Highly Symptomatic Progressing Cardiac Paraganglioma With Intracardiac Extension Treated With 177Lu-DOTATATE: A Case Report
Bibliographic record
Abstract
Introduction Primary cardiac paragangliomas are rare tumors. Metastatic disease is even rarer. Surgical management is technically challenging, and sometimes even impossible. Available therapeutic modalities for metastatic disease include external beam radiation therapy as well as systemic treatments, namely 131I-MIBG and more recently, peptide receptor radionuclide therapy (PRRT) with 177Lu-DOTATATE. To our knowledge, this is the first case of progressive unresectable cardiac paraganglioma with intracardiac extension treated with dosimetry based personalized PRRT to be reported. This case is of particular interest since it documents for the first time the efficacy, and especially the safety of the 177Lu-DOTATATE PRRT in this precarious context for which therapeutic options are limited. Case Presentation A 47-year-old man with no medical history consulted for rapidly decreasing exercise tolerance. The investigation demonstrated an unresectable progressing metastatic cardiac paraganglioma with intracardiac extension. The patient was treated with personalized 177Lu-DOTATATE PRRT and showed complete symptomatic and partial anatomical responses, with a progression-free survival of 13 months. Conclusions PRRT with 177Lu-DOTATATE should be considered for inoperable cardiac paraganglioma. No major hemodynamic complications were experienced. Therapy resulted in safety and substantially improved quality of life.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| 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".