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Integration of advanced digital technologies along with ensuring environmental sustainability in the logistics sector is becoming the need of the hour novel multimodal transportation concept. The rapid technological development in the era of industry 4.0 can not only create new opportunities in achieving highly efficient, intelligent, and smart logistics systems but also enable new business models for value addition, additionally, this novel system will also avoid environmental degradation and use of scarce natural resources that contribute to climate change. This paper summarizes the research trends of these technologies in multimodal logistics systems since 2005 through a systematic literature review. The results revealed a mixed picture of the situation, starting from emerging technologies like artificial intelligence, machine learning, and blockchain becoming key technological concepts for multimodal logistics systems to government policy hurdles and lack of impact breakthroughs in the industry. However, the results show that adaptation to these technologies improves the overall environmental, economic, and social sustainability of the system.

Abstract Background Shortages of mechanical ventilation have become a constant problem in Emergency Departments (EDs), thereby affecting the timely deployment of medical interventions that counteract the severe health complications experienced during respiratory disease seasons. It is then necessary to count on agile and robust methodological approaches predicting the expected demand loads to EDs while supporting the timely allocation of ventilators. In this paper, we propose an integration of Artificial Intelligence (AI) and Discrete-event Simulation (DES) to design effective interventions ensuring the high availability of ventilators for patients needing these devices. Methods First, we applied Random Forest (RF) to estimate the mechanical ventilation probability of respiratory-affected patients entering the emergency wards. Second, we introduced the RF predictions into a DES model to diagnose the response of EDs in terms of mechanical ventilator availability. Lately, we pretested two different interventions suggested by decision-makers to address the scarcity of this resource. A case study in a European hospital group was used to validate the proposed methodology. Results The number of patients in the training cohort was 734, while the test group comprised 315. The sensitivity of the AI model was 93.08% (95% confidence interval, [88.46 − 96.26%]), whilst the specificity was 85.45% [77.45 − 91.45%]. On the other hand, the positive and negative predictive values were 91.62% (86.75 − 95.13%) and 87.85% (80.12 − 93.36%). Also, the Receiver Operator Characteristic (ROC) curve plot was 95.00% (89.25 − 100%). Finally, the median waiting time for mechanical ventilation was decreased by 17.48% after implementing a new resource capacity strategy. Conclusions Combining AI and DES helps healthcare decision-makers to elucidate interventions shortening the waiting times for mechanical ventilators in EDs during respiratory disease epidemics and pandemics.

The aim of this informative review was to investigate the application of radiomics in cancer imaging and to summarize the results of recent studies to support oncological imaging with particular attention to breast cancer, rectal cancer and primitive and secondary liver cancer. This review also aims to provide the main findings, challenges and limitations of the current methodologies. Clinical studies published in the last four years (2019–2022) were included in this review. Among the 19 studies analyzed, none assessed the differences between scanners and vendor-dependent characteristics, collected images of individuals at additional points in time, performed calibration statistics, represented a prospective study performed and registered in a study database, conducted a cost-effectiveness analysis, reported on the cost-effectiveness of the clinical application, or performed multivariable analysis with also non-radiomics features. Seven studies reached a high radiomic quality score (RQS), and seventeen earned additional points by using validation steps considering two datasets from two distinct institutes and open science and data domains (radiomics features calculated on a set of representative ROIs are open source). The potential of radiomics is increasingly establishing itself, even if there are still several aspects to be evaluated before the passage of radiomics into routine clinical practice. There are several challenges, including the need for standardization across all stages of the workflow and the potential for cross-site validation using real-world heterogeneous datasets. Moreover, multiple centers and prospective radiomics studies with more samples that add inter-scanner differences and vendor-dependent characteristics will be needed in the future, as well as the collecting of images of individuals at additional time points, the reporting of calibration statistics and the performing of prospective studies registered in a study database.

Intraductal papillary mucinous neoplasms (IPMNs) are a very common incidental finding during patient radiological assessment. These lesions may progress from low-grade dysplasia (LGD) to high-grade dysplasia (HGD) and even pancreatic cancer. The IPMN progression risk grows with time, so discontinuation of surveillance is not recommended. It is very important to identify imaging features that suggest LGD of IPMNs, and thus, distinguish lesions that only require careful surveillance from those that need surgical resection. It is important to know the management guidelines and especially the indications for surgery, to be able to point out in the report the findings that suggest malignant degeneration. The imaging tools employed for diagnosis and risk assessment are Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) with contrast medium. According to the latest European guidelines, MRI is the method of choice for the diagnosis and follow-up of patients with IPMN since this tool has a highest sensitivity in detecting mural nodules and intra-cystic septa. It plays a key role in the diagnosis of worrisome features and high-risk stigmata, which are associated with IPMNs malignant degeneration. Nowadays, the main limit of diagnostic tools is the ability to identify the precursor of pancreatic cancer. In this context, increasing attention is being given to artificial intelligence (AI) and radiomics analysis. However, these tools remain in an exploratory phase, considering the limitations of currently published studies. Key limits include noncompliance with AI best practices, radiomics workflow standardization, and clear reporting of study methodology, including segmentation and data balancing. In the radiological report it is useful to note the type of IPMN so as the morphological features, size, rate growth, wall, septa and mural nodules, on which the indications for surveillance and surgery are based. These features should be reported so as the surveillance time should be suggested according to guidelines.

Background: In patient with a complete or near-complete clinical response after neoadjuvant treatment for locally advanced rectal cancer, the organ-sparing approach [watch & wait (W&W) or local excision (LE)] is a possible alternative to major rectal resection. Although, in case of local recurrence or regrowth, after these treatments, a total mesorectal excision (TME) can be operated. Method: In this retrospective study, we selected 120 patients with locally advanced rectal cancer (LARC) who had a complete or near-complete clinical response after neoadjuvant treatment, from June 2011 to June 2021. Among them, 41 patients were managed by W&W approach, whereas 79 patients were managed by LE. Twenty-three patients underwent salvage TME for an unfavorable histology after LE (11 patients) or a local recurrence/regrowth (seven patients in LE group – five patients in W&W group), with a median follow-up of 42 months. Results: Following salvage TME, no patients died within 30 days; serious adverse events occurred in four patients; 8 (34.8%) patients had a definitive stoma; 8 (34.8%) patients undergone to major surgery for unfavorable histology after LE – a complete response was confirmed. Conclusion: Notably active surveillance after rectal sparing allows prompt identifying signs of regrowth or relapse leading to a radical TME. Rectal sparing is a possible strategy for LARC patients although an active surveillance is necessary.

The capture of carbon and sequestration (CCS) activity is considered strategic in the context of world energy policy. In fact, CO2 emissions from fossil/conventional-fuel-fired power plants can be lowered by using CCS on the same. Various other methods have been developed to date to capture the carbon and store it. This article focuses on the various carbon capture technologies and the storage technologies such as pre-combustion, post-combustion, oxyfuel technology, and direct air capture (DAC) technology, including their subparts, along with the factors affecting the carbon capture technologies. The aim of the present study is to develop an overview of carbon dioxide removal (CDR) technologies and CO2 sequestration, including a vast coverage of the various factors that have a huge impact on CCS. It emerged that the existing technologies that deal with CO2 sequestration and capture are being used at large scale to produce derivatives including chemicals, polymers, building materials, and various other products. The newest technology that has been seen creating a huge effect is direct air capture, and commercial use of such technologies has been seen. Future potential application areas have been realised in this review work. In addition, this article explores policy recommendations for the future.

In a global context, the development of new technologies and becomes an entrepreneurial challenge for the near future. One of the most promising phenomena of this new way are startups. This phenomenon is also emerging in developing countries like Pakistan. However, the success rate of startups is prone to several micro and macro environmental challenges and if these challenges not addressed properly, cause failure of startups. This study intends to contribute to research by proposing a methodological approach to find out the macro-environmental factors and their impact on startups from the perspective of developing countries. Firstly, the PESTEL (Political, Economic, Social, Technological, Environmental, and Legal) analysis is conducted to identify macro-environmental factors displayed in the Cause and effect diagram. Secondly, the Fuzzy Failure Mode and Effect Analysis (FFMEA) is applied to prioritize the risks to devise strategies. Thirdly, to formulate a risk mitigation strategies and policies to support startup ecosystem. The results show that inflation rates, currency depreciation, and corruption are significant challenges for startups. Therefore, this paper aims to help policy makers, entrepreneurs and business schools to work in join collaboration to devise risk mitigation strategies for startups in emerging economies.

Abstract Background Metastatic disease in tumors originating from the gastrointestinal tract can exhibit varying degrees of tumor burden at presentation. Some patients follow a less aggressive disease course, characterized by a limited number of metastatic sites, referred to as “oligo-metastatic disease” (OMD). The precise biological characteristics that define the oligometastatic behavior remain uncertain. In this study, we present a protocol designed to prospectively identify OMD, with the aim of proposing novel therapeutic approaches and monitoring strategies. Methods The PREDICTION study is a monocentric, prospective, observational investigation. Enrolled patients will receive standard treatment, while translational activities will involve analysis of the tumor microenvironment and genomic profiling using immunohistochemistry and next-generation sequencing, respectively. The first primary objective (descriptive) is to determine the prevalence of biological characteristics in OMD derived from gastrointestinal tract neoplasms, including high genetic concordance between primary tumors and metastases, a significant infiltration of T lymphocytes, and the absence of clonal evolution favoring specific driver genes (KRAS and PIK3CA). The second co-primary objective (analytic) is to identify a prognostic score for true OMD, with a primary focus on metastatic colorectal cancer. The score will comprise genetic concordance (> 80%), high T-lymphocyte infiltration, and the absence of clonal evolution favoring driver genes. It is hypothesized that patients with true OMD (score 3+) will have a lower rate of progression/recurrence within one year (20%) compared to those with false OMD (80%). The endpoint of the co-primary objective is the rate of recurrence/progression at one year. Considering a reasonable probability (60%) of the three factors occurring simultaneously in true OMD (score 3+), using a significance level of α = 0.05 and a test power of 90%, the study requires a minimum enrollment of 32 patients. Discussion Few studies have explored the precise genetic and biological features of OMD thus far. In clinical settings, the diagnosis of OMD is typically made retrospectively, as some patients who undergo intensive treatment for oligometastases develop polymetastatic diseases within a year, while others do not experience disease progression (true OMD). In the coming years, the identification of true OMD will allow us to employ more personalized and comprehensive strategies in cancer treatment. Trial registration ClinicalTrials.gov ID NCT05806151.

The textile industry, a vital contributor to Pakistan’s economy, faces pressing challenges in transitioning towards sustainability amid global environmental concerns. This manuscript presents a comprehensive case study on the implementation of IoT-driven strategies in the Pakistani textile sector to achieve digital and sustainable transformation. The findings reveal that the implementation of IoT technologies facilitated real-time environmental monitoring, enabling compliance with regulatory standards, and fostering sustainable manufacturing practices. Ultimately, this manuscript offers valuable insights into the transformative potential of IoT technologies in driving sustainable practices in the textile industry. The case study serves as a benchmark for other textile-producing regions aiming to embark on a digital and sustainable journey. These findings hold significant implications for the ongoing dialogue on sustainable industrial development, providing valuable direction for policymakers and stakeholders in shaping a more resilient and ecologically conscious future. Future research should prioritize addressing issues like data confidentiality and interoperability while adhering to standard requirements. Additionally, exploring analytics and machine learning methods for predictive maintenance, optimized performance, and operational improvement is crucial.

Abstract 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.

Abstract Cyberspace has continued to change throughout the 1990s and 2000s, when the Internet became widely used. The concept of a massive, integrated, sustainable, and interconnected cyber world is the heart of the metaverse. The aim of the metaverse is to create a digital world that is analogous to the existing world. Thus, the most recent metaverse development is investigated in light of cutting‐edge technologies and metaverse ecosystems. To this end, a pilot survey to provide a first overview of upcoming challenges and opportunities of the metaverse is presented. The results provide researchers with a direction for future study as well as potential applications in the metaverse.

Artificial intelligence (AI) represents a promising frontier for cultural heritage, offering new perspectives for conservation, cataloguing, research and valorisation. AI can allow us to preserve and pass on our cultural roots to future generations. However, a "balanced" approach is needed, in which technological innovation is embraced while preserving the integrity and value of the works of art and of history itself. With careful management, artificial intelligence can become a valuable tool for preserving and enhancing our cultural heritage for future generations. What are the benefits, challenges and future developments of AI in the context of cultural heritage?

Purpose: We aimed to assess the efficacy of machine learning and radiomics analysis using magnetic resonance imaging (MRI) with a hepatospecific contrast agent, in a pre-surgical setting, to predict tumor budding in liver metastases. Methods: Patients with MRI in a pre-surgical setting were retrospectively enrolled. Manual segmentation was made by means 3D Slicer image computing, and 851 radiomics features were extracted as median values using the PyRadiomics Python package. Balancing was performed and inter- and intraclass correlation coefficients were calculated to assess the between observer and within observer reproducibility of all radiomics extracted features. A Wilcoxon–Mann–Whitney nonparametric test and receiver operating characteristics (ROC) analysis were carried out. Balancing and feature selection procedures were performed. Linear and non-logistic regression models (LRM and NLRM) and different machine learning-based classifiers including decision tree (DT), k-nearest neighbor (KNN) and support vector machine (SVM) were considered. Results: The internal training set included 49 patients and 119 liver metastases. The validation cohort consisted of a total of 28 single lesion patients. The best single predictor to classify tumor budding was original_glcm_Idn obtained in the T1-W VIBE sequence arterial phase with an accuracy of 84%; wavelet_LLH_firstorder_10Percentile was obtained in the T1-W VIBE sequence portal phase with an accuracy of 92%; wavelet_HHL_glcm_MaximumProbability was obtained in the T1-W VIBE sequence hepatobiliary excretion phase with an accuracy of 88%; and wavelet_LLH_glcm_Imc1 was obtained in T2-W SPACE sequences with an accuracy of 88%. Considering the linear regression analysis, a statistically significant increase in accuracy to 96% was obtained using a linear weighted combination of 13 radiomic features extracted from the T1-W VIBE sequence arterial phase. Moreover, the best classifier was a KNN trained with the 13 radiomic features extracted from the arterial phase of the T1-W VIBE sequence, obtaining an accuracy of 95% and an AUC of 0.96. The validation set reached an accuracy of 94%, a sensitivity of 86% and a specificity of 95%. Conclusions: Machine learning and radiomics analysis are promising tools in predicting tumor budding. Considering the linear regression analysis, there was a statistically significant increase in accuracy to 96% using a weighted linear combination of 13 radiomics features extracted from the arterial phase compared to a single radiomics feature.

Abstract Background The clinical observation showed a potential additive effect of anti-PD-1 agents and cetirizine in patients with advanced melanoma. Methods Clinical outcomes of concomitant cetirizine/anti-PD-1 treatment of patients with stage IIIb–IV melanoma were retrospectively collected, and a transcriptomic analysis was performed on blood samples obtained at baseline and after 3 months of treatment. Results Patients treated with cetirizine concomitantly with an anti-PD-1 agent had significantly longer progression-free survival (PFS; mean PFS: 28 vs 15 months, HR 0.46, 95% CI: 0.28–0.76; p = 0.0023) and OS (mean OS was 36 vs 23 months, HR 0.48, 95% CI: 0.29–0.78; p = 0.0032) in comparison with those not receiving cetirizine. The concomitant treatment was significantly associated with ORR and DCR (p

Abstract Background We retrospectively evaluated safety and performance of magnetic seed localisation of nonpalpable breast lesions. Methods We reviewed records of patients with nonpalpable breast lesions preoperative localised by placing magnetic Magseed® marker between February 2019 and December 2020. During surgery, Sentimag® magnetic probe was used to localise the marker and guide surgery. Safety, lesion identification and excision with tumour with free margins and re-excision rate were assessed. Results A total of 77 Magseed® devices were placed into the breasts of 73 patients, 44 under ultrasound and 33 under stereotactic guidance (4 bilateral). All devices were retrieved as were the target lesions. Magnetic marker placement was successful in all cases without any adverse event. Intraoperative identification and excision of the localised lesion were successful in 77 of 77 of cases (100%). In three cases (all of them calcifications with the seed placed under stereotactic guidance), the seed did not reach the exact target position of the biopsy clip; thus, larger excision was needed, with localisation failure attributed to incorrect clip insertion (n = 1) or to clip dislocation (n = 2). Migration of the marker was negligible in all patients. Complete excision after the initial procedure with at least 1-mm disease-free margins was obtained in 74 out of 77 (96.1%) lesions. The re-excision rate was 3 out of 77 (4%). Conclusions Magnetic marker localisation for nonpalpable breast lesions was safe, reliable, and effective in terms of lesion identification, excision with tumour-free margins and re-excision rate.

Abstract 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.

Abstract 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.

Abstract Background To date, no paper reports cases of lymphangitis after COVID 19 vaccination. We present a case of lymphangitis after vaccination from COVID 19, in a patient with colorectal liver metastases. Methods We described the case of a 56-year-old woman with history of a surgical resection of colorectal cancer and liver metastases, without any kind of drug therapy for about a month. In addition, a recent administration (2 days ago) of Spikevax (mRNA-1273, Moderna vaccine), as a booster dose, on the right arm was reported. Results The magnetic resonance (MR) examination showed the effects of the previous surgical resection and five new hepatic metastases, located in the VIII, VI, V, IV and II hepatic segments. As an accessory finding the presence of lymphadenopathy in the axillary area and lymphangitis of the right breast and chest were identified. The computed tomography scan performed a week earlier, and re-evaluated in light of the MR data, did not identify the presence of lymphadenopathy in the axillary area and lymphangitis signs. Conclusions Lymphangitis could occur after COVID 19 vaccine and it is important to know this data to avoid alarmism in patients and clinicians and economic waste linked to the execution of various radiological investigations for the search for a tumour that probably does not exist. Trial registration: Not applicable.

Abstract 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.

Purpose:The purpose of this study was to discriminate between benign and malignant breast lesions through several classifiers using, as predictors, radiomic metrics extracted from CEM and DCE-MRI images. In order to optimize the analysis, balancing and feature selection procedures were performed. Methods: Fifty-four patients with 79 histo-pathologically proven breast lesions (48 malignant lesions and 31 benign lesions) underwent both CEM and DCE-MRI. The lesions were retrospectively analyzed with radiomic and artificial intelligence approaches. Forty-eight textural metrics were extracted, and univariate and multivariate analyses were performed: non-parametric statistical test, receiver operating characteristic (ROC) and machine learning classifiers. Results: Considering the single metrics extracted from CEM, the best predictors were KURTOSIS (area under ROC curve (AUC) = 0.71) and SKEWNESS (AUC = 0.71) calculated on late MLO view. Considering the features calculated from DCE-MRI, the best predictors were RANGE (AUC = 0.72), ENERGY (AUC = 0.72), ENTROPY (AUC = 0.70) and GLN (gray-level nonuniformity) of the gray-level run-length matrix (AUC = 0.72). Considering the analysis with classifiers and an unbalanced dataset, no significant results were obtained. After the balancing and feature selection procedures, higher values of accuracy, specificity and AUC were reached. The best performance was obtained considering 18 robust features among all metrics derived from CEM and DCE-MRI, using a linear discriminant analysis (accuracy of 0.84 and AUC = 0.88). Conclusions: Classifiers, adjusted with adaptive synthetic sampling and feature selection, allowed for increased diagnostic performance of CEM and DCE-MRI in the differentiation between benign and malignant lesions.

BackgroundMetastatic colorectal cancer is one of the most common causes of cancer death worldwide. RAS and BRAF mutational analyses are strongly recommended before beginning chemotherapy in the metastatic setting for their predictive role for the efficacy of anti-EGFR monoclonal antibodies. In most of cases, mutational status coincides between primary tumor and metastases. In RAS and BRAF wild-type patients treated with anti-EGFRs, after an induction treatment period, recent evidence supports the role of a maintenance treatment with fluoropyrimidines and anti-EGFRs. However, skin toxicity is the most described and limiting side-effect of maintenance. Moreover, it is described that the continuous administration of these monoclonal antibodies leads to an acquired resistance to anti-EGFRs, with subsequent treatment failure. Intermittent strategy with chemotherapy plus anti-EGFR may help maintain treatment efficacy, delaying resistance.Case presentationIn this case report, we describe the case of a RAS-BRAF wild-type elderly patient undergoing first-line chemotherapy with FOLFOX + panitumumab, reporting response of disease on all metastatic sites except for a node. This node, surgically removed, revealed host BRAF V600 mutant clones. After surgery, patient continued chemotherapy with a stop-and-go strategy continuing to benefit from the same drugs after 4 years since diagnosis, and continuing to achieve response when on treatment, avoiding unacceptable anti-EGFR toxicity. This patient, still alive after 6 years since the diagnosis, represents the case of a good synergy between molecular profiling of disease, surgery, and intermittent treatment.

We previously described three patients affected by metastatic colorectal cancer (mCRC) who experienced spontaneous tumour shrinkage during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Thereafter, the patients were closely monitored and no systemic treatments were applied. Here, we report follow-up clinical information about these patients as well as genetic characterization of their primary tumours through the TruSigt™Oncology 500 Next Generation Sequencing test targeting 523 cancer-relevant genes. An Illumina NovaSeq 6000 platform was used to perform sequencing. Time-to-progression was 23 and 2 months, respectively, in Patients 2 and 3 while it was not reached in Patient 1. Patients 1 and 2 had the greatest anti-SARS-CoV-2 IgG titres. Assessment of genetic landscapes evidenced common mutation in BARD1 gene (p.Val507Met) in Patients 1 and 2. Although our report is descriptive in its nature, we suggest that complex and unexplored interactions between genetic background and components of the immune response to SARS-CoV-2 infection could be responsible of unexpected rare mCRC shrinkage.

Background Nivolumab is an anti-PD-1 antibody approved for treating metastatic melanoma (MM), for which still limited evidence is available on the correlation between drug exposure and patient outcomes.Methods In this observational retrospective study, we assessed whether nivolumab concentration is associated with treatment response in 88 patients with MM and if the patient’s genetic profile plays a role in this association.Results We observed a statistically significant correlation between nivolumab serum concentration and clinical outcomes, measured as overall and progression-free survival. Moreover, patients who achieved a clinical or partial response tended to have higher levels of nivolumab than those who reached stable disease or had disease progression. However, the difference was not statistically significant. In particular, patients who reached a clinical response had a significantly higher concentration of nivolumab and presented a distinct genetic signature, with more marked activation of ICOS and other genes involved in effector T-cells mediated proinflammatory pathways.Conclusions In conclusion, these preliminary results show that in patients with MM, nivolumab concentration correlates with clinical outcomes and is associated with an increased expression of ICOS and other genes involved in the activation of T effectors cells.

Neuroendocrine neoplasms (NENs) are a group of lesions originating from cells of the diffuse neuroendocrine system. NENs may involve different sites, including the gastrointestinal tract (GEP-NENs). The incidence and prevalence of GEP-NENs has been constantly rising thanks to the increased diagnostic power of imaging and immuno–histochemistry. Despite the plethora of biochemical markers and imaging techniques, the prognosis and therapeutic choice in GEP-NENs still represents a challenge, mainly due to the great heterogeneity in terms of tumor lesions and clinical behavior. The concept that biomedical images contain information about tissue heterogeneity and pathological processes invisible to the human eye is now well established. From this substrate comes the idea of radiomics. Computational analysis has achieved promising results in several oncological settings, and the use of radiomics in different types of GEP-NENs is growing in the field of research, yet with conflicting results. The aim of this narrative review is to provide a comprehensive update on the role of radiomics on GEP-NEN management, focusing on the main clinical aspects analyzed by most existing reports: predicting tumor grade, distinguishing NET from other tumors, and prognosis assessment.

Abstract 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.

Abstract Background Radiomics is an emerging field and has a keen interest, especially in the oncology field. The process of a radiomics study consists of lesion segmentation, feature extraction, consistency analysis of features, feature selection, and model building. Manual segmentation is one of the most critical parts of radiomics. It can be time-consuming and suffers from variability in tumor delineation, which leads to the reproducibility problem of calculating parameters and assessing spatial tumor heterogeneity, particularly in large or multiple tumors. Radiomic features provides data on tumor phenotype as well as cancer microenvironment. Radiomics derived parameters, when associated with other pertinent data and correlated with outcomes data, can produce accurate robust evidence based clinical decision support systems. The principal challenge is the optimal collection and integration of diverse multimodal data sources in a quantitative manner that delivers unambiguous clinical predictions that accurately and robustly enable outcome prediction as a function of the impending decisions. Methods The search covered the years from January 2010 to January 2021. The inclusion criterion was: clinical study evaluating radiomics of liver colorectal metastases. Exclusion criteria were studies with no sufficient reported data, case report, review or editorial letter. Results We recognized 38 studies that assessed radiomics in mCRC from January 2010 to January 2021. Twenty were on different tpics, 5 corresponded to most criteria; 3 are review, or letter to editors; so 10 articles were included. Conclusions In colorectal liver metastases radiomics should be a valid tool for the characterization of lesions, in the stratification of patients based on the risk of relapse after surgical treatment and in the prediction of response to chemotherapy treatment.

In recent years, the focus on digital transformation has begun to push companies and society towards an epochal change that will require a complete overhaul of the culture, operations, technologies and value delivery of individual companies and of the entire society worldwide [...]

In recent years, the potential of the metaverse as a tool to connect people has been increasingly recognized. The opportunities offered by the metaverse seem enormous in many sectors and fields of application. However, on the academic side, although a growing number of papers have been found to address the adoption of the metaverse, a clear overview of the solutions in place and their impact on education has been largely neglected so far. In the context of increasing challenges found with the metaverse, this review aims to investigate the role of the metaverse as tool in education. This contribution aims to address this research gap by offering a state-of-the-art analysis of the role the metaverse plays in education in relation to the future of work. The study is based on a systematic review approach performed by means of the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) protocol. The findings of this research help us to better understand the benefits, potential and risks of the metaverse as a tool for immersive and innovative learning experiences. Implications are discussed and streams for future investigation are identified.

Abstract The criteria of economic, social, and environmental sustainability defined by the United Nations and consolidated in Agenda 2030 must become a ‘lighthouse’ to promote the use of digital technologies as an essential tool for sustainable development. Thus, the role of decision makers must therefore be oriented to promote technological development towards a sustainable world. However, any technological innovation, even the best, can give negative effects if not applied with a perspective on sustainability. This is increasingly evident with the growth of globalization. Thus, the aim of the present research is to identify challenges to achieve Circular Economy and Bioeconomy in a digital era and to define a blueprint for a ‘digicircular’ transformation. An integrated and interdisciplinary framework is proposed to prioritize digital capabilities which are hindering the digicircular economy implementation. An interdisciplinary and multicriteria tool to enable a digicircular model is developed. Bloomberg's environmental and Corporate Knights Global Sustainability Score which use private and public information from companies served for define the research model.

Abstract Background To investigate the potential of semiquantitative time-intensity curve parameters compared to textural radiomic features on arterial phase images by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for early prediction of breast cancer neoadjuvant therapy response. Methods A retrospective study of 45 patients subjected to DCE-MRI by public datasets containing examination performed prior to the start of treatment and after the treatment first cycle (‘QIN Breast DCE-MRI’ and ‘QIN-Breast’) was performed. In total, 11 semiquantitative parameters and 50 texture features were extracted. Non-parametric test, receiver operating characteristic analysis with area under the curve (ROC-AUC), Spearman correlation coefficient, and Kruskal-Wallis test with Bonferroni correction were applied. Results Fifteen patients with pathological complete response (pCR) and 30 patients with non-pCR were analysed. Significant differences in median values between pCR patients and non-pCR patients were found for entropy, long-run emphasis, and busyness among the textural features, for maximum signal difference, washout slope, washin slope, and standardised index of shape among the dynamic semiquantitative parameters. The standardised index of shape had the best results with a ROC-AUC of 0.93 to differentiate pCR versus non-pCR patients. Conclusions The standardised index of shape could become a clinical tool to differentiate, in the early stages of treatment, responding to non-responding patients.

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.

Abstract Aim To compare liver-specific EOB-GD-DTPA and liver-non-specific Gd-BT-DO3A MR, in hepatocellular carcinoma (HCC) and liver colorectal metastases. Material and methods Seventy HCC patients with 158 nodules and 90 colorectal liver metastases (mCRC) with 370 lesions were included in the retrospective analysis. HCC patients underwent MR at 0 time (MR0), after 3 (MR3) and 6 months (MR6) using two different CM; 69 mCRC patients underwent MR with Gd-EOB-BTPA and 21 mCRC patients with Gd-BT-DO3A. We evaluated arterial phase hyperenhancement, lesion-to-liver contrast during portal phase, hepatobiliary phase parenchymal hyperenhancement. Results In HCC patients arterial phase hyperenhancement degree was statistically higher (p = 0.03) with Gd-BT-DO3A (mean 4) than GD-EOB-DTPA (mean 2.6), while we found no significant statistical differences among mean (2.6) values at MR0 and MR6 using GD-EOB-DTPA. For all 209 patients underwent Gd-EOB-DTPA, we found that lesion-to-liver contrast during portal phase mean value was 4 while for patients underwent MR with Gd-BT-DO3A was 3 (p = 0.04). For HCC hepatobiliary phase parenchymal hyperenhancement mean value was 2.4. For mCRC patients: among 63 patients underwent previous chemotherapy hepatobiliary phase parenchymal hyperenhancement mean value was 3.1 while for 6 patients no underwent previous chemotherapy was 4 (p = 0.05). Conclusions Gd-EOB-DTPA should be chosen in pre surgical setting in patients with colorectal liver metastases.

Abstract Background Combination of chemotherapies (fluoropirimidines, oxaliplatin and irinotecan) with biologic drugs (bevacizumab, panitumumab, cetuximab) have improved clinical responses and survival of metastatic colorectal cancer (mCRC). However, patients’ selection thorough the identification of predictive factors still represent a challange. Cetuximab (Erbitux®), a chimeric monoclonal antibody binding to the Epidermal Growth Factor Receptor (EGFR), belongs to the Immunoglobulins (Ig) grade 1 subclass able to elicite both in vitro and in vivo the Antibody-Dependent Cell-mediated Cytotoxicity (ADCC). ADCC is the cytotoxic killing of antibody-coated target cells by immunologic effectors. The effector cells express a receptor for the Fc portion of these antibodies (FcγR); genetic polymorphisms of FcγR modify the binding affinity with the Fc of IgG1. Interestingly, the high-affinity FcγRIIIa V/V is associated with increased ADCC in vitro and in vivo. Thus, ADCC could partially account for cetuximab activity. Methods/design CIFRA is a single arm, open-label, phase II study assessing the activity of cetuximab in combination with irinotecan and fluorouracile in FcγRIIIa V/V patients with KRAS, NRAS, BRAF wild type mCRC. The study is designed with a two-stage Simon model based on a hypothetical higher response rate (+ 10%) of FcγRIIIa V/V patients as compared to previous trials (about 60%) assuming ADCC as one of the possible mechanisms of cetuximab action. The test power is 95%, the alpha value of the I-type error is 5%. With these assumptions the sample for passing the first stage is 14 patients with > 6 responses and the final sample is 34 patients with > 18 responses to draw positive conclusions. Secondary objectives include toxicity, responses’ duration, progression-free and overall survival. Furthermore, an associated translational study will assess the patients’ cetuximab-mediated ADCC and characterize the tumor microenvironment. Discussion The CIFRA study will determine whether ADCC contributes to cetuximab activity in mCRC patients selected on an innovative immunological screening. Data from the translational study will support results’ interpretation as well as provide new insights in host-tumor interactions and cetuximab activity. Trial registration The CIFRA trial (version 0.0, June 21, 2018) has been registered into the NIH-US National Library of Medicine, ClinicalTrials.gov database with the identifier number (NCT03874062).

Abstract Background Imaging is an essential tool in the management of patients with Colorectal cancer (CRC) by helping evaluate number and sites of metastases, determine resectability, assess response to treatment, detect drug toxicities and recurrences. Although multidetector computed tomography (MDCT) is the first tool used for staging and patient’s surveillance, magnetic resonance imaging (MRI) is the most reliable imaging modality that allows to assess liver metastases. Our purpose is to compare the diagnostic performance of gadoxetic acid-(Gd-EOB) enhanced liver MRI and contrast-enhanced MDCT in the detection of liver metastasis from colorectal cancer (mCRC). Methods One hundred and twenty-eight patients with pathologically proven mCRC (512 liver metastases) underwent Gd-EOB MRI and MDCT imaging. An additional 46 patients without mCRC were included as control subjects. Three radiologists independently graded the presence of liver nodules on a five-point confidence scale. Sensitivity and specificity for the detection 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 489 liver metastases and MDCT 384. In terms of per-lesion sensitivity in the detection of liver metastasis, all three readers had higher diagnostic sensitivity with Gd-EOB MRI than with MDCT (95.5% vs. 72% reader 1; 90% vs. 72% reader 2; 96% vs. 75% reader 3). Each reader showed a statistical significant difference (p

Herein, we describe three patients affected by metastatic colorectal cancer (mCRC) experiencing infection by severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) and reduction of disease burden during coronavirus disease 2019 (COVID-19) course. Insights into tumor-associated angiotensin-converting enzyme (ACE)-2 expression and lymphocyte function suggest a correlation between host/SARS-Cov-2 infection and tumor burden reduction. This may shed new light into (a) the infection mechanism of SARS-CoV-2 virus and (b) the multiple aspects of a composite antiviral immune response with potential paradoxical and unexpected applications.

Background: The intensive study of predictive factors has strongly ameliorated the therapeutic flow-chart of metastatic colorectal cancer (mCRC) by allowing the selection of patients who benefit from specific therapies. For instance, in mRAS (mutated RAS) mCRC patients, anti-EGFR drugs (cetuximab and panitumumab) are not recommended; in this group of patients, the use of anti-angiogenic drugs (bevacizumab and aflibercept) is predominant. However, at progression to standard bevacizumab-based first-line chemotherapy, still to date, there are no studies to guide oncologists in the choice of the best second-line anti-angiogenic drug (bevacizumab beyond progression versus aflibercept). Methods: ARBITRATION is a prospective, observational study assessing efficacy differences between second-line fluorouracil/irinotecan (FOLFIRI)/bevacizumab versus FOLFIRI/aflibercept at progression to fluoropyrimidines, oxaliplatin and bevacizumab in mRAS mCRC patients. A test power of 80%, a median survival of 9 months from second-line treatment start and a hazard ratio of 0.67 between the two schedules were the basis for statistical design. The final sample will be 220 patients (110 per treatment). The significance will be verified with a two-tailed log-rank test with an alpha value of the I-type error of 5%. Time-to-outcome will be described by Kaplan–Meier curves and prognostic factors studied through multivariable analyses based on the Cox model. Secondary objectives include safety, responses’ duration and progression-free survival. A translational research will be conducted to measure several angiogenic proteins in patients’ serum before starting the therapy in order to evidence any angiogenic factor patterns related to outcome. Discussion: We present a large, prospective, observational study aiming to answer two scientific questions: (1) outcome differences between second-line treatments with FOLFIRI/bevacizumab beyond progression versus FOLFIRI/aflibercept in mRAS mCRC patients, (2) angiogenic factors’ patterns that could associate with efficacy and help oncologists to apply best the therapeutic anti-angiogenic strategies. Trial registration: The ARBITRATION trial (version 0.0, 13 April 2020) has been registered into the clinicaltrials.gov registry on 20 May 2020 with identifier NCT04397601.

Objective: To evaluate the consistency of the quantitative imaging decision support (QIDS TM ) tool and radiomic analysis using 594 metrics in lung carcinoma on chest CT scan. Materials and Methods: We included, retrospectively, 150 patients with histologically confirmed lung cancer who underwent chemotherapy and baseline and follow-ups CT scans. Using the QIDS TM platform, 3 radiologists segmented each lesion and automatically collected the longest diameter and the density mean value. Inter-observer variability, Bland Altman analysis and Spearman’s correlation coefficient were performed. QIDS TM tool consistency was assessed in terms of agreement rate in the treatment response classification. Kruskal Wallis test and the least absolute shrinkage and selection operator (LASSO) method with 10-fold cross validation were used to identify radiomic metrics correlated with lesion size change. Results: Good and significant correlation was obtained between the measurements of largest diameter and of density among the QIDS TM tool and the radiologists measurements. Inter-observer variability values were over 0.85. HealthMyne QIDS TM tool quantitative volumetric delineation was consistent and matched with each radiologist measurement considering the RECIST classification (80-84%) while a lower concordance among QIDS TM and the radiologists CHOI classification was observed (58-63%). Among 594 extracted metrics, significant and robust predictors of RECIST response were energy, histogram entropy and uniformity, Kurtosis, coronal long axis, longest planar diameter, surface, Neighborhood Grey-Level Different Matrix (NGLDM) dependence nonuniformity and low dependence emphasis as Volume, entropy of Log(2.5 mm), wavelet energy, deviation and root man squared. Conclusion: In conclusion, we demonstrated that HealthMyne quantitative volumetric delineation was consistent and that several radiomic metrics extracted by QIDS TM were significant and robust predictors of RECIST response.

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.

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.

This article provides an overview of imaging assessment of ablated pancreatic cancer. Only studies reporting radiological assessment on pancreatic ablated cancer were retained. We found 16 clinical studies that satisfied the inclusion criteria. Radiofrequency ablation and irreversible electroporation have become established treatment modalities because of their efficacy, low complication rates, and availability. Microwave Ablation (MWA) has several advantages over radiofrequency ablation (RFA), which may make it more attractive to treat pancreatic cancer. Electrochemotherapy (ECT) is a very interesting emerging technique, characterized by low complication rate and safety profile. According to the literature, the assessment of the effectiveness of ablative therapies is difficult by means of the Response Evaluation Criteria in Solid Tumors (RECIST) criteria that are not suitable to evaluate the treatment response considering that are related to technique used, the timing of reassessment, and the imaging procedure being used to evaluate the efficacy. RFA causes various appearances on imaging in the ablated zone, correlating to the different effects, such as interstitial edema, hemorrhage, carbonization, necrosis, and fibrosis. Irreversible electroporation (IRE) causes the creation of pores within the cell membrane causing cell death. Experimental studies showed that Diffusion Weigthed Imaging (DWI) extracted parameters could be used to detect therapy effects. No data about functional assessment post MWA is available in literature. Morphologic data extracted by Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) do not allow to differentiate partial, complete, or incomplete response after ECT conversely to functional parameters, obtained with Position Emission Tomography (PET), MRI, and CT.

Background: Despite effective treatments, metastatic colorectal cancer (mCRC) prognosis is still poor, mostly in RAS -mutated tumors, thus suggesting the need for novel combinatorial therapies. Epigenetic alterations play an important role in initiation and progression of cancers, including CRC. Histone-deacetylase inhibitors (HDACi) have shown activity in combination with chemotherapy in the treatment of solid tumors. Owing to its HDACi activity and its safe use for epileptic disorders, valproic acid (VPA) is a good candidate for anticancer therapy that we have largely explored preclinically translating our findings in currently ongoing clinical studies. We have shown in CRC models that HDACi, including VPA, induces synergistic antitumor effects in combination with fluoropyrimidines. Furthermore, unpublished results from our group demonstrated that VPA induces differentiation and sensitization of CRC stem cells to oxaliplatin. Moreover, preclinical and clinical data suggest that HDACi may prevent/reverse anti-angiogenic resistance. Methods/Design: A randomized, open-label, two-arm, multicenter phase-II study will be performed to explore whether the addition of VPA to first line bevacizumab/oxaliplatin/fluoropyrimidine regimens (mFOLFOX-6/mOXXEL) might improve progression-free survival (PFS) in RAS -mutated mCRC patients. A sample size of 200 patients was calculated under the hypothesis that the addition of VPA to chemotherapy/bevacizumab can improve PFS from 9 to 12 months, with one-sided alpha of 0.20 and a power of 0.80. Secondary endpoints are overall survival, objective response rate, metastases resection rate, toxicity, and quality of life. Moreover, the study will explore several prognostic and predictive biomarkers on blood samples, primary tumors, and on resected metastases. Discussion: The “Revolution” study aims to improve the treatment efficacy of RAS -mutated mCRC through an attractive strategy evaluating the combination of VPA with standard cancer treatment. Correlative studies could identify novel biomarkers and could add new insight in the mechanism of interaction between VPA, fluoropyrimidine, oxaliplatin, and bevacizumab. Trial Registration: EudraCT: 2018-001414-15; ClinicalTrials.gov identifier: NCT04310176

Objective To conduct a systematic literature review of imaging techniques and findings in patients with peribiliary liver metastasis. Methods Several electronic datasets were searched from January 1990 to June 2017 to identify studies assessing the use of different imaging techniques for the detection and staging of peribiliary metastases. Results The search identified 44 studies, of which six met the inclusion criteria and were included in the systematic review. Multidetector computed tomography (MDCT) is the technique of choice in the preoperative setting and during the follow-up of patients with liver tumors. However, the diagnostic performance of MDCT for the assessment of biliary tree neoplasms was low compared with magnetic resonance imaging (MRI). Ultrasound (US), without and with contrast enhancement (CEUS), is commonly employed as a first-line tool for evaluating focal liver lesions; however, the sensitivity and specificity of US and CEUS for both the detection and characterization are related to operator expertise and patient suitability. MRI has thus become the gold standard technique because of its ability to provide morphologic and functional data. MRI showed the best diagnostic performance for the detection of peribiliary metastases. Conclusions MRI should be considered the gold standard technique for the radiological assessment of secondary biliary tree lesions.

Background: Despite great technical advances in imaging, such as multidetector computed tomography and magnetic resonance imaging (MRI), diagnosing pancreatic solid lesions correctly remains challenging, due to overlapping imaging features with benign lesions. We wanted to evaluate functional MRI to differentiate pancreatic tumors, peritumoral inflammatory tissue, and normal pancreatic parenchyma by means of dynamic contrast-enhanced MRI (DCE-MRI)-, diffusion kurtosis imaging (DKI)-, and intravoxel incoherent motion model (IVIM) diffusion-weighted imaging (DWI)-derived parameters. Methods: We retrospectively analyzed 24 patients, each with histopathological diagnosis of pancreatic tumor, and 24 patients without pancreatic lesions. Functional MRI was acquired using a 1.5 MR scanner. Peritumoral inflammatory tissue was assessed by drawing regions of interest on the tumor contours. DCE-MRI, IVIM and DKI parameters were extracted. Nonparametric tests and receiver operating characteristic (ROC) curves were calculated. Results: There were statistically significant differences in median values among the three groups observed by Kruskal–Wallis test for the DKI mean diffusivity (MD), IVIM perfusion fraction (fp) and IVIM tissue pure diffusivity (Dt). MD had the best results to discriminate normal pancreas plus peritumoral inflammatory tissue versus pancreatic tumor, to separate normal pancreatic parenchyma versus pancreatic tumor and to differentiate peritumoral inflammatory tissue versus pancreatic tumor, respectively, with an accuracy of 84%, 78%, 83% and area under ROC curve (AUC) of 0.85, 0.82, 0.89. The findings were statistically significant compared with those of other parameters ( p value 0.05 at McNemar’s test). Conclusions: Diffusion parameters, mainly MD by DKI, could be helpful for the differentiation of normal pancreatic parenchyma, perilesional inflammation, and pancreatic tumor.

BackgroundMRI 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.MethodsOne 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.ResultsMRI 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).ConclusionAbbreviated protocol showed the same detection rate than conventional study in detection of liver metastases.

Objective: To predict the risk of metastatic lymph nodes and the tumor grading related to oral tongue squamous cell carcinoma (OTSCC) through the combination of clinical data with radiomics metrics by computed tomography, and to develop a supportive approach in the management of the lymphatic cervical areas, with particular attention to the early stages (T1−T2). Between March 2016 and February 2020, patients with histologically confirmed OTSCC, treated by partial glossectomy and ipsilateral laterocervical lymphadenectomy and subjected to computed tomography (CT) before surgery, were identified by two centers: 81 patients (49 female and 32 male) with 58 years as the median age (range 19–86 years). Univariate analysis with non-parametric tests and multivariate analysis with machine learning approaches were used. Clinical, hematological parameters and radiological features extracted by CT were considered individually and in combination. All clinical parameters showed statistically significant differences (p < 0.05) for the Kruskal−Wallis test when discriminating both the tumor grading and the metastatic lymph nodes. DOI, PLR, SII, and SIRI showed an accuracy of 0.70 (ROC analysis) when identifying the tumor grading, while an accuracy ≥ 0.78 was shown by DOI, NLR, PLR, SII, and SIRI when discriminating metastatic lymph nodes. In the context of the analysis of radiomics metrics, the original_glszm_HighGrayLevelZoneEmphasis feature was selected for identifying the tumor grading (accuracy of 0.70), while the wavelet_HHH_glrlm_LowGrayLevelRunEmphasis predictor was selected for determining metastatic lymph nodes (accuracy of 0.96). Remarkable findings were also obtained when classifying patients with a machine learning approach. Radiomics features alone can predict tumor grading with an accuracy of 0.76 using a logistic regression model, while an accuracy of 0.82 can be obtained by running a CART algorithm through a combination of three clinical parameters (SIRI, DOI, and PLR) with a radiomics feature (wavelet_LLL_glszm_SizeZoneNonUniformityNormalized). In the context of predicting metastatic lymph nodes, an accuracy of 0.94 was obtained using 15 radiomics features in a logistic regression model, while both CART and CIDT achieved an asymptotic accuracy value of 1.00 using only one radiomics feature. Radiomics features and clinical parameters have an important role in identifying tumor grading and metastatic lymph nodes. Machine learning approaches can be used as an easy-to-use tool to stratify patients with early-stage OTSCC, based on the identification of metastatic and non-metastatic lymph nodes.

Abstract Hepatocellular carcinoma (HCC) is one of the most common human solid malignancies worldwide. Although the MRI is the technique that is best adapted to characterize HCC, there is not an agreement regarding the study protocol and even what the role of Diffusion-weighted imaging (DWI). The possibility that imaging study can correlate to histologic grade to selecting the therapeutic strategy would be valuable in helping to direct the proper management of HCC. Apparent Diffusion Coefficient (ADC) and IVIM-derived perfusion fraction (fp) and tissue diffusivity (Dt) values of HCC showed significantly better diagnostic performance in differentiating high-grade HCC from low-grade HCC, and significant correlation was observed between ADC, fp, Dt and histological grade.

Big Data, the Internet of Things, and robotic and augmented realities are just some of the technologies that belong to Industry 4.0. These technologies improve working conditions and increase productivity and the quality of industry production. However, they can also improve life and society as a whole. A new perspective is oriented towards social well-being and it is called Society 5.0. Industry 4.0 supports the transition to the new society, but other drivers are also needed. To guide the transition, it is necessary to identify the enabling factors that integrate Industry 4.0. A conceptual framework was developed in which these factors were identified through a literature review and the analytical hierarchy process (AHP) methodology. Furthermore, the way in which they relate was evaluated with the help of the interpretive structural modeling (ISM) methodology. The proposed framework fills a research gap, which has not yet consolidated a strategy that includes all aspects of Society 5.0. As a result, the main driver, in addition to technology, is international politics.

In women at high/intermediate lifetime risk of breast cancer (BC-LTR), contrast-enhanced magnetic resonance imaging (MRI) added to mammography ± ultrasound (MX ± US) increases sensitivity but decreases specificity. Screening with MRI alone is an alternative and potentially more cost-effective strategy. Here, we describe the study protocol and the characteristics of enrolled patients for MRIB feasibility, multicenter, randomized, controlled trial, which aims to compare MRI alone versus MX+US in women at intermediate breast cancer risk (aged 40–59, with a 15–30% BC-LTR and/or extremely dense breasts). Two screening rounds per woman were planned in ten centers experienced in MRI screening, the primary endpoint being the rate of cancers detected in the 2 arms after 5 years of follow-up. From July 2013 to November 2015, 1254 women (mean age 47 years) were enrolled: 624 were assigned to MX+US and 630 to MRI. Most of them were aged below 50 (72%) and premenopausal (45%), and 52% used oral contraceptives. Among postmenopausal women, 15% had used hormone replacement therapy. Breast and/or ovarian cancer in mothers and/or sisters were reported by 37% of enrolled women, 79% had extremely dense breasts, and 41% had a 15–30% BC-LTR. The distribution of the major determinants of breast cancer risk profiles (breast density and family history of breast and ovarian cancer) of enrolled women varied across centers.