Technology | Computed Tomography (CT) | September 26, 2019

FDA Clears Modules of AI-Rad Companion Chest CT From Siemens Healthineers

Artificial intelligence-based software enables automated enhanced visualization of CT images of the lungs, heart and aorta

FDA Clears Modules of AI-Rad Companion Chest CT From Siemens Healthineers

September 26, 2019 — The U.S. Food and Drug Administration (FDA) has cleared three modules of AI-Rad Companion Chest CT, an intelligent software assistant from Siemens Healthineers that brings artificial intelligence (AI) to computed tomography (CT). They include the AI-Rad Companion Engine (K183272), Pulmonary (K183271) and Cardiovascular (K183268) modules. Representing the first intelligent assistant of the new AI-Rad Companion platform, AI-Rad Companion Chest CT helps radiologists interpret images of the thorax (chest) quickly with desired accuracy and precision, and automatically documents these findings as structured reports.

Although CT chest images are mainly assessed by radiologists with regard to the primary indication, these images contain additional clinically relevant information. The algorithms in AI-Rad Companion Chest CT were trained on extensive datasets and annotated by qualified clinical specialists to provide segmentation, measurement and highlighting of key anatomical structures, to support quantitative and qualitative analysis.

Using CT images of the chest, AI-Rad Companion Chest CT differentiates among various structures in that region – including the lungs, heart and aorta – highlights them individually, and marks and measures potential abnormalities, such as coronary calcifications. It supports a variety of tasks, including: 

  • Automated detection of lesions, localization of abnormalities and measurement of lung lesions
  • Quantification of per-lobe low-attenuation parenchyma; 
  • Enhanced visualization of lung lesions; 
  • Automated segmentation of lung lobes and enhanced visualization of low-attenuation parenchyma; 
  • Segmentation and measurement of maximum diameters of the thoracic aorta; 
  • Quantification of the total calcium volume in the coronary arteries; and 
  • Detection of nine anatomical landmarks as identified by American Heart Association (AHA) guidelines.

Based on the AI-supported analysis, AI-Rad Companion Chest CT automatically generates standardized, reproducible, and quantitative reports in Digital Imaging and Communications in Medicine (DICOM) SC format. In addition to reducing time spent on manual results documentation, these reports can be accessed by radiologists on the picture archiving and communication system (PACS) in the clinical routine. AI-Rad Companion Chest CT also highlights potentially clinically relevant changes that might otherwise remain unnoticed because they were not the primary indication for the exam.

AI-Rad Companion Chest CT is a cloud-based solution that has been tested and validated for CT scanners from Siemens Healthineers, GE Healthcare and Philips Healthcare. It uses certified, secure teamplay infrastructure and integrates seamlessly into existing clinical workflows.

For more information: www.siemens-healthineers.com

Related Content

#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2

Getty Images

Feature | Coronavirus (COVID-19) | April 07, 2020 | By Melinda Taschetta-Millane and Dave Fornell
In an effort to keep the imaging field updated on the latest information being released on coronavirus (COVID-19), th
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2  The first of three clinical scenarios presented to the panel with final recommendations. Mild features refer to absence of significant pulmonary dysfunction or damage. Pre-test probability is based upon background prevalence of disease and may be further modified by individual’s exposure risk. The absence of resource constraints corresponds to sufficient availability of personnel, personal protective equipment, COVID-19 testing, hospital beds, and/or ve

 The first of three clinical scenarios presented to the panel with final recommendations. Mild features refer to absence of significant pulmonary dysfunction or damage. Pre-test probability is based upon background prevalence of disease and may be further modified by individual’s exposure risk. The absence of resource constraints corresponds to sufficient availability of personnel, personal protective equipment, COVID-19 testing, hospital beds, and/or ventilators with the need to rapidly triage patients. Contextual detail and considerations for imaging with CXR (chest radiography) versus CT (computed tomography) are presented in the text. (Pos=positive, Neg=negative, Mod=moderate). [Although not covered by this scenario and not shown in the figure, in the presence of significant resources constraints, there is no role for imaging of patients with mild features of COVID-19.] Image courtesy of the journal Radiology

News | Coronavirus (COVID-19) | April 07, 2020
April 7, 2020 — A multinational consens...
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2 Chest CT findings of pediatric patients with COVID-19 on transaxial images. (a) Male, 2 months old, 2 days after symptom onset. Patchy ground-glass opacities GGO in the right lower lobe

Chest CT findings of pediatric patients with COVID-19 on transaxial images. Male, 2 months old, 2 days after symptom onset. Patchy ground-glass opacities GGO in the right lower lobe. Image courtesy of Radiology: Cardiothoracic Imaging

News | Coronavirus (COVID-19) | April 06, 2020
April 6, 2020 — Children and teenagers with COVID-19...
A recent study earlier this year in the journal Nature, which included researchers from Google Health London, demonstrated that artificial intelligence (AI) technology outperformed radiologists in diagnosing breast cancer on mammograms
Feature | Breast Imaging | April 06, 2020 | By Samir Parikh
A recent study earlier this year in the journal Nature,
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2 Sonogram taken under rib cage shows liver (grey) with curved diaphragm-lung border (white). Arrows point to vertical B lines (white) demonstrating diseased lung tissue. The more B lines the worse the disease. Healing is measured by reduction in the number of B lines.

Sonogram taken under rib cage shows liver (grey) with curved diaphragm-lung border (white). Arrows point to vertical B lines (white) demonstrating diseased lung tissue. The more B lines the worse the disease. Healing is measured by reduction in the number of B lines.

News | Coronavirus (COVID-19) | April 06, 2020
April 6, 2020 — Robert L.
Varian received FDA clearance for its Ethos therapy in February 2020. It is an adaptive intelligence solution that uses onboard AI in the treatment system to take the cone beam CT imaging on the system, compare it to the treatment plan and deliver an entire adaptive treatment plan in a typical 15-minute treatment time slot, from patient setup through treatment delivery.

Varian received FDA clearance for its Ethos therapy in February 2020, shown here displayed for the first time at ASTRO 2019. It is an adaptive intelligence solution that uses onboard AI in the treatment system to take the cone beam CT imaging on the system, compare it to the treatment plan and deliver an entire adaptive treatment plan in a typical 15-minute treatment time slot, from patient setup through treatment delivery.

Feature | Treatment Planning | April 03, 2020 | Dave Fornell, Editor
The traditional treatment planning process takes days to create an optimized radiation therapy delivery plan, but new
Recommended best practices for nuclear imaging departments under the COVIF-19 pandemic have been issues by the ASNC and SNMMI. #COVID19 #ASNC #SNMMI #Coronavirus #SARScov2
News | Coronavirus (COVID-19) | April 03, 2020
April 3, 2020 — A new guidance document on best practices to maintain safety and minimize contamination in nuclear im