Value of ultrasound combined with MRI in the diagnosis of primary and recurrent hepatocellular carcinoma

Ji, Xiaoli; Zhou, Shisheng; Yang, Peng; Liu, Faqin; Li, Yan; Li, Hong

doi:10.3892/ol.2019.10945

“…Second, CEUS revealed precise and obvious washout of the nodule with its pure blood pool contrast agent, ruling out interstitial contrast agent leakage demonstrated on CT [14]. Third, repeated treatments may impair the liver and worsen cirrhosis, resulting in reduced enhancement of the lesion on CT/MRI [18,19].…”

Section: Discussionmentioning

confidence: 95%

Complementary Role of CEUS and CT/MR LI-RADS for Diagnosis of Recurrent HCC

Cheng,

Huang,

Ruan

et al. 2023

Cancers

2

0

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Purpose: We retrospectively compared the diagnostic performance of contrast-enhanced ultrasonography (CEUS) and contrast-enhanced computer tomography–magnetic resonance imaging (CT/MRI) for recurrent hepatocellular carcinoma (HCC) after curative treatment. Materials and methods: After curative treatment with 421 ultrasound (US) detected lesions, 303 HCC patients underwent both CEUS and CT/MRI. Each lesion was assigned a Liver Imaging Reporting and Data System (LI-RADS) category according to CEUS and CT/MRI LI-RADS. Receiver-operating characteristic (ROC) curves were computed to determine the optimal diagnosis algorithms for CEUS, CT and MRI. The diagnostic accuracy, sensitivity, specificity, and area under the curve (AUC) were compared between CEUS and CT/MRI. Results: Among the 421 lesions, 218 were diagnosed as recurrent HCC, whereas 203 lesions were diagnosed as benign. In recurrent HCC, CEUS detected more arterial hyperenhancement (APHE) and washout than CT and more APHE than MRI. CEUS yielded better diagnostic performance than CT (AUC: 0.981 vs. 0.958) (p = 0.024) comparable diagnostic performance to MRI (AUC: 0.952 vs. 0.933) (p > 0.05) when using their optimal diagnostic criteria. CEUS missed 12 recurrent HCCs, CT missed one, and MRI missed none. The detection rate of recurrent HCC on CEUS (94.8%, 218/230) was lower than that on CT/MRI (99.6%, 259/260) (p = 0.001). Lesions located on the US blind spots and visualization score C would hinder the ability of CEUS to detect recurrent HCC. Conclusion: CEUS demonstrated excellent diagnostic performance but an inferior detection rate for recurrent HCC. CEUS and CT/MRI played a complementary role in the detection and characterization of recurrent HCC.

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“…Thereby, tumors can be easily distinguished from nontumor nodules, but the degree of pathological differentiation of tumors cannot be accurately inferred. With the continuous development of functional MRI technology, it can not only reflect histological characteristics such as microcirculation state and cell density of tumors but also reflect cell metabolism and biochemical information of tumors [ 11 , 12 ]. This makes it possible to assess the pathological grading of PHC accurately using MRI.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Algorithm in Classification and Recognition of Primary Hepatic Carcinoma Images under Magnetic Resonance Imaging

He

¹

,

Huang

²

,

Liao

³

et al. 2022

Contrast Media & Molecular Imaging

3

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This study aimed to discuss the application value of the bias field correction algorithm in magnetic resonance imaging (MRI) images of patients with primary hepatic carcinoma (PHC). In total, 52 patients with PHC were selected as the experimental group and divided into three subgroups: mild (15 cases), moderate (19 cases), and severe (18 cases) according to pathological grading. Another 52 patients with hepatic nodules in the same period were included in the control group. All the patients underwent dynamic contrast-enhanced (DCE) MRI examination, and the image qualities of MRI before and after bias field correction were compared. The DCE-MRI perfusion parameters were measured, including the transport constant Ktrans, reverse rate constant Kep, extravascular extracellular volume fraction (Ve), plasma volume (Vp), microvascular density (MVD), hepatic artery perfusion index (HPI), mean transit time of contrast agent (MTT), time to peak (TTP), blood volume (BV), hepatic arterial perfusion (HAP), full perfusion (FP), and portal venous perfusion (PVP). It was found that the sensitivity (93.63%), specificity (71.62%), positive predictive value (95.63%), negative predictive value (71.62%), and accuracy (90.01%) of MRI examination processed by the bias field correction algorithm were all significantly greater than those before processing P < 0.05 . The Ktrans, Kep, Ve, Vp, and MVD of patients in the experimental group were significantly larger than those of the control group, and severe group> moderate group> mild group P < 0.05 . HPI, MTT, TTP, BV, and HAP of patients in the experimental group were also significantly greater than those of the control group, which was shown as severe group > moderate group > mild group P < 0.05 . FP and PVP of the experimental group were significantly lower than those of the control group, and severe group < moderate group < mild group P < 0.05 . It was suggested that in MRI images of patients with PHC, the bias field correction algorithm could significantly improve the diagnosis rate. Each perfusion parameter was related to the pathological grading, which could be used to evaluate the prognosis of patients.

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Nanoparticles and their application in the diagnosis of hepatocellular carcinoma

Li,

Cao,

Zhang

et al. 2024

Nanotechnology Reviews

0

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Most patients are at advanced stages when they are diagnosed with hepatocellular carcinoma, leading to poor prognosis and a low 5-year survival rate. Serological markers, ultrasound, computed tomography, magnetic resonance imaging, positron emission tomography, and liver biopsy are the common clinical diagnostic techniques for liver cancer. Effective interventions in the early stage will be beneficial to improve the prognosis of liver cancer patients and reduce the global burden. Therefore, it is urgent to develop new diagnostic methods to improve the diagnosis and management of liver cancer. Nanotechnology has become a new frontier subject in medical detection along with the application of nanomaterials in the manufacture of drug carriers, diagnostic tools, and therapeutic devices. Many studies have shown that nanoparticles (NPs) can be applied to the clinical diagnosis of liver cancer in combination with existing technologies, providing a new method for the early diagnosis of liver cancer. In this review, we elaborate on the theoretical basis and characteristics of NPs in the diagnosis of liver cancer, and the research progress and prospects of NPs in the diagnosis of liver cancer are summarized.

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Value of ultrasound combined with MRI in the diagnosis of primary and recurrent hepatocellular carcinoma

Cited by 3 publications

References 25 publications

Complementary Role of CEUS and CT/MR LI-RADS for Diagnosis of Recurrent HCC

Complementary Role of CEUS and CT/MR LI-RADS for Diagnosis of Recurrent HCC

Artificial Intelligence Algorithm in Classification and Recognition of Primary Hepatic Carcinoma Images under Magnetic Resonance Imaging

Nanoparticles and their application in the diagnosis of hepatocellular carcinoma

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