Imaging Predictors of Intracerebral Hemorrhage in Patients with Brain Tumors Treated with Anticoagulation
Bibliographic record
Abstract
Introduction Spontaneous intracerebral hemorrhage (sICH) frequently occurs in patients with primary or metastatic brain tumors treated with anticoagulation and presents primarily as intratumoral bleeding. While an association between the burden of cerebral small vessel disease (CSVD) on brain magnetic resonance imaging (MRI) and sICH has been observed in patients receiving anticoagulation, it is unknown whether this holds true for patients with brain tumors. Intratumoral siderosis, a marker of prior subclinical sICH, represents a potential risk factor for subsequent sICH. Aim To evaluate whether markers of CSVD on brain MRI and intratumoral siderosis are associated with sICH in patients with brain tumors treated with anticoagulation. Methods This was a preplanned sub-study of the ABC study, a retrospective multinational cohort study which included 745 adults with primary or metastatic brain tumors treated with therapeutic-dose anticoagulation (low molecular weight heparin [LMWH] or direct oral anticoagulant [DOAC]) for any indication or duration (1/1/2014 - 1/1/2022), with 12 month follow up. All patients in whom baseline MRI images were available were included in the current study. MRI scans were analyzed for imaging markers of CSVD that are known to be independently associated with sICH in the general population, including white matter hyperintensities graded by Fazekas score (to reflect CSVD burden) and cerebral microbleeds. Baseline MRI scans were read and analyzed according to STRIVE-2 classification by a neurovascular research group specialized in CSVD imaging with excellent interrater reliability for these measures (Naftali 2023. PMID: 37978833). Intratumoral siderosis were also analyzed. The study outcome was sICH over 12 months follow-up, identified by record review and confirmed by a neuroradiologist, who was blinded to baseline MRIs. Baseline MRI readers were blinded to occurrence of sICH outcomes during follow up. Univariate analysis assessed associations between baseline MRI parameters and sICH, stratified for study center and adjusted for stopping anticoagulation. An additional analysis adjusted for cancer type as well. Results This analysis included 294 with baseline MRI of the 745 ABC patients. The median age was 63.0 years and 148 (50%) were female. Cancer types included primary brain tumors (123; 42.0%), metastases from primary lung (105; 36.0%), breast (29; 9.9%), and melanoma grouped with renal cell carcinoma tumors (12; 4.1%), as well as other types of cancer (25; 8.5%). The indication for anticoagulation was venous thromboembolism in 265 (90%) patients; 169 (57.5%) patients were treated with LMWH and 125 (42.5%) were treated with a DOAC. The 12-month cumulative incidence of sICH was 7.9% (95% confidence interval [CI] 5.3%-12.0%); 20/22 sICH events were intratumoral. The baseline MRI was performed at a median of 14 days (IQR 0-39) before study index date (i.e., first day of concurrent anticoagulation and brain tumor). Cerebral microbleeds and intratumoral siderosis could be assessed in the 224/294 patients with susceptibility weighted imaging (SWI) sequences performed. Fazekas score could be evaluated in the 290/294 patients with fluid attenuated inversion recovery (FLAIR) sequences. Nineteen of 224 (8.5%) patients had extratumoral cerebral microbleeds. Intratumoral siderosis was demonstrated in 83/224 (37%) patients. The Fazekas score was 0 or 1 (no or mild CSVD burden) in 261/290 (90%) patients and 2 or 3 (moderate to severe CSVD burden) in 29/290 (10%) patients. On univariable analysis, intratumoral siderosis (hazard ratio [HR] 3.44; 95% CI 1.01-11.7); cerebral microbleeds (HR 8.13; 95% CI 1.81-36.6) and moderate to severe CSVD burden (HR 4.71; 95% CI 1.89-11.7) were associated with sICH. Adjustment for cancer type demonstrated similar associations for intratumoral siderosis (HR 2.59; 95% CI 0.70-9.67), cerebral microbleeds (HR 11.4; 95% CI 1.71 - 76.1) and moderate to severe CSVD burden (HR 5.28; 95% CI 1.94 - 14.4). In a cross-correlation analysis, no statistically significant associations between the 3 MRI parameters were observed at baseline. Conclusion Baseline MRI findings appear to be predictive of sICH in patients with brain tumors treated with anticoagulation. Future studies should assess whether these parameters can guide management of anticoagulation in this population.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".