Jiménez de los Santos ME, Reyes-Pérez JA, Domínguez Osorio V, Villaseñor-Navarro Y, Moreno-Astudillo L, Vela-Sarmiento I, Sollozo-Dupont I. Whole lesion histogram analysis of apparent diffusion coefficient predicts therapy response in locally advanced rectal cancer. World J Gastroenterol 2022; 28(23): 2609-2624 [PMID: 35949349 DOI: 10.3748/wjg.v28.i23.2609]
Corresponding Author of This Article
Isabel Sollozo-Dupont, PhD, Academic Research, Statistician, Department of Radiology, National Cancer Institute, Av. San Fernando No. 22, Col. Sección XVI Delegación Tlalpan, Mexico 14080, Mexico. sodi8507@gmail.com
Research Domain of This Article
Oncology
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
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/
World J Gastroenterol. Jun 21, 2022; 28(23): 2609-2624 Published online Jun 21, 2022. doi: 10.3748/wjg.v28.i23.2609
Whole lesion histogram analysis of apparent diffusion coefficient predicts therapy response in locally advanced rectal cancer
Mayra Evelia Jiménez de los Santos, Juan Armando Reyes-Pérez, Victor Domínguez Osorio, Yolanda Villaseñor-Navarro, Liliana Moreno-Astudillo, Itzel Vela-Sarmiento, Isabel Sollozo-Dupont
Mayra Evelia Jiménez de los Santos, Juan Armando Reyes-Pérez, Victor Domínguez Osorio, Yolanda Villaseñor-Navarro, Liliana Moreno-Astudillo, Isabel Sollozo-Dupont, Department of Radiology, National Cancer Institute, Mexico 14080, Mexico
Itzel Vela-Sarmiento, Department of Gastrointestinal Surgery, National Cancer Institute, Mexico 14080, Mexico
Author contributions: Sollozo-Dupont I designed the study; Sollozo-Dupont I and Domínguez Osorio V analyzed the data; Domínguez Osorio V and Vela-Sarmiento I collected the data; Sollozo-Dupont I, Jiménez de los Santos ME, and Reyes-Pérez JA wrote the paper; Villaseñor-Navarro Y and Moreno-Astudillo L reviewed the study; Jiménez de los Santos ME and Reyes-Pérez JA contributed equally to this work; All authors contributed to the manuscript for important intellectual content and approved the submission.
Institutional review board statement: The study protocol was approved by the Institutional Review Board of the National Cancer Institute from México, city, and was in accordance with the Declaration of Helsinki (Approval No. 2021/026).
Informed consent statement: Patients were not required to give informed consent to the study because the analysis used anonymous clinical data that were obtained after each patient agreed to treatment by written consent.
Conflict-of-interest statement: The authors have no conflicts of interest to declare.
Data sharing statement: The raw data supporting the conclusions of this article will be made available by the authors.
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: Isabel Sollozo-Dupont, PhD, Academic Research, Statistician, Department of Radiology, National Cancer Institute, Av. San Fernando No. 22, Col. Sección XVI Delegación Tlalpan, Mexico 14080, Mexico. sodi8507@gmail.com
Received: September 23, 2021 Peer-review started: September 23, 2021 First decision: November 16, 2021 Revised: November 25, 2021 Accepted: April 22, 2022 Article in press: April 22, 2022 Published online: June 21, 2022
ARTICLE HIGHLIGHTS
Research background
Studies have shown that successful treatment of many tumors can be detected using diffusion-weighted magnetic resonance imaging (MRI) as an increase in the apparent diffusion coefficient (ADC). However, findings from rectal cancer have been limited. Therefore, the criteria used for tumor staging and surveillance are largely based on anatomic criteria at this time. Broadly, whole lesion histogram analysis of ADC aims to fill this gap, extracting and analyzing the higher quantitative data with the aim of more accurate, tumor-specific evaluation and characterization.
Research motivation
ADC histogram parameters reflect the distribution and variation of all voxels within the entire lesion, which reduce the subjectivity of region of interest (ROI) placement and improves repeatability in the quantitative ADC analysis. Previous studies have applied volumetric ADC histogram analysis to predict treatment response of squamous carcinoma, breast cancers, and ovarian cancers. No ADC histogram study thus far has focused on locally advanced rectal cancer (LARC).
Research objectives
We aim to evaluate the effectiveness of whole lesion histogram analysis of ADC in the prediction to neoadjuvant chemoradiation therapy (nCRT) response in patients with LARC.
Research methods
This was a retrospective study. We collected data of 48 consecutive patients with histologically confirmed LARC. All patients underwent a pre-treatment MRI for primary tumor staging and a second restaging MRI for response evaluation. The sample was distributed as follows: responders (R), n = 18; and non-responders (non-R), n = 30. Eight parameters derived from the histogram analysis of ADC, as well as the ADCmean from the hot spot ROI, were obtained and compared between R and non-R. The diagnostic accuracy in the prediction of treatment response of all variables included in the present study was calculated as well.
Research results
Post-nCRT kurtosis, ∆%kurtosis, post-nCRT skewness an ∆skewness exhibited the highest diagnostic performance in predicting a good response to nCRT.
Research conclusions
The results of our study support that histogram-parameters derived from ADC values can be used to stratify good responders into studies exploring individualized, less extensive treatment regimens, such as the omission of radiotherapy and less extensive surgery, or even deferral of surgery.
Research perspectives
We need to expand the sample size to confirm further the diagnostic accuracy of kurtosis and skewness. In addition, the long-term outcome of this analysis should be a radiomic model for predict treatment response in rectal cancer.
