Application of texture analysis based on apparent diffusion coefficient maps in discriminating different stages of rectal cancer

Liu, Liheng; Liu, Yuhui; Xu, Liang; Li, Zhenjiang; Lv, Han; Dong, Ningning; Li, Wenwu; Yang, Zhenghan; Wang, Zhenchang; Jin, Erhu

doi:10.1002/jmri.25460

Cited by 100 publications

(126 citation statements)

References 35 publications

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“…Especially first‐order entropy correlated with overall stage with a correlation coefficient of 0.677, which was higher than ADC mean and ADC min ( r = –0.446, –0.437, respectively) in our previous study . Liu et al reported that first‐order entropy derived from the largest tumor slice of ADC map correlated with overall stage of rectal cancers ( r = 0.486), which was also weaker than the current study …”

Section: Discussioncontrasting

confidence: 90%

Whole‐volume apparent diffusion coefficient‐based entropy parameters for assessment of gastric cancer aggressiveness

Liu

Zheng

Zhang

et al. 2017

Magnetic Resonance Imaging

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Purpose: To explore the role of whole-volume apparent diffusion coefficient (ADC)-based entropy parameters in the preoperative assessment of gastric cancer's aggressiveness. Materials and Methods: In all, 64 patients with gastric cancers who underwent 3.0T magnetic resonance imaging (MRI) were retrospectively included. Regions of interest were drawn manually using in-house software, around gastric cancer lesions on each slice of the diffusion-weighted images and ADC maps. Entropy-related parameters based on ADC maps were calculated automatically: (1) first-order entropy; (2-5) second-order entropies, including entropy(H) 0 , entropy(H) 45 , entropy(H) 90 , and entropy(H) 135 ; (6) entropy(H) mean ; and (7) entropy(H) range . Correlations between entropy-related parameters and pathological characteristics were analyzed with the Spearman correlation test. The parameters were compared among different pathological characteristics with independent-samples Kruskal-Wallis or Mann-Whitney U-test. Additionally, diagnostic performances of parameters in differentiating different pathological characteristics were analyzed by receiver operating characteristic (ROC) curve analysis. Results: All the entropy-related parameters significantly correlated with T, N, and overall stages, especially the firstorder entropy (r 5 0.588, 0.585, and 0.677, respectively, all P < 0.05). All the entropy-related parameters showed significant differences in gastric cancers at different T, N, and overall stages, as well as at different status of vascular invasion (P < 0.001-0.027). And four parameters, including entropy, entropy(H) 0 , entropy(H) 45 , and entropy(H) 90 , showed significant differences between gastric cancers with and without perineural invasion (P 0.006-0.040). Conclusion: Entropy-related parameters derived from whole-volume ADC texture analysis could help assess the aggressiveness of gastric cancers via analyzing intratumoral heterogeneity quantitatively, especially the first-order entropy. Level of Evidence: 2 Technical Efficacy: Stage 2

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Section: Discussioncontrasting

confidence: 90%

Whole‐volume apparent diffusion coefficient‐based entropy parameters for assessment of gastric cancer aggressiveness

Liu

Zheng

Zhang

et al. 2017

Magnetic Resonance Imaging

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“…This finding corresponds to previous studies in other malignant tumors, exemplarily clear cell renal cell carcinoma, and rectal cancer, which revealed that increased skewness of ADC histograms is associated with a more advanced disease stage [19,20]. Furthermore, an increase in ADC histogram skewness was observed in patients suffering from recurrent high grade glioma who showed disease progress under anti-proliferative chemotherapy, indicating ongoing proliferation of glioma cells within the tumor [21].…”

Section: Discussionsupporting

confidence: 89%

Histogram Analysis of Diffusion Weighted Imaging at 3T is Useful for Prediction of Lymphatic Metastatic Spread, Proliferative Activity, and Cellularity in Thyroid Cancer

Schob

Meyer

Dieckow

et al. 2017

IJMS

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Pre-surgical diffusion weighted imaging (DWI) is increasingly important in the context of thyroid cancer for identification of the optimal treatment strategy. It has exemplarily been shown that DWI at 3T can distinguish undifferentiated from well-differentiated thyroid carcinoma, which has decisive implications for the magnitude of surgery. This study used DWI histogram analysis of whole tumor apparent diffusion coefficient (ADC) maps. The primary aim was to discriminate thyroid carcinomas which had already gained the capacity to metastasize lymphatically from those not yet being able to spread via the lymphatic system. The secondary aim was to reflect prognostically important tumor-biological features like cellularity and proliferative activity with ADC histogram analysis. Fifteen patients with follicular-cell derived thyroid cancer were enrolled. Lymph node status, extent of infiltration of surrounding tissue, and Ki-67 and p53 expression were assessed in these patients. DWI was obtained in a 3T system using b values of 0, 400, and 800 s/mm2. Whole tumor ADC volumes were analyzed using a histogram-based approach. Several ADC parameters showed significant correlations with immunohistopathological parameters. Most importantly, ADC histogram skewness and ADC histogram kurtosis were able to differentiate between nodal negative and nodal positive thyroid carcinoma. Conclusions: histogram analysis of whole ADC tumor volumes has the potential to provide valuable information on tumor biology in thyroid carcinoma. However, further studies are warranted.

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“…Radiomics features are quantitative descriptors that reflect textural variations in image intensity, shape, size, or volume to offer information on tumor phenotype, then these derived data can be mined for possible associations with underlying biology and reflect the behavior of malignant tumors . Successful applications of this technique have been performed on oncologic DWI datasets …”

mentioning

confidence: 99%

Radiomics analysis of apparent diffusion coefficient in cervical cancer: A preliminary study on histological grade evaluation

Liu

Zhang

Cheng

et al. 2018

Magnetic Resonance Imaging

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Application of texture analysis based on apparent diffusion coefficient maps in discriminating different stages of rectal cancer

Abstract: 3 J. MAGN. RESON. IMAGING 2017;45:1798-1808.

Cited by 100 publications

References 35 publications

Whole‐volume apparent diffusion coefficient‐based entropy parameters for assessment of gastric cancer aggressiveness

Whole‐volume apparent diffusion coefficient‐based entropy parameters for assessment of gastric cancer aggressiveness

Histogram Analysis of Diffusion Weighted Imaging at 3T is Useful for Prediction of Lymphatic Metastatic Spread, Proliferative Activity, and Cellularity in Thyroid Cancer

Radiomics analysis of apparent diffusion coefficient in cervical cancer: A preliminary study on histological grade evaluation

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