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Amide Proton Transfer-Weighted Imaging Combined With Intravoxel Incoherent Motion for Evaluating Microsatellite
Changjun Ma1,2, Shifeng Tian1,2, Qingling Song1,2
1Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Background:
Microsatellite instability (MSI), caused by mismatch repair (MMR) protein defects that lead to uncorrectable mismatch bases, results in the accumulation of gene mutations and ultimately to tumors. Preoperative prediction of MSI can provide a basis for personalized and precise treatment of endometrial cancer (EC) patients.
Purpose:
To investigate amide proton transfer weighting (APTw) imaging combined with intravoxel incoherent motion (IVIM) in the assessment of MSI in EC.
Study Type:
Retrospective.
Population:
A total of 71 patients with EC (12 classified as the MSI group and 22 as the microsatellite stabilization [MSS] group after entering and leaving the group standard).
Field Strength/Sequence:
A 3.0 T/IVIM, diffusion-weighted imaging (DWI) and APTw.
Assessment:
Amide proton transfer (APT) value, apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo diffusion coefficient (D*), and perfusion fraction (f) were calculated and compared between MSI and MSS groups.
Statistical Tests:
The Kendall's W test; Mann-Whitney U-test; Chi-square test or Fisher's exact test; logistic regression analysis; Area under the receiver operating characteristic (ROC) curve (AUC); The Delong test; Pearson or Spearman correlation coefficients. The significance threshold was set at P < 0.05.
Results:
APT and D* values of the MSI group were significantly higher than those of the MSS group. While ADC, D, and f values in the MSI group were significantly lower than those in the MSS group. The multivariate analysis revealed that only APT and D* values were independent predictors to evaluate the MSI status. And the ROC curves indicated that the combination of APT and D* values could distinguish the MSI status of EC with the highest diagnostic efficacy (AUC = 0.973), even without significant difference to those by APT (AUC = 0.894) or D* (AUC = 0.920) value separately (P = 0.149 and 0.078, respectively).
Conclusion:
Combination of APTw and IVIM imaging may serve as an effective noninvasive method for clinical assessment of MSI in EC.
Evidence Level:
3 TECHNICAL EFFICACY: Stage 2.
Insights
Preoperative prediction of microsatellite instability (MSI) in endometrial cancer (EC) is improved by combining amide proton transfer weighting (APTw) imaging and intravoxel incoherent motion (IVIM). This noninvasive approach enhances diagnostic accuracy for personalized treatment strategies.
Area of Science:
- Oncology
- Radiology
- Biomedical Imaging
Background:
- Microsatellite instability (MSI) in endometrial cancer (EC) arises from DNA mismatch repair defects, leading to mutations and tumor development.
- Preoperative MSI prediction is crucial for tailoring personalized and precise treatment plans for EC patients.
Purpose of the Study:
- To evaluate the efficacy of amide proton transfer weighting (APTw) imaging combined with intravoxel incoherent motion (IVIM) for assessing MSI in EC.
- To determine if these imaging techniques can noninvasively predict MSI status in EC patients.
Main Methods:
- A retrospective study involving 71 EC patients (12 MSI, 22 MSS).
- Utilized 3.0T MRI with IVIM, diffusion-weighted imaging (DWI), and APTw sequences.
- Calculated and compared parameters including APT value, ADC, D, D*, and f between MSI and MSS groups.
Main Results:
- Patients with MSI showed significantly higher APT and D* values compared to the MSS group.
- Conversely, ADC, D, and f values were significantly lower in the MSI group.
- Multivariate analysis identified APT and D* as independent predictors of MSI status, with their combination achieving the highest diagnostic efficacy (AUC = 0.973).
Conclusions:
- The combination of APTw and IVIM imaging offers a promising noninvasive method for the clinical assessment of MSI in EC.
- This approach can aid in preoperative prediction and guide personalized treatment decisions for EC patients.
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