823 Multiparametric ultrasound of the prostate: A new imaging approach using contrast enhanced transrectal ultrasound in combination with real-time elastography to detect prostate cancer

В обзоре литературы рассматривается применение различных модальностей трансректального ультразвукового исследования в диагностике рака предстательной железы. Представлена диагностическая эффективность В-режима (включая микроультразвуковое исследование, использующее сверхвысокие частоты), различных методов оценки кровотока (включая микродопплеровское картирование), гистосканирования, эластографии (качественный и количественный анализ), контрастного усиления (качественный и количественный анализ). Показана роль магнитно-резонансного и ультразвукового совмещения (фьюжен) при биопсии предстательной железы. Обсуждаются перспективы объединения различных ультразвуковых методов в мультипараметрическое трансректальное ультразвуковое исследование, возможности создания стандартизированных шкал для описания выявленных изменений. Имеющиеся данные подтверждают, что использование современных технологий трансректального ультразвукового исследования значительно повышает его диагностическую точность, в том числе в выявлении клинически значимого рака предстательной железы. Ключевые слова: трансректальное ультразвуковое исследование (ТРУЗИ), допплеровское исследование, ультразвуковое исследование с контрастным усилением, ультразвуковая эластография, микродопплеровское картирование, микроультразвуковое исследование, мультипараметрическое ультразвуковое исследование, магнитно-резонансное и ультразвуковое совмещение (фьюжен), рак предстательной железы; transrectal ultrasound (TRUS), Doppler ultrasound, contrast-enhanced ultrasound (CEUS), ultrasound elastography, micro-Doppler, micro-ultrasound, multiparametric ultrasound, magnetic resonance/transrectal ultrasound fusion (MRI/TRUS fusion), prostate cancer.

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Automated multiparametric localization of prostate cancer based on B-mode, shear-wave elastography, and contrast-enhanced ultrasound radiomics

European Radiology ◽

10.1007/s00330-019-06436-w ◽

2019 ◽

Vol 30 (2) ◽

pp. 806-815 ◽

Cited By ~ 6

Author(s):

Rogier R. Wildeboer ◽

Christophe K. Mannaerts ◽

Ruud J. G. van Sloun ◽

Lars Budäus ◽

Derya Tilki ◽

...

Keyword(s):

Prostate Cancer ◽

Machine Learning ◽

Radical Prostatectomy ◽

Shear Wave ◽

Transrectal Ultrasound ◽

Shear Wave Elastography ◽

Contrast Enhanced Ultrasound ◽

Operating Characteristics ◽

Contrast Enhanced ◽

Multiparametric Ultrasound

Abstract Objectives The aim of this study was to assess the potential of machine learning based on B-mode, shear-wave elastography (SWE), and dynamic contrast-enhanced ultrasound (DCE-US) radiomics for the localization of prostate cancer (PCa) lesions using transrectal ultrasound. Methods This study was approved by the institutional review board and comprised 50 men with biopsy-confirmed PCa that were referred for radical prostatectomy. Prior to surgery, patients received transrectal ultrasound (TRUS), SWE, and DCE-US for three imaging planes. The images were automatically segmented and registered. First, model-based features related to contrast perfusion and dispersion were extracted from the DCE-US videos. Subsequently, radiomics were retrieved from all modalities. Machine learning was applied through a random forest classification algorithm, using the co-registered histopathology from the radical prostatectomy specimens as a reference to draw benign and malignant regions of interest. To avoid overfitting, the performance of the multiparametric classifier was assessed through leave-one-patient-out cross-validation. Results The multiparametric classifier reached a region-wise area under the receiver operating characteristics curve (ROC-AUC) of 0.75 and 0.90 for PCa and Gleason > 3 + 4 significant PCa, respectively, thereby outperforming the best-performing single parameter (i.e., contrast velocity) yielding ROC-AUCs of 0.69 and 0.76, respectively. Machine learning revealed that combinations between perfusion-, dispersion-, and elasticity-related features were favored. Conclusions In this paper, technical feasibility of multiparametric machine learning to improve upon single US modalities for the localization of PCa has been demonstrated. Extended datasets for training and testing may establish the clinical value of automatic multiparametric US classification in the early diagnosis of PCa. Key Points • Combination of B-mode ultrasound, shear-wave elastography, and contrast ultrasound radiomics through machine learning is technically feasible. • Multiparametric ultrasound demonstrated a higher prostate cancer localization ability than single ultrasound modalities. • Computer-aided multiparametric ultrasound could help clinicians in biopsy targeting.

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Contrast-Enhanced Transrectal Ultrasound in Focal Therapy for Prostate Cancer

Current Urology Reports ◽

10.1007/s11934-018-0836-6 ◽

2018 ◽

Vol 19 (10) ◽

Cited By ~ 3

Author(s):

Akbar N. Ashrafi ◽

Nima Nassiri ◽

Inderbir S. Gill ◽

Mittul Gulati ◽

Daniel Park ◽

...

Keyword(s):

Prostate Cancer ◽

Transrectal Ultrasound ◽

Focal Therapy ◽

Contrast Enhanced

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Multiparametric ultrasound and micro-ultrasound in prostate cancer: a comprehensive review

British Journal of Radiology ◽

10.1259/bjr.20210633 ◽

2021 ◽

Author(s):

Adriano Basso Dias ◽

Ciara O’Brien ◽

Jean-Michel Correas ◽

Sangeet Ghai

Keyword(s):

Prostate Cancer ◽

Specific Antigen ◽

Transrectal Ultrasound ◽

Digital Rectal Examination ◽

High Sensitivity ◽

Cost Effective ◽

Cognitive Fusion ◽

Clinically Significant ◽

Multiparametric Ultrasound ◽

Targeted Biopsies

Prostate cancer (PCa) is the most common non-cutaneous cancer diagnosed in males. Traditional tools for screening and diagnosis, such as prostate-specific antigen, digital rectal examination and conventional transrectal ultrasound (TRUS), present low accuracy for PCa detection. Multiparametric MRI has become a game changer in the PCa diagnosis pathway and MRI-targeted biopsies are currently recommended for males at risk of clinically significant PCa, even in biopsy-naïve patients. Recent advances in ultrasound have also emerged with the goal to provide a readily accessible and cost-effective tool for detection of PCa. These newer techniques include elastography and contrast-enhanced ultrasound, as well as improved B-mode and Doppler techniques. These modalities can be combined to define a novel ultrasound approach, multiparametric ultrasound. High frequency Micro-ultrasound has emerged as a promising imaging technology for PCa diagnosis. Initial results have shown high sensitivity of Micro-ultrasound in detecting PCa in addition to its potential in improving the accuracy of targeted biopsies, based on targeting under real-time visualization, rather than relying on cognitive/fusion software MRI-transrectal ultrasound-guided biopsy.

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