A Longitudinal Multimodal Imaging Study in Patients with Temporo-Insular Diffuse Low-Grade Tumors: How the Inferior Fronto-Occipital Fasciculus Provides Information on Cognitive Outcomes

Abstract

Background: Tractography allows the in vivo study of subcortical white matter, and it is a potential tool for providing predictive indices on post-operative outcomes. We aim at establishing whether there is a relation between cognitive outcome and the status of the inferior fronto-occipital fasciculus's (IFOF's) microstructure.

Methods: The longitudinal neuropsychological data of thirty young (median age: 35 years) patients operated on for DLGG in the left temporo-insular cortex along with pre-surgery tractography data were processed.

Results: A degraded integrity of the left (vs. right) IFOF (lower fractional anisotropy and length, p < 0.001; higher mean and axial diffusivity, p < 0.01) was found, with lower microstructural variables in the infiltration (vs. dislocation) group. Significant decreases immediately post-surgery vs. pre-surgery mainly occurred in lexico-semantics (p < 0.001), with significant improvements at follow-up in all the tests (p < 0.01 to p < 0.001), despite values in the range of 44% to 47.82% of patients with below cut-off scores regarding naming verbs and making visual lexical decisions. The status of left and right IFOFs is predictive of a decrease in immediate post-surgery performance for several tests (p < 0.05); similarly, it is predictive of better recovery in the follow-up performance for naming nouns, naming verbs, making phonological fluency lexical decisions, and the token test (p < -0.05). For the ROC analysis, a significant result was obtained for the verb-naming test, with a cut-off of 79%.

Conclusions: This study supports the role of the predictive value of pre-operative tractography for assessing the immediate post-operative result and at follow-up the risk of developing a cognitive deficit.

Keywords: fiber tracking; inferior fronto-occipital fasciculus; lower-grade gliomas; microstructure analysis; neuropsychology; predictive value.

Figure 1

Left hemisphere temporo-insular low-grade glioma: (A) the qualitative analysis shows left IFOF (in green) downward displacement in axial and sagittal planes in 3D neuroradiological view of the tumor (in yellow). (B) T2-weighted sequences showing axial, coronal, and sagittal view of the tumor (in yellow) and the course of IFOF in the healthy and tumoral hemisphere (in green).

Figure 2

Brain areas that were maximally invaded by the tumor in the whole patient sample. (A) shows the maximum lesion overlay of all the patients’ volumes of interest drawn on their lesion volume. The color bar represents the number of cases, with yellow–orange indicating the maximum overlay. (B) shows the same maximum lesion overlay which is displayed on axial slices of a T1-weighted template, along with the Johns Hopkins University (JHU) Diffusion Tensor Imaging (DTI)-based white matter atlases [27]. The colors represent the different white matter pathways according to the atlas. Data are displayed in neurological conventions.

Figure 3

Patients’ performance before (pre), immediately post-surgery (1 week after, 1 w), and at follow-up (fup) assessment. (a) For executive functions the length of the short-term memory and working memory span is displayed; (b) Oral and limb (ideomotor apraxia), % of correct responses is shown; (c) % of correct responses in tests tapping semantics (N nam = noun naming; v nam = verb naming; P&P = Pyramids and Palm Trees Test; Au lex dec and V lex dec = auditory and visual lexical decisions); (d) for verbal fluency the number of words retrieved is displayed; (e) % of correct responses in tests tapping comprehension (Token = Token test; Au Com N and Au Com V = Auditory comprehension of nouns and verbs; Pho Dis = phonologic discrimination); (f) % of correct responses in tests tapping reading, repetition, and writing (W = words; PW = pseudowords; Read = reading; Rep = repetition; Wri = writing). Asterisks * denote significant changes.

Figure 4

Examples of association between IFOF status and performance at follow-up for naming verbs (A) shows the relation to NS of the LH, (B) shows the relation to AD of the LH, (C) shows the relation to MD of the RH and (D) shows the relation to MD of the RH), Token Test (E) shows the relation to FA of the RH, and Naming nouns (F) shows the relation to MD of the RH.

Figure 5

Receiver operating characteristic (ROC) analysis showed that the area under the curve of the verb naming at the immediate post-surgery evaluation was 0.8750 (CI 95% 0.68326–1). Predictive accuracy was 84% naming immediately post-surgery. (It is represented by the closest point to the top left corner of the graph, indicated by the blue star).