Dual-source virtual non-contrast CT of the head: a preliminary study

Abstract

：Objective To investigateimage quality and clinical value of dual-source dual energy virtual non-contrast (VNC) CTof the head. Methods Sixty-two patients suspected of cerebrovascular diseases underwentconventional non-contrast (CNC) CT and dual energy CTA examination of the head withdual-source CT. Virtual non-contrast images were reconstructed using dual energy software.The CT values of gray matter, white matter, cerebrospinal fluid, hyperdense hemorrhagiclesion and hypodense ischemic lesion were compared between CNC and VNC images. Afour-score scale was used to assess image quality subjectively. Image noise, radiationdosage and detection rate were compared between CNC and VNC images. Paired t test,Wilcoxon signed ranks test and Chi-square test (McNemar test and Kappa test) were used.Results The CT value on CNC and VNC images, were (43. 3 ± 1.5) and (33. 2 ± 1.3) HU forgray matter (t = 46.98, P ＜ 0. 01), (32. 9 ± 1.3) and(28.8 ± 1.6) HU for white matter(t = 16. 28, P ＜0.01), (9.0 ± 1.4) and (5.3± 1.9) HU for cerebrospinal fluid (t=12.41, P＜0.01),(62.8 ±10.0) and (51.3± 11.5) HU for hyperdense lesion (Z = -4.37, P ＜ 0.01), (20.7 ±4.7) and (18.0 ±6. 9) HU for hypodense lesion (t = 3. 84, P＜ 0. 01), respectively. VNC images[(1.63 ±0.34)HU]had more noise than CNC images[(0.99±0.18) HU](Z= -6.41, P＜0.01). VNC [(0. 53 ± 0. 08)mSv]had less effective dose than CNC[(1.37 ± 0. 23) mSy](Z= - 6. 45, P ＜ 0. 01).In subjective assessment, VNC images had more noise (2. 7 ±0. 5 for VNC and 3.9 ± 0. 3 for CNC,Z = -6. 84, P ＜ 0. 01) and skull base-related artifacts (2. 4 ± 0. 9 for VNC and 3.7 ± 0. 5 forCNC,Z = -6. 15, P ＜0. 01) than CNC images. The gray/white mattercontrast (1.3 ± 0. 5 for VNC and 3.3 ±0. 6 for CNC, Z = - 7. 01, P ＜ 0. 01), hyperdense lesion display (3.0 ± 0. 4 for VNC and 4. 0 ±0. 0 for CNC,Z = -4. 52, P ＜ 0. 01) and hypodense lesiondisplay (3.2 ± 0. 8 for VNC and 3.9 ± 0. 3 for CNC,Z= -3. 12, P ＜0.01) on VNC images were lower than those on CNC images. In per-patient analysis,29 cases ofhyperdense lesion (hemorrhage) were found on VNC images without misdiagnosis. Thesensitivity, specificity, positive predictive value and negative predictive value were all100. 0% (29/29,33/33, 29/29, 33/33). VNC images had the same detection rate of hyperdenselesions as CNC images (P ＞0. 05, Kappa = 1. 000) atper-patient level. Twenty-two patients with hypodense ischemic lesions were found on VNCimages with one false positive case and two false negative cases. Thesensitivity,specificity, positive predictive value and negative predictive value were91.3% (21/23), 97.4%(38/39), 95.5% (21/22) and 95.0% (38/40) respectively. No statisticaldifference was found in detecting hypodense lesions between VNC and CNC images (χ2 =0. 00, P ＞ 0. 05, Kappa = 0. 895). Inper-lesion analysis, 53 hemorrhage lesions were found on VNC images with false negativeresults of four lesions and no false positive result. The sensitivity, specificity,positive predictive value and negative predictive value were 93.0% (53/57), 100. 0%(38/38), 100. 0% (53/53) and 90. 5% (38/42)respectively. There was no significantdifference in detection rate of hyperdense lesion between VNC and CNC images (χ2 =2.25, P ＞0. 05, Kappa =0. 914). Thirty-eight hypodense lesions were found onVNC images with 2 false positive lesions and 13 false negative lesions. The sensitivity,specificity, positive predictive value and negative predictive value were 73.5% (36/49),96.4% (53/55), 94. 7% (36/38)and 80. 3% (53/66) respectively. The detection rate ofhypodense lesion on VNC images was lower than that on CNC images (χ2 =6. 67 ,P ＜ 0.01,Kappa = 0. 707). Conclusion Compared with CNC images,head VNC images have reduced imagequality and radiation dosage. VNC images can replace CNC images potentially in detectingintracranial hemorrhage and provide information for ischemic cerebrovascular diseases tosome extent. Key words: Tomography,X-ray computed; Head; Cerebrovascular trauma