Key Highlights

Review the clinical application of PelvicAssist in pelvic floor ultrasound, including AI-assisted auto-alignment, levator hiatus measurement, and workflow standardization with HERA Z20

PelvicAssist Clinical Application & Workflow Benefits White Paper

This white paper presents the clinical application and workflow benefits of PelvicAssist, an AI-powered measurement feature integrated within Samsung’s HERA Z20 ultrasound system. Designed for pelvic floor ultrasound, PelvicAssist supports automated volume alignment and anatomical measurement in 3D/4D transperineal ultrasound examinations. The paper focuses on pelvic floor sonography for evaluating the levator ani muscle complex and related pelvic floor structures during rest, voluntary contraction, and Valsalva. It explains how standardized imaging and reproducible measurements can support the assessment of pelvic floor dysfunction, pelvic organ prolapse, levator hiatus changes, and puborectalis integrity.

Core Functionalities

PelvicAssist provides core functionalities including auto-alignment and auto-measurement of key levator hiatus parameters. These include:

ㆍ Levator hiatus area and circumference

ㆍ Anterior-posterior diameter and lateral diameter

ㆍ Bilateral levator-urethra gap measurements

The feature is designed to help clinicians streamline measurement workflows by automatically analyzing 3D pelvic floor ultrasound datasets.

Evaluation and Workflow Efficiency

The evaluation described in the white paper was performed using the HERA Z20 ultrasound system with a CMV1-10 transducer, following a standardized 4D pelvic floor acquisition protocol. The assessment included volumes acquired at rest, during voluntary pelvic floor contraction, and during the Valsalva maneuver across a cohort of 35 female subjects.

Results from the white paper highlight potential workflow benefits, including improved standardization, reduced operator-dependent variability, and faster measurement generation. In the described setting, PelvicAssist reduced the time required for dynamic assessment from approximately 25 seconds to approximately 10 seconds, representing about a 60% reduction compared with manual assessment.

Clinical Integration

By supporting consistent plane selection, automated segmentation, and rapid biometric measurement, PelvicAssist may help clinicians perform pelvic floor ultrasound assessments more efficiently in routine practice, research workflows, pelvic floor rehabilitation pathways, and educational settings. As with all clinical tools, healthcare professionals should rely on their own professional judgment when interpreting results and making clinical decisions.

To learn more about AI-assisted pelvic floor ultrasound and standardized levator hiatus measurement, access the PelvicAssist expert insights.

Key Highlights

Review how MV-Flow Vascularity Index supports intestinal ultrasound in ulcerative colitis, including bowel wall vascularity, BWT assessment, and standardized IUS monitoring.

Multiparametric Intestinal Ultrasound for Ulcerative Colitis Monitoring White Paper

This white paper outlines the clinical implementation of multiparametric intestinal ultrasound for ulcerative colitis monitoring, with a focus on MV-Flow Vascularity Index. It introduces how intestinal ultrasound can support noninvasive and repeatable assessment of inflammatory bowel disease by integrating bowel wall structure, vascularity, and adjunctive stiffness evaluation. The paper explains key IUS parameters used in ulcerative colitis assessment, including bowel wall thickness, wall layer stratification, edema, vascular dilatation, and bowel wall vascularity. It highlights the importance of standardized acquisition conditions, including patient position, compression, respiration, gain, PRF, low-velocity filters, and follow-up measurements at the same bowel segment whenever possible.

MV-Flow Microvascular Flow Imaging

MV-Flow, a microvascular flow imaging feature on Samsung’s V8 ultrasound system, is presented as a tool for visualizing low-velocity intramural bowel wall flow that may be difficult to detect with conventional color Doppler. The white paper discusses how MV-Flow can be used with semi-quantitative evaluation, such as Vascularity Index, to support bowel wall vascularity assessment in ulcerative colitis.

Practical Implementation & Reproducibility

The paper also describes practical implementation points for measuring Vascularity Index, including the need to standardize ROI placement and acquisition settings. In the author’s clinical practice, Vascularity Index is measured based on the following specific criteria to help improve reproducibility:

ㆍ Measured over a 1-cm length

ㆍ Includes the entire thickness of the anterior wall of the target bowel segment

Structure and Stiffness Evaluation

In addition to vascularity assessment, the paper addresses bowel wall structure and stiffness. Bowel wall thickness measurement is discussed as an operator-dependent process where future AI-assisted segmentation and measurement may help improve reproducibility and workflow. Shear-wave elastography is also introduced as an adjunctive parameter that may provide information related to chronic change, although its role in ulcerative colitis is described as less established than in Crohn’s disease.

Overall, the white paper positions MV-Flow as a feature that may support microvascular flow visualization in intestinal ultrasound for ulcerative colitis monitoring. When used with standardized imaging protocols and well-defined operational rules, MV-Flow Vascularity Index may help clinicians incorporate bowel wall vascularity assessment into routine IUS workflows.

This white paper evaluates mid-trimester ultrasound workflow efficiency using Live ViewAssist, a deep learning-based tool integrated into obstetric ultrasound platforms.

The study was a prospective observational analysis conducted at a single center, including 80 singleton pregnancies undergoing routine second trimester ultrasound at 19–24 weeks of gestation. All examinations followed ISUOG guidelines for fetal anatomy and biometry assessment. Each patient underwent two examinations: one performed conventionally by manual acquisition of all required views and another performed using Live ViewAssist.

Live ViewAssist automatically classifies fetal structures in real time, annotates images, performs measurements, and replaces suboptimal views during live scanning without requiring additional keystrokes. The software integrates existing tools such as ViewAssist, BiometryAssist, and HeartAssist to standardize plane acquisition and fetal biometry.

The primary outcome was total scan duration, measured from the first to the last acquired image. The median examination time was significantly longer with conventional ultrasound compared to Live ViewAssist (21 minutes [IQR 18–25] vs 10 minutes [IQR 8–12]; p < 0.01), representing a 52% reduction in scan time.

The findings suggest that AI-assisted mid-trimester ultrasound workflow may enhance efficiency, improve resource utilization, and support clinical practice, particularly in high-volume settings. The study focused on time efficiency rather than diagnostic accuracy and was conducted at a single center.

This white paper explores the clinical use of novel tools in fetal 3D ultrasound, focusing on EzVolume, Fetal Face Auto Detection (FAD), and PortraitVue to enhance fetal face visualization and workflow efficiency.

The paper outlines how 3D obstetric ultrasound plays a central role in evaluating fetal anatomy and facial structures, particularly when assessing anomalies. However, conventional 3D imaging may be limited by acoustic shadowing, suboptimal fetal position, and manual segmentation challenges.

EzVolume is presented as an AI-based automatic segmentation tool that identifies key fetal structures within a 3D volume dataset. By reducing manual interaction and simplifying volume navigation, it supports faster and more consistent analysis.

Fetal Face Auto Detection (FAD) automatically detects and isolates the fetal face within the acquired 3D volume. This reduces operator dependency and helps ensure accurate facial visualization even in technically challenging cases.

PortraitVue enhances 3D rendering by providing realistic surface visualization with improved depth perception and texture detail. This contributes to clearer depiction of facial contours and anatomical relationships.

Together, these tools aim to streamline 3D obstetric ultrasound workflow, reduce manual post-processing, and improve reproducibility in fetal face visualization. The paper emphasizes that integrating AI-assisted segmentation and rendering technologies may support more efficient examinations while maintaining diagnostic quality in fetal 3D ultrasound.

This white paper by Dr. Víctor García evaluates how transvaginal ultrasound for endometriosis can be optimized using the EzExam+ tool while adhering to the four-step IDEA consensus protocol.

Endometriosis is associated with significant diagnostic delay, often influenced by symptom normalization and variability in imaging expertise. Extended transvaginal ultrasound with bowel preparation is central to pre-surgical diagnosis, especially for detecting deep infiltrative endometriosis. However, the examination is complex, time-consuming, and requires systematic evaluation of multiple pelvic compartments.

In a prospective study of 120 patients, extended transvaginal ultrasound examinations were performed using a customized EzExam+ protocol aligned with the IDEA consensus. The tool enabled predefined sequencing of anatomical structures, automatic preset selection, standardized labeling, and automated measurement steps to support workflow consistency.

Patients were divided into two groups based on disease severity. The average examination time was 11 minutes 42 seconds for patients with mild findings and 14 minutes 41 seconds for those with more complex lesions, representing a 25 percent longer duration in advanced cases. All protocol steps were completed in every examination.

The results indicate that EzExam+ supports structured workflow, reduces manual input tasks, maintains logical examination order, and helps prevent omission of key structures. This approach may enhance efficiency and diagnostic completeness in extended transvaginal ultrasound for endometriosis.

This white paper by Prof. Giovanni Maconi presents a comprehensive overview of intestinal ultrasound in IBD using a multiparametric approach.

The document describes how multiparametric intestinal ultrasound integrates structural, vascular, and stiffness assessment to improve the diagnosis, monitoring, and phenotyping of Crohn’s disease and ulcerative colitis. Conventional bowel wall thickness measurement is first reviewed, highlighting intra- and inter-observer variability due to segment heterogeneity. To address this limitation, the white paper introduces BowelAssist, an AI-based tool that automatically segments the bowel wall layers and provides average BWT measurements within a defined ROI, improving reproducibility and efficiency.

For vascular assessment, the paper compares color Doppler with advanced microvascular imaging techniques such as MV-Flow and contrast-enhanced ultrasound. MV-Flow detects smaller vessels and quantifies vascular pixels within a defined ROI to generate a perfusion index, enhancing activity assessment. CEUS is described as particularly valuable for differentiating abscesses from inflammatory masses and evaluating perianal disease.

The evaluation of bowel stiffness is discussed using strain elastography and shear wave elastography. Strain elastography provides semi-quantitative stiffness ratios, while 2D shear wave elastography offers real-time quantitative stiffness measurements in kilopascals with reliability mapping to guide ROI placement.

The conclusion emphasizes that combining AI-based structural analysis, vascular imaging, and elastography allows for a more precise estimation of inflammation and fibrosis, supporting personalized therapy and disease monitoring in IBD patients.