A maximum‐likelihood method to estimate a single ADC value of lesions using diffusion MRI. Issue 6 (7th January 2016)

• Record Type: Journal Article
• Authors: Jha, Abhinav K.; Rodríguez, Jeffrey J.; Stopeck, Alison T.
• Is Part Of: Magnetic resonance in medicine. Volume 76:Issue 6(2016)
• Page Start: 1919
• Page End: 1931
• Publication Date: 2016-01-07
• Subjects: ADC estimation -- maximum‐likelihood method -- statistics of Rician‐distributed random variables -- single ADC value -- motion misalignment; Nuclear magnetic resonance -- Periodicals; Electron paramagnetic resonance -- Periodicals; 616.07548
• DOI: 10.1002/mrm.26072
• Languages: English
• ISSNs: 0740-3194

Abstract

Abstract : Purpose: Design a statistically rigorous procedure to estimate a single apparent diffusion coefficient (ADC) of lesion from the mean lesion signal intensity in diffusion MRI. Theory and Methods: A rigorous maximum‐likelihood technique that incorporated the statistics of the mean lesion intensity and accounted for lesion heterogeneity was derived to estimate the ADC value. Performance evaluation included comparison with the conventionally used linear‐regression and a statistically rigorous state‐of‐the‐art ADC‐map technique using realistic and clinically relevant simulation studies conducted with assistance of patient data for homogeneous and heterogeneous lesion models. Results: The proposed technique outperformed the linear‐regression and ADC‐map approaches over a large spectrum of signal‐to‐noise ratio, ADC, lesion size, image‐misalignment parameters, including at no image misalignment, and different amounts of lesion heterogeneity. The method was also superior at different sets of b values and in studies from specific patient‐image‐derived data. The technique took less than a second to execute. Conclusions: A rigorous, computationally fast, easy‐to‐implement, and convenient‐to‐use maximum‐likelihood technique was proposed to estimate a single ADC value of the lesion. Results provide strong evidence in support of the method. Magn Reson Med 76:1919–1931, 2016. © 2016 International Society for Magnetic Resonance in Medicine