Washout-Computed Tomography Discriminates Pulmonary "Fat-poor" Hamartomas From Neuroendocrine Neoplasms: A Simple Method in the Radiomics Era.


Journal

Journal of thoracic imaging
ISSN: 1536-0237
Titre abrégé: J Thorac Imaging
Pays: United States
ID NLM: 8606160

Informations de publication

Date de publication:
01 Sep 2023
Historique:
medline: 22 8 2023
pubmed: 28 4 2023
entrez: 28 4 2023
Statut: ppublish

Résumé

Pulmonary hamartomas (HAs) and neuroendocrine neoplasms (NENs) are often impossible to discriminate using high-resolution computed tomography (CT) as they share morphologic features. This challenge makes differential diagnosis crucial as HAs are invariably benign, whereas NENs must be considered malignant, thus requiring them to be evaluated for surgical excision.Our aim was, therefore, to develop a simple method to discriminate between pulmonary "fat-poor" HAs and NENs using contrast-enhanced CT (CECT). Between September 2015 and December 2021, 95 patients with a histologically proven diagnosis of lung NENs (74) and HAs (21) and who underwent a preoperative CECT scan were initially identified through a review of our pathologic and radiologic databases. Among these, 55 cases (18 HAs and 37 NENs), which have been studied with biphasic CECT, were ultimately selected and reviewed by 3 radiologists with different levels of experience, analyzing their morphologic and enhancement features.The enhancement analysis was performed by placing a region of interest within the lesion in noncontrast (NCp), postcontrast (PCp, 55 to 65 s after intravenous contrast injection), and delayed phases (Dp, 180 to 300 s). A subgroup of 35 patients who underwent 18FDG-PET/CT was evaluated in a secondary analysis. HU values were significantly different between NENs and HAs in the PCp ( P <0.001). NCp and Dp attenuation values did not show significant differences in the 2 groups. Differences in values of HUs in PCp and Dp allowed to discriminate between NENs and HAs. Wash-out analysis, ΔHU (PCp-Dp), can perfectly discriminate pulmonary "fat-poor" HAs from NENs.

Identifiants

pubmed: 37115915
doi: 10.1097/RTI.0000000000000712
pii: 00005382-990000000-00066
doi:

Substances chimiques

Fluorodeoxyglucose F18 0Z5B2CJX4D

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

278-285

Informations de copyright

Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.

Déclaration de conflit d'intérêts

The authors declare no conflicts of interest.

Références

Fisseler-Eckhoff A, Demes M. Neuroendocrine tumors of the lung. Cancers (Basel). 2012;4:777–798.
Rosado de Christenson ML, Abbott GF, Kirejczyk WM, et al. Thoracic carcinoids: radiologic-pathologic correlation. Radiographics. 1999;19:707–736.
Chong S, Lee KS, Chung MJ, et al. Neuroendocrine tumors of the lung: clinical, pathologic, and imaging findings. Radiographics. 2006;26:41–58.
Zwiebel BR, Austin JH, Grimes MM. Bronchial carcinoid tumors: assessment with CT of location and intratumoral calcification in 31 patients. Radiology. 1991;179:483–486.
Jeung Mi-Y, Gasser B, Gangi A, et al. Bronchial carcinoid tumors of the thorax: spectrum of radiologic findings. Radiographics. 2002;22:351–365.
Evangelista L, Ravelli I, Bignotto A, et al. Ga-68 DOTA-peptides and F-18 FDG PET/CT in patients with neuroendocrine tumor: a review. Clin Imaging. 2020;67:113–116.
Thomas J, Staerkel GA, Whitman G. Pulmonary hamartoma. AJR Am J Roentgenol. 1999;172:1643.
Gaerte Scott C, Meyer CA, Winer-Muram HT, et al. Fat-containing lesions of the chest. Radiographics. 2002;22(suppl_1):S61–S78.
Siegelman SS, Khouri NF, Scott WW Jr, et al. Pulmonary hamartoma: CT findings. Radiology. 1986;160:313–317.
Collins J, Stern EJ. Chest Radiology, The Essentials. Lippincott Williams & Wilkins; 2007.
Bueno J, Landeras L, Chung JH. Updated Fleischner Society Guidelines for Managing Incidental Pulmonary Nodules: common questions and challenging scenarios. Radiographics. 2018;38:1337–1350.
Czeyda-Pommersheim F, Hwang M, Chen SS, et al. Amyloidosis: modern cross-sectional imaging. Radiographics. 2015;35:1381–1392.
Oh JK, Han DH. False-positive multi-detector CT finding for hamartomas. Ann Thorac Surg. 2010;90:1398.
Metovic J, Barella M, Bianchi F, et al. Morphologic and molecular classification of lung neuroendocrine neoplasms. Virchows Arch. 2021;478:5–19.
Rekhtman N. Lung neuroendocrine neoplasms: recent progress and persistent challenges. Mod Pathol. 2022;35(suppl 1):36–50.
Swensen SJ, Viggiano RW, Midthun DE, et al. Lung nodule enhancement at CT: multicenter study. Radiology. 2000;214:73–80.
Swensen SJ, Brown LR, Colby TV, et al. Lung nodule enhancement at CT: prospective findings. Radiology. 1996;201:447–455.
Swensen SJ, Brown LR, Colby TV, et al. Pulmonary nodules: CT evaluation of enhancement with iodinated contrast material. Radiology. 1995;194:393–398.
Mazzei MA, Cioffi Squitieri N, Guerrini S, et al. Quantitative CT perfusion measurements in characterization of solitary pulmonary nodules: new insights and limitations. Recenti Prog Med. 2013;104:430–437.
Jeong YJ, Lee KS, Jeong SY, et al. Solitary pulmonary nodule: characterization with combined wash-in and washout features at dynamic multi-detector row CT. Radiology. 2005;237:675–683.
Yi CA, Lee KS, Kim EA, et al. Solitary pulmonary nodules: dynamic enhanced multi-detector row CT study and comparison with vascular endothelial growth factor and microvessel density. Radiology. 2004;233:191–199.
Furukawa H, Takayasu K, Mukai K, et al. Late contrast-enhanced CT for small pancreatic carcinoma: delayed enhanced area on CT with histopathological correlation. Hepatogastroenterology. 1996;43:1230–1237.
Muramatsu Y, Takayasu K, Moriyama N, et al. Peripheral low-density area of hepatic tumors: CT-pathologic correlation. Radiology. 1986;160:49–52.
Ohno Y, Kauczor HU, Hatabu H, et al. International Workshop for Pulmonary Functional Imaging (IWPFI). MRI for solitary pulmonary nodule and mass assessment: current state of the art. J Magn Reson Imaging. 2018;47:1437–1458.
Zegadło A, Żabicka M, Kania-Pudło M, et al. Assessment of solitary pulmonary nodules based on virtual monochrome images and iodine-dependent images using a single-source dual-energy CT with fast kVp switching. J Clin Med. 2020;9:2514.
Zhu B, Zheng S, Jiang T, et al. Evaluation of dual-energy and perfusion CT parameters for diagnosing solitary pulmonary nodules. Thorac Cancer. 2021;12:2691–2697.
Zhang Y, Cheng J, Hua X, et al. Can spectral CT imaging improve the differentiation between malignant and benign solitary pulmonary nodules? PLoS One. 2016;11:e0147537.
Mazzei MA, Squitieri NC, Sani E, et al. Differences in perfusion CT parameter values with commercial software upgrades: a preliminary report about algorithm consistency and stability. Acta Radiol. 2013;54:805–811.
Cangir AK, Orhan K, Kahya Y, et al. A CT-based radiomic signature for the differentiation of pulmonary hamartomas from carcinoid tumors. Diagnostics (Basel). 2022;12:416.
Jiang L, Huang Y, Tang Q, et al. 18F-FDG PET/CT characteristics of pulmonary sclerosing hemangioma vs. pulmonary hamartoma. Oncol Lett. 2018;16:660–665.
Dadali Y, Özkaçmaz S, Özmen Ö, et al. Computed tomography and PET/CT features of pulmonary hamartomas. J Res Clin Med. 2021;9:19.
Zhao J, Wang H. Differential diagnostic value of 18F-FDG PET/CT in pulmonary carcinoids versus hamartomas. Acad Radiol. 2022;29(suppl 2):S41–S46.
Jiang Y, Hou G, Cheng W. The utility of 18F-FDG and 68Ga-DOTA-Peptide PET/CT in the evaluation of primary pulmonary carcinoid: a systematic review and meta-analysis. Medicine (Baltimore). 2019;98:e14769.
Ozbudak IH, Shilo K, Tavora F, et al. Glucose transporter-1 in pulmonary neuroendocrine carcinomas: expression and survival analysis. Mod Pathol. 2009;22:633–638.

Auteurs

Luca Volterrani (L)

Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences.

Armando Perrella (A)

Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences.

Giulio Bagnacci (G)

Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences.

Nunzia Di Meglio (N)

Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences.

Vito Di Martino (V)

Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences.

Paolo Bertelli (P)

Nuclear Medicine Unit.

Cristiana Bellan (C)

Unit of Pathological Anatomy and Histology, Department of Medical Biotechnologies.

Maria A Mazzei (MA)

Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences.

Luca Luzzi (L)

Thoracic Surgery Unit, Department of Medical, Surgical and Neuro Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy.

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