Evaluation of Cerebrospinal Fluid Neurofilament Light Chain as a Routine Biomarker in a Memory Clinic.

Systematic evaluation of biomarkers in representative populations is needed to validate their clinical utility. In this work, we assessed the diagnostic performance of cerebrospinal fluid (CSF) neurofilament light chain (NfL) in a neurocognitive clinical setting. A total of 51 patients with different cognitive clinical syndromes and 11 cognitively normal individuals were evaluated in a memory clinic in Argentina. Clinical conditions included mild cognitive impairment (MCI, n = 12), dementia of Alzheimer's type (DAT, n = 14), behavioral variant frontotemporal dementia (bvFTD, n = 13), and primary progressive aphasia (logopenic [n = 6], semantic [n = 2], and nonfluent [n = 4]). We quantified CSF NfL and core Alzheimer's disease biomarkers using commercially available ELISA kits. Cortical thickness was analyzed on brain magnetic resonance imaging scans from 10 controls and 10 patients. CSF NfL was significantly increased in MCI, FTD, and DAT patients compared with controls (Kruskal-Wallis, p < .0001). Interestingly, receiver operating characteristic curve analysis showed the highest area under the curve (AUC) value when analyzing control versus bvFTD patients (AUC = 0.9441). Also, we observed a marginally significant correlation between NfL levels and left orbitofrontal cortex thickness in a small group of patients with FTD. Overall, our results further support CSF NfL as a promising biomarker in the diagnostic workup of bvFTD.

Multicentre evaluation of the INTERPRET decision support system 2.0 for brain tumour classification.

In a previous study, we have shown the added value of (1) H MRS for the neuroradiological characterisation of adult human brain tumours. In that study, several methods of MRS analysis were used, and a software program, the International Network for Pattern Recognition of Tumours Using Magnetic Resonance Decision Support System 1.0 (INTERPRET DSS 1.0), with a short-TE classifier, provided the best results. Since then, the DSS evolved into a version 2.0 that contains an additional long-TE classifier. This study has two objectives. First, to determine whether clinicians with no experience of spectroscopy are comparable with spectroscopists in the use of the system, when only minimum training in the use of the system was given. Second, to assess whether or not a version with another TE is better than the initial version. We undertook a second study with the same cases and nine evaluators to assess whether the diagnostic accuracy of DSS 2.0 was comparable with the values obtained with DSS 1.0. In the second study, the analysis protocol was flexible in comparison with the first one to mimic a clinical environment. In the present study, on average, each case required 5.4 min by neuroradiologists and 9 min by spectroscopists for evaluation. Most classes and superclasses of tumours gave the same results as with DSS 1.0, except for astrocytomas of World Health Organization (WHO) grade III, in which performance measured as the area under the curve (AUC) decreased: AUC = 0.87 (0.72-1.02) with DSS 1.0 and AUC = 0.62 (0.55-0.70) with DSS 2.0. When analysing the performance of radiologists and spectroscopists with respect to DSS 1.0, the results were the same for most classes. Having data with two TEs instead of one did not affect the results of the evaluation.

Compatibility between 3T 1H SV-MRS data and automatic brain tumour diagnosis support systems based on databases of 1.5T 1H SV-MRS spectra.

OBJECT: This study demonstrates that 3T SV-MRS data can be used with the currently available automatic brain tumour diagnostic classifiers which were trained on databases of 1.5T spectra. This will allow the existing large databases of 1.5T MRS data to be used for diagnostic classification of 3T spectra, and perhaps also the combination of 1.5T and 3T databases. MATERIALS AND METHODS: Brain tumour classifiers trained with 154 1.5T spectra to discriminate among high grade malignant tumours and common grade II glial tumours were evaluated with a subsequently-acquired set of 155 1.5T and 37 3T spectra. A similarity study between spectra and main brain tumour metabolite ratios for both field strengths (1.5T and 3T) was also performed. RESULTS: Our results showed that classifiers trained with 1.5T samples had similar accuracy for both test datasets (0.87 ± 0.03 for 1.5T and 0.88 ± 0.03 for 3.0T). Moreover, non-significant differences were observed with most metabolite ratios and spectral patterns. CONCLUSION: These results encourage the use of existing classifiers based on 1.5T datasets for diagnosis with 3T (1)H SV-MRS. The large 1.5T databases compiled throughout many years and the prediction models based on 1.5T acquisitions can therefore continue to be used with data from the new 3T instruments.

Loss of heterozygosity at 1p-19q induces a global change in oligodendroglial tumor gene expression.

Oligodendroglial tumors presenting loss of heterozygosity (LOH) at 1p and 19q have been shown to be sensitive to chemotherapy, thus making 1p-19q status testing a key aspect in oligodendroglioma diagnosis and prognosis. Twenty-nine tumor samples (19 oligodendrogliomas, 10 oligoastrocytomas) were analyzed in order to obtain a molecular profile identifying those bearing 1p-19q LOH. Other genomic anomalies usually present in gliomas, such as EGFR amplification, CDKN2A/ARF deletion, 10q LOH and TP53 mutation, were also studied. Tumors with 1p-19q LOH overexpressed genes related to neurogenesis. Genes linked to immune response, proliferation and inflammation were overexpressed in the group with intact 1p-19q; this group could in turn be further divided in two subgroups: one overexpressing genes involved in immune response and inflammation that did not show major genetic aberrations other than the TP53 mutation and EGFR trisomy in a few cases, and another overexpressing genes related to immune response and proliferation that had a predominance of samples carrying several anomalies and presenting worse outcomes. This molecular signature was validated by analyzing a set of ten tumor samples (three oligodendrogliomas, seven oligoastrocytomas); all ten samples were correctly assigned. LOH at 1p-19q results in haploinsufficiency and copy number reduction of several genes, including NOTCH 2; this phenomenon produces a global change in gene expression inducing a pro-neural status that results in restrictions to cell migration and proliferation. Tumors without LOH at 1p-19q exhibit the opposite characteristics, explaining their more aggressive behavior.

Fast awakening from minimally conscious state with apomorphine.

BACKGROUND: Traumatic brain injury (TBI) can induce long-term severe disorders of consciousness. Evidence suggests an underlying dopaminergic deficit. Dopamine agonists may therefore play an important role in recovery of consciousness. OBJECTIVE: To explore the response to continuous subcutaneous administration of apomorphine in a patient who had remained in minimally conscious state for 104 days and to evaluate the anatomical substrate of the effect. DESIGN: A prospective, open-label, daily treatment, dose-escalation single case clinical study, with retrospective diffusion tensor image (DTI) evaluation. RESULTS: On the fist day of treatment, the patient was able to move his limbs on command and answer yes/no questions which had not been the case prior to apomorphine administration. Subsequently there was a full recovery of consciousness and substantial functional recovery that was sustained even after apomorphine discontinuation. At the highest dose, mild dyskinesias were observed. These resolved with a lowering of the dose. DTI demonstrated a decrease of thalamocortical and corticothalamic projections in this MCS patient compared to normal volunteers. CONCLUSION: Although this is an open-label single-patient case report, the data are consistent with the theory that a dopaminergic deficit underlies MCS and that it may be overcome with apomorphine administration.

Accurate 1H tumor spectra quantification from acquisitions without water suppression.

Monovoxel magnetic resonance spectroscopy (MRS) is a technique extensively used for the study of brain tumors in many imaging centers. However, given the fact that monovoxel spectrum quality depends upon voxel size, region of acquisition and the presence of metal and/or blood residue after surgery can make the comparison of MRS brain tumor spectra more difficult than that of other pathologies. This study was conducted in order to evaluate whether it is possible to predict in which cases a tumor spectrum will be quantifiable from acquisitions obtained without water suppression, allowing comparison to other spectra. Three different methods were employed: a qualitative, clinical method and two quantitative ones (Amares and Quest). It was found that by using Quest, it is possible to estimate the number of acquisitions needed to obtain a quantifiable spectrum before its acquisition, something which was not feasible with Amares (given the base used). On examining the spectra as physicians would, it was found that after a certain number of acquisitions, they did not change. The study shows that it is possible to optimize MRS acquisition time in brain tumors and guarantee spectrum quantification for comparison of different MRS studies, obtained both from a single patient or different patients.

Development of a decision support system for diagnosis and grading of brain tumours using in vivo magnetic resonance single voxel spectra.

A computer-based decision support system to assist radiologists in diagnosing and grading brain tumours has been developed by the multi-centre INTERPRET project. Spectra from a database of 1H single-voxel spectra of different types of brain tumours, acquired in vivo from 334 patients at four different centres, are clustered according to their pathology, using automated pattern recognition techniques and the results are presented as a two-dimensional scatterplot using an intuitive graphical user interface (GUI). Formal quality control procedures were performed to standardize the performance of the instruments and check each spectrum, and teams of expert neuroradiologists, neurosurgeons, neurologists and neuropathologists clinically validated each case. The prototype decision support system (DSS) successfully classified 89% of the cases in an independent test set of 91 cases of the most frequent tumour types (meningiomas, low-grade gliomas and high-grade malignant tumours--glioblastomas and metastases). It also helps to resolve diagnostic difficulty in borderline cases. When the prototype was tested by radiologists and other clinicians it was favourably received. Results of the preliminary clinical analysis of the added value of using the DSS for brain tumour diagnosis with MRS showed a small but significant improvement over MRI used alone. In the comparison of individual pathologies, PNETs were significantly better diagnosed with the DSS than with MRI alone.