Diagnosis of liver hemangioma using magnetic resonance diffusion-derived vessel density (DDVD) pixelwise map: a preliminary descriptive study

Liver hemangiomas (HGs) are characterized by cavernous venous spaces delineated by a lining of vascular endothelial cells and interspersed with connective tissue septa. Typically, a liver HG has higher apparent diffusion coefficient (ADC) and T2 values than those of hepatocellular carcinomas (HCCs)...

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Veröffentlicht in:Quantitative imaging in medicine and surgery 2024-12, Vol.14 (12), p.8064-8082
Hauptverfasser: Hu, Gen-Wen, Li, Cai-Ying, Zhang, Ge, Zheng, Cun-Jing, Ma, Fu-Zhao, Quan, Xian-Yue, Chen, Weibo, Sabarudin, Akmal, Zhu, Michael S Y, Li, Xin-Ming, Wáng, Yì Xiáng J
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Sprache:eng
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Zusammenfassung:Liver hemangiomas (HGs) are characterized by cavernous venous spaces delineated by a lining of vascular endothelial cells and interspersed with connective tissue septa. Typically, a liver HG has higher apparent diffusion coefficient (ADC) and T2 values than those of hepatocellular carcinomas (HCCs) and liver metastases, and lower ADC and T2 values than those of liver simple cysts. However, a portion of HGs shows ADC and T2 overlapping with those of HCC, liver metastasis, and simple cyst. When MRI is the first line examination for the liver, contrast enhanced imaging is commonly used to confirm the diagnosis of liver HG. Magnetic resonance diffusion-derived vessel density (DDVD) is a physiological surrogate of the area of microvessels per unit tissue area. DDVD is calculated according to: DDVD(b0b2) = Sb0/ROIarea0 - Sb2/ROIarea2, where Sb0 and Sb2 refer to the tissue signal when is 0 or 2 (s/mm ). Sb2 and ROIarea2 can also be approximated by other low -values (such as =10) diffusion-weighted imaging (DWI). In this study, we conducted a preliminary evaluation of magnetic resonance DDVD pixelwise map (DDVDm) for liver HG diagnosis. Three testing datasets were included. All imaging data were acquired at 3.0T. Dataset-1 consisted of 16 HGs (lesion diameter: 1.5-8.85 cm), 4 focal nodular hyperplasia (FNHs, lesion diameter: 1.72-5.7 cm), and 24 HCCs (lesion diameter: 1.83-12.77 cm), and DDVDm was reconstructed with =0 and =2 images. Dataset-2 consisted of 6 HGs (lesion diameter: 1.14-6.2 cm), and DDVDm was reconstructed with =0 and =10 images. Dataset-3 consisted of 28 HCCs (lesion diameter: 1.91-3.52 cm), and DDVDm was reconstructed with =0 and =2 images. For dataset-1 and dataset-2, a trained reader was required to make a diagnosis for a lesion solely based on DDVDm with 4 choices: (I) HG with confidence; (II) HG without confidence; (III) solid mass-forming lesion (MFL) with confidence; (IV) solid MFL without confidence. Then, three readers attempted to confirm whether DDVDm features summarized from dataset-1 and dataset-2 would be generalizable to dataset-3. For dataset-1 and dataset-2 together, the correct diagnosis was made by the trained reader in 90.9% (20/22) of the HGs (77.7% with confidence) and 96.4% (27/28) of the MFLs (85.7% with confidence). HG generally showed substantially higher DDVD signal relative to background liver parenchyma. Though not necessarily, HG DDVD signals could be similar to those of blood vessels. Some HGs showed DDVD signals high
ISSN:2223-4292
2223-4306
DOI:10.21037/qims-24-1837