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Advances in CT and MRI for the assessment of progressive pulmonary fibrosis
WEI Bo  WANG Xiaodong  HAN Bo  YIN Wenjing  ZHANG Hao 

Cite this article as WEI B, WANG X D, HAN B, et al. Advances in CT and MRI for the assessment of progressive pulmonary fibrosis[J]. Chin J Magn Reson Imaging, 2026, 17(8): 184-189. DOI:10.12015/issn.1674-8034.2026.08.021.


[Abstract] Interstitial lung disease (ILD) encompasses a heterogeneous group of disorders characterized by diverse patterns of evolution and markedly variable prognoses. Compared to patients experiencing spontaneous resolution or disease stabilization, those with progressive pulmonary fibrosis (PPF) face a significantly poorer prognosis and elevated mortality risk. Consequently, early diagnosis and risk stratification in PPF have emerged as critical unmet clinical needs. Imaging plays an integral role throughout the entire disease trajectory of PPF, contributing substantially to disease screening, longitudinal monitoring, and prognostic assessment. High-resolution computed tomography (HRCT) remains the cornerstone of PPF diagnosis and management, and CT technology continues to undergo iterative advancements. However, X-ray-based imaging modalities, including photon-counting computed tomography (PCCT), are associated with inherent risks of ionizing radiation exposure. In recent years, the rapid evolution of magnetic resonance imaging (MRI) has enabled parenchymal lung imaging, offering a multi-dimensional perspective for the radiation-free assessment of PPF. This article reviews the research progress of HRCT and MRI in the evaluation of PPF, and discusses current technical limitations and future directions, with the aim of facilitating early diagnosis, tracking disease progression, and guiding clinical management.
[Keywords] progressive pulmonary fibrosis;interstitial lung disease;high-resolution computed tomography;magnetic resonance imaging

WEI Bo1, 2   WANG Xiaodong1, 2   HAN Bo1, 2   YIN Wenjing1, 2   ZHANG Hao1, 2*  

1 The First Clinical Medical College of Lanzhou University, Lanzhou 730000, China

2 Intelligent Imaging Medical Engineering Research, Department of Radiology, the First Hospital of Lanzhou University, Lanzhou 730000, China

Corresponding author: ZHANG H, E-mail: zhanghao@lzu.edu.cn

Conflicts of interest   None.

Received  2026-04-21
Accepted  2026-07-12
DOI: 10.12015/issn.1674-8034.2026.08.021
Cite this article as WEI B, WANG X D, HAN B, et al. Advances in CT and MRI for the assessment of progressive pulmonary fibrosis[J]. Chin J Magn Reson Imaging, 2026, 17(8): 184-189. DOI:10.12015/issn.1674-8034.2026.08.021.

[1]
PARK C, YEO Y, LA WOO A, et al. Korean guidelines for diagnosis and management of interstitial lung diseases[J]. Tuberc Respir Dis, 2025, 88(4): 654-672. DOI: 10.4046/trd.2025.0044.
[2]
CHELALA L, BRIXEY A G, HOBBS S B, et al. Current state of fibrotic interstitial lung disease imaging[J/OL]. Radiology, 2025, 316: e242531 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/40590695/. DOI: 10.1148/radiol.242531.
[3]
MAHER T M. Interstitial lung disease: a review[J/OL]. Jama, 2024, 331(19): 1655 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/38648021/. DOI: 10.1001/jama.2024.3669.
[4]
WIJSENBEEK M, COTTIN V. Spectrum of fibrotic lung diseases[J]. N Engl J Med, 2020, 383(10): 958-968. DOI: 10.1056/nejmra2005230.
[5]
COTTIN V, WOLLIN L, FISCHER A, et al. Fibrosing interstitial lung diseases: knowns and unknowns[J/OL]. Eur Respir Rev, 2019, 28(151): 180100 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/30814139/. DOI: 10.1183/16000617.0100-2018.
[6]
WELLS A U, BROWN K K, FLAHERTY K R, et al. What's in a name That which we call IPF, by any other name would act the same[J/OL]. Eur Respir J, 2018, 51(5): 1800692 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/29773608/. DOI: 10.1183/13993003.00692-2018.
[7]
BEHR J, SALISBURY M L, WALSH S L F, et al. The role of inflammation and fibrosis in interstitial lung disease treatment decisions[J]. Am J Respir Crit Care Med, 2024, 210(4): 392-400. DOI: 10.1164/rccm.202401-0048PP.
[8]
BUSCHULTE K, KABITZ H J, HAGMEYER L, et al. Disease trajectories in interstitial lung diseases–data from the EXCITING-ILD registry[J/OL]. Respir Res, 2024, 25(1): 113 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/38448953/. DOI: 10.1186/s12931-024-02731-3.
[9]
RAGHU G, REMY-JARDIN M, RICHELDI L, et al. Idiopathic pulmonary fibrosis (an update) and progressive pulmonary fibrosis in adults: an official ATS/ERS/JRS/ALAT clinical practice guideline[J/OL]. Am J Respir Crit Care Med, 2022, 205(9): e18-e47 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/35486072/. DOI: 10.1164/rccm.202202-0399ST.
[10]
RYERSON C J, BANKIER A, BEASLEY M B, et al. Standardized clinical terms and definitions for interstitial lung disease: a consensus statement from the fleischner society[J]. Am J Respir Crit Care Med, 2025, 211(10): 1756-1774. DOI: 10.1164/rccm.202505-1142SO.
[11]
HAMBLY N, FAROOQI M M, DVORKIN-GHEVA A, et al. Prevalence and characteristics of progressive fibrosing interstitial lung disease in a prospective registry[J/OL]. Eur Respir J, 2022, 60(4): 2102571 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/35273032/. DOI: 10.1183/13993003.02571-2021.
[12]
FLAHERTY K R, WELLS A U, COTTIN V, et al. Nintedanib in progressive interstitial lung diseases: data from the whole INBUILD trial[J/OL]. Eur Respir J, 2022, 59(3): 2004538 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/34475231/. DOI: 10.1183/13993003.04538-2020.
[13]
ZHAO T M, LIU K D, DUAN Z M, et al. Prognostic factors for fibrosing interstitial lung diseases: a prospective cohort study[J]. Chin J Mult Organ Dis Elder, 2021, 20(6): 414-418. DOI: 10.11915/j.issn.1671-5403.2021.06.086.
[14]
CHENG Y X, CHEN X, GUAN Y, et al. Research progress on imaging evaluation of interstitial lung disease[J]. Radiol Practice, 2026, 41(1): 97-101. DOI: 10.13609/j.cnki.1000-0313.2026.01.016.
[15]
YANAGAWA M, HAN J, WADA N, et al. Advances in concept and imaging of interstitial lung disease[J/OL]. Radiology, 2025, 315(2): e241252 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/40358445/. DOI: 10.1148/radiol.241252.
[16]
BRONCANO J, SHIFREN A, ROYUELA J, et al. Role of MRI in interstitial lung diseases[J]. CHEST, 2026, 169(3): 698-709. DOI: 10.1016/j.chest.2025.09.143.
[17]
RAJAN S K, COTTIN V, DHAR R, et al. Progressive pulmonary fibrosis: an expert group consensus statement[J/OL]. Eur Respir J, 2023, 61(3): 2103187 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/36517177/. DOI: 10.1183/13993003.03187-2021.
[18]
LARICI A R, BIEDERER J, CICCHETTI G, et al. ESR Essentials: imaging in fibrotic lung diseases: practice recommendations by the European Society of Thoracic Imaging[J]. Eur Radiol, 2025, 35(4): 2245-2255. DOI: 10.1007/s00330-024-11054-2.
[19]
BEST A C, MENG J F, LYNCH A M, et al. Idiopathic pulmonary fibrosis: physiologic tests, quantitative CT indexes, and CT visual scores as predictors of mortality[J]. Radiology, 2008, 246(3): 935-940. DOI: 10.1148/radiol.2463062200.
[20]
GOH N S, DESAI S R, VEERARAGHAVAN S, et al. Interstitial lung disease in systemic sclerosis: a simple staging system[J]. Am J Respir Crit Care Med, 2008, 177(11): 1248-1254. DOI: 10.1164/rccm.200706-877OC.
[21]
UZUN Ç, ATMAN E D, ÇORUH A G, et al. Idiopathic pulmonary fibrosis and progressive pulmonary fibrosis: correlation between radiological progression criteria and pulmonary function tests[J/OL]. Eur J Radiol, 2026, 195: 112631 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/41499910/. DOI: 10.1016/j.ejrad.2025.112631.
[22]
BARATELLA E, BORGHESI A, CALANDRIELLO L, et al. Quantification of progressive pulmonary fibrosis by visual scoring of HRCT images: recommendations from Italian chest radiology experts[J]. La Radiol Med, 2025, 130(6): 965-977. DOI: 10.1007/s11547-025-01985-1.
[23]
BERNARDINELLO N, PEZZUTO F, D'SA L, et al. Predicting biomarkers of progressive pulmonary fibrosis: morphological, cytokine profile, and clinical portrait[J/OL]. Front Immunol, 2025, 16: 1514439 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/40612945/. DOI: 10.3389/fimmu.2025.1514439.
[24]
PUGASHETTI J V, ADEGUNSOYE A, WU Z, et al. Validation of proposed criteria for progressive pulmonary fibrosis[J]. Am J Respir Crit Care Med, 2023, 207(1): 69-76. DOI: 10.1164/rccm.202201-0124OC.
[25]
CHO H R, CHUNG M J, CHOI H, et al. Prognostic impact of radiologic and pathologic features on the development of progressive pulmonary fibrosis in patients with interstitial lung disease other than idiopathic pulmonary fibrosis[J]. Korean J Radiol, 2026, 27(1): 63-75. DOI: 10.3348/kjr.2025.0977.
[26]
GAILLANDRE Y, DUHAMEL A, FLOHR T, et al. Ultra-high resolution CT imaging of interstitial lung disease: impact of photon-counting CT in 112 patients[J]. Eur Radiol, 2023, 33(8): 5528-5539. DOI: 10.1007/s00330-023-09616-x.
[27]
VAN BALLAER V, DUBBELDAM A, MUSCOGIURI E, et al. Impact of ultra-high-resolution imaging of the lungs on perceived diagnostic image quality using photon-counting CT[J]. Eur Radiol, 2024, 34(3): 1895-1904. DOI: 10.1007/s00330-023-10174-5.
[28]
LEE K, LEE J H, KOH S Y, et al. Risk factors and prognostic indicators for progressive fibrosing interstitial lung disease: a deep learning-based CT quantification approach[J]. Eur Radiol, 2025, 35(12): 8151-8161. DOI: 10.1007/s00330-025-11714-x.
[29]
AHN Y, KIM H C, LEE J K, et al. Usefulness of CT quantification-based assessment in defining progressive pulmonary fibrosis[J]. Acad Radiol, 2024, 31(11): 4696-4708. DOI: 10.1016/j.acra.2024.05.005.
[30]
WANG J M, ADEGUNSOYE A, PUGASHETTI J V, et al. A quantitative imaging measure of progressive pulmonary fibrosis[J]. Am J Respir Crit Care Med, 2025, 211(10): 1785-1793. DOI: 10.1164/rccm.202501-0208OC.
[31]
KOH S Y, LEE J H, PARK H, et al. Value of CT quantification in progressive fibrosing interstitial lung disease: a deep learning approach[J]. Eur Radiol, 2024, 34(7): 4195-4205. DOI: 10.1007/s00330-023-10483-9.
[32]
KOSLOW M, BARAGHOSHI D, SWIGRIS J J, et al. One-year change in quantitative computed tomography is associated with meaningful outcomes in fibrotic lung disease[J]. Am J Respir Crit Care Med, 2025, 211(10): 1775-1784. DOI: 10.1164/rccm.202503-0535OC.
[33]
GEORGE P M, RENNISON-JONES C, BENVENUTI G, et al. Evaluation of e-Lung automated quantitative computed tomography biomarkers in idiopathic pulmonary fibrosis[J]. ERJ Open Res, 2024, 10(6): 00570-02024. DOI: 10.1183/23120541.00570-2024.
[34]
PARK S, KIM M J, LEE J H, et al. Quantitative CT imaging in progressive pulmonary fibrosis clinical usefulness and meaningful threshold definition[J]. CHEST, 2026, 169(5): 1255-1266. DOI: 10.1016/j.chest.2025.11.031.
[35]
VALENZUELA C, COTTIN V. Epidemiology and real-life experience in progressive pulmonary fibrosis[J]. Curr Opin Pulm Med, 2022, 28(5): 407-413. DOI: 10.1097/MCP.0000000000000908.
[36]
BATTAGLIA C, PELAIA C, LUPIA C, et al. Quantification and analysis of lung involvement by artificial intelligence in patients with progressive pulmonary fibrosis treated with nintedanib[J/OL]. Medicina (Kaunas), 2025, 61(9): 1646 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/41011037/. DOI: 10.3390/medicina61091646.
[37]
MARINESCU D C, HAGUE C J, MULLER N L, et al. CT honeycombing and traction bronchiectasis extent independently predict survival across fibrotic interstitial lung disease subtypes[J/OL]. Radiology, 2025, 314(2): e241001 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/39903073/. DOI: 10.1148/radiol.241001.
[38]
SVERZELLATI N, MILANESE G, RYERSON C J, et al. Interstitial lung abnormalities on unselected abdominal and thoracoabdominal CT scans in 21 118 patients[J/OL]. Radiology, 2024, 313(2): e233374 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/39560484/. DOI: 10.1148/radiol.233374.
[39]
DELAMEILLIEURE A, SOMOGYI V, SCHENK S, et al. Identifying outcome domains to establish a core outcome set for progressive pulmonary fibrosis: a scoping review[J/OL]. Eur Respir Rev, 2025, 34(175): 240133 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/39843158/. DOI: 10.1183/16000617.0133-2024.
[40]
YU N, ZHANG Y, WANG W, et al. Some thoughts based on diagnostic criteria of progressive pulmonary fibrosis[J]. Chin J Pract Intern Med, 2024, 44(6): 446-451. DOI: 10.19538/j.nk2024060102.
[41]
YANG T Y, PU D D, YU N. Current status of magnetic resonance imaging in connective tissue disease-associated interstitial lung disease[J]. Chin J Magn Reson Imaging, 2025, 16(3): 167-172. DOI: 10.12015/issn.1674-8034.2025.03.028.
[42]
LANDINI N. MRI and zero or ultra-short echo-time sequences in secondary interstitial lung diseases: current applicability and future perspectives[J]. Eur Radiol, 2025, 35(6): 2955-2957. DOI: 10.1007/s00330-025-11378-7.
[43]
DOURNES G, WOODS J C. Chronic pediatric lung diseases: counterpoint-a growing role for MRI[J/OL]. AJR Am J Roentgenol, 2025, 224(6): e2432405 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/39629774/. DOI: 10.2214/AJR.24.32405.
[44]
HATABU H, OHNO Y, GEFTER W B, et al. Expanding applications of pulmonary MRI in the clinical evaluation of lung disorders: fleischner society position paper[J]. Radiology, 2020, 297(2): 286-301. DOI: 10.1148/radiol.2020201138.
[45]
LANDINI N, ORLANDI M, OCCHIPINTI M, et al. Ultrashort echo-time magnetic resonance imaging sequence in the assessment of systemic sclerosis-interstitial lung disease[J]. J Thorac Imaging, 2023, 38(2): 97-103. DOI: 10.1097/RTI.0000000000000637.
[46]
LANDINI N, ORLANDI M, CALISTRI L, et al. Advanced and traditional chest MRI sequence for the clinical assessment of systemic sclerosis related interstitial lung disease, compared to CT: disease extent analysis and correlations with pulmonary function tests[J/OL]. Eur J Radiol, 2024, 170: 111239 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/38056347/. DOI: 10.1016/j.ejrad.2023.111239.
[47]
UFUK F, KURNAZ B, PEKER H, et al. Comparing three-dimensional zero echo time (3D-ZTE) lung MRI and chest CT in the evaluation of systemic sclerosis-related interstitial lung disease[J]. Eur Radiol, 2025, 35(6): 2958-2967. DOI: 10.1007/s00330-024-11216-2.
[48]
ROMEI C, TURTURICI L, TAVANTI L, et al. The use of chest magnetic resonance imaging in interstitial lung disease: a systematic review[J/OL]. Eur Respir Rev, 2018, 27(150): 180062 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/30567932/. DOI: 10.1183/16000617.0062-2018.
[49]
TORRES L A, LEE K E, BARTON G P, et al. Dynamic contrast enhanced MRI for the evaluation of lung perfusion in idiopathic pulmonary fibrosis[J/OL]. Eur Respir J, 2022, 60(4): 2102058 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/35273033/. DOI: 10.1183/13993003.02058-2021.
[50]
HAHN A D, CAREY K J, BARTON G P, et al. Hyperpolarized 129Xe MR spectroscopy in the lung shows 1-year reduced function in idiopathic pulmonary fibrosis[J]. Radiology, 2022, 305(3): 688-696. DOI: 10.1148/radiol.211433.
[51]
NI Y F, WANG H Y, WANG J P, et al. Characteristics of fibrosing interstitial lung diseases on phase-resolved functional lung magnetic resonance imaging[J]. Chin J Med Imaging, 2026, 34(4): 409-414, 421. DOI: 10.3969/j.issn.1005-5185.2026.04.009.
[52]
OUYANG T, LIU Q M, ZHANG H M, et al. Quantitative phase-resolved functional lung MRI prediction of disease progression in connective tissue disease-associated interstitial lung disease[J/OL]. Radiology, 2026, 319(1): e253337 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/42048592/. DOI: 10.1148/radiol.253337.
[53]
JIANG Y L, LI J, ZHANG P F, et al. Staging liver fibrosis with various diffusion-weighted magnetic resonance imaging models[J]. World J Gastroenterol, 2024, 30(9): 1164-1176. DOI: 10.3748/wjg.v30.i9.1164.
[54]
BUZAN M T, EICHINGER M, KREUTER M, et al. T2 mapping of CT remodelling patterns in interstitial lung disease[J]. Eur Radiol, 2015, 25(11): 3167-3174. DOI: 10.1007/s00330-015-3751-y.
[55]
RUANO C A, MORAES-FONTES M F, BORBA A, et al. Lung magnetic resonance imaging for prediction of progression in patients with nonidiopathic pulmonary fibrosis interstitial lung disease: a pilot study[J]. J Thorac Imaging, 2023, 38(6): 346-357. DOI: 10.1097/RTI.0000000000000744.
[56]
HOCHHEGGER B, LONZETTI L, RUBIN A, et al. Chest MRI with CT in the assessment of interstitial lung disease progression in patients with systemic sclerosis[J]. Rheumatology (Oxford), 2022, 61(11): 4420-4426. DOI: 10.1093/rheumatology/keac148.
[57]
MA H, ZHOU I Y, CHEN Y I, et al. Tailored chemical reactivity probes for systemic imaging of aldehydes in fibroproliferative diseases[J]. J Am Chem Soc, 2023, 145(38): 20825-20836. DOI: 10.1021/jacs.3c04964.
[58]
BAYRAK E, BAYIR E, BAYSOY E, et al. Nintedanib loaded iron (III) chelated melanin nanoparticles as an MRI-visible antifibrotic drug delivery system[J/OL]. Colloids Surf B Biointerfaces, 2025, 252: 114652 [2026-04-20]. https://pubmed.ncbi.nlm.nih.gov/40184721/. DOI: 10.1016/j.colsurfb.2025.114652.

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