Histogram analysis of diffusion kurtosis imaging in the differentiation of malignant from benign breast lesions

2019 ◽  
Vol 117 ◽  
pp. 156-163 ◽  
Author(s):  
Wei Liu ◽  
Chaogang Wei ◽  
Jiayuan Bai ◽  
Xin Gao ◽  
Lijuan Zhou
Keyword(s):  
Histogram Analysis ◽  
Diffusion Kurtosis Imaging ◽  
Breast Lesions ◽  
Benign Breast Lesions ◽  
Diffusion Kurtosis

Histogram analysis in prostate cancer: a comparison of diffusion kurtosis imaging model versus monoexponential model

2020 ◽  
Vol 61 (10) ◽  
pp. 1431-1440
Author(s):  
Yuwei Jiang ◽  
Chunmei Li ◽  
Ying Liu ◽  
Kaining Shi ◽  
Wei Zhang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Histogram Analysis ◽  
Diffusion Kurtosis Imaging ◽  
Single Shot ◽  
Diagnostic Efficiency ◽  
Planar Imaging ◽  
Significant Difference ◽  
Monoexponential Model ◽  
The Mean ◽  
Diffusion Kurtosis

Background There is still little research about histogram analysis of diffusion kurtosis imaging (DKI) using in prostate cancer at present. Purpose To verify the utility of histogram analysis of DKI model in detection and assessment of aggressiveness of prostate cancer, compared with monoexponential model (MEM). Material and Methods Twenty-three patients were enrolled in this study. For DKI model and MEM, the Dapp, Kapp, and apparent diffusion coefficient (ADC) were obtained by using single-shot echo-planar imaging sequence. The pathologies were confirmed by in-bore magnetic resonance (MR)-guided biopsy. Regions of interest (ROI) were drawn manually in the position where biopsy needle was put. The mean values and histogram parameters in cancer and noncancerous foci were compared using independent-samples T test. Receiver operating characteristic curves were used to investigate the diagnostic efficiency. Spearman’s test was used to evaluate the correlation of parameters and Gleason scores. Results The mean, 10th, 25th, 50th, 75th, and 90th percentiles of ADC and Dapp were significantly lower in prostate cancer than non-cancerous foci ( P < 0.001). The mean, 50th, 75th, and 90th percentiles of Kapp were significantly higher in prostate cancer ( P < 0.05). There was no significant difference between the AUCs of two models (0.971 vs. 0.963, P > 0.05). With the increasing Gleason scores, the 10th ADC decreased ( ρ = −0.583, P = 0.018), but the 90th Kapp increased ( ρ = 0.642, P = 0.007). Conclusion Histogram analysis of DKI model is feasible for diagnosing and grading prostate cancer, but it has no significant advantage over MEM.

Histogram analysis of diffusion kurtosis imaging derived maps may distinguish between low and high grade gliomas before surgery

2017 ◽  
Vol 28 (4) ◽  
pp. 1748-1755 ◽  
Author(s):  
Xi-Xun Qi ◽  
Da-Fa Shi ◽  
Si-Xie Ren ◽  
Su-Ya Zhang ◽  
Long Li ◽  
...  
Keyword(s):  
Histogram Analysis ◽  
Diffusion Kurtosis Imaging ◽  
High Grade ◽  
High Grade Gliomas ◽  
Diffusion Kurtosis

scholarly journals Application of Diffusion Kurtosis Imaging and Histogram Analysis for Assessing Preoperative Stages of Rectal Cancer

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Hui Xie ◽  
Guangyao Wu
Keyword(s):  
Rectal Cancer ◽  
Lymph Node ◽  
Rectal Adenocarcinoma ◽  
Area Under The Curve ◽  
Histogram Analysis ◽  
Diffusion Kurtosis Imaging ◽  
Diagnostic Efficiency ◽  
Significant Difference ◽  
Adc Values ◽  
Diffusion Kurtosis

Objective. To explore the value of diffusion kurtosis imaging (DKI) and histogram analysis for assessing preoperative stages and heterogeneity in rectal cancer. Methods. Fifty patients with pathologically confirmed rectal adenocarcinoma were enrolled. The value of DKI parameters and histogram metrics for assessing the preoperative stages and heterogeneity in rectal cancer was analyzed retrospectively. Results. (1) ADC-10th percentile and ADC-25th percentile were significantly higher in T1-2 than in the T3-4 rectal cancer (the ADC values were 0.65 ± 0.08 × 10−3 mm2/s versus 0.58 ± 0.11 × 10−3 mm2/s and 0.73 ± 0.11 × 10−3 mm2/s versus 0.65 ± 0.11 × 10−3 mm2/s; p values were 0.035 and 0.024, resp.). (2) D-10th percentile and D-25th percentile were also significantly higher in T1-2 than in T3-4 rectal cancer (the D values were 0.96 ± 0.19 × 10−3 mm2/s versus 0.84 ± 0.16 × 10−3 mm2/s and 1.15 ± 0.27 × 10−3 mm2/s versus 0.99 ± 0.18 × 10−3 mm2/s; p values were 0.017 and 0.044, resp.). (3) K value and its histogram metrics showed no statistically significant difference between T1-2 and T3-4. (4) D-10th had the largest area under the curve (AUC 0.799) among all the parameters; the sensitivity and specificity were 84.2 and 61.3%, respectively. (5) DKI combined with traditional MRI had an accuracy of 68% while assessing the lymph node of rectal cancer. Conclusion. DKI parameters and histogram metrics are rather valuable in assessing the preoperative stages of rectal cancer; D-10th percentile exhibits the highest diagnostic efficiency.

Diffusion kurtosis imaging does not improve differentiation performance of breast lesions in a short clinical protocol

2019 ◽  
Vol 63 ◽  
pp. 205-216 ◽  
Author(s):  
Theresa Palm ◽  
Evelyn Wenkel ◽  
Sabine Ohlmeyer ◽  
Rolf Janka ◽  
Michael Uder ◽  
...  
Keyword(s):  
Diffusion Kurtosis Imaging ◽  
Breast Lesions ◽  
Clinical Protocol ◽  
Diffusion Kurtosis

Histogram analysis in predicting the grade and histological subtype of meningiomas based on diffusion kurtosis imaging

2020 ◽  
Vol 61 (9) ◽  
pp. 1228-1239
Author(s):  
Xiaodan Chen ◽  
Lin Lin ◽  
Jie Wu ◽  
Guang Yang ◽  
Tianjin Zhong ◽  
...  
Keyword(s):  
Pearson Correlation ◽  
Mean Diffusivity ◽  
Labeling Index ◽  
Histogram Analysis ◽  
Diffusion Kurtosis Imaging ◽  
Low Grade ◽  
High Grade ◽  
Ki 67 ◽  
Diffusion Kurtosis ◽  
Median Maximum

Background Presurgical grading is particularly important for selecting the best therapeutic strategy for meningioma patients. Purpose To investigate the value of histogram analysis of diffusion kurtosis imaging (DKI) maps in the differentiation of grades and histological subtypes of meningiomas. Material and Methods A total of 172 patients with histopathologically proven meningiomas underwent preoperative magnetic resonance imaging (MRI) and were classified into low-grade and high-grade groups. Mean kurtosis (MK), fractional anisotropy (FA), and mean diffusivity (MD) histograms were generated based on solid components of the whole tumor. The following parameters of each histogram were obtained: 10th, 25th, 75th, and 90th percentiles, mean, median, maximum, minimum, and kurtosis, skewness, and variance. Comparisons of different grades and subtypes were made by Mann–Whitney U test, Kruskal–Wallis test, ROC curves analysis, and multiple logistic regression. Pearson correlation was used to evaluate correlations between histogram parameters and the Ki-67 labeling index. Results Significantly higher maximum, skewness, and variance of MD, mean, median, maximum, variance, 10th, 25th, 75th, and 90th percentiles of MK were found in high-grade than low-grade meningiomas (all P < 0.05). DKI histogram parameters differentiated 7/10 pairs of subtype pairs. The 90th percentile of MK yielded the highest AUC of 0.870 and was the only independent indicator for grading meningiomas. Various DKI histogram parameters were correlated with the Ki-67 labeling index ( P < 0.05). Conclusion The histogram analysis of DKI is useful for differentiating meningioma grades and subtypes. The 90th percentile of MK may serve as an optimal parameter for predicting the grade of meningiomas.

scholarly journals Accuracy of diffusion kurtosis imaging in characterization of breast lesions

2017 ◽  
Vol 90 (1073) ◽  
pp. 20160873 ◽  
Author(s):  
Alexandra Christou ◽  
Abraham Ghiatas ◽  
Dimitrios Priovolos ◽  
Konstantia Veliou ◽  
Haralambos Bougias
Keyword(s):  
Diffusion Kurtosis Imaging ◽  
Breast Lesions ◽  
Diffusion Kurtosis
Sign in / Sign up

Export Citation Format

Share Document