Multi-Dynamic-Multi-Echo-based MRI for the Pre-Surgical Determination of Sellar Tumor Consistency: a Quantitative Approach for Predicting Lesion Resectability.

Multiparametric Magnetic Resonance Imaging Pituitary Adenoma Prospective Studies Reference Standards Sellar Lesions

Journal

Clinical neuroradiology
ISSN: 1869-1447
Titre abrégé: Clin Neuroradiol
Pays: Germany
ID NLM: 101526693

Informations de publication

Date de publication:
19 Apr 2024
Historique:
received: 26 12 2023
accepted: 18 03 2024
medline: 19 4 2024
pubmed: 19 4 2024
entrez: 19 4 2024
Statut: aheadofprint

Résumé

Pre-surgical information about tumor consistency could facilitate neurosurgical planning. This study used multi-dynamic-multi-echo (MDME)-based relaxometry for the quantitative determination of pituitary tumor consistency, with the aim of predicting lesion resectability. Seventy-two patients with suspected pituitary adenomas, who underwent preoperative 3 T MRI between January 2020 and January 2022, were included in this prospective study. Lesion-specific T1-/T2-relaxation times (T1R/T2R) and proton density (PD) metrics were determined. During surgery, data about tumor resectability were collected. A Receiver Operating Characteristic (ROC) curve analysis was performed to investigate the diagnostic performance (sensitivity/specificity) for discriminating between easy- and hard-to-remove by aspiration (eRAsp and hRAsp) lesions. A Mann-Whitney-U-test was done for group comparison. A total of 65 participants (mean age, 54 years ± 15, 33 women) were enrolled in the quantitative analysis. Twenty-four lesions were classified as hRAsp, while 41 lesions were assessed as eRAsp. There were significant differences in T1R (hRAsp: 1221.0 ms ± 211.9; eRAsp: 1500.2 ms ± 496.4; p = 0.003) and T2R (hRAsp: 88.8 ms ± 14.5; eRAsp: 137.2 ms ± 166.6; p = 0.03) between both groups. The ROC analysis revealed an area under the curve of 0.72 (95% CI: 0.60-0.85) at p = 0.003 for T1R (cutoff value: 1248 ms; sensitivity/specificity: 78%/58%) and 0.66 (95% CI: 0.53-0.79) at p = 0.03 for T2R (cutoff value: 110 ms; sensitivity/specificity: 39%/96%). MDME-based relaxometry enables a non-invasive, pre-surgical characterization of lesion consistency and, therefore, provides a modality with which to predict tumor resectability.

Identifiants

DOI: 10.1007/s00062-024-01407-1 PMID: 38639770
pubmed: 38639770
doi: 10.1007/s00062-024-01407-1
pii: 10.1007/s00062-024-01407-1
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024. The Author(s).

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Auteurs

Mehmet Salih Yildirim (MS)

Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.

Victor Ulrich Schmidbauer (VU)

Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.

Alexander Micko (A)

Department of Neurosurgery, Medical University of Graz, Auenbruggerplatz 29, 8036, Graz, Austria.

Lisa Lechner (L)

Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.

Michael Weber (M)

Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.

Julia Furtner (J)

Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.

Stefan Wolfsberger (S)

Department of Neurosurgery, Medical University of Graz, Auenbruggerplatz 29, 8036, Graz, Austria.

Intesar-Victoria Malla Houech (IV)

Department of Diagnostic Imaging, Medical University of Sofia, Sveti Georgi Sofiyski 1, 1431, Sofia, Bulgaria.

Anna Cho (A)

Department of Neurosurgery, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.

Gregor Dovjak (G)

Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.

Gregor Kasprian (G)

Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.

Daniela Prayer (D)

Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.

Wolfgang Marik (W)

Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria. wolfgang.marik@meduniwien.ac.at.
ORCID: 0000-0002-1193-0970

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