Sophia Khan

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 JACRVariance 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

DCGI Classifies Over 100 Medical Devices Linked To Radiology

In accordance with the intended use, risk associated with the device, and other parameters specified in the First Schedule of the Medical Devices Rules-2017, the Drugs Controller General of India (DCGI), Directorate General of Health Services, India’s central medical device regulator, the Central Drugs Standards Control Organization (CDSCO), has classified medical devices pertaining to interventional Radiology, Rehabilitation, Dermatological and Plastic Surgery, and Physical support.

 

Read the full list : https://medicaldialogues.in/news/industry/medical-devices/dcgi-classifies-over-100-medical-devices-linked-to-radiology-plastic-surgery-others-details-80594

India’s medical device market including medical imaging to be supported by reform and infrastructure

The Make In India initiative will be a long-term driver of local medical device manufacturing, Fitch Solutions has said. The scheme for the promotion of medical device parks will help develop the necessary infrastructure, providing 90 percent of the project cost in north-eastern and hilly states and 70 percent in other states.

In the short-term, diagnostic imaging will grow strongly throughout 2021 due to increased demand as a result of the Covid-19 pandemic, expanding by 40.8 percent in 2021 and returning to mid-single-digit growth from 2023, supported in the long-term by market advancements.

Read the full article: https://www.aninews.in/news/business/indias-medical-device-market-to-be-supported-by-reform-infrastructure-fitch20210807102211/

Hybrid PET/MRI spares 20% of brain tumor patients from unnecessary follow-up treatment

A molecular, hybrid imaging approach accurately detects malignant brain tumors while also preventing unnecessary invasive procedures, recently published research suggests.

Combined PET/MRI scanning with radiopharmaceuticals such as 18F-fluorethyl tyrosine (18F-FET) has proven to enhance diagnostic performance, but there’s less evidence such imaging impacts clinical decision-making. German researchers tested the approach in patients with brain tumors, reporting positive results.

Further studies considering these aspects might evaluate finally if 18F-FET PET/MR as a hybrid modality qualifies for evidence-based use in clinical routine.

Read the full article: https://www.healthimaging.com/topics/molecular/petmri-brain-tumor-patients-unnecessary-treatment

Robotic scanner that automates diagnostic imaging in the eye

Engineers and ophthalmologists at Duke University have developed a robotic imaging tool that can automatically detect and scan a patient’s eyes for markers of different eye diseases. By removing the need for highly trained technicians, the imaging tool could make it easier to diagnose eye diseases outside of specialized clinics

The new tool, which combines an imaging scanner with a robotic arm, can automatically track and image a patient’s eyes in less than a minute, and produce images that are as clear as the traditional scanners in specialized eye clinics.

Read the full article :

https://pratt.duke.edu/about/news/robotic-scanner-automates-diagnostic-imaging-eye

Emerging trends in the Treatment Planning Systems Market

Medical imaging software is considered one of healthcare’s fastest-growing segments inclusive of multiple image modalities.

The increasing prevalence of cancer is boosting demand for innovative treatment practices in oncology. There is rising adoption of artificial intelligence (AI) and machine learning (ML) into oncology processes. Radiotherapy is also is gaining popularity as one of the prominent and cost-effective treatment options. Although the global demand for radiology services is increasing, the rate of trained radiologists is only increasing at half its pace. Therefore there is a high demand for advanced image processing solutions. Three-dimensional image reconstruction and advanced radiotherapy are also anticipated to grow over the next few years.

Read the full article :

https://www.itnonline.com/article/analysis-treatment-planning-systems-market

MRI features can predict response to neoadjuvant chemotherapy for breast cancer

The Czarnota Research Team investigated whether pre-treatment T2-weighted magnetic resonance imaging can be used to predict response to neoadjuvant chemotherapy in breast cancer.

Pre-treatment T2-weighted MRI texture features can predict NAC response with reasonable accuracy. The study examined T2 non-contrast images in predicting the treatment response to NAC. They intend to expand the current study cohort to include a higher number of patients to perform more robust validation strategies, including consideration of external validation from a different institution.

Read the full article:

https://www.news-medical.net/news/20210806/MRI-texture-features-can-predict-response-to-neoadjuvant-chemotherapy-in-patients-with-breast-cancer.aspx