Dr. Mark Schiebler presenting
at the session
Radiology editorial board highlights top research papers of 2020
December 10, 2020
by Lauren Dubinsky
, Senior Reporter
While the main topic on everyone's mind these days, COVID-19 does not erase the other issues medical professionals face.
“Certainly, this last year was dominated by new imaging research regarding COVID-19, yet our research community has been as productive as ever in other areas,” said Dr. David A. Bluemke, editor of Radiology, at this year’s RSNA virtual meeting in a session, titled Review of 2020: New Research That Should Impact Your Practice.
In this talk, members of Radiology’s editorial board highlighted the “most impactful” research papers from the past year. Papers spanned the fields of neuroimaging, abdomen/pelvic imaging and chest imaging.
Study: Correlation of Chest CT and RT-PCR Testing for Coronavirus Disease 2019 in China
A study investigating the connection between chest CT and reverse transcription polymerase chain reaction (RT-PCR) in 1,014 COVID cases in China has already been cited 2,147 times, and is the most downloaded paper in Radiology this year.
The research team found that RT-PCR assay, which was developed to rapidly detect COVID, and chest CT were positive in nearly 60% of the patients (601 of 1,014 patients). In the RT-PCR positivity group, chest CT sensitivity for COVID-19 was 97% (580 of 601 patients). It also found that 308 patients had a negative RT-PCR assay and positive CT scans. Of those patients 147 were considered “highly likely” to have COVID and 103 were “clinically probable.”
In addition, among a small subgroup of 57 patients, 60% had a positive CT scan consistent with COVID-19 before the initial positive RT-PCR results, and 42% showed improvement on follow-up chest CT scans before the RT-PCR results turned negative.
“Chest CT can play an important role in the care of patients with respiratory illness during this pandemic,” said Dr. Mark Schiebler, professor of radiology at the University of Wisconsin, Madison. “However, we need to be cognizant of the fact that the use of imaging needs to be individualized to the needs of the patient and the availability of medical care.”
Study: Brain MR Findings in Patients in the Intensive Care Unit with COVID-19 Infection
Since a third or more of COVID patients develop neurologic symptoms, researchers at the University of Iowa Hospital and Clinics decided to study brain MR findings in ICU patients with the infection. The study included 749 such patients that were admitted to eight hospitals from March 1 to April 18. Of them, 50 developed neurologic symptoms and 27 underwent brain MR exams. Ten showed abnormalities in MR signal intensity in the brain and two had vascular abnormalities.
This study shows that although neurologic symptoms are common in COVID patients, MR does not frequently show abnormalities. The causes of these abnormalities were not discovered and none of the patients had COVID in their cerebrospinal fluid.
“It’s hard to be sure which of these findings were related directly to COVID-19 and what is the result of just being sick in the ICU," said Dr. Chris Hess, chair of radiology at University of California, San Francisco (UCSF).
Study: Artificial Intelligence Systems Approaching Neuroradiologist-level Differential Diagnosis Accuracy at Brain MRI
Researchers at UCSF identified 178 patients with 19 diseases ranging from tumors to vascular disease, and designed a composite AI system that models how a radiologist makes an imaging diagnosis.
“Instead of looking for a single diagnosis within an image, it uses AI to detect a broad class of lesions and then uses human domain knowledge to assign a differential diagnosis for detecting lesions," explained Hess.
They used Bayesian inference for this process, which is a way of embedding neuroradiologist knowledge to differentiate between the likelihood of different lesions, and found that the AI system included the correct diagnosis in 91% of the cases. In addition, they found that that the AI had better results than residents, general radiologists and one of two neuroradiology fellows, and was equivalent to the performance of the academic faculty.
“It was also noted that the removal of clinical features from the algorithm resulted in a decline in performance of the system by 20%," said Hess.
Study: Diagnostic Accuracy of CEUS LI-RADS for the Characterization of Liver Nodules 20 mm or Smaller in Patients at Risk for Hepatocellular Carcinoma
Contrast-enhanced ultrasound (CEUS) is now a first-line test for at-risk patients in many countries worldwide. In addition, LI-RADS offers the opportunity to improve diagnosis in at-risk patients, but performance still needs further evaluation, according to Dr. Vicky Goh, professor and chair of clinical cancer imaging at Kings College, London.
A retrospective single-center study recruited 172 at-risk patients with 175 treatment-naïve liver nodules that were 2 centimeters or smaller. CEUS LI-RADS and the World and European criteria (WFUMB-EFSUMB) for diagnosing HCC were compared against the composite reference standard of imaging follow-up and histology. Inter-reader agreement was assessed.
The data revealed that 60% of nodules were HCCs and that inter-reader agreement was excellent. The study also found that CEUS LI-RADS was highly specific and had a high positive predictive value of 98% when LR5 was used. However, the World and European criteria only had a 89% sensitivity rate and a 87% specificity rate.
“Diagnosis of small cancer remains a challenge because of the multi-stage nature of carcinogenesis, the dual blood supply to the liver and overlapping perfusion patterns of regenerative and dysplastic nodules,” said Goh.
She concludes that “CEUS LI-RADS is reproducible and effectively categorizes small liver nodules in patients at risk for HCC."