X-Ray

Could adjustments to quality assurance review facilitate improved teamwork between radiologists and referring clinicians?

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

Catch up on the top AI-related news and research in radiology over the past month.

An emerging deep learning algorithm can reportedly triage 40 percent of no-change X-rays while providing 88 to 90 percent accuracy for detecting changes with X-rays obtained in the emergency department and intensive care unit at a tertiary referral hospital, according to recently published research.

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

The Allia IGS Pulse reportedly has the first monopolar X-ray tube geared to interventional procedures.

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

By leveraging subtle signals on routine X-rays to assess bone mineral density (BMD), the technology may facilitate earlier detection of osteoporosis and help prevent fragility fractures.

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

Integrating clinical data parameters along with chest X-ray findings, the multimodal artificial intelligence (AI) model outperformed the use of clinical parameters only and chest X-rays only for various conditions ranging from congestive heart failure and chronic kidney disease to hypertension and pneumonia.

Leveraging artificial intelligence (AI) algorithms, the qXR-CTR reportedly provides automated cardiothoracic ratios (CTRs) through assessment of plain chest radiographs.

Is the continued rise of artificial intelligence (AI) driven by legitimate “machine learning,” or do the frequently “suspicious” chest X-rays and questionable detection of subtle findings on head CTs reveal a hype-driven train of new products with an ultimately “planned obsolescence”?

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

In a multicenter study examining four commercially available artificial intelligence (AI) software products for chest X-rays in over 2,000 patients, researchers found sensitivity rates ranging between 33 to 61 percent for vague airspace disease and 9 to 94 percent for small pneumothorax and pleural effusion.

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While there may be awkwardness and a degree of embarrassment in noting obvious findings to referring clinicians in radiology, consistent communication of those findings is essential.

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

Catch up on the top AI-related news and research from the past month.

When facilities routinely forward X-rays for “pain,” vascular ultrasound studies without Doppler or chest computed tomography (CT) scans devoid of breath holding, patient care suffers.

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

The artificial intelligence (AI)-enabled VisiRad XR reportedly demonstrated an 83 percent sensitivity rate for detecting lung nodules and masses on chest X-rays in one retrospective study.

The notion of non-physician practitioners (NPPs) attempting to do radiologist-level work is a very slippery slope and what this author refers to as the “bargaining” stage of grief.

Noting recent double-digit increases in health-care associated infections (HAIs) and potential vulnerabilities in radiology departments, this author emphasizes proactive preventive measures to protect patients and staff.

Superfluous pan scans have become standard for a vast majority of minor injury presentations in emergency room settings.

While it stands to reason that referring physicians would prefer a condensed summary of relevant imaging findings, vagaries with insurers, patients and other possible readers of the radiology report may warrant an inefficient minutiae-cluttered approach.