Automated classification of short echo time in in vivo 1H brain tumor spectra: a multicenter study

Automated pattern recognition techniques are needed to help radiologists categorize MRS data of brain tumors according to histological type and grade. A major question is whether a computer program "trained" on spectra from one hospital will be able to classify those from another, particularly if the acquisition protocol is different. A subset of 144 histopathologically validated brain tumor spectra in the INTERPRET database, obtained from three of the collaborating centers, was grouped into meningiomas, low-grade astrocytomas, and "aggressive tumors" (glioblastomas and metastases). Spectra from two centers formed the training set (94 spectra) while the third acted as the test set (50 spectra). Linear discriminant analysis successfully classified 48/50 in the test set; the remaining two were atypical cases. When the training and test sets were combined, 133 of the 144 spectra were correctly classified using the leave-one-out procedure. These spectra had been obtained using different sequences (STEAM and PRESS), different echo times (20, 30, 31, and 32 ms), different repetition times (1600 and 2000 ms), and different manufacturers' instruments (GE and Philips). Pattern recognition algorithms are less sensitive to acquisition parameters than had been expected.

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.

Proton magnetic resonance spectroscopy ((1)H MRS) of human brain tumours: assessment of differences between tumour types and its applicability in brain tumour categorization

Our objective was to evaluate the usefulness of proton magnetic resonance spectroscopy ((1)H MRS) in categorizing brain tumours. In vivo single-voxel (1)H MRS at an echo time of 136 ms was performed in 108 patients with brain neoplasms that included 29 meningiomas (MEN), 15 low-grade astrocytomas (LGA), 12 anaplastic astrocytomas (AA), 25 glioblastomas (GBM) and 27 metastases (MET). Time-domain fitted areas of nine resonances were evaluated in all spectra. Twenty-five additional tumours were prospectively included as independent test set. Differences in at least two resonances were found in all pairwise comparisons of tumour groups except in GBM vs MET. Large lipid resonance at 1.30 ppm was found to be characteristic of GBM and MET, and alanine was characteristic of MEN. Significant differences were found between LGA and AA in choline-containing compounds and total creatine resonances. When implemented in a stepwise algorithm, these findings correctly classified 84% (21 of 25) tumours in the independent test set. Some additional utility was found in glycine/myo-inositol at 3.55 ppm for bilateral differentiation between GBM and MET (9 of 11, 82% correct classification in the test set). (1)H MRS provides useful information to categorize the most common brain tumours that can be implemented in clinical practice with satisfactory results.

Classification of brain tumours using short echo time 1H MR spectra

The purpose was to objectively compare the application of several techniques and the use of several input features for brain tumour classification using Magnetic Resonance Spectroscopy (MRS). Short echo time 1H MRS signals from patients with glioblastomas (n = 87), meningiomas (n = 57), metastases (n = 39), and astrocytomas grade II (n = 22) were provided by six centres in the European Union funded INTERPRET project. Linear discriminant analysis, least squares support vector machines (LS-SVM) with a linear kernel and LS-SVM with radial basis function kernel were applied and evaluated over 100 stratified random splittings of the dataset into training and test sets. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of binary classifiers, while the percentage of correct classifications was used to evaluate the multiclass classifiers. The influence of several factors on the classification performance has been tested: L2- vs. water normalization, magnitude vs. real spectra and baseline correction. The effect of input feature reduction was also investigated by using only the selected frequency regions containing the most discriminatory information, and peak integrated values. Using L2-normalized complete spectra the automated binary classifiers reached a mean test AUC of more than 0.95, except for glioblastomas vs. metastases. Similar results were obtained for all classification techniques and input features except for water normalized spectra, where classification performance was lower. This indicates that data acquisition and processing can be simplified for classification purposes, excluding the need for separate water signal acquisition, baseline correction or phasing.

Brain tumor classification based on long echo proton MRS signals

There has been a growing research interest in brain tumor classification based on proton magnetic resonance spectroscopy (1H MRS) signals. Four research centers within the EU funded INTERPRET project have acquired a significant number of long echo 1H MRS signals for brain tumor classification. In this paper, we present an objective comparison of several classification techniques applied to the discrimination of four types of brain tumors: meningiomas, glioblastomas, astrocytomas grade II and metastases. Linear and non-linear classifiers are compared: linear discriminant analysis (LDA), support vector machines (SVM) and least squares SVM (LS-SVM) with a linear kernel as linear techniques and LS-SVM with a radial basis function (RBF) kernel as a non-linear technique. Kernel-based methods can perform well in processing high dimensional data. This motivates the inclusion of SVM and LS-SVM in this study. The analysis includes optimal input variable selection, (hyper-) parameter estimation, followed by performance evaluation. The classification performance is evaluated over 200 stratified random samplings of the dataset into training and test sets. Receiver operating characteristic (ROC) curve analysis measures the performance of binary classification, while for multiclass classification, we consider the accuracy as performance measure. Based on the complete magnitude spectra, automated binary classifiers are able to reach an area under the ROC curve (AUC) of more than 0.9 except for the hard case glioblastomas versus metastases. Although, based on the available long echo 1H MRS data, we did not find any statistically significant difference between the performances of LDA and the kernel-based methods, the latter have the strength that no dimensionality reduction is required to obtain such a high performance.

Adult primitive neuroectodermal tumor: proton MR spectroscopic findings with possible application for differential diagnosis

PURPOSE

To assess the utility of proton magnetic resonance (MR) spectroscopy in the clinical categorization of primitive neuroectodermal tumors (PNETs) in adults.

MATERIALS AND METHODS

In vivo proton MR spectroscopy was performed with an echo time of 136 msec in nine adults with PNET, and findings were retrospectively compared with spectroscopic findings of 22 meningiomas, 12 low-grade astrocytomas, eight anaplastic astrocytomas, 23 glioblastomas, and 21 metastases. Nine resonances were semiquantitatively evaluated. Statistical analysis was performed by using Kruskal-Wallis and Mann-Whitney U tests. The Hochberg correction was applied for multiple comparisons. Results were prospectively validated in 24 tumors of the six types included in the study.

RESULTS

The resonances of choice for identifying PNET were alanine (P <.001) and glutamate and glutamine (P =.004), both decreased with respect to meningioma; choline increased with respect to low-grade (P <.001) and anaplastic astrocytoma (P =.055); and lipids at 1.30 ppm decreased and choline and other trimethyl-amine-containing compounds increased with respect to glioblastoma (P <.001 and P =.004, respectively) and metastasis (P <.001 and P =.021, respectively). We developed an algorithm for bilateral differential diagnosis between PNET and other tumor types. The leave-one-out method was used to test the five possible differential situations in the retrospective data set, with the following results: PNET versus meningioma, 31/23/5/3 (number of total/correct/unclassifiable/incorrect procedures); PNET versus low-grade astrocytoma, 21/19/2/0; PNET versus anaplastic astrocytoma, 17/6/9/2; PNET versus glioblastoma, 32/28/2/2; and PNET versus metastasis, 30/27/1/2. In total, 131 consecutive procedures produced 103 (79%) correct classifications and nine (7%) misclassifications. Twenty-five (78%) of 32 possible procedures in the prospective independent test set produced correct classifications and four (13%) produced incorrect classifications.

CONCLUSION

In vivo proton MR spectroscopy provides useful information in clinical differentiation between PNETs and common brain tumors in adults.

Towards a method for automated classification of 1H MRS spectra from brain tumours

Recent studies have shown that MRS can substantially improve the non-invasive categorization of human brain tumours. However, in order for MRS to be used routinely by clinicians, it will be necessary to develop reliable automated classification methods that can be fully validated. This paper is in two parts: the first part reviews the progress that has been made towards this goal, together with the problems that are involved in the design of automated methods to process and classify the spectra. The second part describes the development of a simple prototype system for classifying 1H single voxel spectra, obtained at an echo time (TE) of 135 ms, of the four most common types of brain tumour (meningioma (MM), astrocytic (AST), oligodendroglioma (OD) and metastasis (ME)) and cysts. This system was developed in two stages: firstly, an initial database of spectra was used to develop a prototype classifier, based on a linear discriminant analysis (LDA) of selected data points. Secondly, this classifier was tested on an independent test set of 15 newly acquired spectra, and the system was refined on the basis of these results. The system correctly classified all the non-astrocytic tumours. However, the results for the the astrocytic group were poorer (between 55 and 100%, depending on the binary comparison). Approximately 50% of high grade astrocytoma (glioblastoma) spectra in our data base showed very little lipid signal, which may account for the poorer results for this class. Consequently, for the refined system, the astrocytomas were subdivided into two subgroups for comparison against other tumour classes: those with high lipid content and those without.

In vivo, ex vivo, and in vitro one- and two-dimensional nuclear magnetic resonance spectroscopy of an intracerebral glioma in rat brain: assignment of resonances

An in vivo study of intracerebral rat glioma using proton-localized NMR spectroscopy showed important modifications of the spectra in the tumor as compared with the contralateral brain. To carry out the assignment of the resonances of the glioma spectra, tumoral and normal rat brain tissues were studied in vivo, ex vivo, and in vitro by one-dimensional and two-dimensional proton spectroscopy. N-Acetylaspartate was found at an extremely low level in the glioma. The change of peak ratio total creatine/3.2 ppm peak was found to be due to a simultaneous decrease of the total creatine content and an increase of the 3.2 ppm peak. The 3.2 ppm resonance in the glioma spectra has been shown to originate from choline, phosphocholine, glycerophosphocholine, taurine, inositol, and phosphoethanolamine. The increase of the 3.2 ppm peak in the glioma was found to result from the increase of taurine and phosphoethanolamine contents. The peak in the 1.3 ppm region of the glioma spectra was due to both lactate and mobile fatty acids. Moreover, two-dimensional spectroscopy of excised tissues and extracts showed the presence of hypotaurine only in the tumor.

Magnetic resonance spectroscopy of brain hemangiopericytomas: high myoinositol concentrations and discrimination from meningiomas

OBJECT

Hemangiopericytomas are a rare type of brain tumor that are very similar to meningiomas in appearance and symptoms but require different treatment. It is not normally possible to distinguish between them by using magnetic resonance (MR) imaging and computerized tomography studies. However, discrimination may be possible by using in vivo MR spectroscopy (MRS) because the biochemical composition of these two lesions is different. The goal of this study was to describe the use of MRS in discriminating between these similar tumor types.

METHODS

In vivo MRS spectra were acquired in 27 patients (three with hemangiopericytomas and 24 with meningiomas) by using a single-voxel proton brain examination system at 1.5 teslas with short- (20-msec) and long- (135-msec) echo times. In addition, brain biopsy specimens obtained by open craniotomy were frozen within 5 minutes of resection and stored in liquid nitrogen until they were used. The specimens were powdered, extracted with perchloric acid, redissolved in 2H2O2 and high-resolution in vitro MRS was used at 9.4 teslas to record their spectra.

CONCLUSIONS

In this study the authors show that hemangiopericytomas could be clearly distinguished from meningiomas because they have a larger peak at 3.56 ppm. Measurements of extracts of the tumors and comparison of spectra acquired with MRS at long- (135-msec) and short- (20-msec) echo times established that this was due to the much higher levels of myoinositol in the hemangiopericytomas.

Natural-abundance 13C NMR of brain

In natural-abundance 13C NMR spectrum of excised rat brain 55 resonances were resolved. The chemical shifts of most of the resonances were well correlated with those of pure brain metabolites, determined under identical experimental conditions. These resonances were also found in the cytosol fraction and perchloric acid extract of the brain. Some brain resonances were not observed in the perchloric acid extract but only in the microsomes or cytosol.

Taurine Detection by Proton Magnetic Resonance Spectroscopy in Medulloblastoma: Contribution to Noninvasive Differential Diagnosis with Cerebellar Astrocytoma

OBJECTIVE:

We sought to evaluate whether taurine detection in short-echo (20 ms) proton magnetic resonance spectroscopy contributes to the noninvasive differential diagnosis between medulloblastoma and cerebellar astrocytoma in children and young adults. These two types of tumor have very different prognoses and may be difficult to differentiate by neuroradiological or clinical means.

METHODS:

Single-voxel proton magnetic resonance spectra of tumors were acquired at 1.5 T in 14 patients with biopsy-proven primary cerebellar tumors (six medulloblastomas, seven astrocytomas, and one mixed astroependymoma) using short-echo time (20 ms) and long-echo time (135 ms). For taurine assignment, qualitative analysis was performed on short-echo time spectra and results were compared in vitro with spectra of model solutions. Perchloric acid extracts of postsurgical tumor biopsies were performed in two medulloblastoma cases.

RESULTS:

Taurine detection was demonstrated in all patients with medulloblastoma and in none of those with astrocytoma. We were unable to ascertain any relationship between taurine and metastatic spread within the medulloblastoma group.

CONCLUSION:

Medulloblastomas characteristically seem to show taurine detectable in vivo by short-echo proton magnetic resonance spectroscopy, which may help to discriminate medulloblastoma from cerebellar astrocytoma.

Utility of proton MR spectroscopy in the diagnosis of radiologically atypical intracranial meningiomas

Our aim was to evaluate the usefulness of proton MR spectroscopy ((1)H MRS) in the diagnosis of radiologically atypical brain meningiomas. We studied 37 patients with intracranial meningiomas with MRI and (1)H MRS (TE 136 ms). Their spectra were quantitatively assessed and compared with those of 93 other intracranial brain neoplasms: 15 low-grade and 14 anaplastic astrocytomas, 30 glioblastomas and 34 metastases. The most characteristic features of meningiomas were the presence of alanine, high relative concentrations of choline and glutamine/glutamate and low concentrations of creatine-containing compounds, N-acetyl-containing compounds and lipids. These resonances were assembled in algorithms for two-way differentiation between meningioma and the other tumours. The performance of the algorithms was tested in the 130 patients using the leave-one-out method, with 94% success in differentiating between meningioma and other tumour. Of the 37 meningiomas, five (14%) were thought atypical on MRI, and in only one of these, found to be malignant on histology, was a diagnosis other than meningioma suggested by the algorithm. The other four were correctly classified. We suggest that (1)H MRS provides information on intracranial meningiomas which may be useful in diagnosis of radiologically atypical cases.

Pattern recognition analysis of 1H NMR spectra from perchloric acid extracts of human brain tumor biopsies

Pattern recognition techniques (factor analysis and neural networks) were used to investigate and classify human brain tumors based on the 1H NMR spectra of chemically extracted biopsies (n = 118). After removing information from lactate (because of variable ischemia times), unsupervised learning suggested that the spectra separated naturally into two groups: meningiomas and other tumors. Principal component analysis reduced the dimensionality of the data. A back-propagation neural network using the first 30 principal components gave 85% correct classification of meningiomas and nonmeningiomas. Simplification by vector rotation gave vectors that could be assigned to various metabolites, making it possible to use or to reject their information for neural network classification. Using scores calculated from the four rotated vectors due to creatine and glutamine gave the best classification into meningiomas and nonmeningiomas (89% correct). Classification of gliomas (n = 47) gave 62% correct within one grade. Only inositol showed a significant correlation with glioma grade.

Proton MR spectroscopy improves discrimination between tumor and pseudotumoral lesion in solid brain masses

BACKGROUND AND PURPOSE

Differentiating between tumors and pseudotumoral lesions by conventional MR imaging may be a challenging question. This study aims to evaluate the potential usefulness and the added value that single-voxel proton MR spectroscopy could provide on this discrimination.

MATERIALS AND METHODS

A total of 84 solid brain lesions were retrospectively included in the study (68 glial tumors and 16 pseudotumoral lesions). Single-voxel spectra at TE 30 ms (short TE) and 136 ms (long TE) were available in all cases. Two groups were defined: "training-set" (56 cases) and "test-set" (28 cases). Tumors and pseudotumors were compared in the training-set with the Mann-Whitney U test. Ratios between resonances were defined as classifiers for new cases, and thresholds were selected with receiver operating characteristic (ROC) curves. The added value of spectroscopy was evaluated by 5 neuroradiologists and assessed with the Wilcoxon signed-rank test.

RESULTS

Differences between tumors and pseudotumors were found in myo-inositol (mIns); P < .01) at short TE, and N-acetylaspartate (NAA; P < .001), glutamine (Glx; P < .01), and choline (CHO; P < .05) at long TE. Classifiers suggested tumor when mIns/NAA ratio was more than 0.9 at short TE and also when CHO/NAA ratio was more than 1.9 at long TE. Classifier accuracy was tested in the test-set with the following results: short TE, 82% (23/28); long TE, 79% (22/28). The neuroradiologists' confidence rating of the test-cases on a 5-point scale (0-4) improved between 5% (from 2.86-3) and 27% (from 2.25-2.86) with spectroscopy (mean, 17%; P < .01).

CONCLUSIONS

The proposed ratios of mIns/NAA at short TE and CHO/NAA at long TE provide valuable information to discriminate between brain tumor and pseudotumor by improving neuroradiologists' accuracy and confidence.

1H NMR of intact muscle at 11 T

1H NMR spectra of intact frog, and chicken skeletal muscles, were recorded at 470 MHz with the Plateau and Guéron pulse sequence for the suppression of water [(1982) J. Am. Chem. Soc. 104, 7310]. Only a few transients were required to resolve the resonances from the protons of muscle metabolites. The previously unobserved exchangeable protons of muscles were also recorded and thereby phosphocreatine and creatine could be measured simultaneously. During aging of dissected frog muscle, changes in levels of phosphocreatine, creatine and lactic acid, and the decrease in the intracellular pH were followed by 1H NMR.

1H NMR spectroscopy of colon tumors and normal mucosal biopsies; elevated taurine levels and reduced polyethyleneglycol absorption in tumors may have diagnostic significance

Twenty-three pairs of normal mucosa and colonic adenocarcinoma biopsy specimens have been examined in this pilot study by 1H NMR spectroscopy at 9.4 T to determine whether it was possible to find spectral malignancy markers. The 3.2 ppm (trimethylamine-containing compounds)/0.9 ppm (methyl of fatty acids) resonance intensity ratio in water suppressed spectra, proposed by other authors as a malignancy marker, results in our hands, using resonance areas, in partial overlap between tumor and mucosa values, which reduces its diagnostic value. Furthermore, we have found that submucosa contamination could mask the normal mucosa pattern and artifactually decrease the 3.2/0.9 ppm, ratio value by increasing the 0.9 ppm resonance due to the known triglyceride content of normal submucosa. On the other hand, we have observed in the Hahn spin-echo spectra of intact biopsies resonances arising from taurine and exogenous polyethyleneglycol (PEG). Their assignment and quantification has been carried out in perchloric acid extracts of the tissue biopsies. The taurine (3.4 ppm)/creatine (3.0 ppm) area ratio produced an excellent discrimination between normal mucosa and tumour groups while the PEG (3.7 ppm)/creatine (3.0 ppm) area ratio presented a large overlap, although it was clearly higher in the mucosae than in the tumors for paired samples. These two NMR observable parameters are in our hands highly discriminating and are accordingly proposed as malignancy markers in tissue biopsies although their possible utility for in vivo studies remains to be demonstrated.

Quantitative and qualitative characterization of 1H NMR spectra of colon tumors, normal mucosa and their perchloric acid extracts: decreased levels of myo-inositol in tumours can be detected in intact biopsies

Sixteen colonic tumours and 10 normal mucosa biopsies have been examined by 1H NMR spectroscopy at 9.4 T. A complete characterization and quantification of the aliphatic region of PCA extract spectra and the analysis of the two-dimensional COSY spectra of five pairs of intact biopsies (tumor and control mucosa) has been carried out. The analysis of the PCA extracts demonstrated a significant increase in the concentration of the endogenous compounds: lactate, glutamate, aspartate, taurine, spermine, glutathione and glycerophosphoethanolamine, and a significant decrease of myo- and scyllo-inositol, in tumours with respect to mucosae. Among these metabolites, the high myo-inositol and taurine levels and the reciprocal changes found between them in tumours and mucosae make their resonances interesting as possible malignancy markers if they are detectable in vivo. In contrast to the easy observation of taurine in one-dimensional spectra of intact biopsies, the difficulty of observing myo-inositol prompted us to use two-dimensional COSY spectra for the detection and quantification of both these metabolites. In the two-dimensional spectra, the use of a ratio between the cross-peak volumes of both metabolites permits an excellent differentiation between tumours and normal mucosa and suggests its potential to detect malignant changes in the healthy tissue, provided a two-dimensional approach is used.

Diagnosis of brain abscess by magnetic resonance spectroscopy. Report of two cases

Two cases of brain abscess were diagnosed by combining magnetic resonance spectroscopy (MRS) and magnetic resonance (MR) imaging. The resonances observed in vivo were assigned by means of an in vitro MRS study of the exudates extracted during surgical aspiration of the abscesses. The technique of MRS was demonstrated to be very powerful in the differential diagnosis of brain abscesses from other brain pathologies such as neoplasms. Amino acids, probably originating from extracellular proteolysis, and other compounds, such as acetate, arising from bacterial metabolism, were visible in the MRS spectra of the abscess, whereas they are not present in spectra of neoplasms. In this sense, MRS complemented the information provided by MR imaging to achieve a correct diagnosis of brain abscesses and could be added to routine MR examinations with only a small increase in cost and time.

A possible cellular explanation for the NMR-visible mobile lipid (ML) changes in cultured C6 glioma cells with growth

The NMR-visible mobile lipid (ML) signals of C6 glioma cells have been monitored at 9.4 and 11.7 T (single pulse and 136 ms echo time) from cell pellets by (1)H NMR spectroscopy. A reproducible behavior with growth has been found. ML signals increase from log phase (4 days of culture) to postconfluence (7 days of culture). This ML behavior is paralleled by the percentage of cells containing epifluorescence detectable Nile Red stained cytosolic droplets (range 23%-60% of cells). The number of positive cells increases after seeding (days 0-1), decreases at log phase (days 2-4), increases again at confluence (day 5) and even further at post-confluence (day 7). C6 cells proliferation arrest induced by growth factors deprivation induces an even higher accumulation of cytosolic droplets (up to 100% of cells) and a large ML increase (up to 21-fold with respect to 4-day log phase cells). When neutral lipid content is quantified by thin-layer chromatography (TLC) on total lipid extracts of C6 cells, no statistically significant change can be detected (in microg/10(8) cells) with growth or growth arrest in major neutral lipid containing species (triacylglycerol, TAG, diacylglycerol, DAG, cholesteryl esters, ChoEst) except for DAG, which decreased in post-confluent, 7-day cells. The apparent discrepancy between NMR, optical microscopy and TLC results can be reconciled if possible biophysical changes in the neutral lipid pool with growth are taken into account. A cellular explanation for the observed results is proposed: the TAG-droplet-size-change hypothesis.

Dual T1/ T2 Nanoscale Coordination Polymers as Novel Contrast Agents for MRI: A Preclinical Study for Brain Tumor

In the last years, extensive attention has been paid on designing and developing functional imaging contrast agents for providing accurate noninvasive evaluation of pathology in vivo. However, the issue of false-positives or ambiguous imaging and the lack of a robust strategy for simultaneous dual-mode imaging remain to be fully addressed. One effective strategy for improving it is to rationally design magnetic resonance imaging (MRI) contrast agents (CAs) with intrinsic T₁/ T₂ dual-mode imaging features. In this work, the development and characterization of one-pot synthesized nanostructured coordination polymers (NCPs) which exhibit dual mode T₁/ T₂ MRI contrast behavior is described. The resulting material comprises the combination of different paramagnetic ions (Fe³⁺, Gd³⁺, Mn²⁺) with selected organic ligands able to induce the polymerization process and nanostructure stabilization. Among them, the Fe-based NCPs showed the best features in terms of colloidal stability, low toxicity, and dual T₁/ T₂ MRI contrast performance overcoming the main drawbacks of reported CAs. The dual-mode CA capability was evaluated by different means: in vitro phantoms, ex vivo and in vivo MRI, using a preclinical model of murine glioblastoma. Interestingly, the in vivo MRI of Fe-NCPs show T₁ and T₂ high contrast potential, allowing simultaneous recording of positive and negative contrast images in a very short period of time while being safer for the mouse. Moreover, the biodistribution assays reveals the persistence of the nanoparticles in the tumor and subsequent gradual clearance denoting their biodegradability. After a comparative study with commercial CAs, the results suggest these nanoplatforms as promising candidates for the development of dual-mode MRI CAs with clear advantages.

The reaction of bovine pancreatic ribonuclease A with 6-chloropurineriboside 5'-monophosphate. Evidence on the existence of a phosphate-binding sub-site

The chemical modification of bovine pancreatic ribonuclease A by 6-chloropurine 9-beta-D-ribofuranosyl 5'-monophosphate was studied under several reaction conditions. The reaction, at pH 7.3, 40 degrees C and a nucleotide: enzyme molar ratio of 60, showed a high degree of specificity in comparison to those corresponding to the base or the nucleoside. The main derivative was isolated by means of CM-cellulose chromatography. Subtilisin cleavage of this derivative showed that the substitution had taken place in the S-peptide moiety. Tryptic digestion of the S-peptide indicated that a lysine residue had been modified. Enzymatic and physico-chemical considerations showed that the actual site of reaction was the alpha-amino group of Lys-1. The structural and kinetic properties of the derivative are consistent with the existence of a phosphate-binding sub-site near the N-terminal region of the enzyme.

Comparison between neuroimaging classifications and histopathological diagnoses using an international multicenter brain tumor magnetic resonance imaging database

OBJECT

The aim of this study was to estimate the accuracy of routine magnetic resonance (MR) imaging studies in the classification of brain tumors in terms of both cell type and grade of malignancy.

METHODS

The authors retrospectively assessed the correlation between neuroimaging classifications and histopathological diagnoses by using multicenter database records from 393 patients with brain tumors. An ontology was devised to establish diagnostic agreement. Each tumor category was compared with the corresponding histopathological diagnoses by dichotomization. Sensitivity, specificity, positive and negative predictive values (PPVs and NPVs, respectively), and the Wilson 95% confidence intervals (CI) for each were calculated. In routine reporting of MR imaging examinations, tumor types and grades were classified with a high specificity (85.2-100%); sensitivity varied, depending on the tumor type and grade, alone or in combination. The recognition of broad diagnostic categories (neuroepithelial or meningeal lesions) was highly sensitive, whereas when both detailed type and grade were considered, sensitivity diverged, being highest in low-grade meningioma (sensitivity 100%, 95% CI 96.2-100.0%) and lowest in high-grade meningioma (sensitivity 0.0%, 95% CI 0.0-65.8%) and low-grade oligodendroglioma (sensitivity 15%, 95% CI 5.2-36.0%). In neuroepithelial tumors, sensitivity was inversely related to the precision in reporting of grade and cellular origin; "glioma" was a frequent neuroimaging classification associated with higher sensitivity in the corresponding category. The PPVs varied among categories, in general being greater than their prevalence in this dataset. The NPV was high in all categories (69.8-100%).

CONCLUSIONS

The PPVs and NPVs provided in this study may be used as estimates of posttest probabilities of diagnostic accuracy using MR imaging. This study targets the need for noninvasively increasing sensitivity in categorizing most brain tumor types while retaining high specificity, especially in the differentiation of high- and low-grade glial tumor classes.

Prospective diagnostic performance evaluation of single-voxel 1H MRS for typing and grading of brain tumours

The purpose of this study was to evaluate whether single-voxel (1)H MRS could add useful information to conventional MRI in the preoperative characterisation of the type and grade of brain tumours. MRI and MRS examinations from a prospective cohort of 40 consecutive patients were analysed double blind by radiologists and spectroscopists before the histological diagnosis was known. The spectroscopists had only the MR spectra, whereas the radiologists had both the MR images and basic clinical details (age, sex and presenting symptoms). Then, the radiologists and spectroscopists exchanged their predictions and re-evaluated their initial opinions, taking into account the new evidence. Spectroscopists used four different systems of analysis for (1)H MRS data, and the efficacy of each of these methods was also evaluated. Information extracted from (1)H MRS significantly improved the radiologists' MRI-based characterisation of grade IV tumours (glioblastomas, metastases, medulloblastomas and lymphomas) in the cohort [area under the curve (AUC) in the MRI re-evaluation 0.93 versus AUC in the MRI evaluation 0.85], and also of the less malignant glial tumours (AUC in the MRI re-evaluation 0.93 versus AUC in the MRI evaluation 0.81). One of the MRS analysis systems used, the INTERPRET (International Network for Pattern Recognition of Tumours Using Magnetic Resonance) decision support system, outperformed the others, as well as being better than the MRI evaluation for the characterisation of grade III astrocytomas. Thus, preoperative MRS data improve the radiologists' performance in diagnosing grade IV tumours and, for those of grade II-III, MRS data help them to recognise the glial lineage. Even in cases in which their diagnoses were not improved, the provision of MRS data to the radiologists had no negative influence on their predictions.