Retrospective Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
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
Processing time: 265 Days and 23.6 Hours
Abstract
BACKGROUND

Whole-tumor apparent diffusion coefficient (ADC) histogram analysis is relevant to predicting the neoadjuvant chemoradiation therapy (nCRT) response in patients with locally advanced rectal cancer (LARC).

AIM

To evaluate the performance of ADC histogram-derived parameters for predicting the outcomes of patients with LARC.

METHODS

This is a single-center, retrospective study, which included 48 patients with LARC. All patients underwent a pre-treatment magnetic resonance imaging (MRI) scan for primary tumor staging and a second restaging MRI for response evaluation. The sample was distributed as follows: 18 responder patients (R) and 30 non-responders (non-R). Eight parameters derived from the whole-lesion histogram analysis (ADCmean, skewness, kurtosis, and ADC10th, 25th, 50th, 75th, 90th percentiles), as well as the ADCmean from the hot spot region of interest (ROI), were calculated for each patient before and after treatment. Then all data were compared between R and non-R using the Mann-Whitney U test. Two measures of diagnostic accuracy were applied: the receiver operating characteristic curve and the diagnostic odds ratio (DOR). We also reported intra- and interobserver variability by calculating the intraclass correlation coefficient (ICC).

RESULTS

Post-nCRT kurtosis, as well as post-nCRT skewness, were significantly lower in R than in non-R (both P < 0.001, respectively). We also found that, after treatment, R had a larger loss of both kurtosis and skewness than non-R (∆%kurtosis and ∆skewness, P < 0.001). Other parameters that demonstrated changes between groups were post-nCRT ADC10th, ∆%ADC10th, ∆%ADCmean, and ROI ∆%ADCmean. However, the best diagnostic performance was achieved by ∆%kurtosis at a threshold of 11.85% (Area under the receiver operating characteristic curve [AUC] = 0.991, DOR = 376), followed by post-nCRT kurtosis = 0.78 × 10-3 mm2/s (AUC = 0.985, DOR = 375.3), ∆skewness = 0.16 (AUC = 0.885, DOR = 192.2) and post-nCRT skewness = 1.59 × 10-3 mm2/s (AUC = 0.815, DOR = 168.6). Finally, intraclass correlation coefficient analysis showed excellent intraobserver and interobserver agreement, ensuring the implementation of histogram analysis into routine clinical practice.

CONCLUSION

Whole-tumor ADC histogram parameters, particularly kurtosis and skewness, are relevant biomarkers for predicting the nCRT response in LARC. Both parameters appear to be more reliable than ADCmean from one-slice ROI.

Keywords: Apparent diffusion coefficient; Diffusion-weighted imaging; Histogram analysis; Magnetic resonance imaging; Locally advanced rectal cancer

Core Tip: Whole-tumor apparent diffusion coefficient (ADC) histogram analysis is an emergent imaging analysis in which every voxel is used to obtain a histogram; it thus provides statistical information about tumors. Our study revealed that ADC histogram profiling is a valuable approach that can help differentiate treatment response in locally advanced rectal cancer. When determining tailored treatments that are associated with minimal morbidities, such as the watch and wait method, an accurate treatment response prediction is critical. Given the limitations of this study, more research is needed to establish the clinical utility of our findings.