Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks.

AI automation could 'revolutionize' Crohn's Disease severity CT assessments
Machine learning models could help create a more standardized, reproducible and efficient way of grading Crohn’s disease severity in the small bowel based on CT imaging.
New publicly available deep learning model for CT organ segmentation in children shows promise
The model was developed and validated specifically for liver, spleen and pancreas segmentation, and outperformed a publicly available segmentation model already in use.
New research offers reminder of why ChatGPT should not be used for second opinions
Although these tools have proven themselves valuable in numerous settings, they must be used with caution, especially by patients and nonradiologist providers who may be seeking clarification on imaging reports.
GPT-4 confidently struggles on radiology exam
Image-based questions were significantly more challenging for the large language model to answer, despite the latest version now being capable of accepting image prompts.
AI improves CT assessments, boosts care for real-world heart patients
Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.

18F-FDG PET/CT radiomics nomogram provides detailed insight into neuroblastoma

Better risk stratification can improve clinical decision making and better outcomes, experts involved in the study explained in EJR.

July 21, 2022

Left, coronary CT angiography of a vessel showing plaque heavy calcium burden. Right, image showing color code of various types of plaque morphology showing the complexity of these lesions. The right image was processed using the FDA cleared, AI-enabled plaque assessment from Elucid.

Cardiac CT soft plaque assessment may offer paradigm shift for coronary disease screening

New artificial intelligence software that can evaluate coronary CT scans to automatically assess soft plaques were by far the biggest technology advance discussed at the Society of Cardiovascular Computed Tomography (SCCT) 2022 meeting.

July 20, 2022

Algorithm spots enteric tube misplacement on x-ray with great accuracy

The model was externally validated using more than 1,500 radiographs with real-world incidence of critically misplaced tubes.

July 18, 2022

Content-based AI system decreases read times by 31% while increasing accuracy

Using CBIRS decreased interpretation times despite the radiologists who utilized them having to review the additional information the system provided.

July 14, 2022

Commercial PE-detecting algorithm identifies incidental clots on CT

Experts involved in the study, which analyzed more than 3,000 CT scans, suggested that there could be a future role for the algorithm to assist radiologists in busy settings.

July 13, 2022

An example of the Aidoc alert via smartphone for an AI-detected, suspected aortic dissection. The AI alerts acute care team members automatically after the AI reviews the scans from the CT system before they are viewed by a radiologist to help speed response times.

Aidoc announces strategic hospital partnership that will advance AI in clinical settings

The software will be used for the triage and notification of intracranial hemorrhage (ICH), pulmonary embolism (PE) and c-spine fractures identified on CT imaging.

July 12, 2022

AI/radiologist combo improves breast cancer detection, decreases workloads

The new two-part AI system is based on a decision-referral approach and triages mammograms based on quantification of uncertainty.

July 11, 2022

AI boosts accuracy when discriminating between malignant and benign ovarian tumors on MRI

Out of three trained and tested models that incorporated varying features, the model that combined clinical and radiomics features to predict malignancy exceeded the others in accuracy, precision and sensitivity.

July 11, 2022

Around the web

Cardiovascular Business

AI improves CT assessments, boosts care for real-world heart patients

Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.

Cardiovascular Business

AI predicts cardiovascular risk during CT scans—no invasive tests or contrast required

Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans.

Radiology Business

Google teams with Bayer to address radiologist burnout via AI

"Gen AI can help tackle repetitive tasks and provide insights into massive datasets, saving valuable time," Thomas Kurian, CEO of Google Cloud, said Tuesday.