Archive: 29 August 2021

Emerging AI application in diagnostic imaging

AI is a boon to the medical and healthcare industry. Right from diagnostics to surgeries and medical equipment, artificial intelligence is supporting the healing processes of many human lives. 

There are several use cases for AI and automation in the medical device industry. Companies are using machine learning to monitor patients using sensors and automating medicine delivery via connected apps, integrating AI-driven platforms in medical scanning devices to improve the clarity of images and screening, and utilizing IoT to improve patient monitoring and clinical outcomes.

Read the full article: https://www.analyticsinsight.net/ai-in-medical-devices-these-are-the-emerging-industry-application/

Radiologists routinely underestimate severity of rib fractures on CT

Radiologists routinely underestimate the severity of rib fractures on CT, surgeons claim in a new single-center study published this month. There is a significant discrepancy between how surgeons and radiologists describe the number, patterns and severity of rib displacement. 

Surgeons need to evaluate CT scans themselves in order to appropriately decide management strategies and (surgical stabilization of rib fractures) indications.

Read the full article: https://www.radiologybusiness.com/topics/imaging-informatics/radiologists-severity-rib-fractures-trauma-surgeons

Virtual reality helps radiology department reduce paitient anxiety during contrast delivery

Using virtual reality has helped one radiology department significantly reduce patients’ pain and anxiety tied to peripheral IV catheter placement, according to research.

Children can experience considerable discomfort and distress during the insertion of these devices, used for administering contrast agents, among other things. However, the University of California, Los Angeles, has found early success using a multisensory VR game to help calm kids during their imaging encounter.

Lead author Jeffrey Gold, PhD, and colleagues see promise using this technology in other aspects of radiology and beyond.

Read full article: https://www.radiologybusiness.com/topics/quality/virtual-reality-radiology-reduce-pain-anxiety

First TULSA Procedure Performed at Yale New Haven Hospital

On July 13, the first transurethral localized sonographic ablation (TULSA) procedure was performed at Yale New Haven Hospital.

TULSA is a minimally-invasive procedure, performed with the patient under anesthesia, to treat localized prostate cancer while protecting tissue surrounding the prostate. It uses heat generated by a high intensity ultrasound to kill cancer cells. MRI guidance and MR thermometry are used during the TULSA procedure.

Almost all other ablation technologies require transrectal ultrasound guidance, so TULSA is unique in that it ablates prostate tissue through the urethra.

Multiple studies have also shown this technology to have excellent efficacy in treating lower-grade prostate cancers because of its whole-gland approach, while maintaining a superior risk profile because of the treatment area precision that MRI guidance provides. 

Read more: https://medicine.yale.edu/news-article/first-tulsa-procedure-performed-at-yale-new-haven-hospital/

Removing patients’ misconceptions about radiology

Some patients have little understanding of the role of the radiologist or how it differs from the technologist. 

Belgian imaging providers have developed a novel animated video, explaining radiologists’ work and what to expect during their visit. Testing the intervention on almost 300 patients, researchers made marked progress in boosting patients’ familiarity with the profession.

The content also helped to moderate expectations, reduce anxiety and improve the overall patient experience.

This communication method has proven to be easy to understand, practical, and leads to a better patient waiting experience while decreasing anxiety according to the team.

Read more:  https://www.radiologybusiness.com/topics/quality/patient-misconceptions-radiology-waiting-room

Radiologists investigate learning curve for performing CT-guided thoracic biopsies

Radiologists need at least 32 CT-guided needle biopsies under their belts before they can accurately assess thoracic nodules, according to research.

CT-directed percutaneous transthoracic needle biopsies are commonly used to assess pulmonary abnormalities, yet current guidelines say little about how many training procedures are required before becoming proficient or how to assess radiologists’ performance.

Radiologists continued to learn even after reaching acceptable diagnostic performance levels, indicating check-ins may be needed well beyond training periods.

Read more : https://www.healthimaging.com/topics/interventional/radiologists-learning-curve-ct-guided-biopsies

Why radiologists should consider earlier follow-up imaging for Lung-RADS cases

New evidence out of Stanford suggests providers may want to consider ordering follow-up CTs for probably benign nodules earlier than is currently suggested. Doing so reduced mortality rates and prevented more deaths, among other health benefits. 

Utilizing five month follow-up for Lung-RADS 3 reduced mortality by 0.08% in men and 0.05% among women. Earlier care also averted deaths (36 male vs. 27 female), yielded more screen-detected cases (13 vs. 7, respectively) and lowered the number of combined low-dose CTs per 1 million people.

Further comparative cost-effectiveness analysis using trial data or simulated population are required to evaluate the impact of alternative diagnostic follow-up on cost-effectiveness analysis.

Read more : https://www.healthimaging.com/topics/oncology/radiologists-lung-rads-early-follow-imaging

How AI is assisting medical imaging

Medical imaging is a vital part of healthcare. The margin for error in this branch of healthcare is minimal. The likelihood of human error must be reduced or eliminated altogether. Therefore, using AI-powered systems for medical imaging makes sense from a health expert’s point of view.

Medical imaging systems are needed for detection and preventive screenings for malignant tumors in individuals.

Deep learning can be used in AI-powered medical imaging systems to make MRI scans swift and effective. Deep learning is used for MRI-related applications such as super-resolution, signal processing and image synthesis.

Read the full article : https://www.bbntimes.com/science/how-artificial-intelligence-is-assisting-medical-imaging

Women with benign breast disease after surgery less likely to follow annual imaging surveillance

Women with benign disease after breast-conserving surgery are significantly less likely to adhere to annual surveillance imaging, according to a new analysis published Thursday in JACR. Variance in postsurgical surveillance protocols—due to a lack of uniform recommendations— creates opportunities for lapses in adherence.

Women with benign breast disease were significantly less liable to stick with annual surveillance compared to those with breast cancer. Further exploration of the underlying causes resulting in this decrease in adherence for this specific patient population is required moving forward.

Read the full article : https://www.radiologybusiness.com/topics/quality/benign-breast-disease-surgery-annual-imaging-surveillance