Objectives To evaluate the improved diagnostic efficacy of the emerging non-invasive microstructure imaging technique, MR cytometry, in differentiating benign and malignant prostate lesions, after removing perfusion effect and introducing histogram features. Methods This study included 33 patients with prostate cancer and 39 patients with benign lesions, who underwent time-dependent diffusion MRI examinations, including pulsed gradient spin-echo (PGSE) diffusion-weighted imaging (DWI) and oscillating gradient spin-echo (OGSE) DWI at frequencies of 20 Hz and 40 Hz. A mono-exponential signal-fitting method was used to eliminate perfusion effects. Apparent diffusion coefficients (ADC), MR-cytometry-derived microstructural parameters (cell diameter <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\:\text{d}\)</EquationSource> </InlineEquation>, intracellular volume fraction <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\:{\text{v}}_{\text{i}\text{n}}\)</EquationSource> </InlineEquation>, extracellular diffusivity <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\:{D}_{ex}\)</EquationSource> </InlineEquation> and cellularity <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(\:{\uprho\:}\)</EquationSource> </InlineEquation>) and corresponding histogram features were calculated to differentiate lesions. Mann-Whitney U-tests were used to evaluate the differences between benign and malignant lesions. Uni- and multi-variate logistic regressions were performed and calculated the area under the receiver operating characteristic (AUC) to quantify the diagnostic performance of classifiers. Results Removal of perfusion effect improved the significance level of the difference in the cell diameter <InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(\:d\)</EquationSource> </InlineEquation> (from <InlineEquation ID="IEq6"> <EquationSource Format="TEX">\(\:\text{p}>0.05\)</EquationSource> </InlineEquation> to <InlineEquation ID="IEq7"> <EquationSource Format="TEX">\(\:\text{p}<0.01\)</EquationSource> </InlineEquation>), where <InlineEquation ID="IEq8"> <EquationSource Format="TEX">\(\:\text{d}\)</EquationSource> </InlineEquation> is larger in the benign group. The diagnostic efficacy of a single histogram feature was comparable to that of the corresponding ADC or microstructural parameter mean value. Both removing perfusion effect and incorporating histogram features can improve the AUC of the combined regression models (from 0.885 to 0.918 and 0.908, respectively). Combining both strategies further enhanced the AUC to 0.934. Conclusion In MR cytometry analysis, removing the perfusion effect and incorporating histogram features of ADCs and microstructural parameters can provide better diagnostic efficacy.

Improving the diagnostic efficacy of MR cytometry in prostate cancer imaging

期刊论文
发表日期：

2025年10月31日

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Jiahui Zhang,
Fan Liu,
Qianyu Peng,
Shuohong Gao,
Yongfei Wu,
Xiaoxiao Zhang,
Xin Bai,
Li Chen,
Erjia Guo,
Jinxia Zhu,
Thorsten Feiweier,
Hua Guo,
Zhengyu Jin,
Gumuyang Zhang,
Diwei Shi,
Hao Sun

摘要

Objectives

To evaluate the improved diagnostic efficacy of the emerging non-invasive microstructure imaging technique, MR cytometry, in differentiating benign and malignant prostate lesions, after removing perfusion effect and introducing histogram features.

Methods

This study included 33 patients with prostate cancer and 39 patients with benign lesions, who underwent time-dependent diffusion MRI examinations, including pulsed gradient spin-echo (PGSE) diffusion-weighted imaging (DWI) and oscillating gradient spin-echo (OGSE) DWI at frequencies of 20 Hz and 40 Hz. A mono-exponential signal-fitting method was used to eliminate perfusion effects. Apparent diffusion coefficients (ADC), MR-cytometry-derived microstructural parameters (cell diameter \(\:\text{d}\) , intracellular volume fraction \(\:{\text{v}}_{\text{i}\text{n}}\) , extracellular diffusivity \(\:{D}_{ex}\) and cellularity \(\:{\uprho\:}\) ) and corresponding histogram features were calculated to differentiate lesions. Mann-Whitney U-tests were used to evaluate the differences between benign and malignant lesions. Uni- and multi-variate logistic regressions were performed and calculated the area under the receiver operating characteristic (AUC) to quantify the diagnostic performance of classifiers.

Results

Removal of perfusion effect improved the significance level of the difference in the cell diameter \(\:d\) (from \(\:\text{p}>0.05\) to \(\:\text{p}<0.01\) ), where \(\:\text{d}\) is larger in the benign group. The diagnostic efficacy of a single histogram feature was comparable to that of the corresponding ADC or microstructural parameter mean value. Both removing perfusion effect and incorporating histogram features can improve the AUC of the combined regression models (from 0.885 to 0.918 and 0.908, respectively). Combining both strategies further enhanced the AUC to 0.934.

Conclusion

In MR cytometry analysis, removing the perfusion effect and incorporating histogram features of ADCs and microstructural parameters can provide better diagnostic efficacy.