Novel diffusion tractography methodology using Kalman filter prediction to improve preoperative benefit-risk analysis in pediatric epilepsy surgery

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OBJECTIVE

In this study the authors investigated the clinical reliability of diffusion weighted imaging maximum a posteriori probability (DWI-MAP) analysis with Kalman filter prediction in pediatric epilepsy surgery. This approach can yield a suggested resection margin as a dynamic variable based on preoperative DWI-MAP pathways. The authors sought to determine how well the suggested margin would have maximized occurrence of postoperative seizure freedom (benefit) and minimized occurrence of postoperative neurological deficits (risk).

METHODS

The study included 77 pediatric patients with drug-resistant focal epilepsy (age 10.0 ± 4.9 years) who underwent resection of their presumed epileptogenic zone. In preoperative DWI tractography from the resected hemisphere, 9 axonal pathways, Ci=1–9, were identified using DWI-MAP as follows: C1–3 supporting face, hand, and leg motor areas; C4 connecting Broca’s and Wernicke’s areas; C5–8 connecting Broca’s, Wernicke’s, parietal, and premotor areas; and C9 connecting the occipital lobe and lateral geniculate nucleus. For each Ci, the resection margin, di, was measured by the minimal Euclidean distance between the voxels of Ci and the resection boundary determined by spatially coregistered postoperative MRI. If Ci was resected, di was assumed to be negative (calculated as –1 × average Euclidean distance between every voxel inside the resected Ci volume, ri). Kalman filter prediction was then used to estimate an optimal resection margin, d*i, to balance benefit and risk by approximating the relationship between di and ri. Finally, the authors defined the preservation zone of Ci that can balance the probability of benefit and risk by expanding the cortical area of Ci up to d*i on the 3D cortical surface.

RESULTS

In the whole group (n = 77), nonresection of the preoperative preservation zone (i.e., actual resection margin d*i greater than the Kalman filter–defined d*i) accurately predicted the absence of postoperative motor (d*1–3: 0.93 at seizure-free probability of 0.80), language (d*4–8: 0.91 at seizure-free probability of 0.81), and visual deficits (d*9: 0.90 at seizure-free probability of 0.75), suggesting that the preservation of preoperative Ci within d*i supports a balance between postoperative functional deficit and seizure freedom. The subsequent subgroup analyses found that preservation of preoperative Ci =1–4,9 within d*i =1–4,9 may provide accurate deficit predictions independent of age and seizure frequency, suggesting that the DWI-based surgical margin can be effective for surgical planning even in young children and across a range of epilepsy severity.

CONCLUSIONS

Integrating DWI-MAP analysis with Kalman filter prediction may help guide epilepsy surgery by visualizing the margins of the eloquent white matter pathways to be preserved.

ABBREVIATIONS ADFD = average direct-flip distance; DWI = diffusion weighted imaging; DWI-MAP = DWI maximum a posteriori probability; ECoG = electrocorticography; ESM = electrical stimulation mapping; ILAE = International League Against Epilepsy.

Downloadable materials

  • Supplemental Table and Figures (PDF 0.99 MB)

Article Information

Correspondence Jeong-Won Jeong: Translational Imaging Laboratory, Children’s Hospital of Michigan, Wayne State University, Detroit, MI. jjeong@med.wayne.edu.

INCLUDE WHEN CITING Published online July 5, 2019; DOI: 10.3171/2019.4.PEDS1994.

Disclosures The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

© AANS, except where prohibited by US copyright law.

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Figures

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    Calculation of actual resection margin di=2 based on its association with Ci=2. In cases where C2 was preserved, d2 was calculated as the minimal Euclidean distance between the resection boundary and voxels of C2. Upper: Patient 22 in the validation set, who showed no postoperative hand weakness. In cases where C2 was affected by resection, d2 was assumed to be negative and calculated as −1 × average Euclidean distance between every voxel inside the resected C2. Lower: Patient 33 in the validation set, who did show postoperative hand weakness. Figure is available in color online only.

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    2D plots showing the hidden relationship between resection margin, di, and postoperative volume changes of Ci, ri, which were measured in pre- and postoperative DWI data of the modeling dataset (Supplemental Table 1, n = 40). In each plot, red diamonds and blue squares indicate patients with and without postoperative deficit, respectively. Kalman filter prediction using the Rauch-Tung-Striebel algorithm27 was applied to fit di as a function of a dynamic variable ri, resulting in di(ri) (red dotted line). The radius of each colored ellipsis indicates the covariance of the state variable x(ri), approximating the 95% CI of di(ri). Figure is available in color online only.

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    Identification of the proposed margin, d*i=1–9 = −1.9, 2.3, −4.8, 1.4, 1.6, 0.7, −2.8, 0.7, and −4.6 mm, which was optimized to balance P[deficit|di=1–9(r i=1–9)] versus P[seizure freedom|di=1–9(r i=1–9)] at the DWI-MAP–determined Ci=1–9 of the preoperative DWI data in the modeling dataset (Supplemental Table 1, n = 40). Solid red and blue lines indicate the values of the predicted P[deficit|di(ri)] and P[seizure freedom|di(ri)], where the width of the strips indicates ± 1 × covariance of the predicted P[deficit|di(ri)] and P[seizure freedom|di(ri)], estimated from covariance of the state variable x(ri) (Fig. 2). A dotted black line indicates the average value of P[deficit|di(ri)] and P[seizure freedom|di(ri)], balancing both risk and benefit as a function of di(ri). Figure is available in color online only.

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    Representative examples of surgical resections (red area) that preserved the DWI-proposed preservation zone determined by the preoperative DWI-MAP pathway Ci and Kalman filter–defined margin d*i (blue area). Preoperative tract pathways C1 (face sensorimotor), C2 (hand sensorimotor), and C3 (leg sensorimotor) were obtained from patient 23 in the validation set, who had no postoperative face, hand, or leg deficits. Preoperative tract pathways C4 (Broca’s-Wernicke’s areas) and C7 (Wernicke’s-parietal areas) were obtained from patient 7 in the validation set who had no postoperative language deficits. Preoperative tract pathway C9 (occipital lobe and the lateral geniculate nucleus) was obtained from patient 9 in the validation set, who had no postoperative visual field deficits. It is clear that none of the patients whose DWI-proposed preservation zones of preoperative pathways were preserved showed a postoperative deficit related to a given eloquent pathway. Figure is available in color online only. Fig. 4. Representative examples of surgical resections (red area) that preserved the DWI-proposed preservation zone determined by the preoperative DWI-MAP pathway Ci and Kalman filter–defined margin d*i (blue area). Preoperative tract pathways C1 (face sensorimotor), C2 (hand sensorimotor), and C3 (leg sensorimotor) were obtained from patient 23 in the validation set, who had no postoperative face, hand, or leg deficits. Preoperative tract pathways C4 (Broca’s-Wernicke’s areas) and C7 (Wernicke’s-parietal areas) were obtained from patient 7 in the validation set who had no postoperative language deficits. Preoperative tract pathway C9 (occipital lobe and the lateral geniculate nucleus) was obtained from patient 9 in the validation set, who had no postoperative visual field deficits. It is clear that none of the patients whose DWI-proposed preservation zones of preoperative pathways were preserved showed a postoperative deficit related to a given eloquent pathway. Figure is available in color online only.

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    Representative examples of surgical resections (red area) including some portion (magenta area) of the DWI-proposed preservation zone determined by the preoperative DWI-MAP pathway Ci and Kalman filter–defined margin d*i (blue area). Preoperative tract pathways C1 (face sensorimotor), C2 (hand sensorimotor), and C3 (leg sensorimotor) shown for patient 26 in the validation set, who had postoperative face, hand, and leg weakness. Preoperative tract pathways C4 (Broca’s-Wernicke’s areas) and C7 (Wernicke’s-parietal areas) are shown for patient 23 in the validation set, who had a postoperative language deficit, and C9 (occipital lobe–lateral geniculate nucleus) are shown for patient 23 in the validation set, who had postoperative visual field deficits. White arrows highlight where the proposed margin d*i was affected by resective surgery, which may cause postoperative deficit related to a given pathway. Figure is available in color online only.

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