Impact of Software Modeling on the Accuracy of Perfusion MRI in Glioma

PURPOSE: To determine whether differences in modeling implementation will impact the correction of leakage effects (from blood brain barrier disruption) and relative cerebral blood volume (rCBV) calculations as measured on T2*-weighted dynamic susceptibility-weighted contrast-enhanced (DSC)-MRI at 3T field strength. MATERIALS AND METHODS: This HIPAA-compliant study included 52 glioma patients undergoing DSC-MRI. Thirty-six patients underwent both non Preload Dose (PLD) and PLD-corrected DSC acquisitions, with sixteen patients undergoing PLD-corrected acquisitions only. For each acquisition, we generated two sets of rCBV metrics using two separate, widely published, FDA-approved commercial software packages: IB Neuro (IBN) and NordicICE (NICE). We calculated 4 rCBV metrics within tumor volumes: mean rCBV, mode rCBV, percentage of voxels with rCBV > 1.75 (%>1.75), and percentage of voxels with rCBV > 1.0 (Fractional Tumor Burden or FTB). We determined Pearson (r) and Spearman (ρ) correlations between non-PLD- and PLD-corrected metrics. In a subset of recurrent glioblastoma patients (n=25), we determined Receiver Operator Characteristic (ROC) Areas-Under-Curve (AUC) for FTB accuracy to predict the tissue diagnosis of tumor recurrence versus post-treatment effect (PTRE). We also determined correlations between rCBV and microvessel area (MVA) from stereotactic biopsies (n=29) in twelve patients. RESULTS: Using IBN, rCBV metrics correlated highly between non-PLD- and PLD-corrected conditions for FTB (r=0.96, ρ=0.94), %>1.75 (r=0.93, ρ=0.91), mean (r=0.87, ρ=0.86) and mode (r=0.78, ρ=0.76). These correlations dropped substantially with NICE. Using FTB, IBN was more accurate than NICE in diagnosing tumor vs PTRE (AUC=0.85 vs 0.67) (p<0.01). The highest rCBV-MVA correlations required PLD and IBN (r=0.64, ρ=0.58, p=0.001). CONCLUSIONS: Different implementations of perfusion MRI software modeling can impact the accuracy of leakage correction, rCBV calculation, and correlations with histologic benchmarks

Impact of chronic liver disease upon admission on COVID-19 in-hospital mortality: Findings from COVOCA study

Background Italy has been the first Western country to be heavily affected by the spread of SARS-COV-2 infection and among the pioneers of the clinical management of pandemic. To improve the outcome, identification of patients at the highest risk seems mandatory. Objectives Aim of this study is to identify comorbidities and clinical conditions upon admission associated with in-hospital mortality in several COVID Centers in Campania Region (Italy). Methods COVOCA is a multicentre retrospective observational cohort study, which involved 18 COVID Centers throughout Campania Region, Italy. Data were collected from patients who completed their hospitalization between March-June 2020. The endpoint was in-hospital mortality, assessed either from data at discharge or death certificate, whilst all exposure variables were collected at hospital admission. Results Among 618 COVID-19 hospitalized patients included in the study, 143 in-hospital mortality events were recorded, with a cumulative incidence of about 23%. At multivariable logistic analysis, male sex (OR 2.63, 95%CI 1.42–4.90; p = 0.001), Chronic Liver Disease (OR 5.88, 95%CI 2.39–14.46; p&lt;0.001) and malignancies (OR 2.62, 95%CI 1.21–5.68; p = 0.015) disclosed an independent association with a poor prognosis, Glasgow Coma Scale (GCS) and Respiratory Severity Scale allowed to identify at higher mortality risk. Sensitivity analysis further enhanced these findings. Conclusion Mortality of patients hospitalized for COVID-19 appears strongly affected by both clinical conditions on admission and comorbidities. Originally, we observed a very poor outcome in subjects with a chronic liver disease, alongside with an increase of hepatic damage

Whole plantar nerve conduction study: A new tool for early diagnosis of peripheral diabetic neuropathy

Aims: Peripheral neuropathy (PN) affects two-thirds of type 2 diabetes patients (T2DM). According to diabetic PN length-dependent pattern, neurophysiological evaluation of foot-sole nerves might increase NCS diagnostic sensitivity, hence allowing early diagnosis of PN. Thus, we aim to assess the ability of whole plantar nerve (WPN) conduction in diabetic PN early diagnosis. Methods: This is a single center prospective observational cohort study on 70 T2DM patients referred to Internal Medicine Unit of A.O.U. “Luigi Vanvitelli” between October 2019/October 2020. Primary endpoint was WPN efficacy assessment in PN early detection. As secondary, we evaluated (i) a potential cut-off of SNAPs amplitude by WPN and (ii) WPN diagnostic accuracy vs. gold-standard distal sural nerve conduction. Results: ROC curve analysis allowed to establish two potential cut-offs for people aged ≤60 years (AUROC: 0.83, 95%CI: 0.69–0.96, p &lt; 0.001) and ≤60 years (AUROC: 0.76, 95%CI: 0.59–0.93, p = 0.017). In depth, we fixed a cut-off of WPN-SNAP amplitude of 4.55 μV and 2.65 μV, respectively, with subsequent 48 patients classified as PN-T2DM. Conclusions: Our data support WPN conduction study reliability in characterizing the most distal sensory nerve fibers at lower limbs. Thus, WPN may represent an extremely useful diagnostic tool for diabetic PN early detection

Viability of pegIFNα-RBV for CHC in the direct acting antiviral era: a practical algorithm between efficacy and cost containment

The classical pegylated interferon α (peg-IFNα) and ribavirin (RBV) treatment of chronic hepatitis C (CHC) is progressively being replaced by new direct acting antivirals, whose costs remain a major barrier to widespread use. Using baseline data and viral kinetics, we developed a predictive algorithm to allocate to DAA patients who are not going to respond to peg-IFNα/RBV. This prospective study evaluated 205 CHC patients treated with peg-IFNα/RBV. HCVRNA kinetics during the initial 3 days of therapy and baseline variables including age, genotype, fibrosis and ALTs were used to construct a prediction rule in terms of sustained virological response (SVR). One hundred and twenty-one patients achieved an SVR (59%). Variables independently associated with SVR were HCVRNA, ALT, glycaemia, viral genotype, and fibrosis. The decline of viremia from baseline to 48/72 h was significantly different in SVR compared to non-SVR patients (2.2 vs. 0.65 log10 IU/mL; p < 0.001), and was influenced by viral genotype, levels of ALT, stage of fibrosis and IL28B polymorphism. In genotype 1, HCVRNA decline <0.8 logs had a negative predictive value of 90%, and in genotype 2, HCVRNA decline >1.2 logs had a positive predictive value of 92%. A combination of HCVRNA kinetics and a score based on pre-treatment parameters was highly accurate in predicting SVR in most patients. Outcome of peg-IFNα/RBV treatment may be predicted combining evaluation of baseline variables and HCVRNA kinetics. This allows to individualize treatment, reserving newer and more expensive DAAs to CHC patients who are in most need of them

Endogenous serum erythropoietin and no-reflow in patients with ST-elevation myocardial infarction

Background In models of acute ischaemia, erythropoietin (EPO) administration has been found to attenuate vascular injury largely through reduced apoptosis, suppressed inflammation and increased nitric oxide availability. We studied the association between circulating endogenous EPO and no-reflow in patients with first ST-elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI). Methods Blood sampling was performed before PPCI. Consecutive patients with (n = 24) or without (n = 24) evidence of angiographic no-reflow after PPCI were enrolled. Angiographic no-reflow was defined as Thrombolysis in Myocardial Infarction (TIMI) flow 0.05 for left anterior descending artery, respectively). Conclusions We found an independent, graded, inverse relation between endogenous EPO levels and angiographic and ECG no-reflow following PPCI. In animal models of ischaemia, EPO has been found to be protective. In humans, endogenous EPO may contribute to offset the mechanisms responsible for no-reflow

Predictors of long-term mortality in left-sided infective endocarditis: an historical cohort study in 414 patients

Introduction:: Very limited data are available on the long-term outcome of infective endocarditis (IE) and its determinants. The aim of this study was to identify the predictors of long-term mortality in patients affected by left sided IE (LSIE). Methods:: This was an historical retrospective observational study on prospectively collected data from patients with LSIE hospitalized in our Unit (January 2000-December 2017). Multiple variables relevant to history, physical examination, laboratory tests, echocardiography, comorbidities, complications and outcome were analysed by Cox regression to identify predictors of long-term mortality. Results:: 414 patients were included, and followed up for a median of 39 months [IQR 11-74]. Median age was 59 years [range 3-89], and most patients were male. Over 50% showed at least one comorbidity. Hyperglycaemia, increased creatinine and an indication for surgery predicted in-hospital mortality, while a prior myocardial infarction, chronic kidney disease (CKD) on hemodialysis and a larger vegetation were independent predictors of 1-year mortality. At multivariate analysis, peripheral arterial disease (p= 0.017), hyperglycemia on admission (p=0.013) and a higher BMI (p=0.009) were independent predictors of long-term mortality in 1-year survivors. At multivariable Cox proportional hazard regression, peripheral arterial disease (p=0.002), hyperglycemia (p=0.041) and CKD on hemodialysis (p=0.025) confirmed to be independently associated with an increased risk of long-term mortality in the overall 414 patient cohort. Conclusions:: Cardiovascular and metabolic risk signals, specifically peripheral arterial disease and hyperglicemia, affect long-term mortality of LSIE. An active and long-term follow up seems warranted in IE survivors showing these conditions at outset

Prospective trial evaluating the sensitivity and specificity of 3,4-dihydroxy-6-[18F]-fluoro-l-phenylalanine (18F-DOPA) PET and MRI in patients with recurrent gliomas

Treatment-related changes can be difficult to differentiate from progressive glioma using MRI with contrast (CE). The purpose of this study is to compare the sensitivity and specificity of 18F-DOPA-PET and MRI in patients with recurrent glioma. Thirteen patients with MRI findings suspicious for recurrent glioma were prospectively enrolled and underwent 18F-DOPA-PET and MRI for neurosurgical planning. Stereotactic biopsies were obtained from regions of concordant and discordant PET and MRI CE, all within regions of T2/FLAIR signal hyperintensity. The sensitivity and specificity of 18F-DOPA-PET and CE were calculated based on histopathologic analysis. Receiver operating characteristic curve analysis revealed optimal tumor to normal (T/N) and SUVmax thresholds. In the 37 specimens obtained, 51% exhibited MRI contrast enhancement (M+) and 78% demonstrated 18F-DOPA-PET avidity (P+). Imaging characteristics included M−P− in 16%, M−P+ in 32%, M+P+ in 46% and M+P− in 5%. Histopathologic review of biopsies revealed grade II components in 16%, grade III in 43%, grade IV in 30% and no tumor in 11%. MRI CE sensitivity for recurrent tumor was 52% and specificity was 50%. PET sensitivity for tumor was 82% and specificity was 50%. A T/N threshold &gt; 2.0 altered sensitivity to 76% and specificity to 100% and SUVmax &gt; 1.36 improved sensitivity and specificity to 94 and 75%, respectively. 18F-DOPA-PET can provide increased sensitivity and specificity compared with MRI CE for visualizing the spatial distribution of recurrent gliomas. Future studies will incorporate 18F-DOPA-PET into re-irradiation target volume delineation for RT planning

Impact of Software Modeling on the Accuracy of Perfusion MRI in Glioma.

Background and purposeRelative cerebral blood volume, as measured by T2*-weighted dynamic susceptibility-weighted contrast-enhanced MRI, represents the most robust and widely used perfusion MR imaging metric in neuro-oncology. Our aim was to determine whether differences in modeling implementation will impact the correction of leakage effects (from blood-brain barrier disruption) and the accuracy of relative CBV calculations as measured on T2*-weighted dynamic susceptibility-weighted contrast-enhanced MR imaging at 3T field strength.Materials and methodsThis study included 52 patients with glioma undergoing DSC MR imaging. Thirty-six patients underwent both non-preload dose- and preload dose-corrected DSC acquisitions, with 16 patients undergoing preload dose-corrected acquisitions only. For each acquisition, we generated 2 sets of relative CBV metrics by using 2 separate, widely published, FDA-approved commercial software packages: IB Neuro and nordicICE. We calculated 4 relative CBV metrics within tumor volumes: mean relative CBV, mode relative CBV, percentage of voxels with relative CBV &gt; 1.75, and percentage of voxels with relative CBV &gt; 1.0 (fractional tumor burden). We determined Pearson (r) and Spearman (ρ) correlations between non-preload dose- and preload dose-corrected metrics. In a subset of patients with recurrent glioblastoma (n = 25), we determined receiver operating characteristic area under the curve for fractional tumor burden accuracy to predict the tissue diagnosis of tumor recurrence versus posttreatment effect. We also determined correlations between rCBV and microvessel area from stereotactic biopsies (n = 29) in 12 patients.ResultsWith IB Neuro, relative CBV metrics correlated highly between non-preload dose- and preload dose-corrected conditions for fractional tumor burden (r = 0.96, ρ = 0.94), percentage &gt; 1.75 (r = 0.93, ρ = 0.91), mean (r = 0.87, ρ = 0.86), and mode (r = 0.78, ρ = 0.76). These correlations dropped substantially with nordicICE. With fractional tumor burden, IB Neuro was more accurate than nordicICE in diagnosing tumor versus posttreatment effect (area under the curve = 0.85 versus 0.67) (P &lt; .01). The highest relative CBV-microvessel area correlations required preload dose and IB Neuro (r = 0.64, ρ = 0.58, P = .001).ConclusionsDifferent implementations of perfusion MR imaging software modeling can impact the accuracy of leakage correction, relative CBV calculation, and correlations with histologic benchmarks