Medical Imaging

Physicians utilize medical imaging to see inside the body to diagnose and treat patients. This includes computed tomography (CT), magnetic resonance imaging (MRI), X-ray, ultrasound, fluoroscopy, angiography,  and the nuclear imaging modalities of PET and SPECT. 

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An example of artificial intelligence (AI) automated detection of a intracranial hemorrhage (ICH) in. a CT scan used to send alerts to the stroke acute care team before a radiologist even sees the exam. Example shown by TeraRecon at RSNA 2022.

FDA has now cleared more than 500 healthcare AI algorithms

More than 500 clinical AI algorithms have now been cleared by the FDA, with the majority just in the past couple years.

Childhood exposure to 'toxic stress,' racial disparities shows up on MRI

Childhood adversity alters regions of the brain responsible for processing threats, according to a new neuroimaging study. 

An example of an FDA cleared radiology AI algorithm to automatically take a cardiac CT scan and identify, contour and quantify soft plaque in the coronary arteries. The Cleerly software then generates an automated report with images, measurements and a risk assessment for the patient. This type of quantification is too time consuming and complex for human readers to bother with, but AI assisted reports like this may become a new normal over the next decade. Example from Cleerly Imaging at SCCT 2022.

Legal considerations for artificial intelligence in radiology and cardiology

There are now more than 520 FDA-cleared AI algorithms and the majority are for radiology and cardiology, raising the question of who is liable if the AI gets something wrong.

Radiologist testifies on behalf of defense in murder trial

The neuroradiology specialist offered insight into the imaging findings of a 33-year-old man who is charged with two counts of premeditated first-degree murder. 

Brent Savoie, MD, JD, vice chair for radiology informatics, section chief of cardiovascular imaging, Vanderbilt University, explains who will get sued when there is a misdiagnosis due to artificial intelligence (AI).

VIDEO: Who gets sued when radiology AI fails?

Brent Savoie, MD, JD, vice chair for radiology informatics, section chief of cardiovascular imaging, Vanderbilt University, explains who will get sued when there is a misdiagnosis due to artificial intelligence (AI).

#obesity #alzheimersdisease #alzheimersresearch #neuroimaging #brainMRI

Obesity and Alzheimer's look similar on brain imaging, cause comparable neurodegeneration

New data suggest that both obesity and Alzheimer's can cause excess grey matter cortical thinning. 

Telemammography

4 key trends in breast imaging

These trends include growth in 3D mammography, supplemental imaging for women with dense breasts and in the role of artificial intelligence.

Example of various breast MRI protocol sequences that offer different types of soft tissue enhancement. Imaging performed on a Siemens Magnetom system. Breast MRI can help see through dense breast tissue to better detect cancers. #densebreasts #Breastdensity #BreastMRI

MRI a 'far superior' modality for dense breast imaging

The modality outperformed digital breast tomosynthesis, handheld ultrasound and automated breast ultrasound for cancer detection in a large cohort of women with dense breast tissue.

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Around the web

Cardiovascular Business
GE HealthCare launches new cardiac CT scanner with advanced AI capabilities

GE HealthCare designed the new-look Revolution Vibe CT scanner to help hospitals and health systems embrace CCTA and improve overall efficiency.

Cardiovascular Business
Bracco updates HeartSee coronary flow capacity software with new diagnostic features

Clinicians have been using HeartSee to diagnose and treat coronary artery disease since the technology first debuted back in 2018. These latest updates, set to roll out to existing users, are designed to improve diagnostic performance and user access.

Cardiovascular Business
Key trends in diagnostic heart testing: CT on the rise as some traditional techniques fall out of favor

The cardiac technologies clinicians use for CVD evaluations have changed significantly in recent years, according to a new analysis of CMS data. While some modalities are on the rise, others are being utilized much less than ever before.