| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 3982127 | Clinical Radiology | 2014 | 8 Pages |
•Conventional morphologic imaging (x-ray or CT) is hard to detect the early changes of lungs after thoracic radiotherapy.•CT perfusion imaging metrics may reflect hemodynamic changes in post-irradiation lung.•CT perfusion imaging can detect manifestations of early radiation-induce lung injury cases which appear normal on CT.•CT perfusion imaging is a promising technique for early diagnosis of acute radiation-induce lung injury.
AimTo explore the value of 64-section computed tomography (CT) perfusion imaging (CTPI) in the early diagnosis of acute radiation-induced lung injury (ARILI).Materials and methodsFifty-one patients with oesophageal cancers or malignant thymomas received postoperative radiation therapy with a 60–62 Gy dose and underwent CTPI at pre- and post-radiation therapy time points (week 0, week 4, week 8, and week 12 respectively). The CTPI values were prospectively compared and analysed in order to evaluate the diagnostic utility of CTPI in the early diagnosis of ARILI.ResultsEighteen cases (18/51) of ARILI were diagnosed. The mean values of relative regional blood flow (rrBF), relative regional volume (rrBV), and relative regional permeability surface (rrPS) in the ARILI group were correspondingly higher than those of the non-ARILI group. At week 4, rrBF, rrBV, and rrPS in the ARILI group were significantly higher than those at pre-radiation (each p < 0.05). In the non-ARILI group, rrBF and rrBV were higher than those at pre-radiation (each p < 0.05); however, rrPS was not statistically different from that of pre-irradiation. Applying the diagnostic threshold value of rrPS = 1.22, the sensitivity, specificity, and positive and negative predictive values of CTPI for early diagnosis of ARILI were better than those of CT.ConclusionCTPI metrics may reflect haemodynamic changes in the post-irradiation lung and can detect cases of early ARILI that appear normal at CT. CTPI is a promising technique for early diagnosis of ARILI.
