Partial splenic embolization to manage thrombocytopenia in cancer patients: Case series and review of the literature
Bibliographic record
Abstract
Abstract Introduction Thrombocytopenia is a common complication of cancer and its management (Liebman, 2014). Alleviating thrombocytopenia in cancer patients is essential to avoid dose-reduction or delay of chemotherapy (Soff et al., 2024). Partial splenic embolization (PSE) is a procedure that can increase their platelet count, allowing for initiation/resumption of chemotherapy. We present two cases of cancer patients that had a PSE, but had different experiences/outcomes. Using this case series, we aim to provide some insight on enhancing the procedure's effectiveness and safety for this patient population. Methods A search of the PubMed and Ovid databases for articles that discussed PSEs performed on cancer patients was completed. After excluding irrelevant articles, data was extracted from the remaining papers and organized into tables to support the discussion. Two case reports were written based on up-to-date information from the patients' charts. Data from hematology, oncology and interventional radiology consult notes, lab work and imaging reports were used to present the clinical cases. Results The first case was a patient with metastatic colorectal cancer that had been on palliative chemotherapy, which was repeatedly delayed due to thrombocytopenia. They underwent a PSE that resulted in about 30-35% embolization of the spleen. The PSE increased their platelet count, allowing them to re-initiate chemotherapy. However, their thrombocytopenia worsened 18 months later, such that a second PSE was necessary to return to treatment. The second patient had breast cancer that required adjuvant combined chemoradiation therapy. They had thrombocytopenia, so to improve this and proceed with treatment, they underwent a PSE. After the procedure, the patient was found to have infarction of the whole spleen, severe necrotizing pancreatitis, and splenic and portal vein thrombosis. Although their platelet count increased post-PSE, they were not deemed a candidate for chemotherapy due to delays and complications. Discussion These cases present potential room for improvement of the effectiveness and safety of the PSEs performed. In the first case, the patient had a recurrence of thrombocytopenia after their first PSE, during which 30-35% of the spleen was embolized. The percentage of spleen embolized may partially explain the re-emergence of thrombocytopenia, as one study suggests that a minimum of 50% splenic infarction is associated with long-term improvements in platelet count (up to 5 years post-PSE) in cirrhotic patients with hypersplenism (Zhu et al., 2009). However, the increase in platelet count post-PSE is multifactorial, and this patient also experienced an increase in their chemotherapy dose that could have had an impact. Moreover, in the second case, excessive embolization of the spleen occurred (complete as opposed to partial), likely the result of unintentional non-target embolization. Understanding how to prevent non-target embolization is important to minimize complications. Estimating the volume of spleen that has been infarcted intraprocedurally is a difficult task and most methods strongly rely on operator experience (Koizumi et al., 2013; Ou et al., 2013). Being able to use imaging intraprocedurally for this purpose has the potential to decrease the likelihood of excessive embolization and associated complications (Koizumi et al., 2013). Acquiring a deeper understanding of a patient's splenic anatomy could also help guide a safer embolization. Overall, these cases demonstrate that although a PSE can benefit a cancer patient, there can be serious complications associated with the procedure. Understanding how to enhance the effectiveness and safety of PSEs in cancer patients is key to successful and durable outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".