Klabukov ID, Smirnova A, Kondrasheva I, Baranovskii DS, Yatsenko E. Predictive model based on magnetic resonance imaging for chemotherapy response in colorectal cancer: Toward a radiologic biopsy approach. World J Gastrointest Oncol 2026; 18(1): 115117 [DOI: 10.4251/wjgo.v18.i1.115117]
Corresponding Author of This Article
Ilya D Klabukov, PhD, Director, Department of Regenerative Medicine, National Medical Research Radiological Center, No. 4 Koroleva Street, Obninsk 249036, Kaluzhskaya Oblast’, Russia. ilya.klabukov@gmail.com
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Oncology
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Letter to the Editor
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This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Jan 15, 2026 (publication date) through Jan 12, 2026
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World Journal of Gastrointestinal Oncology
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1948-5204
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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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Klabukov ID, Smirnova A, Kondrasheva I, Baranovskii DS, Yatsenko E. Predictive model based on magnetic resonance imaging for chemotherapy response in colorectal cancer: Toward a radiologic biopsy approach. World J Gastrointest Oncol 2026; 18(1): 115117 [DOI: 10.4251/wjgo.v18.i1.115117]
World J Gastrointest Oncol. Jan 15, 2026; 18(1): 115117 Published online Jan 15, 2026. doi: 10.4251/wjgo.v18.i1.115117
Predictive model based on magnetic resonance imaging for chemotherapy response in colorectal cancer: Toward a radiologic biopsy approach
Ilya D Klabukov, Anna Smirnova, Irina Kondrasheva, Denis S Baranovskii, Elena Yatsenko
Ilya D Klabukov, Anna Smirnova, Irina Kondrasheva, Denis S Baranovskii, Elena Yatsenko, Department of Regenerative Medicine, National Medical Research Radiological Center, Obninsk 249036, Kaluzhskaya Oblast’, Russia
Ilya D Klabukov, Anna Smirnova, Obninsk Institute for Nuclear Power Engineering, National Research Nuclear University MEPhI, Obninsk 249033, Kaluzhskaya Oblast’, Russia
Irina Kondrasheva, Department of Regenerative Dentistry, Tsiolkovsky Kaluga State University, Kaluga 248023, Kaluzhskaya Oblast’, Russia
Denis S Baranovskii, Institute of Systems Biology and Medicine, Russian University of Medicine, Moscow 111398, Russia
Author contributions: Klabukov ID designed and performed research, and wrote the letter; Baranovskii DS and Kondrasheva I analyzed data; Smirnova A and Yatsenko E revised the letter. All authors approved the final version to publish.
Supported by Russian Science Foundation, No. 24-64-00028.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Ilya D Klabukov, PhD, Director, Department of Regenerative Medicine, National Medical Research Radiological Center, No. 4 Koroleva Street, Obninsk 249036, Kaluzhskaya Oblast’, Russia. ilya.klabukov@gmail.com
Received: October 10, 2025 Revised: October 18, 2025 Accepted: November 12, 2025 Published online: January 15, 2026 Processing time: 96 Days and 4.3 Hours
Abstract
We read with great interest the investigation of Kang et al related the applications of the multiparametric magnetic resonance imaging-based predictive model for assessing chemotherapy efficacy in colorectal cancer patients with gene mutations. The authors focused on decision-making based on the integration of tumor differentiation, signal intensity ratio, margin distance, and magnetic resonance imaging-detected lymph node metastasis. Indeed, these multiparameter predictive models could also be used for diagnosis as an alternative to invasive tissue examination methods. However, progress in this field enables us to shift the paradigm to radiology biopsies, particularly given the nonlinear effects of various radiation sources.
Core Tip: This letter comments on Kang et al’s magnetic resonance imaging-based model for evaluating chemo efficacy in mutated colorectal cancer, notes its diagnostic potential, and suggests shifting to radiology biopsies considering radiation nonlinear effects. Advanced contrast agents and super-resolution methods allow for novel diagnostic procedures, radiologic biopsies, which can be used for cancer diagnostics and to provide basic data on the extracellular matrix alterations.
