Multi-omics staging of locally advanced rectal cancer predicts treatment response: a pilot study.

Treatment response assessment of rectal cancer patients is a critical component of personalized cancer care and it allows to identify suitable candidates for organ-preserving strategies. This pilot study employed a novel multi-omics approach combining MRI-based radiomic features and untargeted metabolomics to infer treatment response at staging. The metabolic signature highlighted how tumor cell viability is predictively down-regulated, while the response to oxidative stress was up-regulated in responder patients, showing significantly reduced oxoproline values at baseline compared to non-responder patients (p-value < 10-4). Tumors with a high degree of texture homogeneity, as assessed by radiomics, were more likely to achieve a major pathological response (p-value < 10-3). A machine learning classifier was implemented to summarize the multi-omics information and discriminate responders and non-responders. Combining all available radiomic and metabolomic features, the classifier delivered an AUC of 0.864 (± 0.083, p-value < 10-3) with a best-point sensitivity of 90.9% and a specificity of 81.8%. Our results suggest that a multi-omics approach, integrating radiomics and metabolomic data, can enhance the predictive value of standard MRI and could help to avoid unnecessary surgical treatments and their associated long-term complications.

Air embolism as a rare complication of lung biopsy: A case report.

Lung biopsy is an important interventional radiology procedure allowing the characterization of lesions with suspected malignancy. The most frequent complications are pneumothorax and hemorrhage. Air embolism is a rare but potentially fatal occurrence. In this case report, we present an air embolism after core needle CT-guided biopsy showing CT and MRI features that radiologists should expect in the everyday clinical practice.

Common Clinical and Molecular Pathways between Migraine and Sarcoidosis.

Migraine and sarcoidosis are two distinct medical conditions that may have some common biological and clinical pathways. Sarcoidosis is a chronic granulomatous disease characterized by the formation of granulomas in various organs, including the lungs, skin, cardiovascular system, lymph nodes, and brain. Migraine is a common comorbidity in sarcoidosis patients and a common neurological disorder characterized by recurrent headaches that can be accompanied by other symptoms, such as nausea, vomiting, and sensitivity to light and sound. There have been several reports of individuals with neurosarcoidosis experiencing migraines, though the exact relationship between the two disorders is not well understood. Both conditions have been associated with inflammation and the activation of the immune system. In sarcoidosis, the formation of granulomas is thought to be an immune response to the presence of an unknown antigen. Similarly, the pain and other symptoms associated with migraines are thought to be caused by inflammation in the brain and the surrounding blood vessels. There is also evidence to suggest an interplay of environmental and genetic factors playing a role in both conditions, but evidence is inconsistent with the hypothesis of shared genetic susceptibility. This review aims to illustrate common clinical and biological pathways between migraine and sarcoidosis, including inflammation and dysregulation of the immune system, with a focus on the cumulative burden of concurrent disorders and therapeutic implications.

The effect of different brain lesions on the reorganization of language functions within the dominant hemisphere assessed with task-based BOLD-fMRI.

BACKGROUND AND PURPOSE: Language reorganization has been described in brain lesions with respect to their location and timing, but little is known with respect to their etiology. We used fMRI to investigate the effects of different types of left hemisphere lesions (GL = gliomas, TLE = temporal lobe epilepsy and CA = cavernous angioma) on the topographic intra-hemispheric language plasticity, also considering their location. METHODS: Forty-seven right-handed patients with 3 different left hemisphere lesions (16 GL, 15 TLE and 16 CA) and 17 healthy controls underwent BOLD fMRI with a verb-generation task. Euclidean distance was used to measure activation peak shifts among groups with respect to reference Tailarach coordinates of Inferior Frontal Gyrus, Superior Temporal Sulcus and Temporo-Parietal Junction. Mixed-model ANOVAs were used to test for differences in activation peak shifts. RESULTS: Significant activation peak shifts were found in GL patients with respect both to HC and other groups (TLA and CA). In addition, in the same group of patients a significant effect of tumor location (anterior or posterior) was detected. CONCLUSIONS: We demonstrated that intra-hemispheric language plasticity is influenced by the type of lesion affecting the left hemisphere and that fMRI is especially valuable in the preoperative assessment of such reorganization in glioma patients.

MRI-Based Radiomics Approach Predicts Tumor Recurrence in ER + /HER2 - Early Breast Cancer Patients.

Oncotype Dx Recurrence Score (RS) has been validated in patients with ER + /HER2 - invasive breast carcinoma to estimate patient risk of recurrence and guide the use of adjuvant chemotherapy. We investigated the role of MRI-based radiomics features extracted from the tumor and the peritumoral tissues to predict the risk of tumor recurrence. A total of 62 patients with biopsy-proved ER + /HER2 - breast cancer who underwent pre-treatment MRI and Oncotype Dx were included. An RS > 25 was considered discriminant between low-intermediate and high risk of tumor recurrence. Two readers segmented each tumor. Radiomics features were extracted from the tumor and the peritumoral tissues. Partial least square (PLS) regression was used as the multivariate machine learning algorithm. PLS ß-weights of radiomics features included the 5% features with the largest ß-weights in magnitude (top 5%). Leave-one-out nested cross-validation (nCV) was used to achieve hyperparameter optimization and evaluate the generalizable performance of the procedure. The diagnostic performance of the radiomics model was assessed through receiver operating characteristic (ROC) analysis. A null hypothesis probability threshold of 5% was chosen (p < 0.05). The exploratory analysis for the complete dataset revealed an average absolute correlation among features of 0.51. The nCV framework delivered an AUC of 0.76 (p = 1.1∙10-3). When combining "early" and "peak" DCE images of only T or TST, a tendency toward statistical significance was obtained for TST with an AUC of 0.61 (p = 0.05). The 47 features included in the top 5% were balanced between T and TST (23 and 24, respectively). Moreover, 33/47 (70%) were texture-related, and 25/47 (53%) were derived from high-resolution images (1 mm). A radiomics-based machine learning approach shows the potential to accurately predict the recurrence risk in early ER + /HER2 - breast cancer patients.

Circulating Extracellular Vesicles: Their Role in Patients with Abdominal Aortic Aneurysm (AAA) Undergoing EndoVascular Aortic Repair (EVAR).

Abdominal aortic aneurysm (AAA) is a frequent aortic disease. If the diameter of the aorta is larger than 5 cm, an open surgical repair (OSR) or an endovascular aortic repair (EVAR) are recommended. To prevent possible complications (i.e., endoleaks), EVAR-treated patients need to be monitored for 5 years following the intervention, using computed tomography angiography (CTA). However, this radiological method involves high radiation exposure in terms of CTA/year. In such a context, the study of peripheral-blood-circulating extracellular vesicles (pbcEVs) has great potential to identify biomarkers for EVAR complications. We analyzed several phenotypes of pbcEVs using polychromatic flow cytometry in 22 patients with AAA eligible for EVAR. From each enrolled patient, peripheral blood samples were collected at AAA diagnosis, and after 1, 6, and 12 months following EVAR implantation, i.e. during the diagnostic follow-up protocol. Patients developing an endoleak displayed a significant decrease in activated-platelet-derived EVs between the baseline condition and 6 months after EVAR intervention. Furthermore, we also observed, that 1 month after EVAR implantation, patients developing an endoleak showed higher concentrations of activated-endothelial-derived EVs than patients who did not develop one, suggesting their great potential as a noninvasive and specific biomarker for early identification of EVAR complications.

Developing a Predictive Grading Model for Children with Gliomas Based on Diffusion Kurtosis Imaging Metrics: Accuracy and Clinical Correlations with Patient Survival.

Purpose: To develop a predictive grading model based on diffusion kurtosis imaging (DKI) metrics in children affected by gliomas, and to investigate the clinical impact of the predictive model by correlating with overall survival and progression-free survival. Materials and methods: 59 patients with a histological diagnosis of glioma were retrospectively studied (33 M, 26 F, median age 7.2 years). Patients were studied on a 3T scanner with a standardized MR protocol, including conventional and DKI sequences. Mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), fractional anisotropy (FA), and apparent diffusion coefficient (ADC) maps were obtained. Whole tumour volumes (VOIs) were segmented semi-automatically. Mean DKI values were calculated for each metric. The quantitative values from DKI-derived metrics were used to develop a predictive grading model to develop a probability prediction of a high-grade glioma (pHGG). Three models were tested: DTI-based, DKI-based, and combined (DTI and DKI). The grading accuracy of the resulting probabilities was tested with a receiver operating characteristics (ROC) analysis for each model. In order to account for dataset imbalances between pLGG and pHGG, we applied a random synthetic minority oversampling technique (SMOTE) analysis. Lastly, the most accurate model predictions were correlated with progression-free survival (PFS) and overall survival (OS) using the Kaplan−Meier method. Results: The cohort included 46 patients with pLGG and 13 patients with pHGG. The developed model predictions yielded an AUC of 0.859 (95%CI: 0.752−0.966) for the DTI model, of 0.939 (95%CI: 0.879−1) for the DKI model, and of 0.946 (95%CI: 0.890−1) for the combined model, including input from both DTI and DKI metrics, which resulted in the most accurate model. Sample estimation with the random SMOTE analysis yielded an AUC of 0.98 on the testing set. Model predictions from the combined model were significantly correlated with PFS (25.2 months for pHGG vs. 40.0 months for pLGG, p < 0.001) and OS (28.9 months for pHGG vs. 44.9 months for pLGG, p < 0.001). Conclusions: a DKI-based predictive model was highly accurate for pediatric glioma grading. The combined model, derived from both DTI and DKI metrics, proved that DKI-based model predictions of tumour grade were significantly correlated with progression-free survival and overall survival.

Differentiating solitary brain metastases from high-grade gliomas with MR: comparing qualitative versus quantitative diagnostic strategies.

PURPOSE: To investigate the diagnostic efficacy of MRI diagnostic algorithms with an ascending automatization, in distinguishing between high-grade glioma (HGG) and solitary brain metastases (SBM). METHODS: 36 patients with histologically proven HGG (n = 18) or SBM (n = 18), matched by size and location were enrolled from a database containing 655 patients. Four different diagnostic algorithms were performed serially to mimic the clinical setting where a radiologist would typically seek out further findings to reach a decision: pure qualitative, analytic qualitative (based on standardized evaluation of tumor features), semi-quantitative (based on perfusion and diffusion cutoffs included in the literature) and a quantitative data-driven algorithm of the perfusion and diffusion parameters. The diagnostic yields of the four algorithms were tested with ROC analysis and Kendall coefficient of concordance. RESULTS: Qualitative algorithm yielded sensitivity of 72.2%, specificity of 78.8%, and AUC of 0.75. Analytic qualitative algorithm distinguished HGG from SBM with a sensitivity of 100%, specificity of 77.7%, and an AUC of 0.889. The semi-quantitative algorithm yielded sensitivity of 94.4%, specificity of 83.3%, and AUC = 0.889. The data-driven algorithm yielded sensitivity = 94.4%, specificity = 100%, and AUC = 0.948. The concordance analysis between the four algorithms and the histologic findings showed moderate concordance for the first algorithm, (k = 0.501, P < 0.01), good concordance for the second (k = 0.798, P < 0.01), and third (k = 0.783, P < 0.01), and excellent concordance for fourth (k = 0.901, p < 0.0001). CONCLUSION: When differentiating HGG from SBM, an analytical qualitative algorithm outperformed qualitative algorithm, and obtained similar results compared to the semi-quantitative approach. However, the use of data-driven quantitative algorithm yielded an excellent differentiation.

The restoring of interhemispheric brain connectivity following carotid endarterectomy: an exploratory observational study.

This study aimed to evaluate the differences of brain connectivity between healthy subjects (HS) and patients with extracranial internal carotid artery (eICA) stenosis before and after carotid endarterectomy (CEA). An exploratory prospective study was designed. The study population consisted of a patient group (PG) of 20 patients with eICA stenosis eligible for CEA, and a control group (CG) of 20 HS, matched for age and sex. The subjects of the PG group underwent Magnetic Resonance Imaging (MRI) for resting-state functional connectivity MRI (rs-fc MRI) analysis within one week from the CEA (pre-CEA) and 12 months following CEA (post-CEA). The CG underwent a single MRI with the same protocol utilized for the PG. Three region-of-interest to region-of-interest (ROI-to-ROI) rs-fc MRI analyses were conducted: analysis 1 to compare pre-CEA PG and CG; analysis 2 to compare pre-CEA PG and post-CEA PG; analysis 3 to compare post-CEA PG and CG. The Functional Network Connectivity multivariate parametric technique was used for statistical analysis, adopting a p-uncorrected (p-unc) < 0.05 as connection threshold, and a cluster level False Discovery Rate corrected p (p-FDR) < 0.05 as cluster threshold. The clusters were defined by using a data-driven hierarchical clustering procedure. Analysis 1 revealed two clusters of reduced interhemispheric connectivity of pre-CEA PG when compared to CG. Analysis 2 and 3 showed no statistically significant differences. Our exploratory analysis suggests that patients with eICA stenosis have reduced interhemispheric connectivity when compared to a matched control group, and this difference was not evident anymore following endarterectomy.

A Dedicated Tool for Presurgical Mapping of Brain Tumors and Mixed-Reality Navigation During Neurosurgery.

Brain tumor surgery requires a delicate tradeoff between complete removal of neoplastic tissue while minimizing loss of brain function. Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) have emerged as valuable tools for non-invasive assessment of human brain function and are now used to determine brain regions that should be spared to prevent functional impairment after surgery. However, image analysis requires different software packages, mainly developed for research purposes and often difficult to use in a clinical setting, preventing large-scale diffusion of presurgical mapping. We developed a specialized software able to implement an automatic analysis of multimodal MRI presurgical mapping in a single application and to transfer the results to the neuronavigator. Moreover, the imaging results are integrated in a commercially available wearable device using an optimized mixed-reality approach, automatically anchoring 3-dimensional holograms obtained from MRI with the physical head of the patient. This will allow the surgeon to virtually explore deeper tissue layers highlighting critical brain structures that need to be preserved, while retaining the natural oculo-manual coordination. The enhanced ergonomics of this procedure will significantly improve accuracy and safety of the surgery, with large expected benefits for health care systems and related industrial investors.

Conspicuity and muscle-invasiveness assessment for bladder cancer using VI-RADS: a multi-reader, contrast-free MRI study to determine optimal b-values for diffusion-weighted imaging.

OBJECTIVE: To (1) compare bladder cancer (BC) muscle invasiveness among three b-values using a contrast-free approach based on Vesical Imaging-Reporting and Data System (VI-RADS), to (2) determine if muscle-invasiveness assessment is affected by the reader experience, and to (3) compare BC conspicuity among three b-values, qualitatively and quantitatively. METHODS: Thirty-eight patients who underwent a bladder MRI on a 3.0-T scanner were enrolled. The gold standard was histopathology report following transurethral resection of BC. Three sets of images, including T2w and different b-values for DWI, set 1 (b = 1000 s/mm2), set 2 (b = 1500 s/mm2), and set 3 (b = 2000 s/mm2), were reviewed by three differently experienced readers. Descriptive statistics and Intraclass Correlation Coefficient (ICC) were calculated. Comparisons among readers and DWI sets were performed with the Wilcoxon test. Receiver operating characteristic (ROC) analysis was performed. Areas under the curves (AUCs) and pairwise comparison were calculated. RESULTS: AUCs of muscle-invasiveness assessment ranged from 0.896 to 0.984 (reader 1), 0.952-0.968 (reader 2), and 0.952-0.984 (reader 3) without significant differences among different sets and readers (p > 0.05). The mean conspicuity qualitative scores were higher in Set 1 (2.21-2.33), followed by Set 2 (2-2.16) and Set 3 (1.82-2.14). The quantitative conspicuity assessment showed that mean normalized intensity of tumor was significantly higher in Set 2 (4.217-4.737) than in Set 1 (3.923-4.492) and Set 3 (3.833-3.992) (p < 0.05). CONCLUSION: Muscle invasiveness can be assessed with high accuracy using a contrast-free protocol with T2W and DWI, regardless of reader's experience. b = 1500 s/mm2 showed the best tumor delineation, while b = 1000 s/mm2 allowed for better tumor-wall interface assessment.

Knowledge and attitudes of neurologists toward epilepsy surgery: an Italian survey.

The current study, conceived with the contribution of the Commission for Epilepsy Surgery of the Italian League Against Epilepsy (LICE) and the Epilepsy Study Group of the Italian Neurological Society (SIN), aimed to assess potential physician-related barriers to refer subjects for epilepsy surgery. All the members of SIN and LICE were invited by email to complete a 28-item online questionnaire. The survey items included: (1) individual and medical practice characteristics, (2) knowledge of current indications to select candidates for epilepsy surgery, (3) factors potentially affecting the attitude toward epilepsy surgery. Overall, 210 physicians completed the survey. More than half (63.3%) of the participants showed proper knowledge of the ILAE drug-resistance. Definition and almost two-thirds of them (71.9%) considered themselves adequately informed about indications, risks, and benefits of epilepsy surgery. Surgery was regarded as a valid option to be used as early as possible by 84.8% of the interviewees, and 71% of them estimated its complication rate to be low. However, more than half (63%) of the respondents reportedly referred patients for surgery only after the failure of 3-5 antiseizure medications. Overestimation of risks/complications of surgery and inadequate healthcare resources were identified as the main factor contrasting the patient referral for surgery by 43% and 40.5% of the participants, respectively. In conclusion, this survey confirms the existence of knowledge gap within both physicians and the healthcare system, as well as an educational need regarding epilepsy surgery. Further researches are warranted to define learning outcomes and optimize educational tools.

Molecular Landscape in Infant High-Grade Gliomas: A Single Center Experience.

High-grade gliomas (HGG) represent about 15% of all pediatric brain tumors, with a dismal prognosis and survival rates ranging from 15 to 35%. Approximately 10-12% of pediatric HGGs (pHGG) occur in children younger than five years of age at diagnosis, specifically infants (iHGG), with an unexpected overall survival rate (OS) in 60-70% of cases. In the literature, iHGGs include a large variety of heterogeneous lesions with different molecular profiles that likely explain their different outcomes. We report our single-institution experience of iHGG including 11 children under five years of age with newly diagnosed HGG between 2011 and 2021. All patients received surgery and adjuvant chemotherapy; only two patients received radiotherapy because their age at diagnosis was more than four years-old. Molecular investigations, including next generation sequencing (NGS) and DNA methylation, detected three NTRK-fusions, one ROS1-fusions, one MN1-rearrangement, and two PATZ1-fusions. According to the molecular results, when chemotherapy failed to control the disease, two patients benefited from target therapy with a NTRK-Inhibitor larotrectinib, achieving a complete remission and a very good partial response, respectively, and no severe side-effects. In conclusion, molecular investigations play a fundamental role in the diagnostic work-up and also in the therapeutic decision. Their routine use in clinical practice could help to replace highly toxic chemotherapy regimens with a target therapy that has moderate adverse effects, even in long-term follow-up.

Atypical Sites of Lymphadenopathy after Anti-COVID-19 Vaccine: Ultrasound Features.

Background and Objectives: Several authors have reported cervical and axillary lymphadenopathies as known side effects following anti-COVID-19 vaccine administration. Few data are available about atypical locations of post-anti-COVID-19 vaccine lymphadenopathy. In this investigation, we evaluated the incidence and prevalence of postvaccine lymphadenopathy ultrasound (US) features in atypical sites. Materials and Methods: In this retrospective study, we retrospectively selected 64 patients on whom US was performed between January and October 2021 due to COVID-19 vaccine-related lymphadenopathy. We investigated lymph node anatomical sites, presence, number, size, shape, cortical profile, hilum outline, superb microvascular imaging (SMI), and elastosonography. Results: A total of 170 nodes were assessed. Atypical location was demonstrated in 5/64 patients (7.8%). In all these cases, atypical nodal involvement was associated with lymphadenopathy in a typical site (axillary, supraclavicular) ipsilateral to the vaccine injection site. Two patients presented lymphadenopathy in the infraclavicular station (3.1%), one in the pectoralis major muscle (1.6%), one in the left arm (1.6%), and one in the nuchal site (1.6%). All lymphadenopathies were oval-shaped, with a median size of 0.9 ± 0.2 cm. US features included a symmetric cortex with hilum evidence (4/6, 60%), vascular signal at SMI in both the hilar region and periphery of lymph node (5/6, 83.3%), and a US elastography pattern resembling that of adjacent tissues (5/6, 83.3%). The median age of patients with lymphadenopathies in an atypical location was 23 years. The main type of vaccine associated with lymph node appearance in atypical sites was Moderna's mRNA-1273 (60% of patients, 4/6 lymph nodes accounting for 66.7% among atypical locations). Conclusion: Post-COVID-19 vaccine administration lymphadenopathies in an atypical location represent an intense immune response to antigenic stimuli and they may show alarming US traits superimposed on malignant pathologies, which may complicate the patient's clinical and diagnostic pathway. Despite no distinctive US features between reactive post-COVID-19 vaccination and malignant lymph nodes being available, careful examination of atypical lymph node locations associated with accurate knowledge of patients' clinical background and delay of US exam to four to six weeks after vaccine injection should be considered.

Dynamic susceptibility MR perfusion imaging of the brain: not a question of contrast agent molarity.

PURPOSE: Dynamic susceptibility contrast (DSC) perfusion-weighted MR imaging (PWI) is increasingly used in clinical neuroimaging for a range of conditions. More highly concentrated GBCAs (e.g., gadobutrol) are often preferred for DSC imaging because it is thought that more Gd is present in the volume of interest during first pass for a given equivalent injection rate. However, faster injection of a less viscous GBCA (e.g., gadoteridol) might generate a more compact and narrower contrast bolus thus obviating any perceived benefit of higher Gd concentration. This preliminary study aimed to analyze and compare DSC examinations in the healthy brain hemisphere of patients with brain tumors using gadobutrol and gadoteridol administered at injection rates of 4 and 6 mL/s. METHODS: Thirty-nine brain tumor patients studied with DSC-PWI were evaluated. A simplified gamma-variate model function was applied to calculate the mean peak, area under the curve (AUC), and full-width at half-maximum (FHWM) of concentration-time curves derived from ΔR2* signals at four different regions-of-interest (ROIs). Qualitative assessment of the derived CBV maps was also performed independently by 2 neuroradiologists. RESULTS: No qualitative or quantitative differences between the two GBCAs were observed when administered at a flow rate of 4 mL/s. At a flow rate of 6 mL/s, gadoteridol showed lower FWHM values. CONCLUSION: Gadobutrol and gadoteridol are equivalent for clinical assessment of qualitative CBV maps and quantitative perfusion parameters (FHWM) at a flow rate of 4 mL/s. At 6 mL/s, gadoteridol produces a narrower bolus shape and potentially improves quantitative assessment of perfusion parameters.

Dynamic 11C-Methionine PET-CT: Prognostic Factors for Disease Progression and Survival in Patients with Suspected Glioma Recurrence.

PURPOSE: The prognostic evaluation of glioma recurrence patients is important in the therapeutic management. We investigated the prognostic value of 11C-methionine PET-CT (MET-PET) dynamic and semiquantitative parameters in patients with suspected glioma recurrence. METHODS: Sixty-seven consecutive patients who underwent MET-PET for suspected glioma recurrence at MR were retrospectively included. Twenty-one patients underwent static MET-PET; 46/67 underwent dynamic MET-PET. In all patients, SUVmax, SUVmean and tumour-to-background ratio (T/B) were calculated. From dynamic acquisition, the shape and slope of time-activity curves, time-to-peak and its SUVmax (SUVmaxTTP) were extrapolated. The prognostic value of PET parameters on progression-free (PFS) and overall survival (OS) was evaluated using Kaplan-Meier survival estimates and Cox regression. RESULTS: The overall median follow-up was 19 months from MET-PET. Recurrence patients (38/67) had higher SUVmax (p = 0.001), SUVmean (p = 0.002) and T/B (p < 0.001); deceased patients (16/67) showed higher SUVmax (p = 0.03), SUVmean (p = 0.03) and T/B (p = 0.006). All static parameters were associated with PFS (all p < 0.001); T/B was associated with OS (p = 0.031). Regarding kinetic analyses, recurrence (27/46) and deceased (14/46) patients had higher SUVmaxTTP (p = 0.02, p = 0.01, respectively). SUVmaxTTP was the only dynamic parameter associated with PFS (p = 0.02) and OS (p = 0.006). At univariate analysis, SUVmax, SUVmean, T/B and SUVmaxTTP were predictive for PFS (all p < 0.05); SUVmaxTTP was predictive for OS (p = 0.02). At multivariate analysis, SUVmaxTTP remained significant for PFS (p = 0.03). CONCLUSION: Semiquantitative parameters and SUVmaxTTP were associated with clinical outcomes in patients with suspected glioma recurrence. Dynamic PET-CT acquisition, with static and kinetic parameters, can be a valuable non-invasive prognostic marker, identifying patients with worse prognosis who require personalised therapy.

Predicting Overall Survival Time in Glioblastoma Patients Using Gradient Boosting Machines Algorithm and Recursive Feature Elimination Technique.

Despite advances in tumor treatment, the inconsistent response is a major challenge among glioblastoma multiform (GBM) that lead to different survival time. Our aim was to integrate multimodal MRI with non-supervised and supervised machine learning methods to predict GBM patients' survival time. To this end, we identified different compartments of the tumor and extracted their features. Next, we applied Random Forest-Recursive Feature Elimination (RF-RFE) to identify the most relevant features to feed into a GBoost machine. This study included 29 GBM patients with known survival time. RF-RFE GBoost model was evaluated to assess the survival prediction performance using optimal features. Furthermore, overall survival (OS) was analyzed using univariate and multivariate Cox regression analyses, to evaluate the effect of ROIs and their features on survival. The results showed that a RF-RFE Gboost machine was able to predict survival time with 75% accuracy. The results also revealed that the rCBV in the low perfusion area was significantly different between groups and had the greatest effect size in terms of the rate of change of the response variable (survival time). In conclusion, not only integration of multi-modality MRI but also feature selection method can enhance the classifier performance.

The surgical treatment of epilepsy.

In 2009, the Commission for Epilepsy Surgery of the Italian League Against Epilepsy (LICE) conducted an overview about the techniques used for the pre-surgical evaluation and the surgical treatment of epilepsies. The recognition that, in selected cases, surgery can be considered the first-line approach, suggested that the experience gained by the main Italian referral centers should be pooled in order to provide a handy source of reference. In light of the progress made over these past years, some parts of that first report have accordingly been updated. The present revision aims to harmonize the general principles regulating the patient selection and the pre-surgical work-up, as well as to expand the use of epilepsy surgery, that still represents an underutilized resource, regrettably. The objective of this contribution is drawing up a methodological framework within which to integrate the experiences of each group in this complex and dynamic sector of the neurosciences.