Whole lesion histogram analysis of apparent diffusion coefficient predicts therapy response in locally advanced rectal cancer

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 ADC10 th , 25 th , 50 th , 75 th , 90 th 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 ADC10 th , ∆%ADC10 th , ∆%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 mm 2 /s (AUC = 0.985, DOR = 375.3), ∆skewness = 0.16 (AUC = 0.885, DOR = 192.2) and post-nCRT skewness = 1.59 × 10 -3 mm 2 /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.

Wall characteristics of atherosclerotic middle cerebral arteries in patients with single or multiple infarcts: A high-resolution MRI Study

“…Histogram analysis is a computer-assisted methodology for extracting quantitative features that cannot be visualized from images. Histogram analysis shows promise in multiple pathologies, including glioma, thyroid nodule, and rectal cancer ( 20 – 22 ). However, its application has not been widely investigated in intracranial plaques with HRMRI, and all of the previous studies ( 10 , 11 , 23 , 24 ) focus on differentiating symptomatic from asymptomatic plaques.…”

Combination of intravoxel incoherent motion histogram parameters and clinical characteristics for predicting response to neoadjuvant chemoradiation in Rectal Cancer

“…The distribution curve behaves sharper with a bigger kurtosis, which may imply that the majority of the data set was concentrated around the median. In biological tissues, a sharp distribution curve may occur when water motion complies with Gaussian distribution, suggesting a relatively homogeneous environment [13]. Thus, the tumor with more homogeneous components means a betterdifferentiated degree, which may be more sensitive to chemotherapy drugs and tends to undergo the pCR.…”

“…ADC values obtained at DWI have been con rmed to be related to tumor cellularity, with lower ADC values associated with increased tumor cellularity [9]. However, these studies on the use of ADC values for treatment response evaluation are inconsistent [10][11][12][13][14]. These con icting results may partly be because the ADC values calculated from DWI are based on a mono-exponential decay model, which hypothesizes the free motion of water molecules following a Gaussian distribution [15].…”