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Abstract
Background: The surgical management of persistent or recurrent primary hyperparathyroidism (PHPT) is critically dependent on accurate preoperative localization of ectopic or residual hyperfunctioning glands within a scarred anatomical field. While 18F-Fluorocholine Positron Emission Tomography/Computed Tomography (18F-FCH PET/CT), four-dimensional computed tomography (4D-CT), and 99mTc-Sestamibi scintigraphy are employed, a definitive evidence-based hierarchy to guide their use is absent. This study aimed to establish this hierarchy by comparing their diagnostic performance through a network meta-analysis.
Methods: A systematic search of PubMed, Embase, and Scopus was conducted for comparative studies published between January 2015 and August 2025 evaluating these modalities in persistent/recurrent PHPT. A Bayesian bivariate network meta-analysis was performed to calculate pooled sensitivities and specificities on both a per-patient and per-lesion basis. Modalities were ranked using Surface Under the Cumulative Ranking (SUCRA) scores. Methodological quality, inconsistency, and heterogeneity were formally assessed.
Results: Seven studies involving 687 patients were included. On a per-patient analysis, 18F-FCH PET/CT demonstrated the highest sensitivity at 94.1% (95% Credible Interval [CrI]: 89.8%–97.5%), significantly outperforming 4D-CT (82.5%; 95% CrI: 75.1%–88.9%) and scintigraphy with SPECT/CT (60.3%; 95% CrI: 51.2%–69.1%). Specificities were uniformly high. Per-lesion analysis confirmed this hierarchy. SUCRA rankings identified 18F-FCH PET/CT as the superior modality for both per-patient (98.7%) and per-lesion (99.1%) detection. No significant network inconsistency was detected.
Conclusion: 18F-FCH PET/CT exhibits superior diagnostic accuracy for localizing culprit parathyroid glands in persistent or recurrent PHPT. Its performance, grounded in robust metabolic targeting that overcomes the challenges of a reoperative field, supports its positioning as the primary imaging modality in this setting. These findings advocate for a revision of current diagnostic algorithms to enhance surgical planning and improve patient outcomes.
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