Max Hmc Scheepers

The differentiation between malignant and benign thyroid nodules represents a significant challenge for clinicians globally. The identification of volatile organic compounds (VOCs) has emerged as a novel approach in the field of cancer diagnosis. This prospective pilot study aims to identify VOCs in exhaled breath, blood, and urine that can differentiate benign from malignant thyroid nodules using gas chromatography-ion mobility spectrometry (GC-IMS). Patients with thyroid nodules scheduled for surgery were enrolled at the Maastricht University Medical Center (MUMC+). Breath samples were analyzed using a BreathSpec GC-IMS machine (G.A.S. Dortmund, Germany), specifically designed for breath analysis. All blood and urine samples were analyzed using a separate GC-IMS device, the FlavourSpec® (G.A.S., Dortmund, Germany). In this proof-of-concept study, 70 consecutive patients undergoing thyroid surgery at MUMC+ were included. Of these patients, 29 were confirmed to have thyroid cancer after surgical resection. The overall analysis did not reveal statistically significant differences in VOCs in breath, urine and blood, between patients with benign and malignant thyroid cancer. This proof-of-concept study demonstrated that GC-IMS could not effectively differentiate between the VOC profiles of malignant and benign thyroid nodules. However, due to the small sample size of this study, larger prospective studies are needed to investigate the potential of using VOCs to distinguish between benign and malignant thyroid nodules. Additionally, future research should focus on identifying potential confounding factors that may influence patient VOC profiles. (NCT04883294).

Background: Dual-energy computed tomography (DECT) is an advanced imaging method that enables reconstruction of virtual non-contrast (VNC) images from a contrast-enhanced acquisition. This has the potential to reduce radiation exposure by eliminating the need for a true non-contrast (TNC) phase. Purpose: The purpose is to evaluate the feasibility of VNC images in the neck region. Materials and methods: A total of 100 patients underwent a DECT scan as part of diagnostic workup of primary hyperparathyroidism. VNC images were reconstructed from 30 s (arterial) and 50 s (venous) post-contrast scans. Regions of interest (ROIs) were placed in thyroid tissue, lymph node, carotid artery, jugular vein, fat, and sternocleidomastoid muscle. Mean densities of all anatomical structures were compared between VNC and TNC images. Results: For all anatomical structures except the thyroid gland, the difference in mean density between TNC and VNC images was less than 15 HU. The mean difference in density between TNC and VNC images of the thyroid was 53.2 HU (95% CI 46.8; 59.6, p = <0.001). Conclusion: This study demonstrated an acceptable agreement in density between true non-contrast and virtual non-contrast images for most anatomical structures in the neck region. Therefore, VNC images may have the potential to replace TNC images in the neck. However, due to significant differences in CT density of thyroid tissue, true non-contrast imaging cannot be directly substituted by virtual non-contrast imaging when examining the thyroid and its surrounding tissue.

This proof-of-principle study investigates the diagnostic performance of the Aeonose in differentiating malignant from benign thyroid diseases based on volatile organic compound analysis in exhaled breath. All patients with a suspicious thyroid nodule planned for surgery, exhaled in the Aeonose. Definitive diagnosis was provided by histopathological determination after surgical resection. Breath samples were analyzed utilizing artificial neural networking. About 133 participants were included, 48 of whom were diagnosed with well-differentiated thyroid cancer. A sensitivity of 0.73 and a negative predictive value (NPV) of 0.82 were found. The sensitivity and NPV improved to 0.94 and 0.95 respectively after adding clinical variables via multivariate logistic regression analysis. This study demonstrates the feasibility of the Aeonose to discriminate between malignant and benign thyroid disease. With a high NPV, low cost, and non-invasive nature, the Aeonose may be a promising diagnostic tool in the detection of thyroid cancer.