Histological grades of rectal cancer: Whole-volume histogram analysis of apparent diffusion coefficient based on reduced fieldof- view diffusion-weighted imaging

Yang Peng, Hao Tang, Xiaoyan Meng, Yaqi Shen, Daoyu Hu, Ihab Kamel, Zhen Li

Research output: Contribution to journalArticle

Abstract

Background: To explore the role of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) derived from reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) technique in discriminating histological grades of rectal carcinoma. Methods: Altogether, 49 patients with rectal cancer were enrolled in this retrospective study. All patients received preoperative 3.0 T MR scan. Histogram parameters from rFOV DWI were calculated and correlated with histological differentiation of rectal cancer. The parameters were compared between different histological grades of rectal cancer by independent Student's t-test or Man-Whitney U-test. The Spearman correlation test analyzed correlations between histological grade and histogram parameters. The diagnostic performance of individual parameters for distinguishing poorly from well-/moderately differentiated tumors was assessed by receiver operating characteristic curve (ROC) analysis. Results: There were significant differences for ADCmean, 25th, 50th, 75th, 90th, 95th percentiles, skewness, and kurtosis of rFOV DWI sequence between well-, moderately, and poorly differentiated rectal cancers (P<0.05). Significant correlations were noted between histological grades and the above histogram parameters (r=0.679, 0.540, 0.701, 0.730, 0.669, 0.574, -0.730, and -0.760 respectively, P<0.001). Among the individual histogram parameter, kurtosis achieved the highest AUC of 0.882 with an optimal cutoff value of 1.934 in distinguishing poorly from well-/moderately differentiated rectal cancers. The combination of ADCmean, 75th percentile, and kurtosis yielded the highest AUC of 0.927 with a sensitivity of 88.00% and a sensitivity of 91.7% using logistic regression. Conclusions: Quantitative whole-lesion ADC histogram analysis based on the rFOV DWI technique could help differentiate histological grades of rectal cancer. The combination of ADCmean, 75th percentile, and kurtosis may be the best choice.

Original languageEnglish (US)
Pages (from-to)243-256
Number of pages14
JournalQuantitative Imaging in Medicine and Surgery
Volume10
Issue number1
DOIs
StatePublished - Jan 1 2020

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Rectal Neoplasms
Area Under Curve
ROC Curve
Retrospective Studies
Logistic Models
Students
Carcinoma
Neoplasms

Keywords

  • Cell differentiation
  • Diffusion magnetic resonance imaging (diffusion MRI)
  • Gastrointestinal neoplasms
  • Magnetic resonance imaging (MRI)
  • Rectal neoplasms

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

Histological grades of rectal cancer : Whole-volume histogram analysis of apparent diffusion coefficient based on reduced fieldof- view diffusion-weighted imaging. / Peng, Yang; Tang, Hao; Meng, Xiaoyan; Shen, Yaqi; Hu, Daoyu; Kamel, Ihab; Li, Zhen.

In: Quantitative Imaging in Medicine and Surgery, Vol. 10, No. 1, 01.01.2020, p. 243-256.

Research output: Contribution to journalArticle

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abstract = "Background: To explore the role of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) derived from reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) technique in discriminating histological grades of rectal carcinoma. Methods: Altogether, 49 patients with rectal cancer were enrolled in this retrospective study. All patients received preoperative 3.0 T MR scan. Histogram parameters from rFOV DWI were calculated and correlated with histological differentiation of rectal cancer. The parameters were compared between different histological grades of rectal cancer by independent Student's t-test or Man-Whitney U-test. The Spearman correlation test analyzed correlations between histological grade and histogram parameters. The diagnostic performance of individual parameters for distinguishing poorly from well-/moderately differentiated tumors was assessed by receiver operating characteristic curve (ROC) analysis. Results: There were significant differences for ADCmean, 25th, 50th, 75th, 90th, 95th percentiles, skewness, and kurtosis of rFOV DWI sequence between well-, moderately, and poorly differentiated rectal cancers (P<0.05). Significant correlations were noted between histological grades and the above histogram parameters (r=0.679, 0.540, 0.701, 0.730, 0.669, 0.574, -0.730, and -0.760 respectively, P<0.001). Among the individual histogram parameter, kurtosis achieved the highest AUC of 0.882 with an optimal cutoff value of 1.934 in distinguishing poorly from well-/moderately differentiated rectal cancers. The combination of ADCmean, 75th percentile, and kurtosis yielded the highest AUC of 0.927 with a sensitivity of 88.00{\%} and a sensitivity of 91.7{\%} using logistic regression. Conclusions: Quantitative whole-lesion ADC histogram analysis based on the rFOV DWI technique could help differentiate histological grades of rectal cancer. The combination of ADCmean, 75th percentile, and kurtosis may be the best choice.",
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AU - Tang, Hao

AU - Meng, Xiaoyan

AU - Shen, Yaqi

AU - Hu, Daoyu

AU - Kamel, Ihab

AU - Li, Zhen

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