Lobar pulmonary perfusion quantification with dual-energy CT angiography: Interlobar variability and relationship with regional clot burden in pulmonary embolism

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1
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article
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2022
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EUROPEAN JOURNAL OF RADIOLOGY OPEN, v.9, article ID 100428, 8p, 2022
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Purpose: Semi-automated lobar segmentation tools enable an anatomical assessment of regional pulmonary perfusion with Dual-Energy CTA (DE-CTA). We aimed to quantify lobar pulmonary perfusion with DE-CTA, analyze the perfusion distribution among the pulmonary lobes in subjects without cardiopulmonary diseases and assess the correlation between lobar perfusion and regional endoluminal clots in patients with acute pulmonary embolism (PE). Methods: We evaluated 151 consecutive subjects with suspected PE and without cardiopulmonary comorbidities. DE-CTA derived perfused blood volume (PBV) of each pulmonary lobe was measured applying a semi-automated lobar segmentation technique. In patients with PE, blood clot location was assessed, and CT-based vascular obstruction index of each lobe (CTOIlobe) was calculated and classified into three groups: CTOIlobe= 0, low CTOIlobe (1-50%) and high CTOIlobe (>50%). Results: Among patients without PE (103/151, 68.2%), median lobar PBV was 13.7% (IQR 10.2-18.0%); the right middle lobe presented lower PBV when compared to all the other lobes (p < .001). In patients with PE (48/151, 31.8%), lobar PBV was 12.6% (IQR 9.6-15.7%), 13.7% (IQR 10.1-16.7%) and 6.5% (IQR 5.1-10.2%) in the lobes with CTOIlobe= 0, low CTOIlobe and high CTOIlobe scores, respectively, with a significantly decreased PBV in the lobes with high CTOIlobe score (p < .001). ROC analysis of lobar PBV for prediction of high CTOIlobe score revealed AUC of 0.847 (95%CI 0.785-0.908).
Palavras-chave
Pulmonary embolism, Computed tomography angiography, Pulmonary perfusion, Blood volume, Dual-energy computed tomography (DECT)
Referências
  1. Almquist HM, 1997, J NUCL MED, V38, P962
  2. Altemeier WA, 1998, J APPL PHYSIOL, V85, P2344, DOI 10.1152/jappl.1998.85.6.2344
  3. ALVAREZ RE, 1976, PHYS MED BIOL, V21, P733, DOI 10.1088/0031-9155/21/5/002
  4. ANTHONISEN NR, 1966, J APPL PHYSIOL, V21, P760, DOI 10.1152/jappl.1966.21.3.760
  5. BALL WC, 1962, J CLIN INVEST, V41, P519, DOI 10.1172/JCI104505
  6. Bauer RW, 2011, EUR RADIOL, V21, P1914, DOI 10.1007/s00330-011-2135-1
  7. BRYAN AC, 1964, J APPL PHYSIOL, V19, P395, DOI 10.1152/jappl.1964.19.3.395
  8. Burrowes KS, 2005, ACAD RADIOL, V12, P1464, DOI 10.1016/j.acra.2005.06.004
  9. Estepar RS, 2015, AM J RESP CRIT CARE, V191
  10. Fedorov A, 2012, MAGN RESON IMAGING, V30, P1323, DOI 10.1016/j.mri.2012.05.001
  11. Felloni P, 2017, ACAD RADIOL, V24, P1412, DOI 10.1016/j.acra.2017.05.003
  12. Fuld MK, 2013, RADIOLOGY, V267, P747, DOI 10.1148/radiol.12112789
  13. GLENNY RW, 1992, J APPL PHYSIOL, V72, P2378, DOI 10.1152/jappl.1992.72.6.2378
  14. GLENNY RW, 1991, J APPL PHYSIOL, V71, P620, DOI 10.1152/jappl.1991.71.2.620
  15. GLENNY RW, 1991, J APPL PHYSIOL, V71, P2449, DOI 10.1152/jappl.1991.71.6.2449
  16. HAKIM TS, 1987, J APPL PHYSIOL, V63, P1114, DOI 10.1152/jappl.1987.63.3.1114
  17. Hopkins SR, 2007, J APPL PHYSIOL, V103, P240, DOI 10.1152/japplphysiol.01289.2006
  18. Hopkins SR, 2012, J APPL PHYSIOL, V113, P328, DOI 10.1152/japplphysiol.00320.2012
  19. Hsu K, 2018, J BRONCHOL INTERN PU, V25, P48, DOI 10.1097/LBR.0000000000000445
  20. HUGHES JMB, 1968, RESP PHYSIOL, V4, P58, DOI 10.1016/0034-5687(68)90007-8
  21. Jones AT, 2001, J APPL PHYSIOL, V90, P1342, DOI 10.1152/jappl.2001.90.4.1342
  22. KANEKO K, 1966, J APPL PHYSIOL, V21, P767, DOI 10.1152/jappl.1966.21.3.767
  23. Koike H, 2016, EUR J RADIOL, V85, P1607, DOI 10.1016/j.ejrad.2016.06.016
  24. LISBONA R, 1987, J NUCL MED, V28, P1758
  25. Liu X, 2009, MED PHYS, V36, P1602, DOI 10.1118/1.3097632
  26. Meinel FG, 2013, INVEST RADIOL, V48, P563, DOI 10.1097/RLI.0b013e3182879482
  27. MELSOM MN, 1995, ACTA PHYSIOL SCAND, V153, P343, DOI 10.1111/j.1748-1716.1995.tb09872.x
  28. Mukaka MM, 2012, MALAWI MED J, V24, P69
  29. Nyren S, 1999, J APPL PHYSIOL, V86, P1135, DOI 10.1152/jappl.1999.86.4.1135
  30. Onieva J., 2016, INT J COMPUT ASSIST, V1, pS40
  31. Qanadli SD, 2001, AM J ROENTGENOL, V176, P1415, DOI 10.2214/ajr.176.6.1761415
  32. Rotzinger David C, 2020, Radiol Cardiothorac Imaging, V2, pe190188, DOI 10.1148/ryct.2020190188
  33. Sakamoto A, 2014, AM J ROENTGENOL, V203, P287, DOI 10.2214/AJR.13.11586
  34. Singh R, 2020, EUR RADIOL, V30, P2535, DOI 10.1007/s00330-019-06607-9
  35. Sueyoshi E, 2011, EUR J RADIOL, V80, pE505, DOI 10.1016/j.ejrad.2010.10.011
  36. Suzuki H, 2008, EUR RADIOL, V18, P522, DOI 10.1007/s00330-007-0808-6
  37. WEST JB, 1978, CHEST, V74, P426, DOI 10.1378/chest.74.4.426
  38. Zucker EJ, 2019, INT J CARDIOVAS IMAG, V35, P1473, DOI 10.1007/s10554-019-01602-z