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• Clinical Article •
Diagnostic performance of a multiparameter combined model based on 3D-ASL and TDD-MRI for distinguishing true progression from pseudoprogression of glioma after postoperative radiotherapy
CHANG Junwei  HU Wanjun  HAN Yuping  LI Yisu  DING Xue  ZHANG Jing 

Cite this article as: CHANG J W, HU W J, HAN Y P, et al. Diagnostic performance of a multiparameter combined model based on 3D-ASL and TDD-MRI for distinguishing true progression from pseudoprogression of glioma after postoperative radiotherapy[J]. Chin J Magn Reson Imaging, 2026, 17(9): 118-128. DOI:10.12015/issn.1674-8034.2026.09.016.


[Abstract] Objective To evaluate the diagnostic performance of a combined model based on perfusion parameters derived from three-dimensional arterial spin labeling (3D-ASL) and time-dependent diffusion MRI (TDD-MRI) for differentiating true progression (TP) from pseudoprogression (PsP) in postoperative glioma patients with suspected progression after radiotherapy.Materials and Methods This study was registered at ClinicalTrials.gov under the registration number NCT07687277. Seventy-five postoperative glioma patients with suspected progression during follow-up at Lanzhou University Second Hospital from March 2024 to February 2025 were prospectively enrolled. Final classification was based on the Response Assessment in Neuro-Oncology 2.0 (RANO 2.0) criteria, repeat surgery or biopsy pathology when available, and serial clinical-imaging follow-up findings. Patients were ultimately classified into the TP group (n = 45) and the PsP group (n = 30). All patients underwent conventional MRI, 3D-ASL and TDD-MRI examinations. The contrast-enhancing solid region on contrast-enhanced T1-weighted imaging was delineated as the volume of interest (VOI). Perfusion parameters, including the mean, maximum and minimum relative cerebral blood flow (rCBFmean, rCBFmax and rCBFmin), and microstructural parameters, including the apparent diffusion coefficient at 20 Hz (ADC20 Hz), the apparent diffusion coefficient at 40 Hz (ADC40 Hz), Cellularity, and Diameter, were extracted. Interobserver agreement was assessed using intra-class correlation coefficient (ICC). Group differences were compared using the independent-samples t test or Mann-Whitney U test. Univariable logistic regression, least absolute shrinkage and selection operator (LASSO) regression, and enter-method multivariable logistic regression were performed to identify imaging parameters associated with TP/PsP differentiation and establish a combined model. Receiver operating characteristic (ROC) curve analysis was used to evaluate diagnostic performance.Results All parameters showed good interobserver agreement, with ICCs greater than 0.75. rCBFmean, rCBFmax, rCBFmin, and Cellularity were higher in the TP group than in the PsP group, whereas ADC20 Hz and ADC40 Hz were lower in the TP group. The corresponding group-comparison Z values were 2.926, 3.412, 2.190, 4.451, 4.973, and 4.938, respectively, and all differences were significant (all P < 0.05). Diameter showed no significant difference between the two groups (Z = 0.990, P = 0.322). LASSO regression selected rCBFmax, ADC20 Hz, ADC40 Hz, and Cellularity to construct the combined model. Enter-method multivariable logistic regression showed that rCBFmax (OR = 1.061, 95% CI: 1.001 to 1.126, P = 0.048) and ADC40 Hz (OR = 0.668, 95% CI: 0.473 to 0.942, P = 0.021) were independent factors for differentiating TP from PsP. ROC analysis showed that the combined model had the numerically highest area under the curve (AUC) of 0.890 (95% CI: 0.797 to 0.951), with a sensitivity of 73.33% and a specificity of 93.33%. Among single parameters, ADC40 Hz showed the highest AUC of 0.839 (95% CI: 0.735 to 0.913). The DeLong test showed that the AUC of the combined model was significantly higher than those of rCBFmax and Cellularity (all P < 0.05), whereas its AUC was not significantly different from those of ADC20 Hz or ADC40 Hz (all P > 0.05).Conclusions The multiparametric model combining 3D-ASL and TDD-MRI showed diagnostic performance for differentiating TP from PsP. In glioma patients with suspected progression after postoperative radiotherapy, this model may provide adjunctive information for differential diagnosis and imaging support for comprehensive clinical assessment.
[Keywords] glioma；magnetic resonance imaging；arterial spin labeling；time-dependent diffusion magnetic resonance imaging；combined model；true progression；pseudoprogression

CHANG Junwei1, 2, 3   HU Wanjun1, 2, 3   HAN Yuping1, 2, 3   LI Yisu1, 2, 3   DING Xue4   ZHANG Jing1, 2, 3*  

1 Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 730030, China

2 Second Clinical School, Lanzhou University, Lanzhou 730030, China

3 Gansu Functional and Molecular Imaging Clinical Medical Research Center, Lanzhou 730030, China

4 School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China

Corresponding author: ZHANG J, E-mail: ery_zhangjing@lzu.edu.cn

Conflicts of interest   None.

Received  2026-04-25
Accepted  2026-08-05
DOI: 10.12015/issn.1674-8034.2026.09.016
Cite this article as: CHANG J W, HU W J, HAN Y P, et al. Diagnostic performance of a multiparameter combined model based on 3D-ASL and TDD-MRI for distinguishing true progression from pseudoprogression of glioma after postoperative radiotherapy[J]. Chin J Magn Reson Imaging, 2026, 17(9): 118-128. DOI:10.12015/issn.1674-8034.2026.09.016.

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