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NCT Number: NCT07687277

3D-ASL and TDD-MRI for True Progression and 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.

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Key information

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age 18 years or older.
  • Histopathologically confirmed glioma.
  • Received standard postoperative treatment or routine clinical treatment.
  • New or enlarged contrast-enhancing lesion on follow-up MRI suggestive of tumor progression.
  • Able to undergo routine MRI, three-dimensional arterial spin labeling (3D-ASL), and time-dependent diffusion MRI (TDD-MRI).
  • MRI image quality sufficient for image processing, registration, lesion segmentation, and quantitative parameter extraction.
  • Written informed consent provided by the participant or legally authorized representative.

Exclusion criteria

  • Incomplete clinical, pathological, or imaging follow-up data.
  • MRI images with severe motion artifacts, susceptibility artifacts, or geometric distortion affecting image analysis.
  • Failure to complete routine MRI, 3D-ASL, or TDD-MRI examinations according to the study protocol.
  • Lesions too small or poorly defined for reliable three-dimensional volume-of-interest delineation and parameter extraction.
  • Any other condition judged by the investigators to make participation inappropriate.

Treatment and study plan

Multiparametric MRI (3D-ASL and TDD-MRI)

Diagnostic Test

Participants undergo standardized multiparametric magnetic resonance imaging, including routine MRI, three-dimensional arterial spin labeling (3D-ASL), and time-dependent diffusion MRI (TDD-MRI). Quantitative perfusion and diffusion parameters are extracted for evaluation of their diagnostic performance in differentiating true progression from pseudoprogression after glioma surgery. No experimental therapeutic intervention is administered as part of the study.

Primary outcomes

  1. AUC of the Combined 3D-ASL and TDD-MRI Model

    Time frame: From enrollment through completion of clinical and imaging follow-up (up to 12 months)

    Area under the receiver operating characteristic curve (AUC) of the combined three-dimensional arterial spin labeling (3D-ASL) and time-dependent diffusion MRI (TDD-MRI) model for differentiating true progression from pseudoprogression after glioma surgery.

Secondary outcomes

  1. AUC of rCBFmean

    Time frame: From enrollment through completion of clinical and imaging follow-up (up to 12 months)

    Area under the receiver operating characteristic curve (AUC) of mean relative cerebral blood flow (rCBFmean) for differentiating true progression from pseudoprogression.

  2. AUC of rCBFmax

    Time frame: From enrollment through completion of clinical and imaging follow-up (up to 12 months)

    Area under the receiver operating characteristic curve (AUC) of maximum relative cerebral blood flow (rCBFmax) for differentiating true progression from pseudoprogression.

  3. AUC of rCBFmin

    Time frame: From enrollment through completion of clinical and imaging follow-up (up to 12 months)

    Area under the receiver operating characteristic curve (AUC) of minimum relative cerebral blood flow (rCBFmin) for differentiating true progression from pseudoprogression.

  4. AUC of ADC20Hz

    Time frame: From enrollment through completion of clinical and imaging follow-up (up to 12 months)

    Area under the receiver operating characteristic curve (AUC) of ADC20Hz derived from time-dependent diffusion MRI for differentiating true progression from pseudoprogression.

  5. AUC of ADC40Hz

    Time frame: From enrollment through completion of clinical and imaging follow-up (up to 12 months)

    Area under the receiver operating characteristic curve (AUC) of ADC40Hz derived from time-dependent diffusion MRI for differentiating true progression from pseudoprogression.

  6. AUC of Cellularity

    Time frame: From enrollment through completion of clinical and imaging follow-up (up to 12 months)

    Area under the receiver operating characteristic curve (AUC) of the Cellularity parameter derived from time-dependent diffusion MRI for differentiating true progression from pseudoprogression.

  7. AUC of Diameter

    Time frame: From enrollment through completion of clinical and imaging follow-up (up to 12 months)

    Area under the receiver operating characteristic curve (AUC) of the Diameter parameter derived from time-dependent diffusion MRI for differentiating true progression from pseudoprogression.

  8. Sensitivity of the Combined 3D-ASL and TDD-MRI Model

    Time frame: From enrollment through completion of clinical and imaging follow-up (up to 12 months)

    Sensitivity of the combined 3D-ASL and TDD-MRI model for differentiating true progression from pseudoprogression.

  9. Specificity of the Combined 3D-ASL and TDD-MRI Model

    Time frame: From enrollment through completion of clinical and imaging follow-up (up to 12 months)

    Specificity of the combined 3D-ASL and TDD-MRI model for differentiating true progression from pseudoprogression.

  10. Youden Index of the Combined 3D-ASL and TDD-MRI Model

    Time frame: From enrollment through completion of clinical and imaging follow-up (up to 12 months)

    Youden index of the combined 3D-ASL and TDD-MRI model for differentiating true progression from pseudoprogression.

  11. Optimal Cutoff of the Combined 3D-ASL and TDD-MRI Model

    Time frame: From enrollment through completion of clinical and imaging follow-up (up to 12 months)

    Optimal cutoff value of the combined 3D-ASL and TDD-MRI model determined from receiver operating characteristic curve analysis.

  12. AUC Difference Between the Combined Model and the Best Individual MRI Parameter

    Time frame: From enrollment through completion of clinical and imaging follow-up (up to 12 months)

    Difference in AUC between the combined 3D-ASL and TDD-MRI model and the best-performing individual MRI parameter.

  13. Hosmer-Lemeshow Goodness-of-Fit P Value

    Time frame: After completion of model construction and statistical analysis

    Hosmer-Lemeshow goodness-of-fit test P value for evaluating calibration of the combined 3D-ASL and TDD-MRI model.

  14. Clinical Net Benefit of the Combined 3D-ASL and TDD-MRI Model

    Time frame: After completion of model construction and statistical analysis

    Clinical net benefit of the combined 3D-ASL and TDD-MRI model assessed using decision curve analysis.

  15. Interobserver Agreement for MRI Parameter Measurements

    Time frame: At image analysis after completion of MRI examinations

    Interobserver agreement for quantitative MRI parameter measurements assessed using the intraclass correlation coefficient (ICC).

Sponsors and collaborators

Lead sponsor

Lanzhou University Second Hospital

Other

Registry information

Official study title

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

Acronym: ASL-TDD

Important dates

Study start
2024
Primary completion
2026
Study completion
2026
First posted
Jul 7, 2026
Registry last updated
Jul 7, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

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This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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