Diagnosis of Idiopathic Pulmonary Fibrosis in High-Resolution Computed Tomography Scans Using a Combination of Handcrafted Radiomics and Deep Learning.

artificial intelligence (AI) computed tomography idiopathic pulmonary fibrosis interpretability interstitial lung disease radiomics

Journal

Frontiers in medicine
ISSN: 2296-858X
Titre abrégé: Front Med (Lausanne)
Pays: Switzerland
ID NLM: 101648047

Informations de publication

Date de publication:
2022
Historique:
received: 07 04 2022
accepted: 07 06 2022
entrez: 11 7 2022
pubmed: 12 7 2022
medline: 12 7 2022
Statut: epublish

Résumé

To develop handcrafted radiomics (HCR) and deep learning (DL) based automated diagnostic tools that can differentiate between idiopathic pulmonary fibrosis (IPF) and non-IPF interstitial lung diseases (ILDs) in patients using high-resolution computed tomography (HRCT) scans. In this retrospective study, 474 HRCT scans were included (mean age, 64.10 years ± 9.57 [SD]). Five-fold cross-validation was performed on 365 HRCT scans. Furthermore, an external dataset comprising 109 patients was used as a test set. An HCR model, a DL model, and an ensemble of HCR and DL model were developed. A virtual In five-fold cross-validation, the HCR model, DL model, and the ensemble of HCR and DL models achieved accuracies of 76.2 ± 6.8, 77.9 ± 4.6, and 85.2 ± 2.7%, respectively. For the diagnosis of IPF and non-IPF ILDs on the external test set, the HCR, DL, and the ensemble of HCR and DL models achieved accuracies of 76.1, 77.9, and 85.3%, respectively. The ensemble model outperformed the diagnostic performance of clinicians who achieved a mean accuracy of 66.3 ± 6.7% ( Deep learning and HCR models can complement each other and serve as useful clinical aids for the diagnosis of IPF and non-IPF ILDs.

Identifiants

pubmed: 35814761
doi: 10.3389/fmed.2022.915243
pmc: PMC9259876
doi:

Types de publication

Journal Article

Langues

eng

Pagination

915243

Informations de copyright

Copyright © 2022 Refaee, Salahuddin, Frix, Yan, Wu, Woodruff, Gietema, Meunier, Louis, Guiot and Lambin.

Déclaration de conflit d'intérêts

PL reports, as non-practicing MD, in the last 3 years, within and outside the submitted work, grants/sponsored research agreements from Radiomics SA, Convert Pharmaceuticals and LivingMed Biotech. PL received a presenter fee (in cash or in kind) and/or reimbursement of travel costs/consultancy fee (in cash or in kind) from Radiomics SA, BHV, Varian, Elekta, ptTheragnostic/DNAmito, BMS, and Convert pharmaceuticals. PL has minority shares in the companies Radiomics SA, Convert pharmaceuticals, Comunicare, and LivingMed Biotech, and he is co-inventor of two issued patents with royalties on radiomics (PCT/NL2014/050248 and PCT/NL2014/050728), licensed to Radiomics SA; one issued patent on mtDNA (PCT/EP2014/059089), licensed to ptTheragnostic/DNAmito; one non-issued patent on LSRT (PCT/P126537PC00), licensed to Varian; three non-patented inventions (softwares) licensed to ptTheragnostic/DNAmito, Radiomics SA and Health Innovation Ventures and two non-issued, non-licensed patents on Deep Learning-Radiomics (N2024482, N2024889). PL confirms that none of the above entities or funding sources were involved in the preparation of this manuscript. JG reports personal fees for advisory board, work and lectures from Boehringer Ingelheim, Janssens, SMB, GSK, Roche and Chiesi, non-financial support for meeting attendance from Chiesi, Roche, Boehringer Ingelheim and Janssens. He is in the permanent SAB of Radiomics (Oncoradiomics SA) for the SALMON trial without any specific consultancy fee for this work. He is co-inventor of one issued patent on radiomics licensed to Radiomics (Oncoradiomics SA). He confirms that none of the above entities or funding was involved in the preparation of this work. HW has minority shares in the company Radiomics SA. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Références

Eur J Radiol. 2015 Dec;84(12):2640-5
pubmed: 26391232
Clinics (Sao Paulo). 2019 Feb 04;74:e225
pubmed: 30726312
Eur Radiol. 2020 Jul;30(7):4050-4057
pubmed: 32112116
Radiology. 2016 Feb;278(2):563-77
pubmed: 26579733
Eur Radiol. 2020 Jan;30(1):523-536
pubmed: 31350588
Eur Radiol. 2022 May;32(5):3458-3468
pubmed: 34981135
Radiology. 2020 May;295(2):328-338
pubmed: 32154773
Am J Respir Crit Care Med. 2011 Feb 15;183(4):431-40
pubmed: 20935110
Lancet. 2012 Aug 18;380(9842):689-98
pubmed: 22901890
Methods. 2021 Apr;188:20-29
pubmed: 32504782
BMC Cancer. 2020 Jan 10;20(1):29
pubmed: 31924170
Lancet Respir Med. 2018 Nov;6(11):837-845
pubmed: 30232049
J Pers Med. 2021 Aug 27;11(9):
pubmed: 34575619
Nature. 2015 May 28;521(7553):436-44
pubmed: 26017442
Eur J Radiol. 2021 May;138:109673
pubmed: 33774441
Eur J Radiol. 2021 Jul;140:109744
pubmed: 33962253
Am J Respir Crit Care Med. 1994 Oct;150(4):967-72
pubmed: 7921471
Eur Respir J. 2019 Mar 18;53(3):
pubmed: 30886022
Eur J Cancer. 2012 Mar;48(4):441-6
pubmed: 22257792
Comput Biol Med. 2021 Dec 4;140:105111
pubmed: 34891095
Med Res Rev. 2022 Jan;42(1):426-440
pubmed: 34309893
Invest Radiol. 2019 Oct;54(10):627-632
pubmed: 31483764
Lancet. 2017 May 13;389(10082):1941-1952
pubmed: 28365056
JCO Clin Cancer Inform. 2019 Feb;3:1-9
pubmed: 30730766
Am J Respir Crit Care Med. 2011 Mar 15;183(6):788-824
pubmed: 21471066
Br J Radiol. 2019 Jul;92(1099):20190159
pubmed: 31166787
Am J Respir Crit Care Med. 2018 Sep 1;198(5):e44-e68
pubmed: 30168753
Eur Radiol. 2019 Sep;29(9):4742-4750
pubmed: 30778717
Am J Respir Crit Care Med. 2013 Sep 15;188(6):733-48
pubmed: 24032382
Chest. 2013 Nov;144(5):1644-1651
pubmed: 23828161
Eur J Radiol. 2020 Aug;129:109095
pubmed: 32531722
Nat Rev Clin Oncol. 2017 Dec;14(12):749-762
pubmed: 28975929
BMJ. 2015 Oct 28;351:h5527
pubmed: 26511519

Auteurs

Turkey Refaee (T)

The D-Lab, Department of Precision Medicine, GROW-School for Oncology and Reproduction, Maastricht University, Maastricht, Netherlands.
Department of Diagnostic Radiology, Faculty of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia.

Zohaib Salahuddin (Z)

The D-Lab, Department of Precision Medicine, GROW-School for Oncology and Reproduction, Maastricht University, Maastricht, Netherlands.

Anne-Noelle Frix (AN)

Department of Respiratory Medicine, University Hospital of Liège, Liège, Belgium.

Chenggong Yan (C)

The D-Lab, Department of Precision Medicine, GROW-School for Oncology and Reproduction, Maastricht University, Maastricht, Netherlands.
Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.

Guangyao Wu (G)

Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Henry C Woodruff (HC)

The D-Lab, Department of Precision Medicine, GROW-School for Oncology and Reproduction, Maastricht University, Maastricht, Netherlands.
Department of Radiology and Nuclear Medicine, GROW-School for Oncology, Maastricht University Medical Center, Maastricht, Netherlands.

Hester Gietema (H)

Department of Radiology and Nuclear Medicine, GROW-School for Oncology, Maastricht University Medical Center, Maastricht, Netherlands.

Paul Meunier (P)

Department of Radiology, University Hospital of Liège, Liège, Belgium.

Renaud Louis (R)

Department of Respiratory Medicine, University Hospital of Liège, Liège, Belgium.

Julien Guiot (J)

Department of Respiratory Medicine, University Hospital of Liège, Liège, Belgium.

Philippe Lambin (P)

The D-Lab, Department of Precision Medicine, GROW-School for Oncology and Reproduction, Maastricht University, Maastricht, Netherlands.
Department of Radiology and Nuclear Medicine, GROW-School for Oncology, Maastricht University Medical Center, Maastricht, Netherlands.

Classifications MeSH