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Pulmonary cysts as a diagnostic indicator of Birt-Hogg-Dubé syndrome in patients with renal neoplasm

  • Amreen Shakur
  • , Grant D. Stewart
  • , Timothy J. Sadler
  • , Judith L. Babar
  • , Anne Y. Warren
  • , Stephen Scullion
  • , Abhishekh H. Ashok
  • , Sumit Karia
  • , Igor Chipurovski
  • , James Whitworth
  • , Stefan J. Marciniak
  • , Eamonn R. Maher
  • , Maria TA Wetscherek*
  • *Corresponding author for this work
  • Cambridge University Hospitals NHS Foundation Trust, Department of Radiology, Addenbrooke’s Hospital, Cambridge, UK, ROR: https://ror.org/04v54gj93, GRID: grid.24029.3d, ISNI: 0000 0004 0383 8386
  • Cambridge Biomedical Campus, Department of Surgery, University of Cambridge, Cambridge, UK, ROR: https://ror.org/013meh722, GRID: grid.5335.0, ISNI: 0000 0001 2188 5934
  • University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Department of Radiology, Cambridge, UK, ROR: https://ror.org/04v54gj93, GRID: grid.24029.3d, ISNI: 0000 0004 0383 8386
  • University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Department of Pathology, Cambridge, UK, ROR: https://ror.org/04v54gj93, GRID: grid.24029.3d, ISNI: 0000 0004 0383 8386
  • West Suffolk Hospital NHS Foundation Trust, Department of Radiology, Bury St Edmunds, UK, ROR: https://ror.org/02ts7ew79, GRID: grid.417049.f, ISNI: 0000 0004 0417 1800
  • Cambridge Biomedical Campus, Department of Urology, University of Cambridge, Cambridge, UK, ROR: https://ror.org/013meh722, GRID: grid.5335.0, ISNI: 0000 0001 2188 5934
  • University of Cambridge and NIHR Cambridge Biomedical Research Centre, Department of Medical Genetics, Cambridge, UK, GRID: grid.529246.e, ISNI: 0000 0004 8340 8617
  • Royal Papworth Hospital NHS Foundation Trust, Respiratory Medicine, Cambridge, UK, ROR: https://ror.org/01qbebb31, GRID: grid.412939.4, ISNI: 0000 0004 0383 5994

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Abstract

Objectives: To assess the presence and CT features of pulmonary cysts (PCs) in patients with renal neoplasms (RN) as a hallmark of Birt-Hogg-Dubé syndrome (BHDS). Materials and methods: Single institution retrospective study of all patients with histological RN between May 2014 and May 2020. Individuals with non-renal neoplasm, nephroblastoma, benign cysts, < 18 years old, or without thoracic CT were excluded. Demographics, history of smoking, pneumothorax and cutaneous fibrofolliculomas/trichodischomas, family history of pneumothorax or RN, and genetic testing were recorded. Number, location, distribution and morphology of PCs were assessed on thoracic CT. Differences between patients with positive (BHD+) and negative (BHD−) genetics were analysed. An independent cohort of 10 BHDS patients was added to calculate the diagnostic accuracy of cyst features. Results: Of 1475 patients with RN, 127 (8.6%) had PCs; 40 underwent genetic testing (median age 56 [49–68], 28 men), and 6/127 (4.7%) individuals tested positive for BHDS. BHD+ had significantly more and larger cysts, affecting more lobes (p < 0.01). Higher prevalence of PCs with a perivascular (100% vs. 37%; p = 0.01) and interlobular septal location (100% vs. 16%; p < 0.001), and perilymphatic distribution (100% vs. 5%; p < 0.001) was found in BHD+. All BHD+ had elliptical, irregular, and variable shape PCs, compared to a lower prevalence of these in BHD− (p < 0.01). Traversing vein sign was more common in BHD+ (83% vs. 24%; p = 0.01). The highest accuracy was achieved for perilymphatic distribution (97%), followed by irregular shape (94%) and interlobular septal location (91%). Conclusion: Specific CT features of PC in patients with RN can be highly indicative of BHDS. Critical relevance statement: Radiologists can play a crucial role in the diagnosis of Birt-Hogg-Dubé syndrome (BHDS) by recognising specific CT features of pulmonary cysts; a diagnosis of BHDS has implications for family testing and timely, life-long screening for renal neoplasm. Key Points: Birt-Hogg-Dubé syndrome (BHDS) should be considered in patients with renal neoplasms and multiple pulmonary cysts. A lower zone predominant, perilymphatic distribution of pulmonary cysts is a strong indicator of BHDS. Identifying specific CT features of pulmonary cysts can improve recognition of BHDS.
Original languageEnglish
Article number169
Number of pages11
JournalInsights into Imaging
Volume16
Early online date6 Aug 2025
DOIs
Publication statusPublished - 6 Aug 2025

Bibliographical note

Copyright © The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/.

Funding

The following authors receive research support from the following institutions: G.D.S. receives research support from Cancer Research UK, YCR and NIHR. A.Y.W. receives research support from Cancer Research UK Cambridge Centre [C9685/A25177] and NIHR Cambridge Biomedical Research Centre [BRC-1215-20014]. A.H.A. [NIHR ACF-2019-14-004] and E.R.M. [NIHR203312] receive research support from NIHR. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. J.W. receives research support from the University of Cambridge. S.J.M. receives research support from the Myrovlytis Trust [MT21_1] and [MT22_15], and from the LifeArc Centre. M.T.A.W. receives research support from the Myrovlytis Trust [MT22_15]. No funding was received to conduct this specific study.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Birt-Hogg-Dubé syndrome
  • Cystic lung disease
  • Renal cancer
  • Computed tomography

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