Fuzzy Fibers: Uncertainty in dMRI Tractography

Fiber tracking based on diffusion weighted Magnetic Resonance Imaging (dMRI) allows for noninvasive reconstruction of fiber bundles in the human brain. In this chapter, we discuss sources of error and uncertainty in this technique, and review strategies that afford a more reliable interpretation of the results. This includes methods for computing and rendering probabilistic tractograms, which estimate precision in the face of measurement noise and artifacts. However, we also address aspects that have received less attention so far, such as model selection, partial voluming, and the impact of parameters, both in preprocessing and in fiber tracking itself. We conclude by giving impulses for future research

Deterministic diffusion fiber tracking improved by quantitative anisotropy

Diffusion MRI tractography has emerged as a useful and popular tool for mapping connections between brain regions. In this study, we examined the performance of quantitative anisotropy (QA) in facilitating deterministic fiber tracking. Two phantom studies were conducted. The first phantom study examined the susceptibility of fractional anisotropy (FA), generalized factional anisotropy (GFA), and QA to various partial volume effects. The second phantom study examined the spatial resolution of the FA-aided, GFA-aided, and QA-aided tractographies. An in vivo study was conducted to track the arcuate fasciculus, and two neurosurgeons blind to the acquisition and analysis settings were invited to identify false tracks. The performance of QA in assisting fiber tracking was compared with FA, GFA, and anatomical information from T 1-weighted images. Our first phantom study showed that QA is less sensitive to the partial volume effects of crossing fibers and free water, suggesting that it is a robust index. The second phantom study showed that the QA-aided tractography has better resolution than the FA-aided and GFA-aided tractography. Our in vivo study further showed that the QA-aided tractography outperforms the FA-aided, GFA-aided, and anatomy-aided tractographies. In the shell scheme (HARDI), the FA-aided, GFA-aided, and anatomy-aided tractographies have 30.7%, 32.6%, and 24.45% of the false tracks, respectively, while the QA-aided tractography has 16.2%. In the grid scheme (DSI), the FA-aided, GFA-aided, and anatomy-aided tractographies have 12.3%, 9.0%, and 10.93% of the false tracks, respectively, while the QA-aided tractography has 4.43%. The QA-aided deterministic fiber tracking may assist fiber tracking studies and facilitate the advancement of human connectomics. © 2013 Yeh et al

Hemispheric Asymmetry in White Matter Connectivity of the Temporoparietal Junction with the Insula and Prefrontal Cortex

The temporoparietal junction (TPJ) is a key node in the brain's ventral attention network (VAN) that is involved in spatial awareness and detection of salient sensory stimuli, including pain. The anatomical basis of this network's right-lateralized organization is poorly understood. Here we used diffusion-weighted MRI and probabilistic tractography to compare the strength of white matter connections emanating from the right versus left TPJ to target regions in both hemispheres. Symmetry of structural connectivity was evaluated for connections between TPJ and target regions that are key cortical nodes in the right VAN (insula and inferior frontal gyrus) as well as target regions that are involved in salience and/or pain (putamen, cingulate cortex, thalamus). We found a rightward asymmetry in connectivity strength between the TPJ and insula in healthy human subjects who were scanned with two different sets of diffusion-weighted MRI acquisition parameters. This rightward asymmetry in TPJ-insula connectivity was stronger in females than in males. There was also a leftward asymmetry in connectivity strength between the TPJ and inferior frontal gyrus, consistent with previously described lateralization of language pathways. The rightward lateralization of the pathway between the TPJ and insula supports previous findings on the roles of these regions in stimulus-driven attention, sensory awareness, interoception and pain. The findings also have implications for our understanding of acute and chronic pains and stroke-induced spatial hemineglect

Subventricular zones: new key targets for glioblastoma treatment

Abstract Background We aimed to identify subventricular zone (SVZ)-related prognostic factors of survival and patterns of recurrence among patients with glioblastoma. Methods Forty-three patients with primary diagnosed glioblastoma treated in our Cancer Center between 2006 and 2010 were identified. All patients received surgical resection, followed by temozolomide-based chemoradiation. Ipsilateral (iSVZ), contralateral (cSVZ) and bilateral (bSVZ) SVZs were retrospectively segmented and radiation dose-volume histograms were generated. Multivariate analysis using the Cox proportional hazards model was assessed to examine the relationship between prognostic factors and time to progression (TTP) or overall survival (OS). Results Median age was 59 years (range: 25–85). Median follow-up, OS and TTP were 22.7 months (range 7.5–69.7 months), 22.7 months (95% CI 14.5–26.2 months) and 6.4 months (95% CI 4.4–9.3 months), respectively. On univariate analysis, initial contact to SVZ was a poor prognostic factor for OS (18.7 vs 41.7 months, p = 0.014) and TTP (4.6 vs 12.9 months, p = 0.002). Patients whose bSVZ volume receiving at least 20 Gy (V20Gy) was greater than 84% had a significantly improved TTP (17.7 months vs 5.2 months, p = 0.017). This radiation dose coverage was compatible with an hippocampal sparing. On multivariate analysis, initial contact to SVZ and V20 Gy to bSVZ lesser than 84% remained poor prognostic factors for TTP (HR = 3.07, p = 0.012 and HR = 2.67, p = 0.047, respectively). Conclusion Our results suggest that contact to SVZ, as well as insufficient bSVZ radiation dose coverage (V20Gy <84%), might be independent poor prognostic factors for TTP. Therefore, targeting SVZ could be of crucial interest for optimizing glioblastoma treatment

Identification of a candidate biomarker from perfusion MRI to anticipate glioblastoma progression after chemoradiation

International audienceTo identify relevant relative cerebral blood volume biomarkers from T2* dynamic-susceptibility contrast magnetic resonance imaging to anticipate glioblastoma progression after chemoradiation. Twenty-five patients from a prospective study with glioblastoma, primarily treated by chemoradiation, were included. According to the last follow-up MRI confirmed status, patients were divided into: relapse group (n = 13) and control group (n = 12). The time of last MR acquisition was t(end); MR acquisitions performed at t(end-2M), t(end-4M) and t(end-6M) (respectively 2, 4 and 6 months before t(end)) were analyzed to extract relevant variations among eleven perfusion biomarkers (B). These variations were assessed through R(B), as the absolute value of the ratio between a dagger B from t(end-4M) to t(end-2M) and a dagger B from t(end-6M) to t(end-4M). The optimal cut-off for R(B) was determined using receiver-operating-characteristic curve analysis. The fraction of hypoperfused tumor volume (F_hP(g)) was a relevant biomarker. A ratio R(F_hP(g)) aeyenaEuroe0.61 would have been able to anticipate relapse at the next follow-up with a sensitivity/specificity/accuracy of 92.3 %/63.6 %/79.2 %. High R(F_hPg) (aeyen0.61) was associated with more relapse at t(end) compared to low R(F_hPg) (75 % vs 12.5 %, p = 0.008). Iterative analysis of F_hP(g) from consecutive examinations could provide surrogate markers to predict progression at the next follow-up. aEuro cent Related rCBV biomarkers from DSC were assessed to anticipate GBM progression. aEuro cent Biomarkers were assessed through their patterns of variation during the follow-up. aEuro cent The fraction of hypoperfused tumour volume (F_hP (g) ) seemed to be a relevant biomarker. aEuro cent An innovative ratio R(F_hP (g) ) could be an early surrogate marker of relapse. aEuro cent A significant time gain could be achieved in the management of GBM patients