The evolving role of contrast-enhanced ultrasound in urology: a review

Clinical application of radiomics for the prediction of treatment outcome and survival in patients with renal cell carcinoma: a systematic review

PURPOSE

The management of renal cell carcinoma (RCC) relies on clinical and histopathological features for treatment decisions. Recently, radiomics, which involves the extraction and analysis of quantitative imaging features, has shown promise in improving RCC management. This review evaluates the current application and limitations of radiomics for predicting treatment and oncological outcomes in RCC.

METHODS

A systematic search was conducted in Medline, EMBASE, and Web of Science databases or studies that used radiomics to predict response to treatment and survival outcomes in patients with RCC. The study quality was assessed using the Radiomics Quality Score (RQS) tools.

RESULTS

The systematic review identified a total of 27 studies, examining 6,119 patients. The most used imaging modality was contrast-enhanced abdominal CT. The reviewed studies extracted between 19 and 3376 radiomics features, including Histogram, Texture, Filter, or transformation method. Radiomics-based risk stratification models provided valuable insights into treatment response and oncological outcomes. All developed signatures demonstrated at least modest accuracy (AUC range: 0.55-0.99). The studies included in this analysis reported heterogeneous results regarding radiomics methods. The range of Radiomics Quality Score (RQS) was from - 5 to 20, with a mean RQS total of 9.15 ± 7.95.

CONCLUSION

Radiomics has emerged as a promising tool in the management of RCC. It offers the potential for improved risk stratification and response assessment. However, future trials must demonstrate the generalizability of findings to prospective cohorts before progressing towards clinical translation.

Diagnostic accuracy of qualitative and quantitative magnetic resonance imaging-guided contrast-enhanced ultrasound (MRI-guided CEUS) for the detection of prostate cancer: a prospective and multicenter study

PURPOSE

To evaluate the diagnostic value of MRI-guided contrast-enhanced ultrasound (CEUS) for prostate cancer (PCa) diagnosis, and characteristics of PCa in qualitative and quantitative CEUS.

MATERIAL AND METHODS

This prospective and multicenter study included 250 patients (133 in the training cohort, 57 in the validation cohort and 60 in the test cohort) who underwent MRI, MRI-guided CEUS and prostate biopsy between March 2021 and February 2023. MRI interpretation, qualitative and quantitative CEUS analysis were conducted. Multitree extreme gradient boosting (XGBoost) machine learning-based models were applied to select the eight most important quantitative parameters. Univariate and multivariate logistic regression models were constructed to select independent predictors of PCa. Diagnostic value was determined for MRI, qualitative and quantitative CEUS using the area under receiver operating characteristic curve (AUC).

RESULTS

The performance of quantitative CEUS was superior to that of the qualitative CEUS and MRI in predicting PCa. The AUC was 0.779 (95%CI 0.70-0.849), 0.756 (95%CI 0.638-0.874) and 0.759 (95%CI 0.638-0.879) of qualitative CEUS, and 0.885 (95%CI 0.831-0.940), 0.802 (95%CI 0.684-0.919) and 0.824 (95%CI 0.713-0.936) of quantitative CEUS in training, validation and test cohort, respectively. Compared with quantitative CEUS, MRI achieved less well performance for AUC 0.811 (95%CI 0.741-0.882, p = 0.099), 0.748 (95%CI 0.628-0.868, p = 0.539) and 0.737 (95%CI 0.602-0.873, p = 0.029), respectively. Moreover, the highest specificity of 80.6% was obtained by quantitative CEUS.

CONCLUSION

We developed a reliable method of MRI-guided CEUS that demonstrated enhanced performance compared to MRI. The qualitative and quantitative CEUS characteristics will contribute to improved diagnosis of PCa.

Acoustic response and ambient pressure sensitivity characterization of SonoVue for noninvasive pressure estimation

Subharmonic aided pressure estimation (SHAPE) is a noninvasive pressure measurement technique based on the pressure dependent subharmonic signal from contrast microbubbles. Here, SonoVue microbubble with a sulfur hexafluoride (SF6) core, was investigated for use in SHAPE. The study uses excitations of 25-700 kPa peak negative pressure (PNP) and 3 MHz frequency over eight pressurization cycles between atmospheric pressure and overpressures, ranging from 0 to 25 kPa (0 to 186 mm Hg). The SonoVue subharmonic response was characterized into two types. Unlike other microbubbles, SonoVue showed significant subharmonic signals at low excitations (PNPs, 25-400 kPa), denoted here as type I subharmonic. It linearly decreased with increasing overpressure (-0.52 dB/kPa at 100 kPa PNP). However, over multiple pressurization-depressurization cycles, type I subharmonic changed; its value at atmospheric pressure decreased over multiple cycles, and at later cycles, it recorded an increase in amplitude with overpressure (highest, +13 dB at 50 kPa PNP and 10 kPa overpressure). The subharmonic at higher excitations (PNP > 400 kPa), denoted here as type II subharmonic, showed a consistent decrease with the ambient pressure increase with strongest sensitivity of -0.4 dB/kPa at 500 kPa PNP.

Is multiparametric MRI always needed in biopsy-naïve patients with abnormal digital rectal examination? A single-institutional experience combining clinical and micro-ultrasonography-based factors to optimize prostate cancer detection

PURPOSE

To assess the diagnostic performance of microultrasound-targeted biopsy (microUSTBx) and systematic biopsy (SBx) in detecting clinically significant prostate cancer (csPCa) among men with abnormal digital rectal examination (DRE) and suspicious lesions at multiparametric magnetic resonance imaging (mpMRI), and to compare the diagnostic performance of this approach with a mpMRI-guided targeted biopsy (MTBx) plus SBx-based strategy.

METHODS

Biopsy-naïve men with suspicious lesions at mpMRI and abnormal DRE were prospectively evaluated between October 2017 and January 2023. csPCa detection rate by microUSTBx plus SBx and MTBx plus SBx was assessed and then compared by McNemar's test. The added value of prostate-specific antigen density (PSAd) was also evaluated.

RESULTS

Overall, 182 biopsy naïve men were included. MicroUSTBx plus SBx achieved comparable detection rate to MTBx plus SBx in diagnosis of ciPCa and csPCa (ciPCa: 9.3% [17/182] vs 10% [19/182]; csPCa: 63% [114/182] vs 62% [113/182]). MicroUSTBx outperformed MTBx (ciPCa: 5.5% [10/182] vs 6.0% [11/182]; csPCa: 57% [103/182] vs 54% [99/182]). Using microUSTBx plus SBx would have avoided 68/182 (37%) unnecessary mpMRI, while missing only 2/116 (1.7%) csPCa. The decision curve analysis of suspicious microUS plus PSAd ≥ 0.15 ng/ml showed higher net benefit in the ability to identify true positives and reduce the number of unnecessary prostate biopsy in this subcategory of patients.

CONCLUSIONS

The combination of microUSTBx and SBx showed equal diagnostic performance to an mpMRI-based approach in biopsy-naïve patients with an abnormal DRE. The combination of this approach with PSAd maximize the diagnostic accuracy while lowering the need for unnecessary biopsies.

Machine learning based on radiomics features combing B-mode transrectal ultrasound and contrast-enhanced ultrasound to improve peripheral zone prostate cancer detection

PURPOSE

To construct machine learning models based on radiomics features combing conventional transrectal ultrasound (B-mode) and contrast-enhanced ultrasound (CEUS) to improve prostate cancer (PCa) detection in peripheral zone (PZ).

METHODS

A prospective study of 166 men (72 benign, 94 malignant lesions) with targeted biopsy-confirmed pathology who underwent B-mode and CEUS examinations was performed. Risk factors, including age, serum total prostate-specific antigen (tPSA), free PSA (fPSA), f/t PSA, prostate volume and prostate-specific antigen density (PSAD), were collected. Time-intensity curves were obtained using SonoLiver software for all lesions in regions of interest. Four parameters were collected as risk factors: the maximum intensity (IMAX), rise time (RT), time to peak (TTP), and mean transit time (MTT). Radiomics features were extracted from the target lesions from B-mode and CEUS imaging. Multivariable logistic regression analysis was used to construct the model.

RESULTS

A total of 3306 features were extracted from seven categories. Finally, 32 features were screened out from radiomics models. Five models were developed to predict PCa: the B-mode radiomics model (B model), CEUS radiomics model (CEUS model), B-CEUS combined radiomics model (B-CEUS model), risk factors model, and risk factors-radiomics combined model (combined model). Age, PSAD, tPSA, and RT were significant independent predictors in discriminating benign and malignant PZ lesions (P < 0.05). The risk factors model combing these four predictors showed better discrimination in the validation cohort (area under the curve [AUC], 0.84) than the radiomics images (AUC, 0.79 on B model; AUC, 0.78 on CEUS model; AUC, 0.83 on B-CEUS model), and the combined model (AUC: 0.89) achieved the greatest predictive efficacy.

CONCLUSION

The prediction model including B-mode and CEUS radiomics signatures and risk factors represents a promising diagnostic tool for PCa detection in PZ, which may contribute to clinical decision-making.

Diagnostic accuracy of multiparametric ultrasound in the diagnosis of prostate cancer: systematic review and meta-analysis

OBJECTIVES

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.

CONCLUSION

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.

CRITICAL RELEVANCE STATEMENT

This study provides urologists and sonographers with useful data by summarizing the accuracy of multiparametric ultrasound in the detection of prostate cancer.

KEY POINTS

• 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.

Development and validation of a nomogram for predicting prostate cancer based on combining contrast-enhanced transrectal ultrasound and biparametric MRI imaging

Objectives

This study was to explore the feasibility of combining contrast-enhanced transrectal ultrasound (CE-TRUS) with biparametric MRI (CEUS-BpMRI) score for diagnosing prostate cancer (PCa).

Methods

A total of 183 patients with suspected PCa who underwent multiparametric MRI (Mp-MRI) and CE-TRUS were included. CEUS-BpMRI score was developed based on the results of Mp-MRI and CE-TRUS. The diagnostic performance was evaluated by the area under the curve (AUC). The diagnostic efficacy of the CEUS-BpMRI score, BpMRI score, and PI-RADS v2.1 score were compared. Total patients were randomly assigned to a training cohort (70%) or validation cohort (30%). A nomogram was constructed based on univariate and multivariate logistic regression. The model was evaluated by AUC and calibration curve.

Results

The diagnostic performance of CEUS-BpMRI score (AUC 0.857) was comparable to that of PI-RADS v2.1 (AUC 0.862) (P = 0.499), and both were superior to Bp-MRI score (AUC 0.831, P < 0.05). In peripheral zone lesions with Bp-MRI score of 3, there was no statistically significant difference between PI-RADS v2.1 score (AUC 0.728) and CEUS-BpMRI score (AUC 0.668) (P = 0.479). Multivariate analysis showed that age, total prostate specific antigen/free prostate specific antigen (F/T), time to peak (TTP), and CEUS-BpMRI score were independent factors. The AUC of the nomogram was 0.909 in the training cohort and 0.914 in the validation cohort.

Conclusions

CEUS-BpMRI score has high diagnostic efficacy for diagnosing PCa. A nomogram model established by combining age, F/T, TTP, and CEUS-BpMRI score can achieve the best predictive accuracy for PCa.

The diagnostic accuracy of micro-ultrasound for prostate cancer diagnosis: a review

PURPOSE

Micro-UltraSound (microUS) is a new imaging modality capable of identifying and targeting suspicious areas, which might further increase the diagnostic yield of prostate biopsy (PBx). Aim of this review is to provide insights into the usefulness of microUS for the sub-stratification of prostate cancer (PCa), clinically significant PCa (i.e., any Gleason score ≥ 7 PCa; csPCa) along with non-organ-confined disease in patients undergoing PBx.

METHODS

A PubMed literature search was performed using keywords: prostate cancer diagnosis, prostate cancer diagnosis surveillance, systematic biopsy, target biopsy, micro-ultrasound, and prostate risk identification using micro-ultrasound.

RESULTS

MicroUS could significantly improve multiparametric magnetic resonance imaging (mpMRI) findings by adding valuable anatomical and pathological information provided by real-time examination. Furthermore, microUS target biopsy could replace systematic biopsy in clinical practice by reducing the detection of clinically insignificant (ciPCa) and increasing that of csPCa. Finally, microUS may be useful in predicting the presence of non-organ confined PCa before radical prostatectomy and it could also be an effective add-on tool for patient monitoring within the active surveillance program.

CONCLUSION

MicroUS may represent an attractive step forward for the management of csPCa as a complementary or alternative tool to mpMRI. Nevertheless, further longitudinal studies are warranted, and the strength of the evidence is still suboptimal to provide clear recommendations for daily clinical practice.

Contrast-Enhanced Ultrasonography (CEUS) in Imaging of the Reproductive System in Dogs: A Literature Review

The use of contrast-enhanced ultrasound (CEUS) has been widely reported for reproductive imaging in humans and animals. This review aims to analyze the utility of CEUS in characterizing canine reproductive physiology and pathologies. In September 2022, a search for articles about CEUS in canine testicles, prostate, uterus, placenta, and mammary glands was conducted on PubMed and Scopus from 1990 to 2022, showing 36 total results. CEUS differentiated testicular abnormalities and neoplastic lesions, but it could not characterize tumors. In prostatic diseases, CEUS in dogs was widely studied in animal models for prostatic cancer treatment. In veterinary medicine, this diagnostic tool could distinguish prostatic adenocarcinomas. In ovaries, CEUS differentiated the follicular phases. In CEH-pyometra syndrome, it showed a different enhancement between endometrium and cysts, and highlighted angiogenesis. CEUS was shown to be safe in pregnant dogs and was able to assess normal and abnormal fetal-maternal blood flow and placental dysfunction. In normal mammary glands, CEUS showed vascularization only in diestrus, with differences between mammary glands. CEUS was not specific for neoplastic versus non-neoplastic masses and for benign tumors, except for complex carcinomas and neoplastic vascularization. Works on CEUS showed its usefulness in a wide spectrum of pathologies of this non-invasive, reliable diagnostic procedure.