ArticleJournal of neurology2017
A novel imaging technique for better detecting new lesions in multiple sclerosis.
Article in Journal of neurology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Expert Panel Consensus Guidelines of the German Society of Neuroradiology on the Use of Magnetic Resonance Imaging in the Diagnosis and Monitoring of Multiple Sclerosis.Clinical neuroradiology · 2026Guideline
- External validation of a multiple sclerosis treatment decision score using data from the ProVal-MS cohort study.Therapeutic advances in neurological disorders · 2025Article
- Evaluation of the quality and the productivity of neuroradiological reading of multiple sclerosis follow-up MRI scans using an intelligent automation software.Neuroradiology · 2024Article
- Revolutionizing Neurological Disorder Treatment: Integrating Innovations in Pharmaceutical Interventions and Advanced Therapeutic Technologies.Current pharmaceutical design · 2024Review
- Evaluation of the Statistical Detection of Change Algorithm for Screening Patients with MS with New Lesion Activity on Longitudinal Brain MRI.AJNR. American journal of neuroradiology · 2023Article
- Lesion location across diagnostic regions in multiple sclerosis.NeuroImage. Clinical · 2023Article
- Brain Tumour Temporal Monitoring of Interval Change Using Digital Image Subtraction Technique.Frontiers in public health · 2021Article
- Article
- Automated segmentation of changes in FLAIR-hyperintense white matter lesions in multiple sclerosis on serial magnetic resonance imaging.NeuroImage. Clinical · 2019Article
- Diagnostic accuracy of semiautomatic lesion detection plus quantitative susceptibility mapping in the identification of new and enhancing multiple sclerosis lesions.NeuroImage. Clinical · 2018Article
- Non-invasive MRI of choroid plexus-cerebrospinal fluid water exchange using multi-TE FLAIR.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
We developed a tool that performs longitudinal subtraction of 3D double inversion recovery (DIR) images in follow-up magnetic resonance (MR) examinations of patients with multiple sclerosis. As DIR sequences show a high lesion-to-parenchyma contrast, we hypothesized that such a tool might lead to increased sensitivity for new lesions as well as to speeding up the routine clinical work-up of follow-up MR imaging in multiple sclerosis by directly visualizing new lesions. DIR subtraction images of serial MR examinations were calculated in 106 patients with multiple sclerosis. Existence of new lesions was assessed in three different ways: by standard visual comparison, by FLAIR, and by DIR subtraction maps. A reference standard, to which the single modalities were compared, was defined by combining all information from all readouts and all readers. The presence and number of new lesions were determined and the time needed for analysis measured. Accuracy of detecting overall existence of new lesions using DIR subtraction maps was significantly higher than using visual comparison (96 vs. 86%, p = 0.013) or FLAIR subtraction maps (p < 0.001), with increased sensitivity and higher negative predictive value. Significantly more new lesions were detected when using DIR subtraction maps (p < 0.001). Analyzing subtraction maps took less than a third of the time needed for the standard visual comparison (p = 0.007). Thus, DIR subtraction maps improve the detection of new lesions in a clinical setting both in terms of accuracy and in terms of speed.
Indexed as
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.