Evaluating chest CTs can be a complex and time-consuming process. So we’ve packed contextflow ADVANCE Chest CT with qualitative and quantitative insights to help you objectively report on suspected ILD, COPD and lung cancer cases. Over time. From within your native viewer.
DETECT / Nodule Detection
- Detection & measurement of nodules from within your native viewer.
- Nodule characterization from Reveal-Dx proven to reduce false positives and flag at-risk patients sooner:
- 29% reduction in false positives*
- 45% increase in early diagnosis is possible*
- We detect and measure nodules in accordance with the following guidelines:
- British Thoracic Society guidelines for the investigation and management of pulmonary nodules
- European Union Position Statement on Lung Cancer Screening
- Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017
- International Early Lung Cancer Action Program: Screening Protocol, 2021
- Lung-RADS Version 1.1 2019
- Response Evaluation Criteria in Solid Tumors (RECIST)
- For USA only: the DETECT feature is currently under development as a standalone product – not yet cleared for clinical use.
TIMELINE / Nodule Tracking
- Tracks changes in detected nodules over time, regardless of the number of priors
- Indicates time-to-double or halve with intuitive colored graphs
- Helps to prepare for tumor boards and multidisciplinary board meetings
- TIMELINE is currently only available for nodule tracking. Tracking of disease patterns over time is coming in 2023.
INSIGHTS / Lung Tissue Analysis
- Anomaly heatmaps indicating overall distribution of disease patterns
- Quantification of total lung volume affected by disease patterns
- Quantification & individual heatmaps for 8 key image findings:
- Ground-glass opacity
SEARCH / 3D Image Search
- Detection & analysis of 19 image patterns
- Links to differential diagnosis literature
- Retrieval of similar cases to yours from a curated knowledge base
- Validated average report reading time savings 31%
We are very interested in using tools based on artificial intelligence like contextflow SEARCH to support the decision in the diagnostic process based on the image.
Lluís Donoso Bach
President of the International Society of Radiology
At Dubrava University Hospital, we take pride in providing the best care possible to our patients. There are many AI radiology solutions, but we agreed to the proof of concept with contextflow because their solution provides real value, particularly for new residents.
President of the European Society of Radiology
We’re very interested in using AI to improve the hospital experience for both doctors and patients; contextflow’s use of deep learning, particularly for lung diseases, is exactly the type of technology we want to evaluate. I very much look forward to the results.
Head of Radiology at Vienna General Hospital
I really like the transparency of contextflow SEARCH as opposed to other black box AI solutions. It’s designed to support my workflow while leaving the final decision up to me.
Vice Chair and Head of Imaging Informatics at the Department of Radiology at Freiburg University Medical Center
After using and advising several radiology AI software companies, I can say that what contextflow offers is actually the next generation of AI products to support the radiologist, not replace them. Their general approach means they recognize all relevant findings, not just one.
MD, Chief of Interventional Radiology, Providence Little Company of Mary Medical Centers
contextflow SEARCH Lung CT is one of the applications that certainly fits radiology’s current needs and can simplify the analysis of complex lung pathology. With the right insights and technology, we can succeed in introducing AI in a very attractive way to radiology departments on a global scale.
Former President of the European Society of Medical Imaging Informatics (EuSoMII), Radiologist at St. Nikolaus Hospital in Eupen
I have been following contextflow’s progress practically since the company’s founding, and their traction in the area of lung CT is impressive. Being able to shape clinical decision support tools that myself and colleagues can benefit from in clinical practice is a big motivator. We’re literally shaping the future.
Chief Medical Information Officer & Head of Imaging IT and Value-Based Imaging at Erasmus MC