How Much Should I Record During a CEUS Examination? Practical Aspects of the “Real-Time” Feature of a Contrast Ultrasound Study

Deganello, Annamaria; Sellars, Maria E.; Yusuf, Gibran Timothy; Sidhu, Paul S.

doi:10.1055/a-0717-9582

Cited by 6 publications

(4 citation statements)

References 16 publications

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“…If the examination is made with continuous insonation for the whole 4-5 minutes, the US waves can destroy the "bubbles" and lead to a false aspect of malignancy. For this reason, the current recommendation is to insonate and continuously examine during the arterial phase and after this moment to examine discontinuously [15], to preserve the "bubbles" as much as possible. Detailed technical aspects have been clarified by experts in this field in a recent publication [16].…”

Section: Discussionmentioning

confidence: 99%

Contrast-Enhanced Ultrasound for the Characterization of Malignant versus Benign Focal Liver Lesions in a Prospective Multicenter Experience – The SRUMB Study

Sporea

Săndulescu

Şirli

et al. 2019

JGLD

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Aim: This study evaluated the accuracy of contrast-enhanced ultrasound (CEUS) for the differential diagnosis of benign vs. malignant focal liver lesions (FLL) in a real-life, multicenter experience. Methods: This prospective study, including 14 Romanian centers, was performed over a 6 year period (February 2011- April 2017) and included 2062 FLLs assessed by CEUS. Inclusion criteria were: newly diagnosed FLL on B-mode ultrasound, less than three lesions/patient, all FLLs evaluated by CEUS and by a second-line imaging technique (contrast enhanced CT or contrast enhanced MRI) or histology, considered as reference. The trial was registered in clinicaltrials.gov (Identifier NCT01329458). Results: From the 2062 FLLs included in the study, 57.2% (1179) were malignant and 42.8% (883) were benign. CEUS had 83.9% sensitivity (Se), 97.8% specificity (Sp), 98.1% positive predictive value (PPV), 82.2% negative predictive value (NPV) and a diagnostic accuracy (Ac) of 89.9% for the positive diagnosis of malignant lesions. For the benign lesions, CEUS had 97.8% Se, 83.9% Sp, 82.2% PPV, 98.1% NPV 89.9% Ac. The diagnostic performance of CEUS for hepatocellular carcinoma was 76.6% Se, 98.4% Sp, and 91.2% Ac; for hemangioma: 89.2% Se, 99% Sp, and 96.9% Ac and for metastases: 90.9% Se, 98.4% Sp, and 96.9% Ac. Conclusions: CEUS proved a high accuracy in differentiating the malignant vs. benign character of a FLL. It can be confidently used as a first line imaging method in daily practice.

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Section: Discussionmentioning

confidence: 99%

Contrast-Enhanced Ultrasound for the Characterization of Malignant versus Benign Focal Liver Lesions in a Prospective Multicenter Experience – The SRUMB Study

Sporea

Săndulescu

Şirli

et al. 2019

JGLD

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“…The examination should be performed with both the patient and the examiner in a comfortable position, with a view of the lesion in a longitudinal plane to allow continuous observation during respiration. The UCA is administered by an assistant, and the examination is recorded continuously for at least 60 seconds and still images thereafter [52]. The kidneys enhance rapidly and intensely after UCA administration, with potential to assess both the macroand the microvasculature, the former immediately after UCA arri-val.…”

Section: Ultrasound Examination Of Bosniak Cysts: Examination Techniquesmentioning

confidence: 99%

“…Any abnormal enhancement pattern, when compared with the marked enhancement of the cortex, should be observed for subsequent wash-out, thought to be an indicator of malignancy [4,36]. It is important to record the examination as a dynamic cine clip, and to review the examination carefully following completion of the examination [52].…”

Section: Ultrasound Examination Of Bosniak Cysts: Examination Techniquesmentioning

confidence: 99%

EFSUMB 2020 Proposal for a Contrast-Enhanced Ultrasound-Adapted Bosniak Cyst Categorization – Position Statement

et al. 2020

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The well-established Bosniak renal cyst classification is based on contrast-enhanced computed tomography determining the malignant potential of cystic renal lesions. Ultrasound has not been incorporated into this pathway. However, the development of ultrasound contrast agents coupled with the superior resolution of ultrasound makes it possible to redefine the imaging of cystic renal lesions. In this position statement, an EFSUMB Expert Task Force reviews, analyzes, and describes the accumulated knowledge and limitations and presents the current position on the use of ultrasound contrast agents in the evaluation of cystic renal lesions.

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“…across different sites and specialties, we believe that this is primarily due to three reasons. First, while hundreds of images are acquired for procedural guidance, only very few, if any, are archived [58]- [60], thereby suggesting a severe lack of meaningful data for researchers to work with. Second, learning targets beyond segmentation are not well established or defined.…”

Section: Intelligent Intra-operative Imaging a From Data Fusion To In...mentioning

confidence: 99%

CAI4CAI: The Rise of Contextual Artificial Intelligence in Computer-Assisted Interventions

et al. 2020

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Data-driven computational approaches have evolved to enable extraction of information from medical images with a reliability, accuracy and speed which is already transforming their interpretation and exploitation in clinical practice. While similar benefits are longed for in the field of interventional imaging, this ambition is challenged by a much higher heterogeneity. Clinical workflows within interventional suites and operating theatres are extremely complex and typically rely on poorly integrated intra-operative devices, sensors, and support infrastructures. Taking stock of some of the most exciting developments in machine learning and artificial intelligence for computer assisted interventions, we highlight the crucial need to take context and human factors into account in order to address these challenges. Contextual artificial intelligence for computer assisted intervention, or CAI4CAI, arises as an emerging opportunity feeding into the broader field of surgical data science. Central challenges being addressed in CAI4CAI include how to integrate the ensemble of prior knowledge and instantaneous sensory information from experts, sensors and actuators; how to create and communicate a faithful and actionable shared representation of the surgery among a mixed human-AI actor team; how to design interventional systems and associated cognitive shared control schemes for online uncertainty-aware collaborative decision making ultimately producing more precise and reliable interventions.Index Terms-Artificial intelligence, computer assisted interventions, interventional workflow, intra-operative imaging, surgical planning, data fusion, surgical scene understanding, contextaware user interface, machine and deep learning, surgical data science

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How Much Should I Record During a CEUS Examination? Practical Aspects of the “Real-Time” Feature of a Contrast Ultrasound Study

Cited by 6 publications

References 16 publications

Contrast-Enhanced Ultrasound for the Characterization of Malignant versus Benign Focal Liver Lesions in a Prospective Multicenter Experience – The SRUMB Study

Contrast-Enhanced Ultrasound for the Characterization of Malignant versus Benign Focal Liver Lesions in a Prospective Multicenter Experience – The SRUMB Study

EFSUMB 2020 Proposal for a Contrast-Enhanced Ultrasound-Adapted Bosniak Cyst Categorization – Position Statement

CAI4CAI: The Rise of Contextual Artificial Intelligence in Computer-Assisted Interventions

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