Sistemik Skleroz İlişkili İnterstisyel Akciğer Hastalığında Tedavi Yanıtını İzlemede Bilgisayarlı Tomografiye Dayalı Yeni Parametreler

Öz

Yüksek çözünürlüklü bilgisayarlı tomografi (YÇBT) ve solunum fonksiyon testi (SFT) günümüzde Sistemik Skleroza bağlı interstisyel akciğer hastalığının (SSk-İAH) tanısında, tedavi kararında ve tedavinin takibinde kullanılan başlıca yöntemdir. Çalışmamızın amacı, YÇBT görüntülerini analiz ederek hastaların takibinde kullanılabilecek yeni kantitatif parametreleri araştırmaktır. Çalışmaya SSk-İAH nedeniyle tedavi gören, başlangıç ve 12.ay takipleri sırasında YÇBT ve SFT sonuçlarına ulaşılabilen 35 hasta dahil edildi. Hastaların YÇBT görüntüleri Vitrea® Advanced Visualization yazılımı ile analiz edildi. Akciğer atenuasyon eğrisi kullanılarak sağ ve sol akciğerler için ortalama akciğer atenuasyonu (OAA), düşük-, orta- ve yüksek-yoğunluklu akciğer hacimleri, düşük dansite (DD) indeksi ve yüzde dansite 15 (YD15) elde edildi. Elde edilen parametrelerin zaman içerisindeki değişimi ve SSk-İAH hastalarında tedaviye yanıtı değerlendirmek için kullanılan FVC ve DLCO testleri ile arasındaki ilişki incelendi. Çalışmadaki hastaların %82,9’u kadın, %63’ü diffüz cilt tutulumlu, hastalık süresi 8,13±5,96 yıl ve ortalama yaş 53,8±9,96’tı. Takip FVC, DLCO ve tüm BT parametrelerinde başlangıca göre bir değişim saptanmadı. Başlangıç ve takipte DLCO’nun BT parametrelerinden hiçbiri ile korelasyon göstermediği, ancak FVC’nin hem başlangıçta hem de takipte sağ/sol orta-yoğunluklu akciğer volümü ve sağ/sol total akciğer hacmi ile ilişkili olduğu saptandı. Ayrıca fibrozis skoru ile hem başlangıç hem de takipteki sağ ve sol akciğer ortalama atenuasyonu, orta dansiteli volüm, yüksek dansiteli volüm ve akciğer volümü ile orta-kuvvetli ilişki saptandı. Çalışmamızın sonucunda, SSk-İAH hastalarında hem başlangıç hem de takip FVC ve fibrozis skoru ile anlamlı korelasyon gösteren kantitatif YÇBT parametreleri saptanmıştır. Sonuçlarımız, SFT gibi hasta kooperasyonundan ve semi-kantitatif fibrozis yaygınlık skoru gibi radyologların değerlendirmesinden etkilenmeyen parametrelerin geliştirilmesine katkı sağlayacaktır.

Anahtar Kelimeler

• sistemik skleroz
• interstisyel akciğer hastalığı
• yüksek çözünürlüklü bilgisayarlı tomografi

New Computed Tomography-Based Parameters for Monitoring Treatment Response in Systemic Sclerosis-Associated Interstitial Lung Disease

Öz

High-resolution computed tomography (HRCT) and pulmonary function test are currently the main methods used in the diagnosis, treatment decision, and follow-up of systemic sclerosis-associated interstitial lung disease (SSc-ILD). We aimed to analyze new quantitative parameters that can be used in the follow-up of patients by analyzing HRCT images. 35 patients whose HRCT and PFT results were available at baseline and 12th-month follow-up were included in the study. HRCT images of the patients were analyzed with Vitrea® Advanced Visualization software. Using the lung attenuation curve, mean lung attenuation, low-, medium-, and high-density lung volumes, low-density index, and percent density 15 were obtained. Of the patients in the study, 82.9% were female, 63% had diffuse skin involvement, the disease duration was 8.13±5.96 years, and the mean age was 53.8±9.96 years. There was no change in follow-up FVC, DLCO, and CT parameters from baseline. DLCO did not correlate with any of the CT parameters at baseline and follow-up, but FVC was associated with right/left medium-density lung volume and right/left total lung volume at baseline and follow-up. In addition, a moderate-strong relationship was found between the fibrosis score and the mean attenuation, medium-density volume, high-density volume, and lung volume both at baseline and at follow-up. Quantitative HRCT parameters were found to be significantly correlated with both baseline and follow-up FVC and fibrosis scores in SSc-ILD patients. Our results will contribute to the development of quantitative parameters that are not affected by patient cooperation, or the evaluation of radiologists' experience.

Anahtar Kelimeler

• systemic sclerosis
• interstitial lung disease
• high resolution computed tomography

Kaynakça

1. Denton CP, Khanna D. Systemic sclerosis [review]. Lancet 2017; 390:1685–99.
2. Hoffmann-Vold AM, Fretheim H, Halse AK, et al. Tracking impact of interstitial lung disease in systemic sclerosis in a complete nationwide cohort. Am J Respir Crit Care Med 2019; 200: 1258–1266.
3. Bergamasco A, Hartmann N, Wallace L, et al. Epidemiology of systemic sclerosis and systemic sclerosis-associated interstitial lung disease. Clin Epidemiol 2019; 11: 257–273.
4. Elhai M, Meune C, Boubaya M, et al. Mapping and predicting mortality from systemic sclerosis. Ann Rheum Dis 2017; 76: 1897–1905.
5. Konopka KE, Myers JL. Interstitial lung disease pathology in systemic sclerosis. Ther Adv Musculoskelet Dis. 2021 Jul 17;13:1759720X211032437. doi: 10.1177/1759720X211032437. PMID: 34349846; PMCID: PMC8287363
6. Hoffmann-Vold AM, Allanore Y, Alves M, Brunborg C, Airó P, Ananieva LP, Czirják L, Guiducci S, Hachulla E, Li M, Mihai C, Riemekasten G, Sfikakis PP, Kowal-Bielecka O, Riccardi A, Distler O; EUSTAR collaborators. Progressive interstitial lung disease in patients with systemic sclerosis-associated interstitial lung disease in the EUSTAR database. Ann Rheum Dis. 2021 Feb;80(2):219-227. doi: 10.1136/annrheumdis-2020-217455. Epub 2020 Sep 28. PMID: 32988845; PMCID: PMC7815627
7. Hoffmann-Vold AM, Maher TM, Philpot EE, Ashrafzadeh A, Barake R, Barsotti S, et al. The identification and management of interstitial lung disease in systemic sclerosis: evidence-based European consensus statements. Lancet Rheumatol 2020;2:e71–83.
8. Daimon T, Johkoh T, Honda O, et al. Nonspecific interstitial pneumonia associated with collagen vascular disease: analysis of CT features to distinguish the various types. Intern Med 2009; 48: 753–761.

9. Watadani T, Sakai F, Johkoh T, Noma S, Akira M, Fujimoto K, Bankier AA, Lee KS, Müller NL, Song JW, Park JS, Lynch DA, Hansell DM, Remy-Jardin M, Franquet T, Sugiyama Y (2013) Interobserver variability in the CT assessment of honeycombing in the lungs. Radiology 266(3):936–944. https://doi.org/10.1148/ radiol.12112516
10. Walsh SL, Calandriello L, Sverzellati N, Wells AU, Hansell DM (2016) UIP Observer Consort. Interobserver agreement for the ATS/ERS/JRS/ALAT criteria for a UIP pattern on CT. Thorax 71(1):45–51.
11. Bernstein EJ, Jaafar S, Assassi S, Domsic RT, Frech TM, Gordon JK, Broderick RJ, Hant FN, Hinchcliff ME, Shah AA, Shanmugam VK, Steen VD, Khanna D. Performance Characteristics of Pulmonary Function Tests for the Detection of Interstitial Lung Disease in Adults With Early Diffuse Cutaneous Systemic Sclerosis. Arthritis Rheumatol. 2020 Nov;72(11):1892-1896. doi: 10.1002/art.41415. Epub 2020 Sep 22. Erratum in: Arthritis Rheumatol. 2021 Apr;73(4):720. PMID: 32583956; PMCID: PMC7722107.
12. van den Hoogen F, Khanna D, Fransen J, Johnson SR, Baron M, Tyndall A et al (2013) Classification criteria for systemic sclerosis: an American college of rheumatology/European league against rheumatism collaborative initiative. Ann Rheum Dis 72(11):1747–1755. https:// doi. org/ 10. 1136/ annrh eumdis- 2013- 204424
13. 1LeRoy EC, Black C, Fleischmajer R, Jablonska S, Krieg T, Medsger TA Jr, Rowell N, Wollheim F (1988) Scleroderma (systemic sclerosis): classification, subsets and pathogenesis. J Rheumatol 15(2):202–205
14. Suliman YA, Dobrota R, Huscher D, Nguyen-Kim TD, Maurer B, Jordan S, Speich R, Frauenfelder T, Distler O (2015) Brief report: pulmonary function tests: high rate of false-negative results in the early detection and screening of scleroderma-related ınterstitial lung disease. Arthritis Rheumatol 67(12):3256–3261.
15. Shin KE, Chung MJ, Jung MP, Choe BK, Lee KS (2011) Quantitative computed tomographic indexes in diffuse interstitial lung disease: correlation with physiologic tests and computed tomography visual scores. J Comput Assist Tomogr 35(2):266–271.
16. Kauczor HU, Heitmann K, Heussel CP, Marwede D, Uthmann T, Thelen M (2000) Automatic detection and quantification of ground-glass opacities on high-resolution CT using multiple neural networks: comparison with a density mask. AJR Am J Roentgenol 175(5):1329–1334.
17. Goh NS, Desai SR, Veeraraghavan S, Hansell DM, Copley SJ, Maher TM, Corte TJ, Sander CR, Ratoff J, Devaraj A, Bozovic G, Denton CP, Black CM, du Bois RM, Wells AU (2008) Interstitial lung disease in systemic sclerosis: a simple staging system. Am J Respir Crit Care Med 177(11):1248–1254.
18. Suliman YA, Dobrota R, Huscher D, Nguyen-Kim TD, Maurer B, Jordan S, et al. Pulmonary function tests: high rate of false-negative results in the early detection and screening of scleroderma-related interstitial lung disease. Arthritis Rheumatol 2015;67:3256–61
19. Hoffmann-Vold AM, Maher TM, Philpot EE, Ashrafzadeh A, Barake R, Barsotti S, et al. The identification and management of interstitiallung disease in systemic sclerosis: evidence-based European consensus statements. Lancet Rheumatol 2020;2:e71–83
20. Goh NS, Hoyles RK, Denton CP, et al. Short-term pulmonary function trends are predictive of mortality in interstitial lung disease associated with systemic sclerosis. Arthritis Rheumatol 2017; 69: 1670–1678.
21. Wu W, Jordan S, Graf N, et al. Progressive skin fibrosis is associated with a decline in lung function and worse survival in patients with diffuse cutaneous systemic sclerosis in the European Scleroderma Trials and Research (EUSTAR) cohort. Ann Rheum Dis 2019; 78: 648–656.
22. Distler O, Assassi S, Cottin V, et al. Predictors of progression in systemic sclerosis patients with interstitial lung disease. Eur Respir J 2020; 55: 1902026.
23. Khanna D, Mittoo S, Aggarwal R, et al. Connective tissue disease-associated interstitial lung diseases (CTD-ILD) – report from OMERACT CTD-ILD Working Group. J Rheumatol 2015; 42: 2168–2171.
24. Temiz Karadag D, Cakir O, Komac A, Yazici A, Cefle A. Software-based quantitative analysis of lung parenchyma in patients with systemic sclerosis may provide new generation data for pulmonary fibrosis. Int J Clin Pract. 2021 Apr;75(4):e13931. doi: 10.1111/ijcp.13931. Epub 2020 Dec 20. PMID: 33301623.