Computed tomography (CT), magnetic resonance imaging (MRI), and 18-fluorideoxyglucose positron emission tomography (¹⁸FDG-PET) are historically the most accurate imaging techniques for diagnosing liver metastases. Recently, the combination of diffusion-weighted imaging and hepatospecific contrast media, such as gadoxetic acid in MRI, have been demonstrated to have the highest diagnostic accuracy, sensitivity, and specificity for detecting liver metastases. Various recent meta-analyses have confirmed the diagnostic superiority of this combination (diffusion-weighted imaging and gadoxetic acid-enhanced MRI), especially in terms of per lesion sensitivity, as compared with CT and ¹⁸FDG-PET, even for smaller lesions (≤1 cm). However, none of the oncological guidelines have suggested the use of MRI as a first-line technique for liver metastasis detection during the staging process of oncological patients. This review analyzes the history of the principal imaging techniques for the diagnosis of liver metastases, in particular of colorectal liver metastases, focusing on the most accurate method (diffusion-weighted imaging combined with gadoxetic acid-enhanced MRI), possible reasons for the lack of its diffusion in the guidelines, and possible future scenarios.

Purpose: To compare different commercial software in the quantification of Pneumonia Lesions in COVID-19 infection and to stratify the patients based on the disease severity using on chest computed tomography (CT) images. Materials and methods: We retrospectively examined 162 patients with confirmed COVID-19 infection by reverse transcriptase-polymerase chain reaction (RT-PCR) test. All cases were evaluated separately by radiologists (visually) and by using three computer software programs: (1) Thoracic VCAR software, GE Healthcare, United States; (2) Myrian, Intrasense, France; (3) InferRead, InferVision Europe, Wiesbaden, Germany. The degree of lesions was visually scored by the radiologist using a score on 5 levels (none, mild, moderate, severe, and critic). The parameters obtained using the computer tools included healthy residual lung parenchyma, ground-glass opacity area, and consolidation volume. Intraclass coefficient (ICC), Spearman correlation analysis, and non-parametric tests were performed. Results: Thoracic VCAR software was not able to perform volumes segmentation in 26/162 (16.0%) cases, Myrian software in 12/162 (7.4%) patients while InferRead software in 61/162 (37.7%) patients. A great variability (ICC ranged for 0.17 to 0.51) was detected among the quantitative measurements of the residual healthy lung parenchyma volume, GGO, and consolidations volumes calculated by different computer tools. The overall radiological severity score was moderately correlated with the residual healthy lung parenchyma volume obtained by ThoracicVCAR or Myrian software, with the GGO area obtained by the ThoracicVCAR tool and with consolidation volume obtained by Myrian software. Quantified volumes by InferRead software had a low correlation with the overall radiological severity score. Conclusions: Computer-aided pneumonia quantification could be an easy and feasible way to stratify COVID-19 cases according to severity; however, a great variability among quantitative measurements provided by computer tools should be considered.

Gastric cancer (GC) is a common cancer worldwide. Its incidence and mortality vary depending on geographic area, with the highest rates in Asian countries, particularly in China, Japan, and South Korea. Accurate imaging staging has become crucial for the application of various treatment strategies, especially for curative treatments in early stages. Unfortunately, most GCs are still diagnosed at an advanced stage, with the peritoneum (61–80%), distant lymph nodes (44–50%), and liver (26–38%) as the most common metastatic locations. Metastatic disease is limited to the peritoneum in 58% of cases; in nonperitoneal distant metastases, the most involved GC metastasization site is the liver (82%). The eighth edition of the tumor-node-metastasis staging system is the most commonly used system for determining GC prognosis. Endoscopic ultrasonography, computed tomography, and 18-fluorideoxyglucose positron emission tomography are historically the most accurate imaging techniques for GC staging. However, studies have recently shown renewed interest in magnetic resonance imaging (MRI) as a useful tool in GC staging, especially for distant metastasis assessment. The technical improvement of diffusion-weighted imaging and the increasing use of hepatobiliary contrast agents have been shown to increase the diagnostic performance of MRI, particularly for detecting peritoneal and liver metastasis. However, no principal oncological guidelines have included the use of MRI as a first-line technique for distant metastasis evaluation during the GC staging process, such as the National Comprehensive Cancer Network Guidelines. This review analyzed the role of the principal imaging techniques in GC diagnosis and staging, focusing on the potential role of MRI, especially for assessing peritoneal and liver metastases.

Imaging still has a limited capacity to detect microvascular invasion (mVI). The objective of this critical review is the evaluation of the most significant predictors of mVI in hepatocellular carcinoma (HCC) detectable by computed tomography, PET/computed tomography and MRI using a mathematical model. We systematically reviewed 15 observational studies from 2008 to 2018 to analyze factors with most impact on mVI detection. The most significant predictors of mVI correlating with imaging techniques were considered. From 1902 patients considered, we individuated 30 total predictors of mVI in a multivariate analysis. The most frequent predictors related to the highest presence with mVI in HCC were: α-fetoprotein (p < 0.0001), tumor size (p < 0.0001) and number of HCC nodules (p = 0.0020).

Preoperative staging represents a crucial point for the management, type of surgery, and candidacy for neoadjuvant therapy in patient with rectal cancer. The most recent clinical guidelines in oncology recommend an accurate preoperative evaluation in order to address early and advanced tumors to different therapeutic options. In particular, potential pitfalls may occur in the assessment of T3 tumors, which represents the most common stage at diagnosis. The depth of tumor invasion is known to be an important prognostic factor in rectal carcinoma; as a consequence, the T3 imaging classification has a substantial importance for treatment strategy and patient survival. However, the differentiation between tumor invasion of perirectal fat and mesorectal desmoplastic reactions remains a main goal for radiologists. Magnetic resonance imaging (MRI) is actually considered as the best imaging modality for rectal cancer staging. Although the endorectal ultrasound (ERUS) is the preferred staging method for early tumors, it could also be useful in identifying perirectal fat invasion. Moreover, the addiction of diffusion weighted imaging (DWI) improves the diagnostic performance of MRI in rectal cancer staging by adding functional information about rectal tumor and adjacent mesorectal tissues. This study investigated the diagnostic performance of conventional MRI alone, in combination with the DWI technique and ERUS in order to assess the best diagnostic imaging combination for rectal cancer staging.

Hepatocellular adenoma (HCA) is a rare benign liver tumour associated with the use of oral contraceptives or other steroid medications which occurs predominantly in young and middle-aged women. Unlike other benign liver tumours, an HCA may be complicated by bleeding and malignant transformation. HCAs have been divided into four subtypes based on molecular and pathological features: hepatocyte nuclear factor 1α-mutated HCA, inflammatory HCA, β-catenin-mutated HCA, and unclassified HCA. β-catenin-mutated HCA has the highest risk of haemorrhage or malignant transformation. In the latest upgrade of the guidelines regarding the management of benign liver tumours published in 2016 by the European Association for the Study of the Liver, magnetic resonance imaging (MRI) was recognized to be superior to all other imaging modalities in detecting HCAs and in being able to subtype HCAs up to 80%, with positive identification of 1α-mutated HCA or inflammatory HCA achievable with > 90% specificity. This review analyzed the imaging features of HCA using MRI with hepato-specific contrast agents, focusing on the limitations in the HCA characterization.