Imaging of Colorectal Liver Metastasis

Baghdadi, Azarakhsh; Mirpour, Sahar; Ghadimi, Maryam; Motaghi, Mina; Hazhirkarzar, Bita; Pawlik, Timothy M.; Kamel, Ihab R.

doi:10.1007/s11605-021-05164-1

Cited by 15 publications

(13 citation statements)

References 72 publications

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“…GBCAs, with intravascular-interstitial distribution, are generally used with T1W sequences, with or without fat suppression techniques. Dynamic contrast enhanced acquisitions improve the identification and characterization of liver metastases depending on their enhancement behavior[ 10 ].…”

Section: Magnetic Resonance Protocolsmentioning

confidence: 99%

“…These GBCAs are taken up by hepatocytes and excreted in the biliary system and they are extremely valuable in follow-up after locoregional or systemic treatments. These molecules present a biphasic enhancement pattern; the first phase, immediately after intravenous injection, is similar to CT dynamic enhancement after iodine contrast injection while a delayed phase occurs after 10 to 120 min after injection[ 10 , 11 ]. Lesions not containing hepatocytes cannot take up such molecules; therefore, metastasis appear hypointense compared with surrounding healthy liver parenchyma[ 12 ].…”

Section: Magnetic Resonance Protocolsmentioning

confidence: 99%

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Liver metastases: The role of magnetic resonance imaging

Maino,

Vernuccio,

Cannella

et al. 2023

World J Gastroenterol

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The liver is one of the organs most commonly involved in metastatic disease, especially due to its unique vascularization. It’s well known that liver metastases represent the most common hepatic malignant tumors. From a practical point of view, it’s of utmost importance to evaluate the presence of liver metastases when staging oncologic patients, to select the best treatment possible, and finally to predict the overall prognosis. In the past few years, imaging techniques have gained a central role in identifying liver metastases, thanks to ultrasonography, contrast-enhanced computed tomography (CT), and magnetic resonance imaging (MRI). All these techniques, especially CT and MRI, can be considered the non-invasive reference standard techniques for the assessment of liver involvement by metastases. On the other hand, the liver can be affected by different focal lesions, sometimes benign, and sometimes malignant. On these bases, radiologists should face the differential diagnosis between benign and secondary lesions to correctly allocate patients to the best management. Considering the above-mentioned principles, it’s extremely important to underline and refresh the broad spectrum of liver metastases features that can occur in everyday clinical practice. This review aims to summarize the most common imaging features of liver metastases, with a special focus on typical and atypical appearance, by using MRI.

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Section: Magnetic Resonance Protocolsmentioning

confidence: 99%

Section: Magnetic Resonance Protocolsmentioning

confidence: 99%

Liver metastases: The role of magnetic resonance imaging

Maino,

Vernuccio,

Cannella

et al. 2023

World J Gastroenterol

View full text Add to dashboard Cite

show abstract

“…Due to the hepatic parenchyma hypointensity on T2 WI induced by increased iron reserves, CRLM can appear hyperintense, mimicking benign lesions, such as cysts and hemangiomas [57] with whom they also share diffusion restriction on DWI and hypointensity on the hepatobiliary phase [64]. Post-contrast sequences can be useful to differentiate those lesions, unveiling some hallmarks of secondary lesions' dynamic behavior such as rim enhancement on late arterial phase that persists in portal venous phase on T1 WI and ill-defined enhancement of the surrounding liver parenchyma [65].…”

Section: Metastasis (Increased Risk Of Colorectal Cancer)mentioning

confidence: 99%

MRI Appearance of Focal Lesions in Liver Iron Overload

et al. 2022

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Liver iron overload is defined as an accumulation of the chemical element Fe in the hepatic parenchyma that exceeds the normal storage. When iron accumulates, it can be toxic for the liver by producing inflammation and cell damage. This can potentially lead to cirrhosis and hepatocellular carcinoma, as well as to other liver lesions depending on the underlying condition associated to liver iron overload. The correct assessment of liver iron storage is pivotal to drive the best treatment and prevent complication. Nowadays, magnetic resonance imaging (MRI) is the best non-invasive modality to detect and quantify liver iron overload. However, due to its superparamagnetic properties, iron provides a natural source of contrast enhancement that can make challenging the differential diagnosis between different focal liver lesions (FLLs). To date, a fully comprehensive description of MRI features of liver lesions commonly found in iron-overloaded liver is lacking in the literature. Through an extensive review of the published literature, we aim to summarize the MRI signal intensity and enhancement pattern of the most common FLLs that can occur in liver iron overload.

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“…On the other hand, although various imaging modalities such as ultrasound (US), computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography/computed tomography (PET/CT) can be used for the diagnosis and evaluation of CRLM, CT is still the current method of choice for the diagnosis and treatment of CRLM ( 21 , 22 ). Previous studies have shown that the sensitivity and specificity of CT for the diagnosis of CRLM are 82.1% and 73.5%, respectively ( 23 ).…”

Section: Introductionmentioning

confidence: 99%

Dynamic radiomics for predicting the efficacy of antiangiogenic therapy in colorectal liver metastases

Zhai

Zhang

et al. 2023

Front. Oncol.

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Background and objectiveFor patients with advanced colorectal liver metastases (CRLMs) receiving first-line anti-angiogenic therapy, an accurate, rapid and noninvasive indicator is urgently needed to predict its efficacy. In previous studies, dynamic radiomics predicted more accurately than conventional radiomics. Therefore, it is necessary to establish a dynamic radiomics efficacy prediction model for antiangiogenic therapy to provide more accurate guidance for clinical diagnosis and treatment decisions.MethodsIn this study, we use dynamic radiomics feature extraction method that extracts static features using tomographic images of different sequences of the same patient and then quantifies them into new dynamic features for the prediction of treatmentefficacy. In this retrospective study, we collected 76 patients who were diagnosed with unresectable CRLM between June 2016 and June 2021 in the First Hospital of China Medical University. All patients received standard treatment regimen of bevacizumab combined with chemotherapy in the first-line treatment, and contrast-enhanced abdominal CT (CECT) scans were performed before treatment. Patients with multiple primary lesions as well as missing clinical or imaging information were excluded. Area Under Curve (AUC) and accuracy were used to evaluate model performance. Regions of interest (ROIs) were independently delineated by two radiologists to extract radiomics features. Three machine learning algorithms were used to construct two scores based on the best response and progression-free survival (PFS).ResultsFor the task that predict the best response patients will achieve after treatment, by using ROC curve analysis, it can be seen that the relative change rate (RCR) feature performed best among all features and best in linear discriminantanalysis (AUC: 0.945 and accuracy: 0.855). In terms of predicting PFS, the Kaplan–Meier plots suggested that the score constructed using the RCR features could significantly distinguish patients with good response from those with poor response (Two-sided P<0.0001 for survival analysis).ConclusionsThis study demonstrates that the application of dynamic radiomics features can better predict the efficacy of CRLM patients receiving antiangiogenic therapy compared with conventional radiomics features. It allows patients to have a more accurate assessment of the effect of medical treatment before receiving treatment, and this assessment method is noninvasive, rapid, and less expensive. Dynamic radiomics model provides stronger guidance for the selection of treatment options and precision medicine.

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Imaging of Colorectal Liver Metastasis

Cited by 15 publications

References 72 publications

Liver metastases: The role of magnetic resonance imaging

Liver metastases: The role of magnetic resonance imaging

MRI Appearance of Focal Lesions in Liver Iron Overload

Dynamic radiomics for predicting the efficacy of antiangiogenic therapy in colorectal liver metastases

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