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Histogram analysis of MR quantitative parameters: are they correlated with prognostic factors in prostate cancer?
Yanling Chen1, Tiebao Meng2, Wenxin Cao1
1Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, No. 58 Zhongshan 2nd Road, Guangzhou, 510080, Guangdong, People's Republic of China.
Purpose:
To investigate the correlation between quantitative MR parameters and prognostic factors in prostate cancer (PCa).
Method:
A total of 186 patients with pathologically confirmed PCa who underwent preoperative multiparametric MRI (mpMRI), including synthetic MRI (SyMRI), were enrolled from two medical centers. The histogram metrics of SyMRI [T1, T2, proton density (PD)] and apparent diffusion coefficient (ADC) values were extracted. The Mann‒Whitney U test or Student's t test was employed to determine the association between these histogram features and the prognostically relevant factors. Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the differentiation performance. Spearman's rank correlation coefficients were calculated to determine the correlations between histogram parameters and the International Society of Urological Pathology (ISUP) grade group as well as pathological T stage.
Results:
Significant correlations were found between the histogram parameters and the ISUP grade as well as pathological T stage of PCa. Among these histogram parameters, ADC_minimum had the strongest correlation with the ISUP grade (r = - 0.481, p < 0.001), and ADC_Median showed the strongest association with pathological T stage (r = - 0.285, p = 0.008). The ADC_10th percentile exhibited the highest performance in identifying clinically significant prostate cancer (csPCa) (AUC 0.833; 95% CI 0.771-0.883). When discriminating between the status of different prognostically relevant factors, a significant difference was observed between extraprostatic extension-positive and -negative cancers with regard to histogram parameters of the ADC map (10th percentile, 90th percentile, mean, median, minimum) and T1 map (minimum) (p = 0.002-0.032). Moreover, histogram parameters of the ADC map (90th percentile, maximum, mean, median), T2 map (10th percentile, median), and PD map (10th percentile, median) were significantly lower in PCa with perineural invasion (p = 0.009-0.049). The T2 values were significantly lower in patients with seminal vesicle invasion (minimum, p = 0.036) and positive surgical margin (10th percentile, 90th percentile, mean, median, and minimum, p = 0.015-0.025).
Conclusion:
Quantitative histogram parameters derived from synthetic MRI and ADC maps may have great potential for predicting the prognostic features of PCa.
Insights
Quantitative MRI parameters from synthetic MRI and ADC maps correlate with prostate cancer prognostic factors. These findings suggest potential for predicting cancer aggressiveness and staging non-invasively.
Area of Science:
- Radiology
- Oncology
- Medical Imaging
Background:
- Prostate cancer (PCa) prognosis is critical for treatment decisions.
- Accurate staging and grading of PCa are essential for patient management.
- Multiparametric MRI (mpMRI) offers quantitative insights into tumor characteristics.
Purpose of the Study:
- To investigate the correlation between quantitative MRI parameters and prognostic factors in prostate cancer (PCa).
- To evaluate the predictive potential of synthetic MRI (SyMRI) and apparent diffusion coefficient (ADC) histogram metrics for PCa prognosis.
Main Methods:
- 186 PCa patients underwent preoperative mpMRI, including SyMRI.
- Histogram metrics from SyMRI (T1, T2, PD) and ADC maps were extracted.
- Statistical analyses (Mann‒Whitney U, t test, ROC, Spearman correlation) assessed associations with prognostic factors (ISUP grade, T stage, etc.).
Main Results:
- Significant correlations were found between histogram parameters and ISUP grade/pathological T stage.
- ADC_minimum showed the strongest correlation with ISUP grade (r = -0.481), ADC_Median with T stage (r = -0.285).
- ADC_10th percentile demonstrated high performance in identifying clinically significant PCa (AUC 0.833). Significant differences in ADC, T1, T2, and PD parameters were observed for extraprostatic extension, perineural invasion, seminal vesicle invasion, and positive surgical margins.
Conclusions:
- Quantitative histogram parameters from SyMRI and ADC maps show significant correlations with PCa prognostic factors.
- These parameters hold potential for non-invasively predicting PCa aggressiveness and aiding in staging.
- Further validation may establish these quantitative MRI metrics in routine PCa assessment.
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