Whole-spine MRI uncovers abusive head trauma injuries in children

Whole-spine MRI uncovers abusive head trauma injuries in children

Indiana University researchers analyzed imaging data on injuries in children seen at Riley Children’s Hospital in Indianapolis with suspected abusive head trauma. They found whole-spine MRI procedures showed additional abnormalities not identified on cervical spine MRI exams.

Performing MRI of the whole spine in young children thought to be victims of abusive head trauma can help detect injuries that may be missed on regular imaging.

Read more: https://www.auntminnie.com/index.aspx?sec=sup&sub=mri&pag=dis&ItemID=134730

Radiologists warn of worsening imaging backlogs as omicron takes hold

Canadian radiologists are warning of worsening imaging backlogs as the omicron variant continues to spread.  

Wait times for crucial diagnostic services have swelled well beyond the country’s recommended maximum of one month when the pandemic first started. Patients are reportedly now seeing delays upward of 82 days for CT scans and 89 for MRIs.

A recent association survey found that about 75% of radiologist members had not yet been able to reduce their imaging backlogs. Another 30% said they believe wait times may never return to pre-pandemic levels.

Read more: https://www.radiologybusiness.com/topics/care-delivery/canadian-association-radiologists-backlog-omicron

7T Proton MR Spectroscopic Imaging Can Identify Brain Changes In Multiple Sclerosis

A recent study in the journal Radiology suggests that MR spectroscopic imaging at 7.0 T can identify changes in the brains of patients with multiple sclerosis (MS) that were not visible at T1- or T2-weighted MRI. Previous studies have shown that MR spectroscopic imaging (MRSI) allows in vivo assessment of brain metabolism. Also, it is of special interest in MS, where morphologic MRI cannot depict major parts of disease activity.

Read more: https://medicaldialogues.in/radiology/news/7t-proton-mr-spectroscopic-imaging-can-identify-brain-changes-in-multiple-sclerosis-study-86879

Convolutional neural network pipeline has 100% accuracy distinguishing between COVID and pneumonia

A fully automatic pipeline of convolutional neural networks and capsule networks was able to accurately differentiate between COVID-19 and community-acquired pneumonia (CAP) on chest CT images, according to new research.

Chest CTs have been crucial in achieving a timely diagnosis for patients who present with symptoms consistent with COVID. However, COVID-19 and CAP have similar appearances on such scans. It can be difficult for a radiologist to accurately differentiate between the two, but doing so is pertinent to a patient’s treatment plan.

The researchers proposed using a fully automatic pipeline of convolutional neural networks (CNNs) and capsule networks to assist radiologists in discerning between COVID and CAP.

Read more: https://www.healthimaging.com/topics/diagnostic-screening/cnn-pipeline-tells-covid-and-cap-apart

Interventional radiology: Aiding advancements in cancer detection

Dr MC Uthappa, Head-Interventional Radiology, Manipal Group of Hospitals, Bangalore gave his insights on how Interventional Radiology is making Cancer Detection more accurate and safer for patients.

Interventional Radiology involves no sutures and no scars with minimal pain. They are image-guided and have excellent clinical outcomes. Also, there are minimal complications. In many cases the life-saving and emergency procedures are performed by the interventional radiologist. Interventional Radiology is complementing the other stakeholders by becoming the fourth pillar of cancer care.

Read more: https://www.expresshealthcare.in/news/interventional-radiology-aiding-advancements-in-cancer-detection/432885/

COVID-19: Radiology should be looked from point of comorbidity, says AIIMS’s top health experts

A discussion on radiology and COVID-19 was held in an interactive webinar session by the Union Health Ministry in collaboration with the All India institute of medical sciences (AIIMS). The discussion points out that although radiology is important when it comes to pneumonia, now it is important to look at radiology also from the point of comorbidity in COVID cases.

Chest radiograph and CT is to be used in very select situations such as clear cut at the shortness of breath and hypoxia, persistent fever, discordance between clinical, microbiology and high-risk situations it is not a routine investigation bit having done it can give out lots of information.

Read more: https://www.aninews.in/news/national/general-news/covid-19-unlike-last-wave-radiology-should-be-looked-also-from-point-of-comorbidity-says-aiimss-top-health-experts20220107200629/

Ultrasound Imaging of Brain with Machine Learning

A proposed machine-learning technique can convert ultrasound signals into a skull profile, which could lead to noninvasive imaging for medical treatments in the human brain.

The current best practice is to create individual skull profiles using CT scans or MRI. The profile provides exact knowledge of how the skull affects ultrasound propagation. Still, requiring an additional scan “defeats the ease of ultrasound,” says Yun Jing from Pennsylvania State University. CT and MRI methods are resource and time-intensive, and CT scans expose the brain to harmful radiation.

The researcher team proposed a new method to extract the skull properties using radio-frequency (rf) ultrasound pulses reflecting off a skull.

Read about the proposal: https://physics.aps.org/articles/v14/182

Should interval chest CT findings affect timing of lung screening?

In lung cancer screening participants, findings on interval diagnostic chest CT can potentially be used to adjust the timing of subsequent lung cancer screening CT follow-up.

Interval diagnostic chest CT could ‘reset the clock’. It could also serve as a potential substitute for annual low-dose CT, especially if it coincides with the next annual screening date.

Read the findings from the study in detail: https://www.auntminnie.com/index.aspx?sec=sup&sub=cto&pag=dis&ItemID=134571

New AI algorithm can quickly detect x-rays that are positive for fractures

A new study has found that artificial intelligence (AI) can help physicians in interpreting x-rays after an injury and suspected fracture.

Fracture interpretation errors represent up to 24 percent of harmful diagnostic errors seen in the emergency department. Furthermore, inconsistencies in radiographic diagnosis of fractures are more common during the evening and overnight hours (5 p.m. to 3 a.m.), likely related to non-expert reading and fatigue.

The AI algorithm (AI BoneView), was trained on a very large number of X-rays from multiple institutions to detect fractures of the limbs, pelvis, torso and lumbar spine and rib cage.

Read more: https://www.news-medical.net/news/20211221/New-AI-algorithm-can-quickly-detect-x-rays-that-are-positive-for-fractures.aspx

 

U.K. releases practical new guidance on spleen imaging

The U.K. Royal College of Radiologists (RCR) has issued guidelines on incidental radiation of the spleen. The 10-page document is free to download from the RCR website.

The guidance applies to all patients who may receive radiotherapy to the spleen. It is a defined organ at risk as a result of being referred for radiotherapy to the upper abdomen or an adjacent anatomical site where the upper abdomen might also be irradiated.

Read more about the guidelines: https://www.auntminnieeurope.com/index.aspx?sec=sup&sub=cto&pag=dis&ItemID=620971