AI-Guided Imaging Software Allows Nurses without Prior Ultrasound Experience to Capture Diagnostic Quality Images
|
By MedImaging International staff writers Posted on 23 Feb 2021 |

Image: AI-Guided Imaging Software (Photo courtesy of Caption Health)
A new study has demonstrated that ultrasound images captured by nurses using FDA-approved AI-guided medical imaging acquisition software without prior ultrasound experience and reviewed by experienced cardiologists were of diagnostic quality.
The study examined Caption Health’s (Brisbane, CA, USA) Caption AI platform, which includes Caption Guidance and Caption Interpretation, which is the first and only AI-guided medical imaging acquisition software to obtain FDA clearance, enabling a broad range of healthcare workers to perform cardiac ultrasound examinations at the point of care. The study demonstrated that ultrasound images captured by nurses without prior ultrasound experience and reviewed by experienced cardiologists were shown to be of diagnostic quality to assess left ventricular size and function in 98.8% of patients, right ventricular size and function in 92.5% of patients, and in 98.8% of patients for presence of pericardial effusion. The study was conducted with 240 patients aged 20-91, 42% female patients, with 17.6% of patients Black or African-American, and 33% of patients with a BMI of 30 or greater.
Each patient in the study underwent paired ultrasounds: one from a nurse, and one from an experienced registered diagnostic cardiac sonographer. In addition to evaluating diagnostic quality, the cardiologists also made diagnostic assessments. For the diagnostic assessments corresponding to the primary endpoints listed above, there was at least 92.5% agreement between the nurse and sonographer scans. The results indicated that Caption Guidance performed well for patients with various cardiac pathologies that might be encountered in real-world clinical practice; more than 90% of patients were found to have cardiac abnormalities in scheduled full echocardiograms performed within two weeks of the study. The results were also consistent across BMI, sex, and race, further demonstrating Caption Guidance's efficacy and robustness.
"This study shows that AI-guided imaging can expand healthcare professionals' skill sets in a meaningful way with minimal training - giving patients more opportunities to receive timely diagnostic care," said Yngvil Thomas, Head of Medical Affairs & Clinical Development at Caption Health.
"The study's remarkable agreement between nurses' scans and sonographers' scans shows that the use of AI like Caption Guidance could fundamentally change how we use medical imaging," said Dr. Akhil Narang, a cardiologist at Northwestern Medicine and first author on the paper. "This will extend the abilities of healthcare providers to evaluate for different pathologies in critical care, emergency departments and other settings - and perhaps identify them even earlier with the assistance of AI."
Related Links:
Caption Health
The study examined Caption Health’s (Brisbane, CA, USA) Caption AI platform, which includes Caption Guidance and Caption Interpretation, which is the first and only AI-guided medical imaging acquisition software to obtain FDA clearance, enabling a broad range of healthcare workers to perform cardiac ultrasound examinations at the point of care. The study demonstrated that ultrasound images captured by nurses without prior ultrasound experience and reviewed by experienced cardiologists were shown to be of diagnostic quality to assess left ventricular size and function in 98.8% of patients, right ventricular size and function in 92.5% of patients, and in 98.8% of patients for presence of pericardial effusion. The study was conducted with 240 patients aged 20-91, 42% female patients, with 17.6% of patients Black or African-American, and 33% of patients with a BMI of 30 or greater.
Each patient in the study underwent paired ultrasounds: one from a nurse, and one from an experienced registered diagnostic cardiac sonographer. In addition to evaluating diagnostic quality, the cardiologists also made diagnostic assessments. For the diagnostic assessments corresponding to the primary endpoints listed above, there was at least 92.5% agreement between the nurse and sonographer scans. The results indicated that Caption Guidance performed well for patients with various cardiac pathologies that might be encountered in real-world clinical practice; more than 90% of patients were found to have cardiac abnormalities in scheduled full echocardiograms performed within two weeks of the study. The results were also consistent across BMI, sex, and race, further demonstrating Caption Guidance's efficacy and robustness.
"This study shows that AI-guided imaging can expand healthcare professionals' skill sets in a meaningful way with minimal training - giving patients more opportunities to receive timely diagnostic care," said Yngvil Thomas, Head of Medical Affairs & Clinical Development at Caption Health.
"The study's remarkable agreement between nurses' scans and sonographers' scans shows that the use of AI like Caption Guidance could fundamentally change how we use medical imaging," said Dr. Akhil Narang, a cardiologist at Northwestern Medicine and first author on the paper. "This will extend the abilities of healthcare providers to evaluate for different pathologies in critical care, emergency departments and other settings - and perhaps identify them even earlier with the assistance of AI."
Related Links:
Caption Health
Latest Industry News News
- GE HealthCare Showcases AI-Enabled Nuclear Medicine Portfolio at SNMMI 2026
- GE HealthCare Highlights AI-Supported Radiation Therapy Tools at ESTRO 2026
- Nuclear Medicine Set for Continued Growth Driven by Demand for Precision Diagnostics
- GE HealthCare and NVIDIA Collaboration to Reimagine Diagnostic Imaging
- Patient-Specific 3D-Printed Phantoms Transform CT Imaging
- Siemens and Sectra Collaborate on Enhancing Radiology Workflows
- Bracco Diagnostics and ColoWatch Partner to Expand Availability CRC Screening Tests Using Virtual Colonoscopy
- Mindray Partners with TeleRay to Streamline Ultrasound Delivery
- Philips and Medtronic Partner on Stroke Care
- Siemens and Medtronic Enter into Global Partnership for Advancing Spine Care Imaging Technologies
- RSNA 2024 Technical Exhibits to Showcase Latest Advances in Radiology
- Bracco Collaborates with Arrayus on Microbubble-Assisted Focused Ultrasound Therapy for Pancreatic Cancer
- Innovative Collaboration to Enhance Ischemic Stroke Detection and Elevate Standards in Diagnostic Imaging
- RSNA 2024 Registration Opens
- Microsoft collaborates with Leading Academic Medical Systems to Advance AI in Medical Imaging
- GE HealthCare Acquires Intelligent Ultrasound Group’s Clinical Artificial Intelligence Business
Channels
Radiography
view channel
AI Tool Predicts Five-Year Breast Cancer Risk from Mammograms
Breast cancer risk assessment during routine screening is difficult because many women who develop the disease have no known genetic mutations or family history. Static risk tools provide limited discrimination... Read more
AI Mammography Tools Detect Early Breast Cancer Signs Years Before Diagnosis
Breast cancer screening aims to detect tumors before symptoms develop, but subtle mammographic changes can appear years before diagnosis and may be missed during routine reads. Delayed detection can lead... Read moreMRI
view channel
Advanced MRI Reveals Structural Brain Changes Linked to Better Cognitive Health
Objective, noninvasive measures that capture subtle, training-related changes in adult brain structure remain limited in routine clinical practice. Quantifying neuroplasticity with precision is especially... Read more
Cardiac MRI Detects Hidden Heart Dysfunction After Heart Attack
Myocardial infarction often leaves patients with persistent ventricular dysfunction that can progress without obvious signs. Detecting early decline remains difficult because standard measures may miss... Read moreUltrasound
view channel
Simple 2D Ultrasound Tool Accurately Estimates Placental Volume
Stillbirth remains a major cause of perinatal loss, with about 21,000 cases annually in the United States. Although placental abnormalities are linked to adverse pregnancy outcomes, routine monitoring... Read more
Portable 3D Ultrasound System Enables Reproducible Breast Cancer Monitoring
Breast cancer can develop between annual mammograms, and these interval cancers account for 20% to 30% of cases and tend to be more aggressive. The challenge is pronounced in people with dense breast tissue.... Read moreNuclear Medicine
view channel
Radiotherapy Professionals Embrace AI as a Clinical Support Tool
Radiotherapy planning requires precise identification of organs at risk near a tumor, but manual contouring is repetitive and time-consuming, often delaying plan completion and straining specialist capacity.... Read more
Second PSMA PET Identifies Disease in More Than Half of Negative Cases
Biochemical recurrence of prostate cancer after prostatectomy or radiation can be difficult to localize when imaging is negative. Uncertain disease sites may delay salvage therapy and expose patients to... Read moreGeneral/Advanced Imaging
view channel
New PE-RADS Framework Standardizes Pulmonary Embolism Imaging Reports
Pulmonary embolism is a sudden blockage of the lung’s blood vessels that reduces pulmonary blood flow, can strain the right hear,t and may be fatal if untreated. Patients often present with shortness of... Read more
Virtual Staining Technique Creates Histology Images from CT Data
Pulmonary hypertension, a disorder marked by pathological remodeling of the pulmonary vessels, often requires detailed histologic assessment. Yet routine pathology remains anchored in labor‑intensive,... Read more
CT-Derived Biomarker Predicts Outcomes in Gastric Cancer
Gastric cancer, also known as stomach cancer, is the fifth most common malignancy worldwide and often shows heterogeneous outcomes even within the same stage. Prognostic estimates typically rely on tumor-centric... Read more
AI Tool Enhances Response Assessment and Survival Prediction in Pleural Mesothelioma
Pleural mesothelioma, a cancer that grows as a thin, irregular layer along the lung wall, is difficult to measure on imaging. Clinicians rely on diameter-based Response Evaluation Criteria in Solid Tumors... Read moreImaging IT
view channel
Ambient AI Reporting Platform Streamlines Radiology Reporting
Radiology departments face growing imaging volumes and staffing shortages, creating reporting bottlenecks and pressure to maintain turnaround times. Conventional dictation tools document findings after... Read more
Interactive AI Tool Supports Explainable Lung Nodule Assessment
Lung cancer is a leading cause of cancer mortality, and timely characterization of pulmonary nodules on chest computed tomography (CT) is essential for directing care. Interpreting nodule morphology demands... Read more







