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Correlation of Intravoxel Incoherent Motion and Diffusion Kurtosis MR Imaging Models With Reactive Stromal Grade in
Zhiqing Duan1, Shaobo Fang2,3, Jiawei Hu1
1Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, People's Republic of China.
Background:
Reactive stroma is recognized as one of the independent prognostic factors in prostate cancer (PCa). Intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) may be useful for assessing the reactive stromal grade (RSG).
Purpose:
To investigate whether IVIM and DKI models can evaluate RSG in PCa patients.
Study Type:
Retrospective.
Subjects:
A total of 56 PCa patients aged 73 years on average confirmed by MRI and transrectal ultrasound (MRI/TRUS) fusion biopsy divided into two subgroups (18 high RSG and 38 low RSG).
Field Strength/Sequence:
A 3 T/T1 WI-fs, T1 WI, T2 WI-fs, T2 WI, DWI, IVIM, and DKI.
Assessment:
Apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), mean diffusion (MD), mean kurtosis (MK) were obtained. Patients were divided into high RSG PCa (>50% reactive stroma) and low RSG PCa (≤50% reactive stroma) groups on hematoxylin and eosin (H&E) stained sections.
Statistical Tests:
Spearman correlation and independent sample t-test or Wilcoxon's rank sum test was used to investigate the relationship between each imaging parameter and RSG. The combined parameters were calculated using a binary logistic regression model. Receiver operating characteristic (ROC) analysis was used to explore the value of individual and combined parameters to differentiate between high and low RSG group. Area under the ROC curves (AUC) > 0.7 were used as reference standards.
Results:
ADC, D, f, and MD values showed positive correlation with RSG (r = 0.489, 0.619, 0.318, and 0.544, respectively); MK showed negative correlation with RSG (r = -0.444). ADC, D, f, and MD values were significantly lower in the low RSG group than in the high RSG group. The combined model showed the best diagnostic ability to differentiate low and high RSG groups (AUC = 0.887).
Data Conclusion:
Parameters of IVIM and DKI may be promising methods for assessment of RSG in PCa patients.
Evidence Level:
3.
Technical Efficacy:
Stage 3.
Insights
Intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) show promise in evaluating prostate cancer (PCa) reactive stromal grade (RSG). These advanced MRI techniques can help differentiate between high and low RSG, aiding in prognosis.
Area of Science:
- Radiology
- Oncology
- Medical Imaging
Background:
- Reactive stroma is a key prognostic factor in prostate cancer (PCa).
- Assessing reactive stromal grade (RSG) is crucial for PCa patient management.
- Advanced MRI techniques like IVIM and DKI may offer novel ways to evaluate RSG.
Purpose of the Study:
- To investigate the utility of Intravoxel Incoherent Motion (IVIM) and Diffusion Kurtosis Imaging (DKI) models for assessing RSG in PCa patients.
- To determine if IVIM and DKI parameters can effectively differentiate between high and low RSG in PCa.
- To evaluate the diagnostic performance of individual and combined IVIM/DKI parameters.
Main Methods:
- Retrospective analysis of 56 PCa patients (mean age 73 years).
- Data acquired using 3T MRI including IVIM and DKI sequences.
- Apparent diffusion coefficient (ADC), D, D*, f, mean diffusion (MD), and mean kurtosis (MK) were calculated and correlated with RSG determined by H&E staining.
Main Results:
- ADC, D, f, and MD values positively correlated with RSG, while MK showed a negative correlation.
- These parameters were significantly different between high and low RSG groups.
- A combined IVIM/DKI model achieved an AUC of 0.887 for differentiating high from low RSG.
Conclusions:
- IVIM and DKI parameters demonstrate potential for non-invasively assessing RSG in PCa.
- These advanced MRI techniques may serve as valuable tools for PCa prognosis and treatment planning.
- The combined IVIM/DKI model shows high diagnostic accuracy for RSG evaluation.
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