Fourier Transformation-Based Analysis of X-Ray Diffraction Pattern of Keratin for Cancer Detection

Alekseev A. Avdieiev O. Murokh S. Yuk D. Lazarev A. Labelle D. Mourokh L. Lazarev P.
January 2025 Multidisciplinary Digital Publishing Institute (MDPI)

Crystals
2025 #15 Issue 1

With the growing number of cancer cases and deaths around the world, fast, non-invasive, and inexpensive screening is paramount. We examine the feasibility of such cancer detection using the X-ray scattering properties of nails in the canine model. A total of 945 samples taken from 266 dogs were measured, with 84 animals diagnosed with cancer. To analyze the obtained X-ray diffraction patterns of keratin, we propose a method based on the two-dimensional Fourier transformation of the images. We compare 745 combinations of data preprocessing steps and machine learning classifiers and determine the corresponding performance metrics. Excellent classification results are demonstrated, with sensitivity or specificity achieving 100% and the best value for balanced accuracy being 87.5%. We believe that our approach can be extended to human samples to develop a non-invasive, convenient, and cheap method for early cancer detection.

cancer detection , canine model , Fourier transformation , keratin , machine learning , principal component analysis , ROC curves , vitacrystallography , X-ray diffraction

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Matur UK Ltd., 5 New Street Square, London, EC4A 3TW, United Kingdom
Department of Physics and Technology, Karaganda Buketov University, Karaganda, 100028, Kazakhstan
Stuyvesant High School, 345 Chambers Street, New York, 10282, NY, United States
Arion Diagnostics, Inc, 911 Mustang Ct, Petaluma, 94954, CA, United States
Physics Department, Queens College, City University of New York, 65-30 Kissena Blvd, Flushing, 11367, NY, United States

Matur UK Ltd.
Department of Physics and Technology
Stuyvesant High School
Arion Diagnostics
Physics Department

10 лет помогаем публиковать статьи Международный издатель

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