European journal of radiology
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The rapid development of Artificial Intelligence/deep learning technology and its implementation into routine clinical imaging will cause a major transformation to the practice of radiology. Strategic positioning will ensure the successful transition of radiologists into their new roles as augmented clinicians. This paper describes an overall vision on how to achieve a smooth transition through the practice of augmented radiology where radiologists-in-the-loop ensure the safe implementation of Artificial Intelligence systems.
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Multicenter Study
Diagnostic value of 3DFLAIR in clinical practice for the detection of infratentorial lesions in multiple sclerosis in regard to dual echo T2 sequences.
The aim of this prospective study is to investigate and evaluate in clinical practice the diagnostic impact of 3DFLAIR in regards to 2DT2/PD in terms of infratentorial lesions detection in multiple sclerosis (MS). ⋯ Along with the radiologist ability to detect lesions based on his level of experience, the OFSEP optimized 3DFLAIR can significantly improve infratentorial lesion detection in MS compared to 2DT2/PD. This is important in MS follow-up that takes into account new lesions number to adapt patients' treatment.
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To determine the utility of "target sign" on diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) mapping for peripheral nerve sheath tumor (PNST) characterization. ⋯ In this explorative study, a "target sign" suggests a benign PNST and is more often visible on DWI using high b-values and ADC maps compared with anatomic sequences.