State-of-the-art in radiomics of hepatocellular carcinoma: a review of basic principles, applications, and limitations

Santos, João Manoel Miranda Magalhães; Oliveira, Brunna Clemente; Araújo-Filho, José de Arimateia Batista; Assunção-Jr, Antonildes N; Machado, Felipe Augusto de M; Rocha, Camila Carlos Tavares; Horvat, João V.; Menezes, Marcos Roberto de; Horvat, Natally

doi:10.1007/s00261-019-02299-3

Cited by 46 publications

(28 citation statements)

References 48 publications

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“…Radiomics is well suited for oncology and is being evaluated for several indications including detection, diagnosis, assessment of prognosis and prediction of response to treatment. Results have been encouraging in several studies evaluating the use of radiomics in HCC, particularly for the pretreatment prediction of biological tumour characteristics, the risk of recurrence and survival …”

Section: What's New For Quantitative Imaging Of Liver Tumours?mentioning

confidence: 97%

Imaging of liver tumours: What’s new?

Vilgrain

Raynaud

Paulatto

et al. 2020

Liver International

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Liver tumours are very common and malignant tumours represent a major cause of cancer‐related death. Imaging plays an important role at many different stages of the care pathway. This review discusses new aspects and new roles for imaging and for MRI, in particular. MRI is already the best tool for the characterization and staging of benign and malignant liver tumours and it could also become a useful screening tool, especially for hepatocellular carcinoma. Liver imaging will be increasingly quantitative in the future, integrating new approaches such as those of artificial intelligence.

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Section: What's New For Quantitative Imaging Of Liver Tumours?mentioning

confidence: 97%

Imaging of liver tumours: What’s new?

Vilgrain

Raynaud

Paulatto

et al. 2020

Liver International

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“…Previous studies have evaluated the value of radiomics in adult liver cancer. The results were achieved, particularly in the preoperative prediction of pathological features and postoperative recurrence [8,9].…”

Section: Diagnosismentioning

confidence: 99%

Diagnosis and Treatment of Hepatoblastoma: An Update

Zhu¹,

Dong²,

Chen³

et al. 2021

Liver Pathology

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Hepatoblastoma is a rare but the most common solid tumor in children. The incidence is gradually increasing. The international collaboration among four centers in the world has greatly improved the prognosis of hepatoblastoma. They formed the Children's Hepatic Tumor International Collaboration (CHIC) to standardize the staging system (2017 PRETEXT system) and the risk factors for tumor stratification. Multimodal therapy has become the standard for the management of hepatoblastoma, including surgical resection, liver transplantation, chemotherapy, and so on. Surgery is the primary treatment of early stage hepatoblastoma. Threedimensional reconstruction is helpful for preoperative evaluation of large tumors, assisting extended hepatectomy for patients in PRETEXT III or IV. Neoadjuvant therapy is useful for reducing the tumor volume and increasing the resectability. Primary liver transplantation is recommended for advanced hepatoblastoma. The lungs are the most common metastatic organ, the treatment of which is critical for the patient's long-term survival. We reviewed the recent progress in the diagnosis and treatment of hepatoblastoma.

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“…Radiomics is based on the mathematical quantification of images heterogeneity, through the analysis of distribution and relationships of pixel intensities within a region of interest (ROI)[ 15 , 16 ]. Radiomics analysis requires a multistep process, starting from imaging acquisition, and including lesion segmentation, features extraction, features selection and reduction, predictive model building, and finally validation and clinical interpretation of the results[ 19 , 20 , 23 ].…”

Section: Workflow Of Radiomics Analysismentioning

confidence: 99%

“…The first order features are obtained from the analysis of the gray level histogram within a defined ROI, without considering spatial relations among pixels. Most common histogram-based features include mean (average of the pixels within the ROI), standard deviation (dispersion from the mean), skewness (asymmetric of the histogram), kurtosis (peakedness/flatness of the histogram), and entropy (image irregularity or complexity)[ 20 ]. The second order texture features consider the spatial relationship among pixels, and most commonly include grey level co-occurrence matrix (GLCM), that quantifies the arrangements of pairs of pixels with the same values in specific directions, and grey-level run length matrix (GLRLM), that quantifies consecutive pixels with the same intensity along specific directions.…”

Section: Workflow Of Radiomics Analysismentioning

confidence: 99%

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New advances in radiomics of gastrointestinal stromal tumors

Cannella¹,

Grutta²,

Midiri³

et al. 2020

WJG

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Gastrointestinal stromal tumors (GISTs) are uncommon neoplasms of the gastrointestinal tract with peculiar clinical, genetic, and imaging characteristics. Preoperative knowledge of risk stratification and mutational status is crucial to guide the appropriate patients’ treatment. Predicting the clinical behavior and biological aggressiveness of GISTs based on conventional computed tomography (CT) and magnetic resonance imaging (MRI) evaluation is challenging, unless the lesions have already metastasized at the time of diagnosis. Radiomics is emerging as a promising tool for the quantification of lesion heterogeneity on radiological images, extracting additional data that cannot be assessed by visual analysis. Radiomics applications have been explored for the differential diagnosis of GISTs from other gastrointestinal neoplasms, risk stratification and prediction of prognosis after surgical resection, and evaluation of mutational status in GISTs. The published researches on GISTs radiomics have obtained excellent performance of derived radiomics models on CT and MRI. However, lack of standardization and differences in study methodology challenge the application of radiomics in clinical practice. The purpose of this review is to describe the new advances of radiomics applied to CT and MRI for the evaluation of gastrointestinal stromal tumors, discuss the potential clinical applications that may impact patients’ management, report limitations of current radiomics studies, and future directions.

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State-of-the-art in radiomics of hepatocellular carcinoma: a review of basic principles, applications, and limitations

Cited by 46 publications

References 48 publications

Imaging of liver tumours: What’s new?

Imaging of liver tumours: What’s new?

Diagnosis and Treatment of Hepatoblastoma: An Update

New advances in radiomics of gastrointestinal stromal tumors

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