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ORIGINAL RESEARCH ARTICLE

Innovative index for quantifying breast cancer development through T1- and T2-weighted magnetic resonance imaging images        

Mansour Ashoor1 ,  Abdollah Khorshidi1*
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1 Radiation Applications Research School, Nuclear Science and Technology Research Institute, Atomic Energy Organization of Iran (AEOI), Tehran, Iran
Tumor Discovery, 025230041 https://doi.org/10.36922/TD025230041
Received: 2 June 2025 | Revised: 28 September 2025 | Accepted: 22 October 2025 | Published online: 11 November 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Breast cancer has recently received considerable attention in the field of diagnostic imaging. It can present in various forms, including invasive, in situ, or mixed subtypes. As breast tumors grow faster than other tumor types, non-invasive imaging methods, such as magnetic resonance imaging (MRI), are widely used for their quantitative assessment. This study proposes a novel function that utilizes specific mathematical relationships between relaxation times in MRI to generate maps by defining alpha star. We introduced transverse–longitudinal function (TLF), incorporating T1, T2, and alpha parameters. The function equals zero for a given assumed alpha value. Then, when plotting the TLF, a maximum amount was introduced as a percentage of the maximum width at the x-value. By calculating the inverse of the TLF, the full width at × maximum (FW×M)—the difference between the maximum and minimum alpha stars—was obtained for each image pixel. If this parameter were estimated for the entire image, only one FW×M would be obtained. The derived maps demonstrated breast tumor growth and predictive potential, with a reasonable signal-to-noise ratio of 16.5×−0.096. While the x-value approached 1, more details in the entire breast image became visible. The resulting images with the index value of −0.096 revealed breast structures and other information at different stages, potentially facilitating the quantitative assessment of tumor characteristics and progression.

Graphical abstract
Keywords
Breast cancer
Magnetic resonance imaging
Relaxation times
Signal-to-noise ratio
Full width at x maximum
Funding
None.
Conflict of interest
The authors declare that they have no competing interests.
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Tumor Discovery, Electronic ISSN: 2810-9775 Print ISSN: 3060-8597, Published by AccScience Publishing
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