Diagnostic Performance of Magnetic Resonance Imaging for Parathyroid Localization of Primary Hyperparathyroidism: A Systematic Review.

diagnostics magnetic resonance imaging preoperative primary hyperparathyroidism

Journal

Diagnostics (Basel, Switzerland)
ISSN: 2075-4418
Titre abrégé: Diagnostics (Basel)
Pays: Switzerland
ID NLM: 101658402

Informations de publication

Date de publication:
22 Dec 2023
Historique:
received: 20 11 2023
revised: 18 12 2023
accepted: 20 12 2023
medline: 11 1 2024
pubmed: 11 1 2024
entrez: 11 1 2024
Statut: epublish

Résumé

Accurate preoperative localization is crucial for successful minimally invasive parathyroidectomy in primary hyperparathyroidism (PHPT). Preoperative localization can be challenging in patients with recurrent and/or multigland disease (MGD). This has led clinicians to investigate multiple imaging techniques, most of which are associated with radiation exposure. Magnetic resonance imaging (MRI) offers ionizing radiation-free and accurate imaging, making it an attractive alternative imaging modality. The objective of this systematic review is to provide an overview of the diagnostic performance of MRI in the localization of PHPT. PubMed and Embase libraries were searched from 1 January 2000 to 31 March 2023. Studies were included that investigated MRI techniques for the localization of PHPT. The exclusion criteria were (1) secondary/tertiary hyperparathyroidism, (2) studies that provided no diagnostic performance values, (3) studies published before 2000, and (4) studies using 0.5 Tesla MRI scanners. Twenty-four articles were included in the systematic review, with a total of 1127 patients with PHPT. In 14 studies investigating conventional MRI for PHPT localization, sensitivities varied between 39.1% and 94.3%. When employing more advanced MRI protocols like 4D MRI for PHPT localization in 11 studies, sensitivities ranged from 55.6% to 100%. The combination of MR imaging with functional techniques such as 18F-FCH-PET/MRI yielded the highest diagnostic accuracy, with sensitivities ranging from 84.2% to 100% in five studies. Despite the limitations of the available evidence, the results of this review indicate that the combination of MR imaging with functional imaging techniques such as 18F-FCH-PET/MRI yielded the highest diagnostic accuracy. Further research on emerging MR imaging modalities, such as 4D MRI and PET/MRI, is warranted, as MRI exposes patients to minimal or no ionizing radiation compared to other imaging modalities.

Identifiants

pubmed: 38201335
pii: diagnostics14010025
doi: 10.3390/diagnostics14010025
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Auteurs

Max H M C Scheepers (MHMC)

GROW School for Oncology and Developmental Biology, Maastricht University, 6229 ER Maastricht, The Netherlands.

Zaid Al-Difaie (Z)

GROW School for Oncology and Developmental Biology, Maastricht University, 6229 ER Maastricht, The Netherlands.

Lloyd Brandts (L)

Department of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical Centre, 6202 AZ Maastricht, The Netherlands.

Andrea Peeters (A)

Department of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical Centre, 6202 AZ Maastricht, The Netherlands.

Bjorn Winkens (B)

Department of Methodology and Statistics, CAPHRI, Maastricht University Medical Centre, 6229 HX Maastricht, The Netherlands.

Mahdi Al-Taher (M)

Department of Surgery, Maastricht University Medical Center, 6202 AZ Maastricht, The Netherlands.

Sanne M E Engelen (SME)

Department of Surgery, Maastricht University Medical Center, 6202 AZ Maastricht, The Netherlands.

Tim Lubbers (T)

GROW School for Oncology and Developmental Biology, Maastricht University, 6229 ER Maastricht, The Netherlands.
Department of Surgery, Maastricht University Medical Center, 6202 AZ Maastricht, The Netherlands.

Bas Havekes (B)

Department of Internal Medicine, Division of Endocrinology and Metabolic Disease, Maastricht University Medical Center, 6202 AZ Maastricht, The Netherlands.
NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, 6229 ER Maastricht, The Netherlands.

Nicole D Bouvy (ND)

Department of Surgery, Maastricht University Medical Center, 6202 AZ Maastricht, The Netherlands.

Alida A Postma (AA)

Department of Radiology and Nuclear Medicine, School for Mental Health and Sciences (MHENS), Maastricht University Medical Center, 6202 AZ Maastricht, The Netherlands.

Classifications MeSH