Prognosis of a second clinical event from baseline MRI in patients with a CIS: a multicenter study using a machine learning approach.

PURPOSE: To predict the occurrence of a second clinical event in patients with a CIS suggestive of MS, from baseline magnetic resonance imaging (MRI), by means of a pattern recognition approach. METHODS: Two hundred sixty-six patients with a CIS were recruited from four participating centers. Over a follow-up of 3 years, 130 patients had a second clinical episode and 136 did not. Grey matter and white matter T1-hypointensities masks segmented from 3D T1-weighted images acquired on 3 T scanners were used as features for the classification approach. Differences between CIS that remained CIS and those that developed a second event were assessed at a global level and at a regional level, arranging the regions according to their contribution to the classification model. RESULTS: All classification metrics were around or even below 50% for both global and regional approaches. Accuracies did not change when T1-hypointensity maps were added to the model; just the specificity was increased up to 80%. Among the 30 regions with the largest contribution, 26 were grey matter and 4 were white matter regions. For grey matter, regions contributing showed either a larger or a smaller volume in the group of patients that remained CIS, compared to those with a second event. The volume of T1-hypointensities was always larger for the group that presented a second event. CONCLUSIONS: Prediction of a second clinical event in CIS patients from baseline MRI seems to present a highly heterogeneous pattern, leading to very low classification accuracies. Adding the T1-hypointensity maps does not seem to improve the accuracy of the classification model.

Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study.

BACKGROUND AND RATIONALE: Thalamus atrophy has been linked to cognitive decline in multiple sclerosis (MS) using various segmentation methods. We investigated the consistency of the association between thalamus volume and cognition in MS for two common automated segmentation approaches, as well as fully manual outlining. METHODS: Standardized neuropsychological assessment and 3-Tesla 3D-T1-weighted brain MRI were collected (multi-center) from 57 MS patients and 17 healthy controls. Thalamus segmentations were generated manually and using five automated methods. Agreement between the algorithms and manual outlines was assessed with Bland-Altman plots; linear regression assessed the presence of proportional bias. The effect of segmentation method on the separation of cognitively impaired (CI) and preserved (CP) patients was investigated through Generalized Estimating Equations; associations with cognitive measures were investigated using linear mixed models, for each method and vendor. RESULTS: In smaller thalami, automated methods systematically overestimated volumes compared to manual segmentations [ρ=(-0.42)-(-0.76); p-values < 0.001). All methods significantly distinguished CI from CP MS patients, except manual outlines of the left thalamus (p = 0.23). Poorer global neuropsychological test performance was significantly associated with smaller thalamus volumes bilaterally using all methods. Vendor significantly affected the findings. CONCLUSION: Automated and manual thalamus segmentation consistently demonstrated an association between thalamus atrophy and cognitive impairment in MS. However, a proportional bias in smaller thalami and choice of MRI acquisition system might impact the effect size of these findings.

Reduced accuracy of MRI deep grey matter segmentation in multiple sclerosis: an evaluation of four automated methods against manual reference segmentations in a multi-center cohort.

BACKGROUND: Deep grey matter (DGM) atrophy in multiple sclerosis (MS) and its relation to cognitive and clinical decline requires accurate measurements. MS pathology may deteriorate the performance of automated segmentation methods. Accuracy of DGM segmentation methods is compared between MS and controls, and the relation of performance with lesions and atrophy is studied. METHODS: On images of 21 MS subjects and 11 controls, three raters manually outlined caudate nucleus, putamen and thalamus; outlines were combined by majority voting. FSL-FIRST, FreeSurfer, Geodesic Information Flow and volBrain were evaluated. Performance was evaluated volumetrically (intra-class correlation coefficient (ICC)) and spatially (Dice similarity coefficient (DSC)). Spearman's correlations of DSC with global and local lesion volume, structure of interest volume (ROIV), and normalized brain volume (NBV) were assessed. RESULTS: ICC with manual volumes was mostly good and spatial agreement was high. MS exhibited significantly lower DSC than controls for thalamus and putamen. For some combinations of structure and method, DSC correlated negatively with lesion volume or positively with NBV or ROIV. Lesion-filling did not substantially change segmentations. CONCLUSIONS: Automated methods have impaired performance in patients. Performance generally deteriorated with higher lesion volume and lower NBV and ROIV, suggesting that these may contribute to the impaired performance.

Can pancreatic cancer be detected by adrenomedullin in patients with new-onset diabetes? The PaCANOD cohort study protocol.

INTRODUCTION: Pancreatic cancer is a leading cause of cancer-related death. Its diagnosis is often delayed and patients are frequently found to have unresectable disease. Patients diagnosed with new-onset diabetes have an 8-fold risk of harboring pancreatic cancer. Adrenomedullin has been claimed to mediate diabetes in pancreatic cancer. New screening tools are needed to develop an early diagnosis protocol. METHODS: Patients aged 45-75 years within 2 years of first fulfilling the ADA criteria for diabetes will be prospectively enrolled in this study. Sepsis, renal failure, microangiopathy, pregnancy, acute heart failure and previous malignancies will be considered as exclusion criteria. RESULTS: 440 patients diagnosed with new-onset diabetes will be enrolled and divided into 2 groups: one with high adrenomedullin levels and one with low adrenomedullin levels. Patients will undergo 3 years' follow-up to detect pancreatic cancer development. CONCLUSIONS: Identifying a marker for pancreatic cancer among high-risk patients such as new-onset diabetics might lead to the identification of a subpopulation needing to be screened in order to enable early diagnosis and treatment of a highly lethal tumor. TRIAL REGISTRATION: This trial was registered at ClinicalTrials.gov on May 25, 2015 under registration number NCT02456051.

Adjuvant and neoadjuvant therapies in resectable pancreatic cancer: a systematic review of randomized controlled trials.

The timing of surgery and antineoplastic therapies in patients with resectable non-metastatic pancreatic cancer is still a controversial matter of debate, with special regard to neoadjuvant approaches. Following the criteria of the PRISMA statement, a literature search was conducted looking for RCTs focusing on adjuvant and neoadjuvant therapies in resectable pancreatic cancer. The quality of the available evidence was assessed using the Cochrane Collaboration's tool for assessing risk of bias. Data extraction was carried out by two independent investigators. The search led to the identification of 2830 papers of which 14 RCTs focusing on adjuvant and neoadjuvant treatment of resectable pancreatic cancer eligible for the systematic review. Risk of bias was estimated "unclear" in 3 studies and "high" in 5 studies. Median age ranged between 53 and 66. Overall survival in the surgery-only arms ranged between 11 and 20.2 months; in the adjuvant treatment arms 12.5-29.8 months; and in the neoadjuvant setting 9.9-19.4 months. Neoadjuvant protocols should be offered only in randomized clinical trials comparing the standard of care (surgery followed by adjuvant treatments) to a neoadjuvant approach followed by surgery and adjuvant treatment.

Atypical idiopathic inflammatory demyelinating lesions: prognostic implications and relation to multiple sclerosis.

Atypical lesions of a presumably idiopathic inflammatory demyelinating origin present quite variably and may pose diagnostic problems. The subsequent clinical course is also uncertain. We, therefore, wanted to clarify if atypical idiopathic inflammatory demyelinating lesions (AIIDLs) can be classified according to previously suggested radiologic characteristics and how this classification relates to prognosis. Searching the databases of eight tertiary referral centres we identified 90 adult patients (61 women, 29 men; mean age 34 years) with ≥ 1 AIIDL. We collected their demographic, clinical and magnetic resonance imaging data and obtained follow-up (FU) information on 77 of these patients over a mean duration of 4 years. The AIIDLs presented as a single lesion in 72 (80 %) patients and exhibited an infiltrative (n = 35), megacystic (n = 16), Baló (n = 10) or ring-like (n = 16) lesion appearance in 77 (86 %) patients. Additional multiple sclerosis (MS)-typical lesions existed in 48 (53 %) patients. During FU, a further clinical attack occurred rarely (23-35 % of patients) except for patients with ring-like AIIDLs (62 %). Further attacks were also significantly more often in patients with coexisting MS-typical lesions (41 vs. 10 %, p < 0.005). New AIIDLs developed in six (7 %), and new MS-typical lesions in 29 (42 %) patients. Our findings confirm the previously reported subtypes of AIIDLs. Most types confer a relatively low risk of further clinical attacks, except for ring-like lesions and the combination with MS-typical lesions.

Myeloid microvesicles are a marker and therapeutic target for neuroinflammation.

OBJECTIVE: Microvesicles (MVs) have been indicated as important mediators of intercellular communication and are emerging as new biomarkers of tissue damage. Our previous data indicate that reactive microglia/macrophages release MVs in vitro. The aim of the study was to evaluate whether MVs are released by microglia/macrophages in vivo and whether their number varies in brain inflammatory conditions, such as multiple sclerosis (MS). METHODS: Electron and fluorescence microscopy and flow cytometry were used to detect myeloid MVs in the cerebrospinal fluid (CSF) of healthy controls, MS patients, and rodents affected by experimental autoimmune encephalomyelitis (EAE), the animal model of MS. RESULTS: Myeloid MVs were detected in CSF of healthy controls. In relapsing and remitting EAE mice, the concentration of myeloid MVs in the CSF was significantly increased and closely associated with disease course. Analysis of MVs in the CSF of 28 relapsing patients and 28 patients with clinical isolated syndrome from 2 independent cohorts revealed higher levels of myeloid MVs than in 13 age-matched controls, indicating a clinical value of MVs as a companion tool to capture disease activity. Myeloid MVs were found to spread inflammatory signals both in vitro and in vivo at the site of administration; mice impaired in MV shedding were protected from EAE, suggesting a pathogenic role for MVs in the disease. Finally, FTY720, the first approved oral MS drug, significantly reduced the amount of MVs in the CSF of EAE-treated mice. INTERPRETATION: These findings identify myeloid MVs as a marker and therapeutic target of brain inflammation.

Abnormalities of resting state functional connectivity are related to sustained attention deficits in MS.

OBJECTIVES: Resting state (RS) functional MRI recently identified default network abnormalities related to cognitive impairment in MS. fMRI can also be used to map functional connectivity (FC) while the brain is at rest and not adhered to a specific task. Given the importance of the anterior cingulate cortex (ACC) for higher executive functioning in MS, we here used the ACC as seed-point to test for differences and similarities in RS-FC related to sustained attention between MS patients and controls. DESIGN: Block-design rest phases of 3 Tesla fMRI data were analyzed to assess RS-FC in 31 patients (10 clinically isolated syndromes, 16 relapsing-remitting, 5 secondary progressive MS) and 31 age- and gender matched healthy controls (HC). Participants underwent extensive cognitive testing. OBSERVATIONS: In both groups, signal changes in several brain areas demonstrated significant correlation with RS-activity in the ACC. These comprised the posterior cingulate cortex (PCC), insular cortices, the right caudate, right middle temporal gyrus, angular gyri, the right hippocampus, and the cerebellum. Compared to HC, patients showed increased FC between the ACC and the left angular gyrus, left PCC, and right postcentral gyrus. Better cognitive performance in the patients was associated with increased FC to the cerebellum, middle temporal gyrus, occipital pole, and the angular gyrus. CONCLUSION: We provide evidence for adaptive changes in RS-FC in MS patients compared to HC in a sustained attention network. These results extend and partly mirror findings of task-related fMRI, suggesting FC may increase our understanding of cognitive dysfunction in MS.

Incorporating domain knowledge into the fuzzy connectedness framework: application to brain lesion volume estimation in multiple sclerosis.

A method for incorporating prior knowledge into the fuzzy connectedness image segmentation framework is presented. This prior knowledge is in the form of probabilistic feature distribution and feature size maps, in a standard anatomical space, and "intensity hints" selected by the user that allow for a skewed distribution of the feature intensity characteristics. The fuzzy affinity between pixels is modified to encapsulate this domain knowledge. The method was tested by using it to segment brain lesions in patients with multiple sclerosis, and the results compared to an established method for lesion outlining based on edge detection and contour following. With the fuzzy connections (FC) method, the user is required to identify each lesion with a mouse click, to provide a set of seed pixels. The algorithm then grows the features from the seeds to define the lesions as a set of objects with fuzzy connectedness above a preset threshold. The FC method gave improved interobserver reproducibility of lesion volumes, and the set of pixels determined to be lesion was more consistent compared to the contouring method. The operator interaction time required to evaluate one subject was reduced from an average of 111 min with contouring to 16 min with the FC method.

Validation of diagnostic magnetic resonance imaging criteria for multiple sclerosis and response to interferon beta1a.

In the recently proposed diagnostic criteria for multiple sclerosis (MS) by McDonald, the modified magnetic resonance imaging (MRI) Barkhof criteria have been incorporated. We examined the validity of this implementation in the Early Treatment of MS study, a randomized, double-blind, placebo-controlled study of 22 microg interferon beta1a given subcutaneously once weekly in 309 patients with a first episode consistent with demyelinating disease (and abnormal MRI). Conversion to clinically definite MS (CDMS) within 2 years of follow-up, as evidenced by a new clinical episode, occurred in 41% of patients (independent of treatment) with gadolinium enhancement or nine or more T2 lesions versus 11% of those without either finding (p = 0.017); similarly, proportions converting were 44% versus 31% for infratentorial lesions (p = 0.026), 40% versus 35% for juxtacortical lesions (p = 0.413), and 41% versus 17% for three or more periventricular lesions (p = 0.034). The rate of conversion to CDMS based on the number of modified Barkhof criteria was 22% for two or fewer positive criteria, increasing to 47% with four positive criteria. For a cutoff of three positive criteria, the hazard ratio for time to CDMS was 2.3 (95% confidence interval, 1.17-4.55; p = 0.016). Treatment effect seemed more evident as the number of positive criteria increased, and the number of patients needed to avoid one patient converting to CDMS decreased from 50 in patients with one or two positive criteria to 5.6 in patients with four positive criteria. However, the study was not powered to detect statistically significant treatment by variable interaction, and this remains an important issue for further study.