In multiple datasets from a study involving reviewed data from over 2,700 bi-parametric magnetic resonance imaging (MRI) scans, a deep neural network demonstrated area under the receiver operating characteristic (AUROC) scores ranging from 87 to 89 percent for the detection of clinically significant prostate cancer.

The injectable authorized generic reportedly facilitates gallbladder imaging as well as X-ray imaging of the intestinal tract.

The InterView Fusion and InterView XP reportedly improve image quality for single-photon emission computed tomography (SPECT) and offer imaging tools specifically geared to common nuclear medicine studies ranging from bone imaging to cardiac assessment and lung imaging.

In a study cohort of patients undergoing pre-operative workup for transcatheter aortic valve replacement (TAVR), researchers found the use of photon-counting CT for ultra-high resolution coronary CT angiography had a 96 percent sensitivity rate and an 84 percent specificity rate for the detection of coronary artery disease (CAD).

Review the case study and test your knowledge to make the correct diagnosis.

While some may equate extra work hours as honorable self-sacrifice or dedication to patients, striving for an optimal balance of life and work is an individual choice that shouldn’t be criticized.

In multiple mammography datasets with the original radiologist-detected abnormality removed, deep learning detection of breast cancer had an average area under the curve (AUC) of 87 percent and an accuracy rate of 83 percent, according to research presented at the recent Society for Imaging Informatics in Medicine (SIIM) conference.

Catch up on the top radiology content of the past week.

In a recent video interview from the Society for Imaging Informatics in Medicine (SIIM) conference, Ali Tejani, M.D., discussed pertinent insights on leveraging the value of adjunctive artificial intelligence (AI)-enabled triage software for computed tomography (CT) scans with radiology workflow improvements to achieve “clinically meaningful change” for patients with incidental pulmonary emboli findings.

Combining multimodal imaging data and biopsy data, an artificial intelligence (AI) model provided enhanced sensitivity for defining prostate cancer tumor margins in comparison to conventional magnetic resonance imaging (MRI) assessments.

In a recent video interview, Stephen Rose, M.D., reviewed a variety of factors that can impact interpretation of breast imaging for women with breast implants and discussed recent research showing a 22 percent reduction in cancer detection rate for this population in comparison to women without breast implants.

Review the case study and test your knowledge to make the correct diagnosis.

In a new study involving over 400,000 women, researchers found that ultrasound screening was performed for 95.3 percent of women with dense breasts but only 21.7 percent of women with a first-degree family history of breast cancer.

For patients initially diagnosed with non-metastatic, castration-resistant prostate cancer, pelvic lymph node involvement and five or more polymetastases detected with prostate-specific membrane antigen (PSMA)/ positron emission tomography (PET) are significantly associated with lower overall survival rates, according to recently presented research at the American Society of Clinical Oncology (ASCO) conference.

When reviewing radiographs, computed tomography (CT) scans or magnetic resonance imaging (MRI) scans, do you still turn to mnemonics every now and then to jog your short-term memory?

Catch up on the top radiology content of the past week.

Researchers found that a deep convolutional neural network, incorporating B-mode ultrasound and shear wave elastography data, had nearly an 88 percent sensitivity rate for predicting neoadjuvant chemotherapy response in patients with breast cancer.

FIRMM-pix, a brain magnetic resonance imaging (MRI) software module recently launched at the International Society for Magnetic Resonance in Medicine (ISMRM) conference, reportedly employs visual biofeedback and gamification that coaches patients to stay still during brain MRI exams.

For the detection of obstructive coronary artery disease (CAD), stress cardiovascular magnetic resonance imaging (MRI) demonstrated a sensitivity rate of 81 percent and a specificity rate of 86 percent, according to a meta-analysis of 64 studies and data from 74,470 patients with stable chest pain.

Five artificial intelligence (AI) algorithms for mammography assessment were better at predicting breast cancer risk over five years than the Breast Cancer Surveillance Consortium (BCSC) risk model, according to new retrospective research involving over 13,000 women.