A New Approach to Perfusion-Weighted Image Analysis: Measurement via Red–Green–Blue Information Inversion

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Taeyeon Kim, Youngsoo Kim, Youjin Lee, Injung Kim, Seungeon Song, Seokwon Kim, Jinyoung Choi, Dougho Park

Published: 07 Aug 2025, Last Modified: 04 Nov 2025CrossrefEveryoneRevisionsCC BY-SA 4.0
Abstract: This study developed and validated a Python-based program for analyzing the region of interest mean values using red–green–blue (RGB)–reconstructed perfusion-weighted imaging (PWI) data. The program addressed the limitations of traditional source-image-based analysis, including manufacturer dependency, high storage costs, and limited accessibility. High intraclass correlation coefficient (ICC) values for cerebral blood volume and time to peak confirmed the feasibility of this approach, whereas lower ICC values for mean transit time suggested discrepancies between reconstructed RGB images and conventional dynamic susceptibility contrast–based data. Designed with a user-friendly graphical user interface and executable distribution, the program enhances clinical applicability. Future studies should focus on improving the algorithms and validating the approach with multicenter datasets.