Contrast-enhanced ultrasound in evaluation of adrenal lesions with CT/MRI correlation

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

PURPOSE

Ultrasound's versatility and ease of use has expanded its application in many clinical settings. Technological advancements with contrast-enhanced ultrasound (CEUS) have allowed high quality imaging similar to CT or MRI with lower risk of contrast toxicity and radiation exposure. In this review article we examine the development of CEUS and its vast applications in the field of urology.

METHODS

A PubMed literature search was performed using keywords: contrast enhanced ultrasound, prostate cancer, renal cancer, and multiparametric ultrasound.

RESULTS

The development of CEUS has improved transrectal ultrasound imaging with increased detection of prostate cancer (PCa). Further enhancements of CEUS such as subharmonic imaging (SHI), flash replenishment imaging (FRI) and contrast ultrasound dispersion imaging (CUDI) allow improved PCa diagnosis. CEUS has also emerged as an important tool in characterizing suspicious renal mass without compromising renal function with contrast imaging.

CONCLUSION

CEUS has modernized imaging and diagnosis of prostate and renal cancer. Future advancements and utilization of CEUS will allow its expansion into other urological subspecialties.

Binary Particle Swarm Optimization Intelligent Feature Optimization Algorithm-Based Magnetic Resonance Image in the Diagnosis of Adrenal Tumor

This research was aimed to explore the application value of magnetic resonance imaging (MRI) based on binary particle swarm optimization algorithm (BPSO) in the diagnosis of adrenal tumors. 120 patients with adrenal tumors admitted to the hospital were selected and randomly divided into the control group (conventional MRI examination) and the observation group (MRI examination based on the BPSO intelligent feature optimization algorithm), with 60 cases in each group. The sensitivity, specificity, accuracy, and Kappa of the diagnostic methods were compared between the two groups. The results showed that the calculation rate of the BPSO algorithm was the best under the same processing effect (P < 0.05). Optimization algorithm-based MRI is used in the diagnosis of adrenal tumors, and the results showed that the sensitivity, specificity, accuracy, and Kappa (83.33%, 79.17%, 81.67%, and 0.69) of the observation group were higher than those of the control group (50%, 75%, 58.33%, and 0.45). The similarity of tumor location results in the observation group (89.24%) was significantly higher than that in the control group (65.9%) (P < 0.05). In conclusion, compared with SFFS and other algorithms, the BPSO algorithm has more advantages in calculation speed. MRI based on the BPSO intelligent feature optimization algorithm has a good diagnostic effect and higher accuracy in adrenal tumors, showing the good development prospects of computer intelligence technology in the field of medicine.