between surgery and a watch-and-scan strategy in enlarged CLNs.

The present study aimed to assess the diagnostic test accuracy of different ultrasound scanning technologies in the detection of prostate cancer. A systematic search was conducted using the Cochrane Guidelines for Screening and Diagnostic Tests. We performed a systematic search in the international databases PubMed, Medline, Ovid, Embase and Cochrane Library. Searches were designed to find all studies that evaluated Micro-US, mpUS, SWE and CEUS as the main detection modalities for prostate cancer. This study was registered with Research Registry of systematic review and meta-analysis. The QUADAS-2 tool was utilized to perform quality assessment and bias analysis. The literature search generated 1376 studies. Of these, 320 studies were screened for eligibility, with 1056 studies being excluded. Overall, 26 studies with a total of 6370 patients met the inclusion criteria. The pooled sensitivity for grayscale, CEUS, SWE, Micro-US and mpUS modalities were 0.66 (95% CI 0.54-0.73) 0.73 (95% CI 0.58-0.88), 0.82 (95% CI 0.75-0.90), 0.85 (95% CI 0.76-0.94) and 0.87 (95% CI 0.71-1.03), respectively. Moreover, the pooled specificity for grayscale, CEUS, SWE, Micro-US and mpUS modalities were 0.56 (95% CI 0.21-0.90), 0.78 (95% CI 0.67-0.88), 0.76 (95% CI 0.65-0.88), 0.43 (95% CI 0.28-0.59) and 0.68 (95% CI 0.54-0.81), respectively. In terms of sensitivity, substantial heterogeneity between studies was detected (I2 = 72%, p = 0.000 < 0.05). In relation to specificity, extreme heterogeneity was detected (I2 = 93%, p = 0.000 < 0.05). Some studies proved that advanced ultrasound modalities such as mpUS, Micro-US, shear-wave elastography, contrast enhanced and micro-ultrasound are promising methods for the detection of prostate cancer.

Contrast enhanced ultrasound (CEUS) has been widely implemented in clinical practice because of the enormous quantity of information it provides, along with its low cost, reproducibility, minimal invasiveness, and safety of the second-generation ultrasound contrast agents. To overcome the limitation of CEUS given by the subjective evaluation of the contrast enhancement behaviour, quantitative analysis of contrast kinetics with generation of time-intensity curves has been introduced in recent years. The quantification of perfusion parameters [named as dynamic-CEUS (D-CEUS)] has several applications in gastrointestinal neoplastic and inflammatory disorders. However, the limited availability of large studies and the heterogeneity of the technologies employed have precluded the standardisation of D-CEUS, which potentially represents a valuable tool for clinical practice in management of gastrointestinal diseases. In this article, we reviewed the evidence exploring the application of D-CEUS in gastrointestinal diseases, with a special focus on liver, pancreas, and inflammatory bowel diseases.

The development of new applications in ultrasound (US) imaging in recent years has strengthened the role of this imaging technique in the management of different pathologies, particularly in the setting of liver disease. Improved B-mode imaging (3D and 4D), contrast-enhanced US (CEUS) and especially US-based elastography techniques have created the concept of multiparametric ultrasound (MP-US), a term borrowed from radiological sectional imaging. Among the new elastography techniques, shear wave dispersion is a newly developed imaging technology which enables the assessment of the shear waves\' dispersion slope. The analysis of the dispersion qualities of shear waves might be indirectly related to the tissue viscosity, thus providing biomechanical information concerning the pathologic state of the liver such as necroinflammation. Some of the most recent US devices have been embedded with software that evaluate the dispersion of shear waves/liver viscosity. In this review, the feasibility and the clinical applications of liver viscosity are reviewed based on the preliminary findings of both animal and human studies.