Pulmonary vessel volume can help to differentiate fibrotic lung diseases

Abstract

Objectives: Idiopathic pulmonary fibrosis (IPF), non-specific interstitial pneumonia (NSIP), and chronic hypersensitivity pneumonitis (CHP) are diffuse fibrosing lung diseases that are sometimes difficult to differentiate by only visual evaluation of CT images. We aimed to find if pulmonary vessel volume (PVV), a new quantitative CT measure, can help to differentiate these diseases at the time of diagnosis.

Methods: We retrospectively measured PVV values of IPF, NSIP, and CHP patients diagnosed within the last five years in our institution, by using their CT images at the time of diagnosis. We used CALIPER-technology (Computer-Aided Lung Informatics for Pathology Evaluation and Rating) for the quantification of CT images. We compared the PVV values of disease groups by the Kruskal-Wallis test and performed ROC curve analysis to evaluate the ability of PVV to differentiate these diseases.

Results: We measured the PVV values of 152 patients, 113 of them were diagnosed with IPF, 16 with NSIP, and 23 with CHP. The PVV value of the NSIP group was significantly lower than that of both IPF (p = 0.028) and CHP (p = 0.013) groups. However, there was no significant difference between IPF and CHP groups (p = 0.924). Selected cut-off values of PVV were found to differentiate NSIP from IPF with a specificity of 88%, and NSIP from CHP with a specificity of 91%.

Conclusions: PVV measured by CALIPER at the time of diagnosis can help to differentiate NSIP from both IPF and CHP.

Keywords

• Hypersensitivity pneumonitis
• idiopathic pulmonary fibrosis
• nonspecific interstitial pneumonia
• pulmonary vessel volume
• quantitative computed tomography

References

1. 1. Horst C, Gholipour B, Nair A, Jacob J. Differential diagnoses of fibrosing lung diseases. BJR Open 2019;1:20190009.
2. 2. Meyer KC. Diagnosis and management of interstitial lung disease. Transl Respir Med 2014;2:4.
3. 3. Bartholmai BJ, Raghunath S, Karwoski RA, Moua T, Rajagopalan S, Maldonado F, et al. Quantitative CT imaging of interstitial lung diseases. J Thorac Imaging 2013;28:298-307.
4. 4. Crews MS, Bartholmai BJ, Adegunsoye A, Oldham JM, Montner SM, Karwoski RA, et al. Automated CT analysis of major forms of interstitial lung disease. J Clin Med 2020;9:3776.
5. 5. Jacob J, Bartholmai BJ, Rajagopalan S, Kokosi M, Nair A, Karwoski R, et al. Automated quantitative computed tomography versus visual computed tomography scoring in idiopathic pulmonary fibrosis: validation against pulmonary function. J Thorac Imaging 2016;31:304-11.
6. 6. Jacob J, Pienn M, Payer C, Urschler M, Kokosi M, Devaraj A, et al. Quantitative CT-derived vessel metrics in idiopathic pulmonary fibrosis: a structure-function study. Respirology 2019;24:445-52.
7. 7. Occhipinti M, Bruni C, Camiciottoli G, Bartolucci M, Bellando-Randone S, Bassetto A, et al. Quantitative analysis of pulmonary vasculature in systemic sclerosis at spirometry-gated chest CT. Ann Rheum Dis 2020;79:1210-7.
8. 8. Jacob J, Bartholmai BJ, Rajagopalan S, Brun AL, Egashira R, Karwoski R, et al. Evaluation of computer-based computer tomography stratification against outcome models in connective tissue disease-related interstitial lung disease: a patient outcome study. BMC Med 2016;14:190.

9. 9. Jacob J, Bartholmai BJ, Egashira R, Brun AL, Rajagopalan S, Karwoski R, et al. Chronic hypersensitivity pneumonitis: identification of key prognostic determinants using automated CT analysis. BMC Pulm Med 2017;17:81.
10. 10. Jacob J, Bartholmai BJ, Rajagopalan S, Kokosi M, Nair A, Karwoski R, et al. Mortality prediction in idiopathic pulmonary fibrosis: evaluation of computer-based CT analysis with conventional severity measures. Eur Respir J 2017;49:1601011.
11. 11. Jacob J, Pienn M, Payer C, Urschler M, Kokosi M, Devaraj A, et al. Normalized vessel volume from quantitative computed tomography predicts survival in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med 2019;199:A1040.
12. 12. Sverzellati N, Silva M, Seletti V, Galeone C, Palmucci S, Piciucchi S, et al. Stratification of long-term outcome in stable idiopathic pulmonary fibrosis by combining longitudinal computed tomography and forced vital capacity. Eur Radiol 2020;30:2669-79.
13. 13. Jacob J, Hirani N, van Moorsel CHM, Rajagopalan S, Murchison JT, van Es HW, et al. Predicting outcomes in rheumatoid arthritis related interstitial lung disease. Eur Respir J 2019;53:1800869.
14. 14. Newell JD Jr, Sieren J, Hoffman EA. Development of quantitative computed tomography lung protocols. J Thorac Imaging 2013;28:266-71.
15. 15. Wu X, Kim GH, Salisbury ML, Barber D, Bartholmai BJ, Brown KK, et al. Computed Tomographic Biomarkers in Idiopathic Pulmonary Fibrosis. The Future of Quantitative Analysis. Am J Respir Crit Care Med 2019;199:12-21.
16. 16. Wuyts WA, Cavazza A, Rossi G, Bonella F, Sverzellati N, Spagnolo P. Differential diagnosis of usual interstitial pneumonia: when is it truly idiopathic? Eur Respir Rev 2014;23:308-19.
17. 17. Chung JH, Adegunsoye A, Oldham JM, Vij R, Husain A, Montner SM, et al. Vessel-related structures predict UIP pathology in those with a non-IPF pattern on CT. Eur Radiol 2021;31:7295-302.
18. 18. Romei C, Tavanti LM, Taliani A, De Liperi A, Karwoski R, Celi A, et al. Automated Computed Tomography analysis in the assessment of Idiopathic Pulmonary Fibrosis severity and progression. Eur J Radiol 2020;124:108852.
19. 19. Puxeddu E, Cavalli F, Pezzuto G, Teodori E, Rogliani P. Impact of pulmonary vascular volume on mortality in IPF: is it time to reconsider the role of vasculature in disease pathogenesis and progression? Eur Respir J 2017;49:1602345.
20. 20. Wu WJ, Huang WM, Liang CH, Yun CH. Pulmonary vascular volume is associated with DLCO and fibrotic score in idiopathic pulmonary fibrosis: an observational study. BMC Med Imaging 2022;22:76.
21. 21. Jacob J, Bartholmai BJ, Rajagopalan S, van Moorsel CHM, van Es HW, van Beek FT, et al. Predicting outcomes in idiopathic pulmonary fibrosis using automated computed tomographic analysis. Am J Respir Crit Care Med 2018;198:767-76.
22. 22. Jacob J, Bartholmai BJ, Brun AL, Egashira R, Rajagopalan S, Karwoski R, et al. Evaluation of visual and computer-based CT analysis for the identification of functional patterns of obstruction and restriction in hypersensitivity pneumonitis. Respirology 2017;22:1585-91.
23. 23. Turner-Warwick M. Precapillary systemic-pulmonary anastomoses. Thorax 1963;18:225-37.
24. 24. Miller WC, Heard JG, Unger KM, Suich DM. Anatomical lung shunting in pulmonary fibrosis. Thorax 1986;41:208-9.
25. 25. Jee AS, Jo HE, Corte TJ. Hypersensitivity pneumonitis: A protean and challenging disease. Respirology 2017;22:1489-90.
26. 26. Chen A, Karwoski RA, Gierada DS, Bartholmai BJ, Koo CW. Quantitative CT analysis of diffuse lung disease. Radiographics 2020;40:28-43.
27. 27. Weatherley ND, Eaden JA, Stewart NJ, Bartholmai BJ, Swift AJ, Bianchi SM, et al. Experimental and quantitative imaging techniques in interstitial lung disease. Thorax 2019;74:611-9.