Improved Detection of New MS Lesions during Follow-Up Using an Automated MR Coregistration-Fusion Method

Abstract

Our study showed that an automated coregistration-fusion method was more sensitive for detecting new high-signal T2 lesions in patients with MS and reducing reading time. This method could help to improve follow-up care.

PACS Integration of Semiautomated Imaging Software Improves Day-to-Day MS Disease Activity Detection

“…23,24 Semiautomated imaging represents a growing field of MS and radiology research, with methods ranging from assisted lesion assessment to brain volumetric analysis. 6,19,25 Similar growth is seen with an extension of computer-assisted detection called "radiomics," which converts images to minable data for deep learning. 26 Image coregistration is a crucial component of traditional MR imaging comparison.…”

“…Semiautomated imaging software has shown great promise in the field of MS disease monitoring. [17][18][19] Earlier studies of VT concluded that it allowed higher lesion detection with improved interreader reliability and decreased reporting times when used by readers of all radiology training levels (ie, ranging from medical student to fellowship-trained neuroradiologist) compared with their performance using CSSC. 8,9,14 The main caveats of prior research in this area, however, included the retrospective design, artificial research conditions, and/or relatively small sample sizes.…”

“…After incorporating VT-assisted imaging in our hospital's daily MR imaging reporting activities, our findings are in line with other smaller prospective studies that have shown an absolute increase of 13% (22% relative increase) in new MS lesion detection using similar semiautomated software. 19 Perhaps more important, implementation of this software in our department was largely seamless and did not appreciably increase transfer times to PACS or data memory burden. Similarly, a post hoc survey of staff in our department showed an overwhelmingly positive response to the integration of the software in our daily practice.…”

MRI Follow‐up of Astrocytoma: Automated Coregistration and Color‐Coding of FLAIR Sequences Improves Diagnostic Accuracy With Comparable Reading Time

“…However, for the purpose of follow‐up imaging of heteromorphic brain tumors as astrocytoma, for which longitudinal evaluation of disease is paramount, these tools have not been systematically investigated yet. Our hypothesis was that an automated coregistration approach could yield comparable advantages for astrocytoma follow‐up, as previously shown for MS patients . Hence, the study purpose was to compare diagnostic accuracy, required reading time, and diagnostic certainty between longitudinal assessment of FLAIR sequences with and without automated coregistration in patients with low‐ or high‐grade astrocytoma.…”

“…Assessing repetitive MRI examinations, however, is time‐consuming, and comparability may be hampered by discrepant acquisition protocols or the use of heterogeneous MRI scanners. Thus, techniques for subtraction and automated coregistration of such repetitive follow‐ups have been developed and reported to be useful, particularly for follow‐up of multiple sclerosis (MS) with high lesion burden . It was reported that along with the use of these tools, diagnostic accuracy could be increased, while required reading was reduced …”