Inter-observer reproducibility of quantitative dynamic susceptibility contrast and diffusion MRI parameters in histogram analysis of gliomas

Background Dynamic-susceptibility contrast and diffusion-weighted imaging are promising techniques in diagnosing glioma grade. Purpose To compare the inter-observer reproducibility of multiple dynamic-susceptibility contrast and diffusion-weighted imaging parameters and to assess their potential in differentiating low- and high-grade gliomas. Material and Methods Thirty patients (16 men; mean age = 40.6 years) with low-grade (n = 13) and high-grade (n = 17) gliomas and known pathology, scanned with dynamic-susceptibility contrast and diffusion-weighted imaging were included retrospectively between March 2006 and March 2014. Three observers used three different methods to define the regions of interest: (i) circles at maximum perfusion and minimum apparent diffusion coefficient; (ii) freeform 2D encompassing the tumor at largest cross-section only; (iii) freeform 3D on all cross-sections. The dynamic-susceptibility contrast curve was analyzed voxelwise: maximum contrast enhancement; time-to-peak; wash-in rate; wash-out rate; and relative cerebral blood volume. The mean was calculated for all regions of interest. For 2D and 3D methods, histogram analysis yielded additional statistics: the minimum and maximum 5% and 10% pixel values of the tumor (min5%, min10%, max5%, max10%). Intraclass correlations coefficients (ICC) were calculated between observers. Low- and high-grade tumors were compared with independent t-tests or Mann-Whitney tests. Results ICCs were highest for 3D freeform (ICC = 0.836-0.986) followed by 2D freeform (ICC = 0.854-0.974) and circular regions of interest (0.141-0.641). High ICC and significant discrimination between low- and high-grade gliomas was found for the following optimized parameters: apparent diffusion coefficient (P <0.001; ICC = 0.641; mean; circle); time-to-peak (P = 0.015; ICC = 0.986; mean; 3D); wash-in rate (P = 0.004; ICC = 0.826; min10%; 3D); wash-out rate (P <0.001; ICC = 0.860; min10%; 2D); and relative cerebral blood volume (

Transcallosal connection patterns of opposite dorsal premotor regions support a lateralized specialization for action and perception

Lateralization of higher brain functions requires that a dominant hemisphere collects relevant information from both sides. The right dorsal premotor cortex (PMd), particularly implicated in visuomotor transformations, was hypothesized to be optimally located to converge visuospatial information from both hemispheres for goal-directed movement. This was assessed by probabilistic tractography and a novel analysis enabling group comparisons of whole-brain connectivity distributions of the left and right PMd in standard space (16 human subjects). The resulting dominance of contralateral PMd connections was characterized by right PMd connections with left visual and parietal areas, indeed supporting a dominant role in visuomotor transformations, while the left PMd showed dominant contralateral connections with the frontal lobe. Ipsilateral right PMd connections were also stronger with posterior parietal regions, relative to the left PMd connections, while ipsilateral connections of the left PMd were stronger with, particularly, the anterior cingulate, the ventral premotor and anterior parietal cortex. The pattern of dominant right PMd connections thus points to a specific role in guiding perceptual information into the motor system, while the left PMd connections are consistent with action dominance based on a lead in motor intention and fine precision skills

Handedness correlates with the dominant parkinson side:A systematic review and meta-analysis

Parkinson's disease (PD) characteristically presents with asymmetrical symptoms, contralateral to the side of the most extensive cerebral affection. This intriguing asymmetry, even included in the definition for diagnosing PD, however, is still part of a mystery. The relation with handedness as a common indicator of cerebral asymmetry might provide a clue in the search for causal factors of asymmetrical symptom onset in PD. This possible relationship, however, is still under debate. The objective of this study was to establish whether a relation between handedness and dominant PD side exists. We searched for cross-sectional or cohort studies that registered handedness and onset side in PD patients in PubMed, EMBASE, and Web of Science from their first record until 14 February 2011. Data about handedness and dominant PD side was extracted. Authors who registered both but not described their relation were contacted for further information. Odds ratios (ORs) were analyzed with a fixed effect Mantel-Haenszel model. Heterogeneity and indications of publication bias were limited. Our electronic search identified 10 studies involving 4405 asymmetric PD patients. Of the right-handed patients, 2413 (59.5%) had right-dominant and 1644 (40.5%) had left-dominant PD symptoms. For the left-handed patients this relation was reversed, with 142 (40.8%) right-dominant and 206 (59.2%) left-dominant PD symptoms. Overall OR was 2.13 (95% confidence interval [CI], 1.712.66). Handedness and symptom dominance in PD are firmly related with each other in such a way that the PD symptoms emerge more often on the dominant hand-side. Possible causal factors are discussed. (C) 2011 Movement Disorder Societ

Susceptibility weighted imaging in intracranial hemorrhage:not all bleeds are black

To correctly recognize intracranial hemorrhage (ICH) and differentiate it from other lesions, knowledge of the imaging characteristics of an ICH on Susceptibility Weighted Imaging (SWI) is essential. It is a common misconception that blood is always black on SWI, and it is important to realize that hemorrhage has a variable appearance in different stages on SWI. Furthermore, the presence of a low signal on SWI does not equal the presence of blood products. In this review the appearance of ICH on SWI during all its stages and common other causes of a low signal on SWI are further discussed and illustrated.</p

Arterial spin labelling MRI for brain tumour surveillance:do we really need cerebral blood flow maps?

Objectives: Arterial spin labelling (ASL) perfusion MRI is one of the available advanced MRI techniques for brain tumour surveillance. The first aim of this study was to investigate the correlation between quantitative cerebral blood flow (CBF) and non-quantitative perfusion weighted imaging (ASL-PWI) measurements. The second aim was to investigate the diagnostic accuracy of ASL-CBF and ASL-PWI measurements as well as visual assessment for identifying tumour progression. Methods: A consecutive cohort of patients who underwent 3-T MRI surveillance containing ASL for treated brain tumours was used. ROIs were drawn in representative parts of tumours in the ASL-CBF maps and copied to the ASL-PWI. ASL-CBF ratios and ASL-PWI ratios of the tumour ROI versus normal appearing white matter (NAWM) were correlated (Pearson correlation) and AUCs were calculated to assess diagnostic accuracy. Additionally, lesions were visually classified as hypointense, isointense, or hyperintense. We calculated accuracy at two thresholds: low threshold (between hypointense-isointense) and high threshold (between isointense-hyperintense). Results: A total of 173 lesions, both enhancing and non-enhancing, measured in 115 patients (93 glioma, 16 metastasis, and 6 lymphoma) showed a very high correlation of 0.96 (95% CI: 0.88–0.99) between ASL-CBF ratios and ASL-PWI ratios. AUC was 0.76 (95%CI: 0.65–0.88) for ASL-CBF ratios and 0.72 (95%CI: 0.58–0.85) for ASL-PWI ratios. Diagnostic accuracy of visual assessment for enhancing lesions was 0.72. Conclusion: ASL-PWI ratios and ASL-CBF ratios showed a high correlation and comparable AUCs; therefore, quantification of ASL-CBF could be omitted in these patients. Visual classification had comparable diagnostic accuracy to the ASL-PWI or ASL-CBF ratios. Clinical relevance statement: This study shows that CBF quantification of ASL perfusion MRI could be omitted for brain tumour surveillance and that visual assessment provides the same diagnostic accuracy. This greatly reduces the complexity of the use of ASL in routine clinical practice. Key Points: • Arterial spin labelling MRI for clinical brain tumour surveillance is undervalued and underinvestigated. • Non-quantitative and quantitative arterial spin labelling assessments show high correlation and comparable diagnostic accuracy. • Quantification of arterial spin labelling MRI could be omitted to improve daily clinical workflow.</p

A Neural Network Approach to Identify the Peritumoral Invasive Areas in Glioblastoma Patients by Using MR Radiomics

The challenge in the treatment of glioblastoma is the failure to identify the cancer invasive area outside the contrast-enhancing tumour which leads to the high local progression rate. Our study aims to identify its progression from the preoperative MR radiomics. 57 newly diagnosed cerebral glioblastoma patients were included. All patients received 5-aminolevulinic acid (5-ALA) fluorescence guidance surgery and postoperative temozolomide concomitant chemoradiotherapy. Preoperative 3 T MRI data including structure MR, perfusion MR, and DTI were obtained. Voxel-based radiomics features extracted from 37 patients were used in the convolutional neural network to train and as internal validation. Another 20 patients of the cohort were tested blindly as external validation. Our results showed that the peritumoural progression areas had higher signal intensity in FLAIR (p = 0.02), rCBV (p = 0.038), and T1C (p = 0.0004), and lower intensity in ADC (p = 0.029) and DTI-p (p = 0.001) compared to non-progression area. The identification of the peritumoural progression area was done by using a supervised convolutional neural network. There was an overall accuracy of 92.6% in the training set and 78.5% in the validation set. Multimodal MR radiomics can demonstrate distinct characteristics in areas of potential progression on preoperative MRI.</p

A Neural Network Approach to Identify the Peritumoral Invasive Areas in Glioblastoma Patients by Using MR Radiomics.

The challenge in the treatment of glioblastoma is the failure to identify the cancer invasive area outside the contrast-enhancing tumour which leads to the high local progression rate. Our study aims to identify its progression from the preoperative MR radiomics. 57 newly diagnosed cerebral glioblastoma patients were included. All patients received 5-aminolevulinic acid (5-ALA) fluorescence guidance surgery and postoperative temozolomide concomitant chemoradiotherapy. Preoperative 3 T MRI data including structure MR, perfusion MR, and DTI were obtained. Voxel-based radiomics features extracted from 37 patients were used in the convolutional neural network to train and as internal validation. Another 20 patients of the cohort were tested blindly as external validation. Our results showed that the peritumoural progression areas had higher signal intensity in FLAIR (p = 0.02), rCBV (p = 0.038), and T1C (p = 0.0004), and lower intensity in ADC (p = 0.029) and DTI-p (p = 0.001) compared to non-progression area. The identification of the peritumoural progression area was done by using a supervised convolutional neural network. There was an overall accuracy of 92.6% in the training set and 78.5% in the validation set. Multimodal MR radiomics can demonstrate distinct characteristics in areas of potential progression on preoperative MRI