Evidence map›Paper›PMID 40642222›Full record

ArticleEuropean journal of radiology open2025

Limited additional value of dual-layer spectral 4DCT compared with conventional 4DCT for preoperative localization in primary hyperparathyroidism.

Jorian P Krol, Tessa Veerbeek, Laura N Deden, Frank B M Joosten, Marie Louise E Bernsen, Cornelis H Slump, Wim J G Oyen

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Article in European journal of radiology open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Jorian P KrolDepartment of Radiology & Nuclear Medicine, Rijnstate Hospital, Arnhem, the Netherlands.
Tessa VeerbeekDepartment of Radiology & Nuclear Medicine, Rijnstate Hospital, Arnhem, the Netherlands.
Laura N DedenDepartment of Radiology & Nuclear Medicine, Rijnstate Hospital, Arnhem, the Netherlands.
Frank B M JoostenDepartment of Radiology & Nuclear Medicine, Rijnstate Hospital, Arnhem, the Netherlands.
Marie Louise E BernsenDepartment of Radiology & Nuclear Medicine, Rijnstate Hospital, Arnhem, the Netherlands.
Cornelis H SlumpDepartment of Robotics and Mechatronics, Faculty of Electrical Engineering, Mathematics and Computer Sciences, University of Twente, Enschede, the Netherlands.
Wim J G OyenDepartment of Radiology & Nuclear Medicine, Rijnstate Hospital, Arnhem, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Primary hyperparathyroidism, characterized by excessive parathyroid hormone secretion, is typically caused by solitary parathyroid adenomas or multiglandular disease. Accurate preoperative localization is critical for successful surgical parathyroidectomy. While four-dimensional CT (4DCT) is commonly used for this purpose, spectral-CT techniques have recently been introduced, offering improved tissue differentiation. Rapid kV switching and dual-source spectral-CT have been studied, however, this is the first study that evaluates the effectiveness of dual-layer-CT in preoperatively locating parathyroid adenomas in a larger population. Approach: From April 2020 to October 2023, patients with confirmed primary hyperparathyroidism underwent dual-layer spectral 4DCT before surgery. Spectral reconstructions (MonoE40keV, Iodine-Density, Z-effective, Iodine-no-Water, Virtual Non-Contrast) were analyzed alongside conventional CT reconstructions. Mean attenuation values were compared using one-way ANOVA. ROC curves with paired-sample analysis assessed the ability of different reconstructions to distinguish between thyroid and parathyroid tissue, and lymph nodes and parathyroid tissue. Results: Thirty-six patients with thirty-nine parathyroid adenomas were analyzed. Conventional CT reconstructions demonstrated significantly higher AUC values for differentiating thyroid from parathyroid tissue across all phases compared to spectral reconstructions (0.83-0.95 vs. 0.65-0.89, p-value 0.007-<0.001). No significant difference was found between conventional and spectral reconstructions in distinguishing lymph nodes from parathyroid tissue (0.64-0.96 vs. 0.58-0.96, p-value 0.070-0.957). Virtual non-contrast (VNC) reconstructions showed smaller attenuation differences and lower AUC values in arterial and delayed phases compared to true non-contrast (p = 0.031 and 0.034). Conclusions: Dual-layer spectral-CT is comparable or inferior to conventional CT in tissue differentiation. VNC reconstructions are not recommended as a substitute for true non-contrast due to inconsistent results. In this cohort, dual-layer spectral 4DCT did not demonstrate clear clinical advantage; further validation is warranted.

Indexed as

4DCTDual-layer CTParathyroid adenomaPrimary hyperparathyroidismSpectral CT

Identifiers

PMID40642222
PMCPMC12241994

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.