Published online Jun 21, 2022. doi: 10.3748/wjg.v28.i23.2609
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
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.
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).
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.
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.
Post-nCRT kurtosis, ∆%kurtosis, post-nCRT skewness an ∆skewness exhibited the highest diagnostic performance in predicting a good response to nCRT.
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.
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.