Management of systemic prostate cancer: current algorithm from castration sensitive to castration resistant setting

In recent years, the advanced knowledge of clinical, biological and molecular features of prostate cancer have led to the introduction of new drugs and have allowed the relocation of old drugs in different settings. In this way, the new concepts of systemic disease arise: high risk or high volume vs. low risk and low volume disease castration sensitive prostate cancer (CSPC), diversifying the use of previously approved drugs (CRPC) and opening new scenarios for sequence therapy. The aim of this review is to integrate new developments into the medical management of systemic prostate cancer.

The relationship between radiomics and pathomics in Glioblastoma patients: Preliminary results from a cross-scale association study

Glioblastoma multiforme (GBM) typically exhibits substantial intratumoral heterogeneity at both microscopic and radiological resolution scales. Diffusion Weighted Imaging (DWI) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) are two functional MRI techniques that are commonly employed in clinic for the assessment of GBM tumor characteristics. This work presents initial results aiming at determining if radiomics features extracted from preoperative ADC maps and post-contrast T1 (T1C) images are associated with pathomic features arising from H&E digitized pathology images. 48 patients from the public available CPTAC-GBM database, for which both radiology and pathology images were available, were involved in the study. 91 radiomics features were extracted from ADC maps and post-contrast T1 images using PyRadiomics. 65 pathomic features were extracted from cell detection measurements from H&E images. Moreover, 91 features were extracted from cell density maps of H&E images at four different resolutions. Radiopathomic associations were evaluated by means of Spearman's correlation (ρ) and factor analysis. p values were adjusted for multiple correlations by using a false discovery rate adjustment. Significant cross-scale associations were identified between pathomics and ADC, both considering features (n = 186, 0.45 < ρ < 0.74 in absolute value) and factors (n = 5, 0.48 < ρ < 0.54 in absolute value). Significant but fewer ρ values were found concerning the association between pathomics and radiomics features (n = 53, 0.5 < ρ < 0.65 in absolute value) and factors (n = 2, ρ = 0.63 and ρ = 0.53 in absolute value). The results of this study suggest that cross-scale associations may exist between digital pathology and ADC and T1C imaging. This can be useful not only to improve the knowledge concerning GBM intratumoral heterogeneity, but also to strengthen the role of radiomics approach and its validation in clinical practice as "virtual biopsy", introducing new insights for omics integration toward a personalized medicine approach.

Systematic Review of Parotid Gland Sarcomas: Multi-Variate Analysis of Clinicopathologic Findings, Therapeutic Approaches and Oncological Outcomes That Affect Survival Rate

Simple Summary

Primary sarcomas of the parotid gland are rare malignancies of mesenchymal origin for which there is no generally well-defined treatment guideline. The aim of this study was to analyze, through the review of the literature, the factors affecting the prognosis of patients with primary sarcoma of the parotid gland. Size/extension at the diagnosis and the sarcoma’s histotype were the most important prognostic factors. Multivariate analysis showed that surgery performed on the tumor was the only parameter affecting long-term survival. In particular, total parotidectomy with preservation or, in the most advanced cases, with the sacrifice of facial nerve should be performed at any age independently of tumor histology.

Abstract

The aim of this study was to systematically review the literature of sarcoma of the parotid gland in order to analyze the main factors affecting survival rate. A systematic literature review was performed between January 1990 to November 2021, and 88 patients affected by parotid gland sarcomas were included. The most common histological types were Rhabdomyosarcoma and Synovial Sarcoma. From our review, it emerges that primary sarcomas of the parotid glands are locally aggressive but show low tendency to metastasize to the lymph nodes of the neck and that surgery (i.e., total or radical parotidectomy) is the main approach for their treatment. The global overall survival (OS) is 52% at 5 years and 34.1% at 10 years. The OS for T1, T2, T3, T4 tumor at 5 years of follow up is 80.0%, 66.5%, 56.7% and 33.3%, respectively. Size/extension at the diagnosis and the sarcoma’s histotype are the most important prognostic factors. Multivariate analysis showed that surgery (total or radical parotidectomy) performed on the tumor (p = 0.0008) was the only parameter that significantly affected the OS. Among the other variables, age (younger), use of adjuvant therapy and lymph node metastasis showed borderline significative values (p = 0.05). Our analysis suggests that, when a primitive parotid sarcoma is diagnosed, total or radical parotidectomy should be performed at any age independent of tumor histology. Because regional lymph node metastases from parotid sarcomas are uncommon, alternative strategies (e.g., close follow-up by imaging and evaluation of sentinel lymph nodes) should be pursued before lymph node (selective/radical) dissection.

An Isoenergetic Multifactorial Diet Reduces Pancreatic Fat and Increases Postprandial Insulin Response in Patients With Type 2 Diabetes: A Randomized Controlled Trial

OBJECTIVE

To compare the effect of an isocaloric multifactorial diet with a diet rich in monounsaturated fatty acids (MUFA) and similar macronutrient composition on pancreatic fat (PF) and postprandial insulin response in type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

According to a randomized controlled parallel-group design, 39 individuals with T2D, 35-75 years old, in satisfactory blood glucose control, were assigned to an 8 week isocaloric intervention with a multifactorial diet rich in MUFA, polyunsaturated fatty acids, fiber, polyphenols, and vitamins (n = 18) or a MUFA-rich diet (n = 21). Before/after the intervention, PF content was measured by the proton-density fat fraction using a three-dimensional mDIXON MRI sequence, and plasma insulin and glucose concentrations were measured over a 4 h test meal with a similar composition as the assigned diet.

RESULTS

After 8 weeks, PF significantly decreased after the multifactorial diet (from 15.7 ± 6.5% to 14.1 ± 6.3%; P = 0.024), while it did not change after the MUFA diet (from 17.1 ± 10.1% to 18.6 ± 10.6%; P = 0.139) with a significant difference between diets (P = 0.014). Postprandial glucose response was similar in the two groups. Early postprandial insulin response (incremental postprandial areas under the curve [iAUC0-120]) significantly increased with the multifactorial diet (from 36,340 ± 34,954 to 44,138 ± 31,878 pmol/L/min; P = 0.037), while it did not change significantly in the MUFA diet (from 31,754 ± 18,446 to 26,976 ± 12,265 pmol/L/min; P = 0.178), with a significant difference between diets (P = 0.023). Changes in PF inversely correlated with changes in early postprandial insulin response (r = -0.383; P = 0.023).

CONCLUSIONS

In patients with T2D, an isocaloric multifactorial diet, including several beneficial dietary components, markedly reduced PF. This reduction was associated with an improved postprandial insulin response.

Italian adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB 1.0): development and normative data

BACKGROUND

Neuropsychological testing plays a cardinal role in the diagnosis and monitoring of Alzheimer's disease. A major concern is represented by the heterogeneity of the neuropsychological batteries currently adopted in memory clinics and healthcare centers. The current study aimed to solve this issue.

METHODS

Following the initiative of the University of Washington's National Alzheimer's Coordinating Center (NACC), we presented the Italian adaptation of the Neuropsychological Test Battery of the Uniform Data Set (I-UDSNB). We collected data from 433 healthy Italian individuals and employed regression models to evaluate the impact of demographic variables on the performance, deriving the reference norms.

RESULTS

Higher education and lower age were associated with a better performance in the majority of tests, while sex affected only fluency tests and Digit Span Forward.

CONCLUSIONS

The I-UDSNB offers a valuable and harmonized tool for neuropsychological testing in Italy, to be used in clinical and research settings.

The cortical thickness of the area PF of the left inferior parietal cortex mediates technical-reasoning skills

Most recent research highlights how a specific form of causal understanding, namely technical reasoning, may support the increasing complexity of tools and techniques developed by humans over generations, i.e., the cumulative technological culture (CTC). Thus, investigating the neurocognitive foundations of technical reasoning is essential to comprehend the emergence of CTC in our lineage. Whereas functional neuroimaging evidence started to highlight the critical role of the area PF of the left inferior parietal cortex (IPC) in technical reasoning, no studies explored the links between the structural characteristics of such a brain region and technical reasoning skills. Therefore, in this study, we assessed participants’ technical-reasoning performance by using two ad-hoc psycho-technical tests; then, we extracted from participants’ 3 T T1-weighted magnetic-resonance brain images the cortical thickness (i.e., a volume-related measure which is associated with cognitive performance as reflecting the size, density, and arrangement of cells in a brain region) of all the IPC regions for both hemispheres. We found that the cortical thickness of the left area PF predicts participants’ technical-reasoning performance. Crucially, we reported no correlations between technical reasoning and the other IPC regions, possibly suggesting the specificity of the left area PF in generating technical knowledge. We discuss these findings from an evolutionary perspective, by speculating about how the evolution of parietal lobes may have supported the emergence of technical reasoning in our lineage.

Benralizumab reduces eosinophils and inflammatory markers in patients with severe eosinophilic asthma and chronic rhinosinusitis with nasal polyps: A pilot real-life study

Chronic rhinosinusitis with nasal polyps (CRSwNP) and Severe Eosinophilic Asthma (SEA) are both frequently sustained by eosinophilic inflammation and are probably the manifestation of a unique disease of upper and lower respiratory tract. We retrospectively observed 11 patients with severe CRSwNP and concomitant SEA under add-on therapy with benralizumab evaluating symptoms using Sino Nasal Outcome Test-22 (SNOT-22), Visual Analogue Scale (VAS), and Asthma Control Test (ACT) and Nasal polyp size by endoscopic and radiological score by Nasal Polyp Score (NPS) and Lund-Mackay Score (LMS). At 6 and 12 months, the expression of cationic eosinophil protein (ECP), Interleukin 17 (IL-17), Interferon gamma (INF-γ), and vascular endothelial growth factor (VEGF) was measured by nasal scraping to assess mucosal inflammation. After 12 months of benralizumab treatment, SNOT-22 decreased from 45 (23-97) to 14 (5-53) (p < 0.05), total VAS of rhinologic symptoms decreased from 30 (17-44) to 9 (5-37) (p ≤ 0.01) and ACT score increased from 10 (5-15) to 24 (20-25) (p ≤ 0.01). NPS decreased from 5 (3-6) to 3 (2-4) after 6 months (p < 0.05) and to 2 (2-3) after one year respectively (p <  0.05) and LMS total score from 21 (15-24) to 17 (8-21) (p ≤ 0.01) after 12 months from starting treatment. Nasal mucosa scraping found differences in INF-γ and VEGF expression in patients compared to 10 healthy subjects, with a normalization of these markers during eosinophils depletion induced by benralizumab. This is the first pilot real-life study conducted with an anti-IL5R monoclonal antibody in severe eosinophilic asthma and severe CRSwNP patients showing that this treatment can induce benefit both diseases not only from the clinical, but also from the inflammatory point of view. Moreover, our research pointed out that INF-γ and VEGF may represent potential response biomarker.

Long-term outcomes and quality of life following parotidectomy for benign disease

Objective

Parotidectomy worsens quality of life (QoL) in the short-term, but the long-term impact is unknown. In this study, we analysed the long-term effects of parotidectomy on QoL.

Methods

In this prospective long-term follow-up study, participants were divided into three groups: short-term (ST) follow-up of six weeks, long-term (LT) follow-up of 13 years and short- and long-term (SLT) follow-up. QoL was assessed using the Parotidectomy Outcome Inventory (POI-8). Parotidectomies were classified based on whether the great auricular nerve (GAN) had been preserved or sacrificed.

Results

In total, 164 observations were analysed, 74 in the LT group, 57 in the ST group and 33 in the SLT group. Hypoaesthesia was a major problem and facial palsy was a minor problem. Pain (p < 0.01) and hypoaesthesia (p < 0.001) were significantly lower after 13 years compared with after six weeks, and QoL was higher after 13 years compared with after six weeks (p = 0.04). The disease-specific impairment rate decreased from 70% at short-term follow-up to 30% at long-term follow-up. Removal of the GAN was associated with hypoaesthesia in the ST group (p = 0.028).

Conclusions

Hypoaesthesia has a long-term impact on the QoL, and this should be emphasised during preoperative discussions.

The Present and Future of Allergen Immunotherapy in Personalized Medicine

Allergic diseases are particularly suitable for personalized medicine, because they meet the needs for therapeutic success, which include a known molecular mechanism of the disease, a diagnostic tool for that disease and a treatment that blocks this mechanism. A range of tools is available for personalized allergy diagnosis, including molecular diagnostics, treatable traits and omics (i.e., proteomics, epigenomics, metabolomics, transcriptomics and breathomics), to predict patient response to therapies, detect biomarkers and mediators and assess disease control status. Such tools enhance allergen immunotherapy. Higher diagnostic accuracy results in a significant increase (based on a greater performance achieved with personalized treatment) in efficacy, further increasing the known and unique characteristics of a treatment designed to work on allergy causes.

MRI-Based Radiomic Features Help Identify Lesions and Predict Histopathological Grade of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common form of liver cancer. Radiomics is a promising tool that may increase the value of magnetic resonance imaging (MRI) in the management of HCC. The purpose of our study is to develop an MRI-based radiomics approach to preoperatively detect HCC and predict its histological grade. Thirty-eight HCC patients at staging who underwent axial T2-weighted and dynamic contrast-enhanced MRI (DCE-MRI) were considered. Three-dimensional volumes of interest (VOIs) were manually placed on HCC lesions and normal hepatic tissue (HT) on arterial phase post-contrast images. Radiomic features from T2 images and arterial, portal and tardive post-contrast images from DCE-MRI were extracted by using Pyradiomics. Feature selection was performed using correlation filter, Wilcoxon-rank sum test and mutual information. Predictive models were constructed for HCC differentiation with respect to HT and HCC histopathologic grading used at each step an imbalance-adjusted bootstrap resampling (IABR) on 1000 samples. Promising results were obtained from radiomic prediction models, with best AUCs ranging from 71% to 96%. Radiomics MRI based on T2 and DCE-MRI revealed promising results concerning both HCC detection and grading. It may be a suitable tool for personalized treatment of HCC patients and could also be used to develop new prognostic biomarkers useful for HCC assessment without the need for invasive procedures.

Quantitative MRI Harmonization to Maximize Clinical Impact: The RIN-Neuroimaging Network

Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing. We present the overarching vision that yielded to the constitution of RIN-Neuroimaging Network, a national consortium dedicated to identifying disease and subject-specific in-vivo neuroimaging biomarkers of diverse neurological and neuropsychiatric conditions. This ambitious goal needs efforts toward increasing the diagnostic and prognostic power of advanced MRI data. To this aim, 23 Italian Scientific Institutes of Hospitalization and Care (IRCCS), with technological and clinical specialization in the neurological and neuroimaging field, have gathered together. Each IRCCS is equipped with high- or ultra-high field MRI scanners (i.e., ≥3T) for clinical or preclinical research or has established expertise in MRI data analysis and infrastructure. The actions of this Network were defined across several work packages (WP). A clinical work package (WP1) defined the guidelines for a minimum standard clinical qualitative MRI assessment for the main neurological diseases. Two neuroimaging technical work packages (WP2 and WP3, for clinical and preclinical scanners) established Standard Operative Procedures for quality controls on phantoms as well as advanced harmonized quantitative MRI protocols for studying the brain of healthy human participants and wild type mice. Under FAIR principles, a web-based e-infrastructure to store and share data across sites was also implemented (WP4). Finally, the RIN translated all these efforts into a large-scale multimodal data collection in patients and animal models with dementia (i.e., case study). The RIN-Neuroimaging Network can maximize the impact of public investments in research and clinical practice acquiring data across institutes and pathologies with high-quality and highly-consistent acquisition protocols, optimizing the analysis pipeline and data sharing procedures.

Brain Networks Involved in Depression in Patients with Frontotemporal Dementia and Parkinson’s Disease: An Exploratory Resting-State Functional Connectivity MRI Study

Depression is characterized by feelings of sadness, loss, or anger that may interfere with everyday activities. Such a neuropsychiatric condition is commonly reported in multiple neurodegenerative disorders, which are quite different from each other. This study aimed at investigating the brain networks involved in depression in patients with frontotemporal dementia (FTD) and Parkinson’s disease (PD) as compared to healthy controls (HC). Fifty participants were included in the study: 17 depressed FTD/PD patients; 17 non-depressed FTD/PD patients; and 16 non-depressed HCs matched for age and gender. We used the Beck depression inventory (BDI-II) to measure depression in all groups. On the same day, 3T brain magnetic resonance with structural and resting-state functional sequences were acquired. Differences in resting-state functional connectivity (FC) between depressed and non-depressed patients in all the experimental groups were assessed by using seed-to-seed and network-to-network approaches. We found a significant seed-to-seed hyperconnectivity patterns between the left thalamus and the left posterior temporal fusiform cortex, which differentiated FTD/PD depressed patients from the HCs. Network-to-network analysis revealed a significant hyperconnectivity among the default-mode network (left lateral-parietal region), the medial prefrontal cortex and the left lateral prefrontal cortex (i.e., part of the central executive network). We investigated whether such FC patterns could be related to the underlying neurodegenerative disorder by replicating the analyses with two independent samples (i.e., non-depressed PD and non-depressed FTD patients) and adding clinical parameters as covariates. We found no FC differences in these groups, thus suggesting how the FC pattern we found may signal a common depression-related neural pathway implicated in both the neurocognitive disorders.

Diagnostic and prognostic significance of extracellular vesicles in prostate cancer drug resistance: A systematic review of the literature

BACKGROUND

The clinical behavior of prostate cancer is highly heterogeneous, with most patients diagnosed with localized disease that successfully responds to surgery or radiotherapy. However, a fraction of men relapse after initial treatment because they develop drug resistance. The failure of anticancer drugs leaves resistant cancer cells to survive and proliferate, negatively affecting patient survival. Thus, drug resistance remains a significant obstacle to the effective treatment of prostate cancer patients. In this scenario, the involvement of extracellular vesicles (EVs) in intrinsic and acquired resistance have been reported in several tumors, and accumulating data suggests that their differential content can be used as diagnostic or prognostic factors. Thus, we propose a systematic study of literature to provide a snapshot of the current scenario regarding EVs as diagnostic and prognostic biomarkers resource in resistant prostate cancer.

METHODS

We performed the current systematic review according to PRISMA guidelines and comprehensively explored PubMed, EMBASE and Google Scholar databases to achieve the article search.

RESULTS

Thirty-three studies were included and investigated. Among all systematically reviewed EV biomarkers, we found mainly molecules with prognostic significance (61%), molecules with diagnostic relevance (18%), and molecules that serve both purposes (21%). Moreover, among all analyzed molecules isolated from EVs, proteins, mRNAs, and miRNAs emerged to be the most investigated and proposed as potential tools to diagnose or predict resistance/sensitivity to advanced PCa treatments.

DISCUSSION

Our analysis provides a snapshot of the current scenario regarding EVs as potential clinical biomarkers in resistant PCa. Nevertheless, despite many efforts, the use of EV biomarkers in PCa is currently at an early stage: none of the selected EV biomarkers goes beyond preclinical studies, and their translatability is yet far from clinical settings.

Correlation between olfactory function, age, sex, and cognitive reserve index in the Italian population

Purpose

Loss of smell decreases the quality of life and contributes to the failure in recognizing hazardous substances. Given the relevance of olfaction in daily life, it is important to recognize an undiagnosed olfactory dysfunction to prevent these possible complications. Up to now, the prevalence of smell disorders in Italy is unknown due to a lack of epidemiological studies. Hence, the primary aim of this study was to evaluate the prevalence of olfactory dysfunction in a sample of Italian adults.

Methods

Six hundred and thirty-three participants (347 woman and 286 men; mean age 44.9 years, SD 17.3, age range 18–86) were recruited from 10 distinct Italian regions. Participants were recruited using a convenience sapling and were divided into six different age groups: 18–29 years (N = 157), 30–39 years (N = 129), 40–49 years (N = 99), 50–59 years (N = 106), > 60 years (N = 142). Olfactory function, cognitive abilities, cognitive reserve, and depression were assessed, respectively, with: Sniffin’ Sticks 16-item Odor Identification Test, Montreal Cognitive Assessment, Cognitive Reserve Index, and the Beck Depression Inventory. Additionally, socio-demographic data, medical history, and health-related lifestyle information were collected.

Results

About 27% of participants showed an odor identification score < 12 indicating hyposmia. Multiple regression analysis revealed that OI was significantly correlated with age, sex, and cognitive reserve index, and young women with high cognitive reserve index showing the highest olfactory scores.

Conclusion

This study provides data on the prevalence of olfactory dysfunction in different Italian regions.

Evaluation of a Whole-Liver Dixon-Based MRI Approach for Quantification of Liver Fat in Patients with Type 2 Diabetes Treated with Two Isocaloric Different Diets

Dixon-based methods for the detection of fatty liver have the advantage of being non-invasive, easy to perform and analyze, and to provide a whole-liver coverage during the acquisition. The aim of the study was to assess the feasibility of a whole-liver Dixon-based approach for liver fat quantification in type 2 diabetes (T2D) patients who underwent two different isocaloric dietary treatments: a diet rich in monosaturated fatty acids (MUFA) and a multifactorial diet. Thirty-nine T2D patients were randomly assigned to MUFA diet (n = 21) and multifactorial diet (n = 18). The mean values of the proton density fat fraction (PDFF) over the whole liver and over the ROI corresponding to that chosen for MRS were compared to MRS-PDFF using Spearman’s correlation (ρ). Before–after changes in percentage of liver volume corresponding to MRI-PDFF above thresholds associated with hepatic steatosis (LV%TH, with TH = 5.56%, 7.97% and 8.8%) were considered to assess the proposed approach and compared between diets using Wilcoxon rank-sum test. Statistical significance set at p < 0.05. A strong linear relationship was found between MRS-PDFF and MRI-PDFFs (ρ = 0.85, p < 0.0001). Changes in LV%TH% were significantly higher (p < 0.05) in the multifactorial diet than in MUFA diet (25% vs. 9%, 35% vs. 12%, and 38% vs. 13% decrease, respectively, for TH = 5.56%, 7.97%, and 8.8%) and this was reproducible compared to results obtained using the standard liver fat analysis. A volumetric approach based on Dixon method could be an effective, non-invasive technique that could be used for the quantitative analysis of hepatic steatosis in T2D patients.

Self-Reported Sleep Quality Across Age Modulates Resting-State Functional Connectivity in Limbic and Fronto-Temporo-Parietal Networks: An Exploratory Cross-Sectional fMRI Study

Sleep problems are increasingly present in the general population at any age, and they are frequently concurrent with—or predictive of—memory disturbances, anxiety, and depression. In this exploratory cross-sectional study, 54 healthy participants recruited in Naples (Italy; 23 females; mean age = 37.1 years, range = 20–68) completed the Pittsburgh Sleep Quality Index (PSQI) and a neurocognitive assessment concerning both verbal and visuospatial working memory as well as subjective measures of anxiety and depression. Then, 3T fMRI images with structural and resting-state functional sequences were acquired. A whole-brain seed-to-seed functional connectivity (FC) analysis was conducted by contrasting good (PSQI score <5) vs. bad (PSQI score ≥5) sleepers. Results highlighted FC differences in limbic and fronto-temporo-parietal brain areas. Also, bad sleepers showed an anxious/depressive behavioural phenotype and performed worse than good sleepers at visuospatial working-memory tasks. These findings may help to reveal the effects of sleep quality on daily-life cognitive functioning and further elucidate pathophysiological mechanisms of sleep disorders.

Editorial: State of the Art CT and Image Quality, Radiation and Contrast Dose

A special issue of the journal Dose-Response entitled “State of the Art CT and Image Quality, Radiation and Contrast Dose” is proposed. Technological improvements on CT scanners have the potentiality to reduce the issues related to ionizing radiation administration, opening new insights toward innovative applications also thanks to the contamination of other research fields like artificial intelligence algorithms and additive manufacturing technologies. In order to approach these new research directions, a multidisciplinary team becomes needed, overcoming the clinical and radiological point of view and enriching the workflow with different contributes. The real weight of these afferents on patient’s management remains to be assessed and characterized. The main topics will be related to innovative CT applications able to improve patient management and treatment assessment and reduce patients risks due to radiation exposure and iodinated contrast injection.

Evaluation of AI-Based Segmentation Tools for COVID-19 Lung Lesions on Conventional and Ultra-low Dose CT Scans

A reliable diagnosis and accurate monitoring are pivotal steps for treatment and prevention of COVID-19. Chest computed tomography (CT) has been considered a crucial diagnostic imaging technique for the injury assessment of the viral pneumonia. Furthermore, the automatization of the segmentation methods for lung alterations helps to speed up the diagnosis and lighten radiologists' workload. Considering the assiduous pathology monitoring, ultra-low dose (ULD) chest CT protocols have been implemented to drastically reduce the radiation burden. Unfortunately, the available AI technologies have not been trained on ULD-CT data and validated and their applicability deserves careful evaluation. Therefore, this work aims to compare the results of available AI tools (BCUnet, CORADS AI, NVIDIA CLARA Train SDK and CT Pneumonia Analysis) on a dataset of 73 CT examinations acquired both with conventional dose (CD) and ULD protocols. COVID-19 volume percentage, resulting from each tool, was statistically compared. This study demonstrated high comparability of the results on CD-CT and ULD-CT data among the four AI tools, with high correlation between the results obtained on both protocols (R > .68, P < .001, for all AI tools).

Cardiac Magnetic Resonance with Delayed Enhancement of the Right Ventricle in patients with Left Ventricle primary involvement: diagnosis and evaluation of functional parameters

Cardiac Magnetic Resonance (CMR) allows an accurate Right Ventricle (RV) assessment that could be of great relevance in diseases causing inflammation or fibrosis. The aim of this study was to evaluate the concomitant involvement of the RV in patients with delayed enhancement (DE) of the Left Ventricle (LV-DE) using CMR. We retrospectively enrolled 95 (male n. 66; age 55±18years; BMI 26±5kg/m2) consecutive patients with LV-DE who underwent a CMR (Achieva 1.5 T, Philips) for different indications: post-ischemic dilated cardiopathy (PDM), hypertrophic cardiomyopathy (HCM), myocardial infarction (MI), myocarditis/pericarditis (MP) and congenital heart disease (CD). We assessed the presence and extension of DE and functional parameters such as ventricular end-diastolic (EDV), end-systolic volumes (ESV) and ejection fraction (EF) of both LV and RV. Prevalence of RV-DE was 30.5% (29/95): 75% (3/4) for CD, 44% (4/9) for PDM, 36% (17/47) for MI, 27.8% (5/18) for MP and 0% (0/17) for HCM. LV-EF and RV-EF were 53±15mL and 51±13mL, respectively, for patients without RV-DE (RV-DE-), and 40±19 mL and 42±15 mL, respectively, for patients with RV-DE (RV-DE+) (p<0.05), while LV-EDV and LV-ESV were 80±28 mL and 40±26 mL, respectively, for RV-DE- and 100±45 mL and 65±49 mL, respectively, for RV-DE+ (p<0.05). The prevalence of RV-DE in patients with LV primary involvement is not negligible and it is found mainly in patients with CD and PDM and then in patients with MI and MP. It is more often associated with LV-EF and RV-EF reduction and increase in LV volumes.

Advances in chronic rhinosinusitis in 2020 and 2021

Major progress has been achieved in the understanding and clinical practice of chronic rhinosinusitis, with or without nasal polyps. These advances resulted in a better understanding of the pathophysiology, the distribution into subgroups, and consequently in a better management perspective using classical approaches and biologics. Pathomechanisms, endotypes and biomarkers, and finally innovative therapeutic approaches are themes especially for the more severe forms of chronic rhinosinusitis, those with uncontrolled severe nasal polyps. Biologicals against key type 2 cytokines are gaining ground in the long-term treatment approaches of often recurrent nasal polyps, and should be integrated in care pathways making use of classical and innovative treatment pathways. These areas of interest show a fast development and will profoundly change our disease management within a decade.

Early Diagnosis of Multiple Sclerosis Using Swept-Source Optical Coherence Tomography and Convolutional Neural Networks Trained with Data Augmentation

BACKGROUND

The aim of this paper is to implement a system to facilitate the diagnosis of multiple sclerosis (MS) in its initial stages. It does so using a convolutional neural network (CNN) to classify images captured with swept-source optical coherence tomography (SS-OCT).

METHODS

SS-OCT images from 48 control subjects and 48 recently diagnosed MS patients have been used. These images show the thicknesses (45 × 60 points) of the following structures: complete retina, retinal nerve fiber layer, two ganglion cell layers (GCL+, GCL++) and choroid. The Cohen distance is used to identify the structures and the regions within them with greatest discriminant capacity. The original database of OCT images is augmented by a deep convolutional generative adversarial network to expand the CNN's training set.

RESULTS

The retinal structures with greatest discriminant capacity are the GCL++ (44.99% of image points), complete retina (26.71%) and GCL+ (22.93%). Thresholding these images and using them as inputs to a CNN comprising two convolution modules and one classification module obtains sensitivity = specificity = 1.0.

CONCLUSIONS

Feature pre-selection and the use of a convolutional neural network may be a promising, nonharmful, low-cost, easy-to-perform and effective means of assisting the early diagnosis of MS based on SS-OCT thickness data.

Radiogenomics and Artificial Intelligence Approaches Applied to Cardiac Computed Tomography Angiography and Cardiac Magnetic Resonance for Precision Medicine in Coronary Heart Disease: A Systematic Review

The risk of coronary heart disease (CHD) clinical manifestations and patient management is estimated according to risk scores accounting multifactorial risk factors, thus failing to cover the individual cardiovascular risk. Technological improvements in the field of medical imaging, in particular, in cardiac computed tomography angiography and cardiac magnetic resonance protocols, laid the development of radiogenomics. Radiogenomics aims to integrate a huge number of imaging features and molecular profiles to identify optimal radiomic/biomarker signatures. In addition, supervised and unsupervised artificial intelligence algorithms have the potential to combine different layers of data (imaging parameters and features, clinical variables and biomarkers) and elaborate complex and specific CHD risk models allowing more accurate diagnosis and reliable prognosis prediction. Literature from the past 5 years was systematically collected from PubMed and Scopus databases, and 60 studies were selected. We speculated the applicability of radiogenomics and artificial intelligence through the application of machine learning algorithms to identify CHD and characterize atherosclerotic lesions and myocardial abnormalities. Radiomic features extracted by cardiac computed tomography angiography and cardiac magnetic resonance showed good diagnostic accuracy for the identification of coronary plaques and myocardium structure; on the other hand, few studies exploited radiogenomics integration, thus suggesting further research efforts in this field. Cardiac computed tomography angiography resulted the most used noninvasive imaging modality for artificial intelligence applications. Several studies provided high performance for CHD diagnosis, classification, and prognostic assessment even though several efforts are still needed to validate and standardize algorithms for CHD patient routine according to good medical practice.

Rhinoplasty Pre-Surgery Models by Using Low-Dose Computed Tomography, Magnetic Resonance Imaging, and 3D Printing

Rhinoplasty and surgical reconstruction of cartilaginous structures still remain a great challenge today. This study aims to identify an imaging strategy in order to merge the information from CT scans and magnetic resonance imaging (MRI) acquisitions and build a 3D printed model true to the patient's anatomy, for better surgical planning. Using MRI, information can be obtained about the cartilage structures of which the nose is composed. Ten rhinoplasty candidate patients underwent both a low-dose protocol CT scan and a specific MRI for characterization of nasal structures. Bone and soft tissue segmentations were performed in CT, while cartilage segmentations were extrapolated from MRI and validated by both an expert radiologist and surgeon. Subsequently, a 3D model was produced in materials and colors reproducing the density of the three main structures (bone, soft tissue, and cartilage), useful for pre-surgical evaluation. This study has highlighted that the optimization of a CT and MR dedicated protocol has allowed to reduce the CT radiation dose up to 60% compared to standard acquisitions with the same machine, and MR acquisition time of about 20%. Patient-tailored 3D models and pre-surgical planning have reduced the mean operative time by 20 minutes.

A Systematic Review on the Role of the Perfusion Computed Tomography in Abdominal Cancer

Background and purpose

Perfusion Computed Tomography (CTp) is an imaging technique which allows quantitative and qualitative evaluation of tissue perfusion through dynamic CT acquisitions. Since CTp is still considered a research tool in the field of abdominal imaging, the aim of this work is to provide a systematic summary of the current literature on CTp in the abdominal region to clarify the role of this technique for abdominal cancer applications.

Materials and Methods

A systematic literature search of PubMed, Web of Science, and Scopus was performed to identify original articles involving the use of CTp for clinical applications in abdominal cancer since 2011. Studies were included if they reported original data on CTp and investigated the clinical applications of CTp in abdominal cancer.

Results

Fifty-seven studies were finally included in the study. Most of the included articles (33/57) dealt with CTp at the level of the liver, while a low number of studies investigated CTp for oncologic diseases involving UGI tract (8/57), pancreas (8/57), kidneys (3/57), and colon–rectum (5/57).

Conclusions

Our study revealed that CTp could be a valuable functional imaging tool in the field of abdominal oncology, particularly as a biomarker for monitoring the response to anti-tumoral treatment.

Structural Brain Network Reproducibility: Influence of Different Diffusion Acquisition and Tractography Reconstruction Schemes on Graph Metrics

Background: Graph metrics of structural brain networks demonstrate to be a powerful tool for investigating brain topology at a large scale. However, the variability of the results related to applying different magnetic resonance acquisition schemes and tractography reconstruction techniques is not fully characterized. Materials and Methods: The present work aims to evaluate the influence of different combinations of diffusion acquisition schemes (single and multishell), diffusion models (tensor and spherical deconvolution), and tractography reconstruction approaches (deterministic and probabilistic) on the reproducibility of graph metrics derived from structural connectome on test/retest (TRT) data released by the Human Connectome Project. From each implemented experimental setup, both global and local graph metrics were evaluated and their reproducibility was estimated by the intraclass correlation coefficient (ICC). Moreover, the percentage relative standard deviation (pRSD) from the ICC values of local graph metrics was calculated to quantify how much the reproducibility varied across nodes within each experimental setup. Results: The presented results show that different combinations of diffusion acquisition schemes, diffusion models, and tractography algorithms can strongly affect the reproducibility of global and local graph metrics. The combination of constrained spherical deconvolution (CSD) and deterministic tractography gave generally high reproducibility (ICCs >0.75) and lowest pRSD for the considered graph metrics, meanwhile probabilistic CSD with a high b-value returned the highest reproducibility. Notably, the introduction of streamline selection filters on CSD can substantially affect the reproducibility. Discussion: This work demonstrates that the TRT reproducibility of graph metrics is generally high but can vary substantially with different combinations of acquisition and reconstruction schemes. Impact statement This work demonstrates the influence of different diffusion acquisition schemes, diffusion models, and tractography reconstruction approaches on the reproducibility of graph metrics derived from structural connectome. The presented findings impact on the choice of both acquisition protocol and processing pipeline for topological analyses to produce reproducible measurements for brain network studies.

Diffusion tensor imaging for the study of early renal dysfunction in patients affected by bardet-biedl syndrome

Kidney structural abnormalities are common features of Bardet-Biedl syndrome (BBS) patients that lead to a progressive decline in renal function. Magnetic resonance diffusion tensor imaging (DTI) provides useful information on renal microstructures but it has not been applied to these patients. This study investigated using DTI to detect renal abnormalities in BBS patients with no overt renal dysfunction. Ten BBS subjects with estimated glomerular filtration rates over 60 ml/min/1.73m² and 14 individuals matched for age, gender, body mass index and renal function were subjected to high-field DTI. Fractional anisotropy (FA), and mean, radial and axial diffusivity were evaluated from renal cortex and medulla. Moreover, the corticomedullary differentiation of each DTI parameter was compared between groups. Only cortical FA statistically differed between BBS patients and controls (p = 0.033), but all the medullary DTI parameters discriminated between the two groups with lower FA (p < 0.001) and axial diffusivity (p = 0.021) and higher mean diffusivity (p = 0.043) and radial diffusivity (p < 0.001) in BBS patients compared with controls. Corticomedullary differentiation values were significantly reduced in BBS patients. Thus, DTI is a valuable tool for investigating microstructural alterations in renal disorders when kidney functionality is preserved.

Impact of radiogenomics in esophageal cancer on clinical outcomes: A pilot study

BACKGROUND

Esophageal cancer (ESCA) is the sixth most common malignancy in the world, and its incidence is rapidly increasing. Recently, several microRNAs (miRNAs) and messenger RNA (mRNA) targets were evaluated as potential biomarkers and regulators of epigenetic mechanisms involved in early diagnosis. In addition, computed tomography (CT) radiomic studies on ESCA improved the early stage identification and the prediction of response to treatment. Radiogenomics provides clinically useful prognostic predictions by linking molecular characteristics such as gene mutations and gene expression patterns of malignant tumors with medical images and could provide more opportunities in the management of patients with ESCA.

AIM

To explore the combination of CT radiomic features and molecular targets associated with clinical outcomes for characterization of ESCA patients.

METHODS

Of 15 patients with diagnosed ESCA were included in this study and their CT imaging and transcriptomic data were extracted from The Cancer Imaging Archive and gene expression data from The Cancer Genome Atlas, respectively. Cancer stage, history of significant alcohol consumption and body mass index (BMI) were considered as clinical outcomes. Radiomic analysis was performed on CT images acquired after injection of contrast medium. In total, 1302 radiomics features were extracted from three-dimensional regions of interest by using PyRadiomics. Feature selection was performed using a correlation filter based on Spearman’s correlation (ρ) and Wilcoxon-rank sum test respect to clinical outcomes. Radiogenomic analysis involved ρ analysis between radiomic features associated with clinical outcomes and transcriptomic signatures consisting of eight N6-methyladenosine RNA methylation regulators and five up-regulated miRNA. The significance level was set at P < 0.05.

RESULTS

Of 25, five and 29 radiomic features survived after feature selection, considering stage, alcohol history and BMI as clinical outcomes, respectively. Radiogenomic analysis with stage as clinical outcome revealed that six of the eight mRNA regulators and two of the five up-regulated miRNA were significantly correlated with ten and three of the 25 selected radiomic features, respectively (-0.61 < ρ < -0.60 and 0.53 < ρ < 0.69, P < 0.05). Assuming alcohol history as clinical outcome, no correlation was found between the five selected radiomic features and mRNA regulators, while a significant correlation was found between one radiomic feature and three up-regulated miRNAs (ρ = -0.56, ρ = -0.64 and ρ = 0.61, P < 0.05). Radiogenomic analysis with BMI as clinical outcome revealed that four mRNA regulators and one up-regulated miRNA were significantly correlated with 10 and two radiomic features, respectively (-0.67 < ρ < -0.54 and 0.53 < ρ < 0.71, P < 0.05).

CONCLUSION

Our study revealed interesting relationships between the expression of eight N6-methyladenosine RNA regulators, as well as five up-regulated miRNAs, and CT radiomic features associated with clinical outcomes of ESCA patients.

How to predict the outcome of septorhinoplasty? A normative study of ROE and FROI-17 scores

Objective

Normative values of patient-reported outcome instruments are needed to identify good candidates for rhinoplasty. Rhinoplasty Outcome Evaluation (ROE) and Functional Rhinoplasty Outcome Inventory-17 (FROI-17) are disease-specific questionnaires that evaluate quality of life in patients undergoing rhinoplasty.

Methods

The reference cohort contained 1,000 participants, selected from a non-probability panel. Normative ROE and FROI-17 scores from this reference cohort were compared with ROE and FROI-17 scores from a patient cohort before (n = 104) and 6 (n = 55) and 12 months (n = 32) after septorhinoplasty.

Results

Mean FROI-17 scores (± SD) were: overall score, 20.8 ± 17; nasal symptoms, 16.8 ± 7; general symptoms, 24.8 ± 22; and self-confidence, 16.4 ± 21. The ROE total score was 73.1 ± 16. Normative values differed significantly from the preoperative ROE and FROI-17 scores of septorhinoplasty patients (p < 0.01). Except for the FROI-17 general score at 12 months postoperatively (p = 0.004), there were no significant differences between normative ROE/FROI-17 and septorhinoplasty scores postoperatively, indicating that they returned to normalcy.

Conclusions

Normative scores for ROE and FROI-17 provide a reference point from which to identify patients who are most likely to benefit from rhinoplasty.

A quantitative analysis of the retinofugal projections in congenital and late-onset blindness

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Congenital (CB) and late blind (LB) affects the integrity brain visual structures.

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We measured the integrity of the retino-fugal system using structural MRI images.

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Optic nerve, optic tract, optic chiasm and LGN were reduced by 50 to 60% in CB and LB.

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There were no differences between CB and LB.

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In LB, optic nerve volume correlated negatively with blindness duration.

Vision loss early in life has dramatic consequences on the organization of the visual system and hence on structural plasticity of its remnant components. Most of the studies on the anatomical changes in the brain following visual deprivation have focused on the re-organization of the visual cortex and its afferent and efferent projections. In this study, we performed a quantitative analysis of the volume and size of the optic chiasm, optic nerve, optic tract and the lateral geniculate nucleus (LGN), the retino recipient thalamic nucleus. Analysis was carried out on structural T1-weighted MRIs from 22 congenitally blind (CB), 14 late blind (LB) and 29 age -and sex-matched sighted control (SC) subjects. We manually segmented the optic nerve, optic chiasm and optic tract, while LGN volumes were extracted using in-house software. We also measured voxel intensity of optic nerve, optic chiasm and optic tract. Mean volumes of the optic nerve, optic tract and optic chiasm were reduced by 50 to 60% in both CB and LB participants. No significant differences were found between the congenitally and late-onset blind participants for any of the measures. Our data further revealed reduced white matter voxel intensities in optic nerve, optic chiasm and optic tract in blind compared to sighted participants, suggesting decreased myelin content in the atrophied white matter. The LGN was reduced by 50% and 44% in CB and LB, respectively. In LB, optic nerve volume correlated negatively with the blindness duration index; no such correlation was found for optic chiasm, optic tract and LGN. The observation that despite the absence of visual input about half of the subcortical retinofugal projections are structurally preserved raises the question of their functional role. One possibility is that the surviving fibers play a role in the maintenance of circadian rhythms in the blind through the intrinsically photosensitive melanopsin-containing retinal ganglion cells.

Identifying a Common Functional Framework for Apathy Large-Scale Brain Network

Apathy is a neuropsychiatric condition characterized by reduced motivation, initiative, and interest in daily life activities, and it is commonly reported in several neurodegenerative disorders. The study aims to investigate large-scale brain networks involved in apathy syndrome in patients with frontotemporal dementia (FTD) and Parkinson’s disease (PD) compared to a group of healthy controls (HC). The study sample includes a total of 60 subjects: 20 apathetic FTD and PD patients, 20 non apathetic FTD and PD patients, and 20 HC matched for age. Two disease-specific apathy-evaluation scales were used to measure the presence of apathy in FTD and PD patients; in the same day, a 3T brain magnetic resonance imaging (MRI) with structural and resting-state functional (fMRI) sequences was acquired. Differences in functional connectivity (FC) were assessed between apathetic and non-apathetic patients with and without primary clinical diagnosis revealed, using a whole-brain, seed-to-seed approach. A significant hypoconnectivity between apathetic patients (both FTD and PD) and HC was detected between left planum polare and both right pre- or post-central gyrus. Finally, to investigate whether such neural alterations were due to the underlying neurodegenerative pathology, we replicated the analysis by considering two independent patients’ samples (i.e., non-apathetic PD and FTD). In these groups, functional differences were no longer detected. These alterations may subtend the involvement of neural pathways implicated in a specific reduction of information/elaboration processing and motor outcome in apathetic patients.

Advanced/metastatic bladder cancer: current status and future directions

In 2015 bladder cancer was the fourth most frequent malignancy and the eighth cause of death for cancer. At diagnosis, about 30% of bladder cancer (BC) patients present a muscle-invasive bladder cancer (MIBC) and 5% a metastatic bladder carcinoma (MBC). For fit MBC patients, combination chemotherapy (CC) is the standard of care for first-line treatment. CC includes both the treatment with methotrexate, vinblastine, doxorubicin, and cisplatin (MVAC) either the classical or the dose-dense MVAC regimen, and the doublet therapy with cisplatin and gemcitabine (CG). Median progression free survival (PFS) was 7 months and median overall survival (OS) was 15 months. The present review provides an update on the management of MBC, with focus on target therapies, immune checkpoint inhibition, looking for prognostic and predictive factors.

Clinical connectome fingerprints of cognitive decline

Brain connectome fingerprinting is rapidly rising as a novel influential field in brain network analysis. Yet, it is still unclear whether connectivity fingerprints could be effectively used for mapping and predicting disease progression from human brain data. We hypothesize that dysregulation of brain activity in disease would reflect in worse subject identification. We propose a novel framework, Clinical Connectome Fingerprinting, to detect individual connectome features from clinical populations. We show that "clinical fingerprints" can map individual variations between elderly healthy subjects and patients with mild cognitive impairment in functional connectomes extracted from magnetoencephalography data. We find that identifiability is reduced in patients as compared to controls, and show that these connectivity features are predictive of the individual Mini-Mental State Examination (MMSE) score in patients. We hope that the proposed methodology can help in bridging the gap between connectivity features and biomarkers of brain dysfunction in large-scale brain networks.

Investigating Dual-Energy CT Post-Contrast Phases for Liver Iron Quantification: A Preliminary Study

Background and Purpose:

Quantification of hepatic virtual iron content (VIC) by using Multidetector Dual Energy Computed Tomography (DECT) has been recently investigated since this technique could offer a good compromise between accuracy and non-invasiveness for liver iron content quantification. The aim of our study is to investigate differences in VIC at different DECT time points (namely baseline and arterial, venous and tardive phases), identifying the most reliable and also exploring the underlying temporal trend of these values.

Materials and Methods:

Eleven patients who underwent DECT examination and were characterized by low liver fat content were included in this retrospective study. By using the Syngo.via Frontier–DE IronVNC tool, regions of interest (ROI) were placed on the VIC images at 3 hepatic levels, both in left and right liver lobes, at each DECT time point. Friedman’s test followed by Bonferroni-adjusted Wilcoxon signed-rank test for post-hoc analysis was performed to assess differences between DECT timepoints. Page’s L test was performed to test the temporal trend of VIC across the 4 examined timepoints.

Results:

For both liver lobes, Friedman’s test followed by Bonferroni-adjusted Wilcoxon signed-rank test revealed that VIC values differed significantly when extracted from ROIs placed at the 4 different timepoints. The Page’s L test for multiple comparison revealed a significant growing trend for VIC, from baseline acquisition to the fourth and last time point post-contrast agent injection.

Conclusions:

The extraction of hepatic VIC in healthy subjects was found to be significantly influenced by the DECT time point chosen for the extrapolation of the VIC values.

Machine learning and network medicine: a novel approach for precision medicine and personalized therapy in cardiomyopathies

The early identification of pathogenic mechanisms is essential to predict the incidence and progression of cardiomyopathies and to plan appropriate preventive interventions. Noninvasive cardiac imaging such as cardiac computed tomography, cardiac magnetic resonance, and nuclear imaging plays an important role in diagnosis and management of cardiomyopathies and provides useful prognostic information. Most molecular factors exert their functions by interacting with other cellular components, thus many diseases reflect perturbations of intracellular networks. Indeed, complex diseases and traits such as cardiomyopathies are caused by perturbations of biological networks. The network medicine approach, by integrating systems biology, aims to identify pathological interacting genes and proteins, revolutionizing the way to know cardiomyopathies and shifting the understanding of their pathogenic phenomena from a reductionist to a holistic approach. In addition, artificial intelligence tools, applied to morphological and functional imaging, could allow imaging scans to be automatically analyzed to extract new parameters and features for cardiomyopathy evaluation. The aim of this review is to discuss the tools of network medicine in cardiomyopathies that could reveal new candidate genes and artificial intelligence imaging-based features with the aim to translate into clinical practice as diagnostic, prognostic, and predictive biomarkers and shed new light on the clinical setting of cardiomyopathies. The integration and elaboration of clinical habits, molecular big data, and imaging into machine learning models could provide better disease phenotyping, outcome prediction, and novel drug targets, thus opening a new scenario for the implementation of precision medicine for cardiomyopathies.

ECG-gated multislice Computed Tomography angiography as a comprehensive non-invasive imaging tool in patient with aortic coarctation

We describe a case of a 52-year-old-woman with aortic coarctation demonstrated by means of 40-slice MSCT angiography. Based on the information extracted from MSCT it was possible to display the anatomical configuration of the disease, the thoraco-abdominal collateral pathways. The best therapeutic approach was established on the basis of MSCT findings. MSCT is a reliable and comprehensive tool for the assessment of adult patients with aortic coarctation. (www.actabiomedica.it)

Cerebral microstructural abnormalities in impulsivity: a magnetic resonance study

Studies that investigated neurobiological parameters subtended to impulsivity trait found their relationship with structural and functional brain alterations. No studies investigated the white matter microstructural attributes of impulsivity in a large sample of healthy subjects. In the present study 1007 subjects from Human Connectome Project public dataset were divided in two groups, impulsive and not impulsive, basing on Delay Discounting task score. For both groups brain morphometric and microstructural characteristics were investigated. A t-test (correct for multiple comparisons) was performed for each brain parcel and impulsivity measure. Magnetic resonance diffusion images were pre-processed and selected to perform a voxelwise analysis on the fractional anisotropy (FA) maps between impulsive and not impulsive groups. Group analysis showed significant differences in morphometric brain data mainly for temporal and frontal lobes. The impulsive group presented higher FA values in four regions: bilateral medial lemniscus and midbrain reticular formation, right superior longitudinal fasciculus, left forceps major, right corticospinal tract. Not impulsive group showed higher FA values in two significant regions: right and left anterior thalamus radiation. Concluding, macroscopic and microstructural brain alterations were assessed, identifying new neuroanatomical substrates for multidimensional impulsivity construct in a large sample of healthy subjects.

Coronary CT angiography: a guide to examination, interpretation, and clinical indications

INTRODUCTION

The introduction of Cardiac Computed Tomography (CCT) has changed the paradigm in the field of diagnostic cardiovascular medicine. CCT is the primary tool in the assessment of suspected Coronary Artery Disease (CAD) and should be followed by functional assessment when needed to stratify disease and to plan potential interventional or surgical therapy.

AREAS COVERED

We provided the current state of the knowledge on the main aspects of technique of examination, image interpretation and clinical indications. We have focused our attention on the basic routine applications and activities.

EXPERT OPINION

The primary role of CCT in suspected CAD will progressively become the standard approach. In general, any situation in which anatomy of the heart and thoracic vessels/structures is mandatory must be approached using CT first, whenever possible. The quantity and quality of information that can be provided by CCT is big and the operators should learn how to deal with this information. On the other hand, CCT is only apparently a straightforward and simple examination. It is actually the most complex diagnostic procedure that can be performed on CT and requires highly skilled operators and state-of-art-technology.

Fully Automated Synthesis of Novel TSPO PET Imaging Ligand [18F]Fluoroethyltemazepam

Introduction: Benzodiazepines, including temazepam are described as TSPO antagonists. In fact, TSPO was initially described as a peripheral benzodiazepine receptor (PBR) with a secondary binding site for diazepam. TSPO is a potential imaging target of neuroinflammation because there is an amplification of the expression of this receptor. Objectives: Herein, we developed a novel fluorinated benzodiazepine ligand, [¹⁸F]Fluoroethyltemazepam ([¹⁸F]F-FETEM), for positron emission tomography (PET) imaging of translocator protein (18 kDa). Methods: [¹⁸F]F-FETEM was radiolabelled with an automated synthesizer via a one-pot procedure. We conducted a [¹⁸F]F-aliphatic nucleophilic substitution of a tosylated precursor followed by purification on C18 and Alumina N SPE cartridges. Quality control tests was also carried out. Results: We obtained 2.0–3.0% decay-uncorrected radiochemical activity yield (3.7% decay-corrected) within the whole synthesis time about 33 min. The radiochemical purity of [¹⁸F]F-FETEM was over 90% by TLC analysis. Conclusions: This automated procedure may be used as basis for future production of [¹⁸F]F-FETEM for preclinical PET imaging studies.

Radiomic and Genomic Machine Learning Method Performance for Prostate Cancer Diagnosis: Systematic Literature Review

BACKGROUND

Machine learning algorithms have been drawing attention at the joining of pathology and radiology in prostate cancer research. However, due to their algorithmic learning complexity and the variability of their architecture, there is an ongoing need to analyze their performance.

OBJECTIVE

This study assesses the source of heterogeneity and the performance of machine learning applied to radiomic, genomic, and clinical biomarkers for the diagnosis of prostate cancer. One research focus of this study was on clearly identifying problems and issues related to the implementation of machine learning in clinical studies.

METHODS

Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol, 816 titles were identified from the PubMed, Scopus, and OvidSP databases. Studies that used machine learning to detect prostate cancer and provided performance measures were included in our analysis. The quality of the eligible studies was assessed using the QUADAS-2 (quality assessment of diagnostic accuracy studies-version 2) tool. The hierarchical multivariate model was applied to the pooled data in a meta-analysis. To investigate the heterogeneity among studies, I2 statistics were performed along with visual evaluation of coupled forest plots. Due to the internal heterogeneity among machine learning algorithms, subgroup analysis was carried out to investigate the diagnostic capability of machine learning systems in clinical practice.

RESULTS

In the final analysis, 37 studies were included, of which 29 entered the meta-analysis pooling. The analysis of machine learning methods to detect prostate cancer reveals the limited usage of the methods and the lack of standards that hinder the implementation of machine learning in clinical applications.

CONCLUSIONS

The performance of machine learning for diagnosis of prostate cancer was considered satisfactory for several studies investigating the multiparametric magnetic resonance imaging and urine biomarkers; however, given the limitations indicated in our study, further studies are warranted to extend the potential use of machine learning to clinical settings. Recommendations on the use of machine learning techniques were also provided to help researchers to design robust studies to facilitate evidence generation from the use of radiomic and genomic biomarkers.

Prognostic value of 18F-FDG PET/MRI in patients with advanced oropharyngeal and hypopharyngeal squamous cell carcinoma

OBJECTIVE

The aim of this study was to evaluate the prognostic value of combined positron emission tomography (PET)/magnetic resonance imaging (MRI) parameters provided by simultaneous 18F-fluorodeoxyglucose (FDG) PET/MRI in patients with locally advanced oropharyngeal and hypopharyngeal squamous cell carcinomas (OHSCC).

METHODS

Forty-five patients with locally advanced OHSCC who underwent simultaneous FDG PET/MRI before (chemo)radiotherapy were retrospectively enrolled. Peak standardized uptake value (SULpeak), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of the primary lesion were obtained on PET data. On MRI scans, primary tumor size, diffusion and perfusion parameters were assessed using pre-contrast and high-resolution post-contrast images. Ratios between metabolic/metabolo-volumetric parameters and ADC were calculated. Comparisons between groups were performed by Student's t test. Survival analysis was performed by univariate Cox proportional hazard regression analysis. Overall survival curves were obtained by the Kaplan-Meier method and compared with the log-rank test. Survivors were censored at the time of the last clinical control. p < 0.05 was considered statistically significant RESULTS: During follow-up (mean 31.4 ± 21 months), there were 15 deaths. Univariate analysis shows that SULpeak and SULpeak/ADCmean were significant predictors of overall survival (OS). At multivariate analysis, only SULpeak remained a significant predictor of OS. Kaplan-Meier survival analyses showed that patients with higher SULpeak had poorer outcome compared to those with lower values (HR: 3.7, p = 0.007).

CONCLUSION

Pre-therapy SULpeak of the primary site was predictive of overall survival in patients with oropharyngeal or hypopharyngeal cancer treated with (chemo)radiotherapy.

The safety of sublingual immunotherapy, can the rare systemic reactions be prevented?

Introduction: The safety of subcutaneous immunotherapy (SCIT), and particularly the dramatic issue of fatal reactions, has been an obstacle that limited the implementation of a therapy with unique characteristics of action on the causes of allergy. The introduction of sublingual immunotherapy (SLIT) was aimed at solving safety problems while maintaining clinical efficacy.Areas covered: For more than 20 years, SLIT has been based on allergen extracts in drops at low average doses. As evidenced by meta-analyses, the typical adverse events (AE) have consisted of local reactions in the mouth and throat. Unlike the injection route, no correlation was observed between the administered dose and AEs. The development of SLIT products in tablets, based on higher doses than drops, has somewhat changed the concept of SLIT safety. Although large trials, performed to obtain regulatory agency approval, have shown overall high safety, rare anaphylactic reactions have been described.Expert opinion: SLIT is globally safe, and no fatal reactions have ever been reported, but with currently available high biological potency products it is necessary to follow prudential rules, such as the administration of the first dose under medical supervision and the thorough education of patients to avoid taking of higher doses than recommended.