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Abstract #1299

An Imageless Magnetic Resonance Diagnosis procedure for fast and affordable screening and follow-up

Pablo García Cristóbal1, Alba González Cebrián1, Fernando Galve1, Viktor Van Der Valk2, Efe Ilıcak 2, Marius Staring2, Andrew Webb2, and Joseba Alonso1
1Instituto de Instrumentación para Imagen Molecular, CSIC, Universitat Politècnica de València, Valencia, Spain, 2Leiden University Medical Center, Department of Radiology, Leiden, Netherlands

Synopsis

Keywords: Acquisition Methods, Diagnosis/Prediction

Motivation: Traditional MRI is costly and limited in availability, restricting its use for large-scale screening and follow-up. Combining high-efficiency pulse sequences, affordable hardware, and AI could address these limitations.

Goal(s): Our goal was to assess the feasibility of Imageless MR Diagnosis (IMRD) through white matter lesion detection as a simulated case study.

Approach: We optimized a fingerprinting-inspired acquisition of a single radial spoke and used the resulting data to train a deep-learning model for lesion detection.

Results: Simulations using a single-gradient axis achieved an AUC greater than 0.95, indicating the feasibility of IMRD within short scan times (<1 minute).

Impact: The use of Imageless MR sequences, combined with deep-learning methods, could offer a rapid, cost-effective screening technique suitable for large population-wise deployment. In simulations we show how white matter lesions could potentially be detected and characterized.

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Keywords