Diagnostic performance of gadoxetic acid-enhanced liver MRI versus multidetector CT in the assessment of colorectal liver metastases compared to hepatic resection

Intra-patient and inter-observer image quality analysis in liver MRI study with gadoxetic acid using two different multi-arterial phase techniques

PURPOSE

To evaluate intra-patient and interobserver agreement in patients who underwent liver MRI with gadoxetic acid using two different multi-arterial phase (AP) techniques.

METHODS

A total of 154 prospectively enrolled patients underwent clinical gadoxetic acid-enhanced liver MRI twice within 12 months, using two different multi-arterial algorithms: CAIPIRINHA-VIBE and TWIST-VIBE. For every patient, breath-holding time, body mass index, sex, age were recorded. The phase without contrast media and the APs were independently evaluated by two radiologists who quantified Gibbs artefacts, noise, respiratory motion artefacts, and general image quality. Presence or absence of Gibbs artefacts and noise was compared by the McNemar's test. Respiratory motion artefacts and image quality scores were compared using Wilcoxon signed rank test. Interobserver agreement was assessed by Cohen kappa statistics.

RESULTS

Compared with TWIST-VIBE, CAIPIRINHA-VIBE images had better scores for every parameter except higher noise score. Triple APs were always acquired with TWIST-VIBE but failed in 37% using CAIPIRINHA-VIBE: 11% have only one AP, 26% have two. Breath-holding time was the only parameter that influenced the success of multi-arterial techniques. TWIST-VIBE images had worst score for Gibbs and respiratory motion artefacts but lower noise score.

CONCLUSION

CAIPIRINHA-VIBE images were always diagnostic, but with a failure of triple-AP in 37%. TWIST-VIBE was successful in obtaining three APs in all patients. Breath-holding time is the only parameter which can influence the preliminary choice between CAIPIRINHA-VIBE and TWIST-VIBE algorithm.

ADVANCES IN KNOWLEDGE

If the patient is expected to perform good breath-holds, TWIST-VIBE is preferable; otherwise, CAIPIRINHA-VIBE is more appropriate.

Machine learning-based radiomics analysis in predicting RAS mutational status using magnetic resonance imaging

PURPOSE

To assess the efficacy of radiomics features, obtained by magnetic resonance imaging (MRI) with hepatospecific contrast agent, in pre-surgical setting, to predict RAS mutational status in liver metastases.

METHODS

Patients with MRI in pre-surgical setting were enrolled in a retrospective study. Manual segmentation was made by means 3D Slicer image computing, and 851 radiomics features were extracted as median values using the PyRadiomics Python package. The features were extracted considering the agreement with the Imaging Biomarker Standardization Initiative (IBSI). Balancing was performed through synthesis of samples for the underrepresented classes using the self-adaptive synthetic oversampling (SASYNO) approach. Inter- and intraclass correlation coefficients (ICC) were calculated to assess the between-observer and within-observer reproducibility of all radiomics characteristics. For continuous variables, nonparametric Wilcoxon-Mann-Whitney test was utilized. Benjamini and Hochberg's false discovery rate (FDR) adjustment for multiple testing was used. Receiver operating characteristics (ROC) analysis with the calculation of area under the ROC curve (AUC), sensitivity (SENS), specificity (SPEC), positive predictive value (PPV), negative predictive value (NPV) and accuracy (ACC) were assessed for each parameter. Linear and non-logistic regression model (LRM and NLRM) and different machine learning-based classifiers including decision tree (DT), k-nearest neighbor (KNN) and support vector machine (SVM) were considered. Moreover, features selection were performed before and after a normalized procedure using two different methods (3-sigma and z-score). McNemar test was used to assess differences statistically significant between dichotomic tables. All statistical procedures were done using MATLAB R2021b Statistics and Machine Toolbox (MathWorks, Natick, MA, USA).

RESULTS

Seven normalized radiomics features, extracted from arterial phase, 11 normalized radiomics features, from portal phase, 12 normalized radiomics features from hepatobiliary phase and 12 normalized features from T2-W SPACE sequence were robust predictors of RAS mutational status. The multivariate analysis increased significantly the accuracy in RAS prediction when a LRM was used, combining 12 robust normalized features extracted by VIBE hepatobiliary phase reaching an accuracy of 99%, a sensitivity 97%, a specificity of 100%, a PPV of 100% and a NPV of 98%. No statistically significant increase was obtained, considering the tested classifiers DT, KNN and SVM, both without normalization and with normalization methods.

CONCLUSIONS

Normalized approach in MRI radiomics analysis allows to predict RAS mutational status.

Scientific Status Quo of Small Renal Lesions: Diagnostic Assessment and Radiomics

Background: Small renal masses (SRMs) are defined as contrast-enhanced renal lesions less than or equal to 4 cm in maximal diameter, which can be compatible with stage T1a renal cell carcinomas (RCCs). Currently, 50-61% of all renal tumors are found incidentally. Methods: The characteristics of the lesion influence the choice of the type of management, which include several methods SRM of management, including nephrectomy, partial nephrectomy, ablation, observation, and also stereotactic body radiotherapy. Typical imaging methods available for differentiating benign from malignant renal lesions include ultrasound (US), contrast-enhanced ultrasound (CEUS), computed tomography (CT), and magnetic resonance imaging (MRI). Results: Although ultrasound is the first imaging technique used to detect small renal lesions, it has several limitations. CT is the main and most widely used imaging technique for SRM characterization. The main advantages of MRI compared to CT are the better contrast resolution and tissue characterization, the use of functional imaging sequences, the possibility of performing the examination in patients allergic to iodine-containing contrast medium, and the absence of exposure to ionizing radiation. For a correct evaluation during imaging follow-up, it is necessary to use a reliable method for the assessment of renal lesions, represented by the Bosniak classification system. This classification was initially developed based on contrast-enhanced CT imaging findings, and the 2019 revision proposed the inclusion of MRI features; however, the latest classification has not yet received widespread validation. Conclusions: The use of radiomics in the evaluation of renal masses is an emerging and increasingly central field with several applications such as characterizing renal masses, distinguishing RCC subtypes, monitoring response to targeted therapeutic agents, and prognosis in a metastatic context.

Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment

OBJECTIVE

The aim of this study was the evaluation radiomics analysis efficacy performed using computed tomography (CT) and magnetic resonance imaging in the prediction of colorectal liver metastases patterns linked to patient prognosis: tumor growth front; grade; tumor budding; mucinous type. Moreover, the prediction of liver recurrence was also evaluated.

METHODS

The retrospective study included an internal and validation dataset; the first was composed by 119 liver metastases from 49 patients while the second consisted to 28 patients with single lesion. Radiomic features were extracted using PyRadiomics. Univariate and multivariate approaches including machine learning algorithms were employed.

RESULTS

The best predictor to identify tumor growth was the Wavelet_HLH_glcm_MaximumProbability with an accuracy of 84% and to detect recurrence the best predictor was wavelet_HLH_ngtdm_Complexity with an accuracy of 90%, both extracted by T1-weigthed arterial phase sequence. The best predictor to detect tumor budding was the wavelet_LLH_glcm_Imc1 with an accuracy of 88% and to identify mucinous type was wavelet_LLH_glcm_JointEntropy with an accuracy of 92%, both calculated on T2-weigthed sequence. An increase statistically significant of accuracy (90%) was obtained using a linear weighted combination of 15 predictors extracted by T2-weigthed images to detect tumor front growth. An increase statistically significant of accuracy at 93% was obtained using a linear weighted combination of 11 predictors by the T1-weigthed arterial phase sequence to classify tumor budding. An increase statistically significant of accuracy at 97% was obtained using a linear weighted combination of 16 predictors extracted on CT to detect recurrence. An increase statistically significant of accuracy was obtained in the tumor budding identification considering a K-nearest neighbors and the 11 significant features extracted T1-weigthed arterial phase sequence.

CONCLUSIONS

The results confirmed the Radiomics capacity to recognize clinical and histopathological prognostic features that should influence the choice of treatments in colorectal liver metastases patients to obtain a more personalized therapy.

Radiomics and artificial intelligence analysis by T2-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging to predict Breast Cancer Histological Outcome

OBJECTIVE

The objective of the study was to evaluate the accuracy of radiomics features obtained by MR images to predict Breast Cancer Histological Outcome.

METHODS

A total of 217 patients with malignant lesions were analysed underwent MRI examinations. Considering histological findings as the ground truth, four different types of findings were used in both univariate and multivariate analyses: (1) G1 + G2 vs G3 classification; (2) presence of human epidermal growth factor receptor 2 (HER2 + vs HER2 -); (3) presence of the hormone receptor (HR + vs HR -); and (4) presence of luminal subtypes of breast cancer.

RESULTS

The best accuracy for discriminating HER2 + versus HER2 - breast cancers was obtained considering nine predictors by early phase T1-weighted subtraction images and a decision tree (accuracy of 88% on validation set). The best accuracy for discriminating HR + versus HR - breast cancers was obtained considering nine predictors by T2-weighted subtraction images and a decision tree (accuracy of 90% on validation set). The best accuracy for discriminating G1 + G2 versus G3 breast cancers was obtained considering 16 predictors by early phase T1-weighted subtraction images in a linear regression model with an accuracy of 75%. The best accuracy for discriminating luminal versus non-luminal breast cancers was obtained considering 27 predictors by early phase T1-weighted subtraction images and a decision tree (accuracy of 94% on validation set).

CONCLUSIONS

The combination of radiomics analysis and artificial intelligence techniques could be used to support physician decision-making in prediction of Breast Cancer Histological Outcome.

Colorectal liver metastases patients prognostic assessment: prospects and limits of radiomics and radiogenomics

In this narrative review, we reported un up-to-date on the role of radiomics to assess prognostic features, which can impact on the liver metastases patient treatment choice. In the liver metastases patients, the possibility to assess mutational status (RAS or MSI), the tumor growth pattern and the histological subtype (NOS or mucinous) allows a better treatment selection to avoid unnecessary therapies. However, today, the detection of these features require an invasive approach. Recently, radiomics analysis application has improved rapidly, with a consequent growing interest in the oncological field. Radiomics analysis allows the textural characteristics assessment, which are correlated to biological data. This approach is captivating since it should allow to extract biological data from the radiological images, without invasive approach, so that to reduce costs and time, avoiding any risk for the patients. Several studies showed the ability of Radiomics to identify mutational status, tumor growth pattern and histological type in colorectal liver metastases. Although, radiomics analysis in a non-invasive and repeatable way, however features as the poor standardization and generalization of clinical studies results limit the translation of this analysis into clinical practice. Clear limits are data-quality control, reproducibility, repeatability, generalizability of results, and issues related to model overfitting.

Dose Reduction Strategies for Pregnant Women in Emergency Settings

In modern clinical practice, there is an increasing dependence on imaging techniques in several settings, and especially during emergencies. Consequently, there has been an increase in the frequency of imaging examinations and thus also an increased risk of radiation exposure. In this context, a critical phase is a woman's pregnancy management that requires a proper diagnostic assessment to reduce radiation risk to the fetus and mother. The risk is greatest during the first phases of pregnancy at the time of organogenesis. Therefore, the principles of radiation protection should guide the multidisciplinary team. Although diagnostic tools that do not employ ionizing radiation, such as ultrasound (US) and magnetic resonance imaging (MRI) should be preferred, in several settings as polytrauma, computed tomography (CT) nonetheless remains the examination to perform, beyond the fetus risk. In addition, protocol optimization, using dose-limiting protocols and avoiding multiple acquisitions, is a critical point that makes it possible to reduce risks. The purpose of this review is to provide a critical evaluation of emergency conditions, e.g., abdominal pain and trauma, considering the different diagnostic tools that should be used as study protocols in order to control the dose to the pregnant woman and fetus.

Post-Surgical Imaging Assessment in Rectal Cancer: Normal Findings and Complications

Rectal cancer (RC) is one of the deadliest malignancies worldwide. Surgery is the most common treatment for RC, performed in 63.2% of patients. The type of surgical approach chosen aims to achieve maximum residual function with the lowest risk of recurrence. The selection is made by a multidisciplinary team that assesses the characteristics of the patient and the tumor. Total mesorectal excision (TME), including both low anterior resection (LAR) and abdominoperineal resection (APR), is still the standard of care for RC. Radical surgery is burdened by a 31% rate of major complications (Clavien-Dindo grade 3-4), such as anastomotic leaks and a risk of a permanent stoma. In recent years, less-invasive techniques, such as local excision, have been tested. These additional procedures could mitigate the morbidity of rectal resection, while providing acceptable oncologic results. The "watch and wait" approach is not a globally accepted model of care but encouraging results on selected groups of patients make it a promising strategy. In this plethora of treatments, the radiologist is called upon to distinguish a physiological from a pathological postoperative finding. The aim of this narrative review is to identify the main post-surgical complications and the most effective imaging techniques.

Risk Assessment and Cholangiocarcinoma: Diagnostic Management and Artificial Intelligence

Intrahepatic cholangiocarcinoma (iCCA) is the second most common primary liver tumor, with a median survival of only 13 months. Surgical resection remains the only curative therapy; however, at first detection, only one-third of patients are at an early enough stage for this approach to be effective, thus rendering early diagnosis as an efficient approach to improving survival. Therefore, the identification of higher-risk patients, whose risk is correlated with genetic and pre-cancerous conditions, and the employment of non-invasive-screening modalities would be appropriate. For several at-risk patients, such as those suffering from primary sclerosing cholangitis or fibropolycystic liver disease, the use of periodic (6-12 months) imaging of the liver by ultrasound (US), magnetic Resonance Imaging (MRI)/cholangiopancreatography (MRCP), or computed tomography (CT) in association with serum CA19-9 measurement has been proposed. For liver cirrhosis patients, it has been proposed that at-risk iCCA patients are monitored in a similar fashion to at-risk HCC patients. The possibility of using Artificial Intelligence models to evaluate higher-risk patients could favor the diagnosis of these entities, although more data are needed to support the practical utility of these applications in the field of screening. For these reasons, it would be appropriate to develop screening programs in the research protocols setting. In fact, the success of these programs reauires patient compliance and multidisciplinary cooperation.

Diagnostic Management of Gastroenteropancreatic Neuroendocrine Neoplasms: Technique Optimization and Tips and Tricks for Radiologists

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) comprise a heterogeneous group of neoplasms, which derive from cells of the diffuse neuroendocrine system that specializes in producing hormones and neuropeptides and arise in most cases sporadically and, to a lesser extent, in the context of complex genetic syndromes. Furthermore, they are primarily nonfunctioning, while, in the case of insulinomas, gastrinomas, glucagonomas, vipomas, and somatostatinomas, they produce hormones responsible for clinical syndromes. The GEP-NEN tumor grade and cell differentiation may result in different clinical behaviors and prognoses, with grade one (G1) and grade two (G2) neuroendocrine tumors showing a more favorable outcome than grade three (G3) NET and neuroendocrine carcinoma. Two critical issues should be considered in the NEN diagnostic workup: first, the need to identify the presence of the tumor, and, second, to define the primary site and evaluate regional and distant metastases. Indeed, the primary site, stage, grade, and function are prognostic factors that the radiologist should evaluate to guide prognosis and management. The correct diagnostic management of the patient includes a combination of morphological and functional evaluations. Concerning morphological evaluations, according to the consensus guidelines of the European Neuroendocrine Tumor Society (ENETS), computed tomography (CT) with a contrast medium is recommended. Contrast-enhanced magnetic resonance imaging (MRI), including diffusion-weighted imaging (DWI), is usually indicated for use to evaluate the liver, pancreas, brain, and bones. Ultrasonography (US) is often helpful in the initial diagnosis of liver metastases, and contrast-enhanced ultrasound (CEUS) can solve problems in characterizing the liver, as this tool can guide the biopsy of liver lesions. In addition, intraoperative ultrasound is an effective tool during surgical procedures. Positron emission tomography (PET-CT) with FDG for nonfunctioning lesions and somatostatin analogs for functional lesions are very useful for identifying and evaluating metabolic receptors. The detection of heterogeneity in somatostatin receptor (SSTR) expression is also crucial for treatment decision making. In this narrative review, we have described the role of morphological and functional imaging tools in the assessment of GEP-NENs according to current major guidelines.

Immunotherapy Assessment: A New Paradigm for Radiologists

Immunotherapy denotes an exemplar change in an oncological setting. Despite the effective application of these treatments across a broad range of tumors, only a minority of patients have beneficial effects. The efficacy of immunotherapy is affected by several factors, including human immunity, which is strongly correlated to genetic features, such as intra-tumor heterogeneity. Classic imaging assessment, based on computed tomography (CT) or magnetic resonance imaging (MRI), which is useful for conventional treatments, has a limited role in immunotherapy. The reason is due to different patterns of response and/or progression during this kind of treatment which differs from those seen during other treatments, such as the possibility to assess the wide spectrum of immunotherapy-correlated toxic effects (ir-AEs) as soon as possible. In addition, considering the unusual response patterns, the limits of conventional response criteria and the necessity of using related immune-response criteria are clear. Radiomics analysis is a recent field of great interest in a radiological setting and recently it has grown the idea that we could identify patients who will be fit for this treatment or who will develop ir-AEs.

Disappearing colorectal liver metastases in the era of state-of-the-art triple-modality diagnostic imaging

INTRODUCTION

Systemic therapy can result in disappearance of colorectal liver metastases in up to 40% of patients. This might be an overestimation caused by suboptimal imaging modalities. The aim of this study was to investigate the use of imaging modalities and the incidence, management and outcome of patients with disappearing liver metastases (DLMs).

METHODS

This was a retrospective study of consecutive patients treated for colorectal liver metastases at a high volume hepatobiliary centre between January 2013 and January 2015 after receiving induction or neoadjuvant systemic therapy. Main outcomes were use of imaging modalities, incidence, management and longterm outcome of patients with DLMs.

RESULTS

Of 158 patients included, 32 (20%) had 110 DLMs. Most patients (88%) had initial diagnostic imaging with contrast enhanced-CT, primovist-MR and FDG-PET and 94% of patients with DLMs were restaged using primovist-MR. Patients with DLMs had significantly smaller metastases and the median initial size of DLMs was 10 mm (range 5-61). In the per lesion analysis, recurrence after "watch & wait" for DLMs occurred in 36%, while in 19 of 20 resected DLMs no viable tumour cells were found. Median overall (51 vs. 28 months, p < 0.05) and progression free survival (10 vs. 3 months, p = 0.003) were significantly longer for patients with DLMs.

CONCLUSION

Even state-of-the-art imaging and restaging cannot solve problems associated with DLMs. Regrowth of these lesions occurs in approximately a third of the lesions. Patients with DLMs have better survival.

Imaging Features of Main Hepatic Resections: The Radiologist Challenging

Liver resection is still the most effective treatment of primary liver malignancies, including hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), and of metastatic disease, such as colorectal liver metastases. The type of liver resection (anatomic versus non anatomic resection) depends on different features, mainly on the type of malignancy (primary liver neoplasm versus metastatic lesion), size of tumor, its relation with blood and biliary vessels, and the volume of future liver remnant (FLT). Imaging plays a critical role in postoperative assessment, offering the possibility to recognize normal postoperative findings and potential complications. Ultrasonography (US) is the first-line diagnostic tool to use in post-surgical phase. However, computed tomography (CT), due to its comprehensive assessment, allows for a more accurate evaluation and more normal findings than the possible postoperative complications. Magnetic resonance imaging (MRI) with cholangiopancreatography (MRCP) and/or hepatospecific contrast agents remains the best tool for bile duct injuries diagnosis and for ischemic cholangitis evaluation. Consequently, radiologists should be familiar with the surgical approaches for a better comprehension of normal postoperative findings and of postoperative complications.

Risk Assessment and Pancreatic Cancer: Diagnostic Management and Artificial Intelligence

Pancreatic cancer (PC) is one of the deadliest cancers, and it is responsible for a number of deaths almost equal to its incidence. The high mortality rate is correlated with several explanations; the main one is the late disease stage at which the majority of patients are diagnosed. Since surgical resection has been recognised as the only curative treatment, a PC diagnosis at the initial stage is believed the main tool to improve survival. Therefore, patient stratification according to familial and genetic risk and the creation of screening protocol by using minimally invasive diagnostic tools would be appropriate. Pancreatic cystic neoplasms (PCNs) are subsets of lesions which deserve special management to avoid overtreatment. The current PC screening programs are based on the annual employment of magnetic resonance imaging with cholangiopancreatography sequences (MR/MRCP) and/or endoscopic ultrasonography (EUS). For patients unfit for MRI, computed tomography (CT) could be proposed, although CT results in lower detection rates, compared to MRI, for small lesions. The actual major limit is the incapacity to detect and characterize the pancreatic intraepithelial neoplasia (PanIN) by EUS and MR/MRCP. The possibility of utilizing artificial intelligence models to evaluate higher-risk patients could favour the diagnosis of these entities, although more data are needed to support the real utility of these applications in the field of screening. For these motives, it would be appropriate to realize screening programs in research settings.

The role of [99mTc]Tc-HFAPi SPECT/CT in patients with malignancies of digestive system: first clinical experience

BACKGROUND

Recently, PET/CT imaging with radiolabelled FAP inhibitors (FAPIs) has been widely evaluated in diverse diseases. However, rare report has been published using SPECT/CT, a more available imaging method, with [^99mTc]Tc-labelled FAPI. In this study, we evaluated the potential effect of [^99mTc]Tc-HFAPi in clinical analysis for digestive system tumours.

METHODS

This is a single-centre prospective diagnostic efficiency study (Ethic approved No.: XJTU1AF2021LSK-021 of the First Affiliated Hospital of Xi'an Jiaotong University and ChiCTR2100048093 of the Chinese Clinical Trial Register). Forty patients with suspected or confirmed digestive system tumours underwent [^99mTc]Tc-HFAPi SPECT/CT between January and June 2021. For dynamic biodistribution and dosimetry estimation, whole-body planar scintigraphy was performed at 10, 30, 90, 150, and 240 min post-injection in four representative patients. Optimal acquisition time was considered in all the patients at 60-90 min post-injection, then quantified or semi-quantified using SUV_max and T/B ratio was done. The diagnostic performance of [^99mTc]Tc-HFAPi was calculated and compared with those of contrast-enhanced CT (ceCT) using McNemar test, and the changes of tumour stage and oncologic management were recorded.

RESULTS

Physiological distribution of [^99mTc]Tc-HFAPi was observed in the liver, pancreas, gallbladder, and to a lesser extent in the kidneys, spleen and thyroid. Totally, 40 patients with 115 lesions were analysed. The diagnostic sensitivity of [^99mTc]Tc-HFAPi for non-operative primary lesions was similar to that of ceCT (94.29% [33/35] vs 100% [35/35], respectively; P = 0.5); in local relapse detection, [^99mTc]Tc-HFAPi was successfully detected in 100% (n = 3) of patients. In the diagnosis of suspected metastatic lesions, [^99mTc]Tc-HFAPi exhibited higher sensitivity (89.66% [26/29] vs 68.97% [20/29], respectively, P = 0.03) and specificity (97.9% [47/48] vs 85.4% [41/48], respectively, P = 0.03) than ceCT, especially with 100% (24/24) specificity in the diagnosis of liver metastases, resulting in 20.0% (8/40) changes in TNM stage and 15.0% (6/40) changes in oncologic management.

CONCLUSION

[^99mTc]Tc-HFAPi demonstrates a greater diagnostic efficiency than ceCT in the detection of distant metastasis, especially in identifying liver metastases.

Prospective evaluation of 18F-FDG positron emission tomography in the preoperative staging of patients with hepatic colorectal metastases

Background

Despite considerable advances in preoperative imaging, up to one-third of patients operatively explored for hepatic colorectal metastases are unexpectedly found to harbor unresectable intrahepatic or extrahepatic disease.

Methods

The current study is a prospective, blinded study comparing utility of [¹⁸F]2-fluoro-2-deoxyglucose positron emission tomography (¹⁸F-FDG-PET) to computed tomography (CT) and CT arterial portography (CTAP) as preoperative staging.

Results

The 125 planned subjects were enrolled. Findings seen on FDG-PET alone changed therapy for 23 of 125 patients (18%). FDG-PET confirmed other radiologic findings in 16 cases (13%), for an overall influence on therapy in 39 cases (31%). FDG-PET was the most sensitive diagnostic imaging test for extrahepatic cancer; it was 80-90% sensitive for extrahepatic cancer and 70-90% specific. For the 28 cases of unresectable disease due to extrahepatic disease, FDG-PET findings solely changed therapies in 16 cases (57%) and influenced therapy in seven other cases (25%). Of the 21 unresectable cases due to extent of intrahepatic disease, FDG-PET did not solely change therapy in any. Overall, FDG-PET had the lowest sensitivity for hepatic sites compared with CT or CTAP. In particular, small (<1 cm) liver tumors were particularly poorly detected by FDG-PET. The area under the receiver operating characteristic (ROC) curve for small tumors was 0.58 and for patients on chemotherapy it was 0.66, a modest improvement over no imaging.

Conclusions

FDG-PET is an important test for preoperative staging of patients with hepatic colorectal metastases, affecting treatment decisions in nearly one-third of patients. The high yield is due mainly to detection of extrahepatic disease. It is therefore recommended in patients with extrahepatic lesions suspected to be disseminated cancer or those with high risk for extrahepatic disease. It is not a good test for identification of small tumors in the liver.

Multimodality Imaging Assessment of Desmoid Tumors: The Great Mime in the Era of Multidisciplinary Teams

Desmoid tumors (DTs), also known as desmoid fibromatosis or aggressive fibromatosis, are rare, locally invasive, non-metastatic soft tissue tumors. Although histological results represent the gold standard diagnosis, imaging represents the fundamental tool for the diagnosis of these tumors. Although histological analysis represents the gold standard for diagnosis, imaging represents the fundamental tool for the diagnosis of these tumors. DTs represent a challenge for the radiologist, being able to mimic different pathological conditions. A proper diagnosis is required to establish an adequate therapeutic approach. Multimodality imaging, including ultrasound (US), computed tomography (CT) and Magnetic Resonance Imaging (MRI), should be preferred. Different imaging techniques can also guide minimally invasive treatments and monitor their effectiveness. The purpose of this review is to describe the state-of-the-art multidisciplinary imaging of DTs; and its role in patient management.

A Narrative Review on LI-RADS Algorithm in Liver Tumors: Prospects and Pitfalls

Liver cancer is the sixth most detected tumor and the third leading cause of tumor death worldwide. Hepatocellular carcinoma (HCC) is the most common primary liver malignancy with specific risk factors and a targeted population. Imaging plays a major role in the management of HCC from screening to post-therapy follow-up. In order to optimize the diagnostic-therapeutic management and using a universal report, which allows more effective communication among the multidisciplinary team, several classification systems have been proposed over time, and LI-RADS is the most utilized. Currently, LI-RADS comprises four algorithms addressing screening and surveillance, diagnosis on computed tomography (CT)/magnetic resonance imaging (MRI), diagnosis on contrast-enhanced ultrasound (CEUS) and treatment response on CT/MRI. The algorithm allows guiding the radiologist through a stepwise process of assigning a category to a liver observation, recognizing both major and ancillary features. This process allows for characterizing liver lesions and assessing treatment. In this review, we highlighted both major and ancillary features that could define HCC. The distinctive dynamic vascular pattern of arterial hyperenhancement followed by washout in the portal-venous phase is the key hallmark of HCC, with a specificity value close to 100%. However, the sensitivity value of these combined criteria is inadequate. Recent evidence has proven that liver-specific contrast could be an important tool not only in increasing sensitivity but also in diagnosis as a major criterion. Although LI-RADS emerges as an essential instrument to support the management of liver tumors, still many improvements are needed to overcome the current limitations. In particular, features that may clearly distinguish HCC from cholangiocarcinoma (CCA) and combined HCC-CCA lesions and the assessment after locoregional radiation-based therapy are still fields of research.

Imaging Assessment of Interval Metastasis from Melanoma

Interval metastasis is a particular metastatic category of metastatic localizations in the lymph nodes in patients with melanoma. Interval nodes are generally located at nonregional lymphatic stations placed along the pathway of the spread of melanoma, such as the epitrochlear lymph node station, the popliteal fossa, and the retroareolar station. Imaging techniques for evaluation of patients with interval metastasis from melanoma diseases include ultrasound (US), computed tomography (CT), magnetic resonance imaging (MRI), lymphoscintigraphy (LS), and positron emission tomography (PET). A literature review was conducted through a methodical search on the Pubmed and Embase databases. The evaluation of lymph node metastases represents a critical phase in the staging and follow-up of melanoma patients. Therefore, a thorough knowledge of the imaging methods available and the interactions between the clinician and the radiologist are essential for making the correct choice for individual patients, for a better management, and to improve treatment and survival.

Diffusion weighted imaging and diffusion kurtosis imaging in abdominal oncological setting: why and when

This article provides an overview of diffusion kurtosis (DKI) imaging in abdominal oncology. DKI allows for more data on tissue structures than the conventional diffusion model (DWI). However, DKI requires high quality images at b-values greater than 1000 s/mm² and high signal-to-noise ratio (SNR) that traditionally MRI systems are not able to acquire and therefore there are generally amplified anatomical distortions on the images due to less homogeneity of the field. Advances in both hardware and software on modern MRI scanners have currently enabled ultra-high b-value imaging and offered the ability to apply DKI to multiple extracranial sites. Previous studies have evaluated the ability of DKI to characterize and discriminate tumor grade compared to conventional DWI. Additionally, in several studies the DKI sequences used were based on planar echo (EPI) acquisition, which is susceptible to motion, metal and air artefacts and prone to low SNRs and distortions, leading to low quality images for some small lesions, which may affect the accuracy of the results. Another problem is the optimal b-value of DKI, which remains to be explored and not yet standardized, as well as the manual selection of the ROI, which could affect the accuracy of some parameters.

Radiomics and machine learning analysis based on magnetic resonance imaging in the assessment of liver mucinous colorectal metastases

PURPOSE

The purpose of this study is to evaluate the Radiomics and Machine Learning Analysis based on MRI in the assessment of Liver Mucinous Colorectal Metastases.Query METHODS: The cohort of patients included a training set (121 cases) and an external validation set (30 cases) with colorectal liver metastases with pathological proof and MRI study enrolled in this approved study retrospectively. About 851 radiomics features were extracted as median values by means of the PyRadiomics tool on volume on interest segmented manually by two expert radiologists. Univariate analysis, linear regression modelling and pattern recognition methods were used as statistical and classification procedures.

RESULTS

The best results at univariate analysis were reached by the wavelet_LLH_glcm_JointEntropy extracted by T2W SPACE sequence with accuracy of 92%. Linear regression model increased the performance obtained respect to the univariate analysis. The best results were obtained by a linear regression model of 15 significant features extracted by the T2W SPACE sequence with accuracy of 94%, a sensitivity of 92% and a specificity of 95%. The best classifier among the tested pattern recognition approaches was k-nearest neighbours (KNN); however, KNN achieved lower precision than the best linear regression model.

CONCLUSIONS

Radiomics metrics allow the mucinous subtype lesion characterization, in order to obtain a more personalized approach. We demonstrated that the best performance was obtained by T2-W extracted textural metrics.

Imaging Features of Main Posthepatectomy Complications: A Radiologist’s Challenge

In the recent years, the number of liver resections has seen an impressive growth. Usually, hepatic resections remain the treatment of various liver diseases, such as malignant tumors, benign tumors, hydatid disease, and abscesses. Despite technical advancements and tremendous experience in the field of liver resection of specialized centers, there are moderately high rates of postoperative morbidity and mortality, especially in high-risk and older patient populations. Although ultrasonography is usually the first-line imaging examination for postoperative complications, Computed Tomography (CT) is the imaging tool of choice in emergency settings due to its capability to assess the whole body in a few seconds and detect all possible complications. Magnetic resonance cholangiopancreatography (MRCP) is the imaging modality of choice for delineating early postoperative bile duct injuries and ischemic cholangitis that may arise in the late postoperative phase. Moreover, both MDCT and MRCP can precisely detect tumor recurrence. Consequently, radiologists should have knowledge of these surgical procedures for better comprehension of postoperative changes and recognition of the radiological features of various postoperative complications.

ACR Appropriateness Criteria® Staging of Colorectal Cancer: 2021 Update

Preoperative imaging of rectal carcinoma involves accurate assessment of the primary tumor as well as distant metastatic disease. Preoperative imaging of nonrectal colon cancer is most beneficial in identifying distant metastases, regardless of primary T or N stage. Surgical treatment remains the definitive treatment for colon cancer, while organ-sparing approach may be considered in some rectal cancer patients based on imaging obtained before and after neoadjuvant treatment. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Radiomics and Machine Learning Analysis Based on Magnetic Resonance Imaging in the Assessment of Colorectal Liver Metastases Growth Pattern

To assess Radiomics and Machine Learning Analysis in Liver Colon and Rectal Cancer Metastases (CRLM) Growth Pattern, we evaluated, retrospectively, a training set of 51 patients with 121 liver metastases and an external validation set of 30 patients with a single lesion. All patients were subjected to MRI studies in pre-surgical setting. For each segmented volume of interest (VOI), 851 radiomics features were extracted using PyRadiomics package. Nonparametric test, univariate, linear regression analysis and patter recognition approaches were performed. The best results to discriminate expansive versus infiltrative front of tumor growth with the highest accuracy and AUC at univariate analysis were obtained by the wavelet_LHH_glrlm_ShortRunLowGray Level Emphasis from portal phase of contrast study. With regard to linear regression model, this increased the performance obtained respect to the univariate analysis for each sequence except that for EOB-phase sequence. The best results were obtained by a linear regression model of 15 significant features extracted by the T2-W SPACE sequence. Furthermore, using pattern recognition approaches, the diagnostic performance to discriminate the expansive versus infiltrative front of tumor growth increased again and the best classifier was a weighted KNN trained with the 9 significant metrics extracted from the portal phase of contrast study, with an accuracy of 92% on training set and of 91% on validation set. In the present study, we have demonstrated as Radiomics and Machine Learning Analysis, based on EOB-MRI study, allow to identify several biomarkers that permit to recognise the different Growth Patterns in CRLM.

Deep learning-based image reconstruction of 40-keV virtual monoenergetic images of dual-energy CT for the assessment of hypoenhancing hepatic metastasis

OBJECTIVES

To evaluate the diagnostic value of deep learning model (DLM) reconstructed dual-energy CT (DECT) low-keV virtual monoenergetic imaging (VMI) for assessing hypoenhancing hepatic metastases.

METHODS

This retrospective study included 131 patients who underwent contrast-enhanced DECT (80-kVp and 150-kVp with a tin filter) in the portal venous phase for hepatic metastasis surveillance. Linearly blended images simulating 100-kVp images (100-kVp), standard 40-keV VMI images (40-keV VMI), and post-processed 40-keV VMI using a vendor-agnostic DLM (i.e., DLM 40-keV VMI) were reconstructed. Lesion conspicuity and diagnostic acceptability were assessed by three independent reviewers and compared using the Wilcoxon signed-rank test. The contrast-to-noise ratios (CNRs) were also measured placing ROIs in metastatic lesions and liver parenchyma. The detection performance of hepatic metastases was assessed by using a jackknife alternative free-response ROC method. The consensus by two independent radiologists was used as the reference standard.

RESULTS

DLM 40-keV VMI, compared to 40-keV VMI and 100-kVp, showed a higher lesion-to-liver CNR (8.25 ± 3.23 vs. 6.05 ± 2.38 vs. 5.99 ± 2.00), better lesion conspicuity (4.3 (4.0-4.7) vs. 3.7 (3.7-4.0) vs. 3.7 (3.3-4.0)), and better diagnostic acceptability (4.3 (4.0-4.3) vs. 3.0 (2.7-3.3) vs. 4.0 (4.0-4.3)) (p < 0.001 for all). For lesion detection (246 hepatic metastases in 68 patients), the figure of merit was significantly higher with DLM 40-keV VMI than with 40-keV VMI (0.852 vs. 0.822, p = 0.012), whereas no significant difference existed between DLM 40-keV VMI and 100-kVp (0.852 vs. 0.842, p = 0.31).

CONCLUSIONS

DLM 40-keV VMI provided better image quality and comparable diagnostic performance for detecting hypoenhancing hepatic metastases compared to linearly blended images.

KEY POINTS

• DLM 40-keV VMI provides a superior image quality compared with 40-keV or 100-kVp for assessing hypoenhancing hepatic metastasis. • DLM 40-keV VMI has the highest CNR and lesion conspicuity score for hypoenhancing hepatic metastasis due to noise reduction and structural preservation. • DLM 40-keV VMI provides higher lesion detectability than standard 40-keV VMI (p = 0.012).

Conventional, functional and radiomics assessment for intrahepatic cholangiocarcinoma

Background

This paper offers an assessment of diagnostic tools in the evaluation of Intrahepatic Cholangiocarcinoma (ICC).

Methods

Several electronic datasets were analysed to search papers on morphological and functional evaluation in ICC patients. Papers published in English language has been scheduled from January 2010 to December 2021.

Results

We found that 88 clinical studies satisfied our research criteria. Several functional parameters and morphological elements allow a truthful ICC diagnosis. The contrast medium evaluation, during the different phases of contrast studies, support the recognition of several distinctive features of ICC. The imaging tool to employed and the type of contrast medium in magnetic resonance imaging, extracellular or hepatobiliary, should change considering patient, departement, and regional features. Also, Radiomics is an emerging area in the evaluation of ICCs.

Post treatment studies are required to evaluate the efficacy and the safety of therapies so as the patient surveillance.

Conclusions

Several morphological and functional data obtained during Imaging studies allow a truthful ICC diagnosis.

Radiomics in medical imaging: pitfalls and challenges in clinical management

BACKGROUND

Radiomics and radiogenomics are two words that recur often in language of radiologists, nuclear doctors and medical physicists especially in oncology field. Radiomics is the technique of medical images analysis to extract quantitative data that are not detected by human eye.

METHODS

This article is a narrative review on Radiomics in Medical Imaging. In particular, the review exposes the process, the limitations related to radiomics, and future prospects are discussed.

RESULTS

Several studies showed that radiomics is very promising. However, there were some critical issues: poor standardization and generalization of radiomics results, data-quality control, repeatability, reproducibility, database balancing and issues related to model overfitting.

CONCLUSIONS

Radiomics procedure should made considered all pitfalls and challenges to obtain robust and reproducible results that could be generalized in other patients cohort.

Radiomics textural features by MR imaging to assess clinical outcomes following liver resection in colorectal liver metastases

PURPOSE

To assess the efficacy of radiomics features obtained by T2-weighted sequences to predict clinical outcomes following liver resection in colorectal liver metastases patients.

METHODS

This retrospective analysis was approved by the local Ethical Committee board and radiological databases were interrogated, from January 2018 to May 2021, to select patients with liver metastases with pathological proof and MRI study in pre-surgical setting. The cohort of patients included a training set and an external validation set. The internal training set included 51 patients with 61 years of median age and 121 liver metastases. The validation cohort consisted a total of 30 patients with single lesion with 60 years of median age. For each volume of interest, 851 radiomics features were extracted as median values using PyRadiomics. Nonparametric test, intraclass correlation, receiver operating characteristic (ROC) analysis, linear regression modelling and pattern recognition methods (support vector machine (SVM), k-nearest neighbours (KNN), artificial neural network (NNET) and decision tree (DT)) were considered.

RESULTS

The best predictor to discriminate expansive versus infiltrative front of tumour growth was obtained by wavelet_LHL_gldm_DependenceNonUniformityNormalized with an accuracy of 82%; to discriminate high grade versus low grade or absent was the wavelet_LLH_glcm_Imc1 with accuracy of 88%; to differentiate the mucinous type of tumour was the wavelet_LLH_glcm_JointEntropy with accuracy of 92% while to identify tumour recurrence was the wavelet_LLL_glcm_Correlation with accuracy of 85%. Linear regression model increased the performance obtained with respect to the univariate analysis exclusively in the discrimination of expansive versus infiltrative front of tumour growth reaching an accuracy of 90%, a sensitivity of 95% and a specificity of 80%. Considering significant texture metrics tested with pattern recognition approaches, the best performance was reached by the KNN in the discrimination of the tumour budding considering the four textural predictors obtaining an accuracy of 93%, a sensitivity of 81% and a specificity of 97%.

CONCLUSIONS

Ours results confirmed the capacity of radiomics to identify as biomarkers, several prognostic features that could affect the treatment choice in patients with liver metastases, in order to obtain a more personalized approach.

An update on radiomics techniques in primary liver cancers

BACKGROUND

Radiomics is a progressing field of research that deals with the extraction of quantitative metrics from medical images. Radiomic features detention indirectly tissue features such as heterogeneity and shape and can, alone or in combination with demographic, histological, genomic, or proteomic data, be used for decision support system in clinical setting.

METHODS

This article is a narrative review on Radiomics in Primary Liver Cancers. Particularly, limitations and future perspectives are discussed.

RESULTS

In oncology, assessment of tissue heterogeneity is of particular interest: genomic analysis have demonstrated that the degree of tumour heterogeneity is a prognostic determinant of survival and an obstacle to cancer control. Therefore, that Radiomics could support cancer detection, diagnosis, evaluation of prognosis and response to treatment, so as could supervise disease status in hepatocellular carcinoma (HCC) and Intrahepatic Cholangiocarcinoma (ICC) patients. Radiomic analysis is a convenient radiological image analysis technique used to support clinical decisions as it is able to provide prognostic and / or predictive biomarkers that allow a fast, objective and repeatable tool for disease monitoring.

CONCLUSIONS

Although several studies have shown that this analysis is very promising, there is little standardization and generalization of the results, which limits the translation of this method into the clinical context. The limitations are mainly related to the evaluation of data quality, repeatability, reproducibility, overfitting of the model.

TRIAL REGISTRATION

Not applicable.

EOB-MR Based Radiomics Analysis to Assess Clinical Outcomes following Liver Resection in Colorectal Liver Metastases

Simple Summary

The aim of this study was to assess the efficacy of radiomics features obtained by EOB-MRI phase in order to predict clinical outcomes following liver resection in Colorectal Liver Metastases Patients, and evaluate recurrence, mutational status, pathological characteristic (mucinous) and surgical resection margin. Ours results confirmed the capacity of radiomics to identify, as biomarkers, several prognostic features that could affect the treatment choice in patients with liver metastases, in order to obtain a more personalized approach. These results were confirmed by external validation dataset. We obtained a good performance considering the single textural significant metric in the identification of front of tumor growth (expansive versus infiltrative) and tumor budding (high grade versus low grade or absent), in the recognition of mucinous type and in the detection of recurrences.

Abstract

The aim of this study was to assess the efficacy of radiomics features obtained by EOB-MRI phase in order to predict clinical outcomes following liver resection in Colorectal Liver Metastases Patients, and evaluate recurrence, mutational status, pathological characteristic (mucinous) and surgical resection margin. This retrospective analysis was approved by the local Ethical Committee board of National Cancer of Naples, IRCCS “Fondazione Pascale”. Radiological databases were interrogated from January 2018 to May 2021 in order to select patients with liver metastases with pathological proof and EOB-MRI study in pre-surgical setting. The cohort of patients included a training set (51 patients with 61 years of median age and 121 liver metastases) and an external validation set (30 patients with single lesion with 60 years of median age). For each segmented volume of interest by 2 expert radiologists, 851 radiomics features were extracted as median values using PyRadiomics. non-parametric test, intraclass correlation, receiver operating characteristic (ROC) analysis, linear regression modelling and pattern recognition methods (support vector machine (SVM), k-nearest neighbors (KNN), artificial neural network (NNET), and decision tree (DT)) were considered. The best predictor to discriminate expansive versus infiltrative front of tumor growth was HLH_glcm_MaximumProbability extraxted on VIBE_FA30 with an accuracy of 84%, a sensitivity of 83%, and a specificity of 82%. The best predictor to discriminate tumor budding was Inverse Variance obtained by the original GLCM matrix extraxted on VIBE_FA30 with an accuracy of 89%, a sensitivity of 96% and a specificity of 65%. The best predictor to differentiate the mucinous type of tumor was the HHL_glszm_ZoneVariance extraxted on VIBE_FA30 with an accuracy of 85%, a sensitivity of 46% and a specificity of 95%. The best predictor to identify tumor recurrence was the LHL_glcm_Correlation extraxted on VIBE_FA30 with an accuracy of 86%, a sensitivity of 52% and a specificity of 97%. The best linear regression model was obtained in the identification of the tumor growth front considering the height textural significant metrics by VIBE_FA10 (an accuracy of 89%; sensitivity of 93% and a specificity of 82%). Considering significant texture metrics tested with pattern recognition approaches, the best performance for each outcome was reached by a KNN in the identification of recurrence with the 3 textural significant features extracted by VIBE_FA10 (AUC of 91%, an accuracy of 93%; sensitivity of 99% and a specificity of 77%). Ours results confirmed the capacity of radiomics to identify as biomarkers, several prognostic features that could affect the treatment choice in patients with liver metastases, in order to obtain a more personalized approach.

Contrast MR-Based Radiomics and Machine Learning Analysis to Assess Clinical Outcomes following Liver Resection in Colorectal Liver Metastases: A Preliminary Study

Simple Summary

The objective of the study was to evaluate the radiomics features obtained by contrast MRI studies as prognostic biomarkers in colorectal liver metastases patients to predict clinical outcomes following liver resection. We demonstrated a good performance considering the single textural significant metric in the identification of front of tumor growth (expansive versus infiltrative) and tumor budding (high grade versus low grade or absent), in the recognition of mucinous type and in the detection of recurrences. Moreover, considering linear regression models or neural network classifiers in a multivariate approach was possible to increase the performance in terms of accuracy, sensitivity, and specificity.

Abstract

Purpose: To assess radiomics features efficacy obtained by arterial and portal MRI phase in the prediction of clinical outcomes in the colorectal liver metastases patients, evaluating recurrence, mutational status, pathological characteristic (mucinous and tumor budding) and surgical resection margin. Methods: This retrospective analysis was approved by the local Ethical Committee board, and radiological databases were used to select patients with colorectal liver metastases with pathological proof and MRI study in a pre-surgical setting after neoadjuvant chemotherapy. The cohort of patients included a training set (51 patients with 61 years of median age and 121 liver metastases) and an external validation set (30 patients with single lesion with 60 years of median age). For each segmented volume of interest on MRI by two expert radiologists, 851 radiomics features were extracted as median values using the PyRadiomics tool. Non-parametric Kruskal-Wallis test, intraclass correlation, receiver operating characteristic (ROC) analysis, linear regression modelling and pattern recognition methods (support vector machine (SVM), k-nearest neighbors (KNN), artificial neural network (NNET), and decision tree (DT)) were considered. Results: The best predictor to discriminate expansive versus infiltrative tumor growth front was wavelet_LHH_glrlm_ShortRunLowGrayLevelEmphasis extracted on portal phase with accuracy of 82%, sensitivity of 84%, and specificity of 77%. The best predictor to discriminate tumor budding was wavelet_LLH_firstorder_10Percentile extracted on portal phase with accuracy of 92%, a sensitivity of 96%, and a specificity of 81%. The best predictor to differentiate the mucinous type of tumor was the wavelet_LLL_glcm_ClusterTendency extracted on portal phase with accuracy of 88%, a sensitivity of 38%, and a specificity of 100%. The best predictor to identify the recurrence was the wavelet_HLH_ngtdm_Complexity extracted on arterial phase with accuracy of 90%, a sensitivity of 71%, and a specificity of 95%. The best linear regression model was obtained in the identification of mucinous type considering the 13 textural significant metrics extracted by arterial phase (accuracy of 94%, sensitivity of 77% and a specificity of 99%). The best results were obtained in the identification of tumor budding with the eleven textural significant features extracted by arterial phase using a KNN (accuracy of 95%, sensitivity of 84%, and a specificity of 99%). Conclusions: Our results confirmed the capacity of radiomics to identify as biomarkers and several prognostic features that could affect the treatment choice in patients with liver metastases in order to obtain a more personalized approach.

Characteristics of false-positive lesions in evaluating colorectal liver metastases on gadoxetic acid-enhanced magnetic resonance imaging

PURPOSE

Gadoxetic acid-enhanced MRI (Gd-EOB-MRI) shows higher sensitivity for colorectal liver metastases (CRLM) than contrast-enhanced computed tomography (CECT). However, the details of false-positive lesions for each imaging modality are unknown.

METHODS

Cases undergoing hepatectomy for CRLM following a preoperative evaluation with both CECT and Gd-EOB-MRI between July 2008 and December 2016 were reviewed. The false-positive and false-negative rates were assessed for each modality, and the characteristics of false-positive lesions were evaluated.

RESULTS

We evaluated 275 partial hepatectomies in 242 patients without preoperative chemotherapy. Among the 275 hepatectomies, 546 lesions were recognized by CECT and/or Gd-EOB-MRI. The false-positive rates for CECT and Gd-EOB-MRI were 4% (18/422) and 7% (37/536), respectively. The size of false-positive lesions was significantly smaller than that of correctly diagnosed lesions (median: 28 mm [3-120 mm] vs 7.6 mm [320 mm], P  < 0.001). Compared with the 233 correctly diagnosed lesions ≤ 20 mm in diameter, false-positive lesions were more frequently located near the liver surface or vasculobiliary structures than true lesions (33/37 [89%] vs 149/233 [64%], respectively; P  = 0.0021).

CONCLUSION

Gd-EOB-MRI had a 7% false-positive rate. A small size and tumor location near the surface or near vasculobiliary structures were associated with false positivity.

Compressed sensing for breath-hold high-resolution hepatobiliary phase imaging: image noise, artifact, biliary anatomy evaluation, and focal lesion detection in comparison with parallel imaging

PURPOSE

To assess image quality, performance for biliary anatomy diagnosis, and focal lesion detection rate of breath-hold high-resolution 3D T1-weighted hepatobiliary phase imaging using compressed sensing (CS HBP) compared to standard HBP using conventional parallel imaging.

METHODS

This retrospective study assessed consecutive 125 patients who underwent CS HBP and standard HBP between November 2019 and July 2020. Optimized resolution and scan time for CS HBP were 1 × 1.4 × 1 mm³ and 15 s, while those for standard HBP were 1.3 × 1.8 × 3 mm³ and 16 s. Two independent radiologists evaluated qualitative indices on the clarity of liver margin, visibility of the hepatic vessel and bile duct, image noise, and artifact on a 5-point scale. Biliary anatomy, confidence for biliary anatomy diagnosis, expected number of bile duct openings, and number of focal lesions were assessed. Wilcoxon signed-rank test, Pearson chi-square test, and sensitivity for focal lesion were used for statistical analysis. Intraclass correlation coefficient (ICC) and Cohen's kappa (κ) were used to determine inter-observer agreement.

RESULTS

CS HBP showed significantly better liver edge sharpness and bile duct visualization, but greater subjective image noise and non-respiratory artifacts compared to standard HBP. CS HBP showed higher number of concordantly assigned biliary anatomy across readers (86 vs. 80), indicating greater inter-observer agreement for biliary anatomy (κ, 0.67 vs. 0.45) and the number of bile duct openings (ICC, 0.860 vs. 0.579) with significantly higher diagnostic confidence (4.70-4.74 vs. 3.96-4.55; p = 0.002). Both readers identified more focal lesions in CS HBP than in standard HBP (88.2% and 84.5% vs. 66.3% and 73.4%).

CONCLUSION

Breath-hold high-resolution CS HBP was a feasible clinical sequence providing superior liver edge sharpness, bile duct visualization, and focal lesion detection rate compared to standard HBP despite higher noise and artifact. Due to improved spatial resolution, CS HBP yielded a higher inter-observer agreement and confidence for the biliary anatomy diagnosis.

Diagnosis of focal liver lesions with deep learning-based multi-channel analysis of hepatocyte-specific contrast-enhanced magnetic resonance imaging

BACKGROUND

The nature of input data is an essential factor when training neural networks. Research concerning magnetic resonance imaging (MRI)-based diagnosis of liver tumors using deep learning has been rapidly advancing. Still, evidence to support the utilization of multi-dimensional and multi-parametric image data is lacking. Due to higher information content, three-dimensional input should presumably result in higher classification precision. Also, the differentiation between focal liver lesions (FLLs) can only be plausible with simultaneous analysis of multi-sequence MRI images.

AIM

To compare diagnostic efficiency of two-dimensional (2D) and three-dimensional (3D)-densely connected convolutional neural networks (DenseNet) for FLLs on multi-sequence MRI.

METHODS

We retrospectively collected T2-weighted, gadoxetate disodium-enhanced arterial phase, portal venous phase, and hepatobiliary phase MRI scans from patients with focal nodular hyperplasia (FNH), hepatocellular carcinomas (HCC) or liver metastases (MET). Our search identified 71 FNH, 69 HCC and 76 MET. After volume registration, the same three most representative axial slices from all sequences were combined into four-channel images to train the 2D-DenseNet264 network. Identical bounding boxes were selected on all scans and stacked into 4D volumes to train the 3D-DenseNet264 model. The test set consisted of 10-10-10 tumors. The performance of the models was compared using area under the receiver operating characteristic curve (AUROC), specificity, sensitivity, positive predictive values (PPV), negative predictive values (NPV), and f1 scores.

RESULTS

The average AUC value of the 2D model (0.98) was slightly higher than that of the 3D model (0.94). Mean PPV, sensitivity, NPV, specificity and f1 scores (0.94, 0.93, 0.97, 0.97, and 0.93) of the 2D model were also superior to metrics of the 3D model (0.84, 0.83, 0.92, 0.92, and 0.83). The classification metrics of FNH were 0.91, 1.00, 1.00, 0.95, and 0.95 using the 2D and 0.90, 0.90, 0.95, 0.95, and 0.90 using the 3D models. The 2D and 3D networks' performance in the diagnosis of HCC were 1.00, 0.80, 0.91, 1.00, and 0.89 and 0.88, 0.70, 0.86, 0.95, and 0.78, respectively; while the evaluation of MET lesions resulted in 0.91, 1.00, 1.00, 0.95, and 0.95 and 0.75, 0.90, 0.94, 0.85, and 0.82 using the 2D and 3D networks, respectively.

CONCLUSION

Both 2D and 3D-DenseNets can differentiate FNH, HCC and MET with good accuracy when trained on hepatocyte-specific contrast-enhanced multi-sequence MRI volumes.

A meta-analysis evaluating contrast-enhanced intraoperative ultrasound (CE-IOUS) in the context of surgery for colorectal liver metastases

BACKGROUND

This study aimed to assess the outcomes of contrast-enhanced intraoperative ultrasound (CE-IOUS) for patients with colorectal liver metastases (CRLMs) undergoing surgery.

METHOD

A thorough literature search was performed in PubMed, Scopus, and Cochrane databases, in accordance with the PRISMA guidelines. The Odds Ratio, Weighted Mean Difference, and 95% Confidence Interval were evaluated, by means of Random-Effects model.

RESULTS

Eleven articles met the inclusion criteria and incorporated 497 patients. The present study shows that CE-IOUS is associated with higher sensitivity and accuracy compared with multidetector computed tomography (MDCT), magnetic resonance imaging (MRI), and intraoperative ultrasound (IOUS) in identifying CRLMs (p < 0.05). The positive predictive value was similar among the different modalities. Furthermore, new CRLMs were identified by CE-IOUS, thus affecting the surgical plan in 128 patients (51.8% of the patients with new CRLMs). Moreover, 91 patients (71%) underwent a more extensive hepatectomy and 15 patients (11.7%) were considered non-operable. Two alternative contrast agents, Sonazoid and Sonovue, were employed with similar sensitivity (p > 0.05).

CONCLUSION

These outcomes suggest the superiority of the CE-IOUS over MDCT, MRI, and IOUS for the staging of patients with CRLMs undergoing surgery. However, they should be treated with caution given the small number of the included studies.

Diagnostic evaluation and ablation treatments assessment in hepatocellular carcinoma

This article provides an overview of diagnostic evaluation and ablation treatment assessment in Hepatocellular Carcinoma (HCC). Only studies, in the English language from January 2010 to January 202, evaluating the diagnostic tools and assessment of ablative therapies in HCC patients were included. We found 173 clinical studies that satisfied the inclusion criteria.HCC may be noninvasively diagnosed by imaging findings. Multiphase contrast-enhanced imaging is necessary to assess HCC. Intravenous extracellular contrast agents are used for CT, while the agents used for MRI may be extracellular or hepatobiliary. Both gadoxetate disodium and gadobenate dimeglumine may be used in hepatobiliary phase imaging. For treatment-naive patients undergoing CT, unenhanced imaging is optional; however, it is required in the post treatment setting for CT and all MRI studies. Late arterial phase is strongly preferred over early arterial phase. The choice of modality (CT, US/CEUS or MRI) and MRI contrast agent (extracelllar or hepatobiliary) depends on patient, institutional, and regional factors. MRI allows to link morfological and functional data in the HCC evaluation. Also, Radiomics is an emerging field in the assessment of HCC patients.Postablation imaging is necessary to assess the treatment results, to monitor evolution of the ablated tissue over time, and to evaluate for complications. Post- thermal treatments, imaging should be performed at regularly scheduled intervals to assess treatment response and to evaluate for new lesions and potential complications.

Management of indeterminate hepatic nodules and evaluation of factors predicting their malignant potential in patients with colorectal cancer

Some liver nodules remain indeterminate despite hepatocyte-specific contrast MRI in patients with colorectal liver metastasis (CRLM). Our objective was to study the natural course and evaluate possible treatment strategies for indeterminate nodules. We retrospectively evaluated patients in whom MRI revealed 'indeterminate' or 'equivocal' nodules between January 2008 and October 2018. Patients were followed up until October 2019 or until death (median, 18 months; (1-130 months)). The incidence of patients with indeterminate nodules on MRI was 15.4% (60 of 389). The sensitivity and specificity of intraoperative ultrasound for detecting indeterminate nodules were 73.68% and 93.75%, respectively, with a positive predictive value of 96.6%. Over half of the patients followed up had benign nodules (58.8%). By comparing characteristics of patients with benign or malignant nodules in the follow up group, the ratio of positive lymph nodes to total number of lymph nodes resected (pLNR) was significantly greater in patients with malignant nodules (P = 0.006). Intraoperative ultrasound could be considered as an adjunct to MRI in patients with indeterminate nodules owing to its high positive predictive value. The pLNR could be used to help select which patients can undergo conservative therapy, at least in metachronous CRLM.

Endoscopic Ultrasound for Detection of Liver Metastasis: Hope or Hype?

Transabdominal ultrasonography, contrast-enhanced computed tomography, and magnetic resonance imaging (MRI) are the common diagnostic tests for the detection of hepatic lesions. Use of enhanced and advanced MRI technique, that is, diffusion weighted MRI and hepatocyte-specific contrast agents, has further improved the accuracy of detection of metastatic liver lesions ≤10 mm in diameter. However, even with these advanced imaging modalities sensitivity is low for lesions smaller than 10 mm when compared with standard intraoperative ultrasound. Endoscopic ultrasound (EUS) is an emerging imaging modality with resolution sufficient to detect and sample lesions as small as 5 mm in diameter. In this news and views, we have discussed the role of standard and enhanced EUS for the detection of metastatic liver lesions.

Imaging of colorectal cancer liver metastases using contrast-enhanced US, multidetector CT, MRI, and FDG PET/CT: a meta-analysis

BACKGROUND

Imaging of colorectal cancer liver metastases (CRCLMs) has improved in recent years. Therefore, the role of current imaging techniques needs to be defined.

PURPOSE

To assess the diagnostic performance of contrast-enhanced ultrasound (CEUS), multidetector computed tomography (MDCT), magnetic resonance imaging (MRI), and fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT in the detection of CRCLMs.

MATERIAL AND METHODS

PubMed database was searched for articles published during 2000-2019. Inclusion criteria were as follows: diagnosis/suspicion of CRCLMs; CEUS, MDCT, MRI, or FDG PET/CT performed for the detection of CRCLMs; prospective study design; histopathologic examination, intraoperative findings and/or follow-up used as reference standard; and data for calculating sensitivity and specificity reported.

RESULTS

Twelve prospective studies were assessed, including 536 patients with CRCLMs (n = 1335). On a per-lesion basis, the sensitivity of CEUS, MDCT, MRI, and FDG PET/CT was 86%, 84%, 89%, and 62%, respectively. MRI had the highest sensitivity on a per-lesion analysis. CEUS and MDCT had comparable sensitivities. On a per-patient basis, the sensitivity and specificity of CEUS, MDCT, MRI, and FDG PET/CT was 80% and 97%, 87% and 95%, 87% and 94%, and 96% and 97%, respectively. The per-patient sensitivities for MRI and MDCT were similar. The sensitivity for MRI was higher than that for CEUS, MDCT, and FDG PET/CT for lesions <10 mm and lesions at least 10 mm in size. Hepatospecific contrast agent did not improve diagnostic performances.

CONCLUSION

MRI is the preferred imaging modality for evaluating CRCLMs. Both MDCT and CEUS can be used as alternatives.

Imaging and clinical features of colorectal liver metastases with macroscopic intrabiliary growth

PURPOSE

The purpose of this study was to evaluate imaging and clinical features of colorectal liver metastases complicated with macroscopic intrabiliary growth, and correlate the unusual pattern of spread with treatment and follow-up.

METHODS

A retrospective analysis of the clinical, imaging and follow-up files of all patients with surgically resected colorectal liver metastases from January 2016 to October 2020 was reviewed to identify those with macroscopic intrabiliary growth. Two radiologists evaluated the radiological features of colorectal liver metastasis with macroscopic intrabiliary growth. The histopathological findings and follow-up results were also investigated.

RESULTS

A total of 555 patients were included. Colorectal liver metastasis with macroscopic intrabiliary growth was present in 5 patients (0.9 %). Four patients experienced tumor recurrence or progression after surgical treatment (80 %), and recurrent tumors retained propensity for intraductal growth. CT (n = 6) and MR (n = 6) examinations were performed before 8 operations with the pathological examination confirmed macroscopic intrabiliary colorectal metastases. According to the location, intrabiliary colorectal metastases were classified into two categories: peripheral (n = 3) and central involvement (n = 5). The lengths of tumoral extension into the downstream bile duct were more than those of extension into the upstream bile duct (P = 0.029). On CT images, all cases showed dilated bile ducts filled with soft tissue attenuation presenting moderate (n = 4) or obvious (n = 2) enhancement. On MR images, all intra-hepatic and intrabiliary components of the metastases showed restricted diffusion on diffusion-weighted imaging, and peritumoral wedge-shaped T1-weighted hyperintensity appeared in the cases with obstruction of intrahepatic bile ducts.

CONCLUSIONS

The propensity for colorectal liver metastasis with intrabiliary growth to grow longitudinally and extend beyond the intrahepatic tumor edge elevates the risk of high recurrence after operation. Intrabiliary growth of liver metastasis exhibits characteristic MR and CT imaging features, which help to make an accurate diagnosis and improve treatment plans.

Spectrum of liver lesions hyperintense on hepatobiliary phase: an approach by clinical setting

Hepatobiliary MRI contrast agents are increasingly being used for liver imaging. In clinical practice, most focal liver lesions do not uptake hepatobiliary contrast agents. Less commonly, hepatic lesions may show variable signal characteristics on hepatobiliary phase. This pictorial essay reviews a broad spectrum of benign and malignant focal hepatic observations that may show hyperintensity on hepatobiliary phase in various clinical settings. In non-cirrhotic patients, focal hepatic observations that show hyperintensity in the hepatobiliary phase are usually benign and typically include focal nodular hyperplasia. In patients with primary or secondary vascular disorders, focal nodular hyperplasia-like lesions arise as a local hyperplastic response to vascular alterations and tend to be iso- or hyperintense in the hepatobiliary phase. In oncologic patients, metastases and cholangiocarcinoma are hypointense lesions in the hepatobiliary phase; however, occasionally they may show a diffuse, central and inhomogeneous hepatobiliary paradoxical uptake with peripheral rim hypointensity. Post-chemotherapy focal nodular hyperplasia-like lesions may be tricky, and their typical hyperintense rim in the hepatobiliary phase is very helpful for the differential diagnosis with metastases. In cirrhotic patients, hepatocellular carcinoma may occasionally appear hyperintense on hepatobiliary phase.

Contrast-Enhanced Intraoperative Ultrasound Improved Sensitivity and Positive Predictive Value in Colorectal Liver Metastasis: a Systematic Review and Meta-Analysis

BACKGROUND

The diagnostic accuracy of imaging modalities in colorectal cancer liver metastases (CRLM) has improved in recent years, therefore the role of current imaging techniques needs to be defined.

OBJECTIVE

The aim of this study was to assess the diagnostic performance of magnetic resonance imaging, preoperative imaging (magnetic resonance imaging or computed tomography), intraoperative ultrasound, and contrast-enhanced intraoperative ultrasound in the detection of CRLM.

MATERIALS AND METHODS

Eligible trials published before 30 March 2020 were identified from the EMBASE, PubMed, Web of Science, and Cochrane Library databases, and descriptive and quantitative data were extracted. Study quality was evaluated for the identified studies and a random-effects model was used to determine the integrated diagnosis estimation. Meta-regression was implemented to explore the possible contributors to heterogeneity.

RESULTS

Overall, 13 studies were included for analysis, comprising 682 patients with a total of 2303 liver lesions. The pooled sensitivity, specificity, and diagnostic odds ratio of contrast-enhanced intraoperative ultrasound were 0.94 (95% confidence interval [CI] 0.89-0.97), 0.83 (95% CI 0.67-0.92), and 79 (95% CI 32-196), respectively. The overall weighted area under the curve was 0.96 (95% CI 0.94-0.97). In univariate meta-regression analysis, disappearing liver metastasis, contrast agent, and Kupffer phase were the potent sources of heterogeneity; however, in multivariate meta-regression, no definite variable was the source of the study heterogeneity.

CONCLUSION

Contrast-enhanced intraoperative ultrasound demonstrated a high sensitivity and specificity for screening CRLM.

Abbreviated MRI protocol for colorectal liver metastases: How the radiologist could work in pre surgical setting

Background

MRI is the most reliable imaging modality that allows to assess liver metastases. Our purpose is to compare the per-lesion and per-patient detection rate of gadoxetic acid-(Gd-EOB) enhanced liver MRI and fast MR protocol including Diffusion Weighted Imaging (DWI) and T2-W Fat Suppression sequence in the detection of liver metastasis in pre surgical setting.

Methods

One hundred and eight patients with pathologically proven liver metastases (756 liver metastases) underwent Gd-EOBMRI were enrolled in this study. Three radiologist independently graded the presence of liver lesions on a five-point confidence scale assessed only abbreviated protocol (DWI and sampling perfection with application-optimized contrasts using different flip angle evolution (SPACE) fat suppressed sequence) and after an interval of more than 2 weeks the conventional study (all acquired sequences). Per-lesion and per-patient detection rate of metastases were calculated. Weighted к values were used to evaluate inter-reader agreement of the confidence scale regarding the presence of the lesion.

Results

MRI detected 732 liver metastases. All lesions were identified both by conventional study as by abbreviated protocol. In terms of per-lesion detection rate of liver metastasis, all three readers had higher detection rate both with abbreviated protocol and with standard protocol with Gd-EOB (96.8% [732 of 756] vs. 96.5% [730 of 756] for reader 1; 95.8% [725 of 756] vs. 95.2% [720 of 756] for reader 2; 96.5% [730 of 756] vs. 96.5% [730 of 756] for reader 3). Inter-reader agreement of lesions detection rate between the three radiologists was excellent (k range, 0.86–0.98) both for Gd-EOB MRI and for Fast protocol (k range, 0.89–0.99).

Conclusion

Abbreviated protocol showed the same detection rate than conventional study in detection of liver metastases.

Aberrant gastric venous drainage and associated atrophy of hepatic segment II: computed tomography analysis of 2021 patients

PURPOSE

To investigate the prevalence and patterns of aberrant gastric venous drainage and associated atrophy of the hepatic segment on contrast-enhanced computed tomography (CT).

METHODS

Two radiologists retrospectively reviewed contrast-enhanced CT images from 2021 patients who underwent cone-beam CT-guided chemoembolization between January 2013 and December 2018. They determined the presence or absence of an aberrant gastric vein(s) and its drainage site by consensus, and qualitatively analyzed the presence or absence of atrophy of segments II or III. In cases of disagreement between the two reviewers regarding the presence of atrophy, quantitative analysis was performed using dedicated software.

RESULTS

A total of 31 aberrant right gastric veins were revealed on CT (1.5%), most of which drained into P2 (n = 8), the S2/3 border zone (n = 8), S2 (n = 6), or S4 (n = 5). An aberrant left gastric vein was observed in 21 (1.0%) patients, and P2 was the most common drainage site (n = 13) in these patients. Atrophy of segment II was more frequently observed among patients with aberrant gastric veins than among those without (26.9% versus 4.1%; p < 0.001). In addition, an aberrant gastric vein draining into P2 was most frequently accompanied by segment II atrophy (47.6%).

CONCLUSION

Aberrant right and left gastric veins were observed in 1.5% and 1.0% of patients, respectively. Atrophy of segment II was frequently observed in patients with aberrant gastric veins, especially those that drained into P2.

Multimodal therapy with surgery and adjuvant nivolumab for late-onset multiple liver metastases of choroidal malignant melanoma: a case report

BACKGROUND

Choroidal malignant melanoma is the most common primary malignant tumor of the eye in adults. Prognosis after recurrence of this disease has been dismal because of the absence of an effective therapy. However, resection of recurrent foci and a subsequent treatment with immune-checkpoint inhibitor may improve the prognosis after recurrence of this disease. This study presents a case of late-onset liver metastases of choroidal malignant melanoma, successfully treated with hepatectomy and postoperative adjuvant nivolumab.

CASE PRESENTATION

A 53-year-old woman had undergone left ocular enucleation because of choroidal malignant melanoma 13 years prior to admission. She visited a nearby clinic with complaints of epigastric pain. She was referred to our hospital because a giant liver tumor was observed on abdominal ultrasonography. Enhanced computed tomography revealed multiple liver tumors in the right lobe, 49 mm in diameter with ring enhancement in subsegment (S) 5/6, and 14 and 8 mm without any enhancement in S7 and S5, respectively. On magnetic resonance imaging, the main tumor showed high intensity on T1-weighted with fat suppression, suggesting melanin deposition. Based on the diagnosis of multiple liver metastases of choroidal malignant melanoma, right hepatectomy and regional lymphadenectomy were performed. She was discharged without postoperative complications. Histological examination revealed that all tumors were metastatic malignant melanoma. She was treated with nivolumab postoperatively, and no recurrences were observed during 22 months of follow-up.

CONCLUSIONS

Aggressive surgery plus adjuvant nivolumab appears to be a promising treatment for choroidal malignant melanoma with late-onset liver metastases.

Preoperative imaging for colorectal liver metastases: a nationwide population-based study

Background

In patients with colorectal liver metastases (CRLM) preoperative imaging may include contrast‐enhanced (ce) MRI and [¹⁸F]fluorodeoxyglucose (¹⁸F‐FDG) PET–CT. This study assessed trends and variation between hospitals and oncological networks in the use of preoperative imaging in the Netherlands.

Methods

Data for all patients who underwent liver resection for CRLM in the Netherlands between 2014 and 2018 were retrieved from a nationwide auditing database. Multivariable logistic regression analysis was used to assess use of ceMRI, ¹⁸F‐FDG PET–CT and combined ceMRI and ¹⁸F‐FDG PET–CT, and trends in preoperative imaging and hospital and oncological network variation.

Results

A total of 4510 patients were included, of whom 1562 had ceMRI, 872 had ¹⁸F‐FDG PET–CT, and 1293 had combined ceMRI and ¹⁸F‐FDG PET–CT. Use of ceMRI increased over time (from 9·6 to 26·2 per cent; P < 0·001), use of ¹⁸F‐FDG PET–CT decreased (from 28·6 to 6·0 per cent; P < 0·001), and use of both ceMRI and ¹⁸F‐FDG PET–CT 16·9 per cent) remained stable. Unadjusted variation in the use of ceMRI, ¹⁸F‐FDG PET–CT, and combined ceMRI and ¹⁸F‐FDG PET–CT ranged from 5·6 to 100 per cent between hospitals. After case‐mix correction, hospital and oncological network variation was found for all imaging modalities.

Discussion

Significant variation exists concerning the use of preoperative imaging for CRLM between hospitals and oncological networks in the Netherlands. The use of MRI is increasing, whereas that of ¹⁸F‐FDG PET–CT is decreasing.

Cancers Metastatic to the Liver

The liver is a common site of metastatic cancer spread, and metastatic lesions are the most common malignant liver tumors. Diagnosis of liver metastases often is established based on clinical assessment, laboratory tests, and appropriate imaging. Surgical resection is the treatment of choice for resectable colorectal and neuroendocrine liver metastases. Long-term survival outcome data after treatment of hepatic metastases of noncolorectal non-neuroendocrine tumors are less robust. The treatment strategy for patients with liver metastases should be determined case by case in a multidisciplinary setting.