Helck A, Hummel N, Meinel F G, Johnson T, Nikolaou K, Graser A
Institute for Clinical Radiology, University of Munich, Grosshadern Campus, Marchioninistr. 15, 81377, Munich, Germany,
Eur Radiol. 2014 Jul;24(7):1636-42. doi: 10.1007/s00330-014-3192-z. Epub 2014 May 8.
To evaluate whether single-phase dual-energy-CT-based attenuation measurements can reliably differentiate lipid-rich adrenal adenomas from malignant adrenal lesions.
We retrospectively identified 51 patients with adrenal masses who had undergone contrast-enhanced dual-energy-CT (140/100 or 140/80 kVp). Virtual non-contrast and colour-coded iodine images were generated, allowing for measurement of pre- and post-contrast density on a single-phase acquisition. Adrenal adenoma was diagnosed if density on virtual non-contrast images was ≤10 HU. Clinical follow-up, true non-contrast CT, PET/CT, in- and opposed-phase MRI, and histopathology served as the standard of reference.
Based on the standard of reference, 46/57 (80.7%) adrenal masses were characterised as adenomas or other benign lesions; 9 malignant lesions were detected. Based on a cutoff value of 10 HU, virtual non-contrast images allowed for correct identification of adrenal adenomas in 33 of 46 (71%), whereas 13/46 (28%) adrenal adenomas were lipid poor with a density ≥10 HU. Based on the threshold of 10 HU on the virtual non-contrast images, the sensitivity, specificity, and accuracy for detection of benign adrenal lesions was 73%, 100%, and 81% respectively.
Virtual non-contrast images derived from dual-energy-CT allow for accurate characterisation of lipid-rich adrenal adenomas and can help to avoid additional follow-up imaging.
• Adrenal adenomas are a common lesion of the adrenal glands. • Differentiation of benign adrenal adenomas from malignant adrenal lesions is important. • Dual-energy based virtual non-contrast images help to evaluate patients with adrenal adenomas.
评估基于单相双能量CT的衰减测量能否可靠地区分富含脂质的肾上腺腺瘤与肾上腺恶性病变。
我们回顾性纳入了51例接受对比增强双能量CT(140/100或140/80 kVp)检查的肾上腺肿块患者。生成了虚拟平扫和彩色编码碘图像,以便在单相采集中测量对比剂注射前后的密度。若虚拟平扫图像上的密度≤10 HU,则诊断为肾上腺腺瘤。临床随访、真正的平扫CT、PET/CT、同反相位MRI及组织病理学检查作为参考标准。
根据参考标准,57个肾上腺肿块中有46个(80.7%)被判定为腺瘤或其他良性病变;检测到9个恶性病变。基于10 HU的临界值,虚拟平扫图像能够正确识别46个肾上腺腺瘤中的33个(71%),而46个肾上腺腺瘤中有13个(28%)为低脂质腺瘤,密度≥10 HU。基于虚拟平扫图像上10 HU的阈值,检测良性肾上腺病变的敏感性、特异性和准确性分别为73%、100%和81%。
双能量CT生成的虚拟平扫图像能够准确鉴别富含脂质的肾上腺腺瘤,并有助于避免额外的随访成像检查。
•肾上腺腺瘤是肾上腺常见病变。•区分良性肾上腺腺瘤与肾上腺恶性病变很重要。•基于双能量的虚拟平扫图像有助于评估肾上腺腺瘤患者。