Standard transcranial doppler as a resource-efficient first step to screen for MRA-defined cerebral vasculopathy in adults with sickle cell disease
Bibliographic record
Abstract
Abstract Background Cerebral vasculopathy in sickle cell disease (SCD) is associated with thrombotic and hemorrhagic stroke. Magnetic resonance angiography (MRA) can detect SCD-related arterial stenosis and aneurysms across the lifespan. In children, transcranial Doppler (TCD) is widely used to screen for elevated stroke risk and guide early intervention. In adults, however, the optimal neurosurveillance strategy remains undefined. While advanced modalities such as transcranial color-coded duplex sonography (TCCD) have shown high diagnostic accuracy compared to MRA, their availability and technical complexity may limit widespread implementation. Standard TCD, a simpler and more accessible tool, remains underexplored in this context. At our institution, all adults with SCD have access to routine TCD as part of standard care since 2021. If TCD-measured cerebral blood flow velocities correlate with MRA-defined vasculopathy, TCD could serve as a resource-efficient first step to identify adults who require further neurovascular imaging, particularly in resource-constrained settings. Objective The primary objective of this study was to assess whether mean flow velocities (MFV) measured by standard transcranial Doppler (TCD) correlate with MRA-defined cerebral vasculopathy (stenosis or aneurysm) in adults with SCD. We also explored whether a threshold MFV in the middle cerebral artery (MCA), the most routinely assessed vessel, could help rule out significant abnormalities on MRA, positioning TCD as a resource-efficient first step in neurosurveillance. Methods We conducted a retrospective study of adults (≥18 years) with SCD who underwent both routine TCD and MRA between 09/2021 and 07/2024 at a tertiary care center. TCD was performed by one of two certified vascular neurologists, measuring MFV in the middle (MCA), anterior (ACA), and posterior (PCA) cerebral arteries; bilateral values were averaged. MRA was performed using gadolinium-enhanced sequences, and radiology reports were reviewed for the presence of arterial stenosis or aneurysm. MFV were compared between patients with and without MRA-defined vasculopathy using independent samples t-tests. The study was approved by the local research ethics board. Results A total of 187 patients were included. The mean age was 35 ±13 years (range 18–79), and 104 (56%) were women. Hemoglobin phenotypes were evenly distributed, with 91 patients (49%) having SS or Sβ⁰-thalassemia and 96 (51%) having SC or Sβ⁺-thalassemia. The mean hemoglobin level was 11 ± 17 g/dL. One patient had a history of overt stroke. Nine patients (4.8%) had at least one MRA-defined stenosis in any of the 3 large vessels. These patients displayed significantly higher MFV in the MCA, but not in the ACA and PCA, as shown below: MCA MFV (cm/s); stenosis / no stenosis: (81 +/- 20) / (67 +/- 17), p = 0.012*. ACA MFV (cm/s); stenosis / no stenosis: (56 +/- 12) / (53 +/- 13), p = 0.230. PCA MFV (cm/s); stenosis / no stenosis: (47 +/- 9) / (38 +/- 11), p = 0.339. Additionally, all but 3 patients with at least one MRA-defined stenosis (any territory) had TCD-measured MFV ≥ 60 cm/s in the MCA (positive predictive value [PPV] 5%, negative predictive value [NPV] 96%). Thirty-three patients (17.6%) had at least one MRA-defined aneurysm. Likewise, they also displayed significantly higher MFV in the MCA, but not in the ACA and PCA, as shown below: MCA MFV (cm/s); aneurysm / no aneurysm: (75 +/- 17) / (66 +/- 17), p = 0.005*. ACA MFV (cm/s); aneurysm / no aneurysm: (56 +/- 12) / (52 +/- 13), p = 0.069. PCA MFV (cm/s); aneurysm / no aneurysm: (39 +/- 9) / (38 +/- 11), p = 0.353 Similarly, all but 2 patients with at least one MRA-defined aneurysm (any territory) had TCD-measured MFV ≥ 60 cm/s in the MCA territory (PPV 28%, NPV 97%). Conclusions Higher MFV in the MCA territory is associated with both MRA-defined stenoses and aneurysm across the 3 major cerebral arteries. An MCA MFV below 60 cm/s demonstrated a high negative predictive value for excluding these abnormalities. As an inexpensive and accessible tool, standard TCD may serve as a useful first-line screening modality in adults with SCD, particularly in resource-limited settings. These associations may reflect compensatory hyperemia or shear stress–related vascular remodeling, both of which warrant further investigation. Longitudinal studies are needed to validate the role of TCD in neurosurveillance and risk stratification.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".