Utility of the 10 Hounsfield unit threshold for identifying adrenal adenomas: Can we improve?


Journal

American journal of surgery
ISSN: 1879-1883
Titre abrégé: Am J Surg
Pays: United States
ID NLM: 0370473

Informations de publication

Date de publication:
10 2020
Historique:
received: 21 11 2019
revised: 07 03 2020
accepted: 16 04 2020
pubmed: 4 5 2020
medline: 15 12 2020
entrez: 4 5 2020
Statut: ppublish

Résumé

Current recommendations using Hounsfield units (HU) ≤ 10 to identify adrenal adenomas on unenhanced computed tomography (CT) miss 10-40% of benign adenomas. We sought to determine if changing HU threshold and adding absolute percent contrast washout (APW) criteria would identify adrenal adenomas better than current recommendations. Imaging characteristics were compared between patients with adenomas (n = 128) and those with non-adenomas (n = 54) after unilateral adrenalectomy. Sensitivity, specificity, positive and negative predictive values (PPV, NPV) were calculated. Using HU ≤ 10 to identify adenomas had a sensitivity of 47.6%, specificity of 93.3% (AUC = 0.71, p < 0.001), PPV of 95.3%, and NPV of 58.1% for identifying adrenal adenomas. Applying HU ≤ 16 improved sensitivity (65.4%) without reducing specificity (93.3%) (AUC = 0.79, p < 0.001), PPV increased to 96.3%, and NPV decreased to 47.6%. Applying HU ≤ 16 as the initial criterion followed by APW > 60% for lesions exceeding 16 HU, sensitivity increased to 93.4%, specificity was 93.3% and PPV 96.6%, and NPV improved to 85.7% (AUC = 0.96, p < 0.001). Criteria of initial threshold of HU ≤ 16 followed by APW > 60% for lesions exceeding 16 HU yielded improved sensitivity and specificity in identification of adrenal adenomas.

Sections du résumé

BACKGROUND
Current recommendations using Hounsfield units (HU) ≤ 10 to identify adrenal adenomas on unenhanced computed tomography (CT) miss 10-40% of benign adenomas. We sought to determine if changing HU threshold and adding absolute percent contrast washout (APW) criteria would identify adrenal adenomas better than current recommendations.
METHODS
Imaging characteristics were compared between patients with adenomas (n = 128) and those with non-adenomas (n = 54) after unilateral adrenalectomy. Sensitivity, specificity, positive and negative predictive values (PPV, NPV) were calculated.
RESULTS
Using HU ≤ 10 to identify adenomas had a sensitivity of 47.6%, specificity of 93.3% (AUC = 0.71, p < 0.001), PPV of 95.3%, and NPV of 58.1% for identifying adrenal adenomas. Applying HU ≤ 16 improved sensitivity (65.4%) without reducing specificity (93.3%) (AUC = 0.79, p < 0.001), PPV increased to 96.3%, and NPV decreased to 47.6%. Applying HU ≤ 16 as the initial criterion followed by APW > 60% for lesions exceeding 16 HU, sensitivity increased to 93.4%, specificity was 93.3% and PPV 96.6%, and NPV improved to 85.7% (AUC = 0.96, p < 0.001).
CONCLUSIONS
Criteria of initial threshold of HU ≤ 16 followed by APW > 60% for lesions exceeding 16 HU yielded improved sensitivity and specificity in identification of adrenal adenomas.

Identifiants

pubmed: 32359690
pii: S0002-9610(20)30225-7
doi: 10.1016/j.amjsurg.2020.04.021
pmc: PMC7541453
mid: NIHMS1589004
pii:
doi:

Substances chimiques

Contrast Media 0

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

920-924

Subventions

Organisme : NIDDK NIH HHS
ID : T35 DK062709
Pays : United States
Organisme : NCATS NIH HHS
ID : TL1 TR002242
Pays : United States

Informations de copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

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Auteurs

Michael J Kirsch (MJ)

University of Michigan Medical School, USA.

Miranda W Kohli (MW)

Department of Emergency Medicine, University of Wisconsin School of Medicine and Public Health, USA.

Kristin L Long (KL)

Division of Endocrine Surgery, Department of Surgery, University of Wisconsin School of Medicine and Public Health, USA.

Susan C Pitt (SC)

Division of Endocrine Surgery, Department of Surgery, University of Wisconsin School of Medicine and Public Health, USA.

David F Schneider (DF)

Division of Endocrine Surgery, Department of Surgery, University of Wisconsin School of Medicine and Public Health, USA.

Rebecca S Sippel (RS)

Division of Endocrine Surgery, Department of Surgery, University of Wisconsin School of Medicine and Public Health, USA.

Priya H Dedhia (PH)

Division of Surgical Oncology, Department of Surgery, Ohio State University Comprehensive Cancer Center and Ohio State University Wexner Medical Center, USA. Electronic address: priya.dedhia@osumc.edu.

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Classifications MeSH