Eleven-Year Retrospective Report of Super-Selective Venous Sampling for the Evaluation of Recurrent or Persistent Hyperparathyroidism in 32 Patients

Peiman Habibollahi, Benjamin Shin, Sara P. Shamchi, Heather Wachtel, Douglas L. Fraker, Scott O. Trerotola

Research output: Contribution to journalArticle

2 Scopus citations


Purpose: Parathyroid venous sampling (PAVS) is usually reserved for patients with persistent or recurrent hyperparathyroidism after parathyroidectomy with inconclusive noninvasive imaging studies. A retrospective study was performed to evaluate the diagnostic efficacy of super-selective PAVS (SSVS) in patients needing revision neck surgery with inconclusive imaging. Materials and Methods: Patients undergoing PAVS between 2005 and 2016 due to persistent or recurrent hyperparathyroidism following surgery were reviewed. PAVS was performed in all patients using super-selective technique. Single-value measurements within central neck veins performed as part of super-selective PAVS were used to simulate selective venous sampling (SVS) and allow for comparison to data, which might be obtained in a non-super-selective approach. Results: 32 patients (mean age 51 ± 15 years; 8 men and 24 women) met inclusion and exclusion criteria. The sensitivity and positive predictive value (PPV) of SSVS for localizing the source of elevated PTH to a limited area in the neck or chest was 96 and 84%, respectively. Simulated SVS, on the other hand, had a sensitivity of 28% and a PPV of 89% based on the predefined gold standard. SSVS had a significantly higher sensitivity compared to simulated SVS (p < 0.001). Conclusion: SSVS is highly effective in localizing the source of hyperparathyroidism in patients undergoing revision surgery for hyperparathyroidism in whom noninvasive imaging studies are inconclusive. SSVS data had also markedly higher sensitivity for localizing disease in these patients compared to simulated SVS.

Original languageEnglish (US)
Pages (from-to)63-72
Number of pages10
JournalCardiovascular and Interventional Radiology
Issue number1
StatePublished - Jan 1 2018


All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging
  • Cardiology and Cardiovascular Medicine

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