Value of Multiparametric Imaging Based on Three-Dimensional Arterial Spin Labeling Combined With Time-Dependent Diffusion MRI in Differentiating True Progression From Pseudoprogression After Glioma Surgery
Value of Multiparametric Imaging Based on Three-Dimensional Arterial Spin Labeling Combined With Time-Dependent Diffusion MRI in Differentiating True Progression From Pseudoprogression After Glioma Surgery
Background: Differentiating true progression (TP) from pseudoprogression (PsP) after glioma surgery remains a major clinical challenge because conventional magnetic resonance imaging (MRI) often cannot reliably distinguish these conditions.
Objective: This prospective observational diagnostic accuracy study aims to evaluate the value of multiparametric imaging based on three-dimensional arterial spin labeling (3D-ASL) combined with time-dependent diffusion MRI (TDD-MRI) for differentiating TP from PsP in postoperative glioma patients.
Methods: Consecutive adult patients with suspected tumor progression after glioma surgery will undergo routine MRI, 3D-ASL, and TDD-MRI examinations. Quantitative perfusion and diffusion parameters will be extracted, and a combined imaging model will be developed and evaluated. Final diagnosis will be established according to pathological findings when available or by longitudinal clinical and imaging follow-up based on the Response Assessment in Neuro-Oncology (RANO) criteria.
Expected Outcomes: The primary outcome is the diagnostic performance of the combined imaging model, assessed by the area under the receiver operating characteristic curve (AUC). The study is expected to provide a noninvasive imaging strategy for distinguishing TP from PsP and to support clinical decision-making during postoperative follow-up.
Glioma is the most common primary malignant tumor of the central nervous system and is characterized by high invasiveness and a high recurrence rate. During postoperative follow-up after surgery and adjuvant therapy, newly developed or enlarged contrast-enhancing lesions may represent either true progression (TP) or treatment-related pseudoprogression (PsP). Because these entities require substantially different clinical management, accurate differentiation is essential.
Histopathological confirmation remains the reference standard but is invasive and not feasible for all patients. Conventional MRI has limited diagnostic accuracy because TP and PsP often demonstrate overlapping imaging characteristics. Advanced functional MRI techniques have therefore attracted increasing interest for improving noninvasive diagnosis.
Three-dimensional arterial spin labeling (3D-ASL) provides quantitative assessment of cerebral perfusion without exogenous contrast agents, whereas time-dependent diffusion MRI (TDD-MRI) characterizes tissue microstructure by measuring water diffusion under different diffusion times. These techniques provide complementary information regarding tumor vascularity and cellular architecture.
This is a single-center, prospective observational diagnostic accuracy study conducted at Lanzhou University Second Hospital. Approximately 75 consecutive postoperative glioma patients with suspected disease progression will be enrolled. All participants will undergo routine MRI, 3D-ASL, and TDD-MRI examinations according to a standardized imaging protocol. Quantitative imaging parameters, including relative cerebral blood flow (rCBF), ADC20Hz, ADC40Hz, Cellularity, and Diameter, will be extracted after image preprocessing and lesion segmentation.
Participants will not receive any additional therapeutic intervention as part of the study. Clinical management will be determined by treating physicians according to routine clinical practice. Final classification of TP or PsP will be established using pathological confirmation whenever available or comprehensive longitudinal clinical and imaging follow-up according to the RANO 2.0 criteria.
The primary objective is to evaluate the diagnostic performance of the combined 3D-ASL and TDD-MRI model using the area under the receiver operating characteristic curve (AUC). Secondary objectives include evaluating the diagnostic performance of individual imaging parameters, comparing diagnostic models, assessing calibration and clinical utility, determining interobserver agreement, and exploring the influence of clinicopathological factors on model performance.
The findings of this study are expected to establish a reliable, noninvasive multiparametric MRI strategy for differentiating TP from PsP after glioma surgery, thereby facilitating individualized postoperative management and reducing unnecessary invasive procedures.
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